High Accurate Discrimination Method of Forearm Motions from Surface Electromyogram and its Condition | Zendy

Yoshio Nishikawa | Zendy; Yoshihito Kagawa | Zendy; Jun Kurabayashi | Zendy

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High Accurate Discrimination Method of Forearm Motions from Surface Electromyogram and its Condition

Author(s) -

Yoshio Nishikawa,

Yoshihito Kagawa,

Jun Kurabayashi

Publication year - 2011

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2011.p0545

Subject(s) - computer science , electromyography , artificial intelligence , motion (physics) , forearm , computer vision , wavelet transform , wavelet , surface (topology) , mistake , pattern recognition (psychology) , mathematics , physical medicine and rehabilitation , medicine , geometry , pathology , political science , law

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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