A validation study of Fitbit Charge 2â„¢ compared with polysomnography in adults
A validation study of Fitbit Charge 2â„¢ compared with polysomnography in adults
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DOI：
10.1080/07420528.2017.1413578
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发表时间：
2018-01-01
影响因子：
2.8
通讯作者：
Baker, Fiona C.
中科院分区：
文献类型：
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作者：
de Zambotti, Massimiliano;Goldstone, Aimee;Baker, Fiona C.
我们评估了消费者多感官腕带（Fitbit Charge 2（TM））与多导睡眠图（PSG）在测量健康成年人睡眠/觉醒状态和睡眠阶段组成方面的性能。实验室内PSG和Fitbit Charge 2（TM）数据来自SRI人类睡眠研究实验室对44名成年人（19-61岁; 26名女性; 25名高加索人）的单次过夜记录。参与者被筛选为没有精神和医疗状况。采用临床PSG评估睡眠障碍的存在。PSG结果表明，9名参与者的睡眠周期性肢体运动（PLMS，> 15/h），这些参与者与主要组（n = 35）分开分析。使用配对t检验、Bland-Altman图和逐时（EBE）分析比较PSG和Fitbit Charge 2（TM）睡眠数据。（检测睡眠的准确性），0.61特异性（检测唤醒的准确度），检测N1+N2睡眠的准确度为0.81在检测N3睡眠（“深度睡眠”）时的准确度为0.49，在检测快速眼动（REM）睡眠时的准确度为0.74。Fitbit Charge 2（TM）显著（p < 0.05）高估了PSG TST 9分钟，N1+N2睡眠34分钟，低估了PSG SOL 4分钟，N3睡眠24分钟。PSG和Fitbit Charge 2（TM）的结果在WASO和REM睡眠时间方面没有差异。不超过两名参与者的所有睡眠指标都超出了Bland-Altman协议的限制。Fitbit Charge 2（TM）正确识别了82%的PSG定义的非REM-REM睡眠周期。与金标准PSG相比，Fitbit Charge 2（TM）在检测睡眠-觉醒状态和睡眠阶段组成方面显示出了希望，特别是在估计REM睡眠方面，但在N3检测方面存在局限性。Fitbit Charge 2（TM）的准确性和可靠性需要在不同的环境（在家，多个夜晚）和不同的人群中进一步研究，其中睡眠成分已知会有所不同（青少年，老年人，睡眠障碍患者）。
We evaluated the performance of a consumer multi-sensory wristband (Fitbit Charge 2 (TM)), against polysomnography (PSG) in measuring sleep/wake state and sleep stage composition in healthy adults.In-lab PSG and Fitbit Charge 2 (TM) data were obtained from a single overnight recording at the SRI Human Sleep Research Laboratory in 44 adults (19-61 years; 26 women; 25 Caucasian). Participants were screened to be free from mental and medical conditions. Presence of sleep disorders was evaluated with clinical PSG. PSG findings indicated periodic limb movement of sleep (PLMS,> 15/h) in nine participants, who were analyzed separately from the main group (n = 35). PSG and Fitbit Charge 2 (TM) sleep data were compared using paired t-tests, Bland-Altman plots, and epoch-by-epoch (EBE) analysis.In the main group, Fitbit Charge 2 (TM) showed 0.96 sensitivity (accuracy to detect sleep), 0.61 specificity (accuracy to detect wake), 0.81 accuracy in detecting N1+N2 sleep ("light sleep"), 0.49 accuracy in detecting N3 sleep ("deep sleep"), and 0.74 accuracy in detecting rapid-eye-movement (REM) sleep. Fitbit Charge 2 (TM) significantly (p < 0.05) overestimated PSG TST by 9 min, N1+N2 sleep by 34 min, and underestimated PSG SOL by 4 min and N3 sleep by 24 min. PSG and Fitbit Charge 2 (TM) outcomes did not differ for WASO and time spent in REM sleep. No more than two participants fell outside the Bland-Altman agreement limits for all sleep measures. Fitbit Charge 2 (TM) correctly identified 82% of PSG-defined non-REM-REM sleep cycles across the night. Similar outcomes were found for the PLMS group.Fitbit Charge 2 (TM) shows promise in detecting sleep-wake states and sleep stage composition relative to gold standard PSG, particularly in the estimation of REM sleep, but with limitations in N3 detection. Fitbit Charge 2 (TM) accuracy and reliability need to be further investigated in different settings (at-home, multiple nights) and in different populations in which sleep composition is known to vary (adolescents, elderly, patients with sleep disorders).