id	sid	tid	token	lemma	pos
cana-4845	1	1	communications	communication	NOUN
cana-4845	1	2	on	on	ADP
cana-4845	1	3	applied	apply	VERB
cana-4845	1	4	nonlinear	nonlinear	ADJ
cana-4845	1	5	analysis	analysis	NOUN
cana-4845	1	6	issn	issn	NOUN
cana-4845	1	7	:	:	PUNCT
cana-4845	1	8	1074	1074	NUM
cana-4845	1	9	-	-	PUNCT
cana-4845	1	10	133x	133x	NUM
cana-4845	1	11	vol	vol	VERB
cana-4845	1	12	32	32	NUM
cana-4845	1	13	no	no	NOUN
cana-4845	1	14	.	.	PUNCT
cana-4845	2	1	10s	10	NOUN
cana-4845	2	2	(	(	PUNCT
cana-4845	2	3	2025	2025	NUM
cana-4845	2	4	)	)	PUNCT
cana-4845	2	5	546	546	NUM
cana-4845	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	2	7	depression	depression	NOUN
cana-4845	2	8	analysis	analysis	NOUN
cana-4845	2	9	and	and	CCONJ
cana-4845	2	10	diagnosis	diagnosis	NOUN
cana-4845	2	11	using	use	VERB
cana-4845	2	12	machine	machine	NOUN
cana-4845	2	13	learning	learning	NOUN
cana-4845	2	14	sanchita	sanchita	PROPN
cana-4845	2	15	pange1,3	pange1,3	PROPN
cana-4845	2	16	,	,	PUNCT
cana-4845	2	17	vijaya	vijaya	PROPN
cana-4845	2	18	pawar2	pawar2	PROPN
cana-4845	3	1	1department	1department	NUM
cana-4845	3	2	of	of	ADP
cana-4845	3	3	electronics	electronic	NOUN
cana-4845	3	4	and	and	CCONJ
cana-4845	3	5	telecommunication	telecommunication	NOUN
cana-4845	3	6	engineering	engineering	NOUN
cana-4845	3	7	,	,	PUNCT
cana-4845	3	8	aissm	aissm	PROPN
cana-4845	3	9	’s	’s	PROPN
cana-4845	3	10	institute	institute	PROPN
cana-4845	3	11	of	of	ADP
cana-4845	3	12	information	information	PROPN
cana-4845	3	13	&	&	CCONJ
cana-4845	3	14	technology	technology	PROPN
cana-4845	3	15	,	,	PUNCT
cana-4845	3	16	pune	pune	PROPN
cana-4845	3	17	,	,	PUNCT
cana-4845	3	18	india	india	PROPN
cana-4845	3	19	.	.	PUNCT
cana-4845	4	1	2department	2department	NUM
cana-4845	4	2	of	of	ADP
cana-4845	4	3	electronics	electronic	NOUN
cana-4845	4	4	and	and	CCONJ
cana-4845	4	5	telecommunication	telecommunication	NOUN
cana-4845	4	6	engineering	engineering	NOUN
cana-4845	4	7	,	,	PUNCT
cana-4845	4	8	bharati	bharati	PROPN
cana-4845	4	9	vidyapeeth	vidyapeeth	PROPN
cana-4845	4	10	’s	’s	PART
cana-4845	4	11	college	college	NOUN
cana-4845	4	12	of	of	ADP
cana-4845	4	13	engineering	engineering	NOUN
cana-4845	4	14	for	for	ADP
cana-4845	4	15	women	woman	NOUN
cana-4845	4	16	,	,	PUNCT
cana-4845	4	17	pune	pune	NOUN
cana-4845	4	18	,	,	PUNCT
cana-4845	4	19	india	india	PROPN
cana-4845	4	20	.	.	PUNCT
cana-4845	5	1	3.department	3.department	NUM
cana-4845	5	2	of	of	ADP
cana-4845	5	3	electronics	electronic	NOUN
cana-4845	5	4	and	and	CCONJ
cana-4845	5	5	telecommunication	telecommunication	NOUN
cana-4845	5	6	engineering	engineering	NOUN
cana-4845	5	7	,	,	PUNCT
cana-4845	5	8	jayawantrao	jayawantrao	PROPN
cana-4845	5	9	sawant	sawant	PROPN
cana-4845	5	10	college	college	PROPN
cana-4845	5	11	of	of	ADP
cana-4845	5	12	engineering	engineering	PROPN
cana-4845	5	13	,	,	PUNCT
cana-4845	5	14	pune	pune	PROPN
cana-4845	5	15	,	,	PUNCT
cana-4845	5	16	india	india	PROPN
cana-4845	5	17	.	.	PUNCT
cana-4845	6	1	article	article	PROPN
cana-4845	6	2	history	history	NOUN
cana-4845	6	3	:	:	PUNCT
cana-4845	6	4	received	receive	VERB
cana-4845	6	5	:	:	PUNCT
cana-4845	6	6	12	12	NUM
cana-4845	6	7	-	-	SYM
cana-4845	6	8	01	01	NUM
cana-4845	6	9	-	-	PUNCT
cana-4845	6	10	2025	2025	NUM
cana-4845	6	11	revised	revise	VERB
cana-4845	6	12	:	:	PUNCT
cana-4845	6	13	15	15	NUM
cana-4845	6	14	-	-	NUM
cana-4845	6	15	02	02	NUM
cana-4845	6	16	-	-	PUNCT
cana-4845	6	17	2025	2025	NUM
cana-4845	6	18	accepted	accept	VERB
cana-4845	6	19	:	:	PUNCT
cana-4845	6	20	01	01	NUM
cana-4845	6	21	-	-	SYM
cana-4845	6	22	03	03	NUM
cana-4845	6	23	-	-	PUNCT
cana-4845	6	24	2025	2025	NUM
cana-4845	6	25	abstract	abstract	NOUN
cana-4845	6	26	:	:	PUNCT
cana-4845	6	27	the	the	DET
cana-4845	6	28	century	century	NOUN
cana-4845	6	29	's	's	PART
cana-4845	6	30	most	most	ADV
cana-4845	6	31	famous	famous	ADJ
cana-4845	6	32	event	event	NOUN
cana-4845	6	33	is	be	AUX
cana-4845	6	34	the	the	DET
cana-4845	6	35	covid-19	covid-19	PROPN
cana-4845	6	36	pandemic	pandemic	NOUN
cana-4845	6	37	.	.	PUNCT
cana-4845	7	1	many	many	ADJ
cana-4845	7	2	people	people	NOUN
cana-4845	7	3	experience	experience	VERB
cana-4845	7	4	stress	stress	NOUN
cana-4845	7	5	throughout	throughout	ADP
cana-4845	7	6	the	the	DET
cana-4845	7	7	pandemic	pandemic	NOUN
cana-4845	7	8	.	.	PUNCT
cana-4845	8	1	physical	physical	ADJ
cana-4845	8	2	and	and	CCONJ
cana-4845	8	3	mental	mental	ADJ
cana-4845	8	4	health	health	NOUN
cana-4845	8	5	issues	issue	NOUN
cana-4845	8	6	can	can	AUX
cana-4845	8	7	be	be	AUX
cana-4845	8	8	brought	bring	VERB
cana-4845	8	9	on	on	ADP
cana-4845	8	10	by	by	ADP
cana-4845	8	11	prolonged	prolonged	ADJ
cana-4845	8	12	stress	stress	NOUN
cana-4845	8	13	.	.	PUNCT
cana-4845	9	1	it	it	PRON
cana-4845	9	2	takes	take	VERB
cana-4845	9	3	time	time	NOUN
cana-4845	9	4	,	,	PUNCT
cana-4845	9	5	care	care	NOUN
cana-4845	9	6	,	,	PUNCT
cana-4845	9	7	and	and	CCONJ
cana-4845	9	8	experience	experience	NOUN
cana-4845	9	9	to	to	PART
cana-4845	9	10	manually	manually	ADV
cana-4845	9	11	mark	mark	VERB
cana-4845	9	12	depression	depression	NOUN
cana-4845	9	13	.	.	PUNCT
cana-4845	10	1	the	the	DET
cana-4845	10	2	present	present	ADJ
cana-4845	10	3	method	method	NOUN
cana-4845	10	4	detects	detect	NOUN
cana-4845	10	5	and	and	CCONJ
cana-4845	10	6	diagnoses	diagnose	VERB
cana-4845	10	7	depression	depression	NOUN
cana-4845	10	8	using	use	VERB
cana-4845	10	9	eeg	eeg	PROPN
cana-4845	10	10	and	and	CCONJ
cana-4845	10	11	ecg	ecg	PROPN
cana-4845	10	12	measurements	measurement	NOUN
cana-4845	10	13	.	.	PUNCT
cana-4845	11	1	the	the	DET
cana-4845	11	2	goal	goal	NOUN
cana-4845	11	3	of	of	ADP
cana-4845	11	4	this	this	DET
cana-4845	11	5	work	work	NOUN
cana-4845	11	6	is	be	AUX
cana-4845	11	7	to	to	PART
cana-4845	11	8	create	create	VERB
cana-4845	11	9	a	a	DET
cana-4845	11	10	machine	machine	NOUN
cana-4845	11	11	learning	learning	NOUN
cana-4845	11	12	-	-	PUNCT
cana-4845	11	13	based	base	VERB
cana-4845	11	14	framework	framework	NOUN
cana-4845	11	15	that	that	PRON
cana-4845	11	16	uses	use	VERB
cana-4845	11	17	eeg	eeg	PROPN
cana-4845	11	18	and	and	CCONJ
cana-4845	11	19	ecg	ecg	PROPN
cana-4845	11	20	signals	signal	NOUN
cana-4845	11	21	to	to	PART
cana-4845	11	22	assess	assess	VERB
cana-4845	11	23	and	and	CCONJ
cana-4845	11	24	identify	identify	VERB
cana-4845	11	25	depression	depression	NOUN
cana-4845	11	26	.	.	PUNCT
cana-4845	12	1	system	system	NOUN
cana-4845	12	2	design	design	NOUN
cana-4845	12	3	calculations	calculation	NOUN
cana-4845	12	4	and	and	CCONJ
cana-4845	12	5	tactics	tactic	NOUN
cana-4845	12	6	include	include	VERB
cana-4845	12	7	extraction	extraction	NOUN
cana-4845	12	8	and	and	CCONJ
cana-4845	12	9	selection	selection	NOUN
cana-4845	12	10	methods	method	NOUN
cana-4845	12	11	for	for	ADP
cana-4845	12	12	classification	classification	NOUN
cana-4845	12	13	,	,	PUNCT
cana-4845	12	14	including	include	VERB
cana-4845	12	15	hybrid	hybrid	ADJ
cana-4845	12	16	methods	method	NOUN
cana-4845	12	17	.	.	PUNCT
cana-4845	13	1	the	the	DET
cana-4845	13	2	eeg	eeg	PROPN
cana-4845	13	3	and	and	CCONJ
cana-4845	13	4	ecg	ecg	PROPN
cana-4845	13	5	functions	function	NOUN
cana-4845	13	6	are	be	AUX
cana-4845	13	7	then	then	ADV
cana-4845	13	8	submitted	submit	VERB
cana-4845	13	9	for	for	ADP
cana-4845	13	10	categorization	categorization	NOUN
cana-4845	13	11	following	follow	VERB
cana-4845	13	12	retrieval	retrieval	NOUN
cana-4845	13	13	.	.	PUNCT
cana-4845	14	1	the	the	DET
cana-4845	14	2	st	st	PROPN
cana-4845	14	3	segment	segment	NOUN
cana-4845	14	4	,	,	PUNCT
cana-4845	14	5	p	p	NOUN
cana-4845	14	6	wave	wave	NOUN
cana-4845	14	7	,	,	PUNCT
cana-4845	14	8	qrs	qrs	PROPN
cana-4845	14	9	wave	wave	PROPN
cana-4845	14	10	,	,	PUNCT
cana-4845	14	11	and	and	CCONJ
cana-4845	14	12	ecg	ecg	PROPN
cana-4845	14	13	data	datum	NOUN
cana-4845	14	14	are	be	AUX
cana-4845	14	15	extracted	extract	VERB
cana-4845	14	16	as	as	ADP
cana-4845	14	17	functions	function	NOUN
cana-4845	14	18	.	.	PUNCT
cana-4845	15	1	the	the	DET
cana-4845	15	2	most	most	ADV
cana-4845	15	3	significant	significant	ADJ
cana-4845	15	4	characteristics	characteristic	NOUN
cana-4845	15	5	examined	examine	VERB
cana-4845	15	6	from	from	ADP
cana-4845	15	7	eeg	eeg	NOUN
cana-4845	15	8	signals	signal	NOUN
cana-4845	15	9	were	be	AUX
cana-4845	15	10	alpha	alpha	NOUN
cana-4845	15	11	band	band	NOUN
cana-4845	15	12	power	power	NOUN
cana-4845	15	13	,	,	PUNCT
cana-4845	15	14	entropy	entropy	PROPN
cana-4845	15	15	,	,	PUNCT
cana-4845	15	16	standard	standard	ADJ
cana-4845	15	17	deviation	deviation	NOUN
cana-4845	15	18	,	,	PUNCT
cana-4845	15	19	and	and	CCONJ
cana-4845	15	20	hjorth	hjorth	NOUN
cana-4845	15	21	activity	activity	NOUN
cana-4845	15	22	(	(	PUNCT
cana-4845	15	23	ha	ha	INTJ
cana-4845	15	24	)	)	PUNCT
cana-4845	15	25	.	.	PUNCT
cana-4845	16	1	ecg	ecg	PROPN
cana-4845	16	2	data	datum	NOUN
cana-4845	16	3	were	be	AUX
cana-4845	16	4	analyzed	analyze	VERB
cana-4845	16	5	using	use	VERB
cana-4845	16	6	the	the	DET
cana-4845	16	7	long	long	ADJ
cana-4845	16	8	short	short	ADJ
cana-4845	16	9	-	-	PUNCT
cana-4845	16	10	term	term	NOUN
cana-4845	16	11	memory	memory	NOUN
cana-4845	16	12	(	(	PUNCT
cana-4845	16	13	lstm	lstm	NOUN
cana-4845	16	14	)	)	PUNCT
cana-4845	16	15	autoencoders	autoencoder	NOUN
cana-4845	16	16	and	and	CCONJ
cana-4845	16	17	the	the	DET
cana-4845	16	18	rnn	rnn	PROPN
cana-4845	16	19	deep	deep	ADJ
cana-4845	16	20	learning	learning	NOUN
cana-4845	16	21	model	model	NOUN
cana-4845	16	22	methodology	methodology	NOUN
cana-4845	16	23	,	,	PUNCT
cana-4845	16	24	while	while	SCONJ
cana-4845	16	25	eeg	eeg	NOUN
cana-4845	16	26	signals	signal	NOUN
cana-4845	16	27	were	be	AUX
cana-4845	16	28	classified	classify	VERB
cana-4845	16	29	using	use	VERB
cana-4845	16	30	the	the	DET
cana-4845	16	31	support	support	NOUN
cana-4845	16	32	vector	vector	NOUN
cana-4845	16	33	machine	machine	NOUN
cana-4845	16	34	(	(	PUNCT
cana-4845	16	35	svm	svm	PROPN
cana-4845	16	36	)	)	PUNCT
cana-4845	16	37	and	and	CCONJ
cana-4845	16	38	convolutional	convolutional	ADJ
cana-4845	16	39	neural	neural	ADJ
cana-4845	16	40	network	network	NOUN
cana-4845	16	41	(	(	PUNCT
cana-4845	16	42	cnn	cnn	PROPN
cana-4845	16	43	)	)	PUNCT
cana-4845	16	44	techniques	technique	NOUN
cana-4845	16	45	.	.	PUNCT
cana-4845	17	1	higher	high	ADJ
cana-4845	17	2	accuracy	accuracy	NOUN
cana-4845	17	3	,	,	PUNCT
cana-4845	17	4	sensitivity	sensitivity	NOUN
cana-4845	17	5	,	,	PUNCT
cana-4845	17	6	selectivity	selectivity	NOUN
cana-4845	17	7	,	,	PUNCT
cana-4845	17	8	and	and	CCONJ
cana-4845	17	9	specificity	specificity	NOUN
cana-4845	17	10	are	be	AUX
cana-4845	17	11	achieved	achieve	VERB
cana-4845	17	12	when	when	SCONJ
cana-4845	17	13	using	use	VERB
cana-4845	17	14	an	an	DET
cana-4845	17	15	rnn	rnn	NOUN
cana-4845	17	16	and	and	CCONJ
cana-4845	17	17	an	an	DET
cana-4845	17	18	lstm	lstm	ADJ
cana-4845	17	19	autoencoders	autoencoder	NOUN
cana-4845	17	20	with	with	ADP
cana-4845	17	21	two	two	NUM
cana-4845	17	22	-	-	PUNCT
cana-4845	17	23	dimensional	dimensional	ADJ
cana-4845	17	24	sequence	sequence	NOUN
cana-4845	17	25	input	input	NOUN
cana-4845	17	26	as	as	ADP
cana-4845	17	27	classifiers	classifier	NOUN
cana-4845	17	28	.	.	PUNCT
cana-4845	18	1	for	for	ADP
cana-4845	18	2	ecg	ecg	PROPN
cana-4845	18	3	signals	signal	NOUN
cana-4845	18	4	,	,	PUNCT
cana-4845	18	5	the	the	DET
cana-4845	18	6	current	current	ADJ
cana-4845	18	7	system	system	NOUN
cana-4845	18	8	achieves	achieve	VERB
cana-4845	18	9	93	93	NUM
cana-4845	18	10	%	%	NOUN
cana-4845	18	11	accuracy	accuracy	NOUN
cana-4845	18	12	.	.	PUNCT
cana-4845	19	1	cnn	cnn	PROPN
cana-4845	19	2	outperforms	outperform	VERB
cana-4845	19	3	svm	svm	ADJ
cana-4845	19	4	in	in	ADP
cana-4845	19	5	terms	term	NOUN
cana-4845	19	6	of	of	ADP
cana-4845	19	7	accuracy	accuracy	NOUN
cana-4845	19	8	(	(	PUNCT
cana-4845	19	9	97.69	97.69	NUM
cana-4845	19	10	%	%	NOUN
cana-4845	19	11	)	)	PUNCT
cana-4845	19	12	for	for	ADP
cana-4845	19	13	eeg	eeg	NOUN
cana-4845	19	14	signals	signal	NOUN
cana-4845	19	15	.	.	PUNCT
cana-4845	20	1	keywords	keyword	NOUN
cana-4845	20	2	:	:	PUNCT
cana-4845	20	3	lstm	lstm	ADJ
cana-4845	20	4	autoencoders	autoencoder	NOUN
cana-4845	20	5	,	,	PUNCT
cana-4845	20	6	machine	machine	NOUN
cana-4845	20	7	learning	learning	NOUN
cana-4845	20	8	,	,	PUNCT
cana-4845	20	9	eeg	eeg	PROPN
cana-4845	20	10	and	and	CCONJ
cana-4845	20	11	ecg	ecg	PROPN
cana-4845	20	12	signals	signal	NOUN
cana-4845	20	13	,	,	PUNCT
cana-4845	20	14	feature	feature	NOUN
cana-4845	20	15	extraction	extraction	NOUN
cana-4845	20	16	,	,	PUNCT
cana-4845	20	17	and	and	CCONJ
cana-4845	20	18	depression	depression	NOUN
cana-4845	20	19	diagnosis	diagnosis	NOUN
cana-4845	20	20	.	.	PUNCT
cana-4845	21	1	1	1	X
cana-4845	21	2	.	.	X
cana-4845	21	3	overview	overview	NOUN
cana-4845	21	4	electroencephalography	electroencephalography	NOUN
cana-4845	21	5	(	(	PUNCT
cana-4845	21	6	eeg	eeg	NOUN
cana-4845	21	7	)	)	PUNCT
cana-4845	21	8	is	be	AUX
cana-4845	21	9	the	the	DET
cana-4845	21	10	most	most	ADV
cana-4845	21	11	widely	widely	ADV
cana-4845	21	12	used	use	VERB
cana-4845	21	13	and	and	CCONJ
cana-4845	21	14	effective	effective	ADJ
cana-4845	21	15	method	method	NOUN
cana-4845	21	16	of	of	ADP
cana-4845	21	17	recording	record	VERB
cana-4845	21	18	brain	brain	NOUN
cana-4845	21	19	activity	activity	NOUN
cana-4845	21	20	.	.	PUNCT
cana-4845	22	1	neurological	neurological	ADJ
cana-4845	22	2	conditions	condition	NOUN
cana-4845	22	3	such	such	ADJ
cana-4845	22	4	schizophrenia	schizophrenia	NOUN
cana-4845	22	5	,	,	PUNCT
cana-4845	22	6	parkinson	parkinson	NOUN
cana-4845	22	7	's	's	PART
cana-4845	22	8	disease	disease	NOUN
cana-4845	22	9	,	,	PUNCT
cana-4845	22	10	depression	depression	NOUN
cana-4845	22	11	,	,	PUNCT
cana-4845	22	12	epilepsy	epilepsy	NOUN
cana-4845	22	13	,	,	PUNCT
cana-4845	22	14	ocd	ocd	PROPN
cana-4845	22	15	,	,	PUNCT
cana-4845	22	16	seizure	seizure	NOUN
cana-4845	22	17	prediction	prediction	NOUN
cana-4845	22	18	,	,	PUNCT
cana-4845	22	19	alzheimer	alzheimer	PROPN
cana-4845	22	20	's	's	PART
cana-4845	22	21	disease	disease	NOUN
cana-4845	22	22	,	,	PUNCT
cana-4845	22	23	stroke	stroke	NOUN
cana-4845	22	24	,	,	PUNCT
cana-4845	22	25	creutzfeldt	creutzfeldt	ADJ
cana-4845	22	26	-	-	PUNCT
cana-4845	22	27	jakob	jakob	ADJ
cana-4845	22	28	disease	disease	NOUN
cana-4845	22	29	,	,	PUNCT
cana-4845	22	30	sleep	sleep	VERB
cana-4845	22	31	analysis	analysis	NOUN
cana-4845	22	32	,	,	PUNCT
cana-4845	22	33	and	and	CCONJ
cana-4845	22	34	mood	mood	NOUN
cana-4845	22	35	state	state	NOUN
cana-4845	22	36	analysis	analysis	NOUN
cana-4845	22	37	are	be	AUX
cana-4845	22	38	now	now	ADV
cana-4845	22	39	commonly	commonly	ADV
cana-4845	22	40	diagnosed	diagnose	VERB
cana-4845	22	41	with	with	ADP
cana-4845	22	42	it	it	PRON
cana-4845	22	43	.	.	PUNCT
cana-4845	23	1	depression	depression	NOUN
cana-4845	23	2	is	be	AUX
cana-4845	23	3	predicted	predict	VERB
cana-4845	23	4	to	to	PART
cana-4845	23	5	afflict	afflict	VERB
cana-4845	23	6	3.8	3.8	NUM
cana-4845	23	7	%	%	NOUN
cana-4845	23	8	of	of	ADP
cana-4845	23	9	individuals	individual	NOUN
cana-4845	23	10	globally	globally	ADV
cana-4845	23	11	,	,	PUNCT
cana-4845	23	12	5.7	5.7	NUM
cana-4845	23	13	%	%	NOUN
cana-4845	23	14	of	of	ADP
cana-4845	23	15	people	people	NOUN
cana-4845	23	16	over	over	ADP
cana-4845	23	17	60	60	NUM
cana-4845	23	18	,	,	PUNCT
cana-4845	23	19	and	and	CCONJ
cana-4845	23	20	5	5	NUM
cana-4845	23	21	%	%	NOUN
cana-4845	23	22	of	of	ADP
cana-4845	23	23	all	all	DET
cana-4845	23	24	adults	adult	NOUN
cana-4845	23	25	(	(	PUNCT
cana-4845	23	26	4	4	NUM
cana-4845	23	27	%	%	NOUN
cana-4845	23	28	of	of	ADP
cana-4845	23	29	men	man	NOUN
cana-4845	23	30	and	and	CCONJ
cana-4845	23	31	6	6	NUM
cana-4845	23	32	%	%	NOUN
cana-4845	23	33	of	of	ADP
cana-4845	23	34	women	woman	NOUN
cana-4845	23	35	)	)	PUNCT
cana-4845	23	36	.	.	PUNCT
cana-4845	24	1	depression	depression	NOUN
cana-4845	24	2	is	be	AUX
cana-4845	24	3	a	a	DET
cana-4845	24	4	significant	significant	ADJ
cana-4845	24	5	concern	concern	NOUN
cana-4845	24	6	since	since	SCONJ
cana-4845	24	7	it	it	PRON
cana-4845	24	8	affected	affect	VERB
cana-4845	24	9	280	280	NUM
cana-4845	24	10	million	million	NUM
cana-4845	24	11	people	people	NOUN
cana-4845	24	12	globally	globally	ADV
cana-4845	24	13	.	.	PUNCT
cana-4845	25	1	depression	depression	NOUN
cana-4845	25	2	affects	affect	VERB
cana-4845	25	3	10	10	NUM
cana-4845	25	4	%	%	NOUN
cana-4845	25	5	of	of	ADP
cana-4845	25	6	expectant	expectant	ADJ
cana-4845	25	7	and	and	CCONJ
cana-4845	25	8	future	future	ADJ
cana-4845	25	9	mothers	mother	NOUN
cana-4845	25	10	globally	globally	ADV
cana-4845	25	11	.	.	PUNCT
cana-4845	26	1	nearly	nearly	ADV
cana-4845	26	2	7	7	NUM
cana-4845	26	3	lakh	lakh	NOUN
cana-4845	26	4	people	people	NOUN
cana-4845	26	5	die	die	VERB
cana-4845	26	6	by	by	ADP
cana-4845	26	7	suicide	suicide	NOUN
cana-4845	26	8	each	each	DET
cana-4845	26	9	year	year	NOUN
cana-4845	27	1	[	[	X
cana-4845	27	2	23	23	NUM
cana-4845	27	3	]	]	PUNCT
cana-4845	27	4	.	.	PUNCT
cana-4845	28	1	depression	depression	NOUN
cana-4845	28	2	research	research	NOUN
cana-4845	28	3	and	and	CCONJ
cana-4845	28	4	analysis	analysis	NOUN
cana-4845	28	5	often	often	ADV
cana-4845	28	6	aid	aid	VERB
cana-4845	28	7	physicians	physician	NOUN
cana-4845	28	8	in	in	ADP
cana-4845	28	9	detecting	detect	VERB
cana-4845	28	10	and	and	CCONJ
cana-4845	28	11	treating	treat	VERB
cana-4845	28	12	depression	depression	NOUN
cana-4845	28	13	.	.	PUNCT
cana-4845	29	1	depression	depression	NOUN
cana-4845	29	2	research	research	NOUN
cana-4845	29	3	and	and	CCONJ
cana-4845	29	4	analysis	analysis	NOUN
cana-4845	29	5	often	often	ADV
cana-4845	29	6	aid	aid	VERB
cana-4845	29	7	physicians	physician	NOUN
cana-4845	29	8	in	in	ADP
cana-4845	29	9	detecting	detect	VERB
cana-4845	29	10	and	and	CCONJ
cana-4845	29	11	treating	treat	VERB
cana-4845	29	12	depression	depression	NOUN
cana-4845	29	13	.	.	PUNCT
cana-4845	30	1	the	the	DET
cana-4845	30	2	literature	literature	NOUN
cana-4845	30	3	study	study	NOUN
cana-4845	30	4	indicates	indicate	VERB
cana-4845	30	5	that	that	SCONJ
cana-4845	30	6	eeg	eeg	NOUN
cana-4845	30	7	has	have	VERB
cana-4845	30	8	a	a	DET
cana-4845	30	9	bright	bright	ADJ
cana-4845	30	10	future	future	NOUN
cana-4845	30	11	and	and	CCONJ
cana-4845	30	12	can	can	AUX
cana-4845	30	13	be	be	AUX
cana-4845	30	14	used	use	VERB
cana-4845	30	15	to	to	PART
cana-4845	30	16	track	track	VERB
cana-4845	30	17	and	and	CCONJ
cana-4845	30	18	monitor	monitor	VERB
cana-4845	30	19	people	people	NOUN
cana-4845	30	20	's	's	PART
cana-4845	30	21	communications	communication	NOUN
cana-4845	30	22	on	on	ADP
cana-4845	30	23	applied	apply	VERB
cana-4845	30	24	nonlinear	nonlinear	ADJ
cana-4845	30	25	analysis	analysis	NOUN
cana-4845	30	26	issn	issn	NOUN
cana-4845	30	27	:	:	PUNCT
cana-4845	30	28	1074	1074	NUM
cana-4845	30	29	-	-	PUNCT
cana-4845	30	30	133x	133x	NUM
cana-4845	30	31	vol	vol	VERB
cana-4845	30	32	32	32	NUM
cana-4845	30	33	no	no	NOUN
cana-4845	30	34	.	.	PUNCT
cana-4845	31	1	10s	10	NOUN
cana-4845	31	2	(	(	PUNCT
cana-4845	31	3	2025	2025	NUM
cana-4845	31	4	)	)	PUNCT
cana-4845	31	5	547	547	NUM
cana-4845	31	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	31	7	health	health	NOUN
cana-4845	31	8	.	.	PUNCT
cana-4845	32	1	medical	medical	ADJ
cana-4845	32	2	,	,	PUNCT
cana-4845	32	3	psychological	psychological	ADJ
cana-4845	32	4	,	,	PUNCT
cana-4845	32	5	and	and	CCONJ
cana-4845	32	6	physical	physical	ADJ
cana-4845	32	7	approaches	approach	NOUN
cana-4845	32	8	have	have	AUX
cana-4845	32	9	traditionally	traditionally	ADV
cana-4845	32	10	been	be	AUX
cana-4845	32	11	the	the	DET
cana-4845	32	12	cornerstones	cornerstone	NOUN
cana-4845	32	13	of	of	ADP
cana-4845	32	14	depression	depression	NOUN
cana-4845	32	15	treatment	treatment	NOUN
cana-4845	32	16	.	.	PUNCT
cana-4845	33	1	a	a	DET
cana-4845	33	2	novel	novel	NOUN
cana-4845	33	3	,	,	PUNCT
cana-4845	33	4	inexpensive	inexpensive	ADJ
cana-4845	33	5	,	,	PUNCT
cana-4845	33	6	and	and	CCONJ
cana-4845	33	7	relatively	relatively	ADV
cana-4845	33	8	safe	safe	ADJ
cana-4845	33	9	treatment	treatment	NOUN
cana-4845	33	10	for	for	ADP
cana-4845	33	11	depression	depression	NOUN
cana-4845	33	12	is	be	AUX
cana-4845	33	13	acupuncture	acupuncture	NOUN
cana-4845	33	14	.	.	PUNCT
cana-4845	34	1	electroencephalography	electroencephalography	NOUN
cana-4845	34	2	(	(	PUNCT
cana-4845	34	3	eeg	eeg	NOUN
cana-4845	34	4	)	)	PUNCT
cana-4845	34	5	is	be	AUX
cana-4845	34	6	the	the	DET
cana-4845	34	7	most	most	ADV
cana-4845	34	8	widely	widely	ADV
cana-4845	34	9	used	use	VERB
cana-4845	34	10	and	and	CCONJ
cana-4845	34	11	effective	effective	ADJ
cana-4845	34	12	technique	technique	NOUN
cana-4845	34	13	for	for	ADP
cana-4845	34	14	capturing	capture	VERB
cana-4845	34	15	brain	brain	NOUN
cana-4845	34	16	activity	activity	NOUN
cana-4845	34	17	.	.	PUNCT
cana-4845	35	1	neurological	neurological	ADJ
cana-4845	35	2	conditions	condition	NOUN
cana-4845	35	3	such	such	ADJ
cana-4845	35	4	as	as	ADP
cana-4845	35	5	schizophrenia	schizophrenia	NOUN
cana-4845	35	6	,	,	PUNCT
cana-4845	35	7	parkinson	parkinson	NOUN
cana-4845	35	8	's	's	PART
cana-4845	35	9	disease	disease	NOUN
cana-4845	35	10	,	,	PUNCT
cana-4845	35	11	depression	depression	NOUN
cana-4845	35	12	,	,	PUNCT
cana-4845	35	13	epilepsy	epilepsy	NOUN
cana-4845	35	14	,	,	PUNCT
cana-4845	35	15	ocd	ocd	PROPN
cana-4845	35	16	,	,	PUNCT
cana-4845	35	17	alzheimer	alzheimer	PROPN
cana-4845	35	18	's	's	PART
cana-4845	35	19	disease	disease	NOUN
cana-4845	35	20	,	,	PUNCT
cana-4845	35	21	stroke	stroke	NOUN
cana-4845	35	22	,	,	PUNCT
cana-4845	35	23	creutzfeldt	creutzfeldt	ADJ
cana-4845	35	24	-	-	PUNCT
cana-4845	35	25	jakob	jakob	ADJ
cana-4845	35	26	disease	disease	NOUN
cana-4845	35	27	,	,	PUNCT
cana-4845	35	28	sleep	sleep	NOUN
cana-4845	35	29	evaluation	evaluation	NOUN
cana-4845	35	30	,	,	PUNCT
cana-4845	35	31	and	and	CCONJ
cana-4845	35	32	heart	heart	NOUN
cana-4845	35	33	disease	disease	NOUN
cana-4845	35	34	are	be	AUX
cana-4845	35	35	currently	currently	ADV
cana-4845	35	36	diagnosed	diagnose	VERB
cana-4845	35	37	with	with	ADP
cana-4845	35	38	it	it	PRON
cana-4845	35	39	on	on	ADP
cana-4845	35	40	a	a	DET
cana-4845	35	41	large	large	ADJ
cana-4845	35	42	scale	scale	NOUN
cana-4845	35	43	.	.	PUNCT
cana-4845	36	1	3.8	3.8	NUM
cana-4845	36	2	%	%	NOUN
cana-4845	36	3	of	of	ADP
cana-4845	36	4	people	people	NOUN
cana-4845	36	5	worldwide	worldwide	ADV
cana-4845	36	6	suffer	suffer	VERB
cana-4845	36	7	from	from	ADP
cana-4845	36	8	depression	depression	NOUN
cana-4845	36	9	,	,	PUNCT
cana-4845	36	10	which	which	PRON
cana-4845	36	11	affects	affect	VERB
cana-4845	36	12	5.7	5.7	NUM
cana-4845	36	13	%	%	NOUN
cana-4845	36	14	of	of	ADP
cana-4845	36	15	people	people	NOUN
cana-4845	36	16	over	over	ADP
cana-4845	36	17	60	60	NUM
cana-4845	36	18	and	and	CCONJ
cana-4845	36	19	5	5	NUM
cana-4845	36	20	%	%	NOUN
cana-4845	36	21	of	of	ADP
cana-4845	36	22	all	all	DET
cana-4845	36	23	adults	adult	NOUN
cana-4845	36	24	,	,	PUNCT
cana-4845	36	25	with	with	ADP
cana-4845	36	26	4	4	NUM
cana-4845	36	27	%	%	NOUN
cana-4845	36	28	of	of	ADP
cana-4845	36	29	males	male	NOUN
cana-4845	36	30	and	and	CCONJ
cana-4845	36	31	6	6	NUM
cana-4845	36	32	%	%	NOUN
cana-4845	36	33	of	of	ADP
cana-4845	36	34	women	woman	NOUN
cana-4845	36	35	affected	affect	VERB
cana-4845	36	36	.	.	PUNCT
cana-4845	37	1	depression	depression	NOUN
cana-4845	37	2	affects	affect	VERB
cana-4845	37	3	280	280	NUM
cana-4845	37	4	million	million	NUM
cana-4845	37	5	people	people	NOUN
cana-4845	37	6	globally	globally	ADV
cana-4845	37	7	,	,	PUNCT
cana-4845	37	8	making	make	VERB
cana-4845	37	9	it	it	PRON
cana-4845	37	10	a	a	DET
cana-4845	37	11	serious	serious	ADJ
cana-4845	37	12	problem	problem	NOUN
cana-4845	37	13	.	.	PUNCT
cana-4845	38	1	depression	depression	NOUN
cana-4845	38	2	affects	affect	VERB
cana-4845	38	3	10	10	NUM
cana-4845	38	4	%	%	NOUN
cana-4845	38	5	of	of	ADP
cana-4845	38	6	pregnant	pregnant	ADJ
cana-4845	38	7	and	and	CCONJ
cana-4845	38	8	new	new	ADJ
cana-4845	38	9	moms	mom	NOUN
cana-4845	38	10	worldwide	worldwide	ADV
cana-4845	38	11	.	.	PUNCT
cana-4845	39	1	suicide	suicide	NOUN
cana-4845	39	2	claims	claim	VERB
cana-4845	39	3	the	the	DET
cana-4845	39	4	lives	life	NOUN
cana-4845	39	5	of	of	ADP
cana-4845	39	6	almost	almost	ADV
cana-4845	39	7	7	7	NUM
cana-4845	39	8	million	million	NUM
cana-4845	39	9	people	people	NOUN
cana-4845	39	10	year	year	NOUN
cana-4845	40	1	[	[	X
cana-4845	40	2	23	23	NUM
cana-4845	40	3	]	]	PUNCT
cana-4845	40	4	.	.	PUNCT
cana-4845	41	1	researching	research	VERB
cana-4845	41	2	and	and	CCONJ
cana-4845	41	3	diagnosing	diagnose	VERB
cana-4845	41	4	depression	depression	NOUN
cana-4845	41	5	helps	help	VERB
cana-4845	41	6	the	the	DET
cana-4845	41	7	physician	physician	NOUN
cana-4845	41	8	identify	identify	VERB
cana-4845	41	9	and	and	CCONJ
cana-4845	41	10	treat	treat	VERB
cana-4845	41	11	depression	depression	NOUN
cana-4845	41	12	.	.	PUNCT
cana-4845	42	1	according	accord	VERB
cana-4845	42	2	to	to	ADP
cana-4845	42	3	the	the	DET
cana-4845	42	4	literature	literature	NOUN
cana-4845	42	5	study	study	NOUN
cana-4845	42	6	,	,	PUNCT
cana-4845	42	7	eeg	eeg	PROPN
cana-4845	42	8	is	be	AUX
cana-4845	42	9	a	a	DET
cana-4845	42	10	useful	useful	ADJ
cana-4845	42	11	tool	tool	NOUN
cana-4845	42	12	for	for	ADP
cana-4845	42	13	monitoring	monitoring	NOUN
cana-4845	42	14	and	and	CCONJ
cana-4845	42	15	tracking	track	VERB
cana-4845	42	16	human	human	ADJ
cana-4845	42	17	health	health	NOUN
cana-4845	42	18	,	,	PUNCT
cana-4845	42	19	and	and	CCONJ
cana-4845	42	20	the	the	DET
cana-4845	42	21	future	future	NOUN
cana-4845	42	22	seems	seem	VERB
cana-4845	42	23	bright	bright	ADJ
cana-4845	42	24	.	.	PUNCT
cana-4845	43	1	historically	historically	ADV
cana-4845	43	2	,	,	PUNCT
cana-4845	43	3	medical	medical	ADJ
cana-4845	43	4	,	,	PUNCT
cana-4845	43	5	psychological	psychological	ADJ
cana-4845	43	6	,	,	PUNCT
cana-4845	43	7	and	and	CCONJ
cana-4845	43	8	physical	physical	ADJ
cana-4845	43	9	approaches	approach	NOUN
cana-4845	43	10	have	have	AUX
cana-4845	43	11	been	be	AUX
cana-4845	43	12	the	the	DET
cana-4845	43	13	main	main	ADJ
cana-4845	43	14	focus	focus	NOUN
cana-4845	43	15	of	of	ADP
cana-4845	43	16	depression	depression	NOUN
cana-4845	43	17	treatment	treatment	NOUN
cana-4845	43	18	.	.	PUNCT
cana-4845	44	1	an	an	DET
cana-4845	44	2	innovative	innovative	ADJ
cana-4845	44	3	,	,	PUNCT
cana-4845	44	4	reasonably	reasonably	ADV
cana-4845	44	5	priced	price	VERB
cana-4845	44	6	,	,	PUNCT
cana-4845	44	7	and	and	CCONJ
cana-4845	44	8	low	low	ADJ
cana-4845	44	9	-	-	PUNCT
cana-4845	44	10	risk	risk	NOUN
cana-4845	44	11	treatment	treatment	NOUN
cana-4845	44	12	for	for	ADP
cana-4845	44	13	depression	depression	NOUN
cana-4845	44	14	that	that	PRON
cana-4845	44	15	does	do	AUX
cana-4845	44	16	n't	not	PART
cana-4845	44	17	involve	involve	VERB
cana-4845	44	18	the	the	DET
cana-4845	44	19	possibility	possibility	NOUN
cana-4845	44	20	of	of	ADP
cana-4845	44	21	drug	drug	NOUN
cana-4845	44	22	dependence	dependence	NOUN
cana-4845	44	23	is	be	AUX
cana-4845	44	24	acupuncture	acupuncture	NOUN
cana-4845	44	25	.	.	PUNCT
cana-4845	45	1	currently	currently	ADV
