• ISSN 0258-2724
  • CN 51-1277/U
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Volume 26 Issue 1
Jan.  2013
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Article Contents
Journal of Southwest Jiaotong University  > 2013  >  26(1): 178-183.
ZHAO Xiaohua, XU Shili, RONG Jian, ZHANG Xingjian. Discriminating Threshold of Driving Fatigue Based on the Electroencephalography Sample Entropy by Receiver Operating Characteristic Curve Analysis[J]. Journal of Southwest Jiaotong University, 2013, 26(1): 178-183. doi: 10.3969/j.issn.0258-2724.2013.01.028
Citation: ZHAO Xiaohua, XU Shili, RONG Jian, ZHANG Xingjian. Discriminating Threshold of Driving Fatigue Based on the Electroencephalography Sample Entropy by Receiver Operating Characteristic Curve Analysis[J]. Journal of Southwest Jiaotong University, 2013, 26(1): 178-183. doi: 10.3969/j.issn.0258-2724.2013.01.028
shu

Discriminating Threshold of Driving Fatigue Based on the Electroencephalography Sample Entropy by Receiver Operating Characteristic Curve Analysis

doi: 10.3969/j.issn.0258-2724.2013.01.028
  • Received Date: 02 Jun 2011
  • Publish Date: 25 Feb 2013
    Abstract
  • In order to acquire an objective and accurate driving fatigue threshold, electroencephalography (EEG) signals of drivers were collected from driving simulator, and the time-domain characteristics of EGG signals of drivers in sober and mental fatigue states were comparatively analyzed. Considering the different complexity of EEG signals in sober and fatigue states, the sample entropy of EEG signals were calculated to characterize the complexity of signals, and used as the index for identifying driving fatigue. Based on the obtained EGG sample entropy, the receiver operating characteristic (ROC) curve analysis was introduced to obtain the discriminating threshold of driving fatigue. The results indicate that when the EEG sample entropy value is between (0.32, 0.71), the driver is in the transitional period of fatigue, may be in a fatigue state; the sample entropy of less than 0.605 can be identified as the threshold of driving fatigue, and the accuracy is 0.95.

     

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