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Review
. 2022 Oct 12;14(666):eabn6036.
doi: 10.1126/scitranslmed.abn6036. Epub 2022 Oct 12.

Translational gaps and opportunities for medical wearables in digital health

Affiliations
Review

Translational gaps and opportunities for medical wearables in digital health

Shuai Xu et al. Sci Transl Med. .

Abstract

A confluence of advances in biosensor technologies, enhancements in health care delivery mechanisms, and improvements in machine learning, together with an increased awareness of remote patient monitoring, has accelerated the impact of digital health across nearly every medical discipline. Medical grade wearables-noninvasive, on-body sensors operating with clinical accuracy-will play an increasingly central role in medicine by providing continuous, cost-effective measurement and interpretation of physiological data relevant to patient status and disease trajectory, both inside and outside of established health care settings. Here, we review current digital health technologies and highlight critical gaps to clinical translation and adoption.

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Conflict of interest statement

Competing interests: J.A.R. is a co-founder and advisor to Sibel Health, Sonica, and Epicore Biosystems and holds patents associated with these companies.

Figures

Fig. 1.
Fig. 1.. Unique mounting locations.
(A) An overview of emerging mounting locations and form factors for medical wearables. (B) Images of five representative form factors: a miniaturized device on a fingernail (13), a holey device on the skin (42), a binodal pair of skin-like devices on the hand, a soft microfluidic on the skin (17), and an instrumented contact lens on the eye (27). Photographs in (B) are reproduced with permission from (13, 17, 27, 42).
Fig. 2.
Fig. 2.. Emerging applications of medical wearables.
Representative data to illustrate measurement capabilities of clinical importance using emerging medical wearables: blood pressure, swallow activity, EMG signals (43), blood oxygen concentration (13), flow of cerebrospinal fluid (CSF) (12), glucose concentration in sweat (18), and glucose concentration in tear fluid (28). Graphs are reproduced with permission from (12, 13, 18, 28, 43).

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