New neurophysiological human thermal model based on thermoreceptor responses.

Human thermoregulation model Neurophysiology Non-uniform transient environments Thermoreceptor

Journal

International journal of biometeorology
ISSN: 1432-1254
Titre abrégé: Int J Biometeorol
Pays: United States
ID NLM: 0374716

Informations de publication

Date de publication:
Dec 2020
Historique:
received: 23 04 2020
accepted: 07 08 2020
revised: 06 08 2020
pubmed: 21 8 2020
medline: 18 11 2020
entrez: 22 8 2020
Statut: ppublish

Résumé

A new neurophysiological human thermal model based on thermoreceptor responses, the NHTM model, has been developed to predict regulatory responses and physiological variables in asymmetric transient environments. The passive system is based on Wissler's model, which is more complex and refined. Wissler's model segments the human body into 21 cylindrical parts. Each part is divided into 21 layers, 15 for the tissues and 6 for clothes, and each layer is divided into 12 angular sectors. Thus, we have 3780 nodes for the tissues and 1512 for clothes. The passive system simulates heat exchange within the body and between the body and the surroundings. The active system is composed of the thermoregulatory mechanisms, i.e., skin blood flow, shivering thermogenesis, and sweating. The skin blood flow model and the shivering model are based on thermoreceptor responses. The sweating model is that of Fiala et al. and is based on error signals. The NHTM model was compared with Wissler's model, and the results showed that a calculation based on neurophysiology can improve the performance of the thermoregulation model. The NHTM model was more accurate in the prediction of mean skin temperature, with a mean absolute error of 0.27 °C versus 0.80 °C for the original Wissler model. The prediction accuracy of the NHTM model for local skin temperatures and core temperature could be improved via an optimization method to prove the ability of the new thermoregulation model to fit with the physiological characteristics of different populations.

Identifiants

pubmed: 32820392
doi: 10.1007/s00484-020-01990-1
pii: 10.1007/s00484-020-01990-1
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2007-2017

Auteurs

Mohamad El Kadri (M)

Centre Scientifique et Technique du Bâtiment CSTB, Marne-la-Vallée, France. Mohamad.Elkadri@Cstb.Fr.
Laboratory of Engineering Sciences for Environment (LaSIE), UMR CNRS 7356, La Rochelle University, La Rochelle, France. Mohamad.Elkadri@Cstb.Fr.

Fabrice De Oliveira (F)

Centre Scientifique et Technique du Bâtiment CSTB, Marne-la-Vallée, France.

Christian Inard (C)

Laboratory of Engineering Sciences for Environment (LaSIE), UMR CNRS 7356, La Rochelle University, La Rochelle, France.

François Demouge (F)

Centre Scientifique et Technique du Bâtiment CSTB, Marne-la-Vallée, France.

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Classifications MeSH