Wearable physiological monitoring for human thermal-work strain optimization

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Abstract

Safe performance limits of soldiers and athletes have typically relied on predictive work-rest models of ambient conditions, average work intensity, and characteristics of the population. Bioengineering advances in noninvasive sensor technologies, including miniaturization, reduced cost, power requirements, and comfort, now make it possible to produce individual predictions of safe thermal-work limits. These precision medicine assessments depend on the development of thoughtful algorithms based on physics and physiology. Both physiological telemetry and thermal-strain indexes have been available for >50 years, but greater computing power and better wearable sensors now make it possible to provide actionable information at the individual level. Core temperature can be practically estimated from time series heart rate data and, using an adaptive physiological strain index, provides meaningful predictions of safe work limits that cannot be predicted from only core temperature or heart rate measurements. Early adopters of this technology include specialized occupations where individuals operate in complete encapsulation such as chemical protective suits. Emerging technologies that focus on heat flux measurements at the skin show even greater potential for estimating thermal-work strain using a parsimonious sensor set. Applications of these wearable technologies include many sports and military training venues where inexperienced individuals can learn effective work pacing strategies and train to safe personal limits. The same strategies can also provide a technologically based performance edge for experienced workers and athletes faced with novel and nonintuitive physiological challenges, such as health care providers in full protective clothing treating Ebola patients in West Africa in 2014.

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APA

Buller, M. J., Welles, A. P., & Friedl, K. E. (2018, February 1). Wearable physiological monitoring for human thermal-work strain optimization. Journal of Applied Physiology. American Physiological Society. https://doi.org/10.1152/japplphysiol.00353.2017

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