Title: Evaluation of driver fatigue with EEG signal

Authors: Wei Li; Qichang He; Xiumin Fan

Addresses: School of Mechanical Engineering, Shanghai Jiaotong University, No. 800 Dongchuan Road, Minhang District, Shanghai, China ' School of Mechanical Engineering, Shanghai Jiaotong University, No. 800 Dongchuan Road, Minhang District, Shanghai, China; Shanghai Key Lab of Advanced Manufacturing Environment, Shanghai Jiaotong University, Minhang District, Shanghai, China ' School of Mechanical Engineering, Shanghai Jiaotong University, No. 800 Dongchuan Road, Minhang District, Shanghai, China; Shanghai Key Lab of Advanced Manufacturing Environment, Shanghai Jiaotong University, Minhang District, Shanghai, China

Abstract: EEG (Electroencephalogram) signals are used as effective indicators for driver fatigue evaluation. Usually, EEG signals are collected by high-cost electroencephalographs which can record multi-channels of EEG data. This paper is aimed to determine interested electrodes of the relatively optimal EEG based indicator. Firstly, 16 channels of EEG data are collected and transformed into three bands (θ, α, β). Secondly, 12 types of EEG-based parameters are established and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is introduced to determine the optimal indicator of driver fatigue. Thirdly, the interested electrodes (F_p1, F₇) are determined by MDS (multidimensional scaling). Finally, the evaluation model of driver fatigue is established with the indicator of F_p1 and F₇. Experiment results verify that the efficiency has no significant difference between evaluations with two electrodes and 16 electrodes. In addition, the established evaluation model is proven to be efficient to evaluate the driver fatigue.

Keywords: EEG signals; electroencephalograms; driver fatigue; fatigue evaluation; vehicle safety; TOPSIS; MDS; multidimensional scaling.

DOI: 10.1504/IJVS.2013.056970

International Journal of Vehicle Safety, 2013 Vol.6 No.4, pp.368 - 380

Received: 22 Nov 2012
Accepted: 15 Apr 2013
Published online: 16 Oct 2014 *

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