Head Gestures Based Movement Control of Electric Wheelchair for People with Tetraplegia

• Published in: ICCSCE 2022 - Proceedings: 2022 12th IEEE International Conference on Control System, Computing and Engineering
• Main Author: Azraai M.A.M.; Yahaya S.Z.; Chong I.A.; Soh Z.H.C.; Hussain Z.; Boudville R.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142425368&doi=10.1109%2fICCSCE54767.2022.9935646&partnerID=40&md5=86c830433184b6d3e8e8cfa2b8b8dd18

People who have suffered a spinal cord injury (SCI) may experience temporary or permanent loss of motor function, sensory function, and autonomic function. Tetraplegia patients are only able to move their upper body parts, such as the head, neck, and shoulder. They require wheelchair assistance to move around for their daily activities. The existing electric wheelchairs, on the other hand, rely on the users' upper arm for control which makes it difficult for the tetraplegia patients to control it. To address this issue, this project developed a control system in which control can be performed by head gesture. A gyro accelerometer is used to detect the user's head gesture. A microcontroller connected to the sensor will read the data and translate it into instructions to control the movement of the electric wheelchair based on the pre-defined head motion patterns. To obtain an average test result of the system's functionality, the system was tested on a healthy adult subject. The average maneuvering error of the trial run using electric wheelchair model on the smooth surface was 3.18cm and an average 5.2cm on the rough tar road surface. Thus, the developed control system can be assumed to be effective in detecting head gesture and that it accurately maneuvers the electric wheelchair according to the head gesture pattern. © 2022 IEEE.