Development of the hand motion recognition system based on surface EMG using suitable measurement channels for pattern recognition

Abstract

Conventional research on motion recognition using surface electromyogram (SEMG) is mainly focused on how to process with the signals for pattern recognition. However, it is of much consequence to the motion recognition that measurement channels position including useful information about SEMG pattern recognition is selected. In this paper, we present two topics for the hand motion recognition system based on SEMG. First described is the method to select the suitable measurement channels position of multichannel SEMG for the recognition of hand motion, and the second described is an applied systems based on our proposed method. About channel selection, we use a multichannel matrix-type surface electrode attached to the forearm in order to measure the SEMG generated from many active muscles during hand motions. From those electrodes, system decided the number of measurement channels and the position of measurement channels. This can be achieved by using the Monte Carlo method. The recognition experiments of 18 hand motions show that the average rate was measured to be greater than 96%. And the number of selected channels ranged from 4 to 7. About applied systems, our developed system works as an input interface for the computer (keyboard and pointing device) and a robot hand.