Title: An EEG-based perceptual function integration network for application to drowsy driving
Authors: Chuang, Chun-Hsiang
Huang, Chih-Sheng
Ko, Li-Wei
Lin, Chin-Teng
Department of Biological Science and Technology
Department of Computer Science
Brain Research Center
Keywords: Electroencephalogram;Independent component analysis;Multiple classifiers system;Drowsy driving
Issue Date: 1-May-2015
Abstract: Drowsy driving is among the most critical causes of fatal crashes. Thus, the development of an effective algorithm for detecting a driver\'s cognitive state demands immediate attention. For decades, studies have observed clear evidence using electroencephalography that the brain\'s rhythmic activities fluctuate from alertness to drowsiness. Recognition of this physiological signal is the major consideration of neural engineering for designing a feasible countermeasure. This study proposed a perceptual function integration system which used spectral features from multiple independent brain sources for application to recognize the driver\'s vigilance state. The analysis of brain spectral dynamics demonstrated physiological evidenced that the activities of the multiple cortical sources were highly related to the changes of the vigilance state. The system performances showed a robust and improved accuracy as much as 88% higher than any of results performed by a single-source approach. (C) 2015 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/j.knosys.2015.01.007
ISSN: 0950-7051
DOI: 10.1016/j.knosys.2015.01.007
Volume: 80
Begin Page: 143
End Page: 152
Appears in Collections:Articles