A collaborative filtering approach for quasi-brain-death EEG analysis

Xia, Y. and Li, L. and Cao, J. and Golz, M. and Mandic, D. P. (2011) A collaborative filtering approach for quasi-brain-death EEG analysis. In: Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on. (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/2011/3181

Abstract

Evaluating the significance differences between the group of comatose patients and the group of brain death is important in the detection of brain death. This paper presents a novel method for the discrimination between discrete states of brain consciousness. Based on a collaborative adaptive filtering ar- chitecture using a convex combination of two heterogeneous adaptive filters, the evolution of the mixing parameter can be used as an indicator of the fundamental signal nature of different EEG recordings. Simulations illustrate the suitabil- ity of this approach to differentiate between the coma and quasi-brain-death states.

Item Type: Conference or workshop item (UNSPECIFIED)
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/30759 (The current URI for this page, for reference purposes)
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