Titre :

Supervision of time-frequency features selection in EEG signals by a human expert for brain–computer interfacing based on motor imagery

Auteur(s) :

Duprès, Alban [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Cabestaing, Francois [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Rouillard, Jose [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Titre de la manifestation scientifique :

Systems, Man, and Cybernetics (SMC)

Ville :

Budapest

Pays :

Hongrie

Date de début de la manifestation scientifique :

2016-10-09

Mot(s)-clé(s) en anglais :

brain–computer interface
motor imagery
EEG signal processing
sparse feature set
feature selection
human expertise

Discipline(s) HAL :

Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]

Résumé en anglais : [en]

In the context of brain–computer interfacing based on motor imagery, we propose a method which allows an expert to select manually time-frequency features. This selection is performed specifically for each subject, by ...
Lire la suite >In the context of brain–computer interfacing based on motor imagery, we propose a method which allows an expert to select manually time-frequency features. This selection is performed specifically for each subject, by analysing a set of curves that emphasize differences of brain activity recorded from electroencephalographic signals during the execution of various motor imagery tasks. We will show that expert knowledge is very valuable to supervise the selection of a sparse set of significant time-frequency features. Features selection is performed through a graphical user interface to allow an easy access to experts with no specific programming skills. In this paper, we compare our method with three fully-automatic features selection methods, using dataset 2A of BCI competition IV. Results are better for five of the nine subjects compared to the best competing method.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL