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Received December 18 2023, accepted May 6 2024, date of publication May 22, 2024

Development of a Voice-Controlled Wheelchair for Physically 
Impaired Individuals

By Jenina R. Amoguis, Mabel A. Lingon, Edwin R. Arboleda, Airah Cahigan

Department of Computer and Electronics Engineering, Cavite State University, Indang, Cavite, Philippines

ABSTRACT

Background and Objective: Traditional manual wheelchairs provide mobility to individuals with physical impairments but are 
poorly suited for individuals with a combination of physical and cognitive or perceptual impairments. Manual wheelchairs are 
more physically demanding than powered wheelchairs; however, powered wheelchairs require cognitive and physical skills that 
not all individuals possess. The general objective of this study is to develop a voice-controlled wheelchair that allows a disabled 
person to move around independently using a voice-recognition application that is interfaced with motors. The study will be 
beneficial for quadriplegic individuals who are paralyzed in both arms and both legs.
Material and Methods: This study aims to modify a standard wheelchair controlled by voice commands where the EasyVR 3 
Voice Recognition Module, ultrasonic sensors, microcontroller, and 12V wiper motor were integrated. Based on the signal given 
by the motor driving circuit, the controller switches the motor accordingly. The added safety feature is the ultrasonic sensor that 
senses obstacles with a fall detection system and sends a signal to the microcontroller to stop the chair.
Results: Through testing and evaluation, the device’s functionality was proven to meet the desired objectives, and the limita-
tions of the device were concluded. The motors and sensors were also found to be 100% functional. The average speed of the 
wheelchair is 0.2 m/s, and it can move with the user weighing up to 80 kg. The wheelchair lifts at an angle of up to 10˚. The 
overall acceptability of the unit, analyzed using statistical parameters like mean method and standard deviation analysis, gives a 
4.53 average, 4.53 on usability, 4.07 on correctness, 4.37 on control, 4.50 on reliability, 4.33 on safety, and 4.8 on comfort, which 
means the unit meets the objectives.
Conclusion: Based on the evaluation results, the project met the given objectives. The system was able to move following the 
voice command given. The device also proved its functionality, responsiveness, usability, correctness, control, reliability, safety, 
and comfortability. While the current study demonstrates the feasibility of voice-controlled wheelchairs, future research should 
focus on improving the accuracy and robustness of voice recognition systems and the incorporation of sensory feedback mecha-
nisms, such as haptic feedback or auditory cues. 

Keywords – Voice-controlled wheelchair, assistive technology, voice recognition, assistive devices, quadriplegia.

Copyright © 2024. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY): Creative Commons - Attribu-
tion 4.0 International - CC BY 4.0. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) 
are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is 
permitted which does not comply with these terms.



7 J Global Clinical Engineering Vol.6 Issue 3: 2024

Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

INTRODUCTION

Wheelchairs have been a boon for people with physical 
impairments, but they may not be suitable for individuals 
with a combination of physical and cognitive or percep-
tual disabilities. While manual wheelchairs require more 
physical effort, powered wheelchairs require cognitive 
and physical skills that not everyone possesses.1,2

To address these challenges, researchers conducted a 
study and devised a solution. They created a device using 
readily available and affordable materials and developed 
a voice-controlled wheelchair for disabled individuals 
who cannot operate powered wheelchairs.

The general objective of this study was to develop 
a voice-controlled wheelchair for physically impaired 
individuals. Specifically, this study aimed to (a) design 
and construct the circuitry of the device; (b) modify a 
standard wheelchair; (c) integrate the Easy VR 3 shield, 
ultrasonic sensor, microcontroller, 12V wiper motor, and 
standard wheelchair for the device; (d) develop a program 
for the device; (e) test and evaluate the performance of 
the system through pilot testing; and (f) determine the 
cost of the developed system.

The wheelchair could be used by people who suffer from 
mobility disabilities, which include cerebral palsy, spinal 
cord injury, stroke, Parkinson’s disease, arthritis, muscular 
dystrophy, multiple sclerosis, amputation, polio, or other 
conditions resulting in paralysis, muscle weakness, nerve 
damage, stiffness of the joints, strength and endurance, 
short stature, conditions like Osteogenesis Imperfecta 
(“brittle bones”), or lack of balance or coordination.3–7 
This device is also best for quadriplegic individuals who 
are paralyzed in both arms and both legs.8

The design project primarily focuses on recognizing a 
limited set of voice commands for direction control – five 
(5) in total - and two (2) voice commands for trigger and 
standby. It is not intended to perform any other tasks.

