Name
Title | ||
|---|---|---|
A hierarchical classification system for sleep stage scoring via forehead EEG signals |
Abstract | ||
|---|---|---|
The study adopts the structure of hierarchical classification to develop an automatic sleep stage classification system using forehead (Fpl and Fp2) EEG signals. The hierarchical classification consists of a preliminary wake detection rule, a novel feature extraction method based on American Academy of Sleep Medicine (AASM) scoring manual, feature selection methods and SVM. After estimating the preliminary sleep stages, two adaptive adjustment schemes are applied to adjust the preliminary sleep stages and provide the final estimation of sleep stages. Clinical testing reveals that the proposed automatic sleep stage classification system is about 77% accuracy and 67% kappa for individual 10 normal subjects. This system could provide the possibility of long term sleep monitoring at home and provide a preliminary result of sleep stages so that doctor could decide if a patient needs to have a detailed diagnosis using Polysomnography (PSG) system in a sleep laboratory of hospital. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/CCMB.2013.6609157 | CCMB |
Keywords | Field | DocType |
hierarchical classification,long term sleep monitoring,psg,automatic sleep stage classification system,sleep stage scoring,american academy of sleep medicine scoring manual,electroencephalography,sleep,clinical testing,hospitals,medical signal processing,polysomnography system,svm,hospital,sleep laboratory,signal classification,forehead eeg signals,hierarchical classification system,feature selection methods,polysomnography,aasm,support vector machines,feature extraction,accuracy | Forehead,Feature selection,Support vector machine,Sleep medicine,Speech recognition,Feature extraction,Medicine,Electroencephalography,Sleep Stages,Polysomnography | Conference |
Citations | PageRank | References |
3 | 0.50 | 7 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chih-Sheng Huang | 1 | 84 | 8.49 |
| Chun-Ling Lin | 2 | 64 | 7.50 |
| Li-Wei Ko | 3 | 519 | 58.70 |
| Shengyi Liu | 4 | 28 | 4.38 |
| Tung-Ping Su | 5 | 60 | 4.87 |
| Chin-Teng Lin | 6 | 3840 | 392.55 |