Optimal mapping of torus self-organizing map for forearm motion discrimination based on EMG

This paper describes an optimal mapping of the torus self-organizing map for a human forearm motion discrimination based on the myoelectric signal. The high precision motion discrimination is necessary for the artificial hand control. This study proposes the mapping method of SOM that the learning result of the same motion concentrates on one place and the learning result group of each motion separates. As a result, the variance in the same motion group becomes small, and the variance between each motion groups becomes big. Some experiments on the myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.