To evaluate the system’s effectiveness, final testing was 
conducted involving 30 participants, including 25 individu-
als who underwent testing in a simulated environment 
and 5 people with mobility disabilities. The assessment 
measured the system’s ability and responsiveness to 

execute commands accurately. The testing was carried 
out over two (2) weeks in Indang, Cavite, Philippines.

METHODS

This section outlines the important specifications of 
the materials utilized in the design project and the steps 
taken to create the voice-controlled wheelchair. Each 
material was carefully selected based on its functionality 
and compatibility with the other components. 

The voice-controlled wheelchair comprises a standard 
wheelchair, DC motor, voice recognition module, sensors, 
motor driver, microcontroller, and battery. The standard 
wheelchair used is an alloy-type wheelchair that weighs 
only 13.1 kgs compared to a standard wheelchair that 
weighs up to 16 kgs. It is certified by Japan International 
Standards, with a JIS sticker labeled JIS T 9201:2006, 
specifying standards for manually propelled wheelchairs.

The motors used in the project were wiper motors. 
Compared to other DC motors, wiper motors are cheaper 
and provide high torque and low speed, making them 
ideal for wheelchair use. The voice recognition module 
that was used was an EasyVR version 3 shield. Anjum 
and Seetha9 conducted a similar method where EasyVR 
version 3 shield was used as a voice-activated system for 
disabled people. Unlike voice recognition modules that only 
support speaker-dependent features, the EasyVR module 
supports speaker-dependent and speaker-independent 
features. Ultrasonic sensors were used because they are 
the only type of sensor that doesn’t depend on lighting. 
These sensors use ultrasonic frequency to detect objects

The main component used in the motor driver was a 
PNP-NPN Darlington pair transistor. This fast-switching 
device can operate up to 10A, making it a better option 
than relays that cannot operate above 4Hz. The transistor 
can be easily controlled using pulse width modulation 
techniques. The microcontroller used in this project was a 
Gizduino V4.1. Arboleda et al.10 used Gizduino AtMega644 
for smart wheelchairs using touchpad and Android device. 
Compared to the Arduino Uno and Gizduino AtMega644, 
the Gizduino V4.1 is cheaper and more user-friendly, which 
was used in this design. Finally, the battery used was a 
12V 17Ah lead acid battery. This battery is lightweight 
and cheap yet provides a high capacity.



Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

J Global Clinical Engineering Vol.6 Issue 3: 2024  8

Design of the Voice-Controlled Wheelchair

The microphone was placed slightly to one side of the 
mouth (Figure 1) and will then convert the voice signal to 
an electric signal. It was covered with a sponge to suppress 
echo and noise and compress the input voice.

FIGURE 1. The microphone is placed slightly to one side of 
the mouth.

The motor driver used was transistor-based. It has a 
high-current and voltage NPN and PNP Darlington pair. This 
provides faster switching capabilities compared to relays 
(8). It was connected to the back wheel and responded 
according to the given command of the microcontroller. 
Wiper motors were also used to provide mobility in the 
wheelchair. Using a chain, the wiper motors lead the direc-
tion of the back wheel, as shown in Figure 2. Through the 
use of a chain drive, the motor torque was increased. The 
wiper motor was not directly attached to the back wheel.

FIGURE 2. The chain used to connect the wiper and back wheel.

The sensors used were HC-SR04 ultrasonic sensors.11 
Compared to infrared and proximity sensors, this provides 
accurate readings on solid objects, even in dark or bright 
rooms. The sensors were placed on the front and rear of 
the wheelchair, and the wheelchair automatically stops 
when the sensor detects a drop in terrain ahead (e.g., 
stairs) or an obstacle. Specifically, two ultrasonic sensors 
were placed at the front: 1 facing the floor (to detect ap-
proaching stairs) and 1 below the wheelchair (to detect 
approaching obstacles in the lower left front area), both 
within 1–200 cm, as shown in Figure 3. Lastly, two were 
placed at the back: 1 facing the floor (to detect approaching 
stairs) and 1 below the wheelchair (to detect approaching 
obstacles in the lower back area) as shown in Figure 4.

