Application of wavelet entropy in EEG analysis
10.3760/cma.j.issn.1673-4181.2014.02.014
- VernacularTitle:小波熵在脑电信号分析中的应用
- Author:
Meiyun ZHANG
;
Benshu ZHANG
- Publication Type:Journal Article
- Keywords:
Wavelet entropy;
Cognitive;
Epilepsy;
EEG
- From:
International Journal of Biomedical Engineering
2014;37(2):122-125
- CountryChina
- Language:Chinese
-
Abstract:
Wavelet entropy,as a powerful quantitative parameter to measure the ordering/disordering level of multi-scale dynamical behavior for nonlinear signals,provides information of complex degree in nonlinear dynamical process.Recently,the wavelet entropy is attracting more and more attention in electroencephalogram (EEG) signal analysis,which is employed by domestic and overseas scholars to investigate the complex degree of EEG,evoked potential and event-related potential,and to profoundly reveal the dynamic mechanism of physiological electrical activity in the brain.It is mainly used in the research of perception,cognitive activity,dynamic observation of epileptic EEG signals,sleeping,internet addiction and rehabilitation of brain after injury.Not only can the wavelet entropy represent the dynamic evolution process of the frequency synchronization for stimulated EEG signals,but also distinguish the states before and after epileptic seizure,as well as to deepen the understanding of brain dynamics mechanism.The wavelet entropy is becoming a new tool for investigating cognition and exhibits a good application prospect in EEG signal analysis.