Nonlinear analysis of multi-channel EEG and its application to mental workload detection.
- Author:
Dalu LIU
1
;
Zhaohui JIANG
;
Huanqing FENG
;
Guoyan WANG
Author Information
1. Dept. Electronic Sci. & tech., University of Sci. & Tech. of China, Hefei 230026, China.
- Publication Type:Journal Article
- MeSH:
Adult;
Algorithms;
Electroencephalography;
Humans;
Mental Processes;
physiology;
Nonlinear Dynamics;
Signal Processing, Computer-Assisted;
Task Performance and Analysis;
Workload
- From:
Journal of Biomedical Engineering
2006;23(5):960-963
- CountryChina
- Language:Chinese
-
Abstract:
Mental workload research is important to people's health and work efficiency, Psychophysiological measures such as electroencephalography (EEG), ECG and respiration measures can be used to predict mental workload level. A Multi-channel phase-space reconstruction method is proposed in this paper which rearranges signal serials by the correlation coefficients and select time delay by signal determinism. The study of determinism and correlation dimension on simulative data exhibits a good performance. The result of EEG series shows a clearly consistency to workload level variety. The method is useful for multi-channel signals nonlinear analysis and mental workload detection.
