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.
To pre-process or not to pre-process? On the role of EEG enhancement for cybersickness characterization and the importance of amplitude modulation features Article de journal
Dans: Frontiers in Virtual Reality, vol. 6, 2025, ISSN: 26734192 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: 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.
2.
Blais, C.; Arguin, M.; Gosselin, F.
Human visual processing oscillates: Evidence from a classification image technique Article de journal
Dans: Cognition, vol. 128, no 3, p. 353–362, 2013, ISSN: 00100277.
Résumé | Liens | BibTeX | Étiquettes: amplitude modulation, article, Face, female, human, human experiment, Humans, male, normal human, oscillation, Oscillations, Pattern Recognition, Photic Stimulation, priority journal, reaction time, signal noise ratio, Signal-To-Noise Ratio, stimulus response, Temporal processing, vision, Visual, visual acuity, Visual Perception, Visual sampling, visual stimulation
@article{blais_human_2013,
title = {Human visual processing oscillates: Evidence from a classification image technique},
author = {C. Blais and M. Arguin and F. Gosselin},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879014749&doi=10.1016%2fj.cognition.2013.04.009&partnerID=40&md5=c2d20982fa4a5c46b9d99d2912284ff6},
doi = {10.1016/j.cognition.2013.04.009},
issn = {00100277},
year = {2013},
date = {2013-01-01},
journal = {Cognition},
volume = {128},
number = {3},
pages = {353–362},
abstract = {Recent investigations have proposed that visual information may be sampled in a discrete manner, similarly to the snapshots of a camera, but this hypothesis remains controversial. Moreover, assuming a discrete sampling of information, the properties of this sampling-for instance, the frequency at which it operates, and how it synchronizes with the environment-still need to be clarified. We systematically modulated the signal-to-noise ratio of faces through time and examined how it impacted face identification performance. Altogether, our results support the hypothesis of discrete sampling. Furthermore, they suggest that this mechanism may operate at a rate of about 10-15. Hz and that it is synchronized with the onset of the stimulus. © 2013 Elsevier B.V.},
keywords = {amplitude modulation, article, Face, female, human, human experiment, Humans, male, normal human, oscillation, Oscillations, Pattern Recognition, Photic Stimulation, priority journal, reaction time, signal noise ratio, Signal-To-Noise Ratio, stimulus response, Temporal processing, vision, Visual, visual acuity, Visual Perception, Visual sampling, visual stimulation},
pubstate = {published},
tppubtype = {article}
}
Recent investigations have proposed that visual information may be sampled in a discrete manner, similarly to the snapshots of a camera, but this hypothesis remains controversial. Moreover, assuming a discrete sampling of information, the properties of this sampling-for instance, the frequency at which it operates, and how it synchronizes with the environment-still need to be clarified. We systematically modulated the signal-to-noise ratio of faces through time and examined how it impacted face identification performance. Altogether, our results support the hypothesis of discrete sampling. Furthermore, they suggest that this mechanism may operate at a rate of about 10-15. Hz and that it is synchronized with the onset of the stimulus. © 2013 Elsevier B.V.
3.
Blais, C.; Arguin, M.; Gosselin, F.
Human visual processing oscillates: Evidence from a classification image technique Article de journal
Dans: Cognition, vol. 128, no 3, p. 353–362, 2013, ISSN: 00100277.
Résumé | Liens | BibTeX | Étiquettes: amplitude modulation, article, Face, female, human, human experiment, Humans, male, normal human, oscillation, Oscillations, Pattern Recognition, Photic Stimulation, priority journal, reaction time, signal noise ratio, Signal-To-Noise Ratio, stimulus response, Temporal processing, vision, Visual, visual acuity, Visual Perception, Visual sampling, visual stimulation
@article{blaisHumanVisualProcessing2013,
title = {Human visual processing oscillates: Evidence from a classification image technique},
author = {C. Blais and M. Arguin and F. Gosselin},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84879014749&doi=10.1016%2fj.cognition.2013.04.009&partnerID=40&md5=c2d20982fa4a5c46b9d99d2912284ff6},
doi = {10.1016/j.cognition.2013.04.009},
issn = {00100277},
year = {2013},
date = {2013-01-01},
journal = {Cognition},
volume = {128},
number = {3},
pages = {353–362},
abstract = {Recent investigations have proposed that visual information may be sampled in a discrete manner, similarly to the snapshots of a camera, but this hypothesis remains controversial. Moreover, assuming a discrete sampling of information, the properties of this sampling-for instance, the frequency at which it operates, and how it synchronizes with the environment-still need to be clarified. We systematically modulated the signal-to-noise ratio of faces through time and examined how it impacted face identification performance. Altogether, our results support the hypothesis of discrete sampling. Furthermore, they suggest that this mechanism may operate at a rate of about 10-15. Hz and that it is synchronized with the onset of the stimulus. © 2013 Elsevier B.V.},
keywords = {amplitude modulation, article, Face, female, human, human experiment, Humans, male, normal human, oscillation, Oscillations, Pattern Recognition, Photic Stimulation, priority journal, reaction time, signal noise ratio, Signal-To-Noise Ratio, stimulus response, Temporal processing, vision, Visual, visual acuity, Visual Perception, Visual sampling, visual stimulation},
pubstate = {published},
tppubtype = {article}
}
Recent investigations have proposed that visual information may be sampled in a discrete manner, similarly to the snapshots of a camera, but this hypothesis remains controversial. Moreover, assuming a discrete sampling of information, the properties of this sampling-for instance, the frequency at which it operates, and how it synchronizes with the environment-still need to be clarified. We systematically modulated the signal-to-noise ratio of faces through time and examined how it impacted face identification performance. Altogether, our results support the hypothesis of discrete sampling. Furthermore, they suggest that this mechanism may operate at a rate of about 10-15. Hz and that it is synchronized with the onset of the stimulus. © 2013 Elsevier B.V.