cana-4845	45	2	,	,	PUNCT
cana-4845	45	3	clinical	clinical	ADJ
cana-4845	45	4	practice	practice	NOUN
cana-4845	45	5	uses	use	VERB
cana-4845	45	6	psychological	psychological	ADJ
cana-4845	45	7	measures	measure	NOUN
cana-4845	45	8	,	,	PUNCT
cana-4845	45	9	particularly	particularly	ADV
cana-4845	45	10	qualitative	qualitative	ADJ
cana-4845	45	11	ones	one	NOUN
cana-4845	45	12	,	,	PUNCT
cana-4845	45	13	to	to	PART
cana-4845	45	14	evaluate	evaluate	VERB
cana-4845	45	15	the	the	DET
cana-4845	45	16	treatment	treatment	NOUN
cana-4845	45	17	impact	impact	NOUN
cana-4845	45	18	of	of	ADP
cana-4845	45	19	depression	depression	NOUN
cana-4845	45	20	.	.	PUNCT
cana-4845	46	1	there	there	PRON
cana-4845	46	2	is	be	VERB
cana-4845	46	3	a	a	DET
cana-4845	46	4	strong	strong	ADJ
cana-4845	46	5	association	association	NOUN
cana-4845	46	6	between	between	ADP
cana-4845	46	7	the	the	DET
cana-4845	46	8	patient	patient	NOUN
cana-4845	46	9	's	's	PART
cana-4845	46	10	present	present	ADJ
cana-4845	46	11	mental	mental	ADJ
cana-4845	46	12	state	state	NOUN
cana-4845	46	13	and	and	CCONJ
cana-4845	46	14	the	the	DET
cana-4845	46	15	results	result	NOUN
cana-4845	46	16	of	of	ADP
cana-4845	46	17	the	the	DET
cana-4845	46	18	self	self	NOUN
cana-4845	46	19	-	-	PUNCT
cana-4845	46	20	assessed	assess	VERB
cana-4845	46	21	depression	depression	NOUN
cana-4845	46	22	scale	scale	NOUN
cana-4845	46	23	(	(	PUNCT
cana-4845	46	24	sds	sds	PROPN
cana-4845	46	25	)	)	PUNCT
cana-4845	46	26	,	,	PUNCT
cana-4845	46	27	which	which	PRON
cana-4845	46	28	is	be	AUX
cana-4845	46	29	a	a	DET
cana-4845	46	30	time	time	NOUN
cana-4845	46	31	-	-	PUNCT
cana-4845	46	32	consuming	consume	VERB
cana-4845	46	33	and	and	CCONJ
cana-4845	46	34	intricate	intricate	ADJ
cana-4845	46	35	tool	tool	NOUN
cana-4845	46	36	.	.	PUNCT
cana-4845	47	1	the	the	DET
cana-4845	47	2	current	current	ADJ
cana-4845	47	3	approach	approach	NOUN
cana-4845	47	4	analyzes	analyze	VERB
cana-4845	47	5	depression	depression	NOUN
cana-4845	47	6	by	by	ADP
cana-4845	47	7	taking	take	VERB
cana-4845	47	8	into	into	ADP
cana-4845	47	9	account	account	NOUN
cana-4845	47	10	both	both	PRON
cana-4845	47	11	eeg	eeg	PROPN
cana-4845	47	12	and	and	CCONJ
cana-4845	47	13	ecg	ecg	PROPN
cana-4845	47	14	signals	signal	NOUN
cana-4845	47	15	.	.	PUNCT
cana-4845	48	1	choosing	choose	VERB
cana-4845	48	2	the	the	DET
cana-4845	48	3	best	good	ADJ
cana-4845	48	4	course	course	NOUN
cana-4845	48	5	of	of	ADP
cana-4845	48	6	action	action	NOUN
cana-4845	48	7	depends	depend	VERB
cana-4845	48	8	on	on	ADP
cana-4845	48	9	the	the	DET
cana-4845	48	10	suggested	suggest	VERB
cana-4845	48	11	system	system	NOUN
cana-4845	48	12	's	's	PART
cana-4845	48	13	ability	ability	NOUN
cana-4845	48	14	to	to	PART
cana-4845	48	15	withstand	withstand	VERB
cana-4845	48	16	noise	noise	NOUN
cana-4845	48	17	by	by	ADP
cana-4845	48	18	using	use	VERB
cana-4845	48	19	multi	multi	ADJ
cana-4845	48	20	-	-	ADJ
cana-4845	48	21	scale	scale	ADJ
cana-4845	48	22	principal	principal	ADJ
cana-4845	48	23	component	component	NOUN
cana-4845	48	24	analysis	analysis	NOUN
cana-4845	48	25	(	(	PUNCT
cana-4845	48	26	mspca	mspca	INTJ
cana-4845	48	27	)	)	PUNCT
cana-4845	48	28	to	to	PART
cana-4845	48	29	eliminate	eliminate	VERB
cana-4845	48	30	noise	noise	NOUN
cana-4845	48	31	from	from	ADP
cana-4845	48	32	eeg	eeg	NOUN
cana-4845	48	33	readings	reading	NOUN
cana-4845	48	34	.	.	PUNCT
cana-4845	49	1	instead	instead	ADV
cana-4845	49	2	of	of	ADP
cana-4845	49	3	using	use	VERB
cana-4845	49	4	each	each	DET
cana-4845	49	5	main	main	ADJ
cana-4845	49	6	element	element	NOUN
cana-4845	49	7	separately	separately	ADV
cana-4845	49	8	,	,	PUNCT
cana-4845	49	9	to	to	PART
cana-4845	49	10	achieve	achieve	VERB
cana-4845	49	11	the	the	DET
cana-4845	49	12	maximum	maximum	ADJ
cana-4845	49	13	possible	possible	ADJ
cana-4845	49	14	classification	classification	NOUN
cana-4845	49	15	accuracy	accuracy	NOUN
cana-4845	49	16	,	,	PUNCT
cana-4845	49	17	the	the	DET
cana-4845	49	18	mspca	mspca	NOUN
cana-4845	49	19	picks	pick	VERB
cana-4845	49	20	components	component	NOUN
cana-4845	49	21	based	base	VERB
cana-4845	49	22	on	on	ADP
cana-4845	49	23	the	the	DET
cana-4845	49	24	kaiser	kaiser	PROPN
cana-4845	49	25	rule	rule	PROPN
cana-4845	49	26	and	and	CCONJ
cana-4845	49	27	blends	blend	NOUN
cana-4845	49	28	wavelets	wavelet	NOUN
cana-4845	49	29	with	with	ADP
cana-4845	49	30	pca	pca	PROPN
cana-4845	49	31	.	.	PUNCT
cana-4845	50	1	other	other	ADJ
cana-4845	50	2	techniques	technique	NOUN
cana-4845	50	3	are	be	AUX
cana-4845	50	4	assessed	assess	VERB
cana-4845	50	5	by	by	ADP
cana-4845	50	6	the	the	DET
cana-4845	50	7	preprocessing	preprocessing	NOUN
cana-4845	50	8	module	module	NOUN
cana-4845	50	9	.	.	PUNCT
cana-4845	51	1	in	in	ADP
cana-4845	51	2	the	the	DET
cana-4845	51	3	current	current	ADJ
cana-4845	51	4	study	study	NOUN
cana-4845	51	5	,	,	PUNCT
cana-4845	51	6	mspca	mspca	INTJ
cana-4845	51	7	,	,	PUNCT
cana-4845	51	8	temporal	temporal	ADJ
cana-4845	51	9	filtering	filtering	NOUN
cana-4845	51	10	,	,	PUNCT
cana-4845	51	11	and	and	CCONJ
cana-4845	51	12	spatial	spatial	ADJ
cana-4845	51	13	filtering	filtering	NOUN
cana-4845	51	14	were	be	AUX
cana-4845	51	15	the	the	DET
cana-4845	51	16	most	most	ADV
cana-4845	51	17	effective	effective	ADJ
cana-4845	51	18	methods	method	NOUN
cana-4845	51	19	.	.	PUNCT
cana-4845	52	1	while	while	SCONJ
cana-4845	52	2	spectrum	spectrum	NOUN
cana-4845	52	3	entropy	entropy	NOUN
cana-4845	52	4	and	and	CCONJ
cana-4845	52	5	instantaneous	instantaneous	ADJ
cana-4845	52	6	frequency	frequency	NOUN
cana-4845	52	7	features	feature	NOUN
cana-4845	52	8	are	be	AUX
cana-4845	52	9	retrieved	retrieve	VERB
cana-4845	52	10	from	from	ADP
cana-4845	52	11	ecg	ecg	PROPN
cana-4845	52	12	data	data	PROPN
cana-4845	52	13	,	,	PUNCT
cana-4845	52	14	the	the	DET
cana-4845	52	15	primary	primary	ADJ
cana-4845	52	16	features	feature	NOUN
cana-4845	52	17	extracted	extract	VERB
cana-4845	52	18	from	from	ADP
cana-4845	52	19	eeg	eeg	NOUN
cana-4845	52	20	signals	signal	NOUN
cana-4845	52	21	following	follow	VERB
cana-4845	52	22	the	the	DET
cana-4845	52	23	hjorth	hjorth	NOUN
cana-4845	52	24	activity	activity	NOUN
cana-4845	52	25	(	(	PUNCT
cana-4845	52	26	ha	ha	INTJ
cana-4845	52	27	)	)	PUNCT
cana-4845	52	28	are	be	AUX
cana-4845	52	29	standard	standard	ADJ
cana-4845	52	30	deviation	deviation	NOUN
cana-4845	52	31	,	,	PUNCT
cana-4845	52	32	entropy	entropy	NOUN
cana-4845	52	33	,	,	PUNCT
cana-4845	52	34	and	and	CCONJ
cana-4845	52	35	band	band	NOUN
cana-4845	52	36	power	power	NOUN
cana-4845	52	37	alpha	alpha	NOUN
cana-4845	52	38	.	.	PUNCT
cana-4845	53	1	the	the	DET
cana-4845	53	2	lstm	lstm	PROPN
cana-4845	53	3	auto	auto	NOUN
cana-4845	53	4	encoder	encoder	NOUN
cana-4845	53	5	with	with	ADP
cana-4845	53	6	rnn	rnn	NOUN
cana-4845	53	7	classifier	classifier	NOUN
cana-4845	53	8	also	also	ADV
cana-4845	53	9	processes	process	VERB
cana-4845	53	10	these	these	DET
cana-4845	53	11	features	feature	NOUN
cana-4845	53	12	.	.	PUNCT
cana-4845	54	1	as	as	ADP
cana-4845	54	2	part	part	NOUN
cana-4845	54	3	of	of	ADP
cana-4845	54	4	the	the	DET
cana-4845	54	5	system	system	NOUN
cana-4845	54	6	performance	performance	NOUN
cana-4845	54	7	evaluation	evaluation	NOUN
cana-4845	54	8	,	,	PUNCT
cana-4845	54	9	the	the	DET
cana-4845	54	10	classifiers	classifier	NOUN
cana-4845	54	11	and	and	CCONJ
cana-4845	54	12	accuracy	accuracy	NOUN
cana-4845	54	13	utilized	utilize	VERB
cana-4845	54	14	for	for	ADP
cana-4845	54	15	depression	depression	NOUN
cana-4845	54	16	recognition	recognition	NOUN
cana-4845	54	17	with	with	ADP
cana-4845	54	18	physionet	physionet	NOUN
cana-4845	54	19	datasets	dataset	NOUN
cana-4845	54	20	are	be	AUX
cana-4845	54	21	assessed	assess	VERB
cana-4845	54	22	.	.	PUNCT
cana-4845	55	1	a	a	DET
cana-4845	55	2	review	review	NOUN
cana-4845	55	3	of	of	ADP
cana-4845	55	4	literature	literature	NOUN
cana-4845	55	5	the	the	DET
cana-4845	55	6	experts	expert	NOUN
cana-4845	55	7	provide	provide	VERB
cana-4845	55	8	a	a	DET
cana-4845	55	9	thorough	thorough	ADJ
cana-4845	55	10	analysis	analysis	NOUN
cana-4845	55	11	and	and	CCONJ
cana-4845	55	12	evaluation	evaluation	NOUN
cana-4845	55	13	of	of	ADP
cana-4845	55	14	the	the	DET
cana-4845	55	15	studies	study	NOUN
cana-4845	55	16	conducted	conduct	VERB
cana-4845	55	17	in	in	ADP
cana-4845	55	18	the	the	DET
cana-4845	55	19	field	field	NOUN
cana-4845	55	20	of	of	ADP
cana-4845	55	21	depression	depression	NOUN
cana-4845	55	22	detection	detection	NOUN
cana-4845	55	23	.	.	PUNCT
cana-4845	56	1	papers	paper	NOUN
cana-4845	56	2	from	from	ADP
cana-4845	56	3	the	the	DET
cana-4845	56	4	last	last	ADJ
cana-4845	56	5	nine	nine	NUM
cana-4845	56	6	years	year	NOUN
cana-4845	56	7	are	be	AUX
cana-4845	56	8	examined	examine	VERB
cana-4845	56	9	in	in	ADP
cana-4845	56	10	this	this	DET
cana-4845	56	11	presentation	presentation	NOUN
cana-4845	56	12	to	to	PART
cana-4845	56	13	honor	honor	VERB
cana-4845	56	14	work	work	NOUN
cana-4845	56	15	.	.	PUNCT
cana-4845	57	1	according	accord	VERB
cana-4845	57	2	to	to	ADP
cana-4845	57	3	yibo	yibo	PROPN
cana-4845	57	4	zhu	zhu	PROPN
cana-4845	57	5	et	et	PROPN
cana-4845	57	6	al	al	PROPN
cana-4845	57	7	.	.	PROPN
cana-4845	57	8	,	,	PUNCT
cana-4845	57	9	major	major	ADJ
cana-4845	57	10	depressive	depressive	ADJ
cana-4845	57	11	disorder	disorder	NOUN
cana-4845	57	12	(	(	PUNCT
cana-4845	57	13	mdd	mdd	PROPN
cana-4845	57	14	)	)	PUNCT
cana-4845	57	15	can	can	AUX
cana-4845	57	16	have	have	VERB
cana-4845	57	17	a	a	DET
cana-4845	57	18	detrimental	detrimental	ADJ
cana-4845	57	19	effect	effect	NOUN
cana-4845	57	20	on	on	ADP
cana-4845	57	21	actual	actual	ADJ
cana-4845	57	22	recovery	recovery	NOUN
cana-4845	57	23	in	in	ADP
cana-4845	57	24	a	a	DET
cana-4845	57	25	number	number	NOUN
cana-4845	57	26	of	of	ADP
cana-4845	57	27	clinical	clinical	ADJ
cana-4845	57	28	situations	situation	NOUN
cana-4845	57	29	,	,	PUNCT
cana-4845	57	30	including	include	VERB
cana-4845	57	31	strokes	stroke	NOUN
cana-4845	57	32	and	and	CCONJ
cana-4845	57	33	spinal	spinal	ADJ
cana-4845	57	34	cord	cord	NOUN
cana-4845	57	35	injuries	injury	NOUN
cana-4845	57	36	.	.	PUNCT
cana-4845	58	1	the	the	DET
cana-4845	58	2	review	review	NOUN
cana-4845	58	3	's	's	PART
cana-4845	58	4	suggested	suggest	VERB
cana-4845	58	5	assessment	assessment	NOUN
cana-4845	58	6	method	method	NOUN
cana-4845	58	7	employs	employ	VERB
cana-4845	58	8	useful	useful	ADJ
cana-4845	58	9	fnirs	fnir	NOUN
cana-4845	58	10	technology	technology	NOUN
cana-4845	58	11	and	and	CCONJ
cana-4845	58	12	concentrates	concentrate	VERB
cana-4845	58	13	on	on	ADP
cana-4845	58	14	crisis	crisis	NOUN
cana-4845	58	15	preparedness	preparedness	NOUN
cana-4845	58	16	.	.	PUNCT
cana-4845	59	1	this	this	PRON
cana-4845	59	2	can	can	AUX
cana-4845	59	3	be	be	AUX
cana-4845	59	4	quickly	quickly	ADV
cana-4845	59	5	implemented	implement	VERB
cana-4845	59	6	by	by	ADP
cana-4845	59	7	incorporating	incorporate	VERB
cana-4845	59	8	it	it	PRON
cana-4845	59	9	into	into	ADP
cana-4845	59	10	already	already	ADV
cana-4845	59	11	-	-	PUNCT
cana-4845	59	12	existing	exist	VERB
cana-4845	59	13	recovery	recovery	NOUN
cana-4845	59	14	projects	project	NOUN
cana-4845	59	15	.	.	PUNCT
cana-4845	60	1	the	the	DET
cana-4845	60	2	xg	xg	PROPN
cana-4845	60	3	boost	boost	PROPN
cana-4845	60	4	classifier	classifier	NOUN
cana-4845	60	5	produced	produce	VERB
cana-4845	60	6	92	92	NUM
cana-4845	60	7	%	%	NOUN
cana-4845	60	8	precision	precision	NOUN
cana-4845	60	9	,	,	PUNCT
cana-4845	60	10	85	85	NUM
cana-4845	60	11	%	%	NOUN
cana-4845	60	12	recall	recall	NOUN
cana-4845	60	13	,	,	PUNCT
cana-4845	60	14	and	and	CCONJ
cana-4845	60	15	93	93	NUM
cana-4845	60	16	%	%	NOUN
cana-4845	60	17	accuracy	accuracy	NOUN
cana-4845	60	18	for	for	ADP
cana-4845	60	19	the	the	DET
cana-4845	60	20	top	top	ADJ
cana-4845	60	21	5	5	NUM
cana-4845	60	22	normal	normal	ADJ
cana-4845	60	23	elements	element	NOUN
cana-4845	60	24	.	.	PUNCT
cana-4845	61	1	the	the	DET
cana-4845	61	2	average	average	ADJ
cana-4845	61	3	oxygen	oxygen	NOUN
cana-4845	61	4	-	-	PUNCT
cana-4845	61	5	hemodynamic	hemodynamic	NOUN
cana-4845	61	6	was	be	AUX
cana-4845	61	7	determined	determine	VERB
cana-4845	61	8	by	by	ADP
cana-4845	61	9	this	this	DET
cana-4845	61	10	investigation	investigation	NOUN
cana-4845	61	11	.	.	PUNCT
cana-4845	62	1	communications	communication	NOUN
cana-4845	62	2	on	on	ADP
cana-4845	62	3	applied	apply	VERB
cana-4845	62	4	nonlinear	nonlinear	ADJ
cana-4845	62	5	analysis	analysis	NOUN
cana-4845	62	6	issn	issn	NOUN
cana-4845	62	7	:	:	PUNCT
cana-4845	62	8	1074	1074	NUM
cana-4845	62	9	-	-	PUNCT
cana-4845	62	10	133x	133x	NUM
cana-4845	62	11	vol	vol	VERB
cana-4845	62	12	32	32	NUM
cana-4845	62	13	no	no	NOUN
cana-4845	62	14	.	.	PUNCT
cana-4845	63	1	10s	10	NOUN
cana-4845	63	2	(	(	PUNCT
cana-4845	63	3	2025	2025	NUM
cana-4845	63	4	)	)	PUNCT
cana-4845	63	5	548	548	NUM
cana-4845	63	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	63	7	oleksii	oleksii	NOUN
cana-4845	63	8	komarov	komarov	ADJ
cana-4845	63	9	et	et	PROPN
cana-4845	63	10	al	al	PROPN
cana-4845	63	11	.	.	PUNCT
cana-4845	64	1	[	[	X
cana-4845	64	2	2	2	NUM
cana-4845	64	3	]	]	PUNCT
cana-4845	64	4	developed	develop	VERB
cana-4845	64	5	the	the	DET
cana-4845	64	6	daily	daily	ADJ
cana-4845	64	7	sampling	sample	VERB
cana-4845	64	8	system	system	NOUN
cana-4845	64	9	(	(	PUNCT
cana-4845	64	10	dss	dss	NOUN
cana-4845	64	11	)	)	PUNCT
cana-4845	64	12	,	,	PUNCT
cana-4845	64	13	a	a	DET
cana-4845	64	14	smartphone	smartphone	NOUN
cana-4845	64	15	app	app	NOUN
cana-4845	64	16	that	that	PRON
cana-4845	64	17	uses	use	VERB
cana-4845	64	18	a	a	DET
cana-4845	64	19	comprehensive	comprehensive	ADJ
cana-4845	64	20	academic	academic	ADJ
cana-4845	64	21	questionnaire	questionnaire	NOUN
cana-4845	64	22	to	to	PART
cana-4845	64	23	measure	measure	VERB
cana-4845	64	24	changes	change	NOUN
cana-4845	64	25	in	in	ADP
cana-4845	64	26	excitement	excitement	NOUN
cana-4845	64	27	and	and	CCONJ
cana-4845	64	28	sleep	sleep	VERB
cana-4845	64	29	quality	quality	NOUN
cana-4845	64	30	by	by	ADP
cana-4845	64	31	integrating	integrate	VERB
cana-4845	64	32	several	several	ADJ
cana-4845	64	33	levels	level	NOUN
cana-4845	64	34	of	of	ADP
cana-4845	64	35	self	self	NOUN
cana-4845	64	36	-	-	PUNCT
cana-4845	64	37	assessment	assessment	NOUN
cana-4845	64	38	.	.	PUNCT
cana-4845	65	1	after	after	SCONJ
cana-4845	65	2	the	the	DET
cana-4845	65	3	report	report	NOUN
cana-4845	65	4	is	be	AUX
cana-4845	65	5	finished	finish	VERB
cana-4845	65	6	,	,	PUNCT
cana-4845	65	7	it	it	PRON
cana-4845	65	8	also	also	ADV
cana-4845	65	9	examines	examine	VERB
cana-4845	65	10	the	the	DET
cana-4845	65	11	daily	daily	ADJ
cana-4845	65	12	scores	score	NOUN
cana-4845	65	13	of	of	ADP
cana-4845	65	14	individuals	individual	NOUN
cana-4845	65	15	who	who	PRON
cana-4845	65	16	regularly	regularly	ADV
cana-4845	65	17	input	input	VERB
cana-4845	65	18	their	their	PRON
cana-4845	65	19	depression	depression	NOUN
cana-4845	65	20	data	datum	NOUN
cana-4845	65	21	and	and	CCONJ
cana-4845	65	22	took	take	VERB
cana-4845	65	23	part	part	NOUN
cana-4845	65	24	in	in	ADP
cana-4845	65	25	the	the	DET
cana-4845	65	26	relaxationinduced	relaxationinduce	VERB
cana-4845	65	27	eeg	eeg	PROPN
cana-4845	65	28	data	datum	NOUN
cana-4845	65	29	collection	collection	NOUN
cana-4845	65	30	.	.	PUNCT
cana-4845	66	1	the	the	DET
cana-4845	66	2	study	study	NOUN
cana-4845	66	3	collected	collect	VERB
cana-4845	66	4	1835	1835	NUM
cana-4845	66	5	daily	daily	ADJ
cana-4845	66	6	evaluations	evaluation	NOUN
cana-4845	66	7	,	,	PUNCT
cana-4845	66	8	94	94	NUM
cana-4845	66	9	combined	combine	VERB
cana-4845	66	10	eeg	eeg	NOUN
cana-4845	66	11	records	record	NOUN
cana-4845	66	12	,	,	PUNCT
cana-4845	66	13	and	and	CCONJ
cana-4845	66	14	an	an	DET
cana-4845	66	15	80	80	NUM
cana-4845	66	16	%	%	NOUN
cana-4845	66	17	participation	participation	NOUN
cana-4845	66	18	rate	rate	NOUN
cana-4845	66	19	from	from	ADP
cana-4845	66	20	18	18	NUM
cana-4845	66	21	college	college	NOUN
cana-4845	66	22	students	student	NOUN
cana-4845	66	23	(	(	PUNCT
cana-4845	66	24	ages	age	NOUN
cana-4845	66	25	23–27	23–27	NUM
cana-4845	66	26	)	)	PUNCT
cana-4845	66	27	in	in	ADP
cana-4845	66	28	order	order	NOUN
cana-4845	66	29	to	to	PART
cana-4845	66	30	present	present	VERB
cana-4845	66	31	the	the	DET
cana-4845	66	32	daily	daily	ADJ
cana-4845	66	33	data	datum	NOUN
cana-4845	66	34	over	over	ADP
cana-4845	66	35	the	the	DET
cana-4845	66	36	course	course	NOUN
cana-4845	66	37	of	of	ADP
cana-4845	66	38	a	a	DET
cana-4845	66	39	semester	semester	NOUN
cana-4845	66	40	.	.	PUNCT
cana-4845	67	1	marcel	marcel	PROPN
cana-4845	67	2	trotzek	trotzek	PROPN
cana-4845	67	3	et	et	PROPN
cana-4845	67	4	al	al	PROPN
cana-4845	67	5	.	.	PUNCT
cana-4845	68	1	[	[	X
cana-4845	68	2	3	3	X
cana-4845	68	3	]	]	PUNCT
cana-4845	68	4	showed	show	VERB
cana-4845	68	5	that	that	SCONJ
cana-4845	68	6	they	they	PRON
cana-4845	68	7	could	could	AUX
cana-4845	68	8	identify	identify	VERB
cana-4845	68	9	sorrow	sorrow	NOUN
cana-4845	68	10	in	in	ADP
cana-4845	68	11	social	social	ADJ
cana-4845	68	12	media	medium	NOUN
cana-4845	68	13	messages	message	NOUN
cana-4845	68	14	and	and	CCONJ
cana-4845	68	15	used	use	VERB
cana-4845	68	16	machine	machine	NOUN
cana-4845	68	17	learning	learn	VERB
cana-4845	68	18	algorithms	algorithm	NOUN
cana-4845	68	19	to	to	PART
cana-4845	68	20	identify	identify	VERB
cana-4845	68	21	sadness	sadness	NOUN
cana-4845	68	22	early	early	ADV
cana-4845	68	23	.	.	PUNCT
cana-4845	69	1	semantic	semantic	ADJ
cana-4845	69	2	metadata	metadata	NOUN
cana-4845	69	3	supplied	supply	VERB
cana-4845	69	4	by	by	ADP
cana-4845	69	5	users	user	NOUN
cana-4845	69	6	is	be	AUX
cana-4845	69	7	used	use	VERB
cana-4845	69	8	to	to	PART
cana-4845	69	9	analyze	analyze	VERB
cana-4845	69	10	and	and	CCONJ
cana-4845	69	11	classify	classify	VERB
cana-4845	69	12	an	an	DET
cana-4845	69	13	artificial	artificial	ADJ
cana-4845	69	14	neural	neural	ADJ
cana-4845	69	15	network	network	NOUN
cana-4845	69	16	(	(	PUNCT
cana-4845	69	17	ann	ann	PROPN
cana-4845	69	18	)	)	PUNCT
cana-4845	69	19	.	.	PUNCT
cana-4845	70	1	in	in	ADP
cana-4845	70	2	an	an	DET
cana-4845	70	3	ongoing	ongoing	ADJ
cana-4845	70	4	current	current	ADJ
cana-4845	70	5	location	location	NOUN
cana-4845	70	6	task	task	NOUN
cana-4845	70	7	,	,	PUNCT
cana-4845	70	8	it	it	PRON
cana-4845	70	9	is	be	AUX
cana-4845	70	10	demonstrated	demonstrate	VERB
cana-4845	70	11	that	that	SCONJ
cana-4845	70	12	a	a	DET
cana-4845	70	13	combination	combination	NOUN
cana-4845	70	14	of	of	ADP
cana-4845	70	15	both	both	DET
cana-4845	70	16	approaches	approach	NOUN
cana-4845	70	17	yields	yield	VERB
cana-4845	70	18	excellent	excellent	ADJ
cana-4845	70	19	results	result	NOUN
cana-4845	70	20	.	.	PUNCT
cana-4845	71	1	furthermore	furthermore	ADV
cana-4845	71	2	,	,	PUNCT
cana-4845	71	3	a	a	DET
cana-4845	71	4	thorough	thorough	ADJ
cana-4845	71	5	analysis	analysis	NOUN
cana-4845	71	6	of	of	ADP
cana-4845	71	7	the	the	DET
cana-4845	71	8	well	well	ADV
cana-4845	71	9	-	-	PUNCT
cana-4845	71	10	known	know	VERB
cana-4845	71	11	early	early	ADJ
cana-4845	71	12	risk	risk	NOUN
cana-4845	71	13	detection	detection	NOUN
cana-4845	71	14	error	error	NOUN
cana-4845	71	15	(	(	PUNCT
cana-4845	71	16	erde	erde	PROPN
cana-4845	71	17	)	)	PUNCT
cana-4845	71	18	score	score	NOUN
cana-4845	71	19	as	as	ADP
cana-4845	71	20	a	a	DET
cana-4845	71	21	metric	metric	NOUN
cana-4845	71	22	for	for	ADP
cana-4845	71	23	early	early	ADJ
cana-4845	71	24	detection	detection	NOUN
cana-4845	71	25	systems	system	NOUN
cana-4845	71	26	is	be	AUX
cana-4845	71	27	currently	currently	ADV
cana-4845	71	28	in	in	ADP
cana-4845	71	29	progress	progress	NOUN
cana-4845	71	30	.	.	PUNCT
cana-4845	72	1	to	to	PART
cana-4845	72	2	find	find	VERB
cana-4845	72	3	a	a	DET
cana-4845	72	4	more	more	ADV
cana-4845	72	5	effective	effective	ADJ
cana-4845	72	6	method	method	NOUN
cana-4845	72	7	of	of	ADP
cana-4845	72	8	coordinating	coordinate	VERB
cana-4845	72	9	the	the	DET
cana-4845	72	10	metadata	metadata	NOUN
cana-4845	72	11	,	,	PUNCT
cana-4845	72	12	more	more	ADJ
cana-4845	72	13	experiments	experiment	NOUN
cana-4845	72	14	are	be	AUX
cana-4845	72	15	required	require	VERB
cana-4845	72	16	.	.	PUNCT
cana-4845	73	1	the	the	DET
cana-4845	73	2	rm-6280c	rm-6280c	PROPN
cana-4845	73	3	multifunctional	multifunctional	PROPN
cana-4845	73	4	physiology	physiology	NOUN
cana-4845	73	5	experiment	experiment	NOUN
cana-4845	73	6	device	device	NOUN
cana-4845	73	7	from	from	ADP
cana-4845	73	8	chengdu	chengdu	PROPN
cana-4845	73	9	instrument	instrument	PROPN
cana-4845	73	10	factory	factory	NOUN
cana-4845	73	11	in	in	ADP
cana-4845	73	12	sichuan	sichuan	PROPN
cana-4845	73	13	,	,	PUNCT
cana-4845	73	14	china	china	PROPN
cana-4845	73	15	,	,	PUNCT
cana-4845	73	16	was	be	AUX
cana-4845	73	17	used	use	VERB
cana-4845	73	18	by	by	ADP
cana-4845	73	19	zang	zang	PROPN
cana-4845	73	20	xiaohan	xiaohan	PROPN
cana-4845	73	21	and	and	CCONJ
cana-4845	73	22	associates	associate	NOUN
cana-4845	74	1	[	[	X
cana-4845	74	2	4	4	X
cana-4845	74	3	]	]	PUNCT
cana-4845	74	4	to	to	PART
cana-4845	74	5	collect	collect	VERB
cana-4845	74	6	the	the	DET
cana-4845	74	7	participants	participant	NOUN
cana-4845	74	8	'	'	PART
cana-4845	74	9	ecg	ecg	PROPN
cana-4845	74	10	data	datum	NOUN
cana-4845	74	11	at	at	ADP
cana-4845	74	12	a	a	DET
cana-4845	74	13	sample	sample	NOUN
cana-4845	74	14	rate	rate	NOUN
cana-4845	74	15	of	of	ADP
cana-4845	74	16	1	1	NUM
cana-4845	74	17	khz	khz	NOUN
cana-4845	74	18	.	.	PUNCT
cana-4845	75	1	throughout	throughout	ADP
cana-4845	75	2	the	the	DET
cana-4845	75	3	experiment	experiment	NOUN
cana-4845	75	4	,	,	PUNCT
cana-4845	75	5	baseline	baseline	ADJ
cana-4845	75	6	drift	drift	NOUN
cana-4845	75	7	was	be	AUX
cana-4845	75	8	eliminated	eliminate	VERB
cana-4845	75	9	using	use	VERB
cana-4845	75	10	a	a	DET
cana-4845	75	11	median	median	ADJ
cana-4845	75	12	filter	filter	NOUN
cana-4845	75	13	,	,	PUNCT
cana-4845	75	14	power	power	NOUN
cana-4845	75	15	frequency	frequency	NOUN
cana-4845	75	16	interference	interference	NOUN
cana-4845	75	17	was	be	AUX
cana-4845	75	18	eliminated	eliminate	VERB
cana-4845	75	19	using	use	VERB
cana-4845	75	20	a	a	DET
cana-4845	75	21	notch	notch	ADJ
cana-4845	75	22	filter	filter	NOUN
cana-4845	75	23	,	,	PUNCT
cana-4845	75	24	and	and	CCONJ
cana-4845	75	25	emg	emg	NOUN
cana-4845	75	26	interference	interference	NOUN
cana-4845	75	27	was	be	AUX
cana-4845	75	28	eliminated	eliminate	VERB
cana-4845	75	29	using	use	VERB
cana-4845	75	30	a	a	DET
cana-4845	75	31	low	low	ADJ
cana-4845	75	32	-	-	PUNCT
cana-4845	75	33	pass	pass	NOUN
cana-4845	75	34	filter	filter	NOUN
cana-4845	75	35	.	.	PUNCT
cana-4845	76	1	the	the	DET
cana-4845	76	2	5.5	5.5	NUM
cana-4845	76	3	-	-	PUNCT
cana-4845	76	4	minute	minute	NOUN
cana-4845	76	5	dataset	dataset	NOUN
cana-4845	76	6	used	use	VERB
cana-4845	76	7	in	in	ADP
cana-4845	76	8	the	the	DET
cana-4845	76	9	study	study	NOUN
cana-4845	76	10	was	be	AUX
cana-4845	76	11	split	split	VERB
cana-4845	76	12	up	up	ADP
cana-4845	76	13	into	into	ADP
cana-4845	76	14	5	5	NUM
cana-4845	76	15	second	second	ADJ
cana-4845	76	16	(	(	PUNCT
cana-4845	76	17	or	or	CCONJ
cana-4845	76	18	varying	vary	VERB
cana-4845	76	19	duration	duration	NOUN
cana-4845	76	20	)	)	PUNCT
cana-4845	76	21	segments	segment	NOUN
cana-4845	76	22	,	,	PUNCT
cana-4845	76	23	and	and	CCONJ
cana-4845	76	24	each	each	DET
cana-4845	76	25	segment	segment	NOUN
cana-4845	76	26	was	be	AUX
cana-4845	76	27	given	give	VERB
cana-4845	76	28	a	a	DET
cana-4845	76	29	category	category	NOUN
cana-4845	76	30	.	.	PUNCT
cana-4845	77	1	a	a	DET
cana-4845	77	2	one	one	NUM
cana-4845	77	3	-	-	PUNCT
cana-4845	77	4	dimensional	dimensional	ADJ
cana-4845	77	5	cnn	cnn	NOUN
cana-4845	77	6	was	be	AUX
cana-4845	77	7	utilized	utilize	VERB
cana-4845	77	8	to	to	PART
cana-4845	77	9	identify	identify	VERB
cana-4845	77	10	and	and	CCONJ
cana-4845	77	11	extract	extract	VERB
cana-4845	77	12	features	feature	NOUN
cana-4845	77	13	from	from	ADP
cana-4845	77	14	ecg	ecg	PROPN
cana-4845	77	15	segments	segment	NOUN
cana-4845	77	16	.	.	PUNCT
cana-4845	78	1	bueno	bueno	PROPN
cana-4845	78	2	-	-	PUNCT
cana-4845	78	3	notivol	notivol	PROPN
cana-4845	78	4	juan	juan	PROPN
cana-4845	78	5	et	et	PROPN
cana-4845	78	6	al	al	PROPN
cana-4845	78	7	.	.	PROPN
cana-4845	78	8	's	's	PART
cana-4845	78	9	study	study	NOUN
cana-4845	78	10	[	[	X
cana-4845	78	11	5	5	NUM
cana-4845	78	12	]	]	PUNCT
cana-4845	78	13	was	be	AUX
cana-4845	78	14	deemed	deem	VERB
cana-4845	78	15	protected	protect	VERB
cana-4845	78	16	if	if	SCONJ
cana-4845	78	17	it	it	PRON
cana-4845	78	18	provided	provide	VERB
cana-4845	78	19	unambiguous	unambiguous	ADJ
cana-4845	78	20	crosssectional	crosssectional	ADJ
cana-4845	78	21	data	datum	NOUN
cana-4845	78	22	on	on	ADP
cana-4845	78	23	the	the	DET
cana-4845	78	24	prevalence	prevalence	NOUN
cana-4845	78	25	of	of	ADP
cana-4845	78	26	depression	depression	NOUN
cana-4845	78	27	during	during	ADP
cana-4845	78	28	the	the	DET
cana-4845	78	29	covid-19	covid-19	PROPN
cana-4845	78	30	pandemic	pandemic	NOUN
cana-4845	78	31	,	,	PUNCT
cana-4845	78	32	highlighted	highlight	VERB
cana-4845	78	33	societal	societal	ADJ
cana-4845	78	34	factors	factor	NOUN
cana-4845	78	35	with	with	ADP
cana-4845	78	36	extensive	extensive	ADJ
cana-4845	78	37	samples	sample	NOUN
cana-4845	78	38	,	,	PUNCT
cana-4845	78	39	described	describe	VERB
cana-4845	78	40	a	a	DET
cana-4845	78	41	method	method	NOUN
cana-4845	78	42	for	for	ADP
cana-4845	78	43	diagnosing	diagnose	VERB
cana-4845	78	44	or	or	CCONJ
cana-4845	78	45	evaluating	evaluate	VERB
cana-4845	78	46	depression	depression	NOUN
cana-4845	78	47	,	,	PUNCT
cana-4845	78	48	and	and	CCONJ
cana-4845	78	49	made	make	VERB
cana-4845	78	50	sure	sure	ADJ
cana-4845	78	51	the	the	DET
cana-4845	78	52	full	full	ADJ
cana-4845	78	53	text	text	NOUN
cana-4845	78	54	was	be	AUX
cana-4845	78	55	accessible	accessible	ADJ
cana-4845	78	56	.	.	PUNCT
cana-4845	79	1	according	accord	VERB
cana-4845	79	2	to	to	ADP
cana-4845	79	3	the	the	DET
cana-4845	79	4	most	most	ADV
cana-4845	79	5	recent	recent	ADJ
cana-4845	79	6	meta	meta	ADJ
cana-4845	79	7	-	-	PUNCT
cana-4845	79	8	analysis	analysis	NOUN
cana-4845	79	9	,	,	PUNCT
cana-4845	79	10	which	which	PRON
cana-4845	79	11	included	include	VERB
cana-4845	79	12	12	12	NUM
cana-4845	79	13	more	more	ADJ
cana-4845	79	14	studies	study	NOUN
cana-4845	79	15	,	,	PUNCT
cana-4845	79	16	comorbid	comorbid	NOUN
cana-4845	79	17	depression	depression	NOUN
cana-4845	79	18	was	be	AUX
cana-4845	79	19	present	present	ADJ
cana-4845	79	20	in	in	ADP
cana-4845	79	21	25	25	NUM
cana-4845	79	22	%	%	NOUN
cana-4845	79	23	of	of	ADP
cana-4845	79	24	covid-19	covid-19	PROPN
cana-4845	79	25	patients	patient	NOUN
cana-4845	79	26	in	in	ADP
cana-4845	79	27	poor	poor	ADJ
cana-4845	79	28	nations	nation	NOUN
cana-4845	79	29	.	.	PUNCT
cana-4845	80	1	the	the	DET
cana-4845	80	2	different	different	ADJ
cana-4845	80	3	measures	measure	NOUN
cana-4845	80	4	employed	employ	VERB
cana-4845	80	5	in	in	ADP
cana-4845	80	6	the	the	DET
cana-4845	80	7	research	research	NOUN
cana-4845	80	8	that	that	PRON
cana-4845	80	9	made	make	VERB
