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dc.contributor.authorKrogmeier, Claudiaen_US
dc.contributor.authorMousas, Christosen_US
dc.contributor.editorHideaki Uchiyamaen_US
dc.contributor.editorJean-Marie Normanden_US
dc.date.accessioned2022-11-29T07:25:28Z
dc.date.available2022-11-29T07:25:28Z
dc.date.issued2022
dc.identifier.isbn978-3-03868-179-3
dc.identifier.issn1727-530X
dc.identifier.urihttps://doi.org/10.2312/egve.20221283
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/egve20221283
dc.description.abstractIn this work, we recorded brain activity data from participants who viewed 12 affective character animations in virtual reality. Frontal alpha asymmetry (FAA) scores were calculated from electroencephalography (EEG) data to understand objective affective responses to these animations. A subset of these animations were then annotated as either low FAA (meaning they elicited lower FAA responses), or high FAA (meaning they elicited higher FAA responses). Next, these annotated animations were used in a primary 2×2 study in which we a) examined if we could replicate FAA responses to low FAA and high FAA animations in a subsequent study, and b) investigated how the number of characters in the VR environment would influence FAA responses. Additionally, we compared FAA to self-reported affective responses to the four conditions (one character, low FAA; one character, high FAA; four characters, low FAA; four characters, high FAA). In this way, our research seeks to better understand objective and subjective emotional responses in VR. Results suggest that annotated FAA may not inform FAA responses to affective animations in a subsequent study when more characters are present. However, self-reported affective responses to the four conditions is in line with FAA annotated responses. We offer suggestions for the development of specific affective experiences in VR which are based on preliminary brain activity data.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Human-centered computing -> Virtual reality; User studies; Computing methodologies -> Perception; Animation
dc.subjectHuman centered computing
dc.subjectVirtual reality
dc.subjectUser studies
dc.subjectComputing methodologies
dc.subjectPerception
dc.subjectAnimation
dc.titleExploring EEG-Annotated Affective Animations in Virtual Reality: Suggestions for Improvementen_US
dc.description.seriesinformationICAT-EGVE 2022 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments
dc.description.sectionheadersCognition
dc.identifier.doi10.2312/egve.20221283
dc.identifier.pages121-130
dc.identifier.pages10 pages


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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License