Lee, Gaël Van der and Lécuyer, Anatole and Naud, Maxence and Scherer, Reinhold and Cabestaing, FranÇois and Si-Mohammed, Hakim (2026) Towards the Automatic Detection of Vection in Virtual Reality Using EEG. IEEE Transactions on Visualization and Computer Graphics. pp. 1-11. DOI https://doi.org/10.1109/tvcg.2026.3675421
Lee, Gaël Van der and Lécuyer, Anatole and Naud, Maxence and Scherer, Reinhold and Cabestaing, FranÇois and Si-Mohammed, Hakim (2026) Towards the Automatic Detection of Vection in Virtual Reality Using EEG. IEEE Transactions on Visualization and Computer Graphics. pp. 1-11. DOI https://doi.org/10.1109/tvcg.2026.3675421
Lee, Gaël Van der and Lécuyer, Anatole and Naud, Maxence and Scherer, Reinhold and Cabestaing, FranÇois and Si-Mohammed, Hakim (2026) Towards the Automatic Detection of Vection in Virtual Reality Using EEG. IEEE Transactions on Visualization and Computer Graphics. pp. 1-11. DOI https://doi.org/10.1109/tvcg.2026.3675421
Abstract
Vection, the visual illusion of self-motion, provides a strong marker of the VR user experience and plays an important role in both presence and cybersickness. Traditional measurements have been conducted using questionnaires, which exhibit inherent limitations due to their subjective nature and prevent real-time adjustments. Detecting vection in real time would allow VR systems to adapt to users' needs, improving comfort and minimizing negative effects like cybersickness. This paper investigates the presence of vection markers in electroencephalographic (EEG) brain signals using evoked potentials (brain responses to external stimuli). We designed a VR experiment that induces vection using two conditions: (1) forward acceleration or (2) backward acceleration. We recorded electroencephalographic (EEG) signals and gathered subjective reports on thirty (30) participants. We found an evoked potential of vection characterized by a positive peak around 600 ms (P600) after stimulus onset in the parietal region and a simultaneous negative peak in the frontal region. This result paves the way for the automatic detection of vection using EEG as well as a better understanding of vection. It also provides insights into the functional role of the visual system and its integration with the vestibular system during motion-perception. It has the potential to help enhance VR user experience by qualifying users' perceived vection and adapting the VR environments accordingly.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Human-centered computing; Human computer interaction (HCI); Interaction paradigms; Virtual reality |
| Subjects: | Z Bibliography. Library Science. Information Resources > ZR Rights Retention |
| Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
| SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
| Depositing User: | Unnamed user with email elements@essex.ac.uk |
| Date Deposited: | 25 Mar 2026 11:37 |
| Last Modified: | 25 Mar 2026 11:38 |
| URI: | http://repository.essex.ac.uk/id/eprint/42989 |
Available files
Filename: Towards the Automatic Detection of Vection.pdf
Licence: Creative Commons: Attribution 4.0