Issue 52, 2018, Issue in Progress
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RSC Advances

EEG characteristic analysis of coach bus drivers based on brain connectivity as revealed via a graph theoretical network

Fuwang Wang, ORCID logo *a   Xiaolei Zhang,a   Rongrong Fub  and  Guangbin Sun ORCID logo c  

* Corresponding authors

a School of Mechanic Engineering, Northeast Electric Power University, Jilin 132012, China
E-mail: wangfuwangfeixue@163.com, 20152622@neepu.edu.cn, wangfuwangbaiyang@126.com
Tel: +86-432-64807382

b College of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China

c Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China
E-mail: gbsun@csu.ac.cn

Abstract

This study describes the detection of driving fatigue using the characteristics of brain networks in a real driving environment. First, the θ, β and 36–44 Hz rhythm from the EEG signals of drivers were extracted using wavelet packet decomposition (WPD). The correlation between EEG channels was calculated using a Pearson correlation coefficient and subsequently, the brain networks were built. Furthermore, the clustering coefficient (C) and global efficiency (G) of the complex brain networks were calculated to analyze the functional differences in the brains of drivers over time. Combined with the relative power spectrum ratio (β/θ) of EEG signals and the mean value from questionnaires, the correlation of data characteristics between brain networks and subjective and objective data was analyzed. The results show that changes in the fatigue state of drivers can be effectively detected by calculating the data characteristics of brain networks in a real driving environment.

Graphical abstract: EEG characteristic analysis of coach bus drivers based on brain connectivity as revealed via a graph theoretical network

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Article information

DOI
https://doi.org/10.1039/C8RA04846K
Article type
Paper
Submitted
06 Jun 2018
Accepted
06 Aug 2018
First published
23 Aug 2018
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2018,8, 29745-29755

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EEG characteristic analysis of coach bus drivers based on brain connectivity as revealed via a graph theoretical network

F. Wang, X. Zhang, R. Fu and G. Sun, RSC Adv., 2018, 8, 29745 DOI: 10.1039/C8RA04846K

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