Title :
Using EEG to detect drivers´ emotion with Bayesian Networks
Author :
Fan, Xin-an ; Bi, Lu-Zheng ; Chen, Zhi-Long
Author_Institution :
Sch. of Mech. Eng., Beijing Inst. of Technol., Beijing, China
Abstract :
Driver behavior plays a critical role in driving safety. Besides alcohol and fatigue, emotion is another factor influencing driver behavior. Thus, the detection of driver emotion can contribute to improve driving safety. In this paper, we use Bayesian Network (BNs) to develop a detection model of driver emotion with electroencephalogram (EEG), which considers two factors of driver personality and traffic situation. The preliminary experiment results suggest that this method is feasible and therefore can be used to provide adaptive aiding.
Keywords :
belief networks; driver information systems; electroencephalography; emotion recognition; road safety; Bayesian networks; EEG; driver behavior; drivers emotion detection; driving safety; electroencephalogram; Bayesian methods; Biological system modeling; Brain modeling; Driver circuits; Electroencephalography; Probability distribution; Safety; Bayesian Networks; Detection model; Driver emotion; Driving safety; EEG;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580919
