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

Qinghao Xu, Lin Chen, Hao Chen and Bart Julien Dewancker
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Qinghao Xu: School of Electric Power, Civil Engineering and Architecture, University of Shanxi, Taiyuan 030000, China
Lin Chen: School of Mathematical Sciences, University of Shanxi, Taiyuan 030000, China
Hao Chen: School of Electric Power, Civil Engineering and Architecture, University of Shanxi, Taiyuan 030000, China
Bart Julien Dewancker: Graduate School of Environmental Engineering, The University of Kitakyushu, Kitakyushu 8080135, Japan

IJERPH, 2021, vol. 18, issue 8, 1-24

Abstract: The study of exercise thermal sensation is more difficult than that of static thermal sensation in the human body. This work’s main purpose was to examine specific changes in human physiological parameters and subjective perceptions during the exercise process, especially around dynamic–static steps, and to assess exercise thermal sensation. Experiments were conducted in a climate chamber. A total of 16 subjects participated in two activities of different intensities on a treadmill, namely at 4.5 km/h and 6 km/h. The experimental procedure was set to static–dynamic–static. Skin temperature (T sk ), oral temperature (T or ), heart rate (HR), heart rate variability (HRV) parameters, and electrodermal activity (EDA) were measured at fixed time points, and thermal sensation values, thermal comfort values, and sweat feeling index were collected. The results showed complex changes in physiological indicators around the dynamic–static steps. Some important physio-logical indicators can be used as valid parameters for exercise thermal sensation models, such as T sk , T or , and EDA. This study highlighted that prediction models using average change and rate of change of measurements were better than using the original measurements. Our findings suggest that the exercise thermal sensation prediction models should be constructed according to the dynamic–static state and that psychological factors cannot be ignored.

Keywords: dynamic–static steps; exercise thermal sensation; physiological parameter; regression model; thermal alliesthesia (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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