Authors:
Nikolay V. Manyakov
;
Nikolay Chumerin
;
Adrien Combaz
;
Arne Robben
and
Mark M. Van Hulle
Affiliation:
K. U. Leuven, Belgium
Keyword(s):
Steady-state visual evoked potential, EEG, Decoding, Brain-computer interafce.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Computational Neuroscience
;
Computer-Supported Education
;
Domain Applications and Case Studies
;
Fuzzy Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Industrial, Financial and Medical Applications
;
Methodologies and Methods
;
Neural Networks
;
Neurocomputing
;
Neuroinformatics and Bioinformatics
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
In this paper, we propose a new time domain method for decoding the steady-state visual evoked potential recorded while the subject is looking at stimuli flickering with constant frequencies. Using several such stimuli, with different frequencies, a brain-computer interface can be built. We have assessed the influence of the number of electrodes on the decoding accuracy. A comparison between active wet- and bristle dry electrodes were made. The dependence between accuracy and the length of the EEG interval used for decoding
was shown.