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 cla...
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https://www.riss.kr/link?id=A76466687
2001
-
555
학술저널
1-4(4쪽)
0
상세조회0
다운로드다국어 초록 (Multilingual Abstract)
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 cla...
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.
목차 (Table of Contents)