1-413 筋活動電位によるモバイル端末用インターフェースの開発

概要

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Recently, information terminals and mobile phones are widely used. In general, there are some pointing devices such as mouse, data glove, data suit, motion capture, which can measure data such as position, direction, and power. However, these devices are not always comfortable and convenient to use because of their shape and weight in the market. Consequently, we need to develop a new type of input interface whose operation is easier and shape is smaller. We have paid attention to Electromyogram (EMG) which is discussed for an artificial arm or hand about medical use. EMG is generated according to the person's behavior, which contains various level of the power on the wrist behavior. In this paper, we apply neuro-technology to wrist behavior recognition using EMG. We measure EMG on the wrist. We adopt a dry type electrode for 4 channels to detect 6 kinds of pattern on the wrist behavior. They are extension, flexion, pronation, supination, open, grasp. Especially, dry type electrode enables to simplify the system handling. Still more, we refer to online tuning for the proposed system using DSP board and continuous neuro learning to improve its recognition ability. Finally, we show its basic ability and possibility by the simulation.
一般社団法人日本機械学会の論文
2002-11-14