Modeling physiological responses to military scenarios: initial core temperature and downhill work

• Published in: Aviation, space, and environmental medicine space, and environmental medicine, 2005-05, Vol.76 (5), p.475-480
• Main Authors: Yokota, Miyo, Berglund, Larry G, Santee, William R, Buller, Mark J, Hoyt, Reed W
• Format: Article
• Language: English
• Subjects: Adult; Body Temperature - physiology; Heart Rate - physiology; Hot Temperature; Humans; Male; Military Medicine - methods; Military Personnel - education; Models, Biological; Muscle, Skeletal - physiology; Physical Education and Training - methods; Physical Exertion - physiology; Posture; Space life sciences; Task Performance and Analysis
• ISSN: 0095-6562

Previous field studies suggested that a thermoregulatory model developed by the U.S. Army Research Institute of Environmental Medicine (USARIEM) needed an adjustment of initial core temperature (Tcr) for individual variation and a metabolic (M) correction during downhill movements. This study evaluated the updated version of the model incorporating these new features using a dataset collected during U.S. Marine Corps marksmanship training at Quantico, VA. Individual anthropometrics, physiological, and environmental time series data were obtained from five Marine men. The study focused on the marksmanship training for approximately 2 h, then 30-min marching including uphill and downhill movements in a moderately hot environment (air temperature: approximately 30 degrees C; dew point: approximately 21 degrees C). The predicted and observed heart rate (HR) and Tcr measurements were compared by root mean square deviations (RMSD). Overall, the current model improved predictions of physiological measures (HR RMSD = 23 bpm, Tcr RMSD = 0.46 degrees C), particularly for marching in the heat (HR RMSD = 21 bpm, Tcr RMSD = 0.32 degrees C). The model under-predicted both HR and Tcr during marksmanship training, indicating that a greater solar effect or non-thermal factors may have required higher M rates during these periods. Updated features of the model significantly improved physiological predictions. However, accurate M estimates are required for slow movements of subjects under heat stress, such as movements on the firing range. Such improvement should result in more accurate simulations of physiological status and better risk assessment, thereby reducing heat injuries and improving performance of deployed military personnel.