Driving Distraction Analysis by ECG Signals: An Entropy Analysis

  • Lu Yu
  • Xianghong Sun
  • Kan Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6775)


This paper presents a novel method in driving distraction analysis: entropy analysis of ECG signals. ECG signals were recorded continuously while 15 drivers were driving with a simulator. Mental computation task was employed as driving distraction. Sample entropy and power spectrum entropy of drivers. ECG signals while they were driving with and without distraction were derived. The result indicated that entropy of drivers ECG signals was sensitive to driving distraction and were potential significant metrics in driving distraction measurement.


Entropy Driving distraction ECG signal 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Lianeras, R.: NHTSA driver distraction Internet forum: Summary and proceedings (On-line conference proceedings). National Highway Traffic Safety Administration, Washington (2000), Google Scholar
  2. 2.
    Liang, Y., Reyes, M.L., Lee, J.D.: Real-Time Detection of Driver Cognitive Distraction Using Support Vector Machines. IEEE Transactions on Intelligent Transportation Systems 8(2), 340–350 (2007)CrossRefGoogle Scholar
  3. 3.
    Zhang, Y., Owechko, Y., Zhang, J.: Learning-Based Driver Workload Estimation. In: Prokhorov, D. (ed.) Comput. Intel. in Automotive Applications. SCI, vol. 132, pp. 1–24. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  4. 4.
    D’Orazio, T., Leo, M., Guaragnella, C., Distante, A.: A visual approach for driver inattention detection. Pattern Recognition 40, 2341–2355 (2007)CrossRefzbMATHGoogle Scholar
  5. 5.
    Tango, F., Botta, M.: Evaluation of Distraction in a Driver-Vehicle-Environment Framework: An Application of Different Data-Mining Techniques. In: Perner, P. (ed.) ICDM 2009. LNCS, vol. 5633, pp. 176–190. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  6. 6.
    Carcioppo, C.J., Tassinary, L.G.: Inferring psychological significance from physiological signals. American Psychologist 45(1), 16–28 (1990)CrossRefGoogle Scholar
  7. 7.
    Picard, R.W., Vyzas, E., Healey, J.T.: Machine Emotional Intelligence: Analysis of affective physiological state. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(10), 1175–1191 (2001)CrossRefGoogle Scholar
  8. 8.
    Ekman, P.: An argument for basic emotion. Cognition and Emotion 1992(6), 169–200 (1992)CrossRefGoogle Scholar
  9. 9.
    Stemmler, G., Heldmann, M., Pauls, C.A.: Constrains for emotion specificity in fear and anger: the context counts. Psyehophysiology 38, 275–291 (2001)CrossRefGoogle Scholar
  10. 10.
    Kim, K.H., Bang, S.W., Kim, S.R.: Emotion recognition system using short-term monitoring of Physiological signals. Med. Biol. Eng. ComPut. 42, 419–442 (2004)CrossRefGoogle Scholar
  11. 11.
    Jennifer, A.H., Rosalind, W.P.: Detecting Stress During Real-World Driving Tasks Using Physiological Sensors. IEEE Transactions on Intelligent Transportation Systems 6(2), 156–166 (2005)CrossRefGoogle Scholar
  12. 12.
    Collet, C., Clarion, A., Morel, M., Chapon, A., Petit, C.: Physiological and behavioral changes associated to the management of secondary tasks while driving. Applied Ergonomics 40, 1041–1046 (2009)CrossRefGoogle Scholar
  13. 13.
    Hankins, T.C., Wilson, G.F.: A comparison of heart rate, eye activity, EEG and subjective measures of pilot mental workload during flight. Aviation, Space, and Environmental Medicine 69, 360–367 (1998)Google Scholar
  14. 14.
    Wilson, G.F.: Air-to-ground training missions: A psychophysiological workload analysis. Ergonomics 36, 1071–1087 (1993)CrossRefGoogle Scholar
  15. 15.
    Wu, H.J., Zhang, H., Zheng, C.X.: Application of Spectrum Entropy to the Noninvasive detection of focal ischemiccerebal Injury. Journal of Biomedical Engineering 20(2), 229–232 (2003)Google Scholar
  16. 16.
    Liu, H., He, W., Chen, X.: Nonlinear Dynamic Method of Sleeping EEG. Journal of Jiangsu University 26(2), 174–177 (2005)Google Scholar
  17. 17.
    Chang, J.: Application of Entropy Analysis in Bioinformation Processing. Master Thesis, Southwest University (2008)Google Scholar
  18. 18.
    Boucsein, W.: Psychophysiology in the work place – goals and methods. In: Ullsperger, P. (ed.) Psychophysiology of Mental Workload, pp. 35–41. Bundesanstalt fur Arbeitmedizin, Berlin (1993)Google Scholar
  19. 19.
    Wallin, B.G., Fagius, J.: The sympathetic nervous system in man: aspects derived from microelectrode recordings. Trends Neuroscience 9, 63–67 (1986)CrossRefGoogle Scholar
  20. 20.
    Richman, J.S., Moorman, J.R.: Physiological Time Series Analysis using Approximate Entropy and Sample Entropy. American Journal of Physiology - Heart and Circulatory Physiology 278(6), H2039–H2049 (2000)Google Scholar
  21. 21.
    Costa, M., Goldberger, A.L., Peng, C.K.: Multiscale Entropy Analysis of Complex Physiologic Time Series. Physical Review Letters 89(6), 068102-1-1–068102-1-4 (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Lu Yu
    • 1
  • Xianghong Sun
    • 1
  • Kan Zhang
    • 1
  1. 1.Institute of psychologyChinese Academy of SciencesBeijingChina

Personalised recommendations