Application of complexity sequence in sleep staging based on sleep EEG data.
- Author:
Fei LONG
1
;
Daoxin ZHANG
;
Ling FAN
;
Xiaopei WU
;
Huanqing FENG
Author Information
1. Intelligent Computing & Signal Processing Key Laboratory of Ministry of Education, Anhui University, Hefei 230039.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Brain;
physiology;
Electroencephalography;
Fourier Analysis;
Humans;
Nonlinear Dynamics;
Signal Processing, Computer-Assisted;
Sleep Stages;
physiology
- From:
Journal of Biomedical Engineering
2003;20(1):60-63
- CountryChina
- Language:Chinese
-
Abstract:
In this paper an approach of time-window complexity sequence is applied to sleep EEG analysis. This approach can reduce the loss of state information due to the nonstationarity of EEG signal and the unevenness of state space, and can overcome certain limitations of the complexity itself to some extent. It will help to extract the state features of EEG in different sleep stages. In addition, we preprocess EEG by adopting ICA and wavelet transform (WT). The results show that some physiological artifact in EEG can be eliminated effectively by these methods, and the sleep staging based on sleep EEG data will be more exact.
