International journal of advanced smart convergence

  • 제12권3호
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  • Pages.211-220
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  • 2023
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  • 2288-2847(pISSN)
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  • 2288-2855(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
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Visualization of Motor Unit Activities in a Single-channel Surface EMG Signal

  • Hidetoshi Nagai (Department of Artificial Intelligence, Kyushu Institute of Technology)
  • 투고 : 2023.08.16
  • 심사 : 2023.09.06
  • 발행 : 2023.09.30
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초록

Surface electromyography (sEMG) is a noninvasive method used to capture electrically muscle activity, which can be easily measured even during exercise. The basic unit of muscle activity is the motor unit, and because an sEMG signal is a superposition of motor unit action potentials, analysis of muscle activity using sEMG should ideally be done from the perspective of motor unit activity. However, conventional techniques can only evaluate sEMG signals based on abstract signal features, such as root-mean-square (RMS) and mean-power-frequency (MPF), and cannot detect individual motor unit activities from an sEMG signal. On the other hand, needle EMG can only capture the activity of a few local motor units, making it extremely difficult to grasp the activity of the entire muscle. Therefore, in this study, a method to visualize the activities of motor units in a single-channel sEMG signal by relocating wavelet coefficients obtained by redundant discrete wavelet analysis is proposed. The information obtained through this method resides in between the information obtained through needle EMG and the information obtained through sEMG using conventional techniques.

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과제정보

This work was supported by JSPS KAKENHI Grant Number JP19K12205.

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