@inproceedings{brideau-duquette_when_2025,

title = {When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny},

author = {M. Brideau-Duquette and S. S. -P. Côté and P. Charbonneau and P. Renaud},

editor = {Itthipuripat S. and Ascoli G.A. and Li A. and Pat N. and Kuai H.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002448490&doi=10.1007%2f978-981-96-3294-7_10&partnerID=40&md5=61cb61b0534ab807a73107ddc116879d},

doi = {10.1007/978-981-96-3294-7_10},

isbn = {03029743 (ISSN); 978-981963293-0 (ISBN)},

year  = {2025},

date = {2025-01-01},

booktitle = {Lect. Notes Comput. Sci.},

volume = {15541 LNAI},

pages = {121–139},

publisher = {Springer Science and Business Media Deutschland GmbH},

abstract = {This study explores the psychological effects of human-machine interaction, particularly focusing on the phenomenon of the uncanny valley within the context of virtual reality (VR). This study specifically investigates the relationship between oculomotor dynamics, EEG asymmetry, and perceived uncanniness in an immersive setting with a realistic human avatar that can generate uncanny feelings. Participants engaged in a VR scenario designed to optimize their sexual interest. Eye-tracking and EEG data were collected during these interactions to assess the predictors of uncanniness. The final regression model identified significant predictors, including EEG asymmetry in frontal and parietal regions and nonlinear indices of gaze behavior. The findings suggest that the more a participants’ attention was attracted towards specific cues, the higher the uncanniness. The interplay between EEG asymmetries and gaze behavior furthermore indicates that these physiological and behavioral responses are closely linked to the perception of uncanniness, offering insights into how humans interact with increasingly lifelike technologies. These insights contribute to a better understanding of HMI’s potential and may inform the development of more engaging and psychologically attuned virtual content. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.},

note = {Journal Abbreviation: Lect. Notes Comput. Sci.},

keywords = {Brain, Embodied Computing, Eye-tracking, Gaze behaviours, Human machine interaction, Immersive, Nonlinear index, Psychological effects, regression analysis, Regression modelling, Uncanny, Uncanny valley, Virtual environments, virtual reality},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{chartier_online_2008,

title = {An online noise filter for eye-tracker data recorded in a virtual environment},

author = {S. Chartier and P. Renaud},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950329450&doi=10.1145%2f1344471.1344511&partnerID=40&md5=7ba397a215e76c9d511800ccb267b5cd},

doi = {10.1145/1344471.1344511},

isbn = {978-159593982-1 (ISBN)},

year  = {2008},

date = {2008-01-01},

booktitle = {Eye Tracking Research and Applications Symposium (ETRA)},

pages = {153–156},

address = {Savannah, GA},

abstract = {A Recursive Online Weight Average filter (ROWA) is proposed to remove and replace noisy data obtained from eye tracker. Since the filter can be implemented online, it can detect and replace noisy data using solely past records. Simulations results indicate that the filter achieved the same performance compared to other standard offline filters while being simpler. Copyright © 2008 by the Association for Computing Machinery, Inc.},

note = {Journal Abbreviation: Eye Track. Res. Appl. Symp. (ETRA)},

keywords = {Average filter, Eye trackers, Eye-blinks, Eye-tracker, Eye-tracker data, Noise filters, Noise removal, Noisy data, Off-line filters, Online filtering, Virtual environments, virtual reality},

pubstate = {published},

tppubtype = {inproceedings}

}