Accuracy of Fitbit Wristbands in Measuring Sleep Stage Transitions and the Effect of User-Specific Factors
Accuracy of Fitbit Wristbands in Measuring Sleep Stage Transitions and the Effect of User-Specific Factors
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DOI：
10.2196/13384
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发表时间：
2019-06-06
影响因子：
5
通讯作者：
Chapa-Martell, Mario Alberto
中科院分区：
文献类型：
--
作者：
Liang, Zilu;Chapa-Martell, Mario Alberto
背景：新一代消费者腕带已经可以根据多传感器数据对睡眠阶段进行分类。几项研究已经验证了最新型号之一，即Fitbit Charge 2在测量多导睡眠参数方面的准确性，包括总睡眠时间，唤醒时间，睡眠效率（SE）以及每个睡眠阶段的比例。然而，其测量睡眠阶段转换的准确性仍然未知。目的：本研究旨在检查Fitbit Charge 2在自由生活条件下测量清醒、浅睡眠、深睡眠和快速眼动（REM）睡眠之间转换概率的准确性。第二个目标是调查用户特定因素的影响，包括人口统计信息和睡眠模式对测量准确性的影响。方法：同时使用Fitbit Charge 2和医疗设备来测量参与者家中的整晚睡眠。睡眠阶段转换概率来自睡眠催眠图。通过比较Fitbit获得的数据与医疗器械获得的数据，获得测量误差。使用配对双尾t检验和Bland-Altman图检查Fitbit与医疗器械的一致性。进行Wilcoxon符号秩检验来调查用户特定因素的影响。结果：从23名参与者那里收集了睡眠数据。Fitbit Charge 2测量的睡眠阶段转换概率与医疗设备测量的睡眠阶段转换概率显著偏离，除了从深睡眠到清醒的转换概率，从浅睡眠到REM睡眠的转换概率，以及停留在REM睡眠的概率。Bland-Altman图显示系统偏倚范围为0%-60%。Fitbit倾向于高估停留在睡眠阶段的概率，而低估过渡到另一个阶段的概率。SE> 90%（P = 0.047）与测量误差显著增加相关。匹兹堡睡眠质量指数（PSQI）
Background: It has become possible for the new generation of consumer wristbands to classify sleep stages based on multisensory data. Several studies have validated the accuracy of one of the latest models, that is, Fitbit Charge 2, in measuring polysomnographic parameters, including total sleep time, wake time, sleep efficiency (SE), and the ratio of each sleep stage. Nevertheless, its accuracy in measuring sleep stage transitions remains unknown.Objective: This study aimed to examine the accuracy of Fitbit Charge 2 in measuring transition probabilities among wake, light sleep, deep sleep, and rapid eye movement (REM) sleep under free-living conditions. The secondary goal was to investigate the effect of user-specific factors, including demographic information and sleep pattern on measurement accuracy.Methods: A Fitbit Charge 2 and a medical device were used concurrently to measure a whole night's sleep in participants' homes. Sleep stage transition probabilities were derived from sleep hypnograms. Measurement errors were obtained by comparing the data obtained by Fitbit with those obtained by the medical device. Paired 2-tailed t test and Bland-Altman plots were used to examine the agreement of Fitbit to the medical device. Wilcoxon signed-rank test was performed to investigate the effect of user-specific factors.Results: Sleep data were collected from 23 participants. Sleep stage transition probabilities measured by Fitbit Charge 2 significantly deviated from those measured by the medical device, except for the transition probability from deep sleep to wake, from light sleep to REM sleep, and the probability of staying in REM sleep. Bland-Altman plots demonstrated that systematic bias ranged from 0% to 60%. Fitbit had the tendency of overestimating the probability of staying in a sleep stage while underestimating the probability of transiting to another stage. SE>90% (P=.047) was associated with significant increase in measurement error. Pittsburgh sleep quality index (PSQI)