Applications of real-time thermoregulatory models to occupational heat stress: validation with military and civilian field studies

Abstract

A real-time thermoregulatory model using noninvasive measurements as inputs was developed for predicting physiological responses of individuals working long hours. The purpose of the model is to reduce heat-related injuries and illness by predicting the physiological effects of thermal stress on individuals while working. The model was originally validated mainly by using data from controlled laboratory studies. This study expands the validation of the model with field data from 26 test volunteers, including US Marines, Australian soldiers, and US wildland fire fighters (WLFF). These data encompass a range of environmental conditions (air temperature: 19-30° C; relative humidity: 25-63%) and clothing (i.e., battle dress uniform, chemical-biological protective garment, WLFF protective gear), while performing diverse activities (e.g., marksmanship, marching, extinguishing fires, and digging). The predicted core temperatures (Tc), calculated using environmental, anthropometric, clothing, and heart rate measures collected in the field as model inputs, were compared with subjects' Tc collected with ingested telemetry temperature pills. Root mean standard deviation (RMSD) values, used for goodness of fit comparisons, indicated that overall, the model predictions were in close agreement with the measured values (grand mean of RMSD: 0.15-0.38° C). Although the field data showed more individual variability in the physiological data relative to more controlled laboratory studies, this study showed that the performance of the model was adequate.