Department of Internal Medicine, Section General Internal Medicine Unit Acute Medicine, Amsterdam University Medical Center, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Amsterdam Public Health Research Institute, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Department of Pediatrics, Emma Children's Hospital, Amsterdam University Medical Center, Amsterdam, the Netherlands; Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands.
Sleep Med Rev. 2024 Aug;76:101951. doi: 10.1016/j.smrv.2024.101951. Epub 2024 May 7.
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.
多导睡眠图（PSG）是睡眠测量的参考标准，但对参与者来说负担很重，且劳动强度大。价格合理的基于脑电图（EEG）的可穿戴设备易于使用，越来越受欢迎，但对于临床医生和研究人员来说，选择最合适的设备是一个挑战。在这项系统评价中，我们旨在全面概述可用于测量人类睡眠的基于 EEG 的可穿戴设备。对于每个可穿戴设备，将提供有关经过验证的人群和报告的测量特性的概述。在 OVID MEDLINE、Embase.com 和 CINAHL 数据库中进行了系统搜索。使用机器学习算法（ASReview）筛选标题和摘要以确定其是否符合入选标准。总共选择了 60 篇论文，涵盖了 34 种独特的基于 EEG 的可穿戴设备。可行性研究表明，这些设备具有良好的耐受性、高顺应性和成功率。42 项包含验证研究的研究跨越了不同的人群，并一致显示出在睡眠分期检测方面的高准确性。因此，基于 EEG 的可穿戴设备的最新进展显示出作为 PSG 和家庭睡眠监测替代方案的巨大潜力。用户应考虑用户友好性、舒适度和成本等因素，因为这些设备在功能和价格上存在差异，这会影响它们对个人需求的适用性。
