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Facial feature tracking: a psychophysiological measure to assess exercise intensity?

Kathleen H MilesBradley ClarkJulien D PériardRoland GoeckeKevin G Thompson
Published in: Journal of sports sciences (2017)
The primary aim of this study was to determine whether facial feature tracking reliably measures changes in facial movement across varying exercise intensities. Fifteen cyclists completed three, incremental intensity, cycling trials to exhaustion while their faces were recorded with video cameras. Facial feature tracking was found to be a moderately reliable measure of facial movement during incremental intensity cycling (intra-class correlation coefficient = 0.65-0.68). Facial movement (whole face (WF), upper face (UF), lower face (LF) and head movement (HM)) increased with exercise intensity, from lactate threshold one (LT1) until attainment of maximal aerobic power (MAP) (WF 3464 ± 3364mm, P < 0.005; UF 1961 ± 1779mm, P = 0.002; LF 1608 ± 1404mm, P = 0.002; HM 849 ± 642mm, P < 0.001). UF movement was greater than LF movement at all exercise intensities (UF minus LF at: LT1, 1048 ± 383mm; LT2, 1208 ± 611mm; MAP, 1401 ± 712mm; P < 0.001). Significant medium to large non-linear relationships were found between facial movement and power output (r2 = 0.24-0.31), HR (r2 = 0.26-0.33), [La-] (r2 = 0.33-0.44) and RPE (r2 = 0.38-0.45). The findings demonstrate the potential utility of facial feature tracking as a non-invasive, psychophysiological measure to potentially assess exercise intensity.
Keyphrases
  • high intensity
  • resistance training
  • soft tissue
  • machine learning
  • physical activity
  • magnetic resonance imaging
  • blood pressure
  • climate change
  • risk assessment
  • high density
  • human health