Abstract
In recently years, driver fatigue detecting system has gained increasing attentions in the area of public security. Researchers have succeeded in applying the EEG signals to accurately detect individuals fatigue state in sustained attention tasks. However, these studies were performed under laboratory-oriented configurations using tethered, ponderous EEG equipment, which are not feasible to develop the fatigue detecting system in the real environment. This study focused on developing a portable attention level monitoring and alarming (ALMA) system, featuring a mobile NeuroSky MindSet and an android pad based real-time EEG processing platform, for the driver fatigue in the pervasive environment. A brain feature rule which can represent the brain gradual process from focus state to the fatigue state has been formulated. We evaluated the ability of attention level of the system in the simulated driving cockpit and demonstrated that the system can classify the subjects attention level in accordance with the rule in the real time.
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Wan, Z., He, J., Voisine, A. (2013). An Attention Level Monitoring and Alarming System for the Driver Fatigue in the Pervasive Environment. In: Imamura, K., Usui, S., Shirao, T., Kasamatsu, T., Schwabe, L., Zhong, N. (eds) Brain and Health Informatics. BHI 2013. Lecture Notes in Computer Science(), vol 8211. Springer, Cham. https://doi.org/10.1007/978-3-319-02753-1_29
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DOI: https://doi.org/10.1007/978-3-319-02753-1_29
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