High Accurate Discrimination Method of Forearm Motions from Surface Electromyogram and its Condition
Yoshio Nishikawa*, Yoshihito Kagawa*, and Jun Kurabayashi**
*Graduate School of Engineering, Takushoku University, 815-1 Tatemachi, Hachioji, Tokyo 193-0985, Japan
**Faculty of Health Sciences, Kyorin University, 476 Miyashita-cho, Hachioji, Tokyo 192-8508, Japan
We propose high-speed motion discrimination method for three types of motions, pronating, flexing, and grasping without any mistake by acquired surface electromyography (EMG) signals from three locations on the right-forearm. To achieve high-speed and accurate method, we introduce motion discrimination method based on a comparison of features extracted by wavelet transform of EMG signals via a database, and also we examine the places on the forearm where the system acquires surface EMG signals. As a final, we discuss whether the discrimination rate was improved by motion training.
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