Coordination between Visualization and Execution of Movements

Abstract

Individuals living with disabilities often encounter difficulties in executing coordinated movements, particularly those with limited mobility due to conditions such as paralysis, arthritis, or spinal cord injuries. Traditional electric wheelchairs, primarily controlled through upper body strength, may be inaccessible to those with severe upper limb impairments. This study aimed to develop an innovative solution using Electromyography (EMG) technology to enable individuals with limited upper body mobility to control wheelchairs effectively. The objective was to create a user-friendly EMG-based wheelchair control system that interprets hand gestures and converts them into multi-directional commands. The research involved the development of an EMG-based wheelchair control system that recorded EMG signals from the users' hands and analyzed them for controlling forward, left, and right movements. Extensive testing was conducted with three subjects to evaluate the system's accuracy. The results were quantified regarding error percentages and compared among the subjects. The study yielded promising outcomes. Subject A exhibited a 1% error rate for right-hand movement and a 1.85% error rate for left-hand movement. Subject B achieved a 2.84% error rate for right-hand movement and a 1% error rate for left-hand movement. Subject C demonstrated a 3.84% error rate for right-hand movement and a 0% error rate for left-hand movement. The developed EMG-based wheelchair control system offers a viable solution to enhance mobility and independence for individuals with limited upper body mobility. The microprocessor-integrated design significantly improves the reliability and user-friendliness of the system. The research underscores the potential of EMG technology in bridging the gap between visualization and execution of movements for those facing mobility challenges.