Sleep Recording is important for clinical diagnosis and treatment of sleep disorders. Sleep staging is one of the most important steps in sleep analysis and is typically performed based on the characteristics of electrophysiological signals including EEG, EOG, and EMG. Normal healthy sleep consists of sequences of stages. According to the traditional Rechtschaffen & Kales (R&K) rules, these stages include: Awake, Light Sleep, Deep Sleep, and Rapid-Eye Movement (REM) Sleep.
Our study develops a simple four-stage process to classify sleep into wakefulness, stage 1, stage 2, slow wave sleep (SWS) and rapid eye movement (REM) sleep based on single LEOG channel. To achieve this goal, this study first generates feature variables from LEOG signal. The proposed feature selection method is applied to select a subset of features to improve the accuracy of the classifier. By applying the proposed approach to 48727 distinct LEOG epochs that are obtained from 62 subjects, the accuracy rate is about 72.6%. The largest amount of errors occurs in the identification of Stage 1, 56.3% of which was misclassified into stages 2 or wake. The second largest error is associated with REM sleep, 23.7% of which was misclassified into stages 2.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0715109-164853 |
| Date | 15 July 2009 |
| Creators | Wang, Wen-yen |
| Contributors | Chen-Wen Yen, Kang-Ming Chang, Liang-Wen Hang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0715109-164853 |
| Rights | unrestricted, Copyright information available at source archive |
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