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On Pattern Classification of EMG Signals for Walking Motions
H,-L,Choi,H,-J,Byun,W,-G,Song,J,-W,Son,J,-T,Lim 한국과학기술원 인간친화 복지 로봇 시스템 연구센터 2001 International Journal of Assistive Robotics and Me Vol.2 No.3
In this paper, we present a method to classify electromyogram (EMG) signals which are utilized to control signals for patient-responsive walker-supported system for paraplegics. Patterns of EMG signals for different walking motions are classified via adequate filtering, real EMG signal extraction, AR-modeling, and modified self-organizing feature map (MSOFM). In particular, a data-reducing extraction algorithm is employed for real EMG signals. Moreover, MSOFM classifies and determines the results automatically using a fixed map. Finally, the experimental results are presented for validation.