J Neurosci Methods. 2014 Jan 15;221:189-95.
Sleep EEG organization is revealed by sleep scoring, a time-consuming process based on strictly defined visual criteria.
We explore the possibility of sleep scoring using the whole-night time-frequency analysis, termed hypnospectrogram, with a computer-assisted K-means clustering method.
Hypnograms were derived from 10 whole-night sleep EEG recordings using either standard visual scoring under the Rechtshaffen and Kales criteria or semi-automated analysis of the hypnospectrogram derived from a single EEG electrode. We measured substantial agreement between the two approaches with Cohen's kappa considering all 7 stages at 0.61.
A number of existing automated procedures have reached the level of human inter-rater agreement using the standard criteria. However, our approach offers the scorer the opportunity to exploit the information-rich graphic representation of the whole night sleep upon which the automated method works.
This work suggests that the hypnospectrogram can be used as an objective graphical rep-resentation of sleep architecture upon which sleep scoring can be performed with computer-assisted methods.
睡眠脑电图的组织通过睡眠评分来揭示，这是一个基于严格定义的视觉标准的耗时过程。
我们探索了使用全夜时频分析（称为睡眠频谱图）和计算机辅助 K-均值聚类方法进行睡眠评分的可能性。
使用 Rechtshaffen 和 Kales 标准下的标准视觉评分或单个脑电图电极衍生的睡眠频谱图的半自动分析，从 10 个全夜睡眠 EEG 记录中得出了睡眠图。我们考虑所有 7 个阶段，用 Cohen 的 kappa 测量两种方法之间的高度一致性，kappa 值为 0.61。
许多现有的自动化程序已经使用标准标准达到了人类评分者之间的一致性水平。然而，我们的方法为评分者提供了利用自动化方法所依据的整个夜间睡眠的信息丰富的图形表示的机会。
这项工作表明，睡眠频谱图可以用作睡眠结构的客观图形表示，通过计算机辅助方法可以进行睡眠评分。
