Subject-adaptive steady-state visual evoked potential detection for brain-computer interface

Author

Chumerin, Nikolay ; Manyakov, Nikolay V. ; Combaz, Adrien ; Robben, Arne ; Van Vliet, Marijn ; Van Hulle, Marc M.

Author_Institution

Lab. for Neurofysiology, K.U. Leuven, Leuven, Belgium

Volume

1

fYear

2011

fDate

15-17 Sept. 2011

Firstpage

369

Lastpage

373

Abstract

We report on the development of a four command Brain-Computer Interface (BCI) based on steady-state visual evoked potential (SSVEP) responses detected from human electroencephalograms (EEGs). The proposed system combines spatial filtering, feature extraction and selection, and a classifier. Two types of classifiers were compared: one based on equal treatment of all harmonics in all EEG channels and the second based on preliminary training resulting in a weighted treatment of the harmonics. Results from six healthy subjects are evaluated.

Keywords

brain-computer interfaces; electroencephalography; feature extraction; medical signal processing; signal classification; spatial filters; visual evoked potentials; brain-computer interface; classifiers; electroencephalograms; feature extraction; feature selection; spatial filtering; subject-adaptive steady-state visual evoked potential detection; Decoding; Electroencephalography; Games; Harmonic analysis; Signal to noise ratio; Visualization; BCI; EEG; SSVEP; decoding;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2011 IEEE 6th International Conference on

Conference_Location

Prague

Print_ISBN

978-1-4577-1426-9

Type

conf

DOI

10.1109/IDAACS.2011.6072776

Filename

6072776