FIGURE 3. Attachment of front sensors.

FIGURE 4. Attachment of back sensors.

Modifying a Standard Wheelchair

A standard wheelchair was used in the study. This 
provides a control unit, a battery, and a driver unit. These 
components were attached and transformed the wheelchair 
into a voice-controlled wheelchair. The control unit includes 
the microphone, rocker switch, and light-emitting diode 
(LED) indicator. The microphone was placed slightly on 
one side of the user’s mouth. The LED indicators, shown 
in Figure 5, and the rocker switch were placed on the 
right armrest of the wheelchair. A fiberglass and sticker 



9 J Global Clinical Engineering Vol.6 Issue 3: 2024

Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

were used to cover the LED indicator. The EasyVR 3, 
microcontroller, and battery were placed on the flat bar 
and plastic casing below the wheelchair. Figure 6 shows 
the flat bar attached to the wiper motors and battery. Flat 
bars were added on the lower front of the wheelchair 
where the sensors are attached. The plastic casing for the 
shields and motor driver was placed on the lower part of 
the wheelchair. The driver unit includes a motor driver 
circuit and 2 wiper motors. The wiper motor and the back 
wheel of the wheelchair were welded into a sprocket in 
a machine shop. A chain connected the sprockets found 
on the wipers and back wheels. This provides easier 
maneuvering of the wheelchair.

FIGURE 5. LED Indicators placed on the right armrest.

FIGURE 6. Flat bar attachment for wiper motors, battery, and 
ultrasonic sensor.

Integrating the EasyVR 3, Ultrasonic Sensor, 
Microcontroller, 12V Wiper Motor, and Standard 
Wheelchair for the Device

The user drives the wheelchair by giving voice com-
mands converted to electric signals by the microphone 
and processed by the voice recognition module. The voice 
command is stored in memory and converted into digital 

signals using Analog-to-Digital Converters (ADC). The 
microcontroller receives the digital input, which then 
outputs a signal to the motor driving circuit, switching 
the motor accordingly. The ultrasonic sensor senses 
obstacle with a fall detection system and sends a signal 
to microcontroller to stop the chair. The block diagram 
of the voice-controlled wheelchair system is indicated 
in Figure 7.

FIGURE 7. Voice-controlled wheelchair system block diagram.

The voice recognition module was soldered into a 
shield to provide an easy connection with the micro-
controller. To connect the voice recognition module and 
microcontroller, the soldered voice recognition shield 
was attached to the Gizduino. A motor driver shield must 
be present since a motor cannot be directly connected 
to the microcontroller. This is an H-Bridge circuit that 
allows the microcontroller to control high-current mo-
tors. 4 input pins (2N222A transistor base in series with 
a 10KΩ resistor) were connected to the digital pins D5, 
D5, D9, and D10 of the microcontroller. The schematic of 
the motor driver and its physical connections are shown 
in Figures 8 and 9, respectively.

FIGURE 8. Motor driver schematic diagram.



Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

J Global Clinical Engineering Vol.6 Issue 3: 2024  10

FIGURE 9. Physical connections of the device.

After connecting the EasyVR 3, ultrasonic sensors, 
microcontroller, and 12V wiper motor, the motors were 
attached to the flat bar between the front and back wheels. 
This was done in a machine shop. Lastly, the sensors, mi-
crocontroller, motor driver circuit, and voice recognition 
module were mounted below the wheelchair. A plastic 
casing was used in the final casing of the voice-controlled 
wheelchair circuitry. This way, the voice recognition 
module, ultrasonic sensors, microcontroller, motors, and 
wheelchair were integrated.

Developing the Program for the Voice-Controlled 
Wheelchair

The Arduino ATmega 328 microcontroller was pro-
grammed using C / C ++ language. This language was used 
to develop the software to control the wheelchair based 
on the data received from the voice recognition module. 
A predefined list of words controls the application with 
only a modest amount of RAM and program memory. The 
word list was created with the Arduino library. The Arduino 
is a PC-based program that lets users select and imple-
ment the user interface vocabulary. Those settings were 
recorded in memory. This memory was not lost even with 
the power off. The Voice Recognition Library provides an 
audio interface to a user’s application program, allowing 
the user to control the application by uttering discrete 

words in a predefined word library. The words chosen 
for the library are relevant to the interaction between 
the application program and the user.

