HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Artificial Neural Networks to extract Knowledge from EEG

Frédéric Alexandre 1 Nizar Kerkeni 1 Khaled Ben Khalifa Mohamed Hédi Bédoui
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : EEG signals are very difficult to interpret because they are dynamic, non-linear and non-stationary signals. Human expertise also indicates that multi-level analysis must be performed to integrate various sources of knowledge. In this paper, we review these difficulties and propose that artificial neural networks could be good candidates to handle such a difficult problem.
Document type :
Conference papers
Complete list of metadata

https://hal.inria.fr/inria-00001258
Contributor : Agnès Vidard Connect in order to contact the contributor
Submitted on : Tuesday, April 18, 2006 - 2:46:21 PM
Last modification on : Friday, February 4, 2022 - 3:30:22 AM

Identifiers

  • HAL Id : inria-00001258, version 1

Collections

Citation

Frédéric Alexandre, Nizar Kerkeni, Khaled Ben Khalifa, Mohamed Hédi Bédoui. Artificial Neural Networks to extract Knowledge from EEG. The IASTED International Conference on Biomedical Engineering - BioMED2005, Feb 2005, Innsbruck/Austria. ⟨inria-00001258⟩

Share

Metrics

Record views

162