APPLICATION OF DIGITAL CELLULAR RADIO FOR MOBILE LOCATION ESTIMATION
IIUM Engineering Journal, Vol. 20, No. 1, 2019 Abdulsada et al.
INTELLIGENT CONTROL SYSTEM OF A
WHEELCHAIR FOR PEOPLE WITH
QUADRIPLEGIA PARALYSIS
HAYDER FADHIL ABDULSADA1*, SAIF HUSSAM ABDULWAHED2
AND YASSEN SADOON ATIYA3
1Babylon Technical Institute, Al-Furat Al-Awsat Technical University, 51015 Babylon, Iraq.
2Najaf Technical Institute, Al-Furat Al-Awsat Technical University, 31001 Najaf, Iraq.
3Al-Imam Al-Kadhim University College for Islamic Sciences, Babylon, Iraq.
*Corresponding author: inj.had1@atu.edu.iq
(Received: 14th Feb 2019; Accepted: 29th April 2019; Published on-line: 1st June 2019)
https://doi.org/10.31436/iiumej.v20i1.909
ABSTRACT: Our system proposes a wheelchair controlled by head gestures for people
with quadriplegia paralysis (QP) or for those suffering from amputation of their hands
and legs during the war in Iraq. The wheelchair design has an intelligent control that
works with the movement of a patient‘s head in order to enable the patient to drive the
wheelchair in the desired direction. The system consists of two main parts. The first is
the transmitter in which sensing signals are transmitted to the second part and it consists
of a 3-axes accelerometer (ADXL-345), a 433 MHz RF wireless receiver transmitter
module, and Arduino UNO. The ADXL-345 sensor is placed in front of a hat that the
patient wears. The system detects the direction of the patient's head movement then
sends appropriate instructions to the wheelchair’s control part (receiving part). The
receiving part is the wheelchair control system that consists of a 433 MHz RF wireless
receiver transmitter module and an Arduino UNO. The Arduino processes the signals
coming from the first part and moves the wheelchair accordingly in the desired direction.
The research also provides an obstacle avoidance system with a range of 50 cm that
prevents the wheelchair from colliding with objects. The head movement angles have
been selected to be 40, 35 degree for vertical and horizontal movement respectively so
that the QP patient feels comfortable to tilt his head in all directions and control the
wheelchair easily. The system provides a very effective performance and accuracy.
ABSTRAK: Sistem ini bergantung kepada kerusi roda yang dikawal menggunakan
isyarat kepala untuk mereka yang lumpuh kuadriplegia (QP) ataupun mereka yang
dipotong tangan dan kaki semasa perang di Iraq. Ia merupakan reka bentuk pintar pada
kerusi roda dan pesakit boleh mengawal pergerakan mereka dengan isyarat pada kepala.
Sistem ini terdiri daripada dua bahagian utama iaitu yang pertama merupakan pemancar
yang menghantar isyarat gerakan ke bahagian kedua dan ianya terdiri daripada 3 axis
accelerometer (ADXL-345), modul penerima isyarat pemancar tanpa wayar 433 MHz
RF dan Arduino UNO. Sensor ADXL-345 ini diletakkan di bahagian depan topi yang
dipakai oleh pesakit. Sistem ini mengesan arah gerakan kepala pesakit dan kemudiannya
arahan dihantar ke bahagian pengendali kerusi roda (bahagian penerimaan isyarat).
Bahagian ini merupakan sistem pengendalian kerusi roda yang terdiri daripada modul
pemancar penerimaan tanpa wayar 433 MHz RF dan Arduino UNO. Arduino memproses
isyarat yang datang dari bahagian pertama bagi menggerakkan kerusi roda ke arah yang
dikehendaki. Kajian ini turut menyediakan sistem mengelak halangan pada jarak 50 cm
bagi menjauhi kerusi roda daripada melanggar objek. Sudut gerakan kepala telah dipilih
pada 40, 35 darjah bagi gerakan menegak dan mendatar masing-masing, supaya pesakit
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IIUM Engineering Journal, Vol. 20, No. 1, 2019 Abdulsada et al.
QP merasa selesa bagi mengerakkan kepalanya ke semua arah dan mengawal kerusi roda
dengan mudah. Sistem ini juga sangat cekap dan tepat dalam mengawal arah.
KEYWORDS: head gesture recognition; quadriplegia paralysis; wheelchair controlling
1. INTRODUCTION
At present, many people suffer from physical disability as a result of wars and
diseases; therefore, there is a need for advanced support devices with high safety to help
individuals navigate easily. Intelligent wheelchairs have been developed to assist disabled
and injured people. These wheelchairs are supported by some techniques to enhance
performance and efficiency [1,2]. The continuity in research has led to important
developments in the design of supporting devices for people who are injured, wounded, or
affected by some cases of paralysis. This research includes many techniques to drive
wheelchairs such as joysticks, voice recognition, hand gestures, and cameras. [3,4]. The
work in this paper presents intelligent control of wheelchairs for people suffering from
quadriplegia paralysis (QP) or for people who suffer from amputation of their hands and
legs. The subsequent paragraphs are some research regarding the field of wheelchair
control techniques.
