An efficient P300-based brain-computer interface for disabled subjects

Détails

ID Serval
serval:BIB_7055D430DA1C
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
An efficient P300-based brain-computer interface for disabled subjects
Périodique
Journal of Neuroscience Methods
Auteur(s)
Hoffmann  U., Vesin  J. M., Ebrahimi  T., Diserens  K.
ISSN
0165-0270
Statut éditorial
Publié
Date de publication
2007
Peer-reviewed
Oui
Volume
167
Numéro
1
Pages
115-125
Résumé
A brain-computer interface (BCI) is a communication system that translates brain-activity into commands for a computer or other devices. In other words, a BCI allows users to act on their environment by using only brain-activity, without using peripheral nerves and muscles. In this paper, we present a BCI that achieves high classification accuracy and high bitrates for both disabled and able-bodied subjects. The system is based on the P300 evoked potential and is tested with five severely disabled and four able-bodied subjects. For four of the disabled subjects classification accuracies of 100% are obtained. The bitrates obtained for the disabled subjects range between 10 and 25bits/min. The effect of different electrode configurations and machine learning algorithms on classification accuracy is tested. Further factors that are possibly important for obtaining good classification accuracy in P300-based BCI systems for disabled subjects are discussed.
Mots-clé
Adult , Brain/*physiopathology , Brain Diseases/*physiopathology , Brain Mapping , Disabled Persons , Electroencephalography , Event-Related Potentials, P300 , Female , Humans , Male , Middle Aged , Numerical Analysis, Computer-Assisted , Photic Stimulation/methods , Reaction Time , User-Computer Interface
Pubmed
Web of science
Création de la notice
25/01/2008 12:42
Dernière modification de la notice
20/08/2019 15:29
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