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Brain 2 Communicate: EEG-based Affect Recognition to Augment Virtual Social Interactions

dc.contributor.authorRoth, Daniel
dc.contributor.authorWestermeier, Franziska
dc.contributor.authorBrübach, Larissa
dc.contributor.authorFeigl, Tobias
dc.contributor.authorSchell, Christian
dc.contributor.authorLatoschik, Marc Erich
dc.date.accessioned2019-09-05T01:06:05Z
dc.date.available2019-09-05T01:06:05Z
dc.date.issued2019
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/25205
dc.description.abstractThe perception and expression of emotion is a fundamental part of social interaction. This project aims to utilize neuronal signals to augment avatar-mediated communications. We recognize emotions with a brain-computer-interface (BCI) and supervised machine learning. Using an avatar-based communication interface that supports head tracking, gaze tracking, and speech to animation, we leverage the BCI-based affect detection to visualize emotional states.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofMensch und Computer 2019 - Workshopband
dc.relation.ispartofseriesMensch und Computer
dc.subjectbrain-computer interfaces
dc.subjectaugmented social interaction
dc.subjectavatars
dc.subjectshared virtual environments
dc.titleBrain 2 Communicate: EEG-based Affect Recognition to Augment Virtual Social Interactionsen
dc.typeText/Conference Poster
dc.pubPlaceBonn
mci.document.qualitydigidoc
mci.conference.sessiontitleMCI-WS24: User-embodied Interaction in Virtual Reality (UIVR)
mci.conference.locationHamburg
mci.conference.date8.-11. September 2019
dc.identifier.doi10.18420/muc2019-ws-571


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