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作者:

Zhao, Xiaohua (Zhao, Xiaohua.) | Xu, Shili (Xu, Shili.) | Rong, Jian (Rong, Jian.) (学者:荣建) | Zhang, Xingjian (Zhang, Xingjian.)

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摘要:

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.

关键词:

Electrophysiology Time domain analysis Electroencephalography Entropy

作者机构:

  • [ 1 ] [Zhao, Xiaohua]Beijing Key Lab. of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Xu, Shili]Beijing Key Lab. of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Rong, Jian]Beijing Key Lab. of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Zhang, Xingjian]Beijing Key Lab. of Traffic Engineering, Beijing University of Technology, Beijing 100124, China

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来源 :

Journal of Southwest Jiaotong University

ISSN: 0258-2724

年份: 2013

期: 1

卷: 48

页码: 178-183

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 28

ESI高被引论文在榜: 0 展开所有

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