Work

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

Year: 2025

Type: article

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.

Source: MethodsX

DOI: 10.1016/j.mex.2025.103485

Authors: Abdelhakim Haddoun, Dâlel Djabri, Mallak Saidani, Mohamed Benbouzid

Institutions: Larbi Ben M'hidi University of Oum El Bouaghi, Dalian University of Technology, Centre National de la Recherche Scientifique, Université de Bretagne Occidentale, Institut de Recherche Dupuy de Lôme

Language: English

Topic: Gaze Tracking and Assistive Technology

Subfield: Human-Computer Interaction

Field: Computer Science

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Good health and well-being

Open Access status: gold

Estimated APC paid: $1,260