Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions

被引:50
作者
Stone, Jason D. [1 ]
Rentz, Lauren E. [1 ]
Forsey, Jillian [1 ]
Ramadan, Jad [1 ]
Markwald, Rachel R. [2 ]
Finomore, Victor S., Jr. [1 ]
Galster, Scott M. [1 ]
Rezai, Ali [1 ]
Hagen, Joshua A. [1 ]
机构
[1] West Virginia Univ, Rockefeller Neurosci Inst, Morgantown, WV 26506 USA
[2] Naval Hlth Res Ctr, Sleep Tact Efficiency & Endurance Lab, Warfighter Performance Dept, San Diego, CA USA
来源
NATURE AND SCIENCE OF SLEEP | 2020年 / 12卷
关键词
wearables; consumer sleep technologies; sleep duration; sleep efficiency; sleep staging; AMERICAN ACADEMY; HEART-RATE; ACTIGRAPHY; POLYSOMNOGRAPHY; VARIABILITY; ACCURACY; MEDICINE; VALIDATION; STABILITY; VALIDITY;
D O I
10.2147/NSS.S270705
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Purpose: The commercial market is saturated with technologies that claim to collect proficient, free-living sleep measurements despite a severe lack of independent third-party evaluations. Therefore, the present study evaluated the accuracy of various commercial sleep technologies during in-home sleeping conditions. Materials and Methods: Data collection spanned 98 separate nights of ad libitum sleep from five healthy adults. Prior to bedtime, participants utilized nine popular sleep devices while concurrently wearing a previously validated electroencephalography (EEG)-based device. Data collected from the commercial devices were extracted for later comparison against EEG to determine degrees of accuracy. Sleep and wake summary outcomes as well as sleep staging metrics were evaluated, where available, for each device. Results: Total sleep time (TST), total wake time (TWT), and sleep efficiency (SE) were measured with greater accuracy (lower percent errors) and limited bias by Fitbit Ionic [mean absolute percent error, bias (95% confidence interval); TST: 9.90%, 0.25 (-0.11, 0.61); TWT: 25.64%, -0.17 (-0.28, -0.06); SE: 3.49%, 0.65 (-0.82, 2.12)] and Oura smart ring [TST: 7.39%, 0.19 (0.04, 0.35); TWT: 36.29%, -0.18 (-0.31, -0.04); SE: 5.42%, 1.66 (0.17, 3.15)], whereas all other devices demonstrated a propensity to over or underestimate at least one if not all of the aforementioned sleep metrics. No commercial sleep technology appeared to accurately quantify sleep stages. Conclusion: Generally speaking, commercial sleep technologies displayed lower error and bias values when quantifying sleep/wake states as compared to sleep staging durations. Still, these findings revealed that there is a remarkably high degree of variability in the accuracy of commercial sleep technologies, which further emphasizes that continuous evaluations of newly developed sleep technologies are vital. End-users may then be able to determine more accurately which sleep device is most suited for their desired application(s).
引用
收藏
页码:821 / 842
页数:22
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