Literature DB >> 11738956

The short-time Fourier transform and muscle fatigue assessment in dynamic contractions.

D MacIsaac1, P A Parker, R N Scott.   

Abstract

The mean frequency of the power spectrum of an electromyographic signal is an accepted index for monitoring fatigue in static contractions. There is however, indication that it may be a useful index even in dynamic contractions in which muscle length and/or force may vary. The objective of this investigation was to explore this possibility. An examination of the effects of amplitude modulation on modeled electromyographic signals revealed that changes in variance created in this way do not sufficiently affect characteristic frequency data to obscure a trend with fatigue. This validated the contention that not all non-stationarities in signals necessarily manifest in power spectral parameters. While an investigation of the nature and effects of non-stationarities in real electromyographic signals produced from dynamic contractions indicated that a more complex model is warranted, the results also indicated that averaging associated with estimating spectral parameters with the short-time Fourier transform can control the effects of the more complex non-stationarities. Finally, a fatigue test involving dynamic contractions at a force level under 30% of peak voluntary dynamic range, validated that it was possible to track fatigue in dynamic contractions using a traditional short-time Fourier transform methodology.

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Year:  2001        PMID: 11738956     DOI: 10.1016/s1050-6411(01)00021-9

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


  10 in total

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2.  The effects of muscle fatigue and movement height on movement stability and variability.

Authors:  Deanna H Gates; Jonathan B Dingwell
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3.  Changes in muscle activity and kinematics of highly trained cyclists during fatigue.

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4.  The effects of neuromuscular fatigue on task performance during repetitive goal-directed movements.

Authors:  Deanna H Gates; Jonathan B Dingwell
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5.  Nonlinear smooth orthogonal decomposition of kinematic features of sawing reconstructs muscle fatigue evolution as indicated by electromyography.

Authors:  David B Segala; Deanna H Gates; Jonathan B Dingwell; David Chelidze
Journal:  J Biomech Eng       Date:  2011-03       Impact factor: 1.899

Review 6.  EMG Processing Based Measures of Fatigue Assessment during Manual Lifting.

Authors:  E F Shair; S A Ahmad; M H Marhaban; S B Mohd Tamrin; A R Abdullah
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7.  Fatigue Evaluation through Machine Learning and a Global Fatigue Descriptor.

Authors:  G Ramos; J R Vaz; G V Mendonça; P Pezarat-Correia; J Rodrigues; M Alfaras; H Gamboa
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8.  The Reliability of Pelvic Floor Muscle Bioelectrical Activity (sEMG) Assessment Using a Multi-Activity Measurement Protocol in Young Women.

Authors:  Łukasz Oleksy; Anna Mika; Iwona Sulowska-Daszyk; Ewelina Rosłoniec; Renata Kielnar; Artur Stolarczyk
Journal:  Int J Environ Res Public Health       Date:  2021-01-18       Impact factor: 3.390

9.  Slow-time changes in human EMG muscle fatigue states are fully represented in movement kinematics.

Authors:  Miao Song; David B Segala; Jonathan B Dingwell; David Chelidze
Journal:  J Biomech Eng       Date:  2009-02       Impact factor: 1.899

Review 10.  Causes of Performance Degradation in Non-invasive Electromyographic Pattern Recognition in Upper Limb Prostheses.

Authors:  Iris Kyranou; Sethu Vijayakumar; Mustafa Suphi Erden
Journal:  Front Neurorobot       Date:  2018-09-21       Impact factor: 2.650

  10 in total

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