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

Daniel Roth; Franziska Westermeier; Larissa Brübach; Tobias Feigl; Christian Schell; Marc Erich Latoschik

doi:10.18420/muc2019-ws-571

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

Daniel Roth, Franziska Westermeier, Larissa Brübach, Tobias Feigl, Christian Schell, Marc Erich Latoschik

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

The 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.

Original language	English
Pages (from-to)	564-565
Number of pages	2
Journal	Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
DOIs	https://doi.org/10.18420/muc2019-ws-571
State	Published - 2019
Externally published	Yes
Event	Proceedings of the Mensch und Computer 2019, MuC 2019 - Workshop on Konstruktion und praktischer Einsatz von User Experience Fragebogen - Proceedings of the Human and Computer 2019, MuC 2019 - Workshop on Construction and Practical Use of User Experience Questionnaires - Hamburg, Germany Duration: 8 Sep 2019 → 11 Sep 2019

Keywords

affective computing
avatars
brain-computer interfaces

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10.18420/muc2019-ws-571

Cite this

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title = "Brain 2 Communicate: EEG-based Affect Recognition to Augment Virtual Social Interactions",

abstract = "The 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.",

keywords = "affective computing, avatars, brain-computer interfaces",

author = "Daniel Roth and Franziska Westermeier and Larissa Br{\"u}bach and Tobias Feigl and Christian Schell and Latoschik, {Marc Erich}",

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year = "2019",

doi = "10.18420/muc2019-ws-571",

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pages = "564--565",

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issn = "1617-5468",

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AU - Roth, Daniel

AU - Westermeier, Franziska

AU - Brübach, Larissa

AU - Feigl, Tobias

AU - Schell, Christian

AU - Latoschik, Marc Erich

N1 - Publisher Copyright: © Proceedings of the Mensch und Computer 2019 Workshop on User-Embodied Interaction in Virtual Reality.

PY - 2019

Y1 - 2019

N2 - The 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.

AB - The 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.

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KW - avatars

KW - brain-computer interfaces

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DO - 10.18420/muc2019-ws-571

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JO - Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)

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Y2 - 8 September 2019 through 11 September 2019

ER -

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

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