Palaniappan, Ramaswamy, Raveendran, P. (2001) Cognitive task prediction using parametric spectral analysis of EEG signals. Malaysian Journal of Computer Science, 14 (1). pp. 58-67. ISSN 0127-9084. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:70767)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. |
Abstract
In this paper, we are proposing a method to predict cognitive tasks performed by the human brain using spectral analysis of electrical signals extracted from the scalp of the brain. These electrical signals, which are generated by the synapses and neurons in the brain, are also known as Electroencephalogram (EEG) signals. The EEG signals are analysed using autoregressive spectral analysis, a type of modern parametric spectral analysis method, which comparatively yield better power spectrum over the classical Fourier methods. Power spectral densities of the EEG signals are used to train a Fuzzy ARTMAP network to predict the respective cognitive tasks. In our experimental study, we have analysed 3 subjects performing 2 different cognitive tasks and our average results of 72.22% to 93.05% for each subject show that it is highly possible to predict cognitive tasks based on EEG signals. This can be used as a mode of communication or wheelchair control for paralysed patients and also in EEG biofeedback systems.
Item Type: | Article |
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Additional information: | Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - Malays. J. Comput. Sci. [Field not mapped to EPrints] AD - Dept. of Electrical and Telecommunication, Engineering Faculty, University of Malaya, 50603 Kuala Lumpur, Malaysia [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Article [Field not mapped to EPrints] |
Uncontrolled keywords: | Autoregressive spectral analysis, Burg's algorithm, Cognitive task, EEG, Fuzzy ARTMAP |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Palaniappan Ramaswamy |
Date Deposited: | 15 Dec 2018 13:48 UTC |
Last Modified: | 05 Nov 2024 12:33 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/70767 (The current URI for this page, for reference purposes) |
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