Semi-automatic sleep EEG scoring based on the hypnospectrogram.
BACKGROUND
Sleep EEG organization is revealed by sleep scoring, a time-consuming process based on strictly defined visual criteria.


METHODS
We explore the possibility of sleep scoring using the whole-night time-frequency analysis, termed hypnospectrogram, with a computer-assisted K-means clustering method.


RESULTS
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.


METHODS
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.


CONCLUSIONS
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.
Andreas M
AM
Koupparis
Vasileios
V
Kokkinos
George K
GK
Kostopoulos
D000328:Adult; D001331:Automation; D016000:Cluster Analysis; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D017286:Polysomnography / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D012890:Sleep / Q000502:physiology*; D055815:Young Adult