• DocumentCode
    1082437
  • Title

    Single site electromyograph amplitude estimation

  • Author

    Clancy, Edward A. ; Hogan, Neville

  • Author_Institution
    Dept. of Electr. Eng., MIT, Cambridge, MA, USA
  • Volume
    41
  • Issue
    2
  • fYear
    1994
  • Firstpage
    159
  • Lastpage
    167
  • Abstract
    Previous investigators have experimentally demonstrated and/or analytically predicted that temporal whitening of the surface electromyograph (EMG) waveform prior to demodulation improves the EMG amplitude estimate. However, no systematic study of the influence of various whitening filters upon amplitude estimate performance has been reported. The authors describe a phenomenological mathematical model of a single site of the surface EMG waveform and reports on experimental studies which examined the performance of several temporal whitening filters. Surface EMG waveforms were sampled during nonfatiguing, constant-force, isometric contractions of the biceps or triceps muscles, over the range of 10-75% maximum voluntary contraction. A signal-to-noise ratio (SNR) was computed from each amplitude estimate (deviations about the mean value of the estimate were considered as noise). A moving average root mean square estimator (245 ms window) provided an average±standard deviation (A±SD) SNR of 10.7±3.3 for the individual recordings. Temporal whitening with one fourth-order whitening filter designed per site improved the A±SD SNR to 17.6±6.0.
  • Keywords
    bioelectric potentials; muscle; physiological models; 245 ms; biceps muscle; moving average root mean square estimator; nonfatiguing constant-force isometric contractions; phenomenological mathematical model; signal-to-noise ratio; single site electromyograph amplitude estimation; surface EMG waveform; temporal whitening; triceps muscle; voluntary contraction; Amplitude estimation; Demodulation; Electromyography; Filters; Mathematical model; Muscles; Noise level; Root mean square; Signal to noise ratio; Surface waves; Adult; Biomechanics; Calibration; Elbow; Electromyography; Female; Fourier Analysis; Humans; Isometric Contraction; Male; Models, Biological; Models, Statistical; Reference Values; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.284927
  • Filename
    284927