Fingers bending motion controlled electrical wheelchair by using flexible bending sensors with Kalman filter algorithm
Kok Seng Eu, Soon Loong Yong, Mum Wai Yip, Yoon Ket Lee, Ying Hao Ko, Kian Meng Yap · Contemporary Engineering Sciences · 2014
Severely disabled people have difficulties to use joystick in controlling electrical power wheelchair because controlling the joystick requires a large force which is more than the threshold for severely disabled people. It is difficult for them to use joystick to provide precise commands to the electrical system of the wheelchair because they cannot control over the deck tilt angles of joystick precisely. Thus, the idea of using fingers bending motion to control electrical wheelchair provides a solution for this problem. However, trembling fingers motions from disabled people generate signal noise that cause the motion control of the wheelchair not running smoothly. The objective of this paper is to tackle signal noises that are caused by trembling fingers motion. Three filtering methods were conducted which are Moving Average, Low-Pass, and Kalman Filters. The results indicate that Kalman Filter has significantly improved the smoothness of fingers bending command signal to the electrical wheelchair as compared to Moving Average and Low-Pass Filter.