Brain Computer Interfaces (BCIs) are interfaces that put the user in communication with an electronic device through the brain activity produced by the user herself. Non-invasive BCI are mainly based on electroencephalographic (EEG) signals. While using these systems, users become able to manipulate their brain activity to produce signals that will then be used to control computers or other devices without the aid of motor movements. Besides active BCI systems, in which the user directly control the system by a conscious and voluntary mental activity, there are passive BCI that can be used to recognize mental states, like the user's emotional state (in particular the level of engagement) during the interaction or according to a received stimulus. In this paper we describe a passive BCI experiment and its results, wherein users are exposed to a set of emotional artworks and the engagement measured through a BCI headset is compared to their explicit engagement, in order to test the reliability of BCI-based engagement detection.

Do BCIS detect user's engagement? The results of an empirical experiment with emotional artworks

Gena C.;Mattutino C.;De Carolis B.
2019

Abstract

Brain Computer Interfaces (BCIs) are interfaces that put the user in communication with an electronic device through the brain activity produced by the user herself. Non-invasive BCI are mainly based on electroencephalographic (EEG) signals. While using these systems, users become able to manipulate their brain activity to produce signals that will then be used to control computers or other devices without the aid of motor movements. Besides active BCI systems, in which the user directly control the system by a conscious and voluntary mental activity, there are passive BCI that can be used to recognize mental states, like the user's emotional state (in particular the level of engagement) during the interaction or according to a received stimulus. In this paper we describe a passive BCI experiment and its results, wherein users are exposed to a set of emotional artworks and the engagement measured through a BCI headset is compared to their explicit engagement, in order to test the reliability of BCI-based engagement detection.
27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019
cyp
2019
ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization
Association for Computing Machinery, Inc
387
391
9781450367110
http://dl.acm.org/citation.cfm?id=3314183
Affective computing; BCI; User modeling
Gena C.; Pirani S.; Mattutino C.; De Carolis B.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1729022
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