An EEG-based method for detecting drowsy driving state

The characteristic of EEG signal in drowsy driving was researched. A method based on power spectrum analysis and FastICA algorithm was proposed to determining the fatigue degree. In a driving simulation system, the EEG signals of subjects were captured by instrument NT-9200 in two states, one state...

Full description

Saved in:
Bibliographic Details
Published in2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery Vol. 5; pp. 2164 - 2167
Main Authors Li, Ming-ai, Zhang, Cheng, Yang, Jin-Fu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2010
Subjects
Brain modeling
Driver circuits
Electrodes
electroencephalograph(EEG)
Electroencephalography
Fatigue
fatigue driving
fatigue index
Independent component analysis
independent component analysis (ICA)
Indexes
spectrum analysis
Online AccessGet full text
ISBN1424459311
9781424459315
DOI10.1109/FSKD.2010.5569757

Cover

More Information
Summary:The characteristic of EEG signal in drowsy driving was researched. A method based on power spectrum analysis and FastICA algorithm was proposed to determining the fatigue degree. In a driving simulation system, the EEG signals of subjects were captured by instrument NT-9200 in two states, one state was sober, and the other was drowsy. The multi channel signals were analyzed with FastICA algorithm, to remove ocular electric, myoelectric and power frequency interferences. Power spectral densities were calculated after FFT, and the fatigue index F was gotten finally. Experimental results show that the method presented in this paper can be used to determine the drowsiness degree of EEG signal effectually.
ISBN:1424459311
9781424459315
DOI:10.1109/FSKD.2010.5569757