cana-4845	80	10	up	up	ADP
cana-4845	80	11	this	this	DET
cana-4845	80	12	meta	meta	ADJ
cana-4845	80	13	-	-	PUNCT
cana-4845	80	14	analysis	analysis	NOUN
cana-4845	80	15	are	be	AUX
cana-4845	80	16	the	the	DET
cana-4845	80	17	reason	reason	NOUN
cana-4845	80	18	for	for	ADP
cana-4845	80	19	the	the	DET
cana-4845	80	20	disparity	disparity	NOUN
cana-4845	80	21	in	in	ADP
cana-4845	80	22	depression	depression	NOUN
cana-4845	80	23	rates	rate	NOUN
cana-4845	80	24	.	.	PUNCT
cana-4845	81	1	for	for	ADP
cana-4845	81	2	evaluation	evaluation	NOUN
cana-4845	81	3	,	,	PUNCT
cana-4845	81	4	use	use	VERB
cana-4845	81	5	the	the	DET
cana-4845	81	6	sds	sds	NOUN
cana-4845	81	7	scale	scale	NOUN
cana-4845	81	8	and	and	CCONJ
cana-4845	81	9	phq-9	phq-9	NOUN
cana-4845	81	10	.	.	PUNCT
cana-4845	81	11	purude	purude	NOUN
cana-4845	81	12	et	et	PROPN
cana-4845	81	13	al	al	PROPN
cana-4845	81	14	.	.	PUNCT
cana-4845	82	1	[	[	X
cana-4845	82	2	6	6	NUM
cana-4845	82	3	]	]	PUNCT
cana-4845	82	4	talked	talk	VERB
cana-4845	82	5	about	about	ADP
cana-4845	82	6	a	a	DET
cana-4845	82	7	way	way	NOUN
cana-4845	82	8	to	to	PART
cana-4845	82	9	detect	detect	VERB
cana-4845	82	10	depression	depression	NOUN
cana-4845	82	11	by	by	ADP
cana-4845	82	12	gathering	gather	VERB
cana-4845	82	13	information	information	NOUN
cana-4845	82	14	by	by	ADP
cana-4845	82	15	sending	send	VERB
cana-4845	82	16	questionnaires	questionnaire	NOUN
cana-4845	82	17	to	to	ADP
cana-4845	82	18	people	people	NOUN
cana-4845	82	19	on	on	ADP
cana-4845	82	20	several	several	ADJ
cana-4845	82	21	platforms	platform	NOUN
cana-4845	82	22	.	.	PUNCT
cana-4845	83	1	in	in	ADP
cana-4845	83	2	this	this	DET
cana-4845	83	3	context	context	NOUN
cana-4845	83	4	,	,	PUNCT
cana-4845	83	5	classifiers	classifier	NOUN
cana-4845	83	6	such	such	ADJ
cana-4845	83	7	as	as	ADP
cana-4845	83	8	logistic	logistic	ADJ
cana-4845	83	9	regression	regression	NOUN
cana-4845	83	10	,	,	PUNCT
cana-4845	83	11	decision	decision	NOUN
cana-4845	83	12	trees	tree	NOUN
cana-4845	83	13	,	,	PUNCT
cana-4845	83	14	support	support	NOUN
cana-4845	83	15	vector	vector	NOUN
cana-4845	83	16	machines	machine	NOUN
cana-4845	83	17	(	(	PUNCT
cana-4845	83	18	svm	svm	PROPN
cana-4845	83	19	)	)	PUNCT
cana-4845	83	20	,	,	PUNCT
cana-4845	83	21	and	and	CCONJ
cana-4845	83	22	k	k	X
cana-4845	83	23	-	-	PUNCT
cana-4845	83	24	nearest	near	ADJ
cana-4845	83	25	neighbor	neighbor	NOUN
cana-4845	83	26	(	(	PUNCT
cana-4845	83	27	knn	knn	PROPN
cana-4845	83	28	)	)	PUNCT
cana-4845	83	29	are	be	AUX
cana-4845	83	30	used	use	VERB
cana-4845	83	31	.	.	PUNCT
cana-4845	84	1	the	the	DET
cana-4845	84	2	accuracy	accuracy	NOUN
cana-4845	84	3	level	level	NOUN
cana-4845	84	4	attained	attain	VERB
cana-4845	84	5	by	by	ADP
cana-4845	84	6	the	the	DET
cana-4845	84	7	system	system	NOUN
cana-4845	84	8	is	be	AUX
cana-4845	84	9	90	90	NUM
cana-4845	84	10	%	%	NOUN
cana-4845	84	11	.	.	PUNCT
cana-4845	85	1	one	one	NUM
cana-4845	85	2	drawback	drawback	NOUN
cana-4845	85	3	of	of	ADP
cana-4845	85	4	the	the	DET
cana-4845	85	5	system	system	NOUN
cana-4845	85	6	is	be	AUX
cana-4845	85	7	its	its	PRON
cana-4845	85	8	limited	limited	ADJ
cana-4845	85	9	database	database	NOUN
cana-4845	85	10	.	.	PUNCT
cana-4845	86	1	by	by	ADP
cana-4845	86	2	looking	look	VERB
cana-4845	86	3	at	at	ADP
cana-4845	86	4	posts	post	NOUN
cana-4845	86	5	on	on	ADP
cana-4845	86	6	social	social	ADJ
cana-4845	86	7	media	medium	NOUN
cana-4845	86	8	platforms	platform	NOUN
cana-4845	86	9	like	like	ADP
cana-4845	86	10	twitter	twitter	NOUN
cana-4845	86	11	,	,	PUNCT
cana-4845	86	12	a	a	DET
cana-4845	86	13	machine	machine	NOUN
cana-4845	86	14	learning	learn	VERB
cana-4845	86	15	algorithm	algorithm	NOUN
cana-4845	86	16	is	be	AUX
cana-4845	86	17	used	use	VERB
cana-4845	86	18	to	to	PART
cana-4845	86	19	identify	identify	VERB
cana-4845	86	20	depression	depression	NOUN
cana-4845	86	21	.	.	PUNCT
cana-4845	87	1	tweets	tweet	NOUN
cana-4845	87	2	are	be	AUX
cana-4845	87	3	stripped	strip	VERB
cana-4845	87	4	of	of	ADP
cana-4845	87	5	their	their	PRON
cana-4845	87	6	keywords	keyword	NOUN
cana-4845	87	7	.	.	PUNCT
cana-4845	88	1	the	the	DET
cana-4845	88	2	bayes	bayes	PROPN
cana-4845	88	3	classifier	classifier	NOUN
cana-4845	88	4	and	and	CCONJ
cana-4845	88	5	python	python	NOUN
cana-4845	88	6	were	be	AUX
cana-4845	88	7	used	use	VERB
cana-4845	88	8	to	to	PART
cana-4845	88	9	determine	determine	VERB
cana-4845	88	10	whether	whether	SCONJ
cana-4845	88	11	the	the	DET
cana-4845	88	12	person	person	NOUN
cana-4845	88	13	was	be	AUX
cana-4845	88	14	depressed	depressed	ADJ
cana-4845	88	15	.	.	PUNCT
cana-4845	89	1	a	a	DET
cana-4845	89	2	model	model	NOUN
cana-4845	89	3	for	for	ADP
cana-4845	89	4	detecting	detect	VERB
cana-4845	89	5	sorrow	sorrow	NOUN
cana-4845	89	6	based	base	VERB
cana-4845	89	7	on	on	ADP
cana-4845	89	8	local	local	ADJ
cana-4845	89	9	circumstances	circumstance	NOUN
cana-4845	89	10	was	be	AUX
cana-4845	89	11	presented	present	VERB
cana-4845	89	12	by	by	ADP
cana-4845	89	13	bryan	bryan	PROPN
cana-4845	89	14	g.	g.	PROPN
cana-4845	89	15	dadiz	dadiz	PROPN
cana-4845	89	16	et	et	PROPN
cana-4845	89	17	al	al	PROPN
cana-4845	89	18	.	.	PUNCT
cana-4845	90	1	a	a	DET
cana-4845	90	2	video	video	NOUN
cana-4845	90	3	recording	recording	NOUN
cana-4845	90	4	's	's	PART
cana-4845	90	5	facial	facial	ADJ
cana-4845	90	6	image	image	NOUN
cana-4845	90	7	is	be	AUX
cana-4845	90	8	extracted	extract	VERB
cana-4845	90	9	and	and	CCONJ
cana-4845	90	10	cropped	crop	VERB
cana-4845	90	11	.	.	PUNCT
cana-4845	91	1	on	on	ADP
cana-4845	91	2	every	every	DET
cana-4845	91	3	boundary	boundary	NOUN
cana-4845	91	4	,	,	PUNCT
cana-4845	91	5	lbp	lbp	PROPN
cana-4845	91	6	is	be	AUX
cana-4845	91	7	conspicuous	conspicuous	ADJ
cana-4845	91	8	due	due	ADP
cana-4845	91	9	to	to	ADP
cana-4845	91	10	its	its	PRON
cana-4845	91	11	formal	formal	ADJ
cana-4845	91	12	attire	attire	NOUN
cana-4845	91	13	.	.	PUNCT
cana-4845	92	1	the	the	DET
cana-4845	92	2	impacts	impact	NOUN
cana-4845	92	3	are	be	AUX
cana-4845	92	4	grouped	group	VERB
cana-4845	92	5	and	and	CCONJ
cana-4845	92	6	analyzed	analyze	VERB
cana-4845	92	7	using	use	VERB
cana-4845	92	8	the	the	DET
cana-4845	92	9	eigenvalues	eigenvalue	NOUN
cana-4845	92	10	from	from	ADP
cana-4845	92	11	the	the	DET
cana-4845	92	12	first	first	ADJ
cana-4845	92	13	highlights	highlight	NOUN
cana-4845	92	14	during	during	ADP
cana-4845	92	15	principal	principal	ADJ
cana-4845	92	16	component	component	NOUN
cana-4845	92	17	analysis	analysis	NOUN
cana-4845	92	18	(	(	PUNCT
cana-4845	92	19	pca	pca	PROPN
cana-4845	92	20	)	)	PUNCT
cana-4845	92	21	.	.	PUNCT
cana-4845	93	1	the	the	DET
cana-4845	93	2	svm	svm	PROPN
cana-4845	93	3	classifier	classifier	PROPN
cana-4845	93	4	attains	attain	VERB
cana-4845	93	5	an	an	DET
cana-4845	93	6	81	81	NUM
cana-4845	93	7	%	%	NOUN
cana-4845	93	8	accuracy	accuracy	NOUN
cana-4845	93	9	rate	rate	NOUN
cana-4845	93	10	in	in	ADP
cana-4845	93	11	the	the	DET
cana-4845	93	12	system	system	NOUN
cana-4845	93	13	while	while	SCONJ
cana-4845	93	14	using	use	VERB
cana-4845	93	15	a	a	DET
cana-4845	93	16	radial	radial	ADJ
cana-4845	93	17	basis	basis	NOUN
cana-4845	93	18	function	function	NOUN
cana-4845	93	19	as	as	ADP
cana-4845	93	20	the	the	DET
cana-4845	93	21	kernel	kernel	NOUN
cana-4845	93	22	.	.	PUNCT
cana-4845	94	1	in	in	ADP
cana-4845	94	2	addition	addition	NOUN
cana-4845	94	3	to	to	ADP
cana-4845	94	4	capturing	capture	VERB
cana-4845	94	5	particular	particular	ADJ
cana-4845	94	6	communications	communication	NOUN
cana-4845	94	7	on	on	ADP
cana-4845	94	8	applied	apply	VERB
cana-4845	94	9	nonlinear	nonlinear	ADJ
cana-4845	94	10	analysis	analysis	NOUN
cana-4845	94	11	issn	issn	NOUN
cana-4845	94	12	:	:	PUNCT
cana-4845	94	13	1074	1074	NUM
cana-4845	94	14	-	-	PUNCT
cana-4845	94	15	133x	133x	NUM
cana-4845	94	16	vol	vol	VERB
cana-4845	94	17	32	32	NUM
cana-4845	94	18	no	no	NOUN
cana-4845	94	19	.	.	PUNCT
cana-4845	95	1	10s	10	NOUN
cana-4845	95	2	(	(	PUNCT
cana-4845	95	3	2025	2025	NUM
cana-4845	95	4	)	)	PUNCT
cana-4845	95	5	549	549	NUM
cana-4845	95	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	95	7	background	background	NOUN
cana-4845	95	8	elements	element	NOUN
cana-4845	95	9	,	,	PUNCT
cana-4845	95	10	the	the	DET
cana-4845	95	11	viola	viola	PROPN
cana-4845	95	12	and	and	CCONJ
cana-4845	95	13	jones	jones	PROPN
cana-4845	95	14	method	method	PROPN
cana-4845	95	15	was	be	AUX
cana-4845	95	16	utilized	utilize	VERB
cana-4845	95	17	to	to	PART
cana-4845	95	18	extract	extract	VERB
cana-4845	95	19	facial	facial	ADJ
cana-4845	95	20	features	feature	NOUN
cana-4845	95	21	from	from	ADP
cana-4845	95	22	video	video	NOUN
cana-4845	95	23	images	image	NOUN
cana-4845	95	24	.	.	PUNCT
cana-4845	96	1	the	the	DET
cana-4845	96	2	goal	goal	NOUN
cana-4845	96	3	of	of	ADP
cana-4845	96	4	the	the	DET
cana-4845	96	5	study	study	NOUN
cana-4845	96	6	by	by	ADP
cana-4845	96	7	mandar	mandar	PROPN
cana-4845	96	8	deshpande	deshpande	PROPN
cana-4845	96	9	et	et	PROPN
cana-4845	96	10	al	al	PROPN
cana-4845	96	11	.	.	PUNCT
cana-4845	97	1	[	[	X
cana-4845	97	2	9	9	NUM
cana-4845	97	3	]	]	PUNCT
cana-4845	97	4	is	be	AUX
cana-4845	97	5	to	to	PART
cana-4845	97	6	identify	identify	VERB
cana-4845	97	7	sentiment	sentiment	NOUN
cana-4845	97	8	associated	associate	VERB
cana-4845	97	9	with	with	ADP
cana-4845	97	10	depression	depression	NOUN
cana-4845	97	11	by	by	ADP
cana-4845	97	12	examining	examine	VERB
cana-4845	97	13	twitter	twitter	NOUN
cana-4845	97	14	feeds	feed	NOUN
cana-4845	97	15	.	.	PUNCT
cana-4845	98	1	the	the	DET
cana-4845	98	2	tweet	tweet	NOUN
cana-4845	98	3	is	be	AUX
cana-4845	98	4	categorized	categorize	VERB
cana-4845	98	5	as	as	ADP
cana-4845	98	6	either	either	CCONJ
cana-4845	98	7	accurate	accurate	ADJ
cana-4845	98	8	or	or	CCONJ
cana-4845	98	9	inaccurate	inaccurate	ADJ
cana-4845	98	10	based	base	VERB
cana-4845	98	11	on	on	ADP
cana-4845	98	12	the	the	DET
cana-4845	98	13	use	use	NOUN
cana-4845	98	14	of	of	ADP
cana-4845	98	15	a	a	DET
cana-4845	98	16	carefully	carefully	ADV
cana-4845	98	17	selected	select	VERB
cana-4845	98	18	set	set	NOUN
cana-4845	98	19	of	of	ADP
cana-4845	98	20	terms	term	NOUN
cana-4845	98	21	to	to	PART
cana-4845	98	22	identify	identify	VERB
cana-4845	98	23	symptoms	symptom	NOUN
cana-4845	98	24	of	of	ADP
cana-4845	98	25	depression	depression	NOUN
cana-4845	98	26	.	.	PUNCT
cana-4845	99	1	both	both	CCONJ
cana-4845	99	2	svm	svm	PROPN
cana-4845	99	3	and	and	CCONJ
cana-4845	99	4	the	the	DET
cana-4845	99	5	naive	naive	ADJ
cana-4845	99	6	-	-	PUNCT
cana-4845	99	7	bayes	bayes	NOUN
cana-4845	99	8	classifier	classifier	NOUN
cana-4845	99	9	were	be	AUX
cana-4845	99	10	used	use	VERB
cana-4845	99	11	for	for	ADP
cana-4845	99	12	classification	classification	NOUN
cana-4845	99	13	tasks	task	NOUN
cana-4845	99	14	.	.	PUNCT
cana-4845	100	1	the	the	DET
cana-4845	100	2	confusion	confusion	NOUN
cana-4845	100	3	matrix	matrix	NOUN
cana-4845	100	4	,	,	PUNCT
cana-4845	100	5	precision	precision	NOUN
cana-4845	100	6	,	,	PUNCT
cana-4845	100	7	and	and	CCONJ
cana-4845	100	8	f1	f1	NOUN
cana-4845	100	9	score	score	NOUN
cana-4845	100	10	are	be	AUX
cana-4845	100	11	crucial	crucial	ADJ
cana-4845	100	12	categorical	categorical	ADJ
cana-4845	100	13	characteristics	characteristic	NOUN
cana-4845	100	14	that	that	PRON
cana-4845	100	15	are	be	AUX
cana-4845	100	16	utilized	utilize	VERB
cana-4845	100	17	to	to	PART
cana-4845	100	18	illustrate	illustrate	VERB
cana-4845	100	19	the	the	DET
cana-4845	100	20	results	result	NOUN
cana-4845	100	21	.	.	PUNCT
cana-4845	101	1	more	more	ADJ
cana-4845	101	2	than	than	ADP
cana-4845	101	3	10,000	10,000	NUM
cana-4845	101	4	tweets	tweet	NOUN
cana-4845	101	5	were	be	AUX
cana-4845	101	6	gathered	gather	VERB
cana-4845	101	7	for	for	ADP
cana-4845	101	8	the	the	DET
cana-4845	101	9	training	training	NOUN
cana-4845	101	10	and	and	CCONJ
cana-4845	101	11	test	test	NOUN
cana-4845	101	12	databases	database	NOUN
cana-4845	101	13	using	use	VERB
cana-4845	101	14	the	the	DET
cana-4845	101	15	twitter	twitter	NOUN
cana-4845	101	16	api	api	NOUN
cana-4845	101	17	.	.	PROPN
cana-4845	102	1	20	20	NUM
cana-4845	102	2	%	%	NOUN
cana-4845	102	3	of	of	ADP
cana-4845	102	4	the	the	DET
cana-4845	102	5	data	datum	NOUN
cana-4845	102	6	was	be	AUX
cana-4845	102	7	used	use	VERB
cana-4845	102	8	for	for	ADP
cana-4845	102	9	testing	testing	NOUN
cana-4845	102	10	,	,	PUNCT
cana-4845	102	11	while	while	SCONJ
cana-4845	102	12	the	the	DET
cana-4845	102	13	remaining	remain	VERB
cana-4845	102	14	80	80	NUM
cana-4845	102	15	%	%	NOUN
cana-4845	102	16	was	be	AUX
cana-4845	102	17	used	use	VERB
cana-4845	102	18	for	for	ADP
cana-4845	102	19	training	training	NOUN
cana-4845	102	20	.	.	PUNCT
cana-4845	103	1	naive	naive	ADJ
cana-4845	103	2	bayes	bayes	PROPN
cana-4845	103	3	is	be	AUX
cana-4845	103	4	a	a	DET
cana-4845	103	5	popular	popular	ADJ
cana-4845	103	6	text	text	NOUN
cana-4845	103	7	classification	classification	NOUN
cana-4845	103	8	method	method	NOUN
cana-4845	103	9	that	that	PRON
cana-4845	103	10	works	work	VERB
cana-4845	103	11	well	well	ADV
cana-4845	103	12	with	with	ADP
cana-4845	103	13	multinomial	multinomial	ADJ
cana-4845	103	14	data	datum	NOUN
cana-4845	103	15	.	.	PUNCT
cana-4845	104	1	it	it	PRON
cana-4845	104	2	also	also	ADV
cana-4845	104	3	makes	make	VERB
cana-4845	104	4	use	use	NOUN
cana-4845	104	5	of	of	ADP
cana-4845	104	6	the	the	DET
cana-4845	104	7	svm	svm	PROPN
cana-4845	104	8	classifier	classifier	NOUN
cana-4845	104	9	.	.	PUNCT
cana-4845	105	1	shen	shen	PROPN
cana-4845	105	2	jian	jian	PROPN
cana-4845	105	3	et	et	PROPN
cana-4845	105	4	al	al	PROPN
cana-4845	105	5	.	.	PUNCT
cana-4845	106	1	[	[	X
cana-4845	106	2	12	12	NUM
cana-4845	106	3	]	]	PUNCT
cana-4845	106	4	used	use	VERB
cana-4845	106	5	a	a	DET
cana-4845	106	6	three	three	NUM
cana-4845	106	7	-	-	PUNCT
cana-4845	106	8	electrode	electrode	NOUN
cana-4845	106	9	invasive	invasive	ADJ
cana-4845	106	10	eeg	eeg	NOUN
cana-4845	106	11	acquisition	acquisition	NOUN
cana-4845	106	12	device	device	NOUN
cana-4845	106	13	to	to	PART
cana-4845	106	14	record	record	VERB
cana-4845	106	15	eeg	eeg	NOUN
cana-4845	106	16	data	datum	NOUN
cana-4845	106	17	while	while	SCONJ
cana-4845	106	18	the	the	DET
cana-4845	106	19	subjects	subject	NOUN
cana-4845	106	20	'	'	PART
cana-4845	106	21	eyes	eye	NOUN
cana-4845	106	22	were	be	AUX
cana-4845	106	23	closed	close	VERB
cana-4845	106	24	at	at	ADP
cana-4845	106	25	rest	rest	NOUN
cana-4845	106	26	.	.	PUNCT
cana-4845	107	1	using	use	VERB
cana-4845	107	2	ubiquitous	ubiquitous	ADJ
cana-4845	107	3	eeg	eeg	NOUN
cana-4845	107	4	,	,	PUNCT
cana-4845	107	5	a	a	DET
cana-4845	107	6	novel	novel	ADJ
cana-4845	107	7	technique	technique	NOUN
cana-4845	107	8	for	for	ADP
cana-4845	107	9	detecting	detect	VERB
cana-4845	107	10	and	and	CCONJ
cana-4845	107	11	diagnosing	diagnose	VERB
cana-4845	107	12	depression	depression	NOUN
cana-4845	107	13	was	be	AUX
cana-4845	107	14	presented	present	VERB
cana-4845	107	15	by	by	ADP
cana-4845	107	16	examining	examine	VERB
cana-4845	107	17	scalp	scalp	NOUN
cana-4845	107	18	electrodes	electrode	NOUN
cana-4845	107	19	at	at	ADP
cana-4845	107	20	the	the	DET
cana-4845	107	21	emotions	emotion	NOUN
cana-4845	107	22	-	-	PUNCT
cana-4845	107	23	related	relate	VERB
cana-4845	107	24	fp1	fp1	NOUN
cana-4845	107	25	,	,	PUNCT
cana-4845	107	26	fpz	fpz	PROPN
cana-4845	107	27	,	,	PUNCT
cana-4845	107	28	and	and	CCONJ
cana-4845	107	29	fp2	fp2	PROPN
cana-4845	107	30	.	.	PUNCT
cana-4845	108	1	all	all	DET
cana-4845	108	2	170	170	NUM
cana-4845	108	3	patients	patient	NOUN
cana-4845	108	4	(	(	PUNCT
cana-4845	108	5	81	81	NUM
cana-4845	108	6	with	with	ADP
cana-4845	108	7	depression	depression	NOUN
cana-4845	108	8	and	and	CCONJ
cana-4845	108	9	89	89	NUM
cana-4845	108	10	without	without	ADP
cana-4845	108	11	)	)	PUNCT
cana-4845	108	12	had	have	VERB
cana-4845	108	13	their	their	PRON
cana-4845	108	14	peripatetic	peripatetic	ADJ
cana-4845	108	15	pervasive	pervasive	ADJ
cana-4845	108	16	eeg	eeg	NOUN
cana-4845	108	17	recorded	record	VERB
cana-4845	108	18	while	while	SCONJ
cana-4845	108	19	they	they	PRON
cana-4845	108	20	were	be	AUX
cana-4845	108	21	sleeping	sleep	VERB
cana-4845	108	22	with	with	ADP
cana-4845	108	23	their	their	PRON
cana-4845	108	24	eyes	eye	NOUN
cana-4845	108	25	closed	close	VERB
cana-4845	108	26	during	during	ADP
cana-4845	108	27	the	the	DET
cana-4845	108	28	trial	trial	NOUN
cana-4845	108	29	.	.	PUNCT
cana-4845	109	1	to	to	PART
cana-4845	109	2	predict	predict	VERB
cana-4845	109	3	heart	heart	NOUN
cana-4845	109	4	difficulties	difficulty	NOUN
cana-4845	109	5	,	,	PUNCT
cana-4845	109	6	noor	noor	PROPN
cana-4845	109	7	,	,	PUNCT
cana-4845	109	8	sumaiya	sumaiya	PROPN
cana-4845	109	9	tarannum	tarannum	PROPN
cana-4845	109	10	,	,	PUNCT
cana-4845	109	11	and	and	CCONJ
cana-4845	109	12	their	their	PRON
cana-4845	109	13	collaborators	collaborator	NOUN
cana-4845	109	14	[	[	X
cana-4845	109	15	13	13	NUM
cana-4845	109	16	]	]	PUNCT
cana-4845	109	17	used	use	VERB
cana-4845	109	18	a	a	DET
cana-4845	109	19	feature	feature	NOUN
cana-4845	109	20	extraction	extraction	NOUN
cana-4845	109	21	method	method	NOUN
cana-4845	109	22	in	in	ADP
cana-4845	109	23	this	this	DET
cana-4845	109	24	model	model	NOUN
cana-4845	109	25	.	.	PUNCT
cana-4845	110	1	the	the	DET
cana-4845	110	2	extracted	extract	VERB
cana-4845	110	3	st	st	PROPN
cana-4845	110	4	segment	segment	NOUN
cana-4845	110	5	and	and	CCONJ
cana-4845	110	6	qrs	qrs	PROPN
cana-4845	110	7	wave	wave	PROPN
cana-4845	110	8	from	from	ADP
cana-4845	110	9	ecg	ecg	PROPN
cana-4845	110	10	data	datum	NOUN
cana-4845	110	11	can	can	AUX
cana-4845	110	12	be	be	AUX
cana-4845	110	13	used	use	VERB
cana-4845	110	14	by	by	ADP
cana-4845	110	15	a	a	DET
cana-4845	110	16	web	web	NOUN
cana-4845	110	17	application	application	NOUN
cana-4845	110	18	to	to	PART
cana-4845	110	19	identify	identify	VERB
cana-4845	110	20	whether	whether	SCONJ
cana-4845	110	21	a	a	DET
cana-4845	110	22	user	user	NOUN
cana-4845	110	23	is	be	AUX
cana-4845	110	24	under	under	ADP
cana-4845	110	25	acute	acute	ADJ
cana-4845	110	26	,	,	PUNCT
cana-4845	110	27	chronic	chronic	NOUN
cana-4845	110	28	,	,	PUNCT
cana-4845	110	29	or	or	CCONJ
cana-4845	110	30	hyper	hyper	ADJ
cana-4845	110	31	acute	acute	NOUN
cana-4845	110	32	stress	stress	NOUN
cana-4845	110	33	.	.	PUNCT
cana-4845	111	1	this	this	DET
cana-4845	111	2	configuration	configuration	NOUN
cana-4845	111	3	forecasts	forecast	NOUN
cana-4845	111	4	pvc	pvc	ADJ
cana-4845	111	5	,	,	PUNCT
cana-4845	111	6	aberrant	aberrant	ADJ
cana-4845	111	7	,	,	PUNCT
cana-4845	111	8	and	and	CCONJ
cana-4845	111	9	normal	normal	ADJ
cana-4845	111	10	heartbeats	heartbeat	NOUN
cana-4845	111	11	using	use	VERB
cana-4845	111	12	an	an	DET
cana-4845	111	13	lstm	lstm	ADJ
cana-4845	111	14	auto	auto	NOUN
cana-4845	111	15	encoder	encoder	NOUN
cana-4845	111	16	and	and	CCONJ
cana-4845	111	17	an	an	DET
cana-4845	111	18	rnn	rnn	NOUN
cana-4845	111	19	.	.	PUNCT
cana-4845	112	1	an	an	DET
cana-4845	112	2	rnn	rnn	NOUN
cana-4845	112	3	model	model	NOUN
cana-4845	112	4	that	that	PRON
cana-4845	112	5	distinguishes	distinguish	VERB
cana-4845	112	6	between	between	ADP
cana-4845	112	7	pvc	pvc	ADJ
cana-4845	112	8	,	,	PUNCT
cana-4845	112	9	irregular	irregular	ADJ
cana-4845	112	10	,	,	PUNCT
cana-4845	112	11	and	and	CCONJ
cana-4845	112	12	normal	normal	ADJ
cana-4845	112	13	heart	heart	NOUN
cana-4845	112	14	beats	beat	NOUN
cana-4845	112	15	is	be	AUX
cana-4845	112	16	based	base	VERB
cana-4845	112	17	on	on	ADP
cana-4845	112	18	deep	deep	ADJ
cana-4845	112	19	learning	learning	NOUN
cana-4845	112	20	.	.	PUNCT
cana-4845	113	1	the	the	DET
cana-4845	113	2	model	model	NOUN
cana-4845	113	3	forecasts	forecast	VERB
cana-4845	113	4	pvc	pvc	ADJ
cana-4845	113	5	and	and	CCONJ
cana-4845	113	6	irregular	irregular	ADJ
cana-4845	113	7	heartbeats	heartbeat	NOUN
cana-4845	113	8	using	use	VERB
cana-4845	113	9	a	a	DET
cana-4845	113	10	collection	collection	NOUN
cana-4845	113	11	of	of	ADP
cana-4845	113	12	heart	heart	NOUN
cana-4845	113	13	rate	rate	NOUN
cana-4845	113	14	data	datum	NOUN
cana-4845	113	15	.	.	PUNCT
cana-4845	114	1	for	for	ADP
cana-4845	114	2	the	the	DET
cana-4845	114	3	dataset	dataset	NOUN
cana-4845	114	4	,	,	PUNCT
cana-4845	114	5	5000	5000	NUM
cana-4845	114	6	ecg	ecg	PROPN
cana-4845	114	7	samples	sample	NOUN
cana-4845	114	8	were	be	AUX
cana-4845	114	9	used	use	VERB
cana-4845	114	10	.	.	PUNCT
cana-4845	115	1	he	he	PRON
cana-4845	115	2	lang	lang	PROPN
cana-4845	115	3	together	together	ADV
cana-4845	115	4	with	with	ADP
cana-4845	115	5	his	his	PRON
cana-4845	115	6	associates	associate	NOUN
cana-4845	115	7	[	[	X
cana-4845	115	8	15	15	NUM
cana-4845	115	9	]	]	PUNCT
cana-4845	115	10	.	.	PUNCT
cana-4845	116	1	speech	speech	NOUN
cana-4845	116	2	talents	talent	NOUN
cana-4845	116	3	offer	offer	VERB
cana-4845	116	4	useful	useful	ADJ
cana-4845	116	5	information	information	NOUN
cana-4845	116	6	for	for	ADP
cana-4845	116	7	depression	depression	NOUN
cana-4845	116	8	analysis	analysis	NOUN
cana-4845	116	9	.	.	PUNCT
cana-4845	117	1	during	during	ADP
cana-4845	117	2	the	the	DET
cana-4845	117	3	depression	depression	NOUN
cana-4845	117	4	,	,	PUNCT
cana-4845	117	5	a	a	DET
cana-4845	117	6	number	number	NOUN
cana-4845	117	7	of	of	ADP
cana-4845	117	8	depressing	depress	VERB
cana-4845	117	9	marketing	marketing	NOUN
cana-4845	117	10	strategies	strategy	NOUN
cana-4845	117	11	were	be	AUX
cana-4845	117	12	implemented	implement	VERB
cana-4845	117	13	.	.	PUNCT
cana-4845	118	1	recognition	recognition	NOUN
cana-4845	118	2	of	of	ADP
cana-4845	118	3	the	the	DET
cana-4845	118	4	image	image	NOUN
cana-4845	118	5	using	use	VERB
cana-4845	118	6	the	the	DET
cana-4845	118	7	avec2013	avec2013	PROPN
cana-4845	118	8	,	,	PUNCT
cana-4845	118	9	avec2014	avec2014	PROPN
cana-4845	118	10	,	,	PUNCT
cana-4845	118	11	avec2016	avec2016	PROPN
cana-4845	118	12	,	,	PUNCT
cana-4845	118	13	and	and	CCONJ
cana-4845	118	14	avec2017	avec2017	NUM
cana-4845	118	15	datasets	dataset	NOUN
cana-4845	118	16	that	that	PRON
cana-4845	118	17	shows	show	VERB
cana-4845	118	18	innovation	innovation	NOUN
cana-4845	118	19	and	and	CCONJ
cana-4845	118	20	rebellion	rebellion	NOUN
cana-4845	118	21	.	.	PUNCT
cana-4845	119	1	based	base	VERB
cana-4845	119	2	on	on	ADP
cana-4845	119	3	the	the	DET
cana-4845	119	4	avec2013	avec2013	PROPN
cana-4845	119	5	and	and	CCONJ
cana-4845	119	6	avec2014	avec2014	PROPN
cana-4845	119	7	datasets	dataset	NOUN
cana-4845	119	8	,	,	PUNCT
cana-4845	119	9	three	three	NUM
cana-4845	119	10	regression	regression	NOUN
cana-4845	119	11	techniques	technique	NOUN
cana-4845	119	12	were	be	AUX
cana-4845	119	13	developed	develop	VERB
cana-4845	119	14	,	,	PUNCT
cana-4845	119	15	taking	take	VERB
cana-4845	119	16	into	into	ADP
cana-4845	119	17	account	account	NOUN
cana-4845	119	18	the	the	DET
cana-4845	119	19	avec2016	avec2016	PROPN
cana-4845	119	20	and	and	CCONJ
cana-4845	119	21	avec2017	avec2017	PROPN
cana-4845	119	22	data	datum	NOUN
cana-4845	119	23	for	for	ADP
cana-4845	119	24	the	the	DET
cana-4845	119	25	type	type	NOUN
cana-4845	119	26	methodology	methodology	NOUN
cana-4845	119	27	.	.	PUNCT
cana-4845	120	1	it	it	PRON
cana-4845	120	2	makes	make	VERB
cana-4845	120	3	use	use	NOUN
cana-4845	120	4	of	of	ADP
cana-4845	120	5	avec2013	avec2013	PROPN
cana-4845	120	6	and	and	CCONJ
cana-4845	120	7	avec2014	avec2014	PROPN
cana-4845	120	8	data	datum	NOUN
cana-4845	120	9	.	.	PUNCT
cana-4845	121	1	through	through	ADP
cana-4845	121	2	an	an	DET
cana-4845	121	3	analysis	analysis	NOUN
cana-4845	121	4	of	of	ADP
cana-4845	121	5	overall	overall	ADJ
cana-4845	121	6	performance	performance	NOUN
cana-4845	121	7	,	,	PUNCT
cana-4845	121	8	depression	depression	NOUN
cana-4845	121	9	is	be	AUX
cana-4845	121	10	predicted	predict	VERB
cana-4845	121	11	using	use	VERB
cana-4845	121	12	mean	mean	ADJ
cana-4845	121	13	absolute	absolute	ADJ
cana-4845	121	14	error	error	NOUN
cana-4845	121	15	(	(	PUNCT
cana-4845	121	16	mae	mae	PROPN
cana-4845	121	17	)	)	PUNCT
cana-4845	121	18	and	and	CCONJ
cana-4845	121	19	root	root	NOUN
cana-4845	121	20	mean	mean	ADJ
cana-4845	121	21	square	square	ADJ
cana-4845	121	22	error	error	NOUN
cana-4845	121	23	(	(	PUNCT
cana-4845	121	24	rmse	rmse	NOUN
cana-4845	121	25	)	)	PUNCT
cana-4845	121	26	.	.	PUNCT
cana-4845	122	1	muhammad	muhammad	PROPN
cana-4845	122	2	tariq	tariq	PROPN
cana-4845	122	3	sadiq	sadiq	PROPN
cana-4845	122	4	and	and	CCONJ
cana-4845	122	5	colleagues	colleague	NOUN
cana-4845	123	1	[	[	X
cana-4845	123	2	16	16	NUM
cana-4845	123	3	]	]	PUNCT
cana-4845	123	4	proposed	propose	VERB
cana-4845	123	5	a	a	DET
cana-4845	123	6	simple	simple	ADJ
cana-4845	123	7	and	and	CCONJ
cana-4845	123	8	dependable	dependable	ADJ
cana-4845	123	9	automated	automate	VERB
cana-4845	123	10	multivariate	multivariate	NOUN
cana-4845	123	11	empirical	empirical	ADJ
cana-4845	123	12	wavelet	wavelet	NOUN
cana-4845	123	13	transform	transform	NOUN
cana-4845	123	14	(	(	PUNCT
cana-4845	123	15	mewt	mewt	NOUN
cana-4845	123	16	)	)	PUNCT
cana-4845	123	17	approach	approach	NOUN
cana-4845	123	18	for	for	ADP
cana-4845	123	19	decoding	decode	VERB
cana-4845	123	20	different	different	ADJ
cana-4845	123	21	motor	motor	NOUN
cana-4845	123	22	imagery	imagery	NOUN
cana-4845	123	23	(	(	PUNCT
cana-4845	123	24	mi	mi	NOUN
cana-4845	123	25	)	)	PUNCT
cana-4845	123	26	tasks	task	NOUN
cana-4845	123	27	.	.	PUNCT
cana-4845	124	1	there	there	PRON
cana-4845	124	2	have	have	AUX
cana-4845	124	3	been	be	AUX
cana-4845	124	4	four	four	NUM
cana-4845	124	5	significant	significant	ADJ
cana-4845	124	6	contributions	contribution	NOUN
cana-4845	124	7	made	make	VERB
cana-4845	124	8	.	.	PUNCT
cana-4845	125	1	first	first	ADV
cana-4845	125	2	,	,	PUNCT
cana-4845	125	3	preprocessing	preprocessing	NOUN
cana-4845	125	4	is	be	AUX
cana-4845	125	5	done	do	VERB
cana-4845	125	6	using	use	VERB
cana-4845	125	7	the	the	DET
cana-4845	125	8	multi	multi	ADJ
cana-4845	125	9	-	-	ADJ
cana-4845	125	10	scale	scale	ADJ
cana-4845	125	11	principal	principal	ADJ
cana-4845	125	12	component	component	NOUN
cana-4845	125	13	analysis	analysis	NOUN
cana-4845	125	14	technique	technique	NOUN
cana-4845	125	15	.	.	PUNCT
cana-4845	126	1	subsequently	subsequently	ADV
cana-4845	126	2	,	,	PUNCT
cana-4845	126	3	a	a	DET
cana-4845	126	4	novel	novel	ADJ
cana-4845	126	5	automatic	automatic	ADJ
cana-4845	126	6	channel	channel	NOUN
cana-4845	126	7	selection	selection	NOUN
cana-4845	126	8	method	method	NOUN
cana-4845	126	9	is	be	AUX
cana-4845	126	10	introduced	introduce	VERB
cana-4845	126	11	and	and	CCONJ
cana-4845	126	12	assessed	assess	VERB
cana-4845	126	13	by	by	ADP
cana-4845	126	14	closely	closely	ADV
cana-4845	126	15	analyzing	analyze	VERB
cana-4845	126	16	three	three	NUM
cana-4845	126	17	different	different	ADJ
cana-4845	126	18	approaches	approach	NOUN
cana-4845	126	19	to	to	ADP
cana-4845	126	20	channel	channel	NOUN
cana-4845	126	21	matching	matching	NOUN
cana-4845	126	22	.	.	PUNCT
cana-4845	127	1	thirdly	thirdly	ADV
cana-4845	127	2	,	,	PUNCT
cana-4845	127	3	a	a	DET
cana-4845	127	4	technique	technique	NOUN
cana-4845	127	5	combining	combine	VERB
cana-4845	127	6	mewt	mewt	NOUN
cana-4845	127	7	with	with	ADP
