In the near future our brain will be connected to many applications. Recently research has concentrated on using the Brain Computer Interface (BCI) passively to recognize particular users' mental states. In this paper, we explore the possibility to harness electroencephalograph (EEG) signals captured by off-The-shelf EEG low-cost headsets to understand if an exhibition piece is of interest for a visitor. This information can be used to enrich the user profile and consequently to suggest artworks to see during the visit according to a recommendation strategy. The results of the exploratory study show the feasibility of the proposed approach.
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|Titolo:||BrainArt: A BCI-based assessment of user's interests in a museum visit|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|