In 2014, Warad et al. described a motorized wheelchair for handicapped humans
utilizing a speech control technique and flex sensing application. The system permits a
disabled person to drive the wheelchair using voice recognition including voice commands
for movement (forward, backward, and stop) and for speed control of motors (maximum,
medium, and minimum). The flex sensor is used to control the wheelchair direction (left
and right) [5]. Chitte et al. developed a wheelchair control system for disabled persons
with hand gesture sensing. The system is divided into a gesture part and a wheelchair part.
Depending on the direction of the accelerometer sensor that is fixed on the hand, the
ARM7 controller gives orders to move the wheelchair to the desired direction. In case of
emergency, an SMS message alert is sent via GSM to the family of the person [3].
Suchitra and Brinda implemented a hand gesture system to drive and control a car utilizing
a 3-axes accelerometer sensor (MEMS Sensor). The sensor is placed on the user's finger
and the car moves in four directions according to the hand movement. The Arduino UNO
microcontroller is used to control and monitor the comprehensive performance of the
system [6].
Saharia et al. introduced a joystick control wheelchair for Disabled people. The
wheelchair movement was controlled by a joystick. The command of movement was done
by utilizing the joystick and then transmitting the order to the Arduino microcontroller that
processes the command. After that, the controller transmits a digital signal to the motor
driver circuit to control wheelchair movement [7]. Sainath et al. considered hand gestures
for controlling and driving a wheelchair. The sensing circuit included an accelerometer
that translates the hand tilting into pitch and roll. The system is implemented based on a
microcontroller that receives the tilting data from the sensor, processes it, and then
transforms it into digital signals for the motors that drive the wheelchair [8].
In some cases of disabilities, the above techniques are useless because of their
limitations. A wheelchair controlled by a joystick or hand gesture does not fully achieve
the requirements of individuals who are suffering from Parkinson's paralysis, quadriplegia
paralysis, or weakness in their hands because they cannot properly control their
wheelchairs [9]. Additionally, the wheelchair controlled by voice instructions provides
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services for people who cannot use hands and legs to drive the wheelchair, but it is not
suitable for people who have speech difficulties [10,11].
The limitations in the previous works can be overcome using the technique used in
this work, which is suitable for multiple cases of disabilities such as quadriplegia
paralysis, Parkinson's paralysis, speech difficulties, amputation in hands and legs. The
work includes an intelligent control technique based on head gestures. In addition, it
provides an obstacle avoidance system.
2. PROPOSED SYSTEM DESIGN
The proposed system is designed to help people with quadriplegia where they can
only move their head or people suffering from amputation of their hands and legs. The
accelerometer sensor is placed in front of the patient's hat. It is used to detect the
movement of the patient's head, then the Arduino sends appropriate instruction of digital
bits via an RF-transmitter. The transmitting part of the proposed system is shown in Fig. 1.
Fig. 1: Transmitter part of the proposed system (hat part).
Fig. 2: Receiving part of the proposed system (wheelchair part).
The signal is received at the other end by the RF-receiver and is analyzed by the
Arduino. The Arduino gives an order to the motor driver circuit to control the wheelchair
motors and to move the wheelchair in the desired direction according to the direction of
movement of the patient's head. Figure 2 illustrates the block diagram of the receiving
part.
The patient wears the hat on his head to drive and control the wheelchair. In case of
forward head motion, the wheelchair moves forward, while it moves backward when the
head rotates in the back direction as in Fig. 3. When the patient moves his head to the
right side, the wheelchair moves to the right and vice versa for the left direction as
illustrated in Fig. 4. An ultrasound-sensor is placed in the back of the wheelchair to detect
obstacles behind the wheelchair in the case of rotating the head backward. The sensor
detects the obstacles on a range up to 50 cm then the Arduino holds the wheelchair back
moving to avoid collision with obstacles. Figure 5 illustrates a wheelchair model pictures
including the ultrasonic-sensor.
Accelerometer
Sensor
X-axis
Comparator
Y-axis
Comparator
Arduino RF-Transmitter
DC Driver Motor Circuit Arduino-UNO
RF
Receiver
Ultrasonic
Sensor Motor 1 Motor 2
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Fig. 3: Pictures show cases of patient head movement (forward and backward).
Fig. 4: Pictures show cases of patient head movement (left and right).
Fig. 5: Pictures of side and back of the wheelchair.
Ultrasonic
Sensor
ArduinoUNO
RF433 MHz
Receiver
Batteries
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The programming code is written then uploaded to the Arduino UNO board to be
programmed. Figure 6 shows the practical system of the block diagram which is explained
in Fig. 3. It shows the patient's hat including accelerometer sensors (ADXL345), Arduino
UNO, and RF433 MHz transmitter. Figure 7 shows the flowchart of the overall system. At
first, we make a suitable configuration for the motors, accelerometer, and ultrasonic
systems, then we connect them to the Arduino pins. The readings of the x and y axes of
the accelerometer are monitored to choose proper angles of head movement. Then, the
wheelchair moves in a direction that is compatible with the desired x and y axes values.
