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- W2330763643 abstract "Driver is principal part of traffic, and driver's state is related to the traffic safety, such as driver's dangerous emotion state, fatigue state and drunken state. According to scientists' study, the Electroencephalogram (EEG) of people can reflect his different state more accurately. So in the modern Intelligent Transportation Systems which mainly characters are network and information, if the driver's EEG information can be gathered in Real-time, and the transportation system can be adjusted to this, then the driver can be alarmed or the necessary measure will be taken by the car's safety equipment which is designed according to the drivers' EEG information. Compared to the traditional transportation system, this kind of system which using the drivers' EEG information can reduce the traffic accident greatly. In this paper, combining the car simulation driving instrument and the EEG measuring instrument, the EEG measuring experiment system during driving was constructed, and the experiments of fatigued driving, drunken driving and inducing the dangerous emotion were designed, drivers' EEG signals were measured when they were in normal, fatigued, drunken, excited, tense, sad state. FFT and Wavelet Analysis signal processing methods were used to abstract the characters of the EEG signals. The fatigued state's EEG characters were found by different method, and the drunken state's was distinct, the excited, tense and sad state's was found too. The EEG characters of drivers in different state can reflect drivers' state in Real-time, so they can be applied to the Intelligent Transportation Systems." @default.
- W2330763643 created "2016-06-24" @default.
- W2330763643 creator A5030458946 @default.
- W2330763643 creator A5045449635 @default.
- W2330763643 date "2009-07-23" @default.
- W2330763643 modified "2023-09-27" @default.
- W2330763643 title "Study of Driver's EEG and Application in Intelligent Transportation Systems" @default.
- W2330763643 cites W2114872534 @default.
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- W2330763643 doi "https://doi.org/10.1061/41064(358)221" @default.
- W2330763643 hasPublicationYear "2009" @default.
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