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A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue
Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, ele...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231314/ https://www.ncbi.nlm.nih.gov/pubmed/22163810 http://dx.doi.org/10.3390/s110403545 |
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author | Al-Mulla, Mohamed R. Sepulveda, Francisco Colley, Martin |
author_facet | Al-Mulla, Mohamed R. Sepulveda, Francisco Colley, Martin |
author_sort | Al-Mulla, Mohamed R. |
collection | PubMed |
description | Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, electromyography, near-infrared spectroscopy and ultrasound for both isometric and non-isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who wish to select the most appropriate methodology for research on muscle fatigue detection or prediction, or for the development of devices that can be used in, e.g., sports scenarios to improve performance or prevent injury. To date, research on localised muscle fatigue focuses mainly on the clinical side. There is very little research carried out on the implementation of detecting/predicting fatigue using an autonomous system, although recent research on automating the process of localised muscle fatigue detection/prediction shows promising results. |
format | Online Article Text |
id | pubmed-3231314 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-32313142011-12-07 A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue Al-Mulla, Mohamed R. Sepulveda, Francisco Colley, Martin Sensors (Basel) Review Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, electromyography, near-infrared spectroscopy and ultrasound for both isometric and non-isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who wish to select the most appropriate methodology for research on muscle fatigue detection or prediction, or for the development of devices that can be used in, e.g., sports scenarios to improve performance or prevent injury. To date, research on localised muscle fatigue focuses mainly on the clinical side. There is very little research carried out on the implementation of detecting/predicting fatigue using an autonomous system, although recent research on automating the process of localised muscle fatigue detection/prediction shows promising results. Molecular Diversity Preservation International (MDPI) 2011-03-24 /pmc/articles/PMC3231314/ /pubmed/22163810 http://dx.doi.org/10.3390/s110403545 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Review Al-Mulla, Mohamed R. Sepulveda, Francisco Colley, Martin A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue |
title | A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue |
title_full | A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue |
title_fullStr | A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue |
title_full_unstemmed | A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue |
title_short | A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue |
title_sort | review of non-invasive techniques to detect and predict localised muscle fatigue |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231314/ https://www.ncbi.nlm.nih.gov/pubmed/22163810 http://dx.doi.org/10.3390/s110403545 |
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