This review discusses the physiology of hypovolemia and the future potential of wearable sensors and machine learning algorithms to manage hypovolemia in occupational, military, and sports medicine.
Wearable sensors combined with machine learning algorithms hold potential for monitoring and managing hypovolemia in occupational, military, and sports settings.
Hypovolemia is a physiological state of reduced blood volume that can exist as either (1) absolute hypovolemia because of a lower circulating blood (plasma) volume for a given vascular space (dehydration, hemorrhage) or (2) relative hypovolemia resulting from an expanded vascular space (vasodilation) for a given circulating blood volume (e.g., heat stress, hypoxia, sepsis). This paper examines the physiology of hypovolemia and its association with health and performance problems common to occupational, military and sports medicine. We discuss the maturation of individual-specific compensatory reserve or decompensation measures for future wearable sensor systems to effectively manage these hypovolemia problems. The paper then presents areas of future work to allow such technologies to translate from lab settings to use as decision aids for managing hypovolemia. We envision a future that incorporates elements of the compensatory reserve measure with advances in sensing technology and multiple modalities of cardiovascular sensing, additional contextual measures, and advanced noise reduction algorithms into a fully wearable system, creating a robust and physiologically sound approach to manage physical work, fatigue, safety and health issues associated with hypovolemia for workers, warfighters and athletes in austere conditions.
Kimball et al. (Fri,) conducted a review in Hypovolemia. Wearable sensors and machine learning was evaluated. This review discusses the physiology of hypovolemia and the future potential of wearable sensors and machine learning algorithms to manage hypovolemia in occupational, military, and sports medicine.