Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review
The surface electromyography (sEMG) records the electrical activity of muscle fibers during contraction: one of its uses is to assess changes taking place within muscles in the course of a fatiguing contraction to provide insights into our understanding of muscle fatigue in training protocols and re...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-05-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/22/5/529 |
id |
doaj-c416e21e89e540aabf97ccfdbc8020a1 |
---|---|
record_format |
Article |
spelling |
doaj-c416e21e89e540aabf97ccfdbc8020a12020-11-25T02:08:02ZengMDPI AGEntropy1099-43002020-05-012252952910.3390/e22050529Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A ReviewSusanna Rampichini0Taian Martins Vieira1Paolo Castiglioni2Giampiero Merati3Department of Biomedical Sciences for Health, Università degli Studi di Milano, 20133 Milan, ItalyLaboratorio di Ingegneria del Sistema Neuromuscolare (LISiN), Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, 10129 Turin, ItalyIRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, ItalyDepartment of Biomedical Sciences for Health, Università degli Studi di Milano, 20133 Milan, ItalyThe surface electromyography (sEMG) records the electrical activity of muscle fibers during contraction: one of its uses is to assess changes taking place within muscles in the course of a fatiguing contraction to provide insights into our understanding of muscle fatigue in training protocols and rehabilitation medicine. Until recently, these myoelectric manifestations of muscle fatigue (MMF) have been assessed essentially by linear sEMG analyses. However, sEMG shows a complex behavior, due to many concurrent factors. Therefore, in the last years, complexity-based methods have been tentatively applied to the sEMG signal to better individuate the MMF onset during sustained contractions. In this review, after describing concisely the traditional linear methods employed to assess MMF we present the complexity methods used for sEMG analysis based on an extensive literature search. We show that some of these indices, like those derived from recurrence plots, from entropy or fractal analysis, can detect MMF efficiently. However, we also show that more work remains to be done to compare the complexity indices in terms of reliability and sensibility; to optimize the choice of embedding dimension, time delay and threshold distance in reconstructing the phase space; and to elucidate the relationship between complexity estimators and the physiologic phenomena underlying the onset of MMF in exercising muscles.https://www.mdpi.com/1099-4300/22/5/529sEMGapproximate entropysample entropyfuzzy entropyfractal dimensionrecurrence quantification analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Susanna Rampichini Taian Martins Vieira Paolo Castiglioni Giampiero Merati |
spellingShingle |
Susanna Rampichini Taian Martins Vieira Paolo Castiglioni Giampiero Merati Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review Entropy sEMG approximate entropy sample entropy fuzzy entropy fractal dimension recurrence quantification analysis |
author_facet |
Susanna Rampichini Taian Martins Vieira Paolo Castiglioni Giampiero Merati |
author_sort |
Susanna Rampichini |
title |
Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review |
title_short |
Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review |
title_full |
Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review |
title_fullStr |
Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review |
title_full_unstemmed |
Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review |
title_sort |
complexity analysis of surface electromyography for assessing the myoelectric manifestation of muscle fatigue: a review |
publisher |
MDPI AG |
series |
Entropy |
issn |
1099-4300 |
publishDate |
2020-05-01 |
description |
The surface electromyography (sEMG) records the electrical activity of muscle fibers during contraction: one of its uses is to assess changes taking place within muscles in the course of a fatiguing contraction to provide insights into our understanding of muscle fatigue in training protocols and rehabilitation medicine. Until recently, these myoelectric manifestations of muscle fatigue (MMF) have been assessed essentially by linear sEMG analyses. However, sEMG shows a complex behavior, due to many concurrent factors. Therefore, in the last years, complexity-based methods have been tentatively applied to the sEMG signal to better individuate the MMF onset during sustained contractions. In this review, after describing concisely the traditional linear methods employed to assess MMF we present the complexity methods used for sEMG analysis based on an extensive literature search. We show that some of these indices, like those derived from recurrence plots, from entropy or fractal analysis, can detect MMF efficiently. However, we also show that more work remains to be done to compare the complexity indices in terms of reliability and sensibility; to optimize the choice of embedding dimension, time delay and threshold distance in reconstructing the phase space; and to elucidate the relationship between complexity estimators and the physiologic phenomena underlying the onset of MMF in exercising muscles. |
topic |
sEMG approximate entropy sample entropy fuzzy entropy fractal dimension recurrence quantification analysis |
url |
https://www.mdpi.com/1099-4300/22/5/529 |
work_keys_str_mv |
AT susannarampichini complexityanalysisofsurfaceelectromyographyforassessingthemyoelectricmanifestationofmusclefatigueareview AT taianmartinsvieira complexityanalysisofsurfaceelectromyographyforassessingthemyoelectricmanifestationofmusclefatigueareview AT paolocastiglioni complexityanalysisofsurfaceelectromyographyforassessingthemyoelectricmanifestationofmusclefatigueareview AT giampieromerati complexityanalysisofsurfaceelectromyographyforassessingthemyoelectricmanifestationofmusclefatigueareview |
_version_ |
1724928034515976192 |