Skip to main content
Log in

The effects of motor unit synchronization on the power spectrum of the electromyogram

  • Published:
Biological Cybernetics Aims and scope Submit manuscript

Abstract

A realistic model for two synchronized motor unit action potential trains (MUAPT) is presented in which the variability of the time difference between corresponding action potentials (hereafter denoted by delay) is taken into account. Specifically, this delay is modeled as a continuous random variable that may assume both positive and negative values.

Expressions are derived for the auto- and cross-power spectra of two such trains using their relations with the auto- and cross-correlation functions, respectively, with which they form Fourier transform pairs.

The results show that the auto- and the cross-power spectra of two such synchronized MUAPTs differ from the auto- and the cross-spectra of two independent MUAPTs. The contribution of the statistics of the interpulse intervals to one of the autopower spectra is smaller and the cross-power spectra no longer reduce to a Dirac δ-function at the origin but are now determined by the other auto-power spectrum and by the Fourier transform of the density function associated with the time difference between corresponding action potentials. As a consequence of this change in the cross-power spectra synchronization leads to an absolute increase of power at low frequencies and to a relative decrease of power at high frequencies.

The results are then generalized to electromyograms (EMG) composed of more than just two MUAPTs and illustrated with simulated power spectra with which the theory shows excellent agreement.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Agarwal, G.C., Gottlieb, G.L.: An analysis of the electromyogram by Fourier, simulation and experimental techniques. IEEE Trans. BME-22, 225–229 (1975)

    Google Scholar 

  • Bigland-Ritchie, B., Donovan, E.F., Roussos, C.S.: Conduction velocity and EMG power spectrum changes in fatigue of sustained maximal efforts. J. Appl. Physiol.: Respirat. Environ. Exercise Physiol. 51, 1300–1305 (1981)

    Google Scholar 

  • Birö, G., Partridge, L.D.: Analysis of multiunit spike records. J. Appl. Physiol. 30, 521–526 (1971)

    Google Scholar 

  • Blinowska, A., Verroust, J., Cannet, G.: The determination of motor units characteristics from the low frequency electromyographic power spectra. Electromyogr. Clin. Neurophysiol. 19, 281–290 (1979)

    Google Scholar 

  • Blinowska, A., Verroust, J., Cannet, G.: An analysis of synchronisation and double discharge effects on low frequency electromyographic power spectra. Electromyogr. Clin. Neurophysiol. 20, 465–480 (1980)

    Google Scholar 

  • Buchthal, F., Madsen, A.: Synchronous activity in normal and atrophic muscle. Electroencephalogr. Clin. Neurophysiol. 2, 425–444 (1950)

    Google Scholar 

  • Christakos, C.N.: A linear stochastic model of the single motor unit. Biol. Cybern. 44, 79–89 (1982)

    Google Scholar 

  • Christakos, C.N., Lal, S.: Lumped and population stochastic models of skeletal muscle: implications and predictions. Biol. Cybern. 36, 73–85 (1980)

    Google Scholar 

  • Coggshall, J.C.: Linear models for biological transducers and impulse train spectra: general formulation and review. Kybernetik 13, 30–37 (1973)

    Google Scholar 

  • Coggshall, J.C., Bekey, G.A.: A stochastic model of skeletal muscle based on motor unit properties. Math. Biosci. 7, 405–419 (1970)

    Google Scholar 

  • De Luca, C.J.: A model for a motor unit train recorded during constant force isometric contractions. Biol. Cybern. 19, 159–167 (1975)

    Google Scholar 

  • Dietz, V., Bischofberger, E., Wita, C., Freund, H.-J.: Correlation between the discharges of two simultaneous recorded motor units and physiological tremor. Electroencephalogr. Clin. Neurophysiol. 40, 97–105 (1976)

    Google Scholar 

  • Gel'fand, I.M., Gurfinkel, V.S., Kots, Ya.M., Tsetlin, M.L., Shik, M.L.: Synchronization of motor units and associated model concepts. Biophysics 8, 528–541 (1963)

