Abstract
The number of amputees is increasing by industrial or traffic accidents, although safety control and accident prevention are made much of. Since amputees use prosthesis, the needs of prosthesis are increasing year after year. Myoelectric upper limb prosthesis, which considered the EMG signal measurable from residual sources as the control input, attracts attention. The purpose of this research is to construct an intelligence transradial prostheses control system, which uses electromyogram (EMG) signals. Signal processings of EMG signals are performed using a linear multiple regression model, which can learn parameters in a short time. Using this model, joint angles are predicted, and the motion pattern discrimination is conducted. Discriminated motions were grip, open, and chuck of a hand. Predicted joint angles were angles of multifinger corresponding to these three motions. From several experiments, the usefulness of processing EMG signals with a linear multiple regression model was proved.
