Literature DB >> 8143689

Using computer-based models for predicting human thermal responses to hot and cold environments.

R A Haslam1, K C Parsons.   

Abstract

Four influential models, capable of predicting human responses to hot and cold environments and potentially suitable for use in practical applications, were evaluated by comparing their predictions with human data published previously. The models were versions of the Pierce Lab 2-node and Stolwijk and Hardy 25-node models of human thermoregulation, the Givoni and Goldman model of rectal temperature response, and ISO/DIS 7933. Experimental data were available for a wide range of environmental conditions, with air temperatures ranging from -10 to 50 degrees C, and with different levels of air movement, humidity, clothing and work. The experimental data were grouped into environment categories to allow examination of the effects of variables, such as wind or clothing, on the accuracy of the models' predictions. This categorization also enables advice to be given regarding which model is likely to provide the most accurate predictions for a particular combination of environmental conditions. Usually at least one of the models was able to give predictions with an accuracy comparable with the degree of variation that occurred within the data from the human subjects. The evaluation suggests that it is possible to make useful predictions of deep-body and mean skin temperature responses to cool, neutral, warm and hot environmental conditions. The models' predictions of deep-body temperature in the cold were poor. Overall, the 25-node model provided the most consistently accurate predictions. The 2-node model was often accurate but could be poor for exercise conditions. The rectal-temperature model usually overestimated deep-body temperature, although its predictions for very hot or heavy exercise conditions could be useful. The ISO model's allowable exposure times would not have protected subjects for some exercise conditions.

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Year:  1994        PMID: 8143689     DOI: 10.1080/00140139408963659

Source DB:  PubMed          Journal:  Ergonomics        ISSN: 0014-0139            Impact factor:   2.778


  5 in total

1.  Prediction of performance reduction in self-paced exercise as modulated by the rating of perceived exertion.

Authors:  Anthony E Iyoho; Lisa N MacFadden; Laurel J Ng
Journal:  Eur J Appl Physiol       Date:  2014-11-23       Impact factor: 3.078

2.  Multi-sector thermo-physiological head simulator for headgear research.

Authors:  Natividad Martinez; Agnes Psikuta; José Miguel Corberán; René M Rossi; Simon Annaheim
Journal:  Int J Biometeorol       Date:  2016-09-09       Impact factor: 3.787

3.  A 3-D virtual human model for simulating heat and cold stress.

Authors:  Tushar Gulati; Rajeev Hatwar; Ginu Unnikrishnan; Jose E Rubio; Jaques Reifman
Journal:  J Appl Physiol (1985)       Date:  2022-06-23

4.  Thermal responses for men with different fat compositions during immersion in cold water at two depths: prediction versus observation.

Authors:  Xiaojiang Xu; John W Castellani; William Santee; Margaret Kolka
Journal:  Eur J Appl Physiol       Date:  2007-02-16       Impact factor: 3.346

5.  Cardiovascular and thermal strain during 3-4 days of a metabolically demanding cold-weather military operation.

Authors:  John W Castellani; Marissa G Spitz; Anthony J Karis; Svein Martini; Andrew J Young; Lee M Margolis; J Phillip Karl; Nancy E Murphy; Xiaojiang Xu; Scott J Montain; Jamie A Bohn; Hilde K Teien; Pål H Stenberg; Yngvar Gundersen; Stefan M Pasiakos
Journal:  Extrem Physiol Med       Date:  2017-09-06
  5 in total

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