Operationalization of Conceptual Imagery for BCIs - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

Operationalization of Conceptual Imagery for BCIs

Résumé

We present a Brain Computer Interface (BCI) system in an asynchronous setting that allows classifying objects in their semantic categories (e.g. a hammer is a tool). For training, we use visual cues that are representative of the concepts (e.g. a hammer image for the concept of hammer). We evaluate the system in an offline synchronous setting and in an online asynchronous setting. We consider two scenarios: the first one, where concepts are in close semantic families (10 subjects) and the second where concepts are from distinctly different categories (10 subjects). We find that both have classification accuracies of 70% and above, although more distant conceptual categories lead to 5% more in classification accuracy.
Fichier principal
Vignette du fichier
edas.paper-1570103701-2.pdf (1.08 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01208428 , version 1 (02-10-2015)

Identifiants

Citer

Nataliya Kosmyna, Franck Tarpin-Bernard, Bertrand Rivet. Operationalization of Conceptual Imagery for BCIs. EUSIPCO 2015 - 23th European Signal Processing Conference, Aug 2015, Nice, France. pp.2726-2730, ⟨10.1109/EUSIPCO.2015.7362880⟩. ⟨hal-01208428⟩
268 Consultations
147 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More