Abstract/Summary

With increasing global warming, a method to identify individual heat exposure risk and conduct interventions is essential, in order to mitigate impacts of extreme climates on people's health. This paper aims to examine the differences of individual's physiological response in hot environments and consequently proposes a personal-based method to identify potentially vulnerable populations with high risk. A heat exposure experiment was carried out in a climate chamber to build datasets, with nine conditions combining air temperature (35 °C/38 °C/40 °C) and relative humidity (25%/40% /60%). The rectal temperature (Tre), skin temperature (Tsk) and heart rate (HR) of 10 subjects were monitored. Data were analyzed using multiple-dimensional metrics of average deviation(AD), coefficient of variation(CV) and skewness(SKEW). The study introduced the Moment of Inertia (MI) and the Simulated Mass System (MS) in a multidimensional coordinate system and developed a Comprehensive Deviation Coefficient (CDC) method. Using various combinations of AD/CV/SKEW, the values of CDCTre, CDCTsk, CDCHR were calculated; the high-risk thermal environment (40 °C/60%) and subject were thus identified. The proposed CDC method enables to distinguish the individual's physiological response differences, under different hot environments and personal characteristics. The equations in this method can be programed in computer and integrated with smart sensor technology, contributing to identify the high-risk environments and provide precautions for susceptible populations, to mitigate the heat exposure hazards on people’ health and safety.