cana-4845	127	8	sub	sub	ADJ
cana-4845	127	9	-	-	ADJ
cana-4845	127	10	band	band	ADJ
cana-4845	127	11	alignment	alignment	NOUN
cana-4845	127	12	is	be	AUX
cana-4845	127	13	being	be	AUX
cana-4845	127	14	used	use	VERB
cana-4845	127	15	for	for	ADP
cana-4845	127	16	the	the	DET
cana-4845	127	17	first	first	ADJ
cana-4845	127	18	time	time	NOUN
cana-4845	127	19	to	to	PART
cana-4845	127	20	give	give	VERB
cana-4845	127	21	concurrent	concurrent	ADJ
cana-4845	127	22	amplitude	amplitude	NOUN
cana-4845	127	23	and	and	CCONJ
cana-4845	127	24	frequency	frequency	NOUN
cana-4845	127	25	components	component	NOUN
cana-4845	127	26	in	in	ADP
cana-4845	127	27	mi	mi	PROPN
cana-4845	127	28	applications	application	NOUN
cana-4845	127	29	.	.	PUNCT
cana-4845	128	1	additionally	additionally	ADV
cana-4845	128	2	,	,	PUNCT
cana-4845	128	3	a	a	DET
cana-4845	128	4	strong	strong	ADJ
cana-4845	128	5	emphasis	emphasis	NOUN
cana-4845	128	6	is	be	AUX
cana-4845	128	7	placed	place	VERB
cana-4845	128	8	on	on	ADP
cana-4845	128	9	correlation	correlation	NOUN
cana-4845	128	10	-	-	PUNCT
cana-4845	128	11	based	base	VERB
cana-4845	128	12	feature	feature	NOUN
cana-4845	128	13	selection	selection	NOUN
cana-4845	128	14	methods	method	NOUN
cana-4845	128	15	to	to	PART
cana-4845	128	16	reduce	reduce	VERB
cana-4845	128	17	computational	computational	ADJ
cana-4845	128	18	load	load	NOUN
cana-4845	128	19	and	and	CCONJ
cana-4845	128	20	system	system	NOUN
cana-4845	128	21	complexity	complexity	NOUN
cana-4845	128	22	.	.	PUNCT
cana-4845	129	1	communications	communication	NOUN
cana-4845	129	2	on	on	ADP
cana-4845	129	3	applied	apply	VERB
cana-4845	129	4	nonlinear	nonlinear	ADJ
cana-4845	129	5	analysis	analysis	NOUN
cana-4845	129	6	issn	issn	NOUN
cana-4845	129	7	:	:	PUNCT
cana-4845	129	8	1074	1074	NUM
cana-4845	129	9	-	-	PUNCT
cana-4845	129	10	133x	133x	NUM
cana-4845	129	11	vol	vol	VERB
cana-4845	129	12	32	32	NUM
cana-4845	129	13	no	no	NOUN
cana-4845	129	14	.	.	PUNCT
cana-4845	130	1	10s	10	NOUN
cana-4845	130	2	(	(	PUNCT
cana-4845	130	3	2025	2025	NUM
cana-4845	130	4	)	)	PUNCT
cana-4845	130	5	550	550	NUM
cana-4845	130	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	130	7	following	follow	VERB
cana-4845	130	8	computations	computation	NOUN
cana-4845	130	9	,	,	PUNCT
cana-4845	130	10	the	the	DET
cana-4845	130	11	sample	sample	NOUN
cana-4845	130	12	's	's	PART
cana-4845	130	13	classification	classification	NOUN
cana-4845	130	14	accuracy	accuracy	NOUN
cana-4845	130	15	,	,	PUNCT
cana-4845	130	16	sensitivity	sensitivity	NOUN
cana-4845	130	17	,	,	PUNCT
cana-4845	130	18	and	and	CCONJ
cana-4845	130	19	specificity	specificity	NOUN
cana-4845	130	20	were	be	AUX
cana-4845	130	21	found	find	VERB
cana-4845	130	22	to	to	PART
cana-4845	130	23	be	be	AUX
cana-4845	130	24	91.4	91.4	NUM
cana-4845	130	25	%	%	NOUN
cana-4845	130	26	,	,	PUNCT
cana-4845	130	27	92.1	92.1	NUM
cana-4845	130	28	%	%	NOUN
cana-4845	130	29	,	,	PUNCT
cana-4845	130	30	and	and	CCONJ
cana-4845	130	31	93	93	NUM
cana-4845	130	32	%	%	NOUN
cana-4845	130	33	,	,	PUNCT
cana-4845	130	34	respectively	respectively	ADV
cana-4845	130	35	.	.	PUNCT
cana-4845	131	1	text	text	NOUN
cana-4845	131	2	altered	alter	VERB
cana-4845	131	3	was	be	AUX
cana-4845	131	4	developed	develop	VERB
cana-4845	131	5	by	by	ADP
cana-4845	131	6	shamla	shamla	NOUN
cana-4845	131	7	mantri	mantri	PROPN
cana-4845	131	8	and	and	CCONJ
cana-4845	131	9	associates	associate	NOUN
cana-4845	131	10	[	[	X
cana-4845	131	11	17	17	NUM
cana-4845	131	12	]	]	PUNCT
cana-4845	131	13	using	use	VERB
cana-4845	131	14	a	a	DET
cana-4845	131	15	sample	sample	NOUN
cana-4845	131	16	of	of	ADP
cana-4845	131	17	individuals	individual	NOUN
cana-4845	131	18	ages	age	NOUN
cana-4845	131	19	16	16	NUM
cana-4845	131	20	to	to	PART
cana-4845	131	21	60	60	NUM
cana-4845	131	22	.	.	PUNCT
cana-4845	132	1	they	they	PRON
cana-4845	132	2	were	be	AUX
cana-4845	132	3	recommended	recommend	VERB
cana-4845	132	4	for	for	ADP
cana-4845	132	5	usage	usage	NOUN
cana-4845	132	6	by	by	ADP
cana-4845	132	7	both	both	PRON
cana-4845	132	8	those	those	PRON
cana-4845	132	9	with	with	ADP
cana-4845	132	10	and	and	CCONJ
cana-4845	132	11	without	without	ADP
cana-4845	132	12	depression	depression	NOUN
cana-4845	132	13	.	.	PUNCT
cana-4845	133	1	the	the	DET
cana-4845	133	2	traditional	traditional	ADJ
cana-4845	133	3	10	10	NUM
cana-4845	133	4	-	-	SYM
cana-4845	133	5	20	20	NUM
cana-4845	133	6	electrode	electrode	NOUN
cana-4845	133	7	placement	placement	NOUN
cana-4845	133	8	system	system	NOUN
cana-4845	133	9	is	be	AUX
cana-4845	133	10	used	use	VERB
cana-4845	133	11	to	to	PART
cana-4845	133	12	collect	collect	VERB
cana-4845	133	13	brain	brain	NOUN
cana-4845	133	14	impulses	impulse	NOUN
cana-4845	133	15	from	from	ADP
cana-4845	133	16	electrode	electrode	NOUN
cana-4845	133	17	placements	placement	NOUN
cana-4845	133	18	while	while	SCONJ
cana-4845	133	19	the	the	DET
cana-4845	133	20	subject	subject	NOUN
cana-4845	133	21	is	be	AUX
cana-4845	133	22	immobile	immobile	ADJ
cana-4845	133	23	for	for	ADP
cana-4845	133	24	five	five	NUM
cana-4845	133	25	minutes	minute	NOUN
cana-4845	133	26	.	.	PUNCT
cana-4845	134	1	to	to	PART
cana-4845	134	2	eliminate	eliminate	VERB
cana-4845	134	3	power	power	NOUN
cana-4845	134	4	supply	supply	NOUN
cana-4845	134	5	interference	interference	NOUN
cana-4845	134	6	,	,	PUNCT
cana-4845	134	7	samples	sample	NOUN
cana-4845	134	8	are	be	AUX
cana-4845	134	9	taken	take	VERB
cana-4845	134	10	at	at	ADP
cana-4845	134	11	256	256	NUM
cana-4845	134	12	hz	hz	NOUN
cana-4845	134	13	after	after	SCONJ
cana-4845	134	14	the	the	DET
cana-4845	134	15	signal	signal	NOUN
cana-4845	134	16	has	have	AUX
cana-4845	134	17	been	be	AUX
cana-4845	134	18	filtered	filter	VERB
cana-4845	134	19	at	at	ADP
cana-4845	134	20	50	50	NUM
cana-4845	134	21	hz	hz	NOUN
cana-4845	134	22	.	.	PUNCT
cana-4845	135	1	several	several	ADJ
cana-4845	135	2	eeg	eeg	PROPN
cana-4845	135	3	signal	signal	NOUN
cana-4845	135	4	frequency	frequency	NOUN
cana-4845	135	5	bands	band	NOUN
cana-4845	135	6	were	be	AUX
cana-4845	135	7	obtained	obtain	VERB
cana-4845	135	8	using	use	VERB
cana-4845	135	9	the	the	DET
cana-4845	135	10	butterworth	butterworth	ADJ
cana-4845	135	11	band	band	NOUN
cana-4845	135	12	pass	pass	NOUN
cana-4845	135	13	filter	filter	NOUN
cana-4845	135	14	:	:	PUNCT
cana-4845	135	15	δ	δ	NOUN
cana-4845	135	16	up	up	ADP
cana-4845	135	17	to	to	PART
cana-4845	135	18	4	4	NUM
cana-4845	135	19	hz	hz	VERB
cana-4845	135	20	,	,	PUNCT
cana-4845	135	21	θ	θ	PROPN
cana-4845	135	22	up	up	ADP
cana-4845	135	23	to	to	PART
cana-4845	135	24	8	8	NUM
cana-4845	135	25	hz	hz	VERB
cana-4845	135	26	,	,	PUNCT
cana-4845	135	27	α	α	NOUN
cana-4845	135	28	up	up	ADP
cana-4845	135	29	to	to	PART
cana-4845	135	30	13	13	NUM
cana-4845	135	31	hz	hz	NOUN
cana-4845	135	32	,	,	PUNCT
cana-4845	135	33	and	and	CCONJ
cana-4845	136	1	beta	beta	ADP
cana-4845	136	2	β	β	NOUN
cana-4845	136	3	up	up	ADP
cana-4845	136	4	to	to	PART
cana-4845	136	5	30	30	NUM
cana-4845	136	6	hz	hz	NOUN
cana-4845	136	7	.	.	PUNCT
cana-4845	137	1	dft	dft	PROPN
cana-4845	137	2	and	and	CCONJ
cana-4845	137	3	fft	fft	PROPN
cana-4845	137	4	are	be	AUX
cana-4845	137	5	used	use	VERB
cana-4845	137	6	to	to	PART
cana-4845	137	7	extract	extract	VERB
cana-4845	137	8	features	feature	NOUN
cana-4845	137	9	.	.	PUNCT
cana-4845	138	1	ann	ann	PROPN
cana-4845	138	2	and	and	CCONJ
cana-4845	138	3	svm	svm	PROPN
cana-4845	138	4	were	be	AUX
cana-4845	138	5	used	use	VERB
cana-4845	138	6	to	to	PART
cana-4845	138	7	classify	classify	VERB
cana-4845	138	8	eeg	eeg	NOUN
cana-4845	138	9	signals	signal	NOUN
cana-4845	138	10	.	.	PUNCT
cana-4845	139	1	the	the	DET
cana-4845	139	2	accuracy	accuracy	NOUN
cana-4845	139	3	,	,	PUNCT
cana-4845	139	4	specificity	specificity	NOUN
cana-4845	139	5	,	,	PUNCT
cana-4845	139	6	and	and	CCONJ
cana-4845	139	7	term	term	NOUN
cana-4845	139	8	sensitivity	sensitivity	NOUN
cana-4845	139	9	of	of	ADP
cana-4845	139	10	this	this	DET
cana-4845	139	11	approach	approach	NOUN
cana-4845	139	12	are	be	AUX
cana-4845	139	13	used	use	VERB
cana-4845	139	14	to	to	PART
cana-4845	139	15	assess	assess	VERB
cana-4845	139	16	its	its	PRON
cana-4845	139	17	performance	performance	NOUN
cana-4845	139	18	.	.	PUNCT
cana-4845	140	1	table	table	NOUN
cana-4845	140	2	1	1	NUM
cana-4845	140	3	in	in	ADP
cana-4845	140	4	contrast	contrast	NOUN
cana-4845	140	5	with	with	ADP
cana-4845	140	6	previous	previous	ADJ
cana-4845	140	7	studies	study	NOUN
cana-4845	140	8	methodology	methodology	NOUN
cana-4845	140	9	of	of	ADP
cana-4845	140	10	the	the	DET
cana-4845	140	11	author	author	NOUN
cana-4845	140	12	precision	precision	NOUN
cana-4845	140	13	(	(	PUNCT
cana-4845	140	14	%	%	INTJ
cana-4845	140	15	)	)	PUNCT
cana-4845	140	16	the	the	DET
cana-4845	140	17	percentage	percentage	NOUN
cana-4845	140	18	of	of	ADP
cana-4845	140	19	sensitivity	sensitivity	NOUN
cana-4845	140	20	specificity	specificity	NOUN
cana-4845	140	21	(	(	PUNCT
cana-4845	140	22	percent	percent	NOUN
cana-4845	140	23	)	)	PUNCT
cana-4845	140	24	author	author	NOUN
cana-4845	140	25	methodology	methodology	NOUN
cana-4845	140	26	sensitivity	sensitivity	NOUN
cana-4845	140	27	(	(	PUNCT
cana-4845	140	28	%	%	INTJ
cana-4845	140	29	)	)	PUNCT
cana-4845	140	30	specificity	specificity	NOUN
cana-4845	140	31	(	(	PUNCT
cana-4845	140	32	%	%	INTJ
cana-4845	140	33	)	)	PUNCT
cana-4845	140	34	accuracy	accuracy	NOUN
cana-4845	140	35	(	(	PUNCT
cana-4845	140	36	%	%	NOUN
cana-4845	140	37	)	)	PUNCT
cana-4845	140	38	proposed	propose	VERB
cana-4845	140	39	system	system	NOUN
cana-4845	140	40	lstm	lstm	NOUN
cana-4845	140	41	encoder	encoder	NOUN
cana-4845	140	42	(	(	PUNCT
cana-4845	140	43	ecg	ecg	PROPN
cana-4845	140	44	signals	signal	NOUN
cana-4845	140	45	)	)	PUNCT
cana-4845	140	46	97	97	NUM
cana-4845	140	47	98	98	NUM
cana-4845	140	48	93	93	NUM
cana-4845	140	49	cnn	cnn	NOUN
cana-4845	140	50	(	(	PUNCT
cana-4845	140	51	204	204	NUM
cana-4845	140	52	samples	sample	NOUN
cana-4845	140	53	)	)	PUNCT
cana-4845	140	54	(	(	PUNCT
cana-4845	140	55	eeg	eeg	NOUN
cana-4845	140	56	signals	signal	NOUN
cana-4845	140	57	)	)	PUNCT
cana-4845	140	58	97.69	97.69	NUM
cana-4845	140	59	xiaohan	xiaohan	PROPN
cana-4845	140	60	zang	zang	PROPN
cana-4845	140	61	et	et	PROPN
cana-4845	140	62	.	.	PUNCT
cana-4845	141	1	al	al	PROPN
cana-4845	141	2	.	.	PUNCT
cana-4845	142	1	[	[	X
cana-4845	142	2	4	4	NUM
cana-4845	142	3	]	]	X
cana-4845	142	4	cnn	cnn	PROPN
cana-4845	142	5	(	(	PUNCT
cana-4845	142	6	74	74	NUM
cana-4845	142	7	patients	patient	NOUN
cana-4845	142	8	)	)	PUNCT
cana-4845	142	9	(	(	PUNCT
cana-4845	142	10	ecg	ecg	PROPN
cana-4845	142	11	signals	signal	NOUN
cana-4845	142	12	)	)	PUNCT
cana-4845	142	13	89.43	89.43	NUM
cana-4845	142	14	98.49	98.49	NUM
cana-4845	142	15	93.96	93.96	NUM
cana-4845	142	16	muhammad	muhammad	PROPN
cana-4845	142	17	tariq	tariq	PROPN
cana-4845	142	18	sadiq	sadiq	PROPN
cana-4845	142	19	et	et	PROPN
cana-4845	142	20	.	.	PUNCT
cana-4845	143	1	al	al	PROPN
cana-4845	143	2	.	.	PUNCT
cana-4845	144	1	[	[	X
cana-4845	144	2	22	22	NUM
cana-4845	144	3	]	]	PUNCT
cana-4845	144	4	mspca	mspca	NOUN
cana-4845	144	5	,	,	PUNCT
cana-4845	144	6	cascade	cascade	NOUN
cana-4845	144	7	forward	forward	ADV
cana-4845	144	8	neural	neural	ADJ
cana-4845	144	9	network	network	NOUN
cana-4845	144	10	cfnn	cfnn	NOUN
cana-4845	144	11	(	(	PUNCT
cana-4845	144	12	eeg	eeg	NOUN
cana-4845	144	13	signals	signal	NOUN
cana-4845	144	14	)	)	PUNCT
cana-4845	144	15	95.2	95.2	NUM
cana-4845	144	16	96	96	NUM
cana-4845	144	17	95.3	95.3	NUM
cana-4845	144	18	gulay	gulay	NOUN
cana-4845	144	19	tasci	tasci	PROPN
cana-4845	144	20	et	et	NOUN
cana-4845	144	21	.	.	PUNCT
cana-4845	145	1	al	al	PROPN
cana-4845	145	2	.	.	PUNCT
cana-4845	146	1	[	[	X
cana-4845	146	2	21	21	NUM
cana-4845	146	3	]	]	X
cana-4845	146	4	knn	knn	PROPN
cana-4845	146	5	(	(	PUNCT
cana-4845	146	6	eeg	eeg	NOUN
cana-4845	146	7	signals	signal	NOUN
cana-4845	146	8	)	)	PUNCT
cana-4845	146	9	83.96	83.96	NUM
cana-4845	146	10	shamla	shamla	NOUN
cana-4845	146	11	mantri	mantri	PROPN
cana-4845	146	12	et	et	PROPN
cana-4845	146	13	.	.	PUNCT
cana-4845	147	1	al	al	PROPN
cana-4845	147	2	.	.	PUNCT
cana-4845	148	1	[	[	X
cana-4845	148	2	17	17	NUM
cana-4845	148	3	]	]	PUNCT
cana-4845	148	4	,	,	PUNCT
cana-4845	148	5	fft	fft	PROPN
cana-4845	148	6	and	and	CCONJ
cana-4845	148	7	ann	ann	PROPN
cana-4845	148	8	(	(	PUNCT
cana-4845	148	9	eeg	eeg	NOUN
cana-4845	148	10	signals	signal	NOUN
cana-4845	148	11	)	)	PUNCT
cana-4845	148	12	84.00	84.00	NUM
cana-4845	148	13	jian	jian	PROPN
cana-4845	148	14	shen	shen	PROPN
cana-4845	148	15	et	et	PROPN
cana-4845	148	16	.	.	PUNCT
cana-4845	149	1	al	al	PROPN
cana-4845	150	1	[	[	X
cana-4845	150	2	12	12	NUM
cana-4845	150	3	]	]	PUNCT
cana-4845	150	4	support	support	NOUN
cana-4845	150	5	vector	vector	NOUN
cana-4845	150	6	machine	machine	NOUN
cana-4845	150	7	(	(	PUNCT
cana-4845	150	8	svm	svm	PROPN
cana-4845	150	9	)	)	PUNCT
cana-4845	150	10	(	(	PUNCT
cana-4845	150	11	eeg	eeg	NOUN
cana-4845	150	12	signals	signal	NOUN
cana-4845	150	13	)	)	PUNCT
cana-4845	150	14	83.07	83.07	NUM
cana-4845	150	15	on	on	ADP
cana-4845	150	16	a	a	DET
cana-4845	150	17	national	national	ADJ
cana-4845	150	18	and	and	CCONJ
cana-4845	150	19	worldwide	worldwide	ADJ
cana-4845	150	20	scale	scale	NOUN
cana-4845	150	21	,	,	PUNCT
cana-4845	150	22	research	research	NOUN
cana-4845	150	23	indicates	indicate	VERB
cana-4845	150	24	that	that	SCONJ
cana-4845	150	25	ecg	ecg	PROPN
cana-4845	150	26	signals	signal	NOUN
cana-4845	150	27	have	have	VERB
cana-4845	150	28	an	an	DET
cana-4845	150	29	accuracy	accuracy	NOUN
cana-4845	150	30	of	of	ADP
cana-4845	150	31	93.96	93.96	NUM
cana-4845	150	32	%	%	NOUN
cana-4845	150	33	and	and	CCONJ
cana-4845	150	34	eeg	eeg	NOUN
cana-4845	150	35	signals	signal	NOUN
cana-4845	150	36	have	have	VERB
cana-4845	150	37	an	an	DET
cana-4845	150	38	accuracy	accuracy	NOUN
cana-4845	150	39	of	of	ADP
cana-4845	150	40	95.3	95.3	NUM
cana-4845	150	41	%	%	NOUN
cana-4845	150	42	.	.	PUNCT
cana-4845	151	1	this	this	PRON
cana-4845	151	2	is	be	AUX
cana-4845	151	3	compared	compare	VERB
cana-4845	151	4	with	with	ADP
cana-4845	151	5	current	current	ADJ
cana-4845	151	6	systems	system	NOUN
cana-4845	151	7	in	in	ADP
cana-4845	151	8	table	table	NOUN
cana-4845	151	9	1	1	NUM
cana-4845	151	10	.	.	NOUN
cana-4845	151	11	2	2	NUM
cana-4845	151	12	.	.	NOUN
cana-4845	151	13	methods	method	NOUN
cana-4845	151	14	and	and	CCONJ
cana-4845	151	15	material	material	VERB
cana-4845	151	16	the	the	DET
cana-4845	151	17	purpose	purpose	NOUN
cana-4845	151	18	of	of	ADP
cana-4845	151	19	the	the	DET
cana-4845	151	20	current	current	ADJ
cana-4845	151	21	method	method	NOUN
cana-4845	151	22	is	be	AUX
cana-4845	151	23	to	to	PART
cana-4845	151	24	use	use	VERB
cana-4845	151	25	eeg	eeg	PROPN
cana-4845	151	26	and	and	CCONJ
cana-4845	151	27	ecg	ecg	PROPN
cana-4845	151	28	measures	measure	NOUN
cana-4845	151	29	to	to	PART
cana-4845	151	30	diagnose	diagnose	VERB
cana-4845	151	31	depression	depression	NOUN
cana-4845	151	32	.	.	PUNCT
cana-4845	152	1	the	the	DET
cana-4845	152	2	butterworth	butterworth	PROPN
cana-4845	152	3	filter	filter	NOUN
cana-4845	152	4	was	be	AUX
cana-4845	152	5	used	use	VERB
cana-4845	152	6	to	to	PART
cana-4845	152	7	preprocess	preprocess	VERB
cana-4845	152	8	the	the	DET
cana-4845	152	9	raw	raw	ADJ
cana-4845	152	10	eeg	eeg	NOUN
cana-4845	152	11	and	and	CCONJ
cana-4845	152	12	ecg	ecg	PROPN
cana-4845	152	13	signals	signal	NOUN
cana-4845	152	14	.	.	PUNCT
cana-4845	153	1	the	the	DET
cana-4845	153	2	st	st	PROPN
cana-4845	153	3	segment	segment	NOUN
cana-4845	153	4	,	,	PUNCT
cana-4845	153	5	p	p	NOUN
cana-4845	153	6	wave	wave	NOUN
cana-4845	153	7	,	,	PUNCT
cana-4845	153	8	and	and	CCONJ
cana-4845	153	9	qrs	qrs	PROPN
cana-4845	153	10	wave	wave	NOUN
cana-4845	153	11	of	of	ADP
cana-4845	153	12	the	the	DET
cana-4845	153	13	ecg	ecg	PROPN
cana-4845	153	14	signal	signal	NOUN
cana-4845	153	15	are	be	AUX
cana-4845	153	16	extracted	extract	VERB
cana-4845	153	17	independently	independently	ADV
cana-4845	153	18	,	,	PUNCT
cana-4845	153	19	as	as	SCONJ
cana-4845	153	20	are	be	AUX
cana-4845	153	21	the	the	DET
cana-4845	153	22	characteristics	characteristic	NOUN
cana-4845	153	23	from	from	ADP
cana-4845	153	24	the	the	DET
cana-4845	153	25	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-xiaohan-zang-aff1	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-xiaohan-zang-aff1	ADJ
cana-4845	153	26	communications	communication	NOUN
cana-4845	153	27	on	on	ADP
cana-4845	153	28	applied	apply	VERB
cana-4845	153	29	nonlinear	nonlinear	ADJ
cana-4845	153	30	analysis	analysis	NOUN
cana-4845	153	31	issn	issn	NOUN
cana-4845	153	32	:	:	PUNCT
cana-4845	153	33	1074	1074	NUM
cana-4845	153	34	-	-	PUNCT
cana-4845	153	35	133x	133x	NUM
cana-4845	153	36	vol	vol	VERB
cana-4845	153	37	32	32	NUM
cana-4845	153	38	no	no	NOUN
cana-4845	153	39	.	.	PUNCT
cana-4845	154	1	10s	10	NOUN
cana-4845	154	2	(	(	PUNCT
cana-4845	154	3	2025	2025	NUM
cana-4845	154	4	)	)	PUNCT
cana-4845	154	5	551	551	NUM
cana-4845	154	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	154	7	eeg	eeg	NOUN
cana-4845	154	8	's	's	PART
cana-4845	154	9	theta	theta	NOUN
cana-4845	154	10	,	,	PUNCT
cana-4845	154	11	delta	delta	NOUN
cana-4845	154	12	,	,	PUNCT
cana-4845	154	13	alpha	alpha	NOUN
cana-4845	154	14	,	,	PUNCT
cana-4845	154	15	and	and	CCONJ
cana-4845	154	16	beta	beta	ADJ
cana-4845	154	17	waves	wave	NOUN
cana-4845	154	18	.	.	PUNCT
cana-4845	155	1	the	the	DET
cana-4845	155	2	most	most	ADV
cana-4845	155	3	notable	notable	ADJ
cana-4845	155	4	features	feature	NOUN
cana-4845	155	5	are	be	AUX
cana-4845	155	6	forwarded	forward	VERB
cana-4845	155	7	for	for	ADP
cana-4845	155	8	additional	additional	ADJ
cana-4845	155	9	processing	processing	NOUN
cana-4845	155	10	in	in	ADP
cana-4845	155	11	order	order	NOUN
cana-4845	155	12	to	to	PART
cana-4845	155	13	analyze	analyze	VERB
cana-4845	155	14	depression	depression	NOUN
cana-4845	155	15	.	.	PUNCT
cana-4845	156	1	for	for	ADP
cana-4845	156	2	classification	classification	NOUN
cana-4845	156	3	,	,	PUNCT
cana-4845	156	4	the	the	DET
cana-4845	156	5	lstm	lstm	ADJ
cana-4845	156	6	auto	auto	NOUN
cana-4845	156	7	encoder	encoder	NOUN
cana-4845	156	8	with	with	ADP
cana-4845	156	9	rnn	rnn	PROPN
cana-4845	156	10	is	be	AUX
cana-4845	156	11	employed	employ	VERB
cana-4845	156	12	.	.	PUNCT
cana-4845	157	1	the	the	DET
cana-4845	157	2	eeg	eeg	PROPN
cana-4845	157	3	and	and	CCONJ
cana-4845	157	4	ecg	ecg	PROPN
cana-4845	157	5	readings	reading	NOUN
cana-4845	157	6	are	be	AUX
cana-4845	157	7	used	use	VERB
cana-4845	157	8	in	in	ADP
cana-4845	157	9	the	the	DET
cana-4845	157	10	methodical	methodical	ADJ
cana-4845	157	11	procedure	procedure	NOUN
cana-4845	157	12	of	of	ADP
cana-4845	157	13	connecting	connect	VERB
cana-4845	157	14	the	the	DET
cana-4845	157	15	depression	depression	NOUN
cana-4845	157	16	analysis	analysis	NOUN
cana-4845	157	17	technique	technique	NOUN
cana-4845	157	18	depicted	depict	VERB
cana-4845	157	19	in	in	ADP
cana-4845	157	20	figure	figure	NOUN
cana-4845	157	21	1	1	NUM
cana-4845	157	22	.	.	PUNCT
cana-4845	158	1	step	step	NOUN
cana-4845	158	2	1	1	NUM
cana-4845	158	3	:	:	PUNCT
cana-4845	158	4	database	database	VERB
cana-4845	158	5	the	the	DET
cana-4845	158	6	current	current	ADJ
cana-4845	158	7	system	system	NOUN
cana-4845	158	8	uses	use	VERB
cana-4845	158	9	204	204	NUM
cana-4845	158	10	eeg	eeg	NOUN
cana-4845	158	11	signals	signal	NOUN
cana-4845	158	12	in	in	ADP
cana-4845	158	13	"	"	PUNCT
cana-4845	158	14	.	.	PUNCT
cana-4845	159	1	edf	edf	ADJ
cana-4845	159	2	"	"	PUNCT
cana-4845	159	3	format	format	NOUN
cana-4845	159	4	from	from	ADP
cana-4845	159	5	the	the	DET
cana-4845	159	6	physionet	physionet	NOUN
cana-4845	159	7	database	database	NOUN
cana-4845	159	8	.	.	PUNCT
cana-4845	160	1	102	102	NUM
cana-4845	160	2	of	of	ADP
cana-4845	160	3	the	the	DET
cana-4845	160	4	204	204	NUM
cana-4845	160	5	eeg	eeg	NOUN
cana-4845	160	6	signals	signal	NOUN
cana-4845	160	7	are	be	AUX
cana-4845	160	8	from	from	ADP
cana-4845	160	9	healthy	healthy	ADJ
cana-4845	160	10	people	people	NOUN
cana-4845	160	11	,	,	PUNCT
cana-4845	160	12	and	and	CCONJ
cana-4845	160	13	the	the	DET
cana-4845	160	14	remaining	remain	VERB
cana-4845	160	15	102	102	NUM
cana-4845	160	16	are	be	AUX
cana-4845	160	17	from	from	ADP
cana-4845	160	18	patients	patient	NOUN
cana-4845	160	19	who	who	PRON
cana-4845	160	20	are	be	AUX
cana-4845	160	21	sad	sad	ADJ
cana-4845	160	22	.	.	PUNCT
cana-4845	161	1	these	these	DET
cana-4845	161	2	102	102	NUM
cana-4845	161	3	examples	example	NOUN
cana-4845	161	4	include	include	VERB
cana-4845	161	5	34	34	NUM
cana-4845	161	6	with	with	SCONJ
cana-4845	161	7	their	their	PRON
cana-4845	161	8	eyes	eye	NOUN
cana-4845	161	9	open	open	ADJ
cana-4845	161	10	,	,	PUNCT
cana-4845	161	11	34	34	NUM
cana-4845	161	12	with	with	SCONJ
cana-4845	161	13	their	their	PRON
cana-4845	161	14	eyes	eye	NOUN
cana-4845	161	15	closed	close	VERB
cana-4845	161	16	,	,	PUNCT
cana-4845	161	17	and	and	CCONJ
cana-4845	161	18	34	34	NUM
cana-4845	161	19	while	while	SCONJ
cana-4845	161	20	performing	perform	VERB
cana-4845	161	21	a	a	DET
cana-4845	161	22	task	task	NOUN
cana-4845	161	23	.	.	PUNCT
cana-4845	162	1	the	the	DET
cana-4845	162	2	"	"	PUNCT
cana-4845	162	3	.mat	.mat	NOUN
cana-4845	162	4	"	"	PUNCT
cana-4845	162	5	formats	format	NOUN
cana-4845	162	6	of	of	ADP
cana-4845	162	7	the	the	DET
cana-4845	162	8	ecg	ecg	PROPN
cana-4845	162	9	datasets	dataset	NOUN
cana-4845	162	10	.	.	PUNCT
cana-4845	163	1	in	in	ADP
cana-4845	163	2	the	the	DET
cana-4845	163	3	current	current	ADJ
cana-4845	163	4	investigation	investigation	NOUN
cana-4845	163	5	,	,	PUNCT
cana-4845	163	6	8500	8500	NUM
cana-4845	163	7	ecg	ecg	PROPN
cana-4845	163	8	signals	signal	NOUN
cana-4845	163	9	in	in	ADP
cana-4845	163	10	total	total	NOUN
cana-4845	163	11	are	be	AUX
cana-4845	163	12	employed	employ	VERB
cana-4845	163	13	.	.	PUNCT
cana-4845	164	1	of	of	ADP
cana-4845	164	2	those	those	PRON
cana-4845	164	3	,	,	PUNCT
cana-4845	164	4	700	700	NUM
cana-4845	164	5	are	be	AUX
cana-4845	164	6	from	from	ADP
cana-4845	164	7	people	people	NOUN
cana-4845	164	8	who	who	PRON
cana-4845	164	9	are	be	AUX
cana-4845	164	10	depressed	depressed	ADJ
cana-4845	164	11	,	,	PUNCT
cana-4845	164	12	5050	5050	NUM
cana-4845	164	13	are	be	AUX
cana-4845	164	14	from	from	ADP
cana-4845	164	15	people	people	NOUN
cana-4845	164	16	who	who	PRON
cana-4845	164	17	are	be	AUX
cana-4845	164	18	normal	normal	ADJ
cana-4845	164	19	,	,	PUNCT
cana-4845	164	20	and	and	CCONJ
cana-4845	164	21	the	the	DET
cana-4845	164	22	remaining	remain	VERB
cana-4845	164	23	signals	signal	NOUN
cana-4845	164	24	are	be	AUX
cana-4845	164	25	from	from	ADP
cana-4845	164	26	various	various	ADJ
cana-4845	164	27	illnesses	illness	NOUN
cana-4845	164	28	.	.	PUNCT
cana-4845	165	1	step	step	NOUN
cana-4845	165	2	2	2	NUM
cana-4845	165	3	:	:	PUNCT
cana-4845	165	4	preparation	preparation	NOUN
cana-4845	165	5	eeg	eeg	PROPN
cana-4845	165	6	is	be	AUX
cana-4845	165	7	a	a	DET
cana-4845	165	8	painless	painless	ADJ
cana-4845	165	9	way	way	NOUN
cana-4845	165	10	to	to	PART
cana-4845	165	11	detect	detect	VERB
cana-4845	165	12	the	the	DET
cana-4845	165	13	physiological	physiological	ADJ
cana-4845	165	14	indication	indication	NOUN
cana-4845	165	15	of	of	ADP
cana-4845	165	16	a	a	DET
cana-4845	165	17	brain	brain	NOUN
cana-4845	165	18	movement	movement	NOUN
cana-4845	165	19	wave	wave	NOUN
cana-4845	165	20	.	.	PUNCT
cana-4845	166	1	every	every	DET
cana-4845	166	2	recorded	record	VERB
cana-4845	166	3	eeg	eeg	PROPN
cana-4845	166	4	signal	signal	NOUN
cana-4845	166	5	contains	contain	VERB
cana-4845	166	6	noise	noise	NOUN
cana-4845	166	7	,	,	PUNCT
cana-4845	166	8	or	or	CCONJ
cana-4845	166	9	artifacts	artifact	NOUN
cana-4845	166	10	,	,	PUNCT
cana-4845	166	11	which	which	PRON
cana-4845	166	12	can	can	AUX
cana-4845	166	13	occasionally	occasionally	ADV
cana-4845	166	14	make	make	VERB
cana-4845	166	15	it	it	PRON
cana-4845	166	16	difficult	difficult	ADJ
cana-4845	166	17	to	to	PART
cana-4845	166	18	make	make	VERB
cana-4845	166	19	a	a	DET
cana-4845	166	20	precise	precise	ADJ
cana-4845	166	21	diagnosis	diagnosis	NOUN
cana-4845	166	22	.	.	PUNCT
cana-4845	167	1	to	to	PART
cana-4845	167	2	separate	separate	VERB
cana-4845	167	3	noise	noise	NOUN
cana-4845	167	4	from	from	ADP
cana-4845	167	5	the	the	DET
cana-4845	167	6	raw	raw	ADJ
cana-4845	167	7	eeg	eeg	PROPN
cana-4845	167	8	data	datum	NOUN
cana-4845	167	9	,	,	PUNCT
cana-4845	167	10	the	the	DET
cana-4845	167	11	mspca	mspca	NOUN
cana-4845	167	12	technique	technique	NOUN
cana-4845	167	13	is	be	AUX
cana-4845	167	14	first	first	ADV
cana-4845	167	15	used	use	VERB
cana-4845	167	16	.	.	PUNCT
cana-4845	168	1	multi	multi	ADJ
cana-4845	168	2	-	-	ADJ
cana-4845	168	3	scale	scale	ADJ
cana-4845	168	4	principal	principal	ADJ
cana-4845	168	5	component	component	NOUN
cana-4845	168	6	analysis	analysis	NOUN
cana-4845	168	7	(	(	PUNCT
cana-4845	168	8	mspca	mspca	INTJ
cana-4845	168	9	)	)	PUNCT
cana-4845	168	10	is	be	AUX
cana-4845	168	11	a	a	DET
cana-4845	168	12	hybrid	hybrid	ADJ
cana-4845	168	13	signal	signal	NOUN
cana-4845	168	14	denoising	denoising	NOUN
cana-4845	168	15	approach	approach	NOUN
cana-4845	168	16	that	that	PRON
cana-4845	168	17	combines	combine	VERB
cana-4845	168	18	the	the	DET
cana-4845	168	19	advantages	advantage	NOUN
cana-4845	168	20	of	of	ADP
cana-4845	168	21	pca	pca	PROPN
cana-4845	168	22	with	with	ADP
cana-4845	168	23	wavelet	wavelet	NOUN
cana-4845	168	24	transform	transform	NOUN
cana-4845	168	25	.	.	PUNCT
cana-4845	169	1	figure	figure	NOUN
cana-4845	169	2	1	1	NUM
cana-4845	169	3	:	:	PUNCT
cana-4845	169	4	eeg	eeg	PROPN
cana-4845	169	5	and	and	CCONJ
cana-4845	169	6	ecg	ecg	PROPN
cana-4845	169	7	signals	signal	NOUN
cana-4845	169	8	are	be	AUX
cana-4845	169	9	used	use	VERB
cana-4845	169	10	to	to	PART
cana-4845	169	11	diagnose	diagnose	VERB
cana-4845	169	12	depression	depression	NOUN
cana-4845	169	13	.	.	PUNCT
cana-4845	170	1	the	the	DET
cana-4845	170	2	butterworth	butterworth	PROPN
cana-4845	170	3	filter	filter	NOUN
cana-4845	170	4	is	be	AUX
cana-4845	170	5	used	use	VERB
cana-4845	170	6	to	to	PART
cana-4845	170	7	eliminate	eliminate	VERB
cana-4845	170	8	ecg	ecg	PROPN
cana-4845	170	9	signal	signal	NOUN
cana-4845	170	10	artifacts	artifact	NOUN
cana-4845	170	11	.	.	PUNCT
cana-4845	171	1	|𝐻(𝑗𝜔)|	|𝐻(𝑗𝜔)|	X
cana-4845	171	2	=	=	NOUN
cana-4845	171	3	1	1	NUM
cana-4845	171	4	√1	√1	PROPN
cana-4845	171	5	+	+	CCONJ
cana-4845	171	6	(	(	PUNCT
cana-4845	171	7	𝜔	𝜔	PART
cana-4845	171	8	𝜔𝑐	𝜔𝑐	NOUN
cana-4845	171	9	)	)	PUNCT
cana-4845	171	10	2𝑁	2𝑁	NOUN
cana-4845	171	11	(	(	PUNCT
cana-4845	171	12	1	1	NUM
cana-4845	171	13	)	)	PUNCT
cana-4845	171	14	step	step	NOUN
cana-4845	171	15	3	3	NUM
cana-4845	171	16	:	:	PUNCT
cana-4845	171	17	extraction	extraction	NOUN
cana-4845	171	18	of	of	ADP
cana-4845	171	19	features	feature	NOUN
cana-4845	171	20	both	both	CCONJ
cana-4845	171	21	with	with	ADP
cana-4845	171	22	and	and	CCONJ
cana-4845	171	23	without	without	ADP
cana-4845	171	24	the	the	DET
cana-4845	171	25	eyes	eye	NOUN
cana-4845	171	26	,	,	PUNCT
