Research Progress of Automatic Sleep Staging Based on Electroencephalogram Signals.
- Author:
Qunxia GAO
;
Jing ZHOU
;
Xiaoming WU
- Publication Type:Journal Article
- MeSH:
Electroencephalography;
Humans;
Neural Networks (Computer);
Sleep Stages;
Support Vector Machine;
Wavelet Analysis
- From:
Journal of Biomedical Engineering
2015;32(5):1155-1159
- CountryChina
- Language:Chinese
-
Abstract:
The research of sleep staging is not only a basis of diagnosing sleep related diseases but also the precondition of evaluating sleep quality, and has important clinical significance. In recent years, the research of automatic sleep staging based on computer has become a hot spot and got some achievements. The basic knowledge of sleep staging and electroencephalogram (EEG) is introduced in this paper. Then, feature extraction and pattern recognition, two key technologies for automatic sleep staging, are discussed in detail. Wavelet transform and Hilbert-Huang transform, two methods for feature extraction, are compared. Artificial neural network and support vector machine (SVM), two methods for pattern recognition are discussed. In the end, the research status of this field is summarized, and development trends of next phase are pointed out.
