Title :
Determination of an optimal training strategy for a BCI classification task with LDA
Author :
Gareis, I.E. ; Acevedo, R.C. ; Atum, Y.V. ; Gentiletti, G.G. ; Banuelos, V.M. ; Rufiner, H.L.
Author_Institution :
Lab. de Ing. en Rehabilitacion e Investig. Neuromusculares y Sensoriales, Univ. Nac. de Entre Rios, Parana, Argentina
fDate :
April 27 2011-May 1 2011
Abstract :
Brain computer interfaces (BCIs) translate brain activity into computer commands. To enhance the performance of a BCI, it is necessary to improve the feature extraction techniques being applied to decode the users´ intentions. Objective comparison methods are needed to analyze different feature extraction techniques. One possibility is to use the classifier performance as a comparative measure. In this paper, we study the behavior of linear discriminant analysis (LDA) when used to distinguish between electroencephalographic (EEG) signals with and without the presence of event related potentials (ERPs).
Keywords :
bioelectric potentials; brain-computer interfaces; decoding; electroencephalography; feature extraction; handicapped aids; medical signal processing; signal classification; BCI classification task; EEG; ERP; LDA; brain activity; brain computer interfaces; decoding; electroencephalographic signals; event related potentials; feature extraction; linear discriminant analysis; optimal training strategy; Brain computer interfaces; Databases; Electroencephalography; Erbium; Feature extraction; Sensitivity; Training;
Conference_Titel :
Neural Engineering (NER), 2011 5th International IEEE/EMBS Conference on
Conference_Location :
Cancun
Print_ISBN :
978-1-4244-4140-2
DOI :
10.1109/NER.2011.5910543
