Estimating the level of motion sickness based on EEG spectra

Li-Wei Ko*, Chun-Shu Wei, Tzyy Ping Jung, Chin-Teng Lin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations


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.

Original languageEnglish
Title of host publicationFoundations of Augmented Cognition
Subtitle of host publicationDirecting the Future of Adaptive Systems - 6th International Conference, FAC 2011, Held as Part of HCI International 2011, Proceedings
Number of pages8
StatePublished - 2011
Event6th International Conference on Foundations of Augmented Cognition, FAC 2011, Held as Part of HCI International 2011 - Orlando, FL, United States
Duration: 9 Jul 201114 Jul 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6780 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference6th International Conference on Foundations of Augmented Cognition, FAC 2011, Held as Part of HCI International 2011
Country/TerritoryUnited States
CityOrlando, FL


  • EEG
  • ICA
  • driving cognition
  • estimation
  • motion-sickness
  • time-frequency


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