A word spoken through a microphone connected to the 
voice recognition module was analyzed on a frame-by-
frame basis and quantized into feature vectors of sound 
characteristics against a vector codebook. The quantized 
feature vectors were then examined to determine which 
word they most closely match. The binary outputs were 
generated from the voice recognition module, which were 
set as a parameters for the program. The microcontroller 
received the converted voice from the voice recognition 
module. The application program takes appropriate action 
based on the parameters set by the developed program. 
However, once the obstacle and fall detection is active, 
the motors will automatically place the wheelchair in a 
safer place (Figures 10 and 11).

FIGURE 10. Software Flowchart for Speaker Dependent.

Project Testing

Before evaluating the wheelchair, the researchers pilot-
tested the project. The project was tested in the Engineering 
Science Building, College of Engineering and Information 
Technology (CEIT), Cavite State University, Indang, Cavite, 
Philippines. The motors, voice recognition, and sensors 
were tested by giving different voice commands.



11 J Global Clinical Engineering Vol.6 Issue 3: 2024

Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

Project Evaluation

The researchers evaluated the system’s functionality in 
technical evaluation. This is done to identify if the opera-
tions that can be run on the wheelchair are attained. This 
includes tests for each sensor and motor integrated with 
the wheelchair. This way, the wheelchair is placed and 
tested in a quiet room with obstacles like chairs, walls, 
tables, and stairs. The second is placing the wheelchair in 
a room filled with random noise. All of these tests were 
repeated twice; the first is for speaker-independent, and 
the second is for speaker-dependent. The researchers 
identified which of these two features is more efficient.

In the acceptability test, the respondents conducted a 
final test on the device to evaluate usability, correctness, 
control, reliability, safety, and comfort by giving any desired 
voice command. This was done by gathering data from the 
respondents that used the device. The sampling method 
employed was opportunity sampling, whereby individuals 
from the target population who were available and will-
ing to participate were selected to evaluate the device.12 
This includes a total of 30 respondents, which include 25 
students selected from a sample of students at the CEIT 
and 5 persons who suffer from mobility disability. The 
respondents evaluated the device in a simulated envi-
ronment. Each respondent was tied up in the simulated 
environment while using the device. To implement this, 
a hand and foot strap was provided on the wheelchair.

A clearance was sought first from the Ethics Review 
Board to ensure that the device was ready for Persons 
with Disabilities’ (PWD) evaluation. They also gave any 
desired voice commands on the wheelchair.

The evaluation results are analyzed using statistical 
parameters like mean method and standard deviation 
analysis. Tables are used to present and discuss the re-
sults gathered.

Ethical Considerations

Prior to using the wheelchair, the researchers provided 
a detailed explanation of how it is operated. During the 
evaluation, no harm was done to any of the patients. A 
physical therapist also accompanied the researchers to 
provide medical assistance if needed. An informative 
document/manual was attached to the questionnaire 
to ensure the user was seated properly. The following 
parameters were taken into consideration: (a) The user 
is sitting upright in the chair; (b) The pelvic/seat belt is 
secured firmly; (c) The feet are placed flat on the ground; 
(d) The knees are aligned with the hips; (e) The trunk and 
pelvis are centered; (f) The head is centered with the chin 
slightly tucked; (g) The elbows are bent at a 90-degree 
angle; and (h) The chest is lifted. 

Confidentiality and Informed Consent

Maintaining the participant’s anonymity was also ob-
served. They were not required to give their name or share 
personal information with the researchers. Moreover, the 
participants were given informed consent so that they 
could decide whether to participate or not.

PWDs’ Evaluation Location and Compensation

Those participants who suffer from mobility disabilities 
were visited at General Emilio Aguinaldo Medical Hospi-
tal, Trece Martires, Cavite, Philippines. They were given 
compensation like a pack of assorted fruits. In answer-
ing the questionnaire, the patients were assisted by the 
researchers and his/her guardians.

RESULTS

Through this, the researchers could identify which 
voice recognition feature, speaker-dependent and 

FIGURE 11. Software Flowchart for Speaker Independent.



Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

J Global Clinical Engineering Vol.6 Issue 3: 2024  12

speaker-independent, was more responsive. Moreover, as 
a possible strategy to reduce noise, the effect of wearing 
a helmet was also evaluated for both features. 

The motors and sensors were found to be 100% func-
tional. This was done by giving 10 trials per command and 
recording whether the voice was recognized successfully 
or not. The number of trials was based on the study titled 
“Design and Development of Voice Controllable Wheelchair,” 
which also corresponds to the number of trial testing of 
the wheelchair’s functionality.13 The device’s accuracy was 
proven good for speaker-dependent, while for speaker-
independent, the accuracy was excellent. Table 1 shows 
the calculated rating for each word spoken through the 
EasyVR using the speaker-dependent feature. It has a low 
recognition rating for noisy environments, showing that 
the EasyVR is susceptible to noise.

TABLE 1. Functionality and Responsiveness Calculations Using 
Speaker-Dependent

Noisy 
Environment

Quiet 
Environment

Spoken Word
No. of Correct 

Recognized 
Word

No. of Correct 
Recognized 

Word
Start 10 10

Go 4 10
Back 1 10
Left 1 10

Right 0 10
Stop 1 9

Standby 0 7
Average 24.29 94.29

Total Average 59.29

Table 2 shows the calculated rating for each word spo-
ken through the EasyVR using the speaker-independent 
feature. Comparing the results from Table 1, it can be 
shown that the EasyVR is less susceptible to noise using 
speaker independent.

TABLE 2. Functionality and Responsiveness Calculations Using 
Speaker-Independent

Noisy 
Environment

Quiet 
Environment

Spoken Word
No. of Correct 

Recognized 
Word

No. of Correct 
Recognized 

Word
Start 9 10

Go 8 10
Back 6 10
Left 6 10

Right 5 10
Stop 7 10

Standby 7 10
Average 68.57 100

Total Average 84.29

Table 3 shows the calculated rating for each word 
spoken through the EasyVR while wearing a helmet for 
both features. Comparing the results from Tables 1 and 
2, it can be shown that the EasyVR is less susceptible to 
noise while wearing a helmet for speaker-dependent and 
speaker-independent.

TABLE 3. Functionality and Responsiveness Calculations while 
Wearing a Helmet

Speaker Dependent Speaker Independent

Spoken 
Word

No. of Cor-
rect Recog-
nized Word

Spoken 
Word

No. of Cor-
rect Recog-
nized Word

Start 10 Move 10
Go 6 Forward 9

Back 1 Backward 6
Left 2 Left 7

Right 1 Right 7
Stop 3 Stop 8

Standby 1 Down 7
Average 34.29 Average 77.14



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Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

Table 4 shows that the percent error of a well-trained 
speaker dependent is two times greater than the speaker-
independent speech recognition. The error percentage 
was reduced by 10% when wearing a helmet for both 
features. The table suggests that the most effective feature 
is speaker-independent.

Percent Error = 

TABLE 4. Comparison of Speaker Dependent and Speaker 
Independent

Speaker 
Dependent

Speaker 
Independent

Software

The software 
learns the char-

acteristics of 
the user’s voice 

through training

It does not re-
quire training in 

the software

User

Works only to 
the trained user 

to recognize 
commands

Able to recog-
nize commands 

by different 
users 

Accuracy (% 
error)Noisy 

Environment
75.71% 31.43%

Accuracy (% 
error)Quiet 

Environment
5.71% 0 %

Reducing noise 
in wearing a hel-

met(% error)
65.71% 22.86%

The wheelchair’s speed was calculated by dividing the 
distance travelled over time. It was determined that the 
wheelchair has an average speed of 0.2m/s with a person 
weighing 46 kilograms. The maximum weight capacity 
was determined by letting users with different weights, 
specifically, 46 kgs, 53 kgs, 61 kgs, 68 kgs, 72 kgs, and 80 
kgs, sit on the wheelchair. With a user weighing 80 kgs, 
a noticeable decrease on the wheelchair’s speed was 
observed. Figure 11 shows the effect of the user’s weight 
on the wheelchair’s speed.

FIGURE 12. Speed versus weight.

