Literature DB >> 16963280

Simulation analysis of interference EMG during fatiguing voluntary contractions. Part II--changes in amplitude and spectral characteristics.

G V Dimitrov1, T I Arabadzhiev, J-Y Hogrel, N A Dimitrova.   

Abstract

Capabilities of amplitude and spectral methods for information extraction from interference EMG signals were assessed through simulation and preliminary experiment. Muscle was composed of 4 types of motor units (MUs). Different hypotheses on changes in firing frequency of individual MUs, intracellular action potential (IAP) and muscle fibre propagation velocity (MFPV) during fatigue were analyzed. It was found that changes in amplitude characteristics of interference signals (root mean square, RMS, or integrated rectified value, IEMG) detected by intramuscular and surface electrodes differed. RMS and IEMG of surface detected interference signals could increase even under MU firing rate reduction and without MU synchronisation. IAP profile lengthening can affect amplitude characteristics more significantly than MU firing frequency. Thus, an increase of interference EMG amplitude is unreliable to reflect changes in the neural drive. The ratio between EMG amplitude and contraction response can hardly characterise the so-called 'neuromuscular efficiency'. The recently proposed spectral fatigue indices can be used for quantification of interference EMG signals. The indices are practically insensitive to MU firing frequency. IAP profile lengthening and decrease in MFPV enhanced the index value, while recruitment of fast fatigable MUs reduced it. Sensitivity of the indices was higher than that of indices traditionally used.

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Year:  2006        PMID: 16963280     DOI: 10.1016/j.jelekin.2006.07.002

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  9 in total

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3.  Comparative evaluation of motor unit architecture models.

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4.  Influence of motor unit synchronization on amplitude characteristics of surface and intramuscularly recorded EMG signals.

Authors:  Todor I Arabadzhiev; Vladimir G Dimitrov; Nonna A Dimitrova; George V Dimitrov
Journal:  Eur J Appl Physiol       Date:  2009-09-22       Impact factor: 3.078

Review 5.  The extraction of neural strategies from the surface EMG: an update.

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Journal:  J Appl Physiol (1985)       Date:  2014-10-02

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Authors:  Kang-Ming Chang; Shin-Hong Liu; Xuan-Han Wu
Journal:  Sensors (Basel)       Date:  2012-01-05       Impact factor: 3.576

8.  Core and skin temperature influences on the surface electromyographic responses to an isometric force and position task.

Authors:  Nico A Coletta; Matthew M Mallette; David A Gabriel; Christopher J Tyler; Stephen S Cheung
Journal:  PLoS One       Date:  2018-03-29       Impact factor: 3.240

9.  Spatiotemporal characteristics of lower back muscle fatigue during a ten minutes endurance test at 50% upper body weight in healthy inactive, endurance, and strength trained subjects.

Authors:  Christoph Anders; Tim Schönau
Journal:  PLoS One       Date:  2022-09-13       Impact factor: 3.752

  9 in total

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