Citation

Yang G, Lin Y, Bhattacharya P. Inf. Sci. (NY) 2010; 180(10): 1942-1954.

Copyright

(Copyright © 2010, Elsevier Publishing)

DOI

10.1016/j.ins.2010.01.011

PMID

unavailable

Abstract

We propose a driver fatigue recognition model based on the dynamic Bayesian network, information fusion and multiple contextual and physiological features. We include features such as the contact physiological features (e.g., ECG and EEG), and apply the first-order Hidden Markov Model to compute the dynamics of the Bayesian network at different time slices. The experimental validation shows the effectiveness of the proposed system; also it indicates that the contact physiological features (especially ECG and EEG) are significant factors for inferring the fatigue state of a driver.