Identification of muscle fatigue by tracking facial expressions

PLoS One. 2018 Dec 18;13(12):e0208834. doi: 10.1371/journal.pone.0208834. eCollection 2018.

Abstract

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.

Publication types

  • Clinical Trial

MeSH terms

  • Electromyography
  • Facial Expression*
  • Facial Muscles / physiology*
  • Humans
  • Male
  • Middle Aged
  • Muscle Fatigue / physiology*

Grants and funding

The authors received no specific funding for this work.