Wireless and wearable EEG system for evaluating driver vigilance

Lin, CT; Chuang, CH; Huang, CS; Tsai, SF; Lu, SW; Chen, YH; Ko, LW

Wireless and wearable EEG system for evaluating driver vigilance

Lin, CT

Chuang, CH

Huang, CS Tsai, SF Lu, SW Chen, YH Ko, LW

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Biomedical Circuits and Systems, 2014, 8 (2), pp. 165 - 176
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Lin, CT https://orcid.org/0000-0001-8371-8197	en_US
dc.contributor.author	Chuang, CH https://orcid.org/0000-0002-5043-8380	en_US
dc.contributor.author	Huang, CS	en_US
dc.contributor.author	Tsai, SF	en_US
dc.contributor.author	Lu, SW	en_US
dc.contributor.author	Chen, YH	en_US
dc.contributor.author	Ko, LW	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	IEEE Transactions on Biomedical Circuits and Systems, 2014, 8 (2), pp. 165 - 176	en_US
dc.identifier.issn	1932-4545	en_US
dc.identifier.uri	http://hdl.handle.net/10453/118207
dc.description.abstract	Brain activity associated with attention sustained on the task of safe driving has received considerable attention recently in many neurophysiological studies. Those investigations have also accurately estimated shifts in drivers' levels of arousal, fatigue, and vigilance, as evidenced by variations in their task performance, by evaluating electroencephalographic (EEG) changes. However, monitoring the neurophysiological activities of automobile drivers poses a major measurement challenge when using a laboratory-oriented biosensor technology. This work presents a novel dry EEG sensor based mobile wireless EEG system (referred to herein as Mindo) to monitor in real time a driver's vigilance status in order to link the fluctuation of driving performance with changes in brain activities. The proposed Mindo system incorporates the use of a wireless and wearable EEG device to record EEG signals from hairy regions of the driver conveniently. Additionally, the proposed system can process EEG recordings and translate them into the vigilance level. The study compares the system performance between different regression models. Moreover, the proposed system is implemented using JAVA programming language as a mobile application for online analysis. A case study involving 15 study participants assigned a 90 min sustained-attention driving task in an immersive virtual driving environment demonstrates the reliability of the proposed system. Consistent with previous studies, power spectral analysis results confirm that the EEG activities correlate well with the variations in vigilance. Furthermore, the proposed system demonstrated the feasibility of predicting the driver's vigilance in real time. © 2014 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Biomedical Circuits and Systems	en_US
dc.relation.isbasedon	10.1109/TBCAS.2014.2316224	en_US
dc.subject.classification	Electrical & Electronic Engineering	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Electroencephalography	en_US
dc.subject.mesh	Attention	en_US
dc.subject.mesh	Sleep Stages	en_US
dc.subject.mesh	Automobile Driving	en_US
dc.subject.mesh	Clothing	en_US
dc.subject.mesh	Signal Processing, Computer-Assisted	en_US
dc.subject.mesh	Wireless Technology	en_US
dc.subject.mesh	Brain-Computer Interfaces	en_US
dc.title	Wireless and wearable EEG system for evaluating driver vigilance	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	8	en_US
utslib.for	0903 Biomedical Engineering	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	8	en_US

Abstract:

Brain activity associated with attention sustained on the task of safe driving has received considerable attention recently in many neurophysiological studies. Those investigations have also accurately estimated shifts in drivers' levels of arousal, fatigue, and vigilance, as evidenced by variations in their task performance, by evaluating electroencephalographic (EEG) changes. However, monitoring the neurophysiological activities of automobile drivers poses a major measurement challenge when using a laboratory-oriented biosensor technology. This work presents a novel dry EEG sensor based mobile wireless EEG system (referred to herein as Mindo) to monitor in real time a driver's vigilance status in order to link the fluctuation of driving performance with changes in brain activities. The proposed Mindo system incorporates the use of a wireless and wearable EEG device to record EEG signals from hairy regions of the driver conveniently. Additionally, the proposed system can process EEG recordings and translate them into the vigilance level. The study compares the system performance between different regression models. Moreover, the proposed system is implemented using JAVA programming language as a mobile application for online analysis. A case study involving 15 study participants assigned a 90 min sustained-attention driving task in an immersive virtual driving environment demonstrates the reliability of the proposed system. Consistent with previous studies, power spectral analysis results confirm that the EEG activities correlate well with the variations in vigilance. Furthermore, the proposed system demonstrated the feasibility of predicting the driver's vigilance in real time. © 2014 IEEE.

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http://hdl.handle.net/10453/118207