On Pattern Classification of EMG Signals for Walking Motions

• 영문명: On Pattern Classification of EMG Signals for Walking Motions
• 발행기관: 한국과학기술원 인간친화 복지 로봇 시스템 연구센터
• 저자명: H.-L. Choi H.-J. Byun W.-G. Song J.-W. Son J.-T. Lim
• 간행물 정보: 『International Journal of Assistive Robotics and Mechatronics』Journal of HWRS-ERC Vol.2 No.3, 1~4쪽, 전체 4쪽
• 주제분류: 공학 > 제어계측공학
• 파일형태: PDF
• 발행일자: 2001.11.01

영문 초록

  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

Abstract
1. INTRODUCTION
2. EMG SIGNAL PROCESSING
3. EXPERIMENT
4. CONCLUSIONS
5. REFERENCES

키워드

electromyogram(EMG) signal extraction algorithm modified self-organizing feature map(MSOFM)