Fig. 6: Picture of practical transmitting system.
.
Fig. 7: Flow-chart of proposed system.
RF433 MHz
Transmitter
Patient's Hat
ADXL345 Accelerometer
Arduino UNO
Start
Make a suitable configuration for motors,
Accelerometer, and ultrasonic
Monitor the X and Y axes of the
Accelerometer reading
If -16< x <-15
If 3< x <4
Move the wheelchair to
right
Move the wheelchair
to left
If 8< y <9 Move the wheelchair to
forward
If 0< y <1
Stop
Yes
If ultrasonic
Reading= 0
Move the wheelchair
to Backward
No
Yes
No
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3. RESULTS AND DISCUSSION
The proposed system is based on the use of two Arduino UNO boards and an
accelerometer for hardware implementation of intelligent wheelchair control by head
gestures for people with QP. The software and hardware results show that the system
operates very well to help the patients and gives accurate results.
The system is set and calibrated so that the QP patient can properly control the
wheelchair. The patient wears the hat and moves his head in each direction to choose an
appropriate angle of his head movement. The horizontal angles (right and left) have been
selected to be 35 degrees, as shown in Fig. 8. These angles allow the QP patient to move
his head in all directions to some extent, and provides comfortable conditions for the
patient without moving the wheelchair.
Fig. 8: Graph of degree of wheelchair direction versus horizontal head tilting degree.
The vertical angles (forward and backward) have been selected to be 40 degrees as
shown in Fig. 9. The vertical and horizontal angles can be modified to be appropriate to
many QP patient cases. Figure 10 illustrates the x and y axes sensor readings that represent
the horizontal and the vertical head tilting respectively, where the shaded areas act the
corresponding wheelchair movement. When the patient moves his head to the left or the
right, then the reading of x-axis of the accelerometer sensor changed gradually and when
he moves his head forward or backward, then the reading of y-axis of the accelerometer
sensor changes. It is worth mentioning that when the head is in a straight position, the
sensor readings are about -6 for x-axis and 4.5 for y axis.
Table 1 displays the wheelchair performance accuracy which is calculated after
several trials of movement in all directions. For each direction, 50 trials were made to test
the wheelchair movement; the successful movements were as described in the table. The
performance accuracy was calculated by dividing the successful movements in each
-50
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
5
10
15
20
25
30
35
40
45
50
-50 -40 -30 -20 -10 0 10 20 30 40 50 Degree of head
tilting
Degree of wheel direction
Right Movement
Left Movement
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direction on the number of trials for the same direction. After calculating the accuracy for
each direction, the average performance accuracy was calculated to be about 97.5%.
Fig. 9: Graph of degree of wheelchair direction versus vertical head tilting degree.
Fig. 10: Head tilting angles and their wheelchair movement response.
Table 1: system performance accuracy
Movement Trials
number
Successful
Outcomes
Accuracy
Forward 50 50 100%
Backward 50 47 94%
Right 50 49 98%
Left 50 49 98%
Average accuracy : 97.5%
0
0.2
0.4
0.6
0.8
1
-70 -60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60 70
Degree of head tilting
Degree of wheel direction
0
1
2
3
4
5
6
7
8
9
-17-16-15-14-13-12-11-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
Vertical Head Tilting
Forward Movement
Backward Movement
Horizontal Head Tilting
Right-Backward
Right-Forward
Backward
Left-Backward
Right
Left
Left-Forward
Forward
Stop
Wheelchair Movement
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4. CONCLUSION
The proposed control system has been successfully designed and implemented to
move the wheelchair in four directions or to stay in same position based on a patient's head
tilting. This work is useful to support people with QP or disabled people by providing
alternative means to control the wheelchair by the movement of the head. The system also
provides a safety mechanism to prevent collision on a range of 50 cm in case of backward
movement of the wheelchair. The system has a very effective performance and high
accuracy, which is about 97.5%.
ACKNOWLEDGMENTS
The researchers thank the wounded officer in the Iraqi Army (Ahmed Hamza) who drove
the wheelchair easily.
REFERENCES
[1] Eun YK. (2016) Wheelchair navigation system for disabled and elderly people. MDPI
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[3] Chitte PP, Khemnar SB, Kanawade AA, Wakale SB. (2016) A hand gesture based
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[4] Anjaneyulu D, Siva K. (2015) Hand movements based control of an intelligent wheelchair
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[5] Shruti W, Vijayalaxmi H, Preeti D, Vishwanath B, Bhagavati PB. (2014) Speech and flex
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/ENU (Use these settings to create Adobe PDF documents suitable for reliable viewing and printing of business documents. Created PDF documents can be opened with Acrobat and Adobe Reader 6.0 and later.)
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>> setdistillerparams
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/HWResolution [600 600]
/PageSize [595.440 841.680]
>> setpagedevice