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Automated detection of a preseizure state: non‐linear EEG analysis in epilepsy by Cellular Nonlinear Networks and Volterra systems
Author(s) -
Tetzlaff Ronald,
Niederhöfer Christian,
Fischer Philipp
Publication year - 2006
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/cta.344
Subject(s) - realization (probability) , electroencephalography , nonlinear system , computer science , volterra series , feature (linguistics) , epilepsy , warning system , feature extraction , signal processing , artificial intelligence , pattern recognition (psychology) , mathematics , neuroscience , psychology , telecommunications , statistics , computer hardware , digital signal processing , linguistics , physics , philosophy , quantum mechanics
In this paper we present our work analysing electroencephalographic (EEG) signals for the detection of seizure precursors in epilepsy. Volterra systems and Cellular Nonlinear Networks are considered for a multidimensional signal analysis which is called the feature extraction problem throughout this contribution. Recent results obtained by applying a pattern detection algorithm and a non‐linear prediction of brain electrical activity will be discussed in detail. The aim of this interdisciplinary project is the realization of an implantable seizure warning and preventing system. Copyright © 2006 John Wiley & Sons, Ltd.