Modeling thermoregulatory responses during high-intensity exercise in warm environments.

The six cylinder thermoregulatory model (SCTM) has been validated thoroughly for resting humans. This type of modeling is helpful to predict and develop guidance for safe performance of work and recreational activities. In the context of a warming global climate, updating the accuracy of the model for intense exercise in warm environments will help a wide range of individuals in athletic, recreational, and military settings. Three sets of previously collected data were used to determine SCTM accuracy. Dataset 1: two groups [large (LG) 91.5 kg and small (SM) 67.7 kg] of individuals performed 60 min of semirecumbent cycling in temperate conditions (25.1°C) at metabolic rates of 570-700 W. Dataset 2: two LG (100 kg) and SM (65.8 kg) groups performed 60 min of semirecumbent cycling in warm/hot environmental conditions (36.2°C) at metabolic rates of 590-680 W. Dataset 3: seven volunteers completed 8-km track trials (∼30 min) in cool (17°C) and warm (30°C) environments. The volunteers' metabolic rates were estimated to be 1,268 W and 1,166 W, respectively. For all datasets, SCTM-predicted core temperatures were found to be similar to the observed core temperatures. The root mean square deviations (RMSDs) ranged from 0.06 to 0.46°C with an average of 0.2°C deviation, which is less than the acceptance threshold of 0.5°C. Thus, the present validation shows that SCTM predicts core temperatures with acceptable accuracy during intense exercise in warm environments and successfully captures core temperature differences between large and small individuals.NEW & NOTEWORTHY The SCTM has been validated thoroughly for resting humans in warm and cold environments and during water immersion. The present study further demonstrated that SCTM predicts core temperatures with acceptable accuracy during intense exercise up to 1,300 W in temperate and warm environments and captures core temperature differences between large and small individuals. SCTM is potentially useful to develop guidance for safe operation in athletic, military, and occupational settings during exposure to warm or hot environments.

Validation of a human thermoregulatory model during prolonged immersion in warm water.

This study validates the Six Cylinder Thermoregulatory Model (SCTM) during prolonged warm water immersion, which underpins the Probability of Survival Decision Aid (PSDA) currently in use by the United States Coast Guard (USCG). PSDA predicts survival time for hypothermia and dehydration. USCG has been using PSDA for search and rescue operation since 2010. In 2019, USCG organized a workshop to review PSDA performance and concluded that PSDA is an essential tool for operation, although it occasionally overestimates survival times in warm waters above 16 °C. Forty-six human subjects were immersed from the neck down in 18, 22, and 26 °C water for 45 min up to 10 h. Rectal temperature (Tcore), 10-site mean skin temperature (Tsk), and water loss were measured. At the end of immersion, Tcore ranged from 35.2 to 38.0 °C, and Tsk ranged from 19.7 to 27.4 °C. The SCTM-predicted Tcore, Tsk and water loss were compared to the measured values. Root mean squared deviation (RMSD) was used to test for acceptable predictions. Tcore RMSDs were 0.2, 0.14, and 0.3 °C in 18, 22, and 26 °C water respectively. Tsk RMSDs were 1.44, 0.76, and 1.1 °C in 18, 22, and 26 °C water respectively. SCTM underpredicted water loss by 84%. Overall, SCTM predicted Tcore and Tsk with acceptable accuracy in 18 and 22 °C water for up to 10 h, but overpredicted in 26 °C water. Future studies and algorithm development are required to improve water loss prediction as well as Tcore and Tsk prediction in 26 °C water.

The specific heat of the human body is lower than previously believed: The journal Temperature toolbox.

The specific heat capacity of the human body is an important value for heat balance analysis in thermoregulation and metabolism research. The widely used value of 3.47 kJ · kg-1· °C-1 was originally based on assumptions and was not measured or calculated. The purpose of this paper is to calculate the specific heat of the body, defined as the mass-weighted mean of the tissue specific heat. The masses of 24 body tissue types were derived from high-resolution magnetic resonance images of four virtual human models. The specific heat values of each tissue type were obtained from the published tissue thermal property databases. The specific heat of the entire body was calculated to be approximately 2.98 kJ · kg-1 · °C-1 and ranged from 2.44 to 3.39 kJ · kg-1 · °C-1 depending on whether min or max measured tissue values were used for the calculation. To our knowledge, this is the first time specific heat of the body has been calculated from the measured values of individual tissues. The contribution of the muscle to the specific heat of the body is approximately 47%, and the contribution of the fat and skin is approximately 24%. We believe this new information will improve the accuracy of calculations related to human heat balance in future studies of exercise, thermal stress, and related areas.

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.

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.

A geometrically accurate 3 dimensional model of human thermoregulation for transient cold and hot environments.

