可穿戴计算机
多导睡眠图
奇纳
计算机科学
脑电图
梅德林
睡眠(系统调用)
人口
医学
生物信号
精神科
嵌入式系统
操作系统
电信
环境卫生
政治学
法学
无线
作者
C.J. de Gans,P. C. Burger,Eva S. van den Ende,Jeroen Hermanides,Pwb Nanayakkara,R. J. B. J. Gemke,Femke Rutters,Dirk Jan Stenvers
标识
DOI:10.1016/j.smrv.2024.101951
摘要
Polysomnography (PSG) is the reference standard of sleep measurement, but is burdensome for the participant and labor intensive. Affordable electroencephalography (EEG)-based wearables are easy to use and are gaining popularity, yet selecting the most suitable device is a challenge for clinicians and researchers. In this systematic review, we aim to provide a comprehensive overview of available EEG-based wearables to measure human sleep. For each wearable, an overview will be provided regarding validated population and reported measurement properties. A systematic search was conducted in the databases OVID MEDLINE, Embase.com and CINAHL. A machine learning algorithm (ASReview) was utilized to screen titles and abstracts for eligibility. In total, 60 papers were selected, covering 34 unique EEG-based wearables. Feasibility studies indicated good tolerance, high compliance, and success rates. The 42 included validation studies were conducted across diverse populations and showed consistently high accuracy in sleep staging detection. Therefore, the recent advancements in EEG-based wearables show great promise as alternative for PSG and for at-home sleep monitoring. Users should consider factors like user-friendliness, comfort, and costs, as these devices vary in features and pricing, impacting their suitability for individual needs.
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