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• W2135280991 startingPage "1587" @default.
• W2135280991 abstract "To assess the performance of automatic sleep scoring software (ASEEGA) based on a single EEG channel comparatively with manual scoring (2 experts) of conventional full polysomnograms. Polysomnograms from 15 healthy individuals were scored by 2 independent experts using conventional R&K rules. The results were compared to those of ASEEGA scoring on an epoch-by-epoch basis. Sleep laboratory in the physiology department of a teaching hospital. Fifteen healthy volunteers. The epoch-by-epoch comparison was based on classifying into 2 states (wake/sleep), 3 states (wake/REM/NREM), 4 states (wake/REM/stages 1–2/SWS), or 5 states (wake/REM/stage 1/stage 2/SWS). The obtained overall agreements, as quantified by the kappa coefficient, were 0.82, 0.81, 0.75, and 0.72, respectively. Furthermore, obtained agreements between ASEEGA and the expert consensual scoring were 96.0%, 92.1%, 84.9%, and 82.9%, respectively. Finally, when classifying into 5 states, the sensitivity and positive predictive value of ASEEGA regarding wakefulness were 82.5% and 89.7%, respectively. Similarly, sensitivity and positive predictive value regarding REM state were 83.0% and 89.1%. Our results establish the face validity and convergent validity of ASEEGA for single-channel sleep analysis in healthy individuals. ASEEGA appears as a good candidate for diagnostic aid and automatic ambulant scoring." @default.
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• W2135280991 date "2007-11-01" @default.
• W2135280991 modified "2023-10-16" @default.
• W2135280991 title "Automatic Analysis of Single-Channel Sleep EEG: Validation in Healthy Individuals" @default.
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• W2135280991 doi "https://doi.org/10.1093/sleep/30.11.1587" @default.
• W2135280991 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2082104" @default.
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