Internet of Medical Things for Noninvasive and Noncontact Dehydration Monitoring Away From the Hospital: State of the Art, Challenges, and Prospects

The dehydration occurs when the body loses more water than it takes in. The mild dehydration can lead to fatigue, cognitive impairments, and physical complications, while severe dehydration can cause life-threatening conditions, such as heat stroke, kidney damage, and hypovolemic shock. Traditional biochemistry-based clinical gold standard methods are expensive, time-consuming, and invasive. Thus, there is a pressing need to design novel noninvasive methods that could do in situ, early and accurate detection of dehydration, which will in turn allow timely intervention. This article presents a methodological review of the literature on a range of innovative Internet of Medical Things (IoMT)-based techniques for dehydration monitoring. We begin by briefly describing the pathophysiology of the dehydration problem, its clinical significance, and current clinical gold-standard methods for assessing hydration level. Subsequently, we critically examine a number of noninvasive and noncontact hydration assessment studies. We also discuss multimodal sensing methods and assess the impact of dehydration among specific population groups (e.g., elderly, infants, and athletes) and on different organs. We also provide a list of existing public and private datasets which make the backbone of machine learning-driven research on dehydration monitoring. Finally, we provide our opinion statement on the challenges and future prospects of noninvasive and noncontact hydration monitoring.