Abstract
Conventionally, polysomnographic recordings are classified according to the rules published in 1968 by Rechtschaffen and Kales (R&K). The present paper describes an automatic classification system embedded in an e-health solution that has been developed and validated in a large database of healthy controls and sleep disturbed patients. The Somnolyzer 24x7 adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, slow and rapid eye movements), a feature matrix plausibility check, a classifier designed as an expert system and a rule-based smoothing procedure for the start and the end of stages REM and 2. The validation based on 286 recordings in both normal healthy subjects aged 20 to 95 years and patients suffering from organic or nonorganic sleep disorders demonstrated an overall epoch-by-epoch agreement of 80% (Cohen's Kappa: 0.72) between the Somnolyzer 24x7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's Kappa: 0.68) between two human experts. Two Somnolyzer 24x7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's Kappa: 0.991). Moreover, correlation analysis in R&K derived target variables revealed similar -- in 36 out of 38 variables even higher -- relationships between Somnolyzer 24x7 and expert evaluations as compared to the concordance between two human experts. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24x7 both, on the epoch-by-epoch and on the target variable level. These results demonstrate the applicability of the Somnolyzer 24x7 evaluation in clinical routine and sleep studies.
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