A Survey on Visual based Wheelchair Control System for ALS Impaired Patients

Abstract

Thanks to advancements in the construction of electric wheelchairs, people with motor limitations brought on by conditions like the amyotrophic lateral sclerosis (ALS) are now given the ability to become more independent and mobile. But operating and utilising an electric wheelchair often calls for a high level of ability. Additionally, certain individuals with mobility impairments are mechanically unable to regulate the movements of their hands, making it impossible for them to use a joystick to manually adjust an electric wheelchair (as in people with ALS). In this article, we suggest a system that would permit continuous real-time tracking in uncharted terrain and allow someone with a severe disabilities to regulate a wheelchair with eye gaze. The system is made up of a Raspberry Pi board with all the sensors wired up to it, a camera, and an IR sensor to detect objects, an accelerometer to move the wheelchair across all directions, a motor to move forward and backward, and a GPS module to locate the patient. The OpenCV method is presented to enable continuous real-time target detection, route planning, and navigation in uncharted territory. Interesting findings from a case study that involved an ALS patient are presented and examined. The participant performed better in terms of calibration time, task execution time, and maneuvering speed for trips in between office, dining room, and bedroom. Positive outcomes from listening to the carer included the participant driving the wheelchair with more assurance and avoiding mishaps throughout the experiment.