Literature DB >> 2779292

Motor unit power spectrum and firing rate.

Z S Pan, Y Zhang, P A Parker.   

Abstract

Changes in the power density spectrum of myoelectric signal with contraction level have been reported in the literature. These changes can be induced by a number of possible factors including recruitment of differing types of units, conduction velocity changes and firing rate changes. In the paper the single unit power spectrum is investigated and the effects of firing rate mean and variance changes evaluated. Motor unit signal simulation and experiments are carried out to verify predictions. The results show that spectrum peaks will shift with firing rate and the median frequency is weakly dependent on firing rate.

Mesh:

Year:  1989        PMID: 2779292     DOI: 10.1007/BF02442164

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  4 in total

1.  Effect of motor-unit firing time statistics on e.m.g. spectra.

Authors:  P Lago; N B Jones
Journal:  Med Biol Eng Comput       Date:  1977-11       Impact factor: 2.602

2.  Physiology and mathematics of myoelectric signals.

Authors:  C J De Luca
Journal:  IEEE Trans Biomed Eng       Date:  1979-06       Impact factor: 4.538

3.  A model for myoelectric signal generation.

Authors:  G Brody; R N Scott; R Balasubramanian
Journal:  Med Biol Eng       Date:  1974-01

4.  Statistical analysis of motor unit firing patterns in a human skeletal muscle.

Authors:  H P Clamann
Journal:  Biophys J       Date:  1969-10       Impact factor: 4.033

  4 in total
  9 in total

Review 1.  Surface electromyogram signal modelling.

Authors:  K C McGill
Journal:  Med Biol Eng Comput       Date:  2004-07       Impact factor: 2.602

2.  Use of surface potential spectral characteristics for solving the inverse problem in electroneurography.

Authors:  G V Dimitrov; Z C Lateva; N A Dimitrova
Journal:  Med Biol Eng Comput       Date:  1992-07       Impact factor: 2.602

3.  Motor unit recruitment strategies and muscle properties determine the influence of synaptic noise on force steadiness.

Authors:  Jakob L Dideriksen; Francesco Negro; Roger M Enoka; Dario Farina
Journal:  J Neurophysiol       Date:  2012-03-14       Impact factor: 2.714

4.  Comparison of the power spectral changes of the voluntary surface electromyogram and M wave during intermittent maximal voluntary contractions.

Authors:  Javier Rodriguez-Falces; Mikel Izquierdo; Miriam González-Izal; Nicolas Place
Journal:  Eur J Appl Physiol       Date:  2014-06-11       Impact factor: 3.078

5.  Characterization of abdominally acquired uterine electrical signals in humans, using a non-linear analytic method.

Authors:  William L Maner; Lynette B MacKay; George R Saade; Robert E Garfield
Journal:  Med Biol Eng Comput       Date:  2006-03       Impact factor: 2.602

6.  Myo-electric fatigue manifestations revisited: power spectrum, conduction velocity, and amplitude of human elbow flexor muscles during isolated and repetitive endurance contractions at 30% maximal voluntary contraction.

Authors:  C Krogh-Lund; K Jørgensen
Journal:  Eur J Appl Physiol Occup Physiol       Date:  1993

7.  Comparison of different estimators of electromyographic spectral shifts during work when applied on short test contractions.

Authors:  G M Hägg
Journal:  Med Biol Eng Comput       Date:  1991-09       Impact factor: 2.602

8.  Motor Unit Action Potential Clustering-Theoretical Consideration for Muscle Activation during a Motor Task.

Authors:  Michael J Asmussen; Vinzenz von Tscharner; Benno M Nigg
Journal:  Front Hum Neurosci       Date:  2018-01-31       Impact factor: 3.169

9.  A wavelet based time frequency analysis of electromyograms to group steps of runners into clusters that contain similar muscle activation patterns.

Authors:  Vinzenz von Tscharner; Martin Ullrich; Maurice Mohr; Daniel Comaduran Marquez; Benno M Nigg
Journal:  PLoS One       Date:  2018-04-18       Impact factor: 3.240

  9 in total

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