Motion Artifact Elimination Using Fuzzy Rule Based Adaptive Nonlinear Filter (Special Section on Signal Processing and System Theory)

  • KIRYU T.
    Faculty of Engineering, Niigata University
  • Kaneko Hidekazu
    National Institute of Bioscience and Human-Technology, Agency of Industrial Science and Technology
  • Saitoh Yoshiaki
    Faculty of Engineering, Niigata University

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Myoelectric (ME) signals during dynamic movement suffer from motion artifact noise caused by mechanical friction between electrodes and the skin. It is difficult to reject artifact noises using linear filters, because the frequency components of the artifact noise include those of ME signals. This paper describes a nonlinear method of eliminating artifacts. It consists of an inverse autoregressive (AR) filter, a nonlinear filter, and an AR filter. To deal with ME signals during dynamic movement, we introduce an adaptive procedure and fuzzy rules that improve the performance of the nonlinear filter for local features. The result is the best ever reported elimination performance. This fuzzy rule based adaptive nonlinear artifact elimination filter will be useful in measurement of ME signals during dynamic movement.


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