Journal of Northeastern University Natural Science ›› 2014, Vol. 35 ›› Issue (6): 850-853.DOI: 10.12068/j.issn.1005-3026.2014.06.020

• Mechanical Engineering • Previous Articles     Next Articles

Detection of Driver Fatigue Based on Multiphysiological Signals in Wireless Body Area Network

FU Rongrong, WANG Hong, WANG Lin, ZHANG Chi   

  1. School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China.
  • Received:2013-07-01 Revised:2013-07-01 Online:2014-06-15 Published:2014-04-11
  • Contact: WANG Hong
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Abstract: Driver fatigue was detected using electroencephalograph, electromyography and respiration signals, which were collected wirelessly. The approximate entropies of the three signals were selected as features, and the reduction of feature dimensions was achieved by principle component analysis. Statistical analyses were then given to both original features and principle components and an evaluation model for driver fatigue was established using regression equation. The experimental results were evaluated by cross validation and the accuracy was more than 90% based on data fusion method. The results verify that the model is effective in detecting driver fatigue.

Key words: driver fatigue, wireless body area network, electroencephalograph, electromyography, respiration

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