Skip to Main Content
This paper proposes a myoelectric-based virtual joystick to manipulate an electric powered wheelchair for people with severe motor disabilities. It is built on pattern recognition-based myoelectric control that discriminates muscular activities using forearmpsilas surface myoelectric signals. The core of the system is a support vector machine based classifier that classifies signal time domain features. Online training scheme is applied to cope with gradual changes in myoelectric signal patterns. Two indexes, contineousness and entropy, were used to update training data set in real time operation. The results confirm that the proposed myoelectric-based joystick is a reliable alternative for traditional joysticks and its performance is fairly acceptable.