• DocumentCode
    3045078
  • Title

    Novel time-frequency approach for muscle fatigue detection based on sEMG

  • Author

    Fengjun Bai ; Lubecki, Tomasz Marek ; Chee-Meng Chew ; Chee-Leong Teo

  • Author_Institution
    Dept. of Mech. Eng., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2012
  • fDate
    28-30 Nov. 2012
  • Firstpage
    364
  • Lastpage
    367
  • Abstract
    Muscle fatigue is the decrease in its ability to generate a target force. In this paper, a novel muscle fatigue detection algorithm based on sEMG signal is developed. Short-time Fourier transform (STFT) and continuous wavelet transform (CWT) are used to extract features of sEMG signal (mean frequency and signal power). Further signal power and the estimated power relative changes are calculated to derive the fatigue evaluation and generate the general fatigue levels. sEMG signals generated from subjects´ Biceps Brachii muscles under different muscle contraction trials were used to evaluate the feasibility and effectiveness of the proposed fatigue detection methods. Results from STFT and CWT are compared. The results also show that the proposed method is reliable in the analysis of muscle fatigue during isometric and dynamic contractions and quantifying the discrete muscle fatigue levels.
  • Keywords
    Fourier transforms; biomechanics; cellular biophysics; electromyography; feature extraction; medical signal processing; wavelet transforms; EMG signal; bicep brachii muscles; continuous wavelet transform; discrete muscle fatigue levels; dynamic contractions; estimated power relative changes; fatigue detection methods; fatigue evaluation; feature extraction; isometric contractions; muscle contraction trials; muscle fatigue detection algorithm; short-time Fourier transform; signal power; target force; time-frequency approach; Continuous wavelet transforms; Dynamics; Fatigue; Force; Muscles; Time frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Circuits and Systems Conference (BioCAS), 2012 IEEE
  • Conference_Location
    Hsinchu
  • Print_ISBN
    978-1-4673-2291-1
  • Electronic_ISBN
    978-1-4673-2292-8
  • Type

    conf

  • DOI
    10.1109/BioCAS.2012.6418421
  • Filename
    6418421