
Slide

Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Rosanne, O.; Benesch, D.; Kratzig, G.; Paré, S.; Bolt, N.; Falk, T. H.
In: Frontiers in Virtual Reality, vol. 6, 2025, ISSN: 26734192 (ISSN).
Abstract | Links | BibTeX | Tags: amplitude modulation, artifact removal, cybersickness, Electroencephalography, virtual reality
@article{rosannePreprocessNotPreprocess2025,
title = {To pre-process or not to pre-process? On the role of EEG enhancement for cybersickness characterization and the importance of amplitude modulation features},
author = {O. Rosanne and D. Benesch and G. Kratzig and S. Paré and N. Bolt and T. H. Falk},
url = {https://www.scopus.com/pages/publications/85217703600?origin=resultslist},
doi = {10.3389/frvir.2025.1468971},
issn = {26734192 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Frontiers in Virtual Reality},
volume = {6},
publisher = {Frontiers Media SA},
abstract = {Virtual Reality (VR) has expanded beyond the entertainment field and has become a valuable tool across different verticals, including healthcare, education, and professional training, just to name a few. Despite these advancements, widespread usage of VR systems is still limited, mostly due to motion sickness symptoms, such as dizziness, nausea, and headaches, which are collectively termed “cybersickness”. In this paper, we explore the use of electroencephalography (EEG) as a tool for real-time characterization of cybersickness. In particular, we aim to answer three research questions: (1) what neural patterns are indicative of cybersickness levels, (2) do EEG amplitude modulation features convey more important and explainable patterns, and (3) what role does EEG pre-processing play in overall cybersickness characterization. Experimental results show that minimal pre-processing retains artifacts that may be useful for cybersickness detection (e.g., head and eye movements), while more advanced methods enable the extraction of more interpretable neural patterns that may help the research community gain additional insights on the neural underpinnings of cybersickness. Our experiments show that the proposed amplitude modulation features comprise roughly 60% of the top-selected features for EEG-based cybersickness detection. Copyright © 2025 Rosanne, Benesch, Kratzig, Paré, Bolt and Falk.},
keywords = {amplitude modulation, artifact removal, cybersickness, Electroencephalography, virtual reality},
pubstate = {published},
tppubtype = {article}
}
Virtual Reality (VR) has expanded beyond the entertainment field and has become a valuable tool across different verticals, including healthcare, education, and professional training, just to name a few. Despite these advancements, widespread usage of VR systems is still limited, mostly due to motion sickness symptoms, such as dizziness, nausea, and headaches, which are collectively termed “cybersickness”. In this paper, we explore the use of electroencephalography (EEG) as a tool for real-time characterization of cybersickness. In particular, we aim to answer three research questions: (1) what neural patterns are indicative of cybersickness levels, (2) do EEG amplitude modulation features convey more important and explainable patterns, and (3) what role does EEG pre-processing play in overall cybersickness characterization. Experimental results show that minimal pre-processing retains artifacts that may be useful for cybersickness detection (e.g., head and eye movements), while more advanced methods enable the extraction of more interpretable neural patterns that may help the research community gain additional insights on the neural underpinnings of cybersickness. Our experiments show that the proposed amplitude modulation features comprise roughly 60% of the top-selected features for EEG-based cybersickness detection. Copyright © 2025 Rosanne, Benesch, Kratzig, Paré, Bolt and Falk.



