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快速眼动睡眠行为障碍中运动活动自动量化分析

Analysis of automated quantification of motor activity in REM sleep behaviour disorder.

作者信息

Frandsen Rune, Nikolic Miki, Zoetmulder Marielle, Kempfner Lykke, Jennum Poul

机构信息

Danish Centre for Sleep Medicine, Department of Clinical Neurophysiology, Glostrup Hospital, Copenhagen, Denmark.

Faculty of Health Sciences, University of Copenhagen, Glostrup Hospital, Copenhagen, Denmark.

出版信息

J Sleep Res. 2015 Oct;24(5):583-90. doi: 10.1111/jsr.12304. Epub 2015 Apr 29.

Abstract

Rapid eye movement (REM) sleep behaviour disorder (RBD) is characterized by dream enactment and REM sleep without atonia. Atonia is evaluated on the basis of visual criteria, but there is a need for more objective, quantitative measurements. We aimed to define and optimize a method for establishing baseline and all other parameters in automatic quantifying submental motor activity during REM sleep. We analysed the electromyographic activity of the submental muscle in polysomnographs of 29 patients with idiopathic RBD (iRBD), 29 controls and 43 Parkinson's (PD) patients. Six adjustable parameters for motor activity were defined. Motor activity was detected and quantified automatically. The optimal parameters for separating RBD patients from controls were investigated by identifying the greatest area under the receiver operating curve from a total of 648 possible combinations. The optimal parameters were validated on PD patients. Automatic baseline estimation improved characterization of atonia during REM sleep, as it eliminates inter/intra-observer variability and can be standardized across diagnostic centres. We found an optimized method for quantifying motor activity during REM sleep. The method was stable and can be used to differentiate RBD from controls and to quantify motor activity during REM sleep in patients with neurodegeneration. No control had more than 30% of REM sleep with increased motor activity; patients with known RBD had as low activity as 4.5%. We developed and applied a sensitive, quantitative, automatic algorithm to evaluate loss of atonia in RBD patients.

摘要

快速眼动(REM)睡眠行为障碍(RBD)的特征是梦境演绎和REM睡眠时无肌张力减退。肌张力减退是根据视觉标准进行评估的,但需要更客观、定量的测量方法。我们旨在定义并优化一种方法,用于在REM睡眠期间自动量化颏下运动活动时建立基线及所有其他参数。我们分析了29例特发性RBD(iRBD)患者、29例对照者和43例帕金森病(PD)患者多导睡眠图中颏下肌肉的肌电活动。定义了六个可调节的运动活动参数。对运动活动进行自动检测和量化。通过从总共648种可能的组合中识别出最大的受试者工作曲线下面积,研究了将RBD患者与对照者区分开的最佳参数。在PD患者中对最佳参数进行了验证。自动基线估计改善了REM睡眠期间肌张力减退的特征描述,因为它消除了观察者间/观察者内的变异性,并且可以在各诊断中心进行标准化。我们找到了一种优化的方法来量化REM睡眠期间的运动活动。该方法稳定,可用于区分RBD与对照者,并量化神经退行性疾病患者REM睡眠期间的运动活动。没有对照者的REM睡眠中有超过30%的运动活动增加;已知患有RBD的患者运动活动低至4.5%。我们开发并应用了一种灵敏、定量、自动的算法来评估RBD患者的肌张力减退情况。

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