cana-4845	171	27	signals	signal	NOUN
cana-4845	171	28	from	from	ADP
cana-4845	171	29	the	the	DET
cana-4845	171	30	left	left	ADJ
cana-4845	171	31	and	and	CCONJ
cana-4845	171	32	right	right	ADJ
cana-4845	171	33	sides	side	NOUN
cana-4845	171	34	of	of	ADP
cana-4845	171	35	the	the	DET
cana-4845	171	36	brain	brain	NOUN
cana-4845	171	37	are	be	AUX
cana-4845	171	38	recorded	record	VERB
cana-4845	171	39	.	.	PUNCT
cana-4845	172	1	ecg	ecg	PROPN
cana-4845	172	2	signals	signal	VERB
cana-4845	172	3	eeg	eeg	PROPN
cana-4845	172	4	signals	signal	NOUN
cana-4845	172	5	butterworth	butterworth	PROPN
cana-4845	172	6	filter	filter	NOUN
cana-4845	172	7	mspca	mspca	PROPN
cana-4845	172	8	wavelet	wavelet	PROPN
cana-4845	172	9	transform	transform	VERB
cana-4845	172	10	fast	fast	ADJ
cana-4845	172	11	fourier	fourier	NOUN
cana-4845	172	12	transform	transform	VERB
cana-4845	172	13	spectral	spectral	ADJ
cana-4845	172	14	entropy	entropy	NOUN
cana-4845	172	15	and	and	CCONJ
cana-4845	172	16	instantaneous	instantaneous	ADJ
cana-4845	172	17	frequency	frequency	NOUN
cana-4845	172	18	hjorth	hjorth	NOUN
cana-4845	172	19	parameters	parameter	NOUN
cana-4845	172	20	normal	normal	ADJ
cana-4845	172	21	person	person	NOUN
cana-4845	172	22	depress	depress	NOUN
cana-4845	172	23	-	-	PUNCT
cana-4845	172	24	ed	ed	NOUN
cana-4845	172	25	person	person	NOUN
cana-4845	172	26	svm	svm	NOUN
cana-4845	172	27	,	,	PUNCT
cana-4845	172	28	cnn	cnn	PROPN
cana-4845	172	29	,	,	PUNCT
cana-4845	172	30	rnn	rnn	PROPN
cana-4845	172	31	and	and	CCONJ
cana-4845	172	32	lstm	lstm	NOUN
cana-4845	172	33	encoder	encoder	NOUN
cana-4845	172	34	communications	communication	NOUN
cana-4845	172	35	on	on	ADP
cana-4845	172	36	applied	apply	VERB
cana-4845	172	37	nonlinear	nonlinear	ADJ
cana-4845	172	38	analysis	analysis	NOUN
cana-4845	172	39	issn	issn	NOUN
cana-4845	172	40	:	:	PUNCT
cana-4845	172	41	1074	1074	NUM
cana-4845	172	42	-	-	PUNCT
cana-4845	172	43	133x	133x	NUM
cana-4845	172	44	vol	vol	VERB
cana-4845	172	45	32	32	NUM
cana-4845	172	46	no	no	NOUN
cana-4845	172	47	.	.	PUNCT
cana-4845	173	1	10s	10	NOUN
cana-4845	173	2	(	(	PUNCT
cana-4845	173	3	2025	2025	NUM
cana-4845	173	4	)	)	PUNCT
cana-4845	173	5	552	552	NUM
cana-4845	173	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	173	7	average	average	ADJ
cana-4845	173	8	statistical	statistical	ADJ
cana-4845	173	9	features	feature	NOUN
cana-4845	173	10	are	be	AUX
cana-4845	173	11	extracted	extract	VERB
cana-4845	173	12	from	from	ADP
cana-4845	173	13	the	the	DET
cana-4845	173	14	30	30	NUM
cana-4845	173	15	time	time	NOUN
cana-4845	173	16	-	-	PUNCT
cana-4845	173	17	domain	domain	NOUN
cana-4845	173	18	-	-	PUNCT
cana-4845	173	19	analyzed	analyze	VERB
cana-4845	173	20	eeg	eeg	NOUN
cana-4845	173	21	signal	signal	NOUN
cana-4845	173	22	recordings	recording	NOUN
cana-4845	173	23	.	.	PUNCT
cana-4845	174	1	the	the	DET
cana-4845	174	2	sample	sample	NOUN
cana-4845	174	3	mean	mean	VERB
cana-4845	174	4	values	value	NOUN
cana-4845	174	5	of	of	ADP
cana-4845	174	6	the	the	DET
cana-4845	174	7	eeg	eeg	PROPN
cana-4845	174	8	signal	signal	NOUN
cana-4845	174	9	are	be	AUX
cana-4845	174	10	obtained	obtain	VERB
cana-4845	174	11	by	by	ADP
cana-4845	174	12	moving	move	VERB
cana-4845	174	13	window	window	NOUN
cana-4845	174	14	segmentation	segmentation	NOUN
cana-4845	174	15	.	.	PUNCT
cana-4845	175	1	the	the	DET
cana-4845	175	2	following	follow	VERB
cana-4845	175	3	features	feature	NOUN
cana-4845	175	4	are	be	AUX
cana-4845	175	5	used	use	VERB
cana-4845	175	6	to	to	PART
cana-4845	175	7	analyze	analyze	VERB
cana-4845	175	8	eeg	eeg	PROPN
cana-4845	175	9	data	datum	NOUN
cana-4845	175	10	:	:	PUNCT
cana-4845	175	11	a	a	X
cana-4845	175	12	)	)	PUNCT
cana-4845	175	13	linear	linear	ADJ
cana-4845	175	14	features	feature	NOUN
cana-4845	175	15	:	:	PUNCT
cana-4845	175	16	band	band	NOUN
cana-4845	175	17	power	power	NOUN
cana-4845	175	18	,	,	PUNCT
cana-4845	175	19	dft	dft	PROPN
cana-4845	175	20	,	,	PUNCT
cana-4845	175	21	and	and	CCONJ
cana-4845	175	22	fft	fft	PROPN
cana-4845	175	23	b	b	NOUN
cana-4845	175	24	)	)	PUNCT
cana-4845	175	25	features	feature	NOUN
cana-4845	175	26	that	that	PRON
cana-4845	175	27	is	be	AUX
cana-4845	175	28	not	not	PART
cana-4845	175	29	linear	linear	ADJ
cana-4845	175	30	:	:	PUNCT
cana-4845	175	31	discrete	discrete	ADJ
cana-4845	175	32	wavelet	wavelet	NOUN
cana-4845	175	33	transform	transform	NOUN
cana-4845	175	34	c	c	NOUN
cana-4845	175	35	)	)	PUNCT
cana-4845	175	36	statistical	statistical	ADJ
cana-4845	175	37	characteristics	characteristic	NOUN
cana-4845	175	38	:	:	PUNCT
cana-4845	175	39	hjorth	hjorth	NOUN
cana-4845	175	40	parameters	parameter	NOUN
cana-4845	175	41	,	,	PUNCT
cana-4845	175	42	skewness	skewness	NOUN
cana-4845	175	43	and	and	CCONJ
cana-4845	175	44	kurtosis	kurtosis	NOUN
cana-4845	175	45	,	,	PUNCT
cana-4845	175	46	variance	variance	NOUN
cana-4845	175	47	,	,	PUNCT
cana-4845	175	48	standard	standard	ADJ
cana-4845	175	49	deviation	deviation	NOUN
cana-4845	175	50	,	,	PUNCT
cana-4845	175	51	mean	mean	VERB
cana-4845	175	52	,	,	PUNCT
cana-4845	175	53	and	and	CCONJ
cana-4845	175	54	median	median	ADJ
cana-4845	175	55	.	.	PUNCT
cana-4845	176	1	activity	activity	NOUN
cana-4845	176	2	,	,	PUNCT
cana-4845	176	3	mobility	mobility	NOUN
cana-4845	176	4	,	,	PUNCT
cana-4845	176	5	and	and	CCONJ
cana-4845	176	6	complexity	complexity	NOUN
cana-4845	176	7	are	be	AUX
cana-4845	176	8	the	the	DET
cana-4845	176	9	parameters	parameter	NOUN
cana-4845	176	10	.	.	PUNCT
cana-4845	177	1	and	and	CCONJ
cana-4845	177	2	band	band	NOUN
cana-4845	177	3	power	power	NOUN
cana-4845	177	4	alpha	alpha	NOUN
cana-4845	177	5	are	be	AUX
cana-4845	177	6	frequently	frequently	ADV
cana-4845	177	7	employed	employ	VERB
cana-4845	177	8	in	in	ADP
cana-4845	177	9	the	the	DET
cana-4845	177	10	feature	feature	NOUN
cana-4845	177	11	selection	selection	NOUN
cana-4845	177	12	process	process	NOUN
cana-4845	177	13	of	of	ADP
cana-4845	177	14	eeg	eeg	PROPN
cana-4845	177	15	data	datum	NOUN
cana-4845	177	16	processing	processing	NOUN
cana-4845	177	17	.	.	PUNCT
cana-4845	178	1	where	where	SCONJ
cana-4845	178	2	the	the	DET
cana-4845	178	3	signal	signal	NOUN
cana-4845	178	4	is	be	AUX
cana-4845	178	5	denoted	denote	VERB
cana-4845	178	6	by	by	ADP
cana-4845	178	7	y(t	y(t	PROPN
cana-4845	178	8	)	)	PUNCT
cana-4845	178	9	.	.	PUNCT
cana-4845	179	1	activity	activity	NOUN
cana-4845	179	2	in	in	ADP
cana-4845	179	3	hjorth	hjorth	NOUN
cana-4845	179	4	the	the	DET
cana-4845	179	5	signal	signal	NOUN
cana-4845	179	6	power	power	NOUN
cana-4845	179	7	,	,	PUNCT
cana-4845	179	8	or	or	CCONJ
cana-4845	179	9	variance	variance	NOUN
cana-4845	179	10	of	of	ADP
cana-4845	179	11	a	a	DET
cana-4845	179	12	time	time	NOUN
cana-4845	179	13	function	function	NOUN
cana-4845	179	14	,	,	PUNCT
cana-4845	179	15	is	be	AUX
cana-4845	179	16	represented	represent	VERB
cana-4845	179	17	by	by	ADP
cana-4845	179	18	the	the	DET
cana-4845	179	19	activity	activity	NOUN
cana-4845	179	20	parameter	parameter	NOUN
cana-4845	179	21	.	.	PUNCT
cana-4845	180	1	this	this	PRON
cana-4845	180	2	can	can	AUX
cana-4845	180	3	show	show	VERB
cana-4845	180	4	the	the	DET
cana-4845	180	5	frequency	frequency	NOUN
cana-4845	180	6	domain	domain	NOUN
cana-4845	180	7	power	power	NOUN
cana-4845	180	8	spectrum	spectrum	NOUN
cana-4845	180	9	surface	surface	NOUN
cana-4845	180	10	.	.	PUNCT
cana-4845	181	1	the	the	DET
cana-4845	181	2	following	follow	VERB
cana-4845	181	3	equation	equation	NOUN
cana-4845	181	4	serves	serve	VERB
cana-4845	181	5	as	as	ADP
cana-4845	181	6	a	a	DET
cana-4845	181	7	representation	representation	NOUN
cana-4845	181	8	of	of	ADP
cana-4845	181	9	this	this	PRON
cana-4845	181	10	:	:	PUNCT
cana-4845	181	11	𝐴𝑐𝑡𝑖𝑣𝑖𝑡𝑦	𝐴𝑐𝑡𝑖𝑣𝑖𝑡𝑦	PROPN
cana-4845	181	12	=	=	SYM
cana-4845	181	13	𝑣𝑎𝑟(𝑦(𝑡	𝑣𝑎𝑟(𝑦(𝑡	NOUN
cana-4845	181	14	)	)	PUNCT
cana-4845	181	15	)	)	PUNCT
cana-4845	182	1	(	(	PUNCT
cana-4845	182	2	2	2	X
cana-4845	182	3	)	)	PUNCT
cana-4845	182	4	mobility	mobility	NOUN
cana-4845	182	5	of	of	ADP
cana-4845	182	6	hjorth	hjorth	NOUN
cana-4845	182	7	the	the	DET
cana-4845	182	8	power	power	NOUN
cana-4845	182	9	spectrums	spectrum	NOUN
cana-4845	182	10	mean	mean	VERB
cana-4845	182	11	frequency	frequency	NOUN
cana-4845	182	12	or	or	CCONJ
cana-4845	182	13	percentage	percentage	NOUN
cana-4845	182	14	of	of	ADP
cana-4845	182	15	standard	standard	ADJ
cana-4845	182	16	deviation	deviation	NOUN
cana-4845	182	17	is	be	AUX
cana-4845	182	18	represented	represent	VERB
cana-4845	182	19	by	by	ADP
cana-4845	182	20	the	the	DET
cana-4845	182	21	mobility	mobility	NOUN
cana-4845	182	22	parameter	parameter	NOUN
cana-4845	182	23	.	.	PUNCT
cana-4845	183	1	𝑀𝑜𝑏𝑖𝑙𝑖𝑡𝑦	𝑀𝑜𝑏𝑖𝑙𝑖𝑡𝑦	PROPN
cana-4845	183	2	=	=	PUNCT
cana-4845	183	3	√	√	PROPN
cana-4845	183	4	𝑣𝑎𝑟	𝑣𝑎𝑟	NOUN
cana-4845	183	5	(	(	PUNCT
cana-4845	183	6	𝑑𝑦(𝑡	𝑑𝑦(𝑡	NUM
cana-4845	183	7	)	)	PUNCT
cana-4845	183	8	𝑑𝑡	𝑑𝑡	ADP
cana-4845	183	9	)	)	PUNCT
cana-4845	183	10	𝑣𝑎𝑟(𝑦(𝑡	𝑣𝑎𝑟(𝑦(𝑡	NOUN
cana-4845	183	11	)	)	PUNCT
cana-4845	183	12	)	)	PUNCT
cana-4845	184	1	(	(	PUNCT
cana-4845	184	2	3	3	X
cana-4845	184	3	)	)	PUNCT
cana-4845	184	4	complexity	complexity	NOUN
cana-4845	184	5	of	of	ADP
cana-4845	184	6	hjorth	hjorth	NOUN
cana-4845	184	7	the	the	DET
cana-4845	184	8	frequency	frequency	NOUN
cana-4845	184	9	change	change	NOUN
cana-4845	184	10	is	be	AUX
cana-4845	184	11	represented	represent	VERB
cana-4845	184	12	by	by	ADP
cana-4845	184	13	the	the	DET
cana-4845	184	14	complexity	complexity	NOUN
cana-4845	184	15	parameter	parameter	NOUN
cana-4845	184	16	.	.	PUNCT
cana-4845	185	1	the	the	DET
cana-4845	185	2	parameter	parameter	NOUN
cana-4845	185	3	evaluates	evaluate	VERB
cana-4845	185	4	how	how	SCONJ
cana-4845	185	5	similar	similar	ADJ
cana-4845	185	6	the	the	DET
cana-4845	185	7	signal	signal	NOUN
cana-4845	185	8	is	be	AUX
cana-4845	185	9	to	to	ADP
cana-4845	185	10	a	a	DET
cana-4845	185	11	pure	pure	ADJ
cana-4845	185	12	sine	sine	ADJ
cana-4845	185	13	wave	wave	NOUN
cana-4845	185	14	;	;	PUNCT
cana-4845	185	15	if	if	SCONJ
cana-4845	185	16	the	the	DET
cana-4845	185	17	signal	signal	NOUN
cana-4845	185	18	is	be	AUX
cana-4845	185	19	more	more	ADV
cana-4845	185	20	similar	similar	ADJ
cana-4845	185	21	,	,	PUNCT
cana-4845	185	22	the	the	DET
cana-4845	185	23	value	value	NOUN
cana-4845	185	24	converges	converge	VERB
cana-4845	185	25	to	to	ADP
cana-4845	185	26	1	1	NUM
cana-4845	185	27	.	.	PUNCT
cana-4845	186	1	𝐶𝑜𝑚𝑝𝑙𝑒𝑥𝑖𝑡𝑦	𝐶𝑜𝑚𝑝𝑙𝑒𝑥𝑖𝑡𝑦	PROPN
cana-4845	186	2	=	=	SYM
cana-4845	186	3	𝑀𝑜𝑏𝑖𝑙𝑖𝑡𝑦	𝑀𝑜𝑏𝑖𝑙𝑖𝑡𝑦	PROPN
cana-4845	186	4	(	(	PUNCT
cana-4845	186	5	𝑑𝑦(𝑡	𝑑𝑦(𝑡	NUM
cana-4845	186	6	)	)	PUNCT
cana-4845	186	7	𝑑𝑡	𝑑𝑡	ADP
cana-4845	186	8	)	)	PUNCT
cana-4845	186	9	𝑀𝑜𝑏𝑖𝑙𝑖𝑡𝑦(𝑦(𝑡	𝑀𝑜𝑏𝑖𝑙𝑖𝑡𝑦(𝑦(𝑡	PROPN
cana-4845	186	10	)	)	PUNCT
cana-4845	186	11	)	)	PUNCT
cana-4845	186	12	(	(	PUNCT
cana-4845	186	13	4	4	X
cana-4845	186	14	)	)	PUNCT
cana-4845	186	15	the	the	DET
cana-4845	186	16	ecg	ecg	PROPN
cana-4845	186	17	signal	signal	NOUN
cana-4845	186	18	is	be	AUX
cana-4845	186	19	composed	compose	VERB
cana-4845	186	20	of	of	ADP
cana-4845	186	21	the	the	DET
cana-4845	186	22	p	p	PROPN
cana-4845	186	23	-	-	PUNCT
cana-4845	186	24	qrs	qrs	NOUN
cana-4845	186	25	-	-	PUNCT
cana-4845	186	26	t	t	NOUN
cana-4845	186	27	waves	wave	NOUN
cana-4845	186	28	in	in	ADP
cana-4845	186	29	a	a	DET
cana-4845	186	30	single	single	ADJ
cana-4845	186	31	cardiac	cardiac	ADJ
cana-4845	186	32	cycle	cycle	NOUN
cana-4845	186	33	.	.	PUNCT
cana-4845	187	1	we	we	PRON
cana-4845	187	2	can	can	AUX
cana-4845	187	3	extract	extract	VERB
cana-4845	187	4	the	the	DET
cana-4845	187	5	properties	property	NOUN
cana-4845	187	6	of	of	ADP
cana-4845	187	7	the	the	DET
cana-4845	187	8	ecg	ecg	PROPN
cana-4845	187	9	signal	signal	NOUN
cana-4845	187	10	using	use	VERB
cana-4845	187	11	the	the	DET
cana-4845	187	12	wavelet	wavelet	NOUN
cana-4845	187	13	transform	transform	NOUN
cana-4845	187	14	.	.	PUNCT
cana-4845	188	1	the	the	DET
cana-4845	188	2	amplitudes	amplitude	NOUN
cana-4845	188	3	and	and	CCONJ
cana-4845	188	4	intervals	interval	NOUN
cana-4845	188	5	define	define	VERB
cana-4845	188	6	the	the	DET
cana-4845	188	7	communications	communication	NOUN
cana-4845	188	8	on	on	ADP
cana-4845	188	9	applied	apply	VERB
cana-4845	188	10	nonlinear	nonlinear	ADJ
cana-4845	188	11	analysis	analysis	NOUN
cana-4845	188	12	issn	issn	NOUN
cana-4845	188	13	:	:	PUNCT
cana-4845	188	14	1074	1074	NUM
cana-4845	188	15	-	-	PUNCT
cana-4845	188	16	133x	133x	NUM
cana-4845	188	17	vol	vol	VERB
cana-4845	188	18	32	32	NUM
cana-4845	188	19	no	no	NOUN
cana-4845	188	20	.	.	PUNCT
cana-4845	189	1	10s	10	NOUN
cana-4845	189	2	(	(	PUNCT
cana-4845	189	3	2025	2025	NUM
cana-4845	189	4	)	)	PUNCT
cana-4845	189	5	553	553	NUM
cana-4845	189	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	189	7	characteristics	characteristic	NOUN
cana-4845	189	8	of	of	ADP
cana-4845	189	9	the	the	DET
cana-4845	189	10	ecg	ecg	PROPN
cana-4845	189	11	signal	signal	NOUN
cana-4845	189	12	.	.	PUNCT
cana-4845	190	1	the	the	DET
cana-4845	190	2	depression	depression	NOUN
cana-4845	190	3	is	be	AUX
cana-4845	190	4	visible	visible	ADJ
cana-4845	190	5	in	in	ADP
cana-4845	190	6	the	the	DET
cana-4845	190	7	st	st	PROPN
cana-4845	190	8	segments	segment	NOUN
cana-4845	190	9	of	of	ADP
cana-4845	190	10	the	the	DET
cana-4845	190	11	ecg	ecg	PROPN
cana-4845	190	12	signal	signal	NOUN
cana-4845	190	13	.	.	PUNCT
cana-4845	191	1	the	the	DET
cana-4845	191	2	main	main	ADJ
cana-4845	191	3	difference	difference	NOUN
cana-4845	191	4	between	between	ADP
cana-4845	191	5	a	a	DET
cana-4845	191	6	normal	normal	ADJ
cana-4845	191	7	and	and	CCONJ
cana-4845	191	8	depressed	depressed	ADJ
cana-4845	191	9	person	person	NOUN
cana-4845	191	10	is	be	AUX
cana-4845	191	11	the	the	DET
cana-4845	191	12	st	st	PROPN
cana-4845	191	13	segment	segment	NOUN
cana-4845	191	14	in	in	ADP
cana-4845	191	15	figure	figure	NOUN
cana-4845	191	16	2	2	NUM
cana-4845	191	17	.	.	X
cana-4845	191	18	figure	figure	NOUN
cana-4845	191	19	:	:	PUNCT
cana-4845	191	20	2	2	NUM
cana-4845	191	21	ecg	ecg	PROPN
cana-4845	191	22	signal	signal	NOUN
cana-4845	191	23	,	,	PUNCT
cana-4845	191	24	a	a	PRON
cana-4845	191	25	)	)	PUNCT
cana-4845	191	26	normal	normal	ADJ
cana-4845	191	27	b	b	NOUN
cana-4845	191	28	)	)	PUNCT
cana-4845	191	29	depressed	depressed	ADJ
cana-4845	191	30	features	feature	NOUN
cana-4845	191	31	such	such	ADJ
cana-4845	191	32	as	as	ADP
cana-4845	191	33	spectrum	spectrum	NOUN
cana-4845	191	34	entropy	entropy	NOUN
cana-4845	191	35	,	,	PUNCT
cana-4845	191	36	instantaneous	instantaneous	ADJ
cana-4845	191	37	frequency	frequency	NOUN
cana-4845	191	38	,	,	PUNCT
cana-4845	191	39	and	and	CCONJ
cana-4845	191	40	its	its	PRON
cana-4845	191	41	arithmetic	arithmetic	ADJ
cana-4845	191	42	mean	mean	NOUN
cana-4845	191	43	were	be	AUX
cana-4845	191	44	chosen	choose	VERB
cana-4845	191	45	for	for	ADP
cana-4845	191	46	ecg	ecg	PROPN
cana-4845	191	47	signals	signal	NOUN
cana-4845	191	48	.	.	PUNCT
cana-4845	192	1	given	give	VERB
cana-4845	192	2	a	a	DET
cana-4845	192	3	time	time	NOUN
cana-4845	192	4	-	-	PUNCT
cana-4845	192	5	frequency	frequency	NOUN
cana-4845	192	6	power	power	NOUN
cana-4845	192	7	spectrogram	spectrogram	NOUN
cana-4845	192	8	s(t	s(t	PROPN
cana-4845	192	9	,	,	PUNCT
cana-4845	192	10	f	f	PROPN
cana-4845	192	11	)	)	PUNCT
cana-4845	192	12	,	,	PUNCT
cana-4845	192	13	the	the	DET
cana-4845	192	14	probability	probability	NOUN
cana-4845	192	15	distribution	distribution	NOUN
cana-4845	192	16	at	at	ADP
cana-4845	192	17	time	time	NOUN
cana-4845	192	18	t	t	PROPN
cana-4845	192	19	can	can	AUX
cana-4845	192	20	be	be	AUX
cana-4845	192	21	used	use	VERB
cana-4845	192	22	to	to	PART
cana-4845	192	23	calculate	calculate	VERB
cana-4845	192	24	the	the	DET
cana-4845	192	25	instantaneous	instantaneous	ADJ
cana-4845	192	26	spectral	spectral	ADJ
cana-4845	192	27	entropy	entropy	NOUN
cana-4845	192	28	.	.	PUNCT
cana-4845	193	1	𝑃(𝑡	𝑃(𝑡	PROPN
cana-4845	193	2	,	,	PUNCT
cana-4845	193	3	𝑚	𝑚	NOUN
cana-4845	193	4	)	)	PUNCT
cana-4845	193	5	𝑆(𝑡	𝑆(𝑡	NUM
cana-4845	193	6	,	,	PUNCT
cana-4845	193	7	𝑚	𝑚	NOUN
cana-4845	193	8	)	)	PUNCT
cana-4845	193	9	∑	∑	PUNCT
cana-4845	193	10	𝑆(𝑡	𝑆(𝑡	VERB
cana-4845	193	11	,	,	PUNCT
cana-4845	193	12	𝑓)𝑓	𝑓)𝑓	NOUN
cana-4845	193	13	(	(	PUNCT
cana-4845	193	14	5	5	NUM
cana-4845	193	15	)	)	PUNCT
cana-4845	193	16	at	at	ADP
cana-4845	193	17	time	time	NOUN
cana-4845	193	18	t	t	PROPN
cana-4845	193	19	,	,	PUNCT
cana-4845	193	20	the	the	DET
cana-4845	193	21	spectral	spectral	ADJ
cana-4845	193	22	entropy	entropy	NOUN
cana-4845	193	23	is	be	AUX
cana-4845	193	24	then	then	ADV
cana-4845	193	25	:	:	PUNCT
cana-4845	193	26	𝐻(𝑡	𝐻(𝑡	X
cana-4845	193	27	)	)	PUNCT
cana-4845	193	28	=	=	SYM
cana-4845	193	29	−	−	PROPN
cana-4845	193	30	∑	∑	PUNCT
cana-4845	193	31	𝑃(𝑡	𝑃(𝑡	PROPN
cana-4845	193	32	,	,	PUNCT
cana-4845	193	33	𝑚)𝑙𝑜𝑔2	𝑚)𝑙𝑜𝑔2	PROPN
cana-4845	193	34	𝑃(𝑡	𝑃(𝑡	PROPN
cana-4845	193	35	,	,	PUNCT
cana-4845	193	36	𝑚	𝑚	NOUN
cana-4845	193	37	)	)	PUNCT
cana-4845	193	38	(	(	PUNCT
cana-4845	193	39	6	6	X
cana-4845	193	40	)	)	PUNCT
cana-4845	193	41	𝑁	𝑁	ADJ
cana-4845	193	42	𝑚=1	𝑚=1	NOUN
cana-4845	193	43	step	step	NOUN
cana-4845	193	44	4	4	NUM
cana-4845	193	45	:	:	PUNCT
cana-4845	193	46	categorization	categorization	VERB
cana-4845	193	47	the	the	DET
cana-4845	193	48	order	order	NOUN
cana-4845	193	49	is	be	AUX
cana-4845	193	50	finished	finish	VERB
cana-4845	193	51	using	use	VERB
cana-4845	193	52	cnn	cnn	PROPN
cana-4845	193	53	,	,	PUNCT
cana-4845	193	54	knn	knn	PROPN
cana-4845	193	55	,	,	PUNCT
cana-4845	193	56	and	and	CCONJ
cana-4845	193	57	svm	svm	ADJ
cana-4845	193	58	classifiers	classifier	NOUN
cana-4845	193	59	.	.	PUNCT
cana-4845	194	1	most	most	ADJ
cana-4845	194	2	ecg	ecg	PROPN
cana-4845	194	3	signal	signal	ADJ
cana-4845	194	4	analysis	analysis	NOUN
cana-4845	194	5	techniques	technique	NOUN
cana-4845	194	6	make	make	VERB
cana-4845	194	7	extensive	extensive	ADJ
cana-4845	194	8	use	use	NOUN
cana-4845	194	9	of	of	ADP
cana-4845	194	10	them	they	PRON
cana-4845	194	11	.	.	PUNCT
cana-4845	195	1	the	the	DET
cana-4845	195	2	basic	basic	ADJ
cana-4845	195	3	lstm	lstm	NOUN
cana-4845	195	4	technique	technique	NOUN
cana-4845	195	5	provides	provide	VERB
cana-4845	195	6	the	the	DET
cana-4845	195	7	lowest	low	ADJ
cana-4845	195	8	rmse	rmse	NOUN
cana-4845	195	9	value	value	NOUN
cana-4845	195	10	when	when	SCONJ
cana-4845	195	11	compared	compare	VERB
cana-4845	195	12	to	to	ADP
cana-4845	195	13	other	other	ADJ
cana-4845	195	14	models	model	NOUN
cana-4845	195	15	.	.	PUNCT
cana-4845	196	1	thus	thus	ADV
cana-4845	196	2	,	,	PUNCT
cana-4845	196	3	sorrow	sorrow	NOUN
cana-4845	196	4	may	may	AUX
cana-4845	196	5	be	be	AUX
cana-4845	196	6	predicted	predict	VERB
cana-4845	196	7	from	from	ADP
cana-4845	196	8	ecg	ecg	PROPN
cana-4845	196	9	measurements	measurement	NOUN
cana-4845	196	10	using	use	VERB
cana-4845	196	11	the	the	DET
cana-4845	196	12	lstm	lstm	PROPN
cana-4845	196	13	model	model	NOUN
cana-4845	196	14	.	.	PUNCT
cana-4845	197	1	eeg	eeg	PROPN
cana-4845	197	2	readings	reading	NOUN
cana-4845	197	3	are	be	AUX
cana-4845	197	4	analyzed	analyze	VERB
cana-4845	197	5	using	use	VERB
cana-4845	197	6	cnn	cnn	PROPN
cana-4845	197	7	and	and	CCONJ
cana-4845	197	8	svm	svm	ADJ
cana-4845	197	9	algorithms	algorithm	NOUN
cana-4845	197	10	.	.	PUNCT
cana-4845	198	1	assist	assist	VERB
cana-4845	198	2	vector	vector	NOUN
cana-4845	198	3	machine	machine	NOUN
cana-4845	198	4	:	:	PUNCT
cana-4845	198	5	support	support	NOUN
cana-4845	198	6	vector	vector	NOUN
cana-4845	198	7	machines	machine	NOUN
cana-4845	198	8	(	(	PUNCT
cana-4845	198	9	svms	svms	NOUN
cana-4845	198	10	)	)	PUNCT
cana-4845	198	11	,	,	PUNCT
cana-4845	198	12	which	which	PRON
cana-4845	198	13	are	be	AUX
cana-4845	198	14	frequently	frequently	ADV
cana-4845	198	15	utilized	utilize	VERB
cana-4845	198	16	in	in	ADP
cana-4845	198	17	the	the	DET
cana-4845	198	18	diagnosis	diagnosis	NOUN
cana-4845	198	19	of	of	ADP
cana-4845	198	20	neurological	neurological	ADJ
cana-4845	198	21	conditions	condition	NOUN
cana-4845	198	22	like	like	ADP
cana-4845	198	23	epilepsy	epilepsy	NOUN
cana-4845	198	24	and	and	CCONJ
cana-4845	198	25	sleep	sleep	VERB
cana-4845	198	26	disorders	disorder	NOUN
cana-4845	198	27	,	,	PUNCT
cana-4845	198	28	are	be	AUX
cana-4845	198	29	used	use	VERB
cana-4845	198	30	to	to	PART
cana-4845	198	31	classify	classify	VERB
cana-4845	198	32	electroencephalogram	electroencephalogram	NOUN
cana-4845	198	33	(	(	PUNCT
cana-4845	198	34	eeg	eeg	NOUN
cana-4845	198	35	)	)	PUNCT
cana-4845	198	36	signals	signal	NOUN
cana-4845	198	37	.	.	PUNCT
cana-4845	199	1	svm	svm	PROPN
cana-4845	199	2	does	do	VERB
cana-4845	199	3	well	well	ADV
cana-4845	199	4	in	in	ADP
cana-4845	199	5	generalizing	generalize	VERB
cana-4845	199	6	to	to	ADP
cana-4845	199	7	high	high	ADJ
cana-4845	199	8	dimensional	dimensional	ADJ
cana-4845	199	9	data	datum	NOUN
cana-4845	199	10	because	because	SCONJ
cana-4845	199	11	of	of	ADP
cana-4845	199	12	its	its	PRON
cana-4845	199	13	convex	convex	NOUN
cana-4845	199	14	optimization	optimization	NOUN
cana-4845	199	15	problem	problem	NOUN
cana-4845	199	16	.	.	PUNCT
cana-4845	200	1	the	the	DET
cana-4845	200	2	support	support	NOUN
cana-4845	200	3	vector	vector	NOUN
cana-4845	200	4	machine	machine	NOUN
cana-4845	200	5	(	(	PUNCT
cana-4845	200	6	svm	svm	PROPN
cana-4845	200	7	)	)	PUNCT
cana-4845	200	8	is	be	AUX
cana-4845	200	9	a	a	DET
cana-4845	200	10	classification	classification	NOUN
cana-4845	200	11	method	method	NOUN
cana-4845	200	12	that	that	PRON
cana-4845	200	13	is	be	AUX
cana-4845	200	14	grounded	ground	VERB
cana-4845	200	15	in	in	ADP
cana-4845	200	16	statistical	statistical	ADJ
cana-4845	200	17	learning	learning	NOUN
cana-4845	200	18	theory	theory	NOUN
cana-4845	200	19	.	.	PUNCT
cana-4845	201	1	support	support	NOUN
cana-4845	201	2	vector	vector	NOUN
cana-4845	201	3	machines	machine	NOUN
cana-4845	201	4	,	,	PUNCT
cana-4845	201	5	or	or	CCONJ
cana-4845	201	6	svms	svms	NOUN
cana-4845	201	7	,	,	PUNCT
cana-4845	201	8	look	look	VERB
cana-4845	201	9	for	for	ADP
cana-4845	201	10	a	a	DET
cana-4845	201	11	hyper	hyper	ADJ
cana-4845	201	12	plane	plane	NOUN
cana-4845	201	13	that	that	PRON
cana-4845	201	14	maximally	maximally	ADV
cana-4845	201	15	bounds	bound	VERB
cana-4845	201	16	the	the	DET
cana-4845	201	17	separation	separation	NOUN
cana-4845	201	18	of	of	ADP
cana-4845	201	19	the	the	DET
cana-4845	201	20	input	input	NOUN
cana-4845	201	21	space	space	NOUN
cana-4845	201	22	in	in	ADP
cana-4845	201	23	a	a	DET
cana-4845	201	24	given	give	VERB
cana-4845	201	25	two	two	NUM
cana-4845	201	26	-	-	PUNCT
cana-4845	201	27	class	class	NOUN
cana-4845	201	28	linearly	linearly	ADV
cana-4845	201	29	separable	separable	ADJ
cana-4845	201	30	classification	classification	NOUN
cana-4845	201	31	issue	issue	NOUN
cana-4845	201	32	.	.	PUNCT
cana-4845	202	1	equations	equation	NOUN
cana-4845	202	2	7	7	NUM
cana-4845	202	3	communications	communication	NOUN
cana-4845	202	4	on	on	ADP
cana-4845	202	5	applied	apply	VERB
cana-4845	202	6	nonlinear	nonlinear	ADJ
cana-4845	202	7	analysis	analysis	NOUN
cana-4845	202	8	issn	issn	NOUN
cana-4845	202	9	:	:	PUNCT
cana-4845	202	10	1074	1074	NUM
cana-4845	202	11	-	-	PUNCT
cana-4845	202	12	133x	133x	NUM
cana-4845	202	13	vol	vol	VERB
cana-4845	202	14	32	32	NUM
cana-4845	202	15	no	no	NOUN
cana-4845	202	16	.	.	PUNCT
cana-4845	203	1	10s	10	NOUN
cana-4845	203	2	(	(	PUNCT
cana-4845	203	3	2025	2025	NUM
cana-4845	203	4	)	)	PUNCT
cana-4845	203	5	554	554	NUM
cana-4845	203	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	203	7	and	and	CCONJ
cana-4845	203	8	8	8	NUM
cana-4845	203	9	determine	determine	VERB
cana-4845	203	10	the	the	DET
cana-4845	203	11	ideal	ideal	ADJ
cana-4845	203	12	hyper	hyper	ADJ
cana-4845	203	13	plane	plane	NOUN
cana-4845	203	14	in	in	ADP
cana-4845	203	15	this	this	DET
cana-4845	203	16	manner	manner	NOUN
cana-4845	203	17	.	.	PUNCT
cana-4845	204	1	𝑤	𝑤	X
cana-4845	204	2	.	.	PUNCT
cana-4845	205	1	𝑥𝑖	𝑥𝑖	PRON
cana-4845	206	1	+	+	CCONJ
cana-4845	206	2	𝑏	𝑏	PRON
cana-4845	206	3	≥	≥	NOUN
cana-4845	206	4	+1	+1	PROPN
cana-4845	206	5	,	,	PUNCT
cana-4845	206	6	𝑖𝑓	𝑖𝑓	ADP
cana-4845	206	7	𝑦𝑖	𝑦𝑖	NOUN
cana-4845	206	8	=	=	SYM
cana-4845	206	9	+1	+1	PROPN
cana-4845	206	10	(	(	PUNCT
cana-4845	206	11	7	7	NUM
cana-4845	206	12	)	)	PUNCT
cana-4845	206	13	𝑤.	𝑤.	NOUN
cana-4845	206	14	𝑥𝑖	𝑥𝑖	PRON
cana-4845	207	1	+	+	CCONJ
cana-4845	207	2	𝑏	𝑏	PROPN
cana-4845	207	3	≤	≤	X
cana-4845	207	4	+1	+1	PROPN
cana-4845	207	5	,	,	PUNCT
cana-4845	207	6	𝑖𝑓	𝑖𝑓	ADP
cana-4845	207	7	𝑦𝑖	𝑦𝑖	PROPN
cana-4845	207	8	=	=	SYM
cana-4845	207	9	−1	−1	NOUN
cana-4845	207	10	(	(	PUNCT
cana-4845	207	11	8)	8)	NUM
cana-4845	207	12	where	where	SCONJ
cana-4845	207	13	𝑥𝑖	𝑥𝑖	PROPN
cana-4845	207	14	is	be	AUX
cana-4845	207	15	the	the	DET
cana-4845	207	16	ith	ith	PROPN
cana-4845	207	17	input	input	NOUN
cana-4845	207	18	vector	vector	NOUN
cana-4845	207	19	(	(	PUNCT
cana-4845	207	20	x	x	PROPN
cana-4845	207	21	∈	∈	PROPN
cana-4845	207	22	rn	rn	PROPN
cana-4845	207	23	)	)	PUNCT
cana-4845	207	24	,	,	PUNCT
cana-4845	207	25	w	w	PROPN
cana-4845	207	26	is	be	AUX
cana-4845	207	27	the	the	DET
cana-4845	207	28	weight	weight	NOUN
cana-4845	207	29	vector	vector	NOUN
cana-4845	207	30	normal	normal	ADJ
cana-4845	207	31	to	to	ADP
cana-4845	207	32	the	the	DET
cana-4845	207	33	hyper	hyper	ADJ
cana-4845	207	34	plane	plane	NOUN
cana-4845	207	35	,	,	PUNCT
cana-4845	207	36	b	b	PROPN
cana-4845	207	37	is	be	AUX
cana-4845	207	38	the	the	DET
cana-4845	207	39	bias	bias	NOUN
cana-4845	207	40	,	,	PUNCT
cana-4845	207	41	and	and	CCONJ
cana-4845	207	42	yi	yi	PROPN
cana-4845	207	43	is	be	AUX
cana-4845	207	44	the	the	DET
cana-4845	207	45	class	class	NOUN
cana-4845	207	46	label	label	NOUN
cana-4845	207	47	of	of	ADP
cana-4845	207	48	the	the	DET
cana-4845	207	49	ith	ith	PROPN
cana-4845	207	50	input	input	NOUN
cana-4845	207	51	(	(	PUNCT
cana-4845	207	52	y	y	PROPN
cana-4845	207	53	∈	∈	PROPN
cana-4845	207	54	{	{	PUNCT
cana-4845	207	55	-1	-1	NOUN
cana-4845	207	56	,	,	PUNCT
cana-4845	207	57	+1	+1	PROPN
cana-4845	207	58	}	}	PUNCT
cana-4845	207	59	)	)	PUNCT
cana-4845	207	60	.	.	PUNCT
cana-4845	208	1	the	the	DET
cana-4845	208	2	ideal	ideal	ADJ
cana-4845	208	3	hyper	hyper	ADJ
cana-4845	208	4	plane	plane	NOUN
cana-4845	208	5	is	be	AUX
cana-4845	208	6	determined	determine	VERB
cana-4845	208	7	by	by	ADP
cana-4845	208	8	two	two	NUM
cana-4845	208	9	margins	margin	NOUN
cana-4845	208	10	that	that	PRON
cana-4845	208	11	run	run	VERB
cana-4845	208	12	parallel	parallel	ADJ
cana-4845	208	13	to	to	ADP
cana-4845	208	14	it	it	PRON
cana-4845	208	15	.	.	PUNCT
cana-4845	209	1	the	the	DET
cana-4845	209	2	margins	margin	NOUN
cana-4845	209	3	are	be	AUX
cana-4845	209	4	found	find	VERB
cana-4845	209	5	via	via	ADP
cana-4845	209	6	equation	equation	NOUN
cana-4845	209	7	9	9	NUM
cana-4845	209	8	.	.	PUNCT
cana-4845	210	1	𝑤.	𝑤.	NOUN
cana-4845	210	2	𝑥𝑖	𝑥𝑖	PRON
cana-4845	211	1	+	+	CCONJ
cana-4845	211	2	𝑏	𝑏	PROPN
cana-4845	211	3	≤	≤	ADV
cana-4845	211	4	+1	+1	NOUN
cana-4845	211	5	(	(	PUNCT
cana-4845	211	6	9	9	NUM
cana-4845	211	7	)	)	PUNCT
cana-4845	211	8	the	the	DET
cana-4845	211	9	input	input	NOUN
cana-4845	211	10	vectors	vector	NOUN
cana-4845	211	11	used	use	VERB
cana-4845	211	12	to	to	PART
