標題: Wireless and Wearable EEG System for Evaluating Driver Vigilance
作者: Lin, Chin-Teng
Chuang, Chun-Hsiang
Huang, Chih-Sheng
Tsai, Shu-Fang
Lu, Shao-Wei
Chen, Yen-Hsuan
Ko, Li-Wei
生物科技學系
資訊工程學系
電控工程研究所
腦科學研究中心
Department of Biological Science and Technology
Department of Computer Science
Institute of Electrical and Control Engineering
Brain Research Center
關鍵字: Brain computer interface;dry electroencephalographic (EEG) system;machine learning;vigilance monitoring.
公開日期: 1-Apr-2014
摘要: 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.
URI: http://dx.doi.org/10.1109/TBCAS.2014.2316224
http://hdl.handle.net/11536/24756
ISSN: 1932-4545
DOI: 10.1109/TBCAS.2014.2316224
期刊: IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
Volume: 8
Issue: 2
起始頁: 165
結束頁: 176
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