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Digital Fractional Order Low-pass Differentiators for Detecting Peaks of Surface EMG Signal

표면 근전도 신호 피이크 검출을 위한 디지털 분수 차수 저역통과 미분기

  • Lee, Jin (Dept. of control&instrumentation Eng., Kangwon National Univ.) ;
  • Kim, Sung-Hwan (School of electrical and computer Eng., Univ. of Seoul)
  • 이진 (강원대학교 삼척캠퍼스 제어계측공학과) ;
  • 김성환 (서울시립대학교 전자 전기 컴퓨터공학부)
  • Received : 2013.03.28
  • Accepted : 2013.06.19
  • Published : 2013.07.01

Abstract

Signal processing techniques based on fractional order calculus have been successfully applied in analyzing heavy-tailed non-Gaussian signals. It was found that the surface EMG signals from the muscles having nuero-muscular disease are best modeled by using the heavy-tailed non-gaussian random processes. In this regard, this paper describes an application of digital fractional order lowpass differentiators(FOLPD, weighted FOLPD) based on the fractional order calculus in detecting peaks of surface EMG signal. The performances of the FOLPD and WFOLPD are analyzed based on different filter length and varying MUAP wave shape from recorded and simulated surface EMG signals. As a results, the WFOLPD showed better SNR improving factors than the existing WLPD and to be more robust under the various surface EMG signals.

Keywords

References

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