Performance of consumer wrist-worn sleep tracking devices compared to polysomnography: a meta-analysis

Abstract

Study objectives: The use of sleep tracking devices is increasing as people become more aware of the importance of sleep and interested in monitoring their patterns. With many devices on the market, we conducted a meta-analysis comparing sleep scoring data from consumer wrist-worn sleep tracking devices with polysomnography to validate the accuracy of these devices.

Methods: We retrieved studies from the databases of SCOPUS, EMBASE, Cochrane Library, PubMed, Web of Science, and KoreaMed and OVID Medline up to March 2024. We compared personal data about participants and information on objective sleep parameters.

Results: From 24 studies, data of 798 patient using Fitbit, Jawbone, myCadian watch, WHOOP strap, Garmin, Basis B1, Zulu Watch, Huami Arc, E4 wristband, Fatigue Science Readiband, Apple Watch, or Xiaomi Mi Band 5 were analyzed. There were significant differences in total sleep time (mean difference, -16.854; 95% confidence interval, [-26.332; -7.375]), sleep efficiency (mean difference, -4.691; 95% confidence interval, [-7.079; -2.302]), sleep latency (mean difference, 2.574; 95% confidence interval, [0.606; 4.542]), and wake after sleep onset (mean difference, 13.255; 95% confidence interval, [4.522; 21.988]) between all consumer sleep tracking devices and polysomnography. In subgroup analysis, there was no significant difference in wake after sleep onset between Fitbit and polysomnography. There was also no significant difference in sleep latency between other devices and polysomnography. Fitbit measured sleep latency longer than other devices, and other devices measured wake after sleep onset longer. Based on Begg and Egger's test, there was no publication bias in total sleep time and sleep efficiency.

Conclusions: Wrist-worn sleep tracking devices, although popular, are not as reliable as polysomnography in measuring key sleep parameters such as total sleep time, sleep efficiency, and sleep latency. Physicians and consumers should be aware of their limitations and interpret results carefully, though they can still be useful for tracking general sleep patterns. Further improvements and clinical studies are needed to enhance their accuracy.

Citation: Lee YJ, Lee JY, Cho JH, Kang YJ, Choi JH. Performance of consumer wrist-worn sleep tracking devices compared to polysomnography: a meta-analysis. J Clin Sleep Med. 2025;21(3):573-582.

Keywords: consumer sleep tracking device; polysomnography; sleep scoring data.