Zuojin Li, Shengbo E. Li, Renjie Li, Bo Cheng, and Jinliang Shi


  1. [1] R.N. Khushaba, S. Kodagoda, S. Lal, and G. Dissanayake, Driver drowsiness classification using fuzzy wavelet-packetbased feature-extraction algorithm, IEEE Transactions on Biomedical Engineering, 58(1), 2011, 121–131.
  2. [2] A. Picot, S. Charbonnier, and A. Caplier, On-line detection of drowsiness using brain and visual information, IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 42(3), 2012, 764–775.
  3. [3] Z. Li, S.E. Li, R. Li, B. Cheng, and J. Shi, Online detection of driver fatigue using steering wheel angles for real driving conditions, Sensors, 17(3), 2017, 495.
  4. [4] S. Otmani, T. Pebayle, J. Roge, and A. Muzet, Effect of driving duration and partial sleep deprivation on subsequent alertness and performance of car drivers, Physiology & Behavior, 84(5), 2005, 715–724.
  5. [5] E. Vural, Video based detection of driver fatigue, Ph.D. Thesis, Sabanci University, 2009.
  6. [6] D. Das, S. Zhou, and J.D. Lee, Differentiating alcohol-induced driving behavior using steering wheel signals, IEEE Transactions on Intelligent Transportation Systems, 13(3), 2012, 1355–1368.
  7. [7] Z. Chu, D. Zhu, and S.X. Yang, Adaptive terminal sliding mode based sensorless speed control for underwater thruster, International Journal of Robotics and Automation, 31(3), 2016, 4428–4438.
  8. [8] J. Ni, X. Li, M. Hua, and J. Shen, Bioinspired neural network based q-learning approach for robot path planning in unknown environments, International Journal of Robotics and Automation, 31(6), 2016, 4526–4590.
  9. [9] J. Zhang, F. Tian, S.X. Yang, Y. Liu, Z. Liang, and D. Wang, An intelligent and automatic control method for tobacco fluecuring based on machine learning, International Journal of Robotics and Automation, 31(6), 2016, 4697–4763.
  10. [10] Y. Wang, Y. Tuo, S.X. Yang, and M. Fu, Nonlinear model predictive control of dynamic positioning of deep-sea ships with a unified model, International Journal of Robotics and Automation, 31(6), 2016, 4764–4789.
  11. [11] Z. Zhang, Y. Zhou, Z. Chen, X. Tian, S. Du, and R. Huang, Approximate entropy and support vector machines for electroencephalogram signal classification, Neural Regeneration Research, 8(20), 2013, 1844–1852.
  12. [12] J. Krajewski, M. Golz, and D. Sommer, Detecting sleepy drivers by pattern recognition based analysis of steering wheel behaviour, Der Mensch im Mittelpunkt technischer Systeme, 29(22), 2009, 288–291.
  13. [13] X. Qu, B. Cheng, Q. Lin, and S. Li, Drowsy driving detection based on driver’s steering operation characteristics, Automotive Engineering, 35(9), 2010, 803–808.
  14. [14] X. Zhang, B. Cheng, and R. Feng, Real-time detection of driver drowsiness based on steering performance, Journal of Tsinghua University, 50(7), 2010, 1072–1076.
  15. [15] C. Zhang, H. Wang, and R. Fu, Automated detection of driver fatigue based on entropy and complexity measures, IEEE Transactions on Intelligent Transportation Systems, 15(1), 2014, 168–177.
  16. [16] J.M. Yentes, N. Hunt, K.K. Schmid, J.P. Kaipust, D. McGrath, and N. Stergiou, The appropriate use of approximate entropy and sample entropy with short data sets, Annals of Biomedical Engineering, 41(2), 2013, 349–365.
  17. [17] S.M. Pincus, Approximate entropy as a measure of system complexity, Proceedings of the National Academy of Sciences USA, 88(6), 1991, 2297–2301.
  18. [18] Z. Liu and Q. Zhang, An approach to recognize the transient disturbances with spectral kurtosis, IEEE Transactions on Instrumentation and Measurement, 63(1), 2014, 46–55.
  19. [19] A. Khazaal, F. Cabot, E. Anterrieu, and Y. Soldo, A kurtosisbased approach to detect RFI in SMOS image reconstruction data processor, IEEE Transactions on Geoscience and Remote Sensing, 52(11), 2014, 7038–7047.
  20. [20] X.-X. Xie, S. Li, C.-L. Zhang, and J.-K. Li, Study on the application of Lempel–Ziv complexity in the nonlinear detecting, Complex Systems and Complexity Science, 2(3), 2005, 61–66.
  21. [21] W.W. Wierwille, M.G. Lewin, and R.J. Fairbanks, Research on vehicle-based driver status/performance monitoring. PART I. Technical report, 1996.
  22. [22] X. Qu and B. Chen, Detection of driver drowsiness based on steering operation and vehicle state, Master’s Thesis, Tsinghua University, 2012.

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