title: A rule-based automatic sleep staging method.
abstract: In this paper, a rule-based automatic sleep staging method was proposed. Twelve features, including temporal and spectrum analyses of the EEG, EOG, and EMG signals, were utilized. Normalization was applied to each feature to reduce the effect of individual variability. A hierarchical decision tree, with fourteen rules, was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The average accuracy and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of twenty subjects compared with the manual scorings reached 86.5% and 0.78, respectively. This method can assist the clinical staff reduce the time required for sleep scoring in the future.
authors.affiliation: Department of Computer Science and Information Engineering & the Institute of Medical Informatics, National Cheng Kung University, Tainan 701, Taiwan. sfliang@mail.ncku.edu.tw
authors.forename: Sheng-Fu
authors.initials: SF
authors.lastname: Liang
authors.forename: Chih-En
authors.initials: CE
authors.lastname: Kuo
authors.forename: Yu-Han
authors.initials: YH
authors.lastname: Hu
authors.forename: Yu-Shian
authors.initials: YS
authors.lastname: Cheng
mesh_terms: D000465:Algorithms; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D004569:Electroencephalography / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D004585:Electrooculography / Q000379:methods*; D006801:Humans; D008297:Male; D017286:Polysomnography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012894:Sleep Stages / Q000502:physiology*; D055815:Young Adult