cana-4845	211	13	determine	determine	VERB
cana-4845	211	14	the	the	DET
cana-4845	211	15	margins	margin	NOUN
cana-4845	211	16	are	be	AUX
cana-4845	211	17	called	call	VERB
cana-4845	211	18	support	support	NOUN
cana-4845	211	19	vectors	vector	NOUN
cana-4845	211	20	.	.	PUNCT
cana-4845	212	1	if	if	SCONJ
cana-4845	212	2	the	the	DET
cana-4845	212	3	problem	problem	NOUN
cana-4845	212	4	is	be	AUX
cana-4845	212	5	not	not	PART
cana-4845	212	6	linearly	linearly	ADV
cana-4845	212	7	separable	separable	ADJ
cana-4845	212	8	,	,	PUNCT
cana-4845	212	9	the	the	DET
cana-4845	212	10	problem	problem	NOUN
cana-4845	212	11	should	should	AUX
cana-4845	212	12	be	be	AUX
cana-4845	212	13	transformed	transform	VERB
cana-4845	212	14	into	into	ADP
cana-4845	212	15	a	a	DET
cana-4845	212	16	transformed	transform	VERB
cana-4845	212	17	space	space	NOUN
cana-4845	212	18	by	by	ADP
cana-4845	212	19	applying	apply	VERB
cana-4845	212	20	a	a	DET
cana-4845	212	21	kernel	kernel	NOUN
cana-4845	212	22	function	function	NOUN
cana-4845	212	23	to	to	ADP
cana-4845	212	24	the	the	DET
cana-4845	212	25	input	input	NOUN
cana-4845	212	26	vectors	vector	NOUN
cana-4845	212	27	.	.	PUNCT
cana-4845	213	1	𝑘(𝑥𝑖𝑥𝑗	𝑘(𝑥𝑖𝑥𝑗	VERB
cana-4845	213	2	)	)	PUNCT
cana-4845	214	1	=	=	SYM
cana-4845	214	2	𝜑(𝑥	𝜑(𝑥	X
cana-4845	214	3	)	)	PUNCT
cana-4845	214	4	𝜑(𝑥𝑗	𝜑(𝑥𝑗	NOUN
cana-4845	214	5	)	)	PUNCT
cana-4845	214	6	(	(	PUNCT
cana-4845	214	7	10	10	NUM
cana-4845	214	8	)	)	PUNCT
cana-4845	214	9	equation	equation	NOUN
cana-4845	214	10	11	11	NUM
cana-4845	214	11	computes	compute	VERB
cana-4845	214	12	the	the	DET
cana-4845	214	13	following	following	ADJ
cana-4845	214	14	solution	solution	NOUN
cana-4845	214	15	to	to	ADP
cana-4845	214	16	a	a	DET
cana-4845	214	17	linearly	linearly	ADJ
cana-4845	214	18	non	non	ADJ
cana-4845	214	19	-	-	ADJ
cana-4845	214	20	separable	separable	ADJ
cana-4845	214	21	problem	problem	NOUN
cana-4845	214	22	with	with	ADP
cana-4845	214	23	two	two	NUM
cana-4845	214	24	classes	class	NOUN
cana-4845	214	25	.	.	PUNCT
cana-4845	215	1	𝑓(𝑥	𝑓(𝑥	NOUN
cana-4845	215	2	)	)	PUNCT
cana-4845	215	3	=	=	SYM
cana-4845	215	4	𝑠𝑖𝑔𝑛(∑	𝑠𝑖𝑔𝑛(∑	PROPN
cana-4845	215	5	𝛼𝑖𝑦𝑗𝜑(𝑥	𝛼𝑖𝑦𝑗𝜑(𝑥	NOUN
cana-4845	215	6	)	)	PUNCT
cana-4845	215	7	𝜑(𝑥𝑗	𝜑(𝑥𝑗	NOUN
cana-4845	215	8	)	)	PUNCT
cana-4845	215	9	+	+	PUNCT
cana-4845	215	10	𝑏	𝑏	NOUN
cana-4845	215	11	)	)	PUNCT
cana-4845	215	12	(	(	PUNCT
cana-4845	215	13	11	11	NUM
cana-4845	215	14	)	)	PUNCT
cana-4845	215	15	neural	neural	ADJ
cana-4845	215	16	network	network	NOUN
cana-4845	215	17	convolution	convolution	NOUN
cana-4845	215	18	:	:	PUNCT
cana-4845	215	19	figure	figure	NOUN
cana-4845	215	20	3	3	NUM
cana-4845	215	21	depicts	depict	VERB
cana-4845	215	22	the	the	DET
cana-4845	215	23	cnn	cnn	PROPN
cana-4845	215	24	model	model	NOUN
cana-4845	215	25	,	,	PUNCT
cana-4845	215	26	which	which	PRON
cana-4845	215	27	consists	consist	VERB
cana-4845	215	28	of	of	ADP
cana-4845	215	29	input	input	NOUN
cana-4845	215	30	,	,	PUNCT
cana-4845	215	31	output	output	NOUN
cana-4845	215	32	,	,	PUNCT
cana-4845	215	33	pooling	pooling	NOUN
cana-4845	215	34	,	,	PUNCT
cana-4845	215	35	and	and	CCONJ
cana-4845	215	36	convolution	convolution	NOUN
cana-4845	215	37	layers	layer	NOUN
cana-4845	215	38	.	.	PUNCT
cana-4845	216	1	figure	figure	VERB
cana-4845	216	2	3	3	NUM
cana-4845	216	3	:	:	PUNCT
cana-4845	216	4	cnn	cnn	PROPN
cana-4845	216	5	eeg	eeg	PROPN
cana-4845	216	6	signal	signal	PROPN
cana-4845	216	7	model	model	NOUN
cana-4845	216	8	•	•	ADP
cana-4845	216	9	the	the	DET
cana-4845	216	10	maximum	maximum	ADJ
cana-4845	216	11	pooling	pool	VERB
cana-4845	216	12	layer	layer	NOUN
cana-4845	216	13	size	size	NOUN
cana-4845	216	14	is	be	AUX
cana-4845	216	15	two	two	NUM
cana-4845	216	16	.	.	PUNCT
cana-4845	217	1	•	•	NUM
cana-4845	217	2	filters	filter	NOUN
cana-4845	217	3	and	and	CCONJ
cana-4845	217	4	convolution	convolution	NOUN
cana-4845	217	5	layer	layer	NOUN
cana-4845	217	6	:	:	PUNCT
cana-4845	217	7	32	32	NUM
cana-4845	217	8	•	•	NOUN
cana-4845	217	9	size	size	NOUN
cana-4845	217	10	of	of	ADP
cana-4845	217	11	kernel	kernel	NOUN
cana-4845	217	12	:	:	PUNCT
cana-4845	217	13	3	3	X
cana-4845	217	14	.	.	NOUN
cana-4845	217	15	•	•	NUM
cana-4845	217	16	relu	relu	NOUN
cana-4845	217	17	is	be	AUX
cana-4845	217	18	the	the	DET
cana-4845	217	19	activation	activation	NOUN
cana-4845	217	20	function	function	NOUN
cana-4845	217	21	.	.	PUNCT
cana-4845	218	1	•	•	ADV
cana-4845	218	2	there	there	PRON
cana-4845	218	3	are	be	VERB
cana-4845	218	4	sixteen	sixteen	NUM
cana-4845	218	5	secret	secret	ADJ
cana-4845	218	6	layers	layer	NOUN
cana-4845	218	7	.	.	PUNCT
cana-4845	219	1	communications	communication	NOUN
cana-4845	219	2	on	on	ADP
cana-4845	219	3	applied	apply	VERB
cana-4845	219	4	nonlinear	nonlinear	ADJ
cana-4845	219	5	analysis	analysis	NOUN
cana-4845	219	6	issn	issn	NOUN
cana-4845	219	7	:	:	PUNCT
cana-4845	219	8	1074	1074	NUM
cana-4845	219	9	-	-	PUNCT
cana-4845	219	10	133x	133x	NUM
cana-4845	219	11	vol	vol	VERB
cana-4845	219	12	32	32	NUM
cana-4845	219	13	no	no	NOUN
cana-4845	219	14	.	.	PUNCT
cana-4845	220	1	10s	10	NOUN
cana-4845	220	2	(	(	PUNCT
cana-4845	220	3	2025	2025	NUM
cana-4845	220	4	)	)	PUNCT
cana-4845	220	5	555	555	NUM
cana-4845	220	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	220	7	neural	neural	ADJ
cana-4845	220	8	network	network	NOUN
cana-4845	220	9	recurrence	recurrence	NOUN
cana-4845	220	10	compared	compare	VERB
cana-4845	220	11	to	to	ADP
cana-4845	220	12	most	most	ADJ
cana-4845	220	13	existing	exist	VERB
cana-4845	220	14	models	model	NOUN
cana-4845	220	15	,	,	PUNCT
cana-4845	220	16	the	the	DET
cana-4845	220	17	rnn	rnn	NOUN
cana-4845	220	18	model	model	NOUN
cana-4845	220	19	is	be	AUX
cana-4845	220	20	far	far	ADV
cana-4845	220	21	more	more	ADV
cana-4845	220	22	straightforward	straightforward	ADJ
cana-4845	220	23	.	.	PUNCT
cana-4845	221	1	the	the	DET
cana-4845	221	2	lstm	lstm	PROPN
cana-4845	221	3	auto	auto	NOUN
cana-4845	221	4	encoder	encoder	NOUN
cana-4845	221	5	was	be	AUX
cana-4845	221	6	also	also	ADV
cana-4845	221	7	incorporated	incorporate	VERB
cana-4845	221	8	to	to	PART
cana-4845	221	9	enhance	enhance	VERB
cana-4845	221	10	a	a	DET
cana-4845	221	11	model	model	NOUN
cana-4845	221	12	's	's	PART
cana-4845	221	13	performance	performance	NOUN
cana-4845	221	14	.	.	PUNCT
cana-4845	222	1	figure	figure	VERB
cana-4845	222	2	4	4	NUM
cana-4845	222	3	:	:	PUNCT
cana-4845	222	4	block	block	NOUN
cana-4845	222	5	diagram	diagram	NOUN
cana-4845	222	6	for	for	ADP
cana-4845	222	7	lstm	lstm	NOUN
cana-4845	222	8	-	-	PUNCT
cana-4845	222	9	based	base	VERB
cana-4845	222	10	depression	depression	NOUN
cana-4845	222	11	diagnosis	diagnosis	NOUN
cana-4845	222	12	.	.	PUNCT
cana-4845	223	1	figure	figure	NOUN
cana-4845	223	2	4	4	NUM
cana-4845	223	3	shows	show	VERB
cana-4845	223	4	the	the	DET
cana-4845	223	5	system	system	NOUN
cana-4845	223	6	architecture	architecture	NOUN
cana-4845	223	7	,	,	PUNCT
cana-4845	223	8	which	which	PRON
cana-4845	223	9	is	be	AUX
cana-4845	223	10	the	the	DET
cana-4845	223	11	source	source	NOUN
cana-4845	223	12	of	of	ADP
cana-4845	223	13	the	the	DET
cana-4845	223	14	data	datum	NOUN
cana-4845	223	15	.	.	PUNCT
cana-4845	224	1	after	after	ADP
cana-4845	224	2	that	that	PRON
cana-4845	224	3	,	,	PUNCT
cana-4845	224	4	we	we	PRON
cana-4845	224	5	conducted	conduct	VERB
cana-4845	224	6	data	datum	NOUN
cana-4845	224	7	preparation	preparation	NOUN
cana-4845	224	8	to	to	PART
cana-4845	224	9	rename	rename	VERB
cana-4845	224	10	some	some	PRON
cana-4845	224	11	of	of	ADP
cana-4845	224	12	the	the	DET
cana-4845	224	13	dataset	dataset	NOUN
cana-4845	224	14	's	's	PART
cana-4845	224	15	columns	column	NOUN
cana-4845	224	16	and	and	CCONJ
cana-4845	224	17	data	datum	NOUN
cana-4845	224	18	exploration	exploration	NOUN
cana-4845	224	19	to	to	PART
cana-4845	224	20	look	look	VERB
cana-4845	224	21	over	over	ADP
cana-4845	224	22	the	the	DET
cana-4845	224	23	dataset	dataset	NOUN
cana-4845	224	24	.	.	PUNCT
cana-4845	225	1	this	this	DET
cana-4845	225	2	data	data	NOUN
cana-4845	225	3	is	be	AUX
cana-4845	225	4	subsequently	subsequently	ADV
cana-4845	225	5	learned	learn	VERB
cana-4845	225	6	by	by	ADP
cana-4845	225	7	the	the	DET
cana-4845	225	8	rnn	rnn	NOUN
cana-4845	225	9	and	and	CCONJ
cana-4845	225	10	sent	send	VERB
cana-4845	225	11	to	to	ADP
cana-4845	225	12	an	an	DET
cana-4845	225	13	lstm	lstm	ADJ
cana-4845	225	14	auto	auto	NOUN
cana-4845	225	15	encoder	encoder	NOUN
cana-4845	225	16	for	for	ADP
cana-4845	225	17	model	model	NOUN
cana-4845	225	18	training	training	NOUN
cana-4845	225	19	.	.	PUNCT
cana-4845	226	1	following	follow	VERB
cana-4845	226	2	training	training	NOUN
cana-4845	226	3	,	,	PUNCT
cana-4845	226	4	the	the	DET
cana-4845	226	5	training	training	NOUN
cana-4845	226	6	data	datum	NOUN
cana-4845	226	7	is	be	AUX
cana-4845	226	8	subjected	subject	VERB
cana-4845	226	9	to	to	ADP
cana-4845	226	10	a	a	DET
cana-4845	226	11	test	test	NOUN
cana-4845	226	12	portion	portion	NOUN
cana-4845	226	13	that	that	PRON
cana-4845	226	14	classifies	classify	VERB
cana-4845	226	15	and	and	CCONJ
cana-4845	226	16	predicts	predict	VERB
cana-4845	226	17	safe	safe	ADJ
cana-4845	226	18	heartbeats	heartbeat	NOUN
cana-4845	226	19	.	.	PUNCT
cana-4845	227	1	this	this	DET
cana-4845	227	2	yields	yield	VERB
cana-4845	227	3	the	the	DET
cana-4845	227	4	expected	expect	VERB
cana-4845	227	5	result	result	NOUN
cana-4845	227	6	of	of	ADP
cana-4845	227	7	the	the	DET
cana-4845	227	8	model	model	NOUN
cana-4845	227	9	.	.	PUNCT
cana-4845	228	1	there	there	PRON
cana-4845	228	2	are	be	VERB
cana-4845	228	3	two	two	NUM
cana-4845	228	4	parts	part	NOUN
cana-4845	228	5	to	to	ADP
cana-4845	228	6	the	the	DET
cana-4845	228	7	typical	typical	ADJ
cana-4845	228	8	auto	auto	NOUN
cana-4845	228	9	encoder	encoder	NOUN
cana-4845	228	10	construction	construction	NOUN
cana-4845	228	11	.	.	PUNCT
cana-4845	229	1	a	a	DET
cana-4845	229	2	signal	signal	NOUN
cana-4845	229	3	is	be	AUX
cana-4845	229	4	compressed	compress	VERB
cana-4845	229	5	by	by	ADP
cana-4845	229	6	encoders	encoder	NOUN
cana-4845	229	7	and	and	CCONJ
cana-4845	229	8	then	then	ADV
cana-4845	229	9	attempted	attempt	VERB
cana-4845	229	10	to	to	PART
cana-4845	229	11	be	be	AUX
cana-4845	229	12	replicated	replicate	VERB
cana-4845	229	13	by	by	ADP
cana-4845	229	14	decoders	decoder	NOUN
cana-4845	229	15	.	.	PUNCT
cana-4845	230	1	the	the	DET
cana-4845	230	2	yield	yield	NOUN
cana-4845	230	3	expectations	expectation	NOUN
cana-4845	230	4	are	be	AUX
cana-4845	230	5	then	then	ADV
cana-4845	230	6	calculated	calculate	VERB
cana-4845	230	7	using	use	VERB
cana-4845	230	8	these	these	DET
cana-4845	230	9	repeated	repeat	VERB
cana-4845	230	10	input	input	NOUN
cana-4845	230	11	values	value	NOUN
cana-4845	230	12	.	.	PUNCT
cana-4845	231	1	the	the	DET
cana-4845	231	2	rnn	rnn	NOUN
cana-4845	231	3	uses	use	VERB
cana-4845	231	4	the	the	DET
cana-4845	231	5	lstm	lstm	ADJ
cana-4845	231	6	auto	auto	NOUN
cana-4845	231	7	encoder	encoder	NOUN
cana-4845	231	8	to	to	PART
cana-4845	231	9	train	train	VERB
cana-4845	231	10	the	the	DET
cana-4845	231	11	model	model	NOUN
cana-4845	231	12	after	after	ADP
cana-4845	231	13	learning	learn	VERB
cana-4845	231	14	this	this	DET
cana-4845	231	15	data	datum	NOUN
cana-4845	231	16	.	.	PUNCT
cana-4845	232	1	tests	test	NOUN
cana-4845	232	2	to	to	PART
cana-4845	232	3	classify	classify	VERB
cana-4845	232	4	and	and	CCONJ
cana-4845	232	5	predict	predict	VERB
cana-4845	232	6	both	both	CCONJ
cana-4845	232	7	normal	normal	ADJ
cana-4845	232	8	and	and	CCONJ
cana-4845	232	9	depressed	depressed	ADJ
cana-4845	232	10	cardiac	cardiac	ADJ
cana-4845	232	11	rhythms	rhythm	NOUN
cana-4845	232	12	are	be	AUX
cana-4845	232	13	conducted	conduct	VERB
cana-4845	232	14	on	on	ADP
cana-4845	232	15	the	the	DET
cana-4845	232	16	training	training	NOUN
cana-4845	232	17	data	datum	NOUN
cana-4845	232	18	after	after	ADP
cana-4845	232	19	training	training	NOUN
cana-4845	232	20	.	.	PUNCT
cana-4845	233	1	it	it	PRON
cana-4845	233	2	turns	turn	VERB
cana-4845	233	3	out	out	ADP
cana-4845	233	4	that	that	SCONJ
cana-4845	233	5	selectively	selectively	ADV
cana-4845	233	6	constructing	construct	VERB
cana-4845	233	7	an	an	DET
cana-4845	233	8	svm	svm	ADJ
cana-4845	233	9	classifier	classifier	NOUN
cana-4845	233	10	can	can	AUX
cana-4845	233	11	lead	lead	VERB
cana-4845	233	12	to	to	ADP
cana-4845	233	13	very	very	ADV
cana-4845	233	14	high	high	ADJ
cana-4845	233	15	accuracy	accuracy	NOUN
cana-4845	233	16	.	.	PUNCT
cana-4845	234	1	a	a	DET
cana-4845	234	2	common	common	ADJ
cana-4845	234	3	auto	auto	NOUN
cana-4845	234	4	encoder	encoder	NOUN
cana-4845	234	5	structure	structure	NOUN
cana-4845	234	6	consists	consist	VERB
cana-4845	234	7	of	of	ADP
cana-4845	234	8	two	two	NUM
cana-4845	234	9	parts	part	NOUN
cana-4845	234	10	.	.	PUNCT
cana-4845	235	1	encoders	encoder	NOUN
cana-4845	235	2	compress	compress	VERB
cana-4845	235	3	their	their	PRON
cana-4845	235	4	input	input	NOUN
cana-4845	235	5	while	while	SCONJ
cana-4845	235	6	decoders	decoder	NOUN
cana-4845	235	7	try	try	VERB
cana-4845	235	8	to	to	PART
cana-4845	235	9	reconstruct	reconstruct	VERB
cana-4845	235	10	it	it	PRON
cana-4845	235	11	.	.	PUNCT
cana-4845	236	1	predictions	prediction	NOUN
cana-4845	236	2	for	for	ADP
cana-4845	236	3	the	the	DET
cana-4845	236	4	output	output	NOUN
cana-4845	236	5	are	be	AUX
cana-4845	236	6	then	then	ADV
cana-4845	236	7	produced	produce	VERB
cana-4845	236	8	using	use	VERB
cana-4845	236	9	these	these	DET
cana-4845	236	10	restored	restore	VERB
cana-4845	236	11	input	input	NOUN
cana-4845	236	12	values	value	NOUN
cana-4845	236	13	.	.	PUNCT
cana-4845	237	1	extracted	extract	VERB
cana-4845	237	2	from	from	ADP
cana-4845	237	3	the	the	DET
cana-4845	237	4	ecg	ecg	PROPN
cana-4845	237	5	data	datum	NOUN
cana-4845	237	6	in	in	ADP
cana-4845	237	7	order	order	NOUN
cana-4845	237	8	to	to	PART
cana-4845	237	9	classify	classify	VERB
cana-4845	237	10	a	a	DET
cana-4845	237	11	person	person	NOUN
cana-4845	237	12	as	as	ADP
cana-4845	237	13	either	either	CCONJ
cana-4845	237	14	normal	normal	ADJ
cana-4845	237	15	or	or	CCONJ
cana-4845	237	16	depressed	depressed	ADJ
cana-4845	237	17	using	use	VERB
cana-4845	237	18	rnn	rnn	PROPN
cana-4845	237	19	and	and	CCONJ
cana-4845	237	20	auto	auto	NOUN
cana-4845	237	21	encoder	encoder	NOUN
cana-4845	237	22	techniques	technique	NOUN
cana-4845	237	23	.	.	PUNCT
cana-4845	238	1	3	3	X
cana-4845	238	2	.	.	NOUN
cana-4845	238	3	results	result	VERB
cana-4845	238	4	information	information	NOUN
cana-4845	238	5	gathering	gather	VERB
cana-4845	238	6	eeg	eeg	NOUN
cana-4845	238	7	collecting	collect	VERB
cana-4845	238	8	sites	site	NOUN
cana-4845	238	9	and	and	CCONJ
cana-4845	238	10	the	the	DET
cana-4845	238	11	data	data	NOUN
cana-4845	238	12	capture	capture	NOUN
cana-4845	238	13	procedure	procedure	NOUN
cana-4845	238	14	has	have	AUX
cana-4845	238	15	been	be	AUX
cana-4845	238	16	found	find	VERB
cana-4845	238	17	to	to	PART
cana-4845	238	18	be	be	AUX
cana-4845	238	19	closely	closely	ADV
cana-4845	238	20	linked	link	VERB
cana-4845	238	21	to	to	ADP
cana-4845	238	22	depression	depression	NOUN
cana-4845	238	23	.	.	PUNCT
cana-4845	239	1	in	in	ADP
cana-4845	239	2	accordance	accordance	NOUN
cana-4845	239	3	with	with	ADP
cana-4845	239	4	the	the	DET
cana-4845	239	5	international	international	ADJ
cana-4845	239	6	electrode	electrode	NOUN
cana-4845	239	7	system	system	NOUN
cana-4845	239	8	10	10	NUM
cana-4845	239	9	-	-	SYM
cana-4845	239	10	20	20	NUM
cana-4845	239	11	,	,	PUNCT
cana-4845	239	12	surface	surface	NOUN
cana-4845	239	13	electrodes	electrode	NOUN
cana-4845	239	14	fp1	fp1	NOUN
cana-4845	239	15	,	,	PUNCT
cana-4845	239	16	fp2	fp2	PROPN
cana-4845	239	17	,	,	PUNCT
cana-4845	239	18	f3	f3	PROPN
cana-4845	239	19	,	,	PUNCT
cana-4845	239	20	f4	f4	PROPN
cana-4845	239	21	,	,	PUNCT
cana-4845	239	22	c3	c3	PROPN
cana-4845	239	23	,	,	PUNCT
cana-4845	239	24	c4	c4	NOUN
cana-4845	239	25	,	,	PUNCT
cana-4845	239	26	t3	t3	PROPN
cana-4845	239	27	,	,	PUNCT
cana-4845	239	28	t4	t4	PROPN
cana-4845	239	29	,	,	PUNCT
cana-4845	239	30	t5	t5	PROPN
cana-4845	239	31	,	,	PUNCT
cana-4845	239	32	p3	p3	PROPN
cana-4845	239	33	,	,	PUNCT
cana-4845	239	34	and	and	CCONJ
cana-4845	239	35	p4	p4	ADJ
cana-4845	239	36	are	be	AUX
cana-4845	239	37	positioned	position	VERB
cana-4845	239	38	on	on	ADP
cana-4845	239	39	the	the	DET
cana-4845	239	40	scalp	scalp	NOUN
cana-4845	239	41	to	to	PART
cana-4845	239	42	record	record	VERB
cana-4845	239	43	multi	multi	ADJ
cana-4845	239	44	-	-	ADJ
cana-4845	239	45	channel	channel	ADJ
cana-4845	239	46	eeg	eeg	PROPN
cana-4845	239	47	data	datum	NOUN
cana-4845	239	48	.	.	PUNCT
cana-4845	240	1	information	information	NOUN
cana-4845	240	2	regarding	regard	VERB
cana-4845	240	3	the	the	DET
cana-4845	240	4	eeg	eeg	PROPN
cana-4845	240	5	signal	signal	NOUN
cana-4845	240	6	by	by	ADP
cana-4845	240	7	electrode	electrode	PROPN
cana-4845	240	8	fp1	fp1	NOUN
cana-4845	240	9	with	with	ADP
cana-4845	240	10	eyes	eye	NOUN
cana-4845	240	11	closed	close	VERB
cana-4845	240	12	,	,	PUNCT
cana-4845	240	13	eyes	eye	NOUN
cana-4845	240	14	open	open	VERB
cana-4845	240	15	,	,	PUNCT
cana-4845	240	16	and	and	CCONJ
cana-4845	240	17	under	under	ADP
cana-4845	240	18	task	task	NOUN
cana-4845	240	19	state	state	NOUN
cana-4845	240	20	was	be	AUX
cana-4845	240	21	obtained	obtain	VERB
cana-4845	240	22	from	from	ADP
cana-4845	240	23	that	that	DET
cana-4845	240	24	observed	observe	VERB
cana-4845	240	25	information	information	NOUN
cana-4845	240	26	of	of	ADP
cana-4845	240	27	the	the	DET
cana-4845	240	28	eeg	eeg	NOUN
cana-4845	240	29	signal	signal	NOUN
cana-4845	240	30	for	for	ADP
cana-4845	240	31	that	that	DET
cana-4845	240	32	channel	channel	NOUN
cana-4845	240	33	per	per	ADP
cana-4845	240	34	frame	frame	NOUN
cana-4845	240	35	:	:	PUNCT
cana-4845	240	36	32	32	NUM
cana-4845	240	37	,	,	PUNCT
cana-4845	240	38	sampling	sample	VERB
cana-4845	240	39	rate	rate	NOUN
cana-4845	240	40	:	:	PUNCT
cana-4845	240	41	128	128	NUM
cana-4845	240	42	hz	hz	NOUN
cana-4845	240	43	.	.	PROPN
cana-4845	240	44	eeg	eeg	PROPN
cana-4845	240	45	signal	signal	NOUN
cana-4845	240	46	feature	feature	NOUN
cana-4845	240	47	extraction	extraction	NOUN
cana-4845	240	48	was	be	AUX
cana-4845	240	49	completed	complete	VERB
cana-4845	240	50	.	.	PUNCT
cana-4845	241	1	hjorth	hjorth	NOUN
cana-4845	241	2	activity	activity	NOUN
cana-4845	241	3	(	(	PUNCT
cana-4845	241	4	ha	ha	INTJ
cana-4845	241	5	)	)	PUNCT
cana-4845	241	6	,	,	PUNCT
cana-4845	241	7	complexity	complexity	NOUN
cana-4845	241	8	(	(	PUNCT
cana-4845	241	9	hc	hc	NOUN
cana-4845	241	10	)	)	PUNCT
cana-4845	241	11	,	,	PUNCT
cana-4845	241	12	and	and	CCONJ
cana-4845	241	13	mobility	mobility	NOUN
cana-4845	241	14	(	(	PUNCT
cana-4845	241	15	hm	hm	INTJ
cana-4845	241	16	)	)	PUNCT
cana-4845	241	17	are	be	AUX
cana-4845	241	18	the	the	DET
cana-4845	241	19	eight	eight	NUM
cana-4845	241	20	features	feature	NOUN
cana-4845	241	21	that	that	PRON
cana-4845	241	22	are	be	AUX
cana-4845	241	23	examined	examine	VERB
cana-4845	241	24	in	in	ADP
cana-4845	241	25	total	total	NOUN
cana-4845	241	26	.	.	PUNCT
cana-4845	242	1	the	the	DET
cana-4845	242	2	parameters	parameter	NOUN
cana-4845	242	3	that	that	PRON
cana-4845	242	4	are	be	AUX
cana-4845	242	5	used	use	VERB
cana-4845	242	6	include	include	VERB
cana-4845	242	7	standard	standard	ADJ
cana-4845	242	8	communications	communication	NOUN
cana-4845	242	9	on	on	ADP
cana-4845	242	10	applied	apply	VERB
cana-4845	242	11	nonlinear	nonlinear	ADJ
cana-4845	242	12	analysis	analysis	NOUN
cana-4845	242	13	issn	issn	NOUN
cana-4845	242	14	:	:	PUNCT
cana-4845	242	15	1074	1074	NUM
cana-4845	242	16	-	-	PUNCT
cana-4845	242	17	133x	133x	NUM
cana-4845	242	18	vol	vol	VERB
cana-4845	242	19	32	32	NUM
cana-4845	242	20	no	no	NOUN
cana-4845	242	21	.	.	PUNCT
cana-4845	243	1	10s	10	NOUN
cana-4845	243	2	(	(	PUNCT
cana-4845	243	3	2025	2025	NUM
cana-4845	243	4	)	)	PUNCT
cana-4845	243	5	556	556	NUM
cana-4845	243	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-4845	243	7	deviation	deviation	NOUN
cana-4845	243	8	,	,	PUNCT
cana-4845	243	9	entropy	entropy	PROPN
cana-4845	243	10	,	,	PUNCT
cana-4845	243	11	mean	mean	VERB
cana-4845	243	12	,	,	PUNCT
cana-4845	243	13	variance	variance	NOUN
cana-4845	243	14	,	,	PUNCT
cana-4845	243	15	and	and	CCONJ
cana-4845	243	16	band	band	NOUN
cana-4845	243	17	power	power	NOUN
cana-4845	243	18	alpha	alpha	PROPN
cana-4845	243	19	.	.	PUNCT
cana-4845	244	1	eeg	eeg	PROPN
cana-4845	244	2	signals	signal	NOUN
cana-4845	244	3	are	be	AUX
cana-4845	244	4	best	well	ADV
cana-4845	244	5	suited	suit	VERB
cana-4845	244	6	for	for	ADP
cana-4845	244	7	the	the	DET
cana-4845	244	8	hjorth	hjorth	NOUN
cana-4845	244	9	activity	activity	NOUN
cana-4845	244	10	(	(	PUNCT
cana-4845	244	11	ha	ha	INTJ
cana-4845	244	12	)	)	PUNCT
cana-4845	244	13	,	,	PUNCT
cana-4845	244	14	standard	standard	ADJ
cana-4845	244	15	deviation	deviation	NOUN
cana-4845	244	16	,	,	PUNCT
cana-4845	244	17	entropy	entropy	NOUN
cana-4845	244	18	,	,	PUNCT
cana-4845	244	19	and	and	CCONJ
cana-4845	244	20	band	band	NOUN
cana-4845	244	21	power	power	NOUN
cana-4845	244	22	alpha	alpha	NOUN
cana-4845	244	23	.	.	PUNCT
cana-4845	245	1	4	4	X
cana-4845	245	2	.	.	X
cana-4845	245	3	talk	talk	NOUN
cana-4845	245	4	accuracy	accuracy	NOUN
cana-4845	245	5	is	be	AUX
cana-4845	245	6	used	use	VERB
cana-4845	245	7	to	to	PART
cana-4845	245	8	evaluate	evaluate	VERB
cana-4845	245	9	the	the	DET
cana-4845	245	10	system	system	NOUN
cana-4845	245	11	's	's	PART
cana-4845	245	12	overall	overall	ADJ
cana-4845	245	13	performance	performance	NOUN
cana-4845	245	14	.	.	PUNCT
cana-4845	246	1	sensitivity	sensitivity	NOUN
cana-4845	246	2	is	be	AUX
cana-4845	246	3	a	a	DET
cana-4845	246	4	parameter	parameter	NOUN
cana-4845	246	5	associated	associate	VERB
cana-4845	246	6	with	with	ADP
cana-4845	246	7	a	a	DET
cana-4845	246	8	classifier	classifier	NOUN
cana-4845	246	9	's	's	PART
cana-4845	246	10	upper	upper	ADJ
cana-4845	246	11	potential	potential	NOUN
cana-4845	246	12	to	to	PART
cana-4845	246	13	efficiently	efficiently	ADV
cana-4845	246	14	identify	identify	VERB
cana-4845	246	15	good	good	ADJ
cana-4845	246	16	patterns	pattern	NOUN
cana-4845	246	17	.	.	PUNCT
cana-4845	247	1	the	the	DET
cana-4845	247	2	term	term	NOUN
cana-4845	247	3	"	"	PUNCT
cana-4845	247	4	specificity	specificity	NOUN
cana-4845	247	5	"	"	PUNCT
cana-4845	247	6	describes	describe	VERB
cana-4845	247	7	the	the	DET
cana-4845	247	8	classifier	classifier	NOUN
cana-4845	247	9	's	's	PART
cana-4845	247	10	higher	high	ADJ
cana-4845	247	11	likelihood	likelihood	NOUN
cana-4845	247	12	of	of	ADP
cana-4845	247	13	effectively	effectively	ADV
cana-4845	247	14	capturing	capture	VERB
cana-4845	247	15	the	the	DET
cana-4845	247	16	worst	bad	ADJ
cana-4845	247	17	samples	sample	NOUN
cana-4845	247	18	.	.	PUNCT
cana-4845	248	1	recognition	recognition	NOUN
cana-4845	248	2	accuracy	accuracy	NOUN
cana-4845	248	3	is	be	AUX
cana-4845	248	4	the	the	DET
cana-4845	248	5	classifier	classifier	NOUN
cana-4845	248	6	's	's	PART
cana-4845	248	7	bare	bare	ADJ
cana-4845	248	8	potential	potential	NOUN
cana-4845	248	9	to	to	PART
cana-4845	248	10	effectively	effectively	ADV
cana-4845	248	11	locate	locate	VERB
cana-4845	248	12	clearly	clearly	ADV
cana-4845	248	13	labeled	label	VERB
cana-4845	248	14	samples	sample	NOUN
cana-4845	248	15	.	.	PUNCT
cana-4845	249	1	the	the	DET
cana-4845	249	2	following	follow	VERB
cana-4845	249	3	formulas	formula	NOUN
cana-4845	249	4	are	be	AUX
cana-4845	249	5	used	use	VERB
cana-4845	249	6	to	to	PART
cana-4845	249	7	calculate	calculate	VERB
cana-4845	249	8	each	each	PRON
cana-4845	249	9	of	of	ADP
cana-4845	249	10	these	these	DET
cana-4845	249	11	figures	figure	NOUN
cana-4845	249	12	:	:	PUNCT
cana-4845	249	13	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	𝐴𝑐𝑐𝑢𝑟𝑎𝑐𝑦	PROPN
cana-4845	249	14	=	=	SYM
cana-4845	249	15	𝑇𝑃	𝑇𝑃	PROPN
cana-4845	249	16	+	+	CCONJ
cana-4845	249	17	𝑇𝑁	𝑇𝑁	PROPN
cana-4845	249	18	𝑇𝑃	𝑇𝑃	PROPN
cana-4845	249	19	+	+	CCONJ
cana-4845	249	20	𝑇𝑁	𝑇𝑁	PROPN
cana-4845	249	21	+	+	X
cana-4845	249	22	𝐹𝑁	𝐹𝑁	PROPN
cana-4845	249	23	+	+	X
cana-4845	249	24	𝐹𝑃	𝐹𝑃	PROPN
cana-4845	249	25	(	(	PUNCT
cana-4845	249	26	12	12	NUM
cana-4845	249	27	)	)	PUNCT
cana-4845	249	28	𝑆𝑒𝑙𝑒𝑐𝑡𝑖𝑣𝑖𝑡𝑦	𝑆𝑒𝑙𝑒𝑐𝑡𝑖𝑣𝑖𝑡𝑦	PROPN
cana-4845	249	29	=	=	SYM
cana-4845	249	30	𝑇𝑃	𝑇𝑃	PROPN
cana-4845	249	31	𝑇𝑃	𝑇𝑃	PROPN
cana-4845	249	32	+	+	CCONJ
cana-4845	249	33	𝐹𝑃	𝐹𝑃	PROPN
cana-4845	249	34	(	(	PUNCT
cana-4845	249	35	14	14	NUM
cana-4845	249	36	)	)	PUNCT
cana-4845	249	37	𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦	𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦	PROPN
cana-4845	249	38	=	=	SYM
cana-4845	249	39	𝑇𝑁	𝑇𝑁	PROPN
cana-4845	249	40	𝑇𝑁	𝑇𝑁	PROPN
cana-4845	249	41	+	+	X
cana-4845	249	42	𝐹𝑁	𝐹𝑁	PROPN
cana-4845	249	43	(	(	PUNCT
cana-4845	249	44	15	15	NUM
cana-4845	249	45	)	)	PUNCT
cana-4845	249	46	fp	fp	X
cana-4845	249	47	is	be	AUX
cana-4845	249	48	falsely	falsely	ADV
cana-4845	249	49	positive	positive	ADJ
cana-4845	249	50	,	,	PUNCT
cana-4845	249	51	fn	fn	ADV
cana-4845	249	52	is	be	AUX
cana-4845	249	53	falsely	falsely	ADV
cana-4845	249	54	negative	negative	ADJ
cana-4845	249	55	,	,	PUNCT
cana-4845	249	56	tp	tp	PART
cana-4845	249	57	is	be	AUX
cana-4845	249	58	true	true	ADJ
cana-4845	249	59	positive	positive	ADJ
cana-4845	249	60	,	,	PUNCT
cana-4845	249	61	and	and	CCONJ
cana-4845	249	62	tn	tn	NOUN
cana-4845	249	63	is	be	AUX
cana-4845	249	64	true	true	ADJ
cana-4845	249	65	negative	negative	ADJ
cana-4845	249	66	.	.	PUNCT
cana-4845	250	1	features	feature	NOUN
cana-4845	250	2	taken	take	VERB
cana-4845	250	3	from	from	ADP
cana-4845	250	4	eeg	eeg	NOUN
cana-4845	250	5	signals	signal	NOUN
cana-4845	250	6	are	be	AUX
cana-4845	250	7	shown	show	VERB
cana-4845	250	8	in	in	ADP
cana-4845	250	9	table	table	NOUN
cana-4845	250	10	2	2	NUM
cana-4845	250	11	.	.	X
cana-4845	250	12	eeg	eeg	PROPN
cana-4845	250	13	signal	signal	NOUN
cana-4845	250	14	hjorth	hjorth	NOUN
cana-4845	250	15	activity	activity	NOUN
cana-4845	250	16	hjorth	hjorth	NOUN
cana-4845	250	17	hjorth	hjorth	NOUN
cana-4845	250	18	mobility	mobility	NOUN
cana-4845	250	19	band	band	NOUN
cana-4845	250	20	power	power	NOUN
cana-4845	250	21	alpha	alpha	NOUN
cana-4845	250	22	complexity	complexity	NOUN
cana-4845	250	23	hs1ec	hs1ec	PROPN
cana-4845	250	24	310	310	NUM
cana-4845	250	25	4.3	4.3	NUM
cana-4845	250	26	0.18	0.18	NUM
cana-4845	250	27	6	6	NUM
cana-4845	250	28	hs1eo	hs1eo	NOUN
cana-4845	250	29	360	360	NUM
cana-4845	250	30	4.4	4.4	NUM
cana-4845	250	31	0.18	0.18	NUM
cana-4845	250	32	9	9	NUM
cana-4845	250	33	hs1task	hs1task	NOUN
cana-4845	250	34	360	360	NUM
cana-4845	250	35	3.1	3.1	NUM
cana-4845	250	36	0.34	0.34	NUM
cana-4845	250	37	140	140	NUM
cana-4845	250	38	hs2ec	hs2ec	NOUN
cana-4845	250	39	960	960	NUM
cana-4845	250	40	4.7	4.7	NUM
cana-4845	250	41	0.13	0.13	NUM
cana-4845	250	42	6.8	6.8	NUM
cana-4845	250	43	hs2eo	hs2eo	NOUN
cana-4845	250	44	900	900	NUM
cana-4845	250	45	6.6	6.6	NUM
cana-4845	250	46	0.086	0.086	NUM
cana-4845	250	47	37	37	NUM
cana-4845	250	48	hs2task	hs2task	NOUN
cana-4845	250	49	360	360	NUM
cana-4845	250	50	3.1	3.1	NUM