The usability, correctness, control, reliability, safety, 
and comfort were gathered. A total of 30 respondents (25 
students and 5 PWDs) were the participants who answered 
the questionnaire after they had used the wheelchair. Table 
5 shows the user acceptability computations evaluated 
by 25 students at Cavite State University, Indang, Cavite, 
Philippines when the wheelchair was evaluated. It also 
shows that the usability, correctness, control, reliability, 
safety, and comfort of the wheelchair have low standard 
deviation. This means the device met the expected objec-
tive, and the system was considered efficient.

TABLE 5. User Acceptability Computations for Healthy Persons

General Qualities 
of the Wheelchair Mean Standard 

Deviation
Usability 4.6 0.58

Correctness 4.16 0.75
Control 4.4 0.71

Reliability 4.64 0.57
Safety 4.48 0.59

Comfort 4.84 0.47

Table 6 shows the user acceptability computations evalu-
ated by 5 persons who suffered from mobility disability 
when the wheelchair was evaluated. PWDs evaluated it 
after the device was used by healthy persons and rated 



Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

J Global Clinical Engineering Vol.6 Issue 3: 2024  14

the device as acceptable. It also shows that the usability, 
correctness, control, reliability, safety, and comfort of the 
wheelchair have low standard deviation. This means that 
the device met the expected objective, and the system was 
considered efficient for persons with mobility disabilities.

TABLE 6. User Acceptability Computations for PWDs

General Qualities of 
the Wheelchair Mean Standard 

Deviation
Usability 4.2 0.45

Correctness 3.6 0.55
Control 4.2 0.45

Reliability 3.8 0.45
Safety 3.6 0.89

Comfort 4.6 0.55

Table 7 shows the overall user acceptability of the 
wheelchair. The mean and standard deviation evaluated 
by PWDs and students were combined.

TABLE 7. Overall User Acceptability Computations

General Qualities 
of the Wheelchair Mean Standard 

Deviation
Usability 4.53 0.57

Correctness 4.07 0.74
Control 4.37 0.69

Reliability 4.5 0.63
Safety 4.33 0.71

Comfort 4.8 0.48

Table 8 shows the actual cost of the voice-controlled 
wheelchair. This included the main parts of the device 
as well as the casing and screws. The unit cost was 
$369.48, comprising all materials essential to the device’s 
construction.

TABLE 8. Total Cost of Device Construction

Materials Quantity Unit Cost 
(USD)

TOTAL 
COST (USD)

Microcon-
troller (giz-
Duino v3)

1 14 14

EasyVR 
Shield 1 52 52

Ultrasonic 
Sensor 4 5 20

12V 17Ah 
Lead Acid 
Recharge-

able Battery

1 18 18

Battery 
Charger 1 15 15

Standard 
Wheelchair 1 79 79

TIP147 4 2 6
TIP142 4 1 4
2N222A 4 0.5 2
LM7809 1 0.4 0.4
Terminal 

Blocks 3 0.6 1.8

Resistor 8 0.035 0.28
12” × 12” 
Pre-sensi-

tized Circuit 
Board

1 3 3

Wiper 
Motor 2 18 36

Chain 2 5 10
Sprocket 2 8 16

Plastic 
Casing 1 1 1

Labor - - 73
Miscella-

neous Fees - - 18

TOTAL   $369.48



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Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

DISCUSSION

Wheelchairs are crucial for people with paralysis, 
muscle weakness, or any condition that limits their mo-
bility. There are two types of wheelchairs: manual and 
powered. Manual wheelchairs require more physical ef-
fort, while powered wheelchairs demand cognitive and 
physical skills that not everyone possesses. To address 
this issue, researchers have developed a voice-controlled 
wheelchair that allows disabled individuals to move 
around independently. This wheelchair uses a voice rec-
ognition application connected to motors, enabling it to 
receive and perform voice commands given by the user. 
The microcontroller can be programmed to recognize a 
single user’s voice or any voice command.

After conducting a technical evaluation, it was observed 
that the wheelchair was prone to noise, with only 17 out of 
70 spoken words being recognized correctly as speaker-
dependent and 48 out of 70 as speaker-independent. 
However, a helmet helped reduce noise and increased the 
number of correctly recognized spoken words to 24/70 for 
speaker-dependent and 54/70 for speaker-independent. 
This shows that wearing a helmet can significantly improve 
speech recognition accuracy. Furthermore, in situations 
with minimal noise, 66 out of 70 spoken words were 
recognized correctly for speaker-dependent and all 70 for 
speaker-independent. Hence, the speaker-independent 
feature was more accurate and responsive, and the survey 
was conducted using this feature. 

