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Exercise Thermal Sensation: Physiological Response to Dynamic-Static Steps at Moderate Exercise.

Qinghao Xu1,2, Lin Chen3, Hao Chen1

  • 1School of Electric Power, Civil Engineering and Architecture, University of Shanxi, Taiyuan 030000, China.

International Journal of Environmental Research and Public Health
|April 30, 2021
PubMed
Summary

Understanding exercise thermal sensation is complex. This study found that physiological indicators like skin temperature and electrodermal activity, especially their changes over time, are key for accurate exercise thermal sensation models.

Keywords:
dynamic–static stepsexercise thermal sensationphysiological parameterregression modelthermal alliesthesia

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Area of Science:

  • Exercise Physiology
  • Human Thermal Sensation
  • Environmental Health

Background:

  • Assessing thermal sensation during exercise is challenging compared to static conditions.
  • Understanding physiological responses to dynamic thermal environments is crucial for human comfort and performance.

Purpose of the Study:

  • To investigate physiological and perceptual changes during exercise, focusing on dynamic-static transitions.
  • To evaluate exercise thermal sensation by analyzing various physiological parameters.
  • To develop improved models for predicting exercise thermal sensation.

Main Methods:

  • 16 participants engaged in treadmill exercises at 4.5 km/h and 6 km/h within a climate chamber.
  • A static-dynamic-static protocol was employed.
  • Measurements included skin temperature (Tsk), oral temperature (Tor), heart rate (HR), heart rate variability (HRV), and electrodermal activity (EDA), alongside subjective thermal ratings.

Main Results:

  • Physiological indicators exhibited complex changes around dynamic-static transitions.
  • Skin temperature (Tsk), oral temperature (Tor), and electrodermal activity (EDA) were identified as valid parameters for exercise thermal sensation models.
  • Prediction models incorporating the average and rate of change in measurements outperformed models using original measurements.

Conclusions:

  • Exercise thermal sensation prediction models should account for dynamic-static states.
  • The rate of change in physiological parameters is more indicative of thermal sensation than absolute values.
  • Psychological factors play a significant role and must be integrated into thermal sensation models.