Mental fatigue electroencephalogram signals analysis based on singular system.
- Author:
Chong ZHANG
;
Xiaolin YU
;
Yong YANG
;
Lei XU
- Publication Type:Journal Article
- MeSH:
Electroencephalography;
Humans;
Mental Fatigue;
Principal Component Analysis
- From:
Journal of Biomedical Engineering
2014;31(5):1132-1138
- CountryChina
- Language:Chinese
-
Abstract:
In the present paper, the contribution of the largest principal component and the number of principal component needed for accumulative contribution 95% are selected as indices of electroencephalogram (EEG) in mental fatigue state in order to investigate the relationship between these parameters and mental fatigue. The experimental results showed that the contribution of the largest principal component of EEG signals increased in the prefrontal, frontal and central areas, while the number of principal component needed for accumulative contribution decreased by 95% with the increasing mental fatigue level. The parameters of singular system of EEG signals can be regarded as useful features for the estimation of mental fatigue and have larger application value in the study of mental fatigue.