cana-4845	250	51	0.34	0.34	NUM
cana-4845	250	52	140	140	NUM
cana-4845	250	53	ds1ec	ds1ec	NOUN
cana-4845	250	54	60	60	NUM
cana-4845	250	55	1.9	1.9	NUM
cana-4845	250	56	0.3	0.3	NUM
cana-4845	250	57	4.2	4.2	NUM
cana-4845	250	58	ds1eo	ds1eo	ADP
cana-4845	250	59	130	130	NUM
cana-4845	250	60	3.1	3.1	NUM
cana-4845	250	61	0.17	0.17	NUM
cana-4845	250	62	12	12	NUM
cana-4845	250	63	ds1task	ds1task	NOUN
cana-4845	250	64	370	370	NUM
cana-4845	250	65	3.6	3.6	NUM
cana-4845	250	66	0.14	0.14	NUM
cana-4845	250	67	40	40	NUM
cana-4845	250	68	ds2ec	ds2ec	NUM
cana-4845	250	69	130	130	NUM
cana-4845	250	70	1.8	1.8	NUM
cana-4845	250	71	0.25	0.25	NUM
cana-4845	250	72	9.4	9.4	NUM
cana-4845	250	73	ds2eo	ds2eo	NOUN
cana-4845	250	74	480	480	NUM
cana-4845	250	75	3.4	3.4	NUM
cana-4845	250	76	0.13	0.13	NUM
cana-4845	250	77	87	87	NUM
cana-4845	250	78	ds2task	ds2task	SYM
cana-4845	250	79	1900	1900	NUM
cana-4845	250	80	2.6	2.6	NUM
cana-4845	250	81	0.63	0.63	NUM
cana-4845	250	82	20	20	NUM
cana-4845	250	83	the	the	DET
cana-4845	250	84	preprocessed	preprocesse	VERB
cana-4845	250	85	ecg	ecg	PROPN
cana-4845	250	86	data	datum	NOUN
cana-4845	250	87	used	use	VERB
cana-4845	250	88	for	for	ADP
cana-4845	250	89	categorization	categorization	NOUN
cana-4845	250	90	takes	take	VERB
cana-4845	250	91	longer	long	ADV
cana-4845	250	92	and	and	CCONJ
cana-4845	250	93	has	have	VERB
cana-4845	250	94	a	a	DET
cana-4845	250	95	50	50	NUM
cana-4845	250	96	%	%	NOUN
cana-4845	250	97	to	to	PART
cana-4845	250	98	60	60	NUM
cana-4845	250	99	%	%	NOUN
cana-4845	250	100	lower	low	ADJ
cana-4845	250	101	accuracy	accuracy	NOUN
cana-4845	250	102	rate	rate	NOUN
cana-4845	250	103	.	.	PUNCT
cana-4845	251	1	as	as	SCONJ
cana-4845	251	2	seen	see	VERB
cana-4845	251	3	in	in	ADP
cana-4845	251	4	figure	figure	NOUN
cana-4845	251	5	5	5	NUM
cana-4845	251	6	,	,	PUNCT
cana-4845	251	7	training	training	NOUN
cana-4845	251	8	time	time	NOUN
cana-4845	251	9	is	be	AUX
cana-4845	251	10	reduced	reduce	VERB
cana-4845	251	11	and	and	CCONJ
cana-4845	251	12	accuracy	accuracy	NOUN
cana-4845	251	13	is	be	AUX
cana-4845	251	14	increased	increase	VERB
cana-4845	251	15	by	by	ADP
cana-4845	251	16	up	up	ADP
cana-4845	251	17	to	to	PART
cana-4845	251	18	93	93	NUM
cana-4845	251	19	%	%	NOUN
cana-4845	251	20	if	if	SCONJ
cana-4845	251	21	the	the	DET
cana-4845	251	22	ecg	ecg	PROPN
cana-4845	251	23	signal	signal	NOUN
cana-4845	251	24	's	's	PART
cana-4845	251	25	salient	salient	NOUN
cana-4845	251	26	features	feature	NOUN
cana-4845	251	27	are	be	AUX
cana-4845	251	28	extracted	extract	VERB
cana-4845	251	29	and	and	CCONJ
cana-4845	251	30	transmitted	transmit	VERB
cana-4845	251	31	for	for	ADP
cana-4845	251	32	classification	classification	NOUN
cana-4845	251	33	.	.	PUNCT
cana-4845	252	1	numerous	numerous	ADJ
cana-4845	252	2	iterations	iteration	NOUN
cana-4845	252	3	throughout	throughout	ADP
cana-4845	252	4	the	the	DET
cana-4845	252	5	training	training	NOUN
cana-4845	252	6	procedure	procedure	NOUN
cana-4845	252	7	increase	increase	NOUN
cana-4845	252	8	accuracy	accuracy	NOUN
cana-4845	252	9	and	and	CCONJ
cana-4845	252	10	decrease	decrease	VERB
cana-4845	252	11	the	the	DET
cana-4845	252	12	loss	loss	NOUN
cana-4845	252	13	function	function	NOUN
cana-4845	252	14	.	.	PUNCT
cana-4845	253	1	setting	set	VERB
cana-4845	253	2	the	the	DET
cana-4845	253	3	maximum	maximum	ADJ
cana-4845	253	4	number	number	NOUN
cana-4845	253	5	of	of	ADP
cana-4845	253	6	epochs	epoch	NOUN
cana-4845	253	7	during	during	ADP
cana-4845	253	8	training	training	NOUN
cana-4845	253	9	will	will	AUX
cana-4845	253	10	enable	enable	VERB
cana-4845	253	11	the	the	DET
cana-4845	253	12	network	network	NOUN
cana-4845	253	13	to	to	PART
cana-4845	253	14	run	run	VERB
cana-4845	253	15	through	through	ADP
cana-4845	253	16	the	the	DET
cana-4845	253	17	training	training	NOUN
cana-4845	253	18	data	datum	NOUN
cana-4845	253	19	a	a	DET
cana-4845	253	20	certain	certain	ADJ
cana-4845	253	21	number	number	NOUN
cana-4845	253	22	of	of	ADP
cana-4845	253	23	times	time	NOUN
cana-4845	253	24	.	.	PUNCT
cana-4845	254	1	the	the	DET
cana-4845	254	2	maximum	maximum	ADJ
cana-4845	254	3	batch	batch	NOUN
cana-4845	254	4	size	size	NOUN
cana-4845	254	5	is	be	AUX
cana-4845	254	6	varied	varied	ADJ
cana-4845	254	7	from	from	ADP
cana-4845	254	8	30	30	NUM
cana-4845	254	9	to	to	PART
cana-4845	254	10	100	100	NUM
cana-4845	254	11	throughout	throughout	ADP
cana-4845	254	12	the	the	DET
cana-4845	254	13	course	course	NOUN
cana-4845	254	14	communications	communication	NOUN
cana-4845	254	15	on	on	ADP
cana-4845	254	16	applied	apply	VERB
cana-4845	254	17	nonlinear	nonlinear	ADJ
cana-4845	254	18	analysis	analysis	NOUN
cana-4845	254	19	issn	issn	NOUN
cana-4845	254	20	:	:	PUNCT
cana-4845	254	21	1074	1074	NUM
cana-4845	254	22	-	-	PUNCT
cana-4845	254	23	133x	133x	NUM
cana-4845	254	24	vol	vol	VERB
cana-4845	254	25	32	32	NUM
cana-4845	254	26	no	no	NOUN
cana-4845	254	27	.	.	PUNCT
cana-4845	255	1	10s	10	NOUN
cana-4845	255	2	(	(	PUNCT
cana-4845	255	3	2025	2025	NUM
cana-4845	255	4	)	)	PUNCT
cana-4845	255	5	557	557	NUM
cana-4845	255	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	255	7	of	of	ADP
cana-4845	255	8	10	10	NUM
cana-4845	255	9	epochs	epoch	NOUN
cana-4845	255	10	.	.	PUNCT
cana-4845	256	1	we	we	PRON
cana-4845	256	2	can	can	AUX
cana-4845	256	3	set	set	VERB
cana-4845	256	4	a	a	DET
cana-4845	256	5	maximum	maximum	ADJ
cana-4845	256	6	batch	batch	NOUN
cana-4845	256	7	size	size	NOUN
cana-4845	256	8	of	of	ADP
cana-4845	256	9	100	100	NUM
cana-4845	256	10	and	and	CCONJ
cana-4845	256	11	observe	observe	VERB
cana-4845	256	12	training	training	NOUN
cana-4845	256	13	and	and	CCONJ
cana-4845	256	14	testing	testing	NOUN
cana-4845	256	15	accuracy	accuracy	NOUN
cana-4845	256	16	since	since	SCONJ
cana-4845	256	17	above	above	ADP
cana-4845	256	18	100	100	NUM
cana-4845	256	19	,	,	PUNCT
cana-4845	256	20	a	a	DET
cana-4845	256	21	memory	memory	NOUN
cana-4845	256	22	problem	problem	NOUN
cana-4845	256	23	occurs	occur	VERB
cana-4845	256	24	.	.	PUNCT
cana-4845	257	1	when	when	SCONJ
cana-4845	257	2	compared	compare	VERB
cana-4845	257	3	to	to	ADP
cana-4845	257	4	other	other	ADJ
cana-4845	257	5	batch	batch	NOUN
cana-4845	257	6	sizes	size	NOUN
cana-4845	257	7	,	,	PUNCT
cana-4845	257	8	the	the	DET
cana-4845	257	9	maximum	maximum	ADJ
cana-4845	257	10	batch	batch	NOUN
cana-4845	257	11	size	size	NOUN
cana-4845	257	12	of	of	ADP
cana-4845	257	13	100	100	NUM
cana-4845	257	14	performs	perform	NOUN
cana-4845	257	15	better	well	ADV
cana-4845	257	16	.	.	PUNCT
cana-4845	258	1	following	follow	VERB
cana-4845	258	2	that	that	PRON
cana-4845	258	3	,	,	PUNCT
cana-4845	258	4	epochs	epoch	NOUN
cana-4845	258	5	are	be	AUX
cana-4845	258	6	regarded	regard	VERB
cana-4845	258	7	as	as	ADP
cana-4845	258	8	10	10	NUM
cana-4845	258	9	,	,	PUNCT
cana-4845	258	10	20	20	NUM
cana-4845	258	11	,	,	PUNCT
cana-4845	258	12	and	and	CCONJ
cana-4845	258	13	30	30	NUM
cana-4845	258	14	,	,	PUNCT
cana-4845	258	15	and	and	CCONJ
cana-4845	258	16	the	the	DET
cana-4845	258	17	maximum	maximum	ADJ
cana-4845	258	18	batch	batch	NOUN
cana-4845	258	19	size	size	NOUN
cana-4845	258	20	is	be	AUX
cana-4845	258	21	maintained	maintain	VERB
cana-4845	258	22	at	at	ADP
cana-4845	258	23	100	100	NUM
cana-4845	258	24	.	.	PUNCT
cana-4845	259	1	high	high	ADJ
cana-4845	259	2	accuracy	accuracy	NOUN
cana-4845	259	3	is	be	AUX
cana-4845	259	4	obtained	obtain	VERB
cana-4845	259	5	if	if	SCONJ
cana-4845	259	6	the	the	DET
cana-4845	259	7	batch	batch	NOUN
cana-4845	259	8	size	size	NOUN
cana-4845	259	9	and	and	CCONJ
cana-4845	259	10	epoch	epoch	NOUN
cana-4845	259	11	number	number	NOUN
cana-4845	259	12	are	be	AUX
cana-4845	259	13	greater	great	ADJ
cana-4845	259	14	.	.	PUNCT
cana-4845	260	1	depending	depend	VERB
cana-4845	260	2	on	on	ADP
cana-4845	260	3	system	system	NOUN
cana-4845	260	4	ram	ram	NOUN
cana-4845	260	5	,	,	PUNCT
cana-4845	260	6	that	that	PRON
cana-4845	260	7	may	may	AUX
cana-4845	260	8	change	change	VERB
cana-4845	260	9	.	.	PUNCT
cana-4845	261	1	we	we	PRON
cana-4845	261	2	used	use	VERB
cana-4845	261	3	a	a	DET
cana-4845	261	4	batch	batch	NOUN
cana-4845	261	5	size	size	NOUN
cana-4845	261	6	of	of	ADP
cana-4845	261	7	100	100	NUM
cana-4845	261	8	and	and	CCONJ
cana-4845	261	9	epochs	epoch	NOUN
cana-4845	261	10	of	of	ADP
cana-4845	261	11	30	30	NUM
cana-4845	261	12	in	in	ADP
cana-4845	261	13	this	this	DET
cana-4845	261	14	experiment	experiment	NOUN
cana-4845	261	15	.	.	PUNCT
cana-4845	262	1	numerous	numerous	ADJ
cana-4845	262	2	experiments	experiment	NOUN
cana-4845	262	3	and	and	CCONJ
cana-4845	262	4	practical	practical	ADJ
cana-4845	262	5	studies	study	NOUN
cana-4845	262	6	demonstrate	demonstrate	VERB
cana-4845	262	7	that	that	SCONJ
cana-4845	262	8	,	,	PUNCT
cana-4845	262	9	for	for	ADP
cana-4845	262	10	ecg	ecg	PROPN
cana-4845	262	11	signals	signal	NOUN
cana-4845	262	12	,	,	PUNCT
cana-4845	262	13	as	as	SCONJ
cana-4845	262	14	depicted	depict	VERB
cana-4845	262	15	in	in	ADP
cana-4845	262	16	figure	figure	NOUN
cana-4845	262	17	5	5	NUM
cana-4845	262	18	,	,	PUNCT
cana-4845	262	19	the	the	DET
cana-4845	262	20	performance	performance	NOUN
cana-4845	262	21	metrics	metric	NOUN
cana-4845	262	22	of	of	ADP
cana-4845	262	23	two	two	NUM
cana-4845	262	24	-	-	PUNCT
cana-4845	262	25	dimensional	dimensional	ADJ
cana-4845	262	26	sequence	sequence	NOUN
cana-4845	262	27	input	input	NOUN
cana-4845	262	28	to	to	ADP
cana-4845	262	29	the	the	DET
cana-4845	262	30	network	network	NOUN
cana-4845	262	31	,	,	PUNCT
cana-4845	262	32	such	such	ADJ
cana-4845	262	33	as	as	ADP
cana-4845	262	34	accuracy	accuracy	NOUN
cana-4845	262	35	,	,	PUNCT
cana-4845	262	36	sensitivity	sensitivity	NOUN
cana-4845	262	37	,	,	PUNCT
cana-4845	262	38	selectivity	selectivity	NOUN
cana-4845	262	39	,	,	PUNCT
cana-4845	262	40	and	and	CCONJ
cana-4845	262	41	specificity	specificity	NOUN
cana-4845	262	42	,	,	PUNCT
cana-4845	262	43	are	be	AUX
cana-4845	262	44	higher	high	ADJ
cana-4845	262	45	than	than	ADP
cana-4845	262	46	those	those	PRON
cana-4845	262	47	of	of	ADP
cana-4845	262	48	one	one	NUM
cana-4845	262	49	-	-	PUNCT
cana-4845	262	50	dimensional	dimensional	ADJ
cana-4845	262	51	sequence	sequence	NOUN
cana-4845	262	52	input	input	NOUN
cana-4845	262	53	.	.	PUNCT
cana-4845	263	1	the	the	DET
cana-4845	263	2	accuracy	accuracy	NOUN
cana-4845	263	3	of	of	ADP
cana-4845	263	4	svm	svm	PROPN
cana-4845	263	5	and	and	CCONJ
cana-4845	263	6	cnn	cnn	PROPN
cana-4845	263	7	for	for	ADP
cana-4845	263	8	eeg	eeg	NOUN
cana-4845	263	9	signals	signal	NOUN
cana-4845	263	10	is	be	AUX
cana-4845	263	11	displayed	display	VERB
cana-4845	263	12	in	in	ADP
cana-4845	263	13	table	table	NOUN
cana-4845	263	14	(	(	PUNCT
cana-4845	263	15	3	3	NUM
cana-4845	263	16	)	)	PUNCT
cana-4845	263	17	.	.	PUNCT
cana-4845	264	1	table	table	NOUN
cana-4845	264	2	3	3	NUM
cana-4845	264	3	:	:	PUNCT
cana-4845	264	4	svm	svm	PROPN
cana-4845	264	5	and	and	CCONJ
cana-4845	264	6	cnn	cnn	PROPN
cana-4845	264	7	accuracy	accuracy	NOUN
cana-4845	264	8	figure	figure	NOUN
cana-4845	264	9	5	5	NUM
cana-4845	264	10	shows	show	VERB
cana-4845	264	11	the	the	DET
cana-4845	264	12	depression	depression	NOUN
cana-4845	264	13	system	system	NOUN
cana-4845	264	14	's	's	PART
cana-4845	264	15	performance	performance	NOUN
cana-4845	264	16	metrics	metric	NOUN
cana-4845	264	17	using	use	VERB
cana-4845	264	18	ecg	ecg	PROPN
cana-4845	264	19	data	datum	NOUN
cana-4845	264	20	.	.	PUNCT
cana-4845	265	1	60	60	NUM
cana-4845	265	2	%	%	NOUN
cana-4845	265	3	59	59	NUM
cana-4845	265	4	%	%	NOUN
cana-4845	265	5	66	66	NUM
cana-4845	265	6	%	%	NOUN
cana-4845	265	7	61	61	NUM
cana-4845	265	8	%	%	NOUN
cana-4845	265	9	59	59	NUM
cana-4845	265	10	%	%	NOUN
cana-4845	265	11	58	58	NUM
cana-4845	265	12	%	%	NOUN
cana-4845	265	13	67	67	NUM
cana-4845	265	14	%	%	NOUN
cana-4845	265	15	61	61	NUM
cana-4845	265	16	%	%	NOUN
cana-4845	265	17	93	93	NUM
cana-4845	265	18	%	%	NOUN
cana-4845	265	19	97	97	NUM
cana-4845	265	20	%	%	NOUN
cana-4845	265	21	85	85	NUM
cana-4845	265	22	%	%	NOUN
cana-4845	265	23	98	98	NUM
cana-4845	265	24	%	%	NOUN
cana-4845	265	25	91	91	NUM
cana-4845	265	26	%	%	NOUN
cana-4845	265	27	97	97	NUM
cana-4845	265	28	%	%	NOUN
cana-4845	265	29	74	74	NUM
cana-4845	265	30	%	%	NOUN
cana-4845	265	31	79	79	NUM
cana-4845	265	32	%	%	NOUN
cana-4845	265	33	0	0	NUM
cana-4845	265	34	%	%	NOUN
cana-4845	265	35	10	10	NUM
cana-4845	265	36	%	%	NOUN
cana-4845	265	37	20	20	NUM
cana-4845	265	38	%	%	NOUN
cana-4845	265	39	30	30	NUM
cana-4845	265	40	%	%	NOUN
cana-4845	265	41	40	40	NUM
cana-4845	265	42	%	%	NOUN
cana-4845	265	43	50	50	NUM
cana-4845	265	44	%	%	NOUN
cana-4845	265	45	60	60	NUM
cana-4845	265	46	%	%	NOUN
cana-4845	265	47	70	70	NUM
cana-4845	265	48	%	%	NOUN
cana-4845	265	49	80	80	NUM
cana-4845	265	50	%	%	NOUN
cana-4845	265	51	90	90	NUM
cana-4845	265	52	%	%	NOUN
cana-4845	265	53	100	100	NUM
cana-4845	265	54	%	%	NOUN
cana-4845	265	55	1	1	NUM
cana-4845	265	56	)	)	PUNCT
cana-4845	265	57	a	a	DET
cana-4845	265	58	cc	cc	X
cana-4845	265	59	u	u	NOUN
cana-4845	265	60	ra	ra	PROPN
cana-4845	265	61	cy	cy	ADP
cana-4845	265	62	2	2	NUM
cana-4845	265	63	)	)	PUNCT
cana-4845	265	64	s	s	PART
cana-4845	265	65	en	en	X
cana-4845	265	66	si	si	X
cana-4845	265	67	ti	ti	PROPN
cana-4845	265	68	v	v	ADP
cana-4845	265	69	it	it	PRON
cana-4845	265	70	y	y	PROPN
cana-4845	265	71	3	3	NUM
cana-4845	265	72	)	)	PUNCT
cana-4845	265	73	s	s	AUX
cana-4845	265	74	el	el	PROPN
cana-4845	265	75	ec	ec	PROPN
cana-4845	265	76	ti	ti	PROPN
cana-4845	265	77	v	v	ADP
cana-4845	265	78	it	it	PRON
cana-4845	265	79	y	y	PROPN
cana-4845	265	80	4	4	NUM
cana-4845	265	81	)	)	PUNCT
cana-4845	265	82	s	s	AUX
cana-4845	265	83	p	p	X
cana-4845	265	84	ec	ec	PROPN
cana-4845	265	85	if	if	SCONJ
cana-4845	265	86	ic	ic	PROPN
cana-4845	265	87	it	it	PRON
cana-4845	265	88	y	y	PROPN
cana-4845	265	89	1	1	NUM
cana-4845	265	90	)	)	PUNCT
cana-4845	265	91	a	a	DET
cana-4845	265	92	cc	cc	X
cana-4845	265	93	u	u	NOUN
cana-4845	265	94	ra	ra	PROPN
cana-4845	265	95	cy	cy	ADP
cana-4845	265	96	2	2	NUM
cana-4845	265	97	)	)	PUNCT
cana-4845	265	98	s	s	PART
cana-4845	265	99	en	en	X
cana-4845	265	100	si	si	X
cana-4845	265	101	ti	ti	PROPN
cana-4845	265	102	v	v	ADP
cana-4845	265	103	it	it	PRON
cana-4845	265	104	y	y	PROPN
cana-4845	265	105	3	3	NUM
cana-4845	265	106	)	)	PUNCT
cana-4845	265	107	s	s	AUX
cana-4845	265	108	el	el	PROPN
cana-4845	265	109	ec	ec	PROPN
cana-4845	265	110	ti	ti	PROPN
cana-4845	265	111	v	v	ADP
cana-4845	265	112	it	it	PRON
cana-4845	265	113	y	y	PROPN
cana-4845	265	114	4	4	NUM
cana-4845	265	115	)	)	PUNCT
cana-4845	265	116	s	s	VERB
cana-4845	265	117	p	p	X
cana-4845	265	118	ec	ec	PROPN
cana-4845	265	119	if	if	SCONJ
cana-4845	265	120	ic	ic	PROPN
cana-4845	265	121	it	it	PRON
cana-4845	266	1	y	y	PROPN
cana-4845	266	2	training	training	NOUN
cana-4845	266	3	process	process	NOUN
cana-4845	266	4	testing	testing	NOUN
cana-4845	266	5	process	process	NOUN
cana-4845	266	6	performance	performance	NOUN
cana-4845	266	7	parameters	parameter	NOUN
cana-4845	266	8	1	1	NUM
cana-4845	266	9	-	-	SYM
cana-4845	266	10	d	d	NOUN
cana-4845	266	11	2	2	NUM
cana-4845	266	12	-	-	PUNCT
cana-4845	266	13	d	d	NOUN
cana-4845	266	14	sr	sr	PROPN
cana-4845	266	15	.	.	PUNCT
cana-4845	267	1	no	no	INTJ
cana-4845	267	2	.	.	PUNCT
cana-4845	267	3	model	model	NOUN
cana-4845	267	4	accuracy	accuracy	NOUN
cana-4845	267	5	1	1	NUM
cana-4845	267	6	.	.	PUNCT
cana-4845	267	7	cnn	cnn	PROPN
cana-4845	268	1	97.69	97.69	NUM
cana-4845	268	2	%	%	NOUN
cana-4845	268	3	2	2	NUM
cana-4845	268	4	.	.	PUNCT
cana-4845	268	5	svm	svm	PROPN
cana-4845	268	6	76	76	NUM
cana-4845	268	7	%	%	NOUN
cana-4845	268	8	communications	communication	NOUN
cana-4845	268	9	on	on	ADP
cana-4845	268	10	applied	apply	VERB
cana-4845	268	11	nonlinear	nonlinear	ADJ
cana-4845	268	12	analysis	analysis	NOUN
cana-4845	268	13	issn	issn	NOUN
cana-4845	268	14	:	:	PUNCT
cana-4845	268	15	1074	1074	NUM
cana-4845	268	16	-	-	PUNCT
cana-4845	268	17	133x	133x	NUM
cana-4845	268	18	vol	vol	VERB
cana-4845	268	19	32	32	NUM
cana-4845	268	20	no	no	NOUN
cana-4845	268	21	.	.	PUNCT
cana-4845	269	1	10s	10	NOUN
cana-4845	269	2	(	(	PUNCT
cana-4845	269	3	2025	2025	NUM
cana-4845	269	4	)	)	PUNCT
cana-4845	269	5	558	558	NUM
cana-4845	269	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	269	7	5	5	NUM
cana-4845	269	8	.	.	PUNCT
cana-4845	269	9	final	final	ADJ
cana-4845	269	10	comment	comment	NOUN
cana-4845	269	11	the	the	DET
cana-4845	269	12	current	current	ADJ
cana-4845	269	13	approach	approach	NOUN
cana-4845	269	14	uses	use	VERB
cana-4845	269	15	ffts	fft	NOUN
cana-4845	269	16	and	and	CCONJ
cana-4845	269	17	wavelet	wavelet	NOUN
cana-4845	269	18	transforms	transform	VERB
cana-4845	269	19	to	to	PART
cana-4845	269	20	extract	extract	VERB
cana-4845	269	21	features	feature	NOUN
cana-4845	269	22	from	from	ADP
cana-4845	269	23	eeg	eeg	PROPN
cana-4845	269	24	and	and	CCONJ
cana-4845	269	25	ecg	ecg	PROPN
cana-4845	269	26	signals	signal	NOUN
cana-4845	269	27	.	.	PUNCT
cana-4845	270	1	for	for	ADP
cana-4845	270	2	eeg	eeg	NOUN
cana-4845	270	3	signals	signal	NOUN
cana-4845	270	4	,	,	PUNCT
cana-4845	270	5	the	the	DET
cana-4845	270	6	most	most	ADV
cana-4845	270	7	important	important	ADJ
cana-4845	270	8	characteristics	characteristic	NOUN
cana-4845	270	9	are	be	AUX
cana-4845	270	10	hjorth	hjorth	NOUN
cana-4845	270	11	activity	activity	NOUN
cana-4845	270	12	(	(	PUNCT
cana-4845	270	13	ha	ha	INTJ
cana-4845	270	14	)	)	PUNCT
cana-4845	270	15	,	,	PUNCT
cana-4845	270	16	standard	standard	ADJ
cana-4845	270	17	deviation	deviation	NOUN
cana-4845	270	18	,	,	PUNCT
cana-4845	270	19	entropy	entropy	NOUN
cana-4845	270	20	,	,	PUNCT
cana-4845	270	21	and	and	CCONJ
cana-4845	270	22	band	band	NOUN
cana-4845	270	23	power	power	NOUN
cana-4845	270	24	alpha	alpha	NOUN
cana-4845	270	25	;	;	PUNCT
cana-4845	270	26	for	for	ADP
cana-4845	270	27	ecg	ecg	PROPN
cana-4845	270	28	signals	signal	NOUN
cana-4845	270	29	,	,	PUNCT
cana-4845	270	30	the	the	DET
cana-4845	270	31	arithmetic	arithmetic	ADJ
cana-4845	270	32	mean	mean	NOUN
cana-4845	270	33	is	be	AUX
cana-4845	270	34	important	important	ADJ
cana-4845	270	35	.	.	PUNCT
cana-4845	271	1	higher	high	ADJ
cana-4845	271	2	accuracy	accuracy	NOUN
cana-4845	271	3	,	,	PUNCT
cana-4845	271	4	sensitivity	sensitivity	NOUN
cana-4845	271	5	,	,	PUNCT
cana-4845	271	6	selectivity	selectivity	NOUN
cana-4845	271	7	,	,	PUNCT
cana-4845	271	8	and	and	CCONJ
cana-4845	271	9	specificity	specificity	NOUN
cana-4845	271	10	are	be	AUX
cana-4845	271	11	achieved	achieve	VERB
cana-4845	271	12	when	when	SCONJ
cana-4845	271	13	using	use	VERB
cana-4845	271	14	an	an	DET
cana-4845	271	15	rnn	rnn	NOUN
cana-4845	271	16	and	and	CCONJ
cana-4845	271	17	an	an	DET
cana-4845	271	18	lstm	lstm	ADJ
cana-4845	271	19	auto	auto	NOUN
cana-4845	271	20	encoder	encoder	NOUN
cana-4845	271	21	with	with	ADP
cana-4845	271	22	two	two	NUM
cana-4845	271	23	-	-	PUNCT
cana-4845	271	24	dimensional	dimensional	ADJ
cana-4845	271	25	sequence	sequence	NOUN
cana-4845	271	26	input	input	NOUN
cana-4845	271	27	as	as	ADP
cana-4845	271	28	classifiers	classifier	NOUN
cana-4845	271	29	.	.	PUNCT
cana-4845	272	1	for	for	ADP
cana-4845	272	2	ecg	ecg	PROPN
cana-4845	272	3	signals	signal	NOUN
cana-4845	272	4	,	,	PUNCT
cana-4845	272	5	the	the	DET
cana-4845	272	6	current	current	ADJ
cana-4845	272	7	system	system	NOUN
cana-4845	272	8	achieves	achieve	VERB
cana-4845	272	9	93	93	NUM
cana-4845	272	10	%	%	NOUN
cana-4845	272	11	accuracy	accuracy	NOUN
cana-4845	272	12	.	.	PUNCT
cana-4845	273	1	cnn	cnn	PROPN
cana-4845	273	2	outperforms	outperform	VERB
cana-4845	273	3	svm	svm	ADJ
cana-4845	273	4	in	in	ADP
cana-4845	273	5	terms	term	NOUN
cana-4845	273	6	of	of	ADP
cana-4845	273	7	accuracy	accuracy	NOUN
cana-4845	273	8	(	(	PUNCT
cana-4845	273	9	97.69	97.69	NUM
cana-4845	273	10	%	%	NOUN
cana-4845	273	11	)	)	PUNCT
cana-4845	273	12	for	for	ADP
cana-4845	273	13	eeg	eeg	NOUN
cana-4845	273	14	signals	signal	NOUN
cana-4845	273	15	.	.	PUNCT
cana-4845	274	1	assertive	assertive	ADJ
cana-4845	274	2	the	the	DET
cana-4845	274	3	author	author	NOUN
cana-4845	274	4	expresses	express	VERB
cana-4845	274	5	gratitude	gratitude	NOUN
cana-4845	274	6	to	to	PART
cana-4845	274	7	drs	drs	VERB
cana-4845	274	8	.	.	PUNCT
cana-4845	275	1	vinayak	vinayak	PROPN
cana-4845	275	2	k.	k.	PROPN
cana-4845	275	3	biragi	biragi	PROPN
cana-4845	275	4	and	and	CCONJ
cana-4845	275	5	shobha	shobha	NOUN
cana-4845	275	6	nikam	nikam	NOUN
cana-4845	275	7	for	for	ADP
cana-4845	275	8	their	their	PRON
cana-4845	275	9	invaluable	invaluable	ADJ
cana-4845	275	10	counsel	counsel	NOUN
cana-4845	275	11	and	and	CCONJ
cana-4845	275	12	support	support	NOUN
cana-4845	275	13	.	.	PUNCT
cana-4845	276	1	your	your	PRON
cana-4845	276	2	time	time	NOUN
cana-4845	276	3	away	away	ADV
cana-4845	276	4	from	from	ADP
cana-4845	276	5	your	your	PRON
cana-4845	276	6	personal	personal	ADJ
cana-4845	276	7	life	life	NOUN
cana-4845	276	8	to	to	PART
cana-4845	276	9	finish	finish	VERB
cana-4845	276	10	all	all	PRON
cana-4845	276	11	of	of	ADP
cana-4845	276	12	his	his	PRON
cana-4845	276	13	work	work	NOUN
cana-4845	276	14	is	be	AUX
cana-4845	276	15	greatly	greatly	ADV
cana-4845	276	16	appreciated	appreciated	ADJ
cana-4845	276	17	.	.	PUNCT
cana-4845	277	1	we	we	PRON
cana-4845	277	2	express	express	VERB
cana-4845	277	3	our	our	PRON
cana-4845	277	4	gratitude	gratitude	NOUN
cana-4845	277	5	to	to	ADP
cana-4845	277	6	neurologist	neurologist	PROPN
cana-4845	277	7	dr	dr	PROPN
cana-4845	277	8	.	.	PROPN
cana-4845	277	9	mahabal	mahabal	PROPN
cana-4845	277	10	shah	shah	PROPN
cana-4845	277	11	and	and	CCONJ
cana-4845	277	12	psychiatrist	psychiatrist	PROPN
cana-4845	277	13	dr	dr	PROPN
cana-4845	277	14	.	.	PROPN
cana-4845	277	15	pawar	pawar	PROPN
cana-4845	277	16	.	.	PUNCT
cana-4845	278	1	we	we	PRON
cana-4845	278	2	also	also	ADV
cana-4845	278	3	like	like	VERB
cana-4845	278	4	to	to	PART
cana-4845	278	5	thank	thank	VERB
cana-4845	278	6	the	the	DET
cana-4845	278	7	principal	principal	NOUN
cana-4845	278	8	,	,	PUNCT
cana-4845	278	9	dr	dr	PROPN
cana-4845	279	1	.	.	PROPN
cana-4845	279	2	p.	p.	PROPN
cana-4845	279	3	b.	b.	PROPN
cana-4845	279	4	mane	mane	PROPN
cana-4845	279	5	,	,	PUNCT
cana-4845	279	6	and	and	CCONJ
cana-4845	279	7	the	the	DET
cana-4845	279	8	head	head	NOUN
cana-4845	279	9	of	of	ADP
cana-4845	279	10	the	the	DET
cana-4845	279	11	e&tc	e&tc	PROPN
cana-4845	279	12	department	department	PROPN
cana-4845	279	13	,	,	PUNCT
cana-4845	279	14	dr	dr	PROPN
cana-4845	279	15	.	.	PROPN
cana-4845	279	16	dnyandeo	dnyandeo	PROPN
cana-4845	279	17	k.	k.	PROPN
cana-4845	279	18	shedge	shedge	PROPN
cana-4845	279	19	,	,	PUNCT
cana-4845	279	20	for	for	ADP
cana-4845	279	21	their	their	PRON
cana-4845	279	22	kind	kind	ADJ
cana-4845	279	23	support	support	NOUN
cana-4845	279	24	and	and	CCONJ
cana-4845	279	25	availability	availability	NOUN
cana-4845	279	26	of	of	ADP
cana-4845	279	27	the	the	DET
cana-4845	279	28	facilities	facility	NOUN
cana-4845	279	29	we	we	PRON
cana-4845	279	30	required	require	VERB
cana-4845	279	31	.	.	PUNCT
cana-4845	280	1	reference	reference	NOUN
cana-4845	280	2	[	[	X
cana-4845	280	3	1	1	NUM
cana-4845	280	4	]	]	PUNCT
cana-4845	280	5	yibo	yibo	PROPN
cana-4845	280	6	zhu	zhu	PROPN
cana-4845	280	7	,	,	PUNCT
cana-4845	280	8	et	et	PROPN
cana-4845	280	9	al	al	PROPN
cana-4845	280	10	.	.	PROPN
cana-4845	280	11	,	,	PUNCT
cana-4845	280	12	“	"	PUNCT
cana-4845	280	13	classifying	classify	VERB
cana-4845	280	14	major	major	ADJ
cana-4845	280	15	depressive	depressive	ADJ
cana-4845	280	16	disorder	disorder	NOUN
cana-4845	280	17	using	use	VERB
cana-4845	280	18	fnirs	fnir	NOUN
cana-4845	280	19	during	during	ADP
cana-4845	280	20	motor	motor	NOUN
cana-4845	280	21	rehabilitation	rehabilitation	NOUN
cana-4845	280	22	”	"	PUNCT
cana-4845	280	23	,	,	PUNCT
cana-4845	280	24	ieee	ieee	NOUN
cana-4845	280	25	transactions	transaction	NOUN
cana-4845	280	26	on	on	ADP
cana-4845	280	27	neural	neural	ADJ
cana-4845	280	28	systems	system	NOUN
cana-4845	280	29	and	and	CCONJ
cana-4845	280	30	rehabilitation	rehabilitation	NOUN
cana-4845	280	31	engineering	engineering	NOUN
cana-4845	280	32	,	,	PUNCT
cana-4845	280	33	vol	vol	NOUN
cana-4845	280	34	.	.	PROPN
cana-4845	280	35	28	28	NUM
cana-4845	280	36	,	,	PUNCT
cana-4845	280	37	no	no	INTJ
cana-4845	280	38	.	.	NOUN
cana-4845	280	39	4	4	NUM
cana-4845	280	40	,	,	PUNCT
cana-4845	280	41	april	april	PROPN
cana-4845	280	42	2020	2020	NUM
cana-4845	280	43	.	.	PUNCT
cana-4845	281	1	[	[	X
cana-4845	281	2	2	2	X
cana-4845	281	3	]	]	PUNCT
cana-4845	281	4	oleksii	oleksii	NOUN
cana-4845	281	5	komarov	komarov	NOUN
cana-4845	281	6	,	,	PUNCT
cana-4845	281	7	li	li	PROPN
cana-4845	281	8	-	-	PUNCT
cana-4845	281	9	wei	wei	PROPN
cana-4845	281	10	ko	ko	PROPN
cana-4845	281	11	,	,	PUNCT
cana-4845	281	12	and	and	CCONJ
cana-4845	281	13	tzyy	tzyy	ADJ
cana-4845	281	14	-	-	PUNCT
cana-4845	281	15	ping	ping	NOUN
cana-4845	281	16	jung	jung	NOUN
cana-4845	281	17	,	,	PUNCT
cana-4845	281	18	”	"	PUNCT
cana-4845	281	19	associations	association	NOUN
cana-4845	281	20	among	among	ADP
cana-4845	281	21	emotional	emotional	ADJ
cana-4845	281	22	state	state	NOUN
cana-4845	281	23	,	,	PUNCT
cana-4845	281	24	sleep	sleep	VERB
cana-4845	281	25	quality	quality	NOUN
cana-4845	281	26	,	,	PUNCT
cana-4845	281	27	and	and	CCONJ
cana-4845	281	28	resting	rest	VERB
cana-4845	281	29	-	-	PUNCT
cana-4845	281	30	state	state	NOUN
cana-4845	281	31	eeg	eeg	PROPN
cana-4845	281	32	spectra	spectra	NOUN
cana-4845	281	33	:	:	PUNCT
cana-4845	281	34	a	a	DET
cana-4845	281	35	longitudinal	longitudinal	ADJ
cana-4845	281	36	study	study	NOUN
cana-4845	281	37	in	in	ADP
cana-4845	281	38	graduate	graduate	NOUN
cana-4845	281	39	students	student	NOUN
cana-4845	281	40	”	"	PUNCT
cana-4845	281	41	ieee	ieee	NOUN
cana-4845	281	42	transactions	transaction	NOUN
cana-4845	281	43	on	on	ADP
cana-4845	281	44	neural	neural	ADJ
cana-4845	281	45	systems	system	NOUN
cana-4845	281	46	and	and	CCONJ
cana-4845	281	47	rehabilitation	rehabilitation	NOUN
cana-4845	281	48	engineering	engineering	NOUN
cana-4845	281	49	,	,	PUNCT
cana-4845	281	50	vol	vol	NOUN
cana-4845	281	51	.	.	PROPN
cana-4845	282	1	28	28	NUM
cana-4845	282	2	,	,	PUNCT
cana-4845	282	3	no	no	INTJ
cana-4845	282	4	.	.	NOUN
cana-4845	282	5	4	4	NUM
cana-4845	282	6	,	,	PUNCT
cana-4845	282	7	april	april	PROPN
cana-4845	282	8	2020	2020	NUM
cana-4845	282	9	.	.	PUNCT
cana-4845	283	1	[	[	X
cana-4845	283	2	3	3	NUM
cana-4845	283	3	]	]	X
cana-4845	283	4	marcel	marcel	PROPN
cana-4845	283	5	trotzek	trotzek	PROPN
cana-4845	283	6	,	,	PUNCT
cana-4845	283	7	sven	sven	PROPN
cana-4845	283	8	koitka	koitka	PROPN
cana-4845	283	9	,	,	PUNCT
cana-4845	283	10	and	and	CCONJ
cana-4845	283	11	christoph	christoph	PROPN
cana-4845	283	12	m.	m.	PROPN
cana-4845	283	13	friedrich	friedrich	PROPN
cana-4845	283	14	,	,	PUNCT
cana-4845	283	15	”	"	PUNCT
cana-4845	283	16	utilizing	utilize	VERB
cana-4845	283	17	neural	neural	ADJ
cana-4845	283	18	networks	network	NOUN
cana-4845	283	19	and	and	CCONJ
cana-4845	283	20	linguistic	linguistic	ADJ
cana-4845	283	21	metadata	metadata	NOUN
cana-4845	283	22	for	for	ADP
cana-4845	283	23	early	early	ADJ
