Joint Time-Frequency-Space Classification of EEG in a Brain-Computer Interface Application

: Brain-computer interface is a growing field of interest in human-computer interaction with diverse applications ranging from medicine to entertainment. In this paper, we present a system which allows for classification of mental tasks based on a joint time-frequency-space decorrelation, in which m...

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Bibliographic Details
Published inEURASIP journal on advances in signal processing Vol. 2003; no. 7; p. 253269
Main Authors Molina, Gary N Garcia, Ebrahimi, Touradj, Vesin, Jean-Marc
Format Journal Article
LanguageEnglish
Published BioMed Central Ltd 18.06.2003
SpringerOpen
Subjects
ambiguity function
brain-computer interface
EEG
multivariate signals classification
simultaneous diagonalization
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ISSN1687-6180
1687-6172
1687-6180
DOI10.1186/1687-6180-2003-253269

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Summary:: Brain-computer interface is a growing field of interest in human-computer interaction with diverse applications ranging from medicine to entertainment. In this paper, we present a system which allows for classification of mental tasks based on a joint time-frequency-space decorrelation, in which mental tasks are measured via electroencephalogram (EEG) signals. The efficiency of this approach was evaluated by means of real-time experimentations on two subjects performing three different mental tasks. To do so, a number of protocols for visualization, as well as training with and without feedback, were also developed. Obtained results show that it is possible to obtain good classification of simple mental tasks, in view of command and control, after a relatively small amount of training, with accuracies around 80%, and in real time.
ISSN:1687-6180
1687-6172
1687-6180
DOI:10.1186/1687-6180-2003-253269