2A2-B08 ブレイン・マシン・インタフェースを用いた筋電義手の操作性改善 : 筋電位を用いた前腕動作8種の識別(福祉ロボティクス・メカトロニクス(2))

抄録

This article proposes a myoelectric prosthetic hand control system using a brain machine interface that uses electromyogram signals and other biosignals such electroencephalographic signals. The proposed system consists of a feature vector extractor, a neural network estimator, a reference trajectory generator, and an adaptive corrector. As a preparation, an experimental system has been prototyped without adaptive correction using other biosignals. The system is to classify 8 forearm motions by using 2 electromyogram signals and to generate reference trajectories for servo controllers of a prosthetic hand. The experimental results showed that the proposed classification algorithm has basically worked well and that the reference trajectory generator has a potential to make appropriate smooth trajectories.