대한전기학회논문지:시스템및제어부문D (The Transactions of the Korean Institute of Electrical Engineers D)

대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

시스템잡음에 강건한 SOM-TVC 기법을 이용한 근전도 패턴 인식에 관한 연구

A Study on the EMG Pattern Recognition Using SOM-TVC Method Robust to System Noise

  • 김인수 (서울시립대학 전자전기컴퓨터공학부) ;
  • 이진 (삼척대학교 제어계측공학과) ;
  • 김성환 (서울시립대학 전자전기컴퓨터공학부)
  • 발행 : 2005.06.01
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초록

This paper presents an EMG pattern classification method to identify motion commands for the control of the artificial arm by SOM-TVC(self organizing map - tracking Voronoi cell) based on neural network with a feature parameter. The eigenvalue is extracted as a feature parameter from the EMG signals and Voronoi cells is used to define each pattern boundary in the pattern recognition space. And a TVC algorithm is designed to track the movement of the Voronoi cell varying as the condition of additive noise. Results are presented to support the efficiency of the proposed SOM-TVC algorithm for EMG pattern recognition and compared with the conventional EDM and BPNN methods.

키워드

참고문헌

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