Journal
MEDICINE & SCIENCE IN SPORTS & EXERCISE
Volume 51, Issue 7, Pages 1538-1557Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1249/MSS.0000000000001947
Keywords
WEARABLES; POLYSOMNOGRAPHY; VALIDATION; ACTIGRAPHY; DIGITAL HEALTH; SLEEP
Categories
Funding
- National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) [U01 AA021696]
- National Heart, Lung, and Blood Institute (NHLBI) [R01HL139652]
- Mobilize Center, a National Institutes of Health (NIH) Big Data to Knowledge Center of Excellence - NIH [U54 EB020405]
- University of Padua
- MIUR
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The accurate assessment of sleep is critical to better understand and evaluate its role in health and disease. The boom in wearable technology is part of the digital health revolution and is producing many novel, highly sophisticated and relatively inexpensive consumer devices collecting data from multiple sensors and claiming to extract information about users' behaviors, including sleep. These devices are now able to capture different biosignals for determining, for example, HR and its variability, skin conductance, and temperature, in addition to activity. They perform 24/7, generating overwhelmingly large data sets (big data), with the potential of offering an unprecedented window on users' health. Unfortunately, little guidance exists within and outside the scientific sleep community for their use, leading to confusion and controversy about their validity and application. The current state-of-the-art review aims to highlight use, validation and utility of consumer wearable sleep-trackers in clinical practice and research. Guidelines for a standardized assessment of device performance is deemed necessary, and several critical factors (proprietary algorithms, device malfunction, firmware updates) need to be considered before using these devices in clinical and sleep research protocols. Ultimately, wearable sleep technology holds promise for advancing understanding of sleep health; however, a careful path forward needs to be navigated, understanding the benefits and pitfalls of this technology as applied in sleep research and clinical sleep medicine.
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