By Topic

Pattern detection by cellular neuronal networks (CNN) in long-term recordings of a brain electrical activity in epilepsy

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Fischer, P. ; Inst. of Appl. Phys., Frankfurt Univ., Germany ; Tetzlaff, R.

About 0.5% of the world population is suffering from a focal epilepsy (J. Engel et al., 2003), which is a widely spread disease. The goal of the investigations discussed in this paper is an early detection of precursors of an impending epileptic seizure by the analysis of brain electrical activity of multi-electrode EEG recordings. Therefore, methods of nonlinear signal processing were used in CNN simulations. This investigation is based on long-term recordings of approximately one week length, where analysis algorithms proposed in previous investigations (C. Niederhoefer et al., 2003) have been generalised toward new feature extraction methods which are presented in this paper.

Published in:

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on  (Volume:1 )

Date of Conference:

25-29 July 2004