Browsing by Author "Chen, Yen-Hsuan"

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Real-time Assessment of Vigilance Level using an Innovative Mindo4 Wireless EEG System
(2013)
Lin, Chin-Teng
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Chuang, Chun-Hsiang
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Huang, Chih-Sheng
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Chen, Yen-Hsuan
;
Ko, Li-Wei
Monitoring the neurophysiological activities of driver in an operational environment poses a severe measurement challenge using a current laboratory-oriented biosensor technology. The aims of this research are to 1) introduce a dry and wireless EEG system used for conveniently recording EEG signals from forehead regions, 2) propose an effective system for processing EEG recordings and translating them into the vigilance level, and 3) implement the proposed system with a JAVA-based graphical user interface (GUI) for online analysis. To validate the performance of the proposed system, this study recruited eight voluntary subjects to participate a 90-min sustained-attention driving task in a virtual-realistic driving environment. Physiological evidence obtained from the power spectral analysis showed that the dry EEG system could distinguish an alert EEG from a drowsy EEG by evaluating the spectral dynamics of delta and alpha activities. Furthermore, the experimental result of the comparison of the prediction performance using four forehead electrode sites (AF8, FP2, FP1, and AF7) implied that a single-electrode EEG signal used in the mobile and wireless EEG system is able to obtain a high prediction accuracy (similar to 93%). Taken together, the proposed system applied a dry-EEG device combined with an effective algorithm can be a promising technology for real driving applications.
Wireless and Wearable EEG System for Evaluating Driver Vigilance
(2014-04-01)
Lin, Chin-Teng
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Chuang, Chun-Hsiang
;
Huang, Chih-Sheng
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Tsai, Shu-Fang
;
Lu, Shao-Wei
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.