Abstract
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.
Published Version
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