Recognition method of driving mental fatigue based on BP neural network
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(1.School of Transportation and Logistics, Southwest Jiaotong University, 610031 Chengdu, China; 2. Institute of Psychology Chinese Academy of Sciences, 100101 Beijing, China)

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U491

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    Abstract:

    To recognize driving mental fatigue efficiently, this study constructs a recognition method based on ECG. The method proposes hierarchy partition of state of driving mental fatigue by using driving behavior performance as objective evaluation indexes. Meanwhile, taking 6 indexes of HRV as fatigue recognition characterization factors and BP artificial neural network model, this paper establishes the recognition model for state of driving mental fatigue. Finally, according to examples, the mental fatigue is divided into two classifications. Collecting 4 hours continual driving behavior performance and ECG data from 10 drivers to test the model, the result shows that the average recognition accuracy rate is between 71% and 80%, and the average accuracy rate is 73%. The combination of BP neural network model and HRV indexes could recognize fatigue effectively.

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History
  • Received:June 07,2013
  • Revised:
  • Adopted:
  • Online: September 11,2014
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