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在无肌张力缺失的受试者中自动检测快速眼动睡眠。

Automatic detection of REM sleep in subjects without atonia.

作者信息

Kempfner Jacob, Jennum Poul, Nikolic Miki, Christensen Julie A E, Sorensen Helge B D

机构信息

Department of Electrical Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:4242-5. doi: 10.1109/EMBC.2012.6346903.

Abstract

Idiopathic Rapid-Rye-Movement (REM) sleep Behavior Disorder (iRBD) is a strong early marker of Parkinson's Disease and is characterized by REM sleep without atonia (RSWA) and increased phasic muscle activity. Current proposed methods for detecting RSWA assume the presence of a manually scored hypnogram. In this study a full automatic REM sleep detector, using the EOG and EEG channels, is proposed. Based on statistical features, combined with subject specific feature scaling and post-processing of the classifier output, it was possible to obtain an mean accuracy of 0.96 with a mean sensitivity and specificity of 0.94 and 0.96 respectively.

摘要

特发性快速眼动(REM)睡眠行为障碍(iRBD)是帕金森病的一个重要早期标志物,其特征是快速眼动睡眠时无肌张力减退(RSWA)且肌阵挛活动增加。目前用于检测RSWA的方法都假定存在手动评分的睡眠图。在本研究中,我们提出了一种使用眼电图(EOG)和脑电图(EEG)通道的全自动快速眼动睡眠检测器。基于统计特征,结合个体特征缩放和分类器输出的后处理,我们分别获得了平均准确率0.96,平均敏感度0.94和平均特异度0.96。

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