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Modelling of brain consciousness based on collaborative adaptive filters

Li, Ling, Xia, Yili, Jelfs, Beth, Cao, Jianting, Mandic, Danilo P. (2012) Modelling of brain consciousness based on collaborative adaptive filters. Neurocomputing, 76 (1). pp. 36-43. ISSN 0925-2312. (doi:10.1016/j.neucom.2011.05.038) (KAR id:93737)


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
DOI/Identification number: 10.1016/j.neucom.2011.05.038
Additional information: Seventh International Symposium on Neural Networks (ISNN 2010) Advances in Web Intelligence
Uncontrolled keywords: Collaborative adaptive filtering, EEG, Quasi-brain-death (QBD), Coma, Signal nonlinearity
Subjects: Q Science
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.87 Neural computers, neural networks
R Medicine
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Caroline Li
Date Deposited: 25 Mar 2022 10:03 UTC
Last Modified: 08 Sep 2022 14:26 UTC
Resource URI: (The current URI for this page, for reference purposes)

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