| Research has indicated that the human body can adapt to,rather than reluctantly accept,hot environments.This physiological adaptation,known as heat acclimation(HA),can be artificially induced through periodic physical heat training.In this study,a series of heat exposure experiments were carried out in a heat chamber to acclimate participants to heat,including a 15-day HA training regimen,an 8-day regimen,a 7-day regimen,and a 3-day regimen.The sample size was 203,and the participants were instructed to do treadmill exercise.Different regimens had different control variables including air temperature,relative humidity,clothing insulation,exercise intensity,and exercise duration.During exercise,their physiological parameters,subjective perception,work efficiency,and safety performance were measured.In addition,field investigations were also conducted,involving 5 typical hyperthermal workplaces in which the environmental variables and workers' physiological parameters were measured during working time.The results show that HA could lower the physiological peak during heat exposure.Furthermore,the magnitude and time course of HA were determined.In addition,HA could reduce the thermal sensation votes and ratings of perceived exertion,and meanwhile,improve their work efficiency and safety performance.The heat acclimation index(HAI)based on physiological parameters was developed to categorize the magnitude into four levels.And machine learning prediction models were then built for the effectiveness of HA training.Consequently,the importance order of contributors was: exercise intensity > the numbers of exposure >air temperature > duration > clothing insulation > relative humidity.Finally,the results of field investigations show a discrepancy between heat exposure limits and actual conditions.Thus the effect of HA was then incorporated into the current evaluation standard for the heat stress in workplaces,and its accuracy was improved.In addition,the sample diversity was expanded. |
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