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Identification of muscle fatigue by tracking facial expressions
Resistance training (RT) is performed at distinct levels of intensity from the beginning to the end of exercise sets, increasing the sensation of effort as the exercise progress to more vigorous levels, commonly leading to changes on the facial expression of RT practitioners. The objective of this s...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298643/ https://www.ncbi.nlm.nih.gov/pubmed/30562370 http://dx.doi.org/10.1371/journal.pone.0208834 |
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author | Uchida, Marco C. Carvalho, Renato Tessutti, Vitor Daniel Bacurau, Reury Frank Pereira Coelho-Júnior, Hélio José Capelo, Luciane Portas Ramos, Heloiza Prando dos Santos, Marcia Calixto Teixeira, Luís Felipe Milano Marchetti, Paulo Henrique |
author_facet | Uchida, Marco C. Carvalho, Renato Tessutti, Vitor Daniel Bacurau, Reury Frank Pereira Coelho-Júnior, Hélio José Capelo, Luciane Portas Ramos, Heloiza Prando dos Santos, Marcia Calixto Teixeira, Luís Felipe Milano Marchetti, Paulo Henrique |
author_sort | Uchida, Marco C. |
collection | PubMed |
description | Resistance training (RT) is performed at distinct levels of intensity from the beginning to the end of exercise sets, increasing the sensation of effort as the exercise progress to more vigorous levels, commonly leading to changes on the facial expression of RT practitioners. The objective of this study is to evaluate changes in facial expressions using the Facial Action Coding System(FACS) and the activation of facial muscles by surface electromyography(sEMG) at two different levels of effort during resistance exercise and to investigate the correlation between facial expression and exercise intensity and fatigue. Eleven healthy male participants [23±6years; 1.77±6 m; 78±10kg] performed a set of arm curl exercise at 50% and 85% 1RM until muscle fatigue. The Surface electromyography (sEMG activity was recorded simultaneously in areas of the epicranius muscle (EM) and zygomatic major muscle (ZM). Facial expression was recorded and blindly scored by five experienced examiners. Scores (0–5) were based on the level of activity of the ZM (lip corner puller—Action Unit 12-FACS) during exercise. Facial expression and sEMG data were obtained during the exercise at the first repetition and at muscle failure. The root mean square (RMS) of the sEMG amplitude of the EM was significantly increased between the first and last repetition (50%1RM:p = 0.002,d = 1.75; and 85%1RM:p = 0.002,d = 1.54). The RMS values for the ZM were significantly increased between the first and last repetition (50%1RM:p<0.001,d = 2.67; 85%1RM:p<0.001,d = 0.50). The RMS values for the ZM were also increased in 85%1RM compared to values obtained from 50%1RM (p = 0.001,d = 1.12) at the first repetition. AU12 scores and RMS values were not statistically different between 85%1RM and 50%1RM at the last repetition. Furthermore, there was a strong correlation (r = 0.61;p = 0.045) between AU12 scores and the sEMG peak for the ZM. In conclusion, changes in facial expression may be directly correlated with different resistance exercise intensities and fatigue. |
format | Online Article Text |
id | pubmed-6298643 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62986432018-12-28 Identification of muscle fatigue by tracking facial expressions Uchida, Marco C. Carvalho, Renato Tessutti, Vitor Daniel Bacurau, Reury Frank Pereira Coelho-Júnior, Hélio José Capelo, Luciane Portas Ramos, Heloiza Prando dos Santos, Marcia Calixto Teixeira, Luís Felipe Milano Marchetti, Paulo Henrique PLoS One Research Article Resistance training (RT) is performed at distinct levels of intensity from the beginning to the end of exercise sets, increasing the sensation of effort as the exercise progress to more vigorous levels, commonly leading to changes on the facial expression of RT practitioners. The objective of this study is to evaluate changes in facial expressions using the Facial Action Coding System(FACS) and the activation of facial muscles by surface electromyography(sEMG) at two different levels of effort during resistance exercise and to investigate the correlation between facial expression and exercise intensity and fatigue. Eleven healthy male participants [23±6years; 1.77±6 m; 78±10kg] performed a set of arm curl exercise at 50% and 85% 1RM until muscle fatigue. The Surface electromyography (sEMG activity was recorded simultaneously in areas of the epicranius muscle (EM) and zygomatic major muscle (ZM). Facial expression was recorded and blindly scored by five experienced examiners. Scores (0–5) were based on the level of activity of the ZM (lip corner puller—Action Unit 12-FACS) during exercise. Facial expression and sEMG data were obtained during the exercise at the first repetition and at muscle failure. The root mean square (RMS) of the sEMG amplitude of the EM was significantly increased between the first and last repetition (50%1RM:p = 0.002,d = 1.75; and 85%1RM:p = 0.002,d = 1.54). The RMS values for the ZM were significantly increased between the first and last repetition (50%1RM:p<0.001,d = 2.67; 85%1RM:p<0.001,d = 0.50). The RMS values for the ZM were also increased in 85%1RM compared to values obtained from 50%1RM (p = 0.001,d = 1.12) at the first repetition. AU12 scores and RMS values were not statistically different between 85%1RM and 50%1RM at the last repetition. Furthermore, there was a strong correlation (r = 0.61;p = 0.045) between AU12 scores and the sEMG peak for the ZM. In conclusion, changes in facial expression may be directly correlated with different resistance exercise intensities and fatigue. Public Library of Science 2018-12-18 /pmc/articles/PMC6298643/ /pubmed/30562370 http://dx.doi.org/10.1371/journal.pone.0208834 Text en © 2018 Uchida et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Uchida, Marco C. Carvalho, Renato Tessutti, Vitor Daniel Bacurau, Reury Frank Pereira Coelho-Júnior, Hélio José Capelo, Luciane Portas Ramos, Heloiza Prando dos Santos, Marcia Calixto Teixeira, Luís Felipe Milano Marchetti, Paulo Henrique Identification of muscle fatigue by tracking facial expressions |
title | Identification of muscle fatigue by tracking facial expressions |
title_full | Identification of muscle fatigue by tracking facial expressions |
title_fullStr | Identification of muscle fatigue by tracking facial expressions |
title_full_unstemmed | Identification of muscle fatigue by tracking facial expressions |
title_short | Identification of muscle fatigue by tracking facial expressions |
title_sort | identification of muscle fatigue by tracking facial expressions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298643/ https://www.ncbi.nlm.nih.gov/pubmed/30562370 http://dx.doi.org/10.1371/journal.pone.0208834 |
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