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 men...

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Published in:EURASIP journal on advances in signal processing 2003-12, Vol.2003 (7), p.253269, Article 253269
Main Authors: Molina, Gary N. Garcia, Ebrahimi, Touradj, Vesin, Jean-Marc
Format: Article
Language:English
Subjects:
Classification
Cognitive tasks
Command and control
Electroencephalography
Human-computer interface
Real time
Time-frequency analysis
Training
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Ebrahimi, Touradj
Vesin, Jean-Marc
description 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.
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source Publicly Available Content Database; Springer Nature - SpringerLink Journals - Fully Open Access
subjects Classification
Cognitive tasks
Command and control
Electroencephalography
Human-computer interface
Real time
Time-frequency analysis
Training
title Joint Time-Frequency-Space Classification of EEG in a Brain-Computer Interface Application
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