Exercise-responsive skin blood flow modeling enhances thermophysiological predictions in occupational heat stress: The journal Temperature toolbox

Thermophysiological models are widely used to predict human thermal responses during environmental and occupational heat stress. For predictions in the heat, a critical component is the representation of skin blood flow (SkBF), which transports heat from the body’s core to the skin, where it can be lost to the environment. In many existing thermophysiological models, SkBF is represented primarily as a function of core and skin temperatures. However, they do not explicitly account for cardiovascular constraints that arise during exercise, when blood flow must be distributed between active skeletal muscles and thermoregulatory demands. In this study, we integrated the exercise-responsive SkBF model from Kraning and Gonzalez into a thermophysiological model (ThermoSEM) and compared predictions to experimental data. The experimental dataset consists of 83 trials from 25 participants performing 90 min of cycling under controlled environmental conditions (30–45°C) and metabolic heat production levels (200–500 W). Simulations using the original ThermoSEM SkBF formulation systematically overpredicted rectal temperature and underpredicted mean skin temperature, particularly at higher metabolic heat production levels. Incorporating the Kraning-based SkBF model substantially improved agreement with experimental data. Across all protocols, the root mean square error decreased by approximately 40% for rectal temperature and 26% for mean skin temperature, with the largest improvements observed during elevated metabolic heat production. The improved SkBF representation enhanced heat transport to the skin, increasing evaporative capacity and reducing excessive core heat storage. These results demonstrate that incorporating cardiovascular constraints into SkBF modeling can significantly improve thermophysiological predictions during exercise in hot environments.