Recognition of Low Arousal Level Electroencephalogram in the Vigilance Based on Wavelet Packet Rhythm and Support Vector Machine.
- Author:
Jianping YANG
;
Deqian ZHANG
;
Wenlang LUO
;
Xiaopeng XIAO
- Publication Type:Journal Article
- MeSH:
Arousal;
Brain;
physiology;
Electroencephalography;
Humans;
Signal Processing, Computer-Assisted;
Support Vector Machine;
Wavelet Analysis
- From:
Journal of Biomedical Engineering
2016;33(1):61-66
- CountryChina
- Language:Chinese
-
Abstract:
Poor and monotonous work could easily lead to a decrease of arousal level of the monitoring work personnel. In order to improve the performance of monitoring work, low arousal level needs to be recognized and awakened. We proposed a recognition method of low arousal by the electroencephalogram (EEG) as the object of study to recognize the low arousal level in the vigilance. We used wavelet packet transform to decompose the EEG signal so the EEG rhythms of each component were obtained, and then we calculated the parameters of relative energy and energy ratio of high-low frequency, and constructed the feature vector to monitor low arousal state in the operation. We finally used support vector machine (SVM) to recognize the low arousal state in the simulate operation. The experimental results showed that the method introduced in this article could well distinguish low arousal level from arousal level in the vigilance and it could also get a high recognition rate. Have been compared with other analysis methods, the present method could more effectively recognize low arousal level and provide better technical support for wake-up mechanism of low arousal state.
