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Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue?
Injuries caused by the overstraining of muscles could be prevented by means of a system which detects muscle fatigue. Most of the equipment used to detect this is usually expensive. The question then arises whether it is possible to use a low-cost surface electromyography (sEMG) system that is able...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679263/ https://www.ncbi.nlm.nih.gov/pubmed/31330807 http://dx.doi.org/10.3390/s19143204 |
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author | del Toro, Sergio Fuentes Santos-Cuadros, Silvia Olmeda, Ester Álvarez-Caldas, Carolina Díaz, Vicente San Román, José Luís |
author_facet | del Toro, Sergio Fuentes Santos-Cuadros, Silvia Olmeda, Ester Álvarez-Caldas, Carolina Díaz, Vicente San Román, José Luís |
author_sort | del Toro, Sergio Fuentes |
collection | PubMed |
description | Injuries caused by the overstraining of muscles could be prevented by means of a system which detects muscle fatigue. Most of the equipment used to detect this is usually expensive. The question then arises whether it is possible to use a low-cost surface electromyography (sEMG) system that is able to reliably detect muscle fatigue. With this main goal, the contribution of this work is the design of a low-cost sEMG system that allows assessing when fatigue appears in a muscle. To that aim, low-cost sEMG sensors, an Arduino board and a PC were used and afterwards their validity was checked by means of an experiment with 28 volunteers. This experiment collected information from volunteers, such as their level of physical activity, and invited them to perform an isometric contraction while an sEMG signal of their quadriceps was recorded by the low-cost equipment. After a wavelet filtering of the signal, root mean square (RMS), mean absolute value (MAV) and mean frequency (MNF) were chosen as representative features to evaluate fatigue. Results show how the behaviour of these parameters across time is shown in the literature coincides with past studies (RMS and MAV increase while MNF decreases when fatigue appears). Thus, this work proves the feasibility of a low-cost system to reliably detect muscle fatigue. This system could be implemented in several fields, such as sport, ergonomics, rehabilitation or human-computer interactions. |
format | Online Article Text |
id | pubmed-6679263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-66792632019-08-19 Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue? del Toro, Sergio Fuentes Santos-Cuadros, Silvia Olmeda, Ester Álvarez-Caldas, Carolina Díaz, Vicente San Román, José Luís Sensors (Basel) Article Injuries caused by the overstraining of muscles could be prevented by means of a system which detects muscle fatigue. Most of the equipment used to detect this is usually expensive. The question then arises whether it is possible to use a low-cost surface electromyography (sEMG) system that is able to reliably detect muscle fatigue. With this main goal, the contribution of this work is the design of a low-cost sEMG system that allows assessing when fatigue appears in a muscle. To that aim, low-cost sEMG sensors, an Arduino board and a PC were used and afterwards their validity was checked by means of an experiment with 28 volunteers. This experiment collected information from volunteers, such as their level of physical activity, and invited them to perform an isometric contraction while an sEMG signal of their quadriceps was recorded by the low-cost equipment. After a wavelet filtering of the signal, root mean square (RMS), mean absolute value (MAV) and mean frequency (MNF) were chosen as representative features to evaluate fatigue. Results show how the behaviour of these parameters across time is shown in the literature coincides with past studies (RMS and MAV increase while MNF decreases when fatigue appears). Thus, this work proves the feasibility of a low-cost system to reliably detect muscle fatigue. This system could be implemented in several fields, such as sport, ergonomics, rehabilitation or human-computer interactions. MDPI 2019-07-20 /pmc/articles/PMC6679263/ /pubmed/31330807 http://dx.doi.org/10.3390/s19143204 Text en © 2019 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 (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article del Toro, Sergio Fuentes Santos-Cuadros, Silvia Olmeda, Ester Álvarez-Caldas, Carolina Díaz, Vicente San Román, José Luís Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue? |
title | Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue? |
title_full | Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue? |
title_fullStr | Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue? |
title_full_unstemmed | Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue? |
title_short | Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue? |
title_sort | is the use of a low-cost semg sensor valid to measure muscle fatigue? |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679263/ https://www.ncbi.nlm.nih.gov/pubmed/31330807 http://dx.doi.org/10.3390/s19143204 |
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