An EEG-based method for detecting drowsy driving state

Abstract

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.