The testing and evaluation of the wheelchair showed 
that it met the desired objectives and limitations of the 
device. The motors and sensors were fully functional, and 
the wheelchair could move at an average speed of 0.2 m/s, 
carrying a weight of up to 80 kg and lifting at an angle of 
up to 10˚. The overall acceptability of the unit was rated 
at an average of 4.53, with ratings of 4.53 for usability, 
4.07 for correctness, 4.37 for control, 4.50 for reliability, 
4.33 for safety, and 4.8 for comfort. This indicates that 
the unit meets the objectives.

Due to its wiper motor design, the device only responds 
to stored voice commands and cannot be manually con-
trolled. Ultrasonic sensors work well for detecting obstacles 

and stairs but have limited detection range and angle. The 
front sensor only detects obstacles on the left side, and 
the system cannot detect objects beyond 200 cm.

Table 8 presents the cost breakdown of the developed 
system, including the main components of the device as 
well as the casing and screws. The total unit cost was 
$369.48, covering all the necessary materials to construct 
the device.

Several studies and articled were synthesized to assess 
the effectiveness of the device. A research study, “Design 
and Development of Voice Controllable Wheelchair” 
published in 2022, is relevant to the methods and block 
diagram employed in this study for the voice-controlled 
wheelchair.13 The study found that the Arduino analyzed 
the user’s voice commands before transmitting the signal 
to the driver circuit which is similar to the process of this 
study, as depicted in Figure 7. Another study titled “Voice 
Controlled Automatic Wheelchair” produced similar posi-
tive outcomes to this research, although it used Arduino 
R3 as the wheelchair’s primary processing unit.14 A simi-
lar study titled “Development of a Low-cost Electronic 
Wheelchair with Obstacle Avoidance Feature” shows 
similar findings where ultrasonic sensors for obstacle 
avoidance and infrared sensors were also installed and 
thus gave out positive results concerning the individuals 
involved in the testing and evaluation.15 The researcher 
compared the project's overall cost with a similar study 
called “Design of an Arduino Based Voice-Controlled Au-
tomated Wheelchair.”16 The cost of the mentioned study 
was close to the cost of the wheelchair developed in this 
study, indicating that the cost of components and materials 
used to develop this project is not too high. These studies 
validate the efficacy of the techniques and results in this 
research study, which contributes to the knowledge base 
of voice-automated wheelchairs.

Numerous studies have shown that access to indepen-
dent mobility benefits children and adults. It enhances 
their educational and vocational opportunities, reduces 
their reliance on family members and caregivers, and 
promotes feelings of self-reliance.



Amoguis, Lingon, Arboleda, Cahigan: Development of a Voice-Controlled Wheelchair for Physically Impaired Individuals

J Global Clinical Engineering Vol.6 Issue 3: 2024  16

CONCLUSIONS

Upon careful observation and analysis of gathered 
results, the Development of a Voice-Controlled Wheel-
chair for Physically Impaired Individuals has successfully 
met all desired objectives. The wheelchair is designed to 
respond to voice commands, allowing users to navigate 
and control the device through vocal instructions. With 
the capability to detect obstacles and stairs, the unit can 
automatically halt its movement, ensuring the safety and 
convenience of the user. This research study has demon-
strated that technological advancements, particularly in 
trained and reprogrammed modules, can yield significant 
breakthroughs in the equipment used by patients in 
hospital wards. With proper orientation and guidance, 
individuals with physical impairments can operate a 
low-cost wheelchair using voice commands. 

Recent advancements in technology have enabled 
patients to move independently without relying on the 
assistance of hospital staff or their loved ones. By utilizing 
voice commands, individuals with physical impairments 
can effortlessly control their movement, ensuring greater 
independence and convenience in their daily activities. 

This research serves as a foundation for future studies, 
allowing for integrating more advanced technologies into 
voice-controlled wheelchairs. Ultimately, this study has 
the potential to improve the quality of life for individuals 
with physical impairments and those who aim to enhance 
the lives of individuals who cannot care for themselves 
effectively. 

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17 J Global Clinical Engineering Vol.6 Issue 3: 2024

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