表面筋電信号による無発声母音認識システムにおける自己組織化マップを用いたパターン解析

抄録

In this paper, we present some results of analysis on surface electromyogram (SEMG) using Self-Organizing -Maps (SOM) algorithm, which is one of the neural network algorithm, for unspoken vowel recognition system. Three pairs of electrodes were placed on facial muscles and SEMG signals were recorded. We have examined the classification of three pairs of the values of activity for each muscle using SOM algorithm. The SOM algorithm is also able to translate the multi-dimensional vectors of RMS values of SEMG signal into the two-dimensional map.