1.Introduction Injury prevention is an essential element of science and medicine in sports,and it garners attention from stakeholders focused on minimizing athletes’injury risk.Catchy titles including“injury risk”o...1.Introduction Injury prevention is an essential element of science and medicine in sports,and it garners attention from stakeholders focused on minimizing athletes’injury risk.Catchy titles including“injury risk”or“injury prevention”are likely to grab the readers’attention.Meanwhile,studies on injury prevention might assess the impact of interventions on mitigating injury risk factors(e.g.,strength,range of motion(ROM))but fail to report injury data(e.g.,incidence).1,2 Likewise,observational studies may include“injury risk”in their titles,but fail to provide injury data.3 Without injury data.展开更多
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...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.展开更多
基金Centre of Research,Education,Innovation,and Intervention in Sport(CIFI2D)is financed by the Portuguese Foundation for Science and Technology,under the DOI https://doi.org/10.54499/UIDB/05913/2020。
文摘1.Introduction Injury prevention is an essential element of science and medicine in sports,and it garners attention from stakeholders focused on minimizing athletes’injury risk.Catchy titles including“injury risk”or“injury prevention”are likely to grab the readers’attention.Meanwhile,studies on injury prevention might assess the impact of interventions on mitigating injury risk factors(e.g.,strength,range of motion(ROM))but fail to report injury data(e.g.,incidence).1,2 Likewise,observational studies may include“injury risk”in their titles,but fail to provide injury data.3 Without injury data.
基金supported by the Scientific and Technological Research Council of Turkiye(TUBiTAK)Foundation under grant number122M883.
文摘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.
