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 |
Appears in Collections: | Articles |
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