Premium
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
Abstract 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.