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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
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.
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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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