Lee Young Jeong, Lee Jae Yong, Cho Jae Hoon, Kang Yun Jin, Choi Ji Ho
Department of Otorhinolaryngology-Head and Neck Surgery, Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon, Republic of Korea.
Department of Otorhinolaryngology-Head and Neck Surgery, Konkuk University School of Medicine, Seoul, Republic of Korea.
J Clin Sleep Med. 2025 Mar 1;21(3):573-582. doi: 10.5664/jcsm.11460.
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.
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.
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.
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.
Lee YJ, Lee JY, Cho JH, Kang YJ, Choi JH. Performance of consumer wrist-worn sleep tracking devices compared to polysomnography: a meta-analysis. 2025;21(3):573-582.
随着人们越来越意识到睡眠的重要性并对监测自己的睡眠模式感兴趣，睡眠追踪设备的使用正在增加。市场上有许多此类设备，我们进行了一项荟萃分析，将消费者佩戴在手腕上的睡眠追踪设备的睡眠评分数据与多导睡眠图进行比较，以验证这些设备的准确性。
我们检索了截至2024年3月的SCOPUS、EMBASE、Cochrane图书馆、PubMed、Web of Science、KoreaMed和OVID Medline数据库中的研究。我们比较了参与者的个人数据和客观睡眠参数信息。
从24项研究中，分析了使用Fitbit、Jawbone、myCadian手表、WHOOP腕带、Garmin、Basis B1、Zulu手表、Huami Arc、E4腕带、Fatigue Science Readiband、Apple Watch或小米手环5的798名患者的数据。在总睡眠时间（平均差，-16.854；95%置信区间，[-26.332；-7.375]）、睡眠效率（平均差，-4.691；95%置信区间，[-7.079；-2.302]）、睡眠潜伏期（平均差，2.574；95%置信区间，[0.606；4.542]）以及睡眠开始后的觉醒时间（平均差，13.255；95%置信区间，[4.522；21.988]）方面，所有消费者睡眠追踪设备与多导睡眠图之间存在显著差异。在亚组分析中，Fitbit与多导睡眠图在睡眠开始后的觉醒时间方面无显著差异。其他设备与多导睡眠图在睡眠潜伏期方面也无显著差异。Fitbit测量的睡眠潜伏期比其他设备长，其他设备测量的睡眠开始后的觉醒时间长。根据Begg和Egger检验，在总睡眠时间和睡眠效率方面不存在发表偏倚。
手腕佩戴式睡眠追踪设备虽然很受欢迎，但在测量总睡眠时间、睡眠效率和睡眠潜伏期等关键睡眠参数方面不如多导睡眠图可靠。医生和消费者应意识到其局限性并谨慎解读结果，不过它们在追踪一般睡眠模式方面仍可能有用。需要进一步改进和进行临床研究以提高其准确性。
Lee YJ, Lee JY, Cho JH, Kang YJ, Choi JH. 消费者手腕佩戴式睡眠追踪设备与多导睡眠图的性能比较：一项荟萃分析。2025；21(3):573 - 582。
