Algorithms for T c measurement are location-specific and their accuracy is dependent, to a large degree, on sensor placement.

Differences in WBGT index along 23 km of the Boston Marathon race route can be small enough to warrant single measurements. However, significant misclassification of flag categories occurred using WBGT estimates for meteorological stations; thus, local measurements are preferred. If the relation between station WBGT forecasts and the race sites can be established, the forecast WBGT values could be corrected to give advanced warning of approximate flag conditions. Similar work is proposed for other venues to improve heat stress monitoring.

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.

Background:Thermal safety standards for the use of chemical, biological, radiological, and nuclear (CBRN) ensembles have been established for various US occupations, but not for law enforcement personnel.Objectives:We examined thermal strain levels of 30 male US law enforcement personnel who participated in CBRN field training in Arizona, Florida, and Massachusetts.Methods:Physiological responses were examined using unobtrusive heart rate (HR) monitors and a simple thermoregulatory model to predict core temperature (Tc) using HR and environment.Results:Thermal strain levels varied by environments, activity levels, and type of CBRN ensemble. Arizona and Florida volunteers working in hot-dry and hot-humid environment indicated high heat strain (predicted max Tc>38.5°C). The cool environment of Massachusetts reduced thermal strain although thermal strains were occasionally moderate.Conclusions:The non-invasive method of using physiological monitoring and thermoregulatory modeling could improve law enforcement mission to reduce the risk of heat illness or injury.