Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O’Brien WL, Bassett DR, Schmitz KH, Emplaincourt PO, Jacobs DR, Leon AS (2000) Compendium of Physical Activities: an update of activity codes and MET intensities. Medicine & Science in Sports & Exercise 32(Supplement):S498–S516. https://doi.org/10.1097/00005768-200009001-00009
ASHRAE Standard 55. (2004). Thermal environment conditions for human occupancy. American Society of Heating, Refrigerating and Air conditioning Engineers. Atlanta
Cunningham, D. J., Stolwijk, J. (1968). Expansion of a mathematical model of thermoregulation to include high metabolic rates (Technical Report NASA-CR-92443, FR-A).
Fanger PO (1970) Thermal comfort. Analysis and applications in environmental engineering. Technical University of Denmark: DANISH TECHNICAL PRESS, Lyngby https://www.cabdirect.org/cabdirect/abstract/19722700268
Fiala D, Lomas KJ, Stohrer M (2001) Computer prediction of human thermoregulatory and temperature responses to a wide range of environmental conditions. International Journal of Biometeorology 45(3):143–159. https://doi.org/10.1007/s004840100099
Gagge A, Stolwijk J, Nishi Y (1971) An effective temperature scale based on a simple model of human thermological response. ASHRAE 77(1):21–36
Hardy JD, Du Bois EF, Soderstrom GF (1938) The technic of measuring radiation and convection: one figure. The Journal of Nutrition 15(5):461–475. https://doi.org/10.1093/jn/15.5.461
Hayward S, Eckerson D, Collis L (1977) Thermoregulatory heat production in man: predictionn equation based on skin and core temperatures. J. Appl. Physiol. 22:377–384
Hensley DW, Mark AE, Abella JR, Netscher GM, Wissler EH, Diller KR (2013) 50 years of computer simulation of the human thermoregulatory system. Journal of Biomechanical Engineering 135(2):021005-1-9. https://doi.org/10.1115/1.4023383
ISO 7730. (1984). Moderate thermal environment—determination of the PMV and PPD indices and specification of the conditions for thermal comfort. https://www.iso.org/cms/render/live/en/sites/isoorg/contents/data/standard/01/45/14566.html
Kingma, B. (2012). Human thermoregulation: a synergy between physiology and mathematical modeling. PhD dissertation, Universitaire Pers Maastricht.
Lamb S, Kwok KCS (2016) A longitudinal investigation of work environment stressors on the performance and wellbeing of office workers. Applied Ergonomics 52:104–111. https://doi.org/10.1016/j.apergo.2015.07.010
Mekjavic IB, Morrison JB (1985) A model of shivering thermogenesis based on the neurophysiology of thermoreception. IEEE Transactions on Biomedical Engineering BME-32(6):407–417. https://doi.org/10.1109/TBME.1985.325467
Munir A, Takada S, Matsushita T (2009) Re-evaluation of Stolwijk’s 25-node human thermal model under thermal-transient conditions: Prediction of skin temperature in low-activity conditions. Building and Environment 44(9):1777–1787. https://doi.org/10.1016/j.buildenv.2008.11.016
Ooka R, Minami Y, Sakoi T, Tsuzuki K, Rijal HB (2010) Improvement of sweating model in 2-Node Model and its application to thermal safety for hot environments. Building and Environment 45(7):1565–1573. https://doi.org/10.1016/j.buildenv.2009.12.012
Pennes HH (1948) Analysis of tissue and arterial blood temperatures in the resting human forearm. Journal of Applied Physiology 1(2):93–122
Song, H. J. (2017). Overview of Human Thermal Modeling, Thermoregulation, and Thermal Comfort at NASA. NASA, 18.
Stolwijk J, Pierce J (1971) A mathematical model of physiological temperature regulation in man. National Aeronautics and Space Administration 1855:1–82
Tanabe S, Kobayashi K, Nakano J, Ozeki Y, Konishi M (2002) Evaluation of thermal comfort using combined multi-node thermoregulation (65MN) and radiation models and computational ¯uid dynamics (CFD). Energy and Buildings 34:637–646
Wissler EH (1964) A mathematical model of the human thermal system. The Bulletin of Mathematical Biophysics 26(2):147–166. https://doi.org/10.1007/BF02476835
Wissler EH (2008) A quantitative assessment of skin blood flow in humans. European Journal of Applied Physiology 104(2):145–157. https://doi.org/10.1007/s00421-008-0697-7
Wissler, E. H. (2018). Human temperature control: a quantitative approach. The university of Texas at Austin, Department of chemical engineering. https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=1923756
Wissler, P., Kennehter, R. D., Thomas, F. E., John, S. S. (2019). Memorial resolution for Eugene Wissler. McKetta Department of Chemical Engineering. https://che.utexas.edu/2019/05/09/memorial-resolution-for-eugene-wissler/
Wölki, D. (2017). MORPHEUS: Modelica-based implementation of a numerical human model involving individual human aspects. PhD dissertation, RWTH Aachen University. https://doi.org/10.18154/RWTH-2017-04128
Zotterman Y (1953) Special senses: thermal receptors. Annual Review of Physiology 15(1):357–372. https://doi.org/10.1146/annurev.ph.15.030153.002041
Acknowledgments
We would very much like to thank Dr. Eugene H. Wissler, professor emeritus in Chemical Engineering at the University of Texas, for having kindly shared his thermoregulation model with us and for helping us to understand his exceptional research (Wissler et al. 2019). May the soul of this immense researcher rest in peace.
Funding
This work is financed by the CSTB (Centre Scientifique et Technique du bâtiment, Nantes, France).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
El Kadri, M., De Oliveira, F., Inard, C. et al. New neurophysiological human thermal model based on thermoreceptor responses. Int J Biometeorol 64, 2007–2017 (2020). https://doi.org/10.1007/s00484-020-01990-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00484-020-01990-1