NDLI: Functional brain network analysis of the fatigue state for coach bus driver

Content Provider	IEEE Xplore Digital Library
Author	Wenwen Chang Hong Wang
Copyright Year	2015
Description	Author affiliation: Key Lab. of Impression Evidence Examination & Identification Technol, Nat. Police Univ. of China, Shenyang, China (Wenwen Chang; Hong Wang)
Abstract	Traffic accident of coach bus occurred frequently in recent years. One important reason of the accident is the fatigue driving of the bus driver. Thus it is very important to monitor and research the state of the driver during the driving process, which can give an evaluation to driver's driving condition and provide a valuable reference to the coach driving. Because there have some different features of human electroencephalogram (EEG) between the fatigue state and the natural state, we used the portable EEG acquisition device, Emotive, to get the EEG of the driver in the natural state (before driving) and the fatigue state (after driving three hours) in the real driving environment. And through the wavelet packet analysis, the EEG was decomposed to four sub frequency band: theta, alpha, beta and delta band, for each band, the nonlinear correlation of different electrode was calculated and functional brain network was constructed. Then the network was converted to binary network by choose an appropriate threshold and some network feature parameters were calculated and compared between the natural state and the fatigue state. The result shows that the differences of the functional brain network between the two states are very clear and this method can be used to monitor and evaluation the driver's fatigue state.
Starting Page	43
Ending Page	48
File Size	2303478
Page Count	6
File Format	PDF
e-ISBN	9781467376587
DOI	10.1109/ICAwST.2015.7314018
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time-frequency analysis Functional brain network Nonlinear correlation Artificial neural networks Wavelet analysis Electroencephalography Fatigue driving Electroencephalogram (EEG) Wavelet packet analysis
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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