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    Estimation of Heat Production Rate using Thermal Data During Exercise in Indoor Environments: A Study of Heat Storage Rate in Male Athletes
    (Springer, 2024) Balci, Gorkem Aybars; Avci, Ali Berkay; Colakoglu, Muzaffer; Basaran, Tahsin
    The increasing preference for indoor exercise spaces highlights the relationship between indoor thermal environments and physiological responses, particularly concerning thermal comfort during physical activity. Determining the metabolic heat production rate during exercise is essential for optimizing the thermal comfort, well-being, and performance of individuals engaged in physical activities. This value can be determined during the activity using several methods, including direct calorimetry measurement, indirect calorimetry that uses analysis of respiratory gases, or approximations using collected data such as speed, body mass, and heart rate. The study aimed to calculate the metabolic heat production rate by infrared thermal evaluation (ITE) based on the body's thermal balance approach and compare it with the values determined by indirect calorimetry (IC). Fourteen participants volunteered for the study, using a cycling ergometer in a controlled climatic chamber. After the familiarization sessions, maximal O-2 intake levels (VO2max) were determined through maximal graded exercise tests. Subsequently, constant work rate exercise tests were performed at 60% of VO2max for 20 min. The metabolic heat production rates were calculated by IC and ITE for each athlete individually. Respiratory gases were used to determine IC, while body skin and core temperatures, along with physical environmental data, were applied to calculate ITE using the human body thermal balance approximation of ASHRAE. According to the results, heat storage rates were misleading among the body's heat transfer modes, particularly during the first 8 min of the exercise. ITE showed a moderate level of correlation with IC (r: 0.03-0.86) with a higher level of dispersion relative to the mean (CV%: 12-84%). Therefore, a new equation (ITEnew) for the heat storage rates was proposed using the experimental data from this study. The results showed that ITEnew provided more precise estimations for the entire exercise period (p > 0.05). Correlations between ITEnew and IC values were consistently strong throughout the exercise period (r: 0.62-0.85). It can be suggested that ITEnew values can predict IC during the constant work rate steady-state exercise.
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    Exercise and resting periods: Thermal comfort dynamics in gym environments
    (Tsinghua Univ Press, 2024) Avci, Ali Berkay; Balci, Goerkem Aybars; Basaran, Tahsin
    Physical exercise spaces emerged as popular facilities due to recognizing the significance of physical well-being. This study investigates the relationship among physiological responses, human body energy transfer modes, and indoor environmental conditions in influencing thermal comfort perception within indoor physical exercise space. Seven male participants engaged in a 30 min constant-work-rate cycling exercise and a 20 min resting period in a climatic chamber. The physiological and environmental responses were recorded during the experiments, and the body's energy transfer modes were calculated using the collected data. The dataset was prepared using the 2 min averages of the collected data and calculated parameters across the experiment phases, including the features of skin temperature, core temperature, skin relative humidity, heart rate, oxygen consumption, body's heat transfer rates through convection, radiation, evaporation, and respiration, net metabolic heat production rate (metabolic rate minus external work rate), indoor air temperature, indoor relative humidity, air velocity, and radiant temperature. Gradient boosting regressor (GBR) was selected as the analyzing method to estimate predicted mean vote (PMV) and thermal sensation vote (TSV) indices during exercise and resting periods using features determined in the study. Thus, the four GBR models were defined as PMV-Exercise, PMV-Resting, TSV-Exercise, and TSV-Resting. In order to optimize the models' performances, the hyperparameter tuning process was executed using the GridSearchCV method. A permutation feature importance analysis was performed, emphasizing the significance of net metabolic heat production rate (24.2%), radiant temperature (17.0%), and evaporative heat transfer rate (13.1%). According to the results, PMV-Exercise, PMV-Resting, and TSV-Resting GBR models performed better, while TSV-Exercise faced challenges in predicting exercise thermal sensations. Critically, this study addresses the need to understanding the interrelationship among physiological responses, environmental conditions, and human body energy transfer modes during both exercise and resting periods to optimize thermal comfort within indoor exercise spaces. The results of this study contribute to the operation of indoor gym environments to refine their indoor environmental parameters to optimize users' thermal comfort and well-being. The study is limited to a small sample size consisting solely of male participants, which may restrict the generalizability of the findings. Future research could explore personalized thermal comfort control systems and synergies between comfort optimization and energy efficiency in indoor exercise spaces.