This paper outlines the development of a finite element human thermoregulatory model using an anatomically and geometrically correct human body model. The finite element body model was constructed from digital Phantoms and is anatomically realistic, including 13 organs and tissues: skin, muscles, fat, bones, heart, lungs, brain, bladder, intestines, stomach, kidneys, liver, and eyes. The model simulates thermal responses through a passive and active system. The passive system describes heat balance within the body and between the skin surface and environment. The active system describes thermoregulatory mechanisms, i.e., vasodilation, vasoconstriction, sweating, and shivering heat production. This model predicts temperature distribution across the body at high spatial resolution, and provides insight into human thermoregulatory responses to non-uniform and transient environments. Predicted temperatures (i.e., core, skin, muscle and fat) at 29 sites were compared with measured values in comfort, hot, and cold conditions. The comprehensive validation shows predictions are accurate and acceptable.

A digital tool for prevention and management of cold weather injuries-Cold Weather Ensemble Decision Aid (CoWEDA).

This paper describes a Cold Weather Ensemble Decision Aid (CoWEDA) that provides guidance for cold weather injury prevention, mission planning, and clothing selection. CoWEDA incorporates current science from the disciplines of physiology, meteorology, clothing, and computer modeling. The thermal performance of a cold weather ensemble is defined by endurance times, which are the time intervals from initial exposure until the safety limits are reached. These safety limits correspond to conservative temperature thresholds that provide a warning of the approaching onset of frostbite and/or hypothermia. A validated six-cylinder thermoregulatory model is used to predict human thermal responses to cold while wearing different ensembles. The performance metrics, model, and a database of clothing properties were integrated into a user-friendly software application. CoWEDA is the first tool that allows users to build their own ensembles from the clothing menu (i.e., jackets, footwear, and accessories) for each body region (i.e., head, torso, lower body, hands, feet) and view their selections in the context of physiological strain and the operational consequences. Comparison of predicted values to skin and core temperatures, measured during 17 cold exposures ranging from 0 to -40°C, indicated that the accuracy of CoWEDA prediction is acceptable, and most predictions are within measured mean ± SD. CoWEDA predicts the risk of frostbite and hypothermia and ensures that a selected clothing ensemble is appropriate for expected weather conditions and activities. CoWEDA represents a significant enhancement of required clothing insulation (IREQ, ISO 11079) and wind chill index-based guidance for cold weather safety and survival.

Heat strain in chemical protective ensembles: Effects of fabric thermal properties.

An ongoing challenge in material science has been to reduce heat strain experienced by individuals wearing chemical protective ensembles. The objective of this study is to analyze the relationship between the thermal properties of eight chemical protective fabrics and heat strain in ten chemical protective ensembles constructed with those fabrics. The fabric samples were tested on a sweating guarded hot plate to measure fabric thermal and evaporative resistance. The ensembles were then tested on thermal manikins to measure ensemble thermal and evaporative resistance. An empirical thermoregulatory model, the Heat Strain Decision Aid (HSDA), was used to predict thermal responses of core temperature and endurance times. Model inputs included ensemble thermal and evaporative resistances, four environmental conditions and a metabolic rate of 400 W. The fabric intrinsic thermal and evaporative resistances ranged from 0.01 to 0.05 m2 °C·W-1 and from 5.9 to 12.82 m2 Pa·W-1, respectively. Ensemble intrinsic thermal and evaporative resistances ranged from 0.23 to 0.31 m2 °C·W-1 and 51.7-67.8 m2 Pa·W-1, respectively. Predicted endurance times varied from 170 to 300 min at 20 °C/50% RH/2 m s-1 and 26 °C/55% RH/9 m s-1 conditions, and varied from 91 to 98 min at 30 °C/75% RH/2 m s-1 and 40 °C/20% RH/2 m s-1 conditions. Improved fabric thermal properties reduced heat strain and extended endurance times, but the magnitude of the extended times is dependent on the environmental conditions. Consequently, the benefits of improved fabric thermal properties may only be observed under certain environmental conditions.

Measured body composition and geometrical data of four "virtual family" members for thermoregulatory modeling.

The purpose of this paper is to develop a database of tissue composition, distribution, volume, surface area, and skin thickness from anatomically correct human models, the virtual family. These models were based on high-resolution magnetic resonance imaging (MRI) of human volunteers, including two adults (male and female) and two children (boy and girl). In the segmented image dataset, each voxel is associated with a label which refers to a tissue type that occupies up that specific cubic millimeter of the body. The tissue volume was calculated from the number of the voxels with the same label. Volumes of 24 organs in body and volumes of 7 tissues in 10 specific body regions were calculated. Surface area was calculated from the collection of voxels that are touching the exterior air. Skin thicknesses were estimated from its volume and surface area. The differences between the calculated and original masses were about 3 % or less for tissues or organs that are important to thermoregulatory modeling, e.g., muscle, skin, and fat. This accurate database of body tissue distributions and geometry is essential for the development of human thermoregulatory models. Data derived from medical imaging provide new effective tools to enhance thermal physiology research and gain deeper insight into the mechanisms of how the human body maintains heat balance.