Title :
Wireless and Wearable EEG System for Evaluating Driver Vigilance
Author :
Chin-Teng Lin ; Chun-Hsiang Chuang ; Chih-Sheng Huang ; Shu-Fang Tsai ; Shao-Wei Lu ; Yen-Hsuan Chen ; Li-Wei Ko
Author_Institution :
Inst. of Electr. Control Eng. & the Brain Res. Center, Nat. Chiao Tung Univ., Hsinchu, Taiwan
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.
Keywords :
Java; biomedical equipment; biosensors; electroencephalography; medical signal processing; neurophysiology; programming languages; regression analysis; virtual reality; wireless sensor networks; EEG signal recording; JAVA programming language; Mindo system; arousal; automobile drivers; brain activity; driver vigilance status; driving performance; electroencephalographic changes; fatigue; hairy regions; immersive virtual driving environment; laboratory-oriented biosensor technology; mobile wireless EEG system; neurophysiological activities; novel dry EEG sensor; online analysis; regression models; safe driving task; sustained-attention driving task; task performance; wearable EEG system; Biomedical monitoring; Brain models; Electroencephalography; Monitoring; Wireless communication; Wireless sensor networks; Brain computer interface; dry electroencephalographic (EEG) system; machine learning; vigilance monitoring;
Journal_Title :
Biomedical Circuits and Systems, IEEE Transactions on
DOI :
10.1109/TBCAS.2014.2316224