A 3-D virtual human model for simulating heat and cold stress.

In this study, we extended our previously developed anatomically detailed three-dimensional (3-D) thermoregulatory virtual human model for predicting heat stress to allow for predictions of heat and cold stress in one unified model. Starting with the modified Pennes bioheat transfer equation to estimate the spatiotemporal temperature distribution within the body as the underlying modeling structure, we developed a new formulation to characterize the spatial variation of blood temperature between body elements and within the limbs. We also implemented the means to represent heat generated from shivering and skin blood flow that apply to air exposure and water immersion. Then, we performed simulations and validated the model predictions with experimental data from nine studies, representing a wide range of heat- and cold-stress conditions in air and water and physical activities. We observed excellent agreement between model predictions and measured data, with average root mean squared errors of 0.2°C for core temperature, 0.9°C for mean skin temperature, and 27 W for heat from shivering. We found that a spatially varying blood temperature profile within the limbs was crucial to accurately predict core body temperature changes during very cold exposures. Our 3-D thermoregulatory virtual human model consistently predicted the body's thermal state accurately for each of the simulated hot and cold environmental conditions and exertional heat stress. As such, it serves as a reliable tool to assess whole body, localized tissue, and, potentially, organ-specific injury risks, helping develop injury prevention and mitigation strategies in a systematic and expeditious manner. NEW & NOTEWORTHY This work provides a new, unified modeling framework to accurately predict the human body's thermal response to both heat and cold stress caused by environmental conditions and exertional physical activity in one mathematical model. We show that this 3-D anatomically detailed model accurately predicts the spatiotemporal temperature distribution in the body under extreme conditions for exposures to air and water and could be used to help design medical interventions and countermeasures to prevent injuries.