Spectral compression of the electromyographic signal due to decreasing muscle fiber conduction velocity

IEEE Trans Rehabil Eng. 2000 Sep;8(3):353-61. doi: 10.1109/86.867877.

Abstract

Spectral compression of the electromyographic (EMG) signal, due largely to decreasing muscle fiber conduction velocity, is commonly used as an indication of muscle fatigue. Current methods of estimating conduction velocity using characteristic frequencies such as the median frequency of the power spectrum, are based on an assumption of uniform spectral compression. To examine changes in the EMG frequency spectrum during fatigue, muscle fiber conduction velocity was measured during sustained, isometric contractions of the biceps brachii. Compression of the EMG power and amplitude spectra was simultaneously examined using the median frequency and an alternative method-the spectral distribution technique. The spectral distribution technique consistently gave a better estimate of the relative change in muscle fiber conduction velocity than either of the median frequencies. This was further examined using a physiologically based EMG simulation model, which confirmed these findings. The model indicated that firing statistics can significantly influence spectral compression, particularly the behavior of characteristic frequencies in the vicinity of the firing rates. The relative change in the median frequency, whether of the amplitude or frequency spectrum, was consistently greater than the relative change in conduction velocity. The most accurate indication of the relative change in conduction velocity was obtained by calculating the mean shift in the midfrequency region of the EMG amplitude spectrum using the spectral distribution technique.

Publication types

  • Validation Study

MeSH terms

  • Action Potentials
  • Adult
  • Analysis of Variance
  • Bias
  • Computer Simulation*
  • Confounding Factors, Epidemiologic
  • Electromyography / methods*
  • Female
  • Humans
  • Isometric Contraction / physiology*
  • Male
  • Models, Neurological*
  • Muscle Fatigue / physiology*
  • Muscle, Skeletal / physiology*
  • Myofibrils / physiology*
  • Neural Conduction / physiology*
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted*