Development and validation of an individualized predicted heat strain model for simulating physiological responses in various conditions

Abstract

Heat strain may cause heat-related illness and reduce work efficiency as well as represent individual differences. To simulate individualized physiological responses of the human body to various conditions, an individualized predicted heat strain (IPHS) model accounting for individual difference factors including height, weight, gender, and age was proposed based on the widely used predicted heat strain (PHS) model. Subsequently, the IPHS model was validated against the PHS model and human trials (total, 3 cases, 9 conditions, and 51 subjects) from the literature. The results indicated that the maximal difference between simulations and measurements in terms of the core temperature, mean skin temperature, and sweating loss was no more than 1.0 °C, 1.6 °C, and 10 g respectively, for all cases. Specifically, an excellent prediction performance of the IPHS model was found, with a lower maximal difference for the core temperature (PHS: 0.98 °C vs. IPHS: 0.55 °C) and sweating loss (PHS: 335.7 g vs. IPHS: 8.9 g) in Case 1. The maximal difference for core temperature was only 0.59 °C under high metabolism (320 W/m2) conditions in Case 2. Furthermore, the prediction performance of the IPHS model varied with the environment and gender. The proposed model performed better on steady-state skin temperature simulations for women than for men in Case 3. It was concluded that the proposed model can predict individualized core temperature, mean skin temperature, and sweating loss with acceptable accuracy for the studied cases. The proposed model can provide insights into personalized heat management and occupational safety protection.