cana-4845	283	24	detection	detection	NOUN
cana-4845	283	25	of	of	ADP
cana-4845	283	26	depression	depression	NOUN
cana-4845	283	27	indications	indication	NOUN
cana-4845	283	28	in	in	ADP
cana-4845	283	29	text	text	NOUN
cana-4845	283	30	sequences	sequence	NOUN
cana-4845	283	31	”	"	PUNCT
cana-4845	283	32	ieee	ieee	NOUN
cana-4845	283	33	transactions	transaction	NOUN
cana-4845	283	34	on	on	ADP
cana-4845	283	35	knowledge	knowledge	NOUN
cana-4845	283	36	and	and	CCONJ
cana-4845	283	37	data	datum	NOUN
cana-4845	283	38	engineering	engineering	NOUN
cana-4845	283	39	,	,	PUNCT
cana-4845	283	40	vol	vol	NOUN
cana-4845	283	41	.	.	PROPN
cana-4845	283	42	7	7	NUM
cana-4845	283	43	,	,	PUNCT
cana-4845	283	44	no	no	INTJ
cana-4845	283	45	.	.	NOUN
cana-4845	283	46	,	,	PUNCT
cana-4845	283	47	month	month	NOUN
cana-4845	283	48	2018	2018	NUM
cana-4845	283	49	[	[	X
cana-4845	283	50	4	4	NUM
cana-4845	283	51	]	]	X
cana-4845	283	52	xiaohan	xiaohan	PROPN
cana-4845	283	53	zang	zang	PROPN
cana-4845	283	54	,	,	PUNCT
cana-4845	283	55	baimin	baimin	PROPN
cana-4845	283	56	li	li	PROPN
cana-4845	283	57	,	,	PUNCT
cana-4845	283	58	lulu	lulu	PROPN
cana-4845	283	59	zhao	zhao	PROPN
cana-4845	283	60	,	,	PUNCT
cana-4845	283	61	dandan	dandan	PROPN
cana-4845	283	62	yan	yan	PROPN
cana-4845	283	63	&	&	CCONJ
cana-4845	283	64	licai	licai	PROPN
cana-4845	283	65	yang	yang	PROPN
cana-4845	283	66	,	,	PUNCT
cana-4845	283	67	“	"	PUNCT
cana-4845	283	68	end	end	VERB
cana-4845	283	69	-	-	PUNCT
cana-4845	283	70	to	to	ADP
cana-4845	283	71	-	-	PUNCT
cana-4845	283	72	end	end	NOUN
cana-4845	283	73	depression	depression	NOUN
cana-4845	283	74	recognition	recognition	NOUN
cana-4845	283	75	based	base	VERB
cana-4845	283	76	on	on	ADP
cana-4845	283	77	a	a	DET
cana-4845	283	78	one	one	NUM
cana-4845	283	79	-	-	PUNCT
cana-4845	283	80	dimensional	dimensional	ADJ
cana-4845	283	81	convolution	convolution	NOUN
cana-4845	283	82	neural	neural	ADJ
cana-4845	283	83	network	network	NOUN
cana-4845	283	84	model	model	NOUN
cana-4845	283	85	using	use	VERB
cana-4845	283	86	two	two	NUM
cana-4845	283	87	-	-	PUNCT
cana-4845	283	88	lead	lead	NOUN
cana-4845	283	89	ecg	ecg	PROPN
cana-4845	283	90	signal	signal	NOUN
cana-4845	283	91	”	"	PUNCT
cana-4845	283	92	,	,	PUNCT
cana-4845	283	93	journal	journal	NOUN
cana-4845	283	94	of	of	ADP
cana-4845	283	95	medical	medical	ADJ
cana-4845	283	96	and	and	CCONJ
cana-4845	283	97	biological	biological	ADJ
cana-4845	283	98	engineering	engineering	NOUN
cana-4845	283	99	volume	volume	NOUN
cana-4845	283	100	42	42	NUM
cana-4845	283	101	,	,	PUNCT
cana-4845	283	102	pages225–233	pages225–233	X
cana-4845	283	103	(	(	PUNCT
cana-4845	283	104	2022	2022	NUM
cana-4845	283	105	)	)	PUNCT
cana-4845	284	1	[	[	X
cana-4845	284	2	5	5	X
cana-4845	284	3	]	]	PUNCT
cana-4845	284	4	juan	juan	PROPN
cana-4845	284	5	bueno	bueno	PROPN
cana-4845	284	6	-	-	PUNCT
cana-4845	284	7	notivol	notivol	NOUN
cana-4845	284	8	,	,	PUNCT
cana-4845	284	9	patricia	patricia	PROPN
cana-4845	284	10	gracia	gracia	PROPN
cana-4845	284	11	garcía	garcía	PROPN
cana-4845	284	12	,	,	PUNCT
cana-4845	284	13	beatriz	beatriz	PROPN
cana-4845	284	14	olaya	olaya	PROPN
cana-4845	284	15	,	,	PUNCT
cana-4845	284	16	isabel	isabel	PROPN
cana-4845	284	17	lasheras	lashera	NOUN
cana-4845	284	18	,	,	PUNCT
cana-4845	284	19	raúl	raúl	PROPN
cana-4845	284	20	lópez	lópez	PROPN
cana-4845	284	21	antón	antón	NOUN
cana-4845	284	22	,	,	PUNCT
cana-4845	284	23	javier	javier	PROPN
cana-4845	284	24	santabarbara	santabarbara	PROPN
cana-4845	284	25	,	,	PUNCT
cana-4845	284	26	“	"	PUNCT
cana-4845	284	27	prevalence	prevalence	NOUN
cana-4845	284	28	of	of	ADP
cana-4845	284	29	depression	depression	NOUN
cana-4845	284	30	during	during	ADP
cana-4845	284	31	the	the	DET
cana-4845	284	32	covid-19	covid-19	PROPN
cana-4845	284	33	outbreak	outbreak	NOUN
cana-4845	284	34	:	:	PUNCT
cana-4845	284	35	a	a	DET
cana-4845	284	36	meta	meta	ADJ
cana-4845	284	37	-	-	PUNCT
cana-4845	284	38	analysis	analysis	NOUN
cana-4845	284	39	of	of	ADP
cana-4845	284	40	community	community	NOUN
cana-4845	284	41	-	-	PUNCT
cana-4845	284	42	based	base	VERB
cana-4845	284	43	studies	study	NOUN
cana-4845	284	44	”	"	PUNCT
cana-4845	284	45	international	international	ADJ
cana-4845	284	46	journal	journal	NOUN
cana-4845	284	47	of	of	ADP
cana-4845	284	48	clinical	clinical	ADJ
cana-4845	284	49	and	and	CCONJ
cana-4845	284	50	health	health	NOUN
cana-4845	284	51	psychology	psychology	NOUN
cana-4845	284	52	volume	volume	NOUN
cana-4845	284	53	21	21	NUM
cana-4845	284	54	,	,	PUNCT
cana-4845	284	55	issue	issue	NOUN
cana-4845	284	56	january	january	PROPN
cana-4845	284	57	–	–	PUNCT
cana-4845	284	58	april	april	PROPN
cana-4845	284	59	2021	2021	NUM
cana-4845	284	60	,	,	PUNCT
cana-4845	284	61	100196	100196	NUM
cana-4845	284	62	.	.	PUNCT
cana-4845	285	1	[	[	X
cana-4845	285	2	6	6	NUM
cana-4845	285	3	]	]	PUNCT
cana-4845	285	4	purude	purude	NOUN
cana-4845	285	5	vaishali	vaishali	PROPN
cana-4845	285	6	narayanrao	narayanrao	PROPN
cana-4845	285	7	;	;	PUNCT
cana-4845	285	8	p.	p.	PROPN
cana-4845	285	9	lalitha	lalitha	PROPN
cana-4845	286	1	surya	surya	PROPN
cana-4845	286	2	kumari	kumari	PROPN
cana-4845	286	3	,	,	PUNCT
cana-4845	286	4	”	"	PUNCT
cana-4845	286	5	analysis	analysis	NOUN
cana-4845	286	6	of	of	ADP
cana-4845	286	7	machine	machine	NOUN
cana-4845	286	8	learning	learn	VERB
cana-4845	286	9	algorithms	algorithm	NOUN
cana-4845	286	10	for	for	ADP
cana-4845	286	11	predicting	predict	VERB
cana-4845	286	12	depression	depression	NOUN
cana-4845	286	13	”	"	PUNCT
cana-4845	286	14	international	international	ADJ
cana-4845	286	15	conference	conference	NOUN
cana-4845	286	16	on	on	ADP
cana-4845	286	17	computer	computer	NOUN
cana-4845	286	18	science	science	NOUN
cana-4845	286	19	,	,	PUNCT
cana-4845	286	20	engineering	engineering	NOUN
cana-4845	286	21	and	and	CCONJ
cana-4845	286	22	applications	application	NOUN
cana-4845	286	23	(	(	PUNCT
cana-4845	286	24	iccsea	iccsea	NOUN
cana-4845	286	25	)	)	PUNCT
cana-4845	286	26	,	,	PUNCT
cana-4845	286	27	ieee	ieee	NOUN
cana-4845	286	28	xplore	xplore	PROPN
cana-4845	286	29	,	,	PUNCT
cana-4845	286	30	03	03	NUM
cana-4845	286	31	july	july	PROPN
cana-4845	286	32	2020	2020	NUM
cana-4845	286	33	.	.	PUNCT
cana-4845	287	1	[	[	X
cana-4845	287	2	7	7	X
cana-4845	287	3	]	]	X
cana-4845	287	4	wheidima	wheidima	PROPN
cana-4845	287	5	carneiro	carneiro	PROPN
cana-4845	287	6	de	de	PROPN
cana-4845	287	7	melo	melo	PROPN
cana-4845	287	8	;	;	PUNCT
cana-4845	287	9	eric	eric	PROPN
cana-4845	287	10	granger	granger	PROPN
cana-4845	287	11	;	;	PUNCT
cana-4845	287	12	abdenour	abdenour	PROPN
cana-4845	287	13	hadid	hadid	PROPN
cana-4845	287	14	,	,	PUNCT
cana-4845	287	15	”	"	PUNCT
cana-4845	287	16	depression	depression	NOUN
cana-4845	287	17	detection	detection	NOUN
cana-4845	287	18	based	base	VERB
cana-4845	287	19	on	on	ADP
cana-4845	287	20	deep	deep	ADJ
cana-4845	287	21	distribution	distribution	NOUN
cana-4845	287	22	learning	learning	NOUN
cana-4845	287	23	”	"	PUNCT
cana-4845	287	24	978	978	NUM
cana-4845	287	25	-	-	SYM
cana-4845	287	26	1	1	NUM
cana-4845	287	27	-	-	PUNCT
cana-4845	287	28	5386	5386	NUM
cana-4845	287	29	-	-	PUNCT
cana-4845	287	30	6249	6249	NUM
cana-4845	287	31	-	-	SYM
cana-4845	287	32	6/19/	6/19/	NUM
cana-4845	287	33	©	©	PROPN
cana-4845	287	34	2019	2019	NUM
cana-4845	287	35	ieee	ieee	NOUN
cana-4845	287	36	,	,	PUNCT
cana-4845	287	37	icip	icip	NOUN
cana-4845	287	38	2019	2019	NUM
cana-4845	287	39	.	.	PUNCT
cana-4845	288	1	[	[	X
cana-4845	288	2	8	8	X
cana-4845	288	3	]	]	X
cana-4845	288	4	bryan	bryan	PROPN
cana-4845	288	5	g.	g.	PROPN
cana-4845	288	6	dadiz	dadiz	PROPN
cana-4845	288	7	;	;	PUNCT
cana-4845	288	8	nelson	nelson	PROPN
cana-4845	288	9	marcos	marcos	PROPN
cana-4845	288	10	,	,	PUNCT
cana-4845	288	11	“	"	PUNCT
cana-4845	288	12	analysis	analysis	NOUN
cana-4845	288	13	of	of	ADP
cana-4845	288	14	depression	depression	NOUN
cana-4845	288	15	based	base	VERB
cana-4845	288	16	on	on	ADP
cana-4845	288	17	facial	facial	ADJ
cana-4845	288	18	cues	cue	NOUN
cana-4845	288	19	on	on	ADP
cana-4845	288	20	a	a	DET
cana-4845	288	21	captured	capture	VERB
cana-4845	288	22	motion	motion	NOUN
cana-4845	288	23	picture	picture	NOUN
cana-4845	288	24	”	"	PUNCT
cana-4845	288	25	2018	2018	NUM
cana-4845	288	26	ieee	ieee	NOUN
cana-4845	288	27	3rd	3rd	PROPN
cana-4845	288	28	international	international	ADJ
cana-4845	288	29	conference	conference	NOUN
cana-4845	288	30	on	on	ADP
cana-4845	288	31	signal	signal	NOUN
cana-4845	288	32	and	and	CCONJ
cana-4845	288	33	image	image	NOUN
cana-4845	288	34	processing	processing	NOUN
cana-4845	288	35	.	.	PUNCT
cana-4845	289	1	[	[	X
cana-4845	289	2	9	9	X
cana-4845	289	3	]	]	X
cana-4845	289	4	muhammad	muhammad	PROPN
cana-4845	289	5	tariq	tariq	PROPN
cana-4845	289	6	sadiq	sadiq	PROPN
cana-4845	289	7	,	,	PUNCT
cana-4845	289	8	xiaojun	xiaojun	PROPN
cana-4845	289	9	yu	yu	PROPN
cana-4845	289	10	,	,	PUNCT
cana-4845	289	11	zhaohui	zhaohui	PROPN
cana-4845	289	12	yuan	yuan	PROPN
cana-4845	289	13	,	,	PUNCT
cana-4845	289	14	fan	fan	PROPN
cana-4845	289	15	zeming	zeming	PROPN
cana-4845	289	16	,	,	PUNCT
cana-4845	289	17	ateeq	ateeq	ADP
cana-4845	289	18	ur	ur	PROPN
cana-4845	289	19	rehman	rehman	PROPN
cana-4845	289	20	,	,	PUNCT
cana-4845	289	21	inam	inam	PROPN
cana-4845	289	22	ullah	ullah	PROPN
cana-4845	289	23	2	2	NUM
cana-4845	289	24	,	,	PUNCT
cana-4845	289	25	guoqi	guoqi	PROPN
cana-4845	289	26	li	li	PROPN
cana-4845	289	27	,	,	PUNCT
cana-4845	289	28	and	and	CCONJ
cana-4845	289	29	gaoxi	gaoxi	PROPN
cana-4845	289	30	xiao	xiao	PROPN
cana-4845	289	31	,	,	PUNCT
cana-4845	289	32	“	"	PUNCT
cana-4845	289	33	motor	motor	NOUN
cana-4845	289	34	imagery	imagery	NOUN
cana-4845	289	35	eeg	eeg	NOUN
cana-4845	289	36	signals	signal	NOUN
cana-4845	289	37	decoding	decode	VERB
cana-4845	289	38	by	by	ADP
cana-4845	289	39	multivariate	multivariate	NOUN
cana-4845	289	40	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-xiaohan-zang-aff1	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-xiaohan-zang-aff1	PROPN
cana-4845	289	41	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-baimin-li-aff2	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-baimin-li-aff2	PROPN
cana-4845	289	42	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-lulu-zhao-aff3	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-lulu-zhao-aff3	PROPN
cana-4845	289	43	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-dandan-yan-aff1	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-dandan-yan-aff1	PROPN
cana-4845	289	44	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-licai-yang-aff1	https://link.springer.com/article/10.1007/s40846-022-00687-7#auth-licai-yang-aff1	PROPN
cana-4845	289	45	https://link.springer.com/journal/40846	https://link.springer.com/journal/40846	NOUN
cana-4845	289	46	https://ieeexplore.ieee.org/xpl/conhome/9130629/proceeding	https://ieeexplore.ieee.org/xpl/conhome/9130629/proceeding	NOUN
cana-4845	289	47	https://ieeexplore.ieee.org/xpl/conhome/9130629/proceeding	https://ieeexplore.ieee.org/xpl/conhome/9130629/proceede	VERB
cana-4845	289	48	communications	communication	NOUN
cana-4845	289	49	on	on	ADP
cana-4845	289	50	applied	apply	VERB
cana-4845	289	51	nonlinear	nonlinear	ADJ
cana-4845	289	52	analysis	analysis	NOUN
cana-4845	289	53	issn	issn	NOUN
cana-4845	289	54	:	:	PUNCT
cana-4845	289	55	1074	1074	NUM
cana-4845	289	56	-	-	PUNCT
cana-4845	289	57	133x	133x	NUM
cana-4845	289	58	vol	vol	VERB
cana-4845	289	59	32	32	NUM
cana-4845	289	60	no	no	NOUN
cana-4845	289	61	.	.	PUNCT
cana-4845	290	1	10s	10	NOUN
cana-4845	290	2	(	(	PUNCT
cana-4845	290	3	2025	2025	NUM
cana-4845	290	4	)	)	PUNCT
cana-4845	290	5	559	559	NUM
cana-4845	290	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-4845	290	7	empirical	empirical	ADJ
cana-4845	290	8	wavelet	wavelet	NOUN
cana-4845	290	9	transform	transform	NOUN
cana-4845	290	10	-	-	PUNCT
cana-4845	290	11	based	base	VERB
cana-4845	290	12	framework	framework	NOUN
cana-4845	290	13	for	for	ADP
cana-4845	290	14	robust	robust	ADJ
cana-4845	290	15	brain	brain	NOUN
cana-4845	290	16	–	–	PUNCT
cana-4845	290	17	computer	computer	NOUN
cana-4845	290	18	interfaces	interface	NOUN
cana-4845	290	19	”	"	PUNCT
cana-4845	290	20	,	,	PUNCT
cana-4845	290	21	ieee	ieee	NOUN
cana-4845	290	22	access	access	NOUN
cana-4845	290	23	,	,	PUNCT
cana-4845	290	24	volume	volume	NOUN
cana-4845	290	25	7	7	NUM
cana-4845	290	26	,	,	PUNCT
cana-4845	290	27	2019	2019	NUM
cana-4845	290	28	,	,	PUNCT
cana-4845	290	29	page	page	NOUN
cana-4845	290	30	no	no	NOUN
cana-4845	290	31	.	.	PROPN
cana-4845	290	32	171431	171431	NUM
cana-4845	290	33	to	to	ADP
cana-4845	290	34	171451	171451	NUM
cana-4845	290	35	.	.	PUNCT
cana-4845	291	1	[	[	X
cana-4845	291	2	10	10	NUM
cana-4845	291	3	]	]	PUNCT
cana-4845	291	4	gulay	gulay	NOUN
cana-4845	291	5	tasci	tasci	PROPN
cana-4845	291	6	,	,	PUNCT
cana-4845	291	7	et	et	PROPN
cana-4845	291	8	al	al	PROPN
cana-4845	291	9	.	.	PROPN
cana-4845	291	10	,	,	PUNCT
cana-4845	291	11	“	"	PUNCT
cana-4845	291	12	automated	automate	VERB
cana-4845	291	13	accurate	accurate	ADJ
cana-4845	291	14	detection	detection	NOUN
cana-4845	291	15	of	of	ADP
cana-4845	291	16	depression	depression	NOUN
cana-4845	291	17	using	use	VERB
cana-4845	291	18	twin	twin	ADJ
cana-4845	291	19	pascal	pascal	PROPN
cana-4845	291	20	’s	’s	PART
cana-4845	291	21	triangles	triangle	NOUN
cana-4845	291	22	lattice	lattice	PROPN
cana-4845	291	23	pattern	pattern	NOUN
cana-4845	291	24	with	with	ADP
cana-4845	291	25	eeg	eeg	NOUN
cana-4845	291	26	signals	signal	NOUN
cana-4845	291	27	”	"	PUNCT
cana-4845	291	28	[	[	X
cana-4845	291	29	11	11	NUM
cana-4845	291	30	]	]	PUNCT
cana-4845	291	31	muhammad	muhammad	PROPN
cana-4845	291	32	tariq	tariq	PROPN
cana-4845	291	33	sadiq	sadiq	PROPN
cana-4845	291	34	,	,	PUNCT
cana-4845	291	35	xiaojun	xiaojun	PROPN
cana-4845	291	36	yu	yu	PROPN
cana-4845	291	37	,	,	PUNCT
cana-4845	291	38	zhaohui	zhaohui	PROPN
cana-4845	291	39	yuan	yuan	PROPN
cana-4845	291	40	,	,	PUNCT
cana-4845	291	41	muhammad	muhammad	PROPN
cana-4845	291	42	zulkifal	zulkifal	PROPN
cana-4845	291	43	aziz	aziz	PROPN
cana-4845	291	44	,	,	PUNCT
cana-4845	291	45	“	"	PUNCT
cana-4845	291	46	motor	motor	NOUN
cana-4845	291	47	imagery	imagery	NOUN
cana-4845	291	48	bci	bci	NOUN
cana-4845	291	49	classification	classification	NOUN
cana-4845	291	50	based	base	VERB
cana-4845	291	51	on	on	ADP
cana-4845	291	52	novel	novel	ADJ
cana-4845	291	53	two	two	NUM
cana-4845	291	54	-	-	PUNCT
cana-4845	291	55	dimensional	dimensional	ADJ
cana-4845	291	56	modelling	modelling	NOUN
cana-4845	291	57	in	in	ADP
cana-4845	291	58	empirical	empirical	ADJ
cana-4845	291	59	wavelet	wavelet	NOUN
cana-4845	291	60	transform”,06	transform”,06	NUM
cana-4845	291	61	october	october	PROPN
cana-4845	291	62	2020	2020	NUM
cana-4845	291	63	.	.	PUNCT
cana-4845	292	1	https://doi.org/10.1049/el.2020.2509	https://doi.org/10.1049/el.2020.2509	ADJ
cana-4845	292	2	.	.	PUNCT
cana-4845	293	1	[	[	X
cana-4845	293	2	12	12	NUM
cana-4845	293	3	]	]	PUNCT
cana-4845	293	4	world	world	NOUN
cana-4845	293	5	health	health	NOUN
cana-4845	293	6	organization	organization	NOUN
cana-4845	293	7	.	.	PUNCT
cana-4845	294	1	(	(	PUNCT
cana-4845	294	2	2021	2021	NUM
cana-4845	294	3	)	)	PUNCT
cana-4845	294	4	.	.	PUNCT
cana-4845	295	1	depression	depression	NOUN
cana-4845	295	2	.	.	PUNCT
cana-4845	296	1	retrieved	retrieve	VERB
cana-4845	296	2	from	from	ADP
cana-4845	296	3	https://www.who.int/newsroom/fact-sheets/detail/	https://www.who.int/newsroom/fact-sheets/detail/	NOUN
cana-4845	296	4	depression	depression	NOUN
cana-4845	296	5	[	[	X
cana-4845	296	6	13	13	NUM
cana-4845	296	7	]	]	PUNCT
cana-4845	296	8	depression	depression	NOUN
cana-4845	296	9	monitoring	monitoring	NOUN
cana-4845	296	10	”	"	PUNCT
cana-4845	296	11	2017	2017	NUM
cana-4845	296	12	ieee	ieee	NOUN
cana-4845	296	13	international	international	ADJ
cana-4845	296	14	conference	conference	NOUN
cana-4845	296	15	on	on	ADP
cana-4845	296	16	bioinformatics	bioinformatics	NOUN
cana-4845	296	17	and	and	CCONJ
cana-4845	296	18	biomedicine	biomedicine	NOUN
cana-4845	296	19	(	(	PUNCT
cana-4845	296	20	bibm	bibm	NOUN
cana-4845	296	21	)	)	PUNCT
cana-4845	296	22	.	.	PUNCT
cana-4845	297	1	[	[	X
cana-4845	297	2	14	14	NUM
cana-4845	297	3	]	]	X
cana-4845	297	4	chiara	chiara	PROPN
cana-4845	297	5	visentinib	visentinib	PROPN
cana-4845	297	6	megan	megan	PROPN
cana-4845	297	7	cassidya	cassidya	PROPN
cana-4845	297	8	victoria	victoria	PROPN
cana-4845	297	9	jane	jane	PROPN
cana-4845	297	10	birda	birda	PROPN
cana-4845	297	11	stefan	stefan	PROPN
cana-4845	297	12	priebea	priebea	PROPN
cana-4845	297	13	,	,	PUNCT
cana-4845	297	14	“	"	PUNCT
cana-4845	297	15	social	social	ADJ
cana-4845	297	16	networks	network	NOUN
cana-4845	297	17	of	of	ADP
cana-4845	297	18	patients	patient	NOUN
cana-4845	297	19	with	with	ADP
cana-4845	297	20	chronic	chronic	ADJ
cana-4845	297	21	depression	depression	NOUN
cana-4845	297	22	:	:	PUNCT
cana-4845	297	23	a	a	DET
cana-4845	297	24	systematic	systematic	ADJ
cana-4845	297	25	review	review	NOUN
cana-4845	297	26	”	"	PUNCT
cana-4845	297	27	journal	journal	NOUN
cana-4845	297	28	of	of	ADP
cana-4845	297	29	affective	affective	ADJ
cana-4845	297	30	disorders	disorder	NOUN
cana-4845	297	31	.	.	PUNCT
cana-4845	298	1	[	[	X
cana-4845	298	2	15	15	NUM
cana-4845	298	3	]	]	X
cana-4845	298	4	jian	jian	PROPN
cana-4845	298	5	shen	shen	PROPN
cana-4845	298	6	;	;	PUNCT
cana-4845	298	7	shengjie	shengjie	PROPN
cana-4845	298	8	zhao	zhao	PROPN
cana-4845	298	9	;	;	PUNCT
cana-4845	298	10	yuan	yuan	NOUN
cana-4845	298	11	yao	yao	PROPN
cana-4845	298	12	;	;	PUNCT
cana-4845	298	13	yue	yue	PROPN
cana-4845	298	14	wang	wang	PROPN
cana-4845	298	15	;	;	PUNCT
cana-4845	298	16	lei	lei	PROPN
cana-4845	298	17	feng	feng	PROPN
cana-4845	298	18	,	,	PUNCT
cana-4845	298	19	“	"	PUNCT
cana-4845	298	20	a	a	DET
cana-4845	298	21	novel	novel	ADJ
cana-4845	298	22	depression	depression	NOUN
cana-4845	298	23	detection	detection	NOUN
cana-4845	298	24	method	method	NOUN
cana-4845	298	25	based	base	VERB
cana-4845	298	26	on	on	ADP
cana-4845	298	27	pervasive	pervasive	ADJ
cana-4845	298	28	eeg	eeg	PROPN
cana-4845	298	29	and	and	CCONJ
cana-4845	298	30	eeg	eeg	NOUN
cana-4845	298	31	splitting	splitting	NOUN
cana-4845	298	32	criterion	criterion	NOUN
cana-4845	298	33	”	"	PUNCT
cana-4845	298	34	2017	2017	NUM
cana-4845	298	35	ieee	ieee	NOUN
cana-4845	298	36	international	international	ADJ
cana-4845	298	37	conference	conference	NOUN
cana-4845	298	38	on	on	ADP
cana-4845	298	39	bioinformatics	bioinformatics	NOUN
cana-4845	298	40	and	and	CCONJ
cana-4845	298	41	biomedicine	biomedicine	NOUN
cana-4845	298	42	(	(	PUNCT
cana-4845	298	43	bibm	bibm	NOUN
cana-4845	298	44	)	)	PUNCT
cana-4845	298	45	.	.	PUNCT
cana-4845	299	1	[	[	X
cana-4845	299	2	16	16	NUM
cana-4845	299	3	]	]	PUNCT
cana-4845	299	4	sumaiya	sumaiya	PROPN
cana-4845	299	5	tarannum	tarannum	PROPN
cana-4845	299	6	noor	noor	PROPN
cana-4845	299	7	,	,	PUNCT
cana-4845	299	8	syeda	syeda	PROPN
cana-4845	299	9	tasmiah	tasmiah	PROPN
cana-4845	299	10	asad	asad	PROPN
cana-4845	299	11	,	,	PUNCT
cana-4845	299	12	mohammad	mohammad	PROPN
cana-4845	299	13	monirujjaman	monirujjaman	PROPN
cana-4845	299	14	khan	khan	PROPN
cana-4845	299	15	,	,	PUNCT
cana-4845	299	16	gurjot	gurjot	NOUN
cana-4845	299	17	singh	singh	PROPN
cana-4845	299	18	gaba	gaba	PROPN
cana-4845	299	19	,	,	PUNCT
cana-4845	299	20	jehad	jehad	PROPN
cana-4845	299	21	f.	f.	PROPN
cana-4845	299	22	al	al	PROPN
cana-4845	299	23	-	-	PUNCT
cana-4845	299	24	amri	amri	PROPN
cana-4845	299	25	,	,	PUNCT
cana-4845	299	26	and	and	CCONJ
cana-4845	299	27	mehedi	mehedi	PROPN
cana-4845	299	28	masud	masud	PROPN
cana-4845	299	29	,	,	PUNCT
cana-4845	299	30	“	"	PUNCT
cana-4845	299	31	predicting	predict	VERB
cana-4845	299	32	the	the	DET
cana-4845	299	33	risk	risk	NOUN
cana-4845	299	34	of	of	ADP
cana-4845	299	35	depression	depression	NOUN
cana-4845	299	36	based	base	VERB
cana-4845	299	37	on	on	ADP
cana-4845	299	38	ecg	ecg	PROPN
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cana-4845	299	53	,	,	PUNCT
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cana-4845	300	12	;	;	PUNCT
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cana-4845	301	1	[	[	X
cana-4845	301	2	18	18	NUM
cana-4845	301	3	]	]	X
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cana-4845	301	18	speech	speech	NOUN
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cana-4845	301	24	,	,	PUNCT
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cana-4845	302	3	]	]	PUNCT
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cana-4845	302	18	of	of	ADP
cana-4845	302	19	depression	depression	NOUN
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cana-4845	302	21	type	type	NOUN
cana-4845	302	22	2	2	NUM
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cana-4845	302	25	”	"	PUNCT
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cana-4845	302	30	on	on	ADP
cana-4845	302	31	intelligent	intelligent	ADJ
cana-4845	302	32	systems	system	NOUN
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cana-4845	302	34	knowledge	knowledge	NOUN
cana-4845	302	35	engineering	engineering	PROPN
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cana-4845	303	3	]	]	PUNCT
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cana-4845	303	6	;	;	PUNCT
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cana-4845	303	33	november	november	PROPN
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cana-4845	303	35	-	-	SYM
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cana-4845	303	39	|	|	NOUN
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cana-4845	311	55	–	–	PUNCT
cana-4845	311	56	april	april	PROPN
cana-4845	311	57	2021	2021	NUM
cana-4845	311	58	,	,	PUNCT
cana-4845	311	59	100196	100196	NUM
cana-4845	311	60	.	.	PUNCT
cana-4845	312	1	[	[	X
cana-4845	312	2	26	26	NUM
cana-4845	312	3	]	]	X
cana-4845	312	4	komarov	komarov	X
cana-4845	312	5	o	o	NOUN
cana-4845	312	6	,	,	PUNCT
cana-4845	312	7	ko	ko	PROPN
cana-4845	312	8	l	l	PROPN
cana-4845	312	9	,	,	PUNCT
cana-4845	312	10	jung	jung	PROPN
cana-4845	312	11	tp	tp	X
cana-4845	312	12	(	(	PUNCT
cana-4845	312	13	2020	2020	NUM
cana-4845	312	14	)	)	PUNCT
cana-4845	312	15	associations	association	NOUN
cana-4845	312	16	among	among	ADP
cana-4845	312	17	emotional	emotional	ADJ
cana-4845	312	18	state	state	NOUN
cana-4845	312	19	,	,	PUNCT
cana-4845	312	20	sleep	sleep	VERB
cana-4845	312	21	quality	quality	NOUN
cana-4845	312	22	,	,	PUNCT
cana-4845	312	23	and	and	CCONJ
cana-4845	312	24	restingstate	restingstate	PROPN
cana-4845	312	25	eeg	eeg	PROPN
cana-4845	312	26	spectra	spectra	PROPN
cana-4845	312	27	:	:	PUNCT
cana-4845	312	28	a	a	DET
cana-4845	312	29	longitudinal	longitudinal	ADJ
cana-4845	312	30	study	study	NOUN
cana-4845	312	31	in	in	ADP
cana-4845	312	32	graduate	graduate	NOUN
cana-4845	312	33	students	student	NOUN
cana-4845	312	34	.	.	PUNCT
cana-4845	313	1	ieee	ieee	NOUN
cana-4845	313	2	transactions	transaction	NOUN
cana-4845	313	3	on	on	ADP
cana-4845	313	4	neural	neural	ADJ
cana-4845	313	5	systems	system	NOUN
cana-4845	313	6	and	and	CCONJ
cana-4845	313	7	rehabilitation	rehabilitation	NOUN
cana-4845	313	8	engineering	engineering	NOUN
cana-4845	313	9	,	,	PUNCT
cana-4845	313	10	vol	vol	NOUN
cana-4845	313	11	.	.	PROPN
cana-4845	313	12	28	28	NUM
cana-4845	313	13	,	,	PUNCT
cana-4845	313	14	no	no	INTJ
cana-4845	313	15	.	.	NOUN
cana-4845	313	16	4	4	X
cana-4845	313	17	.	.	PUNCT
cana-4845	314	1	[	[	X
cana-4845	314	2	27	27	NUM
cana-4845	314	3	]	]	X
cana-4845	314	4	guozheng	guozheng	PROPN
cana-4845	314	5	rao	rao	PROPN
cana-4845	314	6	et	et	PROPN
cana-4845	314	7	al	al	PROPN
cana-4845	314	8	.	.	PROPN
cana-4845	314	9	,	,	PUNCT
cana-4845	314	10	“	"	PUNCT
cana-4845	314	11	mgl	mgl	PROPN
cana-4845	314	12	-	-	PUNCT
cana-4845	314	13	cnn	cnn	PROPN
cana-4845	314	14	:	:	PUNCT
cana-4845	314	15	a	a	DET
cana-4845	314	16	hierarchical	hierarchical	ADJ
cana-4845	314	17	post	post	NOUN
cana-4845	314	18	representations	representation	NOUN
cana-4845	314	19	model	model	NOUN
cana-4845	314	20	for	for	ADP
cana-4845	314	21	identifying	identify	VERB
cana-4845	314	22	depressed	depressed	ADJ
cana-4845	314	23	individuals	individual	NOUN
cana-4845	314	24	in	in	ADP
cana-4845	314	25	online	online	ADJ
cana-4845	314	26	forums	forum	NOUN
cana-4845	314	27	”	"	PUNCT
cana-4845	314	28	,	,	PUNCT
cana-4845	314	29	volume	volume	NOUN
cana-4845	314	30	8	8	NUM
cana-4845	314	31	,	,	PUNCT
cana-4845	314	32	2020	2020	NUM
cana-4845	314	33	digital	digital	ADJ
cana-4845	314	34	object	object	NOUN
cana-4845	314	35	identifier	identifier	NOUN
cana-4845	314	36	10.1109	10.1109	NUM
cana-4845	314	37	/	/	SYM
cana-4845	314	38	access.2020.2973737	access.2020.2973737	ADJ
cana-4845	314	39	.	.	PUNCT
cana-4845	315	1	[	[	X
cana-4845	315	2	28	28	NUM
cana-4845	315	3	]	]	X
cana-4845	315	4	wheidima	wheidima	PROPN
cana-4845	315	5	carneiro	carneiro	PROPN
cana-4845	315	6	de	de	PROPN
cana-4845	315	7	melo	melo	PROPN
cana-4845	315	8	;	;	PUNCT
cana-4845	315	9	eric	eric	PROPN
cana-4845	315	10	granger	granger	PROPN
cana-4845	315	11	;	;	PUNCT
cana-4845	315	12	abdenour	abdenour	PROPN
cana-4845	315	13	hadid	hadid	PROPN
cana-4845	315	14	,	,	PUNCT
cana-4845	315	15	”	"	PUNCT
cana-4845	315	16	depression	depression	NOUN
cana-4845	315	17	detection	detection	NOUN
cana-4845	315	18	based	base	VERB
cana-4845	315	19	on	on	ADP
cana-4845	315	20	deep	deep	ADJ
cana-4845	315	21	distribution	distribution	NOUN
cana-4845	315	22	learning	learning	NOUN
cana-4845	315	23	”	"	PUNCT
cana-4845	315	24	978	978	NUM
cana-4845	315	25	-	-	SYM
cana-4845	315	26	1	1	NUM
cana-4845	315	27	-	-	PUNCT
cana-4845	315	28	5386	5386	NUM
cana-4845	315	29	-	-	PUNCT
cana-4845	315	30	6249	6249	NUM
cana-4845	315	31	-	-	SYM
cana-4845	315	32	6/19/	6/19/	NUM
cana-4845	315	33	©	©	PROPN
cana-4845	315	34	2019	2019	NUM
cana-4845	315	35	ieee	ieee	NOUN
cana-4845	315	36	,	,	PUNCT
cana-4845	315	37	icip	icip	NOUN
cana-4845	315	38	2019	2019	NUM
cana-4845	315	39	.	.	PUNCT
cana-4845	316	1	[	[	X
cana-4845	316	2	29	29	NUM
cana-4845	316	3	]	]	PUNCT
cana-4845	316	4	feifei	feifei	PROPN
cana-4845	316	5	zhang	zhang	PROPN
cana-4845	316	6	et	et	PROPN
cana-4845	316	7	al	al	PROPN
cana-4845	316	8	.	.	PROPN
cana-4845	316	9	,”depression	,”depression	PROPN
cana-4845	316	10	recognition	recognition	PROPN
cana-4845	316	11	based	base	VERB
cana-4845	316	12	on	on	ADP
cana-4845	316	13	electrocardiogram	electrocardiogram	NOUN
cana-4845	316	14	”	"	PUNCT
cana-4845	316	15	,	,	PUNCT
cana-4845	316	16	ieee	ieee	PROPN
cana-4845	316	17	xplore	xplore	PROPN
cana-4845	316	18	:	:	PUNCT
cana-4845	316	19	26	26	NUM
cana-4845	316	20	june	june	PROPN
cana-4845	316	21	2023doi	2023doi	NUM
cana-4845	316	22	:	:	PUNCT
cana-4845	316	23	10.1109	10.1109	NUM
cana-4845	316	24	/	/	SYM
cana-4845	316	25	icccs57501.2023.10150930	icccs57501.2023.10150930	PROPN
cana-4845	316	26	.	.	PUNCT
cana-4845	317	1	https://ieeexplore.ieee.org/author/37089885854	https://ieeexplore.ieee.org/author/37089885854	PROPN
cana-4845	317	2	https://doi.org/10.1109/icccs57501.2023.10150930	https://doi.org/10.1109/icccs57501.2023.10150930	PROPN