Modelling of Brain Consciousness based on Collaborative Adaptive Filters

Li, L. and Xia, Y. and Jelfs, B. and Cao, J. and Mandic, D. P. (2012) Modelling of Brain Consciousness based on Collaborative Adaptive Filters. Neurocomputing, 76 (1). pp. 182-196. (The full text of this publication is not available from this repository)

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Official URL
http://www.cs.kent.ac.uk/pubs/2012/3179

Abstract

A novel method for the discrimination between discrete states of brain consciousness is proposed, achieved through examination of nonlinear features within the electroencephalogram (EEG). To allow for real time modes of operation, a collaborative adaptive filtering architecture, using a convex combination of adaptive filters is implemented. The evolution of the mixing parameter within this structure is then used as an indication of the predominant nature of the EEG recordings. Simulations based upon a number of different filter combinations illustrate the suitability of this approach to differentiate between the coma and quasi-brain-death states based upon fundamental signal characteristics.

Item Type: Article
Uncontrolled keywords: determinacy analysis, Craig interpolants
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Science Technology and Medical Studies > School of Computing > Computational Intelligence Group
Faculties > Science Technology and Medical Studies > School of Computing > Future Computing Group
Depositing User: Caroline Li
Date Deposited: 21 Sep 2012 09:49
Last Modified: 21 Sep 2012 09:49
Resource URI: http://kar.kent.ac.uk/id/eprint/30831 (The current URI for this page, for reference purposes)
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