Advertisement

Estimating the Level of Motion Sickness Based on EEG Spectra

  • Li-Wei Ko
  • Chun-Shu Wei
  • Tzyy-Ping Jung
  • Chin-Teng Lin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6780)

Abstract

Motion sickness (MS) is a normal response to real, perceived, or even anticipated movement. People tend to get motion sickness on a moving boat, train, airplane, car, or amusement park rides. Although many motion sickness-related biomarkers have been identified, but how to estimate human’s motion sickness level (MSL) is a big challenge in the operational environment. Traditionally, questionnaire and physical check are the common ways to passively evaluate subject’s sickness level. Our past studies had investigated the EEG activities correlated with motion sickness in a virtual-reality based driving simulator. The driving simulator comprised an actual automobile mounted on a Stewart motion platform with six degrees of freedom, providing both visual and vestibular stimulations to induce motion-sickness in a manner that is close to that in daily life. EEG data were acquired at a sampling rate of 500 Hz using a 32-channel EEG system. The acquired EEG signals were analyzed using independent component analysis (ICA) and time-frequency analysis to assess EEG correlates of motion sickness. Subject’s degree of motion-sickness was simultaneously and continuously reported using an onsite joystick, providing non-stop psychophysical references to the recorded EEG changes. We found that the parietal, motor, occipital brain regions exhibited significant EEG power changes in response to vestibular and visual stimuli. Based on these findings and experimental results, this study aims to develop an EEG-based system to estimate subject’s motion sickness level upon the EEG power spectra from motion-sickness related brain areas. The MS evaluation system can be applied to early detection of the subject’s motion sickness and prevent its uncomfortable syndromes in our daily life. Furthermore, the experiment results could also lead to a practical human-machine interface for noninvasive monitoring of motion sickness of drivers or passengers in real-world environments.

Keywords

EEG ICA motion-sickness estimation time-frequency driving cognition 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Reason, J.T., Brand, J.J.: Motion-sickness. Academic Press, London (1975)Google Scholar
  2. 2.
    Brandt, T., Dieterich, M., Danek, A.: Vestibular cortex lesions affect the perception of verticality. Annals of Neurology 35(4), 403–412 (1994)CrossRefGoogle Scholar
  3. 3.
    Fasold, O., von Brevern, M., Kuhberg, M., Ploner, C.J., Villringer, A., Lempert, T., Wenzel, R.: Human vestibular cortex as identified with caloric stimulation in functional magnetic resonance imaging. NeuroImage 17(3), 1384–1393 (2002)CrossRefGoogle Scholar
  4. 4.
    Lobel, E., Kleine, J.F., Le Bihan, D., Leroy-Willig, A., Berthoz, A.: Functional MRI of galvanic vestibular stimulation. The Journal of Neurophysiology 80(5), 2699–2709 (1998)Google Scholar
  5. 5.
    De Waele, C., Baudonniere, P.M., Lepecq, J.C., Tran Ba Huy, P., Vidal, P.P.: Vestibular projections in human cortex. Experimental Brain Research 141, 541–551 (2001)CrossRefGoogle Scholar
  6. 6.
    Wood, C.D., Stewart, J.J., Wood, M.J., Struve, F.A., Straumanis, J.J., Mims, M.E., Patrick, G.Y.: Habituation and motion-sickness. Journal of Clinical Pharmacology 34, 628–634 (1994)CrossRefGoogle Scholar
  7. 7.
    Wood, S.J.: Human otolith-ocular reflexes during off-vertical axis rotation: effect of frequency on tilt-translation ambiguity and motion-sickness. Neuroscience Letters 323(1), 41–44 (2002)CrossRefGoogle Scholar
  8. 8.
    Wu, J.P.: EEG changes in man during motion-sickness induced by parallel swing. Space Medicine and Medical Engineering 5(3), 200–205 (1992)Google Scholar
  9. 9.
    Chelen, W.E., Kabrisky, M., Rogers, S.K.: Spectral analysis of the electroencephalographic response to motion-sickness. Aviation, Space, and Environmental Medicine 64(1), 24–29 (1993)Google Scholar
  10. 10.
    Hu, S., McChesney, K.A., Player, K.A., Bahl, A.M., Buchanan, J.B., Scozzafava, J.E.: Systematic investigation of physiological correlates of motion-sickness induced by viewing an optokinetic rotating drum. Aviation, Space, and Environmental Medicine 70(8), 759–765 (1999)Google Scholar
  11. 11.
    Chen, Y.C., Duann, J.R., Chuang, S.W., Lin, C.L., Ko, L.W., Jung, T.P., Lin, C.T.: Spatial and Temporal EEG Dynamics of Motion Sickness. NeuroImage 49(3), 2862–2870 (2010)CrossRefGoogle Scholar
  12. 12.
    Lin, C.T., Chuang, S.W., Chen, Y.C., Ko, L.W., Liang, S.F., Jung, T.P.: EEG Effects of Motion Sickness Induced in a Dynamic Virtual Reality Environment. In: Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), Cité Internationale, Lyon, France, August 23-26 (2007)Google Scholar
  13. 13.
    Yu, Y.H., Lai, P.C., Ko, L.W., Chuang, C.H., Kuo, B.C., Lin, C.T.: An EEG-based Classification System of Passenger’s Motion Sickness Level by using Feature Extraction/Selection Technologies. In: Proceedings of the 2010 IEEE World Congress on Computational Intelligence (WCCI 2010), Barcelona, Spain, July 18-July 23 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Li-Wei Ko
    • 1
  • Chun-Shu Wei
    • 1
  • Tzyy-Ping Jung
    • 1
    • 2
  • Chin-Teng Lin
    • 1
  1. 1.Brain Research Center, Department of Electrical EngineeringNational Chiao-Tung UniversityHsinchuTaiwan
  2. 2.Swartz Center for Computational Neuroscience, Institute for Neural ComputationUniversity of California San DiegoLa JollaUSA

Personalised recommendations