Validity of Consumer Activity Wristbands and Wearable EEG for Measuring Overall Sleep Parameters and Sleep Structure in Free-Living Conditions
Validity of Consumer Activity Wristbands and Wearable EEG for Measuring Overall Sleep Parameters and Sleep Structure in Free-Living Conditions
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DOI：
10.1007/s41666-018-0013-1
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发表时间：
2018-06-01
影响因子：
5.9
通讯作者：
Martell, Mario Alberto Chapa
中科院分区：
文献类型：
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作者：
Liang, Zilu;Martell, Mario Alberto Chapa
消费者睡眠跟踪技术提供了一种在自由生活条件下监测睡眠的不显眼且经济有效的方法。硬件和软件的技术进步大大提高了最近出现在市场上的新产品的功能。然而，最新的设备能否提供全面的睡眠参数和睡眠结构（如深度睡眠和快速眼动睡眠）的有效测量还没有得到检验。在这项研究中，我们旨在调查最新的消费者睡眠跟踪设备（包括活动腕带Fitbit Charge 2和基于脑电图的可穿戴眼罩Neuroon）与医疗睡眠监测仪的有效性。首先，我们确认Fitbit Charge 2可以以合理的精度自动检测睡眠的开始和偏移。其次，分析发现，与医疗设备相比，两种消费设备在测量总睡眠时间和睡眠效率方面产生了相似的结果。此外，Fitbit能够准确测量觉醒次数，而信号质量好的Neuroon在总清醒时间和睡眠发作潜伏期方面表现令人满意。然而，测量睡眠结构（包括浅睡眠、深度睡眠和快速眼动睡眠）对这两种消费设备来说仍然是一个挑战。第三，在睡眠更中断的夜晚和信号质量较差时，Neuroon和医疗设备之间的差异更大，但在Fitbit Charge 2中没有观察到这种趋势。这项研究表明，目前的消费者睡眠跟踪技术在诊断睡眠障碍方面可能还不成熟，但它们在一般用途和非临床用途方面是相当令人满意的。
Consumer sleep tracking technologies offer an unobtrusive and cost-efficient way to monitor sleep in free-living conditions. Technological advances in hardware and software have significantly improved the functionality of the new gadgets that recently appeared in the market. However, whether the latest gadgets can provide valid measurements on overall sleep parameters and sleep structure such as deep and REM sleep has not been examined. In this study, we aimed to investigate the validity of the latest consumer sleep tracking devices including an activity wristband Fitbit Charge 2 and a wearable EEG-based eye mask Neuroon in comparison to a medical sleep monitor. First, we confirmed that Fitbit Charge 2 can automatically detect the onset and offset of sleep with reasonable accuracy. Second, analysis found that both consumer devices produced comparable results in measuring total sleep duration and sleep efficiency compared to the medical device. In addition, Fitbit accurately measured the number of awakenings, while Neuroon with good signal quality had satisfactory performance on total awake time and sleep onset latency. However, measuring sleep structure including light, deep, and REM sleep remains to be challenging for both consumer devices. Third, greater discrepancies were observed between Neuroon and the medical device in nights with more disrupted sleep and when the signal quality was poor, but no trend was observed in Fitbit Charge 2. This study suggests that current consumer sleep tracking technologies may be immature for diagnosing sleep disorders, but they are reasonably satisfactory for general purpose and non-clinical use.