From Physiology to Bioheat Simulation: A Data‐Driven Framework for Core Temperature Initialization

ABSTRACT Accurate initialization of core body temperature is a critical yet often overlooked component of bioheat transfer models, particularly when such models are applied to heterogeneous populations and real‐world environmental conditions. Conventional bioheat simulations typically rely on fixed or idealized core body temperature values derived from limited datasets, thereby limiting their physiological realism and predictive capacity across diverse demographic and environmental scenarios. Here, we present a data‐driven framework that bridges physiological thermoregulation data and bioheat simulation by systematically integrating literature‐derived core body temperature measurements with synthetic individual‐level data generation. A structured database was compiled from 72 published studies encompassing variations in sex, age group, athletic status, and environmental exposure (indoor vs . outdoor). Using statistical resampling and bootstrap‐based simulation, large‐scale synthetic core body temperature distributions were generated to capture inter‐individual variability while preserving the statistical properties of reported experimental data. These distributions were then used to define physiologically grounded initial conditions for a three‐layer skin bioheat model implemented in COMSOL Multiphysics. Factorial and multivariate statistical analyses revealed that environmental context is the dominant driver of core body temperature variability, with demographic factors such as sex, age, and athletic status exerting secondary, context‐dependent effects that become pronounced primarily under outdoor heat stress. The data‐driven core body temperature initialization was subsequently applied to in‐silico bioheat simulations under realistic indoor conditions and outdoor scenarios representative of Olympic marathon events, incorporating solar irradiance, convection, evaporation, and radiation effects. Simulation

Results: demonstrated consistent depth‐dependent thermal stratification across skin layers and highlighted how variations in initial core body temperature significantly modulate predicted tissue temperatures and cumulative thermal load under high‐irradiance conditions. Overall, this study establishes a physiologically grounded, statistically robust approach for initializing bioheat simulations, enabling more realistic modeling of human thermal responses across populations and environments. The proposed framework provides a transferable foundation for thermophysiological risk assessment and heat‐stress mitigation strategies in elite sport and other high‐heat exposure contexts.