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dc.contributor.authorLin, Chin-Tengen_US
dc.contributor.authorChuang, Chun-Hsiangen_US
dc.contributor.authorHuang, Chih-Shengen_US
dc.contributor.authorTsai, Shu-Fangen_US
dc.contributor.authorLu, Shao-Weien_US
dc.contributor.authorChen, Yen-Hsuanen_US
dc.contributor.authorKo, Li-Weien_US
dc.date.accessioned2014-12-08T15:36:25Z-
dc.date.available2014-12-08T15:36:25Z-
dc.date.issued2014-04-01en_US
dc.identifier.issn1932-4545en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TBCAS.2014.2316224en_US
dc.identifier.urihttp://hdl.handle.net/11536/24756-
dc.description.abstractBrain 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.en_US
dc.language.isoen_USen_US
dc.subjectBrain computer interfaceen_US
dc.subjectdry electroencephalographic (EEG) systemen_US
dc.subjectmachine learningen_US
dc.subjectvigilance monitoring.en_US
dc.titleWireless and Wearable EEG System for Evaluating Driver Vigilanceen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TBCAS.2014.2316224en_US
dc.identifier.journalIEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMSen_US
dc.citation.volume8en_US
dc.citation.issue2en_US
dc.citation.spage165en_US
dc.citation.epage176en_US
dc.contributor.department生物科技學系zh_TW
dc.contributor.department資訊工程學系zh_TW
dc.contributor.department電控工程研究所zh_TW
dc.contributor.department腦科學研究中心zh_TW
dc.contributor.departmentDepartment of Biological Science and Technologyen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.contributor.departmentBrain Research Centeren_US
dc.identifier.wosnumberWOS:000337154000003-
dc.citation.woscount0-
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