Development and evaluation of a head-controlled wheelchair system for users with severe motor impairments

This paper presents an innovative and accessible hands-free wheelchair control system designed for individuals with severe motor impairments, particularly tetraplegic users. Unlike traditional joystick-based systems, which are often unsuitable for users with quadriplegia, our system relies on intuitive head-motion detection to enhance autonomy and ease of use. The system consists of a wearable motion-sensing cap equipped with an MPU-6050 sensor which is a 6-axis Inertial Measurement Unit (IMU) to capture head gestures, processed by an ATmega328 microcontroller (a low-power 8-bit AVR microcontroller widely used in embedded systems) integrated on an Arduino Nano development board. Wireless commands are transmitted via a Bluetooth module (HC-05) to the wheelchair's control unit consisting of an Arduino Uno microcontroller and BTS7960 motor drivers - high-power H-bridge modules that enable bidirectional control of DC motors. The operational flow, including signal processing, gesture interpretation, and wireless transmission, is structured following a detailed flowchart-based design. Experimental results indicate a high response rate and directional accuracy of over 90 % using a 45° head tilt. The optimal safe speed was determined to be 1.87 km/h with a Pulse Width Modulation (PWM) value of 180. Rather than designing a mechanical chassis from scratch, a commercially available electric wheelchair was modified by removing its joystick interface, allowing seamless integration of the head-controlled system. These findings validate the system's usability and precision under real-world conditions. By eliminating manual input and emphasizing simplicity, the proposed solution holds strong potential as a scalable and low-cost mobility aid, especially in low-resource environments.

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Publication Details

Journal
MethodsX
Published
2025-07-05
DOI
https://doi.org/10.1016/j.mex.2025.103485
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
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article

Development and evaluation of a head-controlled wheelchair system for users with severe motor impairments

Mohamed Benbouzid, A. Haddoun, M. Saidani, Dâlel Djabri
1 links
MethodsX
Gaze Tracking and Assistive Technology
article

Development and evaluation of a head-controlled wheelchair system for users with severe motor impairments

Mohamed Benbouzid, A. Haddoun, M. Saidani, Dâlel Djabri
article en

Abstract

This paper presents an innovative and accessible hands-free wheelchair control system designed for individuals with severe motor impairments, particularly tetraplegic users. Unlike traditional joystick-based systems, which are often unsuitable for users with quadriplegia, our system relies on intuitive head-motion detection to enhance autonomy and ease of use. The system consists of a wearable motion-sensing cap equipped with an MPU-6050 sensor which is a 6-axis Inertial Measurement Unit (IMU) to capture head gestures, processed by an ATmega328 microcontroller (a low-power 8-bit AVR microcontroller widely used in embedded systems) integrated on an Arduino Nano development board. Wireless commands are transmitted via a Bluetooth module (HC-05) to the wheelchair's control unit consisting of an Arduino Uno microcontroller and BTS7960 motor drivers - high-power H-bridge modules that enable bidirectional control of DC motors. The operational flow, including signal processing, gesture interpretation, and wireless transmission, is structured following a detailed flowchart-based design. Experimental results indicate a high response rate and directional accuracy of over 90 % using a 45° head tilt. The optimal safe speed was determined to be 1.87 km/h with a Pulse Width Modulation (PWM) value of 180. Rather than designing a mechanical chassis from scratch, a commercially available electric wheelchair was modified by removing its joystick interface, allowing seamless integration of the head-controlled system. These findings validate the system's usability and precision under real-world conditions. By eliminating manual input and emphasizing simplicity, the proposed solution holds strong potential as a scalable and low-cost mobility aid, especially in low-resource environments.

MethodsXVol. 15
Centre National de la Recherche Scientifique (FR), Université de Bretagne Occidentale (FR), Dalian University of Technology (CN), Larbi Ben M'hidi University of Oum El Bouaghi (DZ), Institut de Recherche Dupuy de Lôme (FR)
Openalex Percentile: Top 84%
Gaze Tracking and Assistive Technology
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