CISUC - Epileptic Seizure Prediction and The
CISUC

Epileptic Seizure Prediction and The

Authors

Abstract

Seizures prediction may substantially improve the quality of
life of epileptic patients. Processing EEG signals, by extracting a con-
venient set of features, is the most promising way to classify the brain
state and to predict with some antecedence its evolution to a seizure con-
dition. In this work neural networks are proposed as e ective classi ers
of brain state among 4 classes: interictal, preictal, ictal and postictal.
A two channