제어로봇시스템학회:학술대회논문집

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Walking Motion Detection via Classification of EMG Signals

  • Park, H.L. (KAIST) ;
  • H.J. Byun (KAIST) ;
  • W.G. Song (KAIST) ;
  • J.W. Son (KAIST) ;
  • J.T Lim (KAIST)
  • Published : 2001.10.01
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Abstract

In this paper, we present a method to classify electromyogram (EMG) signals which are utilized to be control signals for patient-responsive walker-supported system for paraplegics. Patterns of EMG signals for dierent walking motions are classied via adequate filtering, real EMG signal extraction, AR-modeling, and modified self-organizing feature map (MSOFM). More efficient signal processing is done via a data-reducing extraction algorithm. Moreover, MSOFM classifies and determines the classified results are presented for validation.

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