Department of Neurology, Inselspital, University Hospital, Bern, Switzerland.
Department of Health Sciences and Technology, Sensory-Motor System Lab, Institute of Robotics and Intelligent Systems, ETH Zurich, Switzerland and.
Sleep. 2023 Jun 13;46(6). doi: 10.1093/sleep/zsad030.
Isolated rapid eye movement sleep behavior disorder (iRBD) is a parasomnia characterized by dream enactment. It represents a prodromal state of α-synucleinopathies, like Parkinson's disease. In recent years, biomarkers of increased risk of phenoconversion from iRBD to overt α-synucleinopathies have been identified. Currently, diagnosis and monitoring rely on self-reported reports and polysomnography (PSG) performed in the sleep lab, which is limited in availability and cost-intensive. Wearable technologies and computerized algorithms may provide comfortable and cost-efficient means to not only improve the identification of patients with iRBD but also to monitor risk factors of phenoconversion. In this work, we review studies using these technologies to identify iRBD or monitor phenoconversion biomarkers.
A review of articles published until May 31, 2022 using the Medline database was performed. We included only papers in which participants with RBD were part of the study population. The selected papers were divided into four sessions: actigraphy, gait analysis systems, computerized algorithms, and novel technologies.
In total, 25 articles were included in the review. Actigraphy, wearable accelerometers, pressure mats, smartphones, tablets, and algorithms based on PSG signals were used to identify RBD and monitor the phenoconversion. Rest-activity patterns, core body temperature, gait, and sleep parameters were able to identify the different stages of the disease.
These tools may complement current diagnostic systems in the future, providing objective ambulatory data obtained comfortably and inexpensively. Consequently, screening for iRBD and follow-up will be more accessible for the concerned patient cohort.
孤立性快速眼动睡眠行为障碍(iRBD)是一种以梦境演化为特征的睡眠障碍。它代表了α-突触核蛋白病(如帕金森病)的前驱状态。近年来,已经确定了 iRBD 向显性 α-突触核蛋白病转化的风险增加的生物标志物。目前,诊断和监测依赖于自我报告的报告和在睡眠实验室进行的多导睡眠图(PSG),这在可用性和成本方面都受到限制。可穿戴技术和计算机算法可能为识别 iRBD 患者提供舒适且具有成本效益的手段,也可能为监测表型转化的风险因素提供便利。在这项工作中,我们综述了使用这些技术来识别 iRBD 或监测表型转化生物标志物的研究。
使用 Medline 数据库对截至 2022 年 5 月 31 日发表的文章进行了回顾。我们仅纳入了参与者属于研究人群的 RBD 研究。所选论文分为四个部分:运动描记术、步态分析系统、计算机算法和新技术。
共有 25 篇文章纳入综述。使用运动描记术、可穿戴加速度计、压力垫、智能手机、平板电脑和基于 PSG 信号的算法来识别 RBD 和监测表型转化。静息-活动模式、核心体温、步态和睡眠参数能够识别疾病的不同阶段。
这些工具未来可能会补充现有的诊断系统,提供舒适且经济的可移动客观数据。因此,iRBD 的筛查和随访将更容易被关注的患者群体接受。