Metabolic heat flux density (M) in the human biometeorological models: Can M be parameterized based on heart rate estimated by smart devices?

  • Ferenc Ács Eötvös Loránd University, Department of Meteorology
  • Erzsébet Kristóf Eötvös Loránd University, Department of Meteorology
Keywords: Metabolic heat flux density, Heart rate, Parameterization, Human biometeorology, Smart tools

Abstract

In this study, we focus on the calculation methods of human metabolic heat flux density (M) and on the applications of these methods in human thermal load models. Special attention was paid to the method that calculates M based on the heart rate (HR). A new M – HR based formula is presented. The connection was determined by measuring the average movement speed (V) and heart rate at the same time and then calculating M from V. The average V was determined by using a stopwatch. The average HR value was measured by using the Applewatch smart watch. The M(V) relationships are taken from the literature. Two persons performed the measurements in Martonvásár (a town close to Budapest), Budapest and Szombathely: a younger woman and an older man. The main lesson of our research is that M – HR based parametrization is individual-specific, despite the fact that the M – HR relationship can be characterized by a general function, which initially increases exponentially and then enters a saturation phase. This type of research will be widespread, given that we are living in the age of smart tools.

References

Amaro-Gahete, F.J., Sanchez-Delgado, G., Alcantara, J.M.A., Martinez-Tellez, B., Acosta, F.M., Merchan-Ramirez, E., Löf, M., Labayen, I., Ruiz, J.M. (2019): Energy expenditure differences across lying, sitting, and standing positions in young healthy adults. PLoS One, 14(6): e0217029. DOI: https://doi.org/10.1371/journal.pone.0217029

Auliciems, A., Kalma, J.D. (1979): A climatic classification of human thermal stress in Australia. Journal of Applied Meteorology, 18(5): 616–626. DOI: https://doi.org/10.1175/1520-0450(1979)018<0616:ACCOHT>2.0.CO;2

Ács, F., Zsákai, A., Kristóf, E., Szabó, A.I., Breuer, H. (2021): Human thermal climate of the Carpathian Basin. International Journal of Climatology, 41(S1): E1846–E1859. DOI: https://doi.org/10.1002/joc.6816

Ács, F., Szalkai, Z., Kristóf, E., Zsákai, A. (2023): Thermal Resistance of Clothing in Human Biometeorological Models. Geographica Pannonica, 27(2): 83–90. DOI: https://doi.org/10.5937/gp27-40554

Ács, F., Kristóf, E., Zsákai, A. (2024): Weather dependence of heart rate and skin surface evaporation: an analysis for selected summer weather conditions (in Hung.). Légkör, 69(4): 231–241. DOI: https://doi.org/10.56474/legkor.2024.4.4

Blazejczyk, K. Krawczyk, B. (1994): Bioclimatic research of the human heat balance. Polish Academy of Sciences, Institute of Geography and Spatial Organization, 28. pp. 66.

Blazejczyk, K., Bröde, P., Fiala, D., Havenith, G., Holmér, I., Jendritzky, G., Kampmann, B., Kunert, A. (2010): Principles of the New Universal Thermal Climate Index (UTCI) and its Application to Bioclimatic Research in European Scale. Miscellanea Geographica, 14, 91–102. DOI: https://doi.org/10.2478/mgrsd-2010-0009

Bröde, P., Kampmann, B. (2019): Accuracy of metabolic rate estimates from heart rate under heat stress–an empirical validation study concerning ISO8996. Industrial Health, 57: 615–620.

Campbell, G.S., Norman, J.M. (1998): An Introduction to Environmental Biophysics. 2nd ed. Springer, New York. pp. 286.

Dubois, D., Dubois, E.F. (1916): A formula to estimate the approximate surface area if height and weight be known. Archives of Internal Medicine, 17: 863–871.

Höppe, P. (1999): The physiological equivalent temperature – a universal index for the biometeorological assessment of the thermal environment. International Journal of Biometeorology, 43(2): 71–75. DOI: https://doi.org/10.1007/s004840050118

ISO8996 (2004): Ergonomics of the thermal environment - Determination of metabolic rate. International Standard Organisation., Geneva, Switzerland, 14 pp.

Judice, P.B., Hamilton, M.T., Sardinha, L.B., Zderic, T.W., Silva, A.M. (2016): What is the metabolic and energy cost of sitting, standing and sit/stand transitions? European Journal of Applied Physiology, 116: 263–273. DOI: https://doi.org/10.1007/s00421-015-3279-5

Malchaire, J., d’Ambrosio Alfano, F.R., Palella, B.I. (2017): Evaluation of the metabolic rate based on the recording of the hearth rate. Industrial Health, 55: 219–232. DOI: https://doi.org/10.2486/indhealth.2016-0177

Mifflin, M.D., St Jeor, S.T., Hill, L.A., Scott, B.J., Daugherty, S.A., Koh, Y.O. (1990): A new predictive equation for resting energy expenditure in healthy individuals. American Journal of Clinical Nutrition, 51(2): 241-247. DOI: https://doi.org/10.1093/ajcn/51.2.241

Potchter, O., Cohen, P., Lin, T.-P., Matzarakis, A. (2018): Outdoor human thermal perception in various climates: A comprehensive review of approaches, methods and quantification. Science of The Total Environment, 631–632, 390–406. DOI: https://doi.org/10.1016/j.scitotenv.2018.02.276

Weyand, P.G., Smith, B.R., Puyau, M.R., Butte, N.F. (2010). The mass-specific energy cost of human walking is set by stature. Journal of Experimental Biology, 213: 3972–3979. DOI: https://doi.org/10.1242/jeb.048199

Zsákai, A., Bodzsár, É. (2014) The relationship between body structure and the socioeconomic status in Hungarian children and adolescents. Collegium Antropologicum, 38(2): 479-485.

Published
2025-12-18
Section
Original papers