title: An E-health solution for automatic sleep classification according to Rechtschaffen and Kales: validation study of the Somnolyzer 24 x 7 utilizing the Siesta database.
abstract: To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It 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 (Somnolyzer 24 x 7) 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, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20-95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen's kappa: 0.72) between the Somnolyzer 24 x 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 x 7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 x 7 and demonstrated its applicability in clinical routine and sleep studies.
authors.affiliation: Department of Psychiatry, Medical University of Vienna, Vienna, Austria. peter.anderer@meduniwien.ac.at
authors.forename: Peter
authors.initials: P
authors.lastname: Anderer
authors.forename: Georg
authors.initials: G
authors.lastname: Gruber
authors.forename: Silvia
authors.initials: S
authors.lastname: Parapatics
authors.forename: Michael
authors.initials: M
authors.lastname: Woertz
authors.forename: Tatiana
authors.initials: T
authors.lastname: Miazhynskaia
authors.forename: Gerhard
authors.initials: G
authors.lastname: Klosch
authors.forename: Bernd
authors.initials: B
authors.lastname: Saletu
authors.forename: Josef
authors.initials: J
authors.lastname: Zeitlhofer
authors.forename: Manuel J
authors.initials: MJ
authors.lastname: Barbanoj
authors.forename: Heidi
authors.initials: H
authors.lastname: Danker-Hopfe
authors.forename: Sari-Leena
authors.initials: SL
authors.lastname: Himanen
authors.forename: Bob
authors.initials: B
authors.lastname: Kemp
authors.forename: Thomas
authors.initials: T
authors.lastname: Penzel
authors.forename: Michael
authors.initials: M
authors.lastname: Grozinger
authors.forename: Dieter
authors.initials: D
authors.lastname: Kunz
authors.forename: Peter
authors.initials: P
authors.lastname: Rappelsberger
authors.forename: Alois
authors.initials: A
authors.lastname: Schlogl
authors.forename: Georg
authors.initials: G
authors.lastname: Dorffner
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D016022:Case-Control Studies; D019992:Databases as Topic; D003663:Decision Trees; D004569:Electroencephalography / Q000379:methods; D004576:Electromyography / Q000379:methods; D001330:Electronic Data Processing; D004585:Electrooculography / Q000379:methods; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D017286:Polysomnography / Q000379:methods; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D012890:Sleep / Q000502:physiology*; D012893:Sleep Wake Disorders / Q000145:classification / Q000175:diagnosis* / Q000503:physiopathology*; D013997:Time Factors; D014851:Wakefulness / Q000502:physiology