A rule-based automatic sleep staging method

Sheng Fu Liang, Chin En Kuo, Yu Han Hu, Yu Shian Cheng

Research output: Contribution to journalArticlepeer-review

75 Citations (Scopus)

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 eliminating individual differences. 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 overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future.

Original languageEnglish
Pages (from-to)169-176
Number of pages8
JournalJournal of Neuroscience Methods
Volume205
Issue number1
DOIs
Publication statusPublished - 2012 Mar 30

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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