caa a22 4500 445367393 CHVBK 20180317142935.0 cr unu---uuuuu 170323e20110701xx s 000 0 eng 10.1007/s00484-010-0371-8 doi (NATIONALLICENCE)springer-10.1007/s00484-010-0371-8 Sweat loss prediction using a multi-model approach [Elektronische Daten] [Xiaojiang Xu, William Santee] A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions. Springer, 2010 Sweat nationallicence Prediction nationallicence Model nationallicence Thermal strain nationallicence Fluid intake nationallicence Xu Xiaojiang Biophysics and Biomedical Modeling Division, US Army Research Institute of Environmental Medicine, Kansas St., 01760, Natick, MA, USA aut Santee William Biophysics and Biomedical Modeling Division, US Army Research Institute of Environmental Medicine, Kansas St., 01760, Natick, MA, USA aut International Journal of Biometeorology Springer-Verlag 55/4(2011-07-01), 501-508 0020-7128 55:4<501 2011 55 484 https://doi.org/10.1007/s00484-010-0371-8 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00484-010-0371-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Xu Xiaojiang Biophysics and Biomedical Modeling Division, US Army Research Institute of Environmental Medicine, Kansas St., 01760, Natick, MA, USA aut NATIONALLICENCE 700 1- Santee William Biophysics and Biomedical Modeling Division, US Army Research Institute of Environmental Medicine, Kansas St., 01760, Natick, MA, USA aut NATIONALLICENCE 773 0- International Journal of Biometeorology Springer-Verlag 55/4(2011-07-01), 501-508 0020-7128 55:4<501 2011 55 484 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer