Considering individual physiological differences in a human thermal model

Physiological differences between individuals can significantly affect human thermal response to the environment. In practice, most thermal models use a single set of physiological data to represent an average person. We have developed a model to translate descriptive data about an individual into a set of physiological parameters which may be used in thermal models. We have incorporated these parameters into a model of human thermoregulation and comfort, which may be used to predict variations in thermal response between individuals. This paper presents this model and examples of its use in thermal simulation. r 2001 Elsevier Science Ltd. All rights reserved

Thermal Indices and Thermophysiological Modeling for Heat Stress

This article is closed access.The assessment of the risk of human exposure to heat is a topic as relevant today as a century ago. The introduction and use of heat stress indices and models to predict and quantify heat stress and heat strain has helped to reduce morbidity and mortality in industrial, military, sports, and leisure activities dramatically. Models used range from simple instruments that attempt to mimic the human-environment heat exchange to complex thermophysiological models that simulate both internal and external heat and mass transfer, including related processes through (protective) clothing. This article discusses the most commonly used indices and models and looks at how these are deployed in the different contexts of industrial, military, and biometeorological applications, with focus on use to predict related thermal sensations, acute risk of heat illness, and epidemiological analysis of morbidity and mortality. A critical assessment is made of tendencies to use simple indices such as WBGT in more complex conditions (e.g., while wearing protective clothing), or when employed in conjunction with inappropriate sensors. Regarding the more complex thermophysiological models, the article discusses more recent developments including model individualization approaches and advanced systems that combine simulation models with (body worn) sensors to provide real-time risk assessment. The models discussed in the article range from historical indices to recent developments in using thermophysiological models in (bio) meteorological applications as an indicator of the combined effect of outdoor weather settings on humans

Comparison of thermoregulatory responses to exercise in dry heat among prepubertal boys, young adults and older males

The purpose of this investigation was to compare the thermoregulatory responses during exercise in a hot climate among three age categories. Eight prepubertal (PP), eight young adult (Y) and eight elderly (O) male subjects cycled at an intensity of 50 ± 1% of their maximum oxygen uptake (V[subscript]o2peak) for 85 min (three 20 min bouts with three 7 min rest periods) in hot and dry conditions (41 ± 0.67ºC, 21 ± .%.. relative humidity). During the exercise-in-heat protocol, rectal temperature (T[subscript]re) skin temperatures (T[subscript]sk), heart rate (HR), V[subscript]O2, V[subscript]CO2, Vsubscript]E, RER, sweat rate, and the number of heat activated sweat glands (HASG) were determined. Despite highest and lowest end-exposure T[subscript]re in the Y and O groups, respectively, the rise in rectal temperature (accounting for differences in baseline T[subscript]re) was similar in all age groups. Changes in body heat storage (Delta S), both absolute and relative to body mass, were highest in the Y and O groups and lowest in the PP group. While end-session as well as changes inmean skin temperature were similar in all three age groups, HR (absolute and percentage of maximum) was significantly lower for the O compared with the PP and Y groups. Total body as well as per body surface sweating rate was significantly lower for the PP group, while body mass-related net metabolic heat production ((M - W) kg [superscript]-1) and heat gained from the environment were highest in the PP and lowest in the O group. Since mass-related evaporative cooling (E[subscript]sk kg [superscript]-1) and sweating efficiency (E[subscript]sk/M[subscript]sw kg[superscript]-1) were highest in the PP and lowest in the O group, the mass-dependent heat stored in the body (Delta S kg[superscript]-1) was lowest in the PP (1.87± 0.03 W kg[superscript]-1) and highest in Y and O groups (2.19 ± 0.08 and1.97 ± 0.11 W kg [superscript]-1, respectively). Furthermore, it was calculated that while the O group required only 4.1 ± 0.5 W of heat energy to raise their body core temperature by 1ºC, and the Y group needed 6.9 ± 0.9 W(1º C)[superscript]-1, the PP group required as much as 12.3 ± 0.7 W to heat up their body core temperature by 1ºC. These results suggest that in conditions similar to those imposed during this study, age and age-related characteristics affect the overall rate of heat gain as well as the mechanisms through which this heat is being dissipated. While prepubertal boys seem to be the most efficient thermoregulators, the elderly subjects appear to be the least efficient thermoregulators