    Google Scholar 

  • Kirkwood, P.A., Sears, T.A.: The synaptic connexions to intercostal motoneurones as revealed by the average common excitation potential. J. Physiol. 275, 103–134 (1978)

    Google Scholar 

  • Lago, P., Jones, N.B.: Effect of motor-unit firing time statistics on EMG spectra. Med. Biol. Eng. Comput. 15, 648–655 (1977)

    Google Scholar 

  • Lindström, L., Hellsing, G.: Masseter muscle fatigue in man objectively quantified by analysis of myoelectric signals. Arch. Oral Biol. 28, 297–301 (1983)

    Google Scholar 

  • Lindström, L., Magnusson, R., Petersén, I.: Muscular fatigue and action potential conduction velocity changes studied with frequency analysis of EMG signals. Electromyography 4, 341–356 (1970)

    Google Scholar 

  • Lippold, O.C.J., Redfearn, J.W.T., Vuco, J.: The rhythmical activity of groups of motor units in the voluntary contraction of muscle. J. Physiol. 137, 473–487 (1957)

    Google Scholar 

  • Lloyd, A.J.: Surface electromyography during sustained isometric contractions. J. Appl. Physiol. 30, 713–719 (1971)

    Google Scholar 

  • Milner-Brown, H.S., Stein, R.B., Yemm, R.: The contractile properties of human motor units during voluntary isometric contractions. J. Physiol. 228, 285–306 (1973)

    Google Scholar 

  • Mori, S.: Discharge patterns of soleus motor units with associated changes in force exerted by foot during quiet stance in man. J. Neurophysiol. 36, 458–471 (1973)

    Google Scholar 

  • Naejje, M., Zorn, H.: Relation between EMG power spectrum shifts and muscle fibre action potential conduction velocity changes during local muscular fatigue in man. Eur. J. Appl. Physiol. 50, 23–33 (1982)

    Google Scholar 

  • Oppenheim, A.V., Schafer, R.W.: Digital signal processing. Englewood Cliffs, NJ: Prentice-Hall 1975

    Google Scholar 

  • Papoulis, A.: Probability, random variables and stochastic processes. New York: McGraw-Hall 1965

    Google Scholar 

  • Perkel, D.H., Gerstein, G.L., Moore, G.P.: Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains. Biophys. J. 7, 419–440 (1967)

    Google Scholar 

  • Person, R.S., Kudina, L.P.: Cross-correlation of electromyograms showing interference patterns. Electroencephalogr. Clin. Neurophysiol. 25, 58–68 (1968)

    Google Scholar 

  • Sears, I.A., Stagg, D.: Short-term synchronisation of intercostal motoneurone activity. J. Physiol. 263, 357–381 (1976)

    Google Scholar 

  • van Boxtel, A., Goudswaard, P., van der Molen, G.M., van den Bosch, W.E.J.: Changes in electromyogram power spectra of facial and jaw-elevator muscles during fatigue. J. Appl. Physiol.: Respirat. Environ. Exercise Physiol. 54, 51–58 (1983)

    Google Scholar 

  • van Boxtel, A., Schomaker, L.R.B.: Motor unit firing rate during static contraction indicated by the surface EMG power spectrum. IEEE Trans. BME-30, 601–609 (1983)

    Google Scholar 

  • Verroust, J., Blinowska, A., Cannet, G.: Functionning of the ensemble of motor units of the muscle determined from global EMG signal. Electromyogr. Clin. Neurophysiol. 21, 11–24 (1981)

    Google Scholar 

  • Welch, P.D.: The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans. AU-15, 70–73 (1967)

    Google Scholar 

  • Weytjens, J.L.F., van Steenberghe, D.: Spectral analysis of the surface electromyogram as a tool for studying rate modulation: a comparison between theory, simulation and experiment. Biol. Cybern. 50, 95–103 (1984)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Weytjens, J.L.F., van Steenberghe, D. The effects of motor unit synchronization on the power spectrum of the electromyogram. Biol. Cybern. 51, 71–77 (1984). https://doi.org/10.1007/BF00357919

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00357919

Keywords

Navigation