A 3-D virtual human thermoregulatory model to predict whole-body and organ-specific heat-stress responses

Human body numerical simulation: An accurate model for a thigh subjected to a cold treatment

This article presents the development of a digital twin model of a thigh portion subjected to various thermal treatments. Two scenarios are investigated: cold water immersion (CWI) and whole body cryotherapy (WBC), for which the comparison of numerical results with experimental measurements validates the consistency of the developed model. The use of real geometry on a first subject demonstrates the high heterogeneity of the temperature field and the need for accurate geometry. A second subject with thicker adipose tissue highlights the impact of the subject's actual morphology on the validity of the treatment and the necessity to work with real geometry in order to optimize cold modalities and develop personalized treatments.

Three dimensional models of human thermoregulation: A review

Numerous human thermoregulatory models have been developed and widely used in various applications such as aerospace, medicine, public health, and physiology research. This paper is a review of three dimensional (3D) models for human thermoregulation. This review begins with a short introduction of thermoregulatory model development followed by key principles for mathematical description of human thermoregulation systems. Different representations of 3D human bodies are discussed with respect to their detail and prediction capability. The human body was divided into fifteen layered cylinders in early 3D models (cylinder model). Recent 3D models have utilized medical image datasets to develop geometrically correct human models (realistic geometry model). The finite element method is mostly used to solve the governing equations and get numerical solutions. The realistic geometry models provide a high degree of anatomical realism and predict whole-body thermoregulatory responses at high resolution and at organ and tissue levels. Thus, 3D models extend to a wide range of applications where temperature distribution is critical, such as hypothermia/hyperthermia therapy and physiology research. The development of thermoregulatory models will continue with the growth in computational power, advancement in numerical methods and simulation software, advances in modern imaging techniques, and progress in the basic science of thermal physiology.

Finite element model of female thermoregulation with geometry based on medical images

INTRODUCTION

this study describes the development of a female finite element thermoregulatory model (FETM) METHOD: the female body model was developed from medical image datasets of a median U.S. female and was constructed to be anatomically correct. The body model preserves the geometric shapes of 13 organs and tissues, including skin, muscles, fat, bones, heart, lungs, brain, bladder, intestines, stomach, kidneys, liver, and eyes. Heat balance within the body is described by the bio-heat transfer equation. Heat exchange at the skin surface includes conduction, convection, radiation, and sweat evaporation. Vasodilation, vasoconstriction, sweating, and shivering are controlled by afferent and efferent signals to and from the skin and hypothalamus.

RESULTS

the model was validated with measured physiological data during exercise and rest in thermoneutral, hot, and cold conditions. Validations show the model predicted the core temperature (rectal and tympanic temperatures) and mean skin temperatures with acceptable accuracy (within 0.5 °C and 1.6 °C, respectively) CONCLUSION: this female FETM predicted high spatial resolution temperature distribution across the female body, which provides quantitative insights into human thermoregulatory responses in females to non-uniform and transient environmental exposure.

Parametric analysis of an efficient boundary condition to control outlet flow rates in large arterial networks

Substantial effort is being invested in the creation of a virtual human-a model which will improve our understanding of human physiology and diseases and assist clinicians in the design of personalised medical treatments. A central challenge of achieving blood flow simulations at full-human scale is the development of an efficient and accurate approach to imposing boundary conditions on many outlets. A previous study proposed an efficient method for implementing the two-element Windkessel model to control the flow rate ratios at outlets. Here we clarify the general role of the resistance and capacitance in this approach and conduct a parametric sweep to examine how to choose their values for complex geometries. We show that the error of the flow rate ratios decreases exponentially as the resistance increases. The errors fall below 4% in a simple five-outlets model and 7% in a human artery model comprising ten outlets. Moreover, the flow rate ratios converge faster and suffer from weaker fluctuations as the capacitance decreases. Our findings also establish constraints on the parameters controlling the numerical stability of the simulations. The findings from this work are directly applicable to larger and more complex vascular domains encountered at full-human scale.

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.

Use of Thermoregulatory Models to Evaluate Heat Stress in Industrial Environments

Heat stress in many industrial workplaces imposes significant risk of injury to individuals. As a means of quantifying these risks, a comparison of four rationally developed thermoregulatory models was conducted. The health-risk prediction (HRP) model, the human thermal regulation model (HuTheReg), the SCENARIO model, and the six-cylinder thermoregulatory model (SCTM) each used the same inputs for an individual, clothing, activity rates, and environment based on previously observed conditions within the Portuguese glass industry. An analysis of model correlations was conducted for predicted temperatures (°C) of brain (TBrain), skin (TSkin), core body (TCore), as well as sweat evaporation rate (ER; Watts). Close agreement was observed between each model (0.81-0.98). Predicted mean ± SD of active phases of exposure for both moderate (TBrain 37.8 ± 0.25, TSkin 36.7 ± 0.49, TCore 37.8 ± 0.45 °C, and ER 207.7 ± 60.4 W) and extreme heat (TBrain 39.1 ± 0.58, TSkin, 38.6 ± 0.71, TCore 38.7 ± 0.65 °C, and ER 468.2 ± 80.2 W) were assessed. This analysis quantifies these heat-risk conditions and provides a platform for comparison of methods to more fully predict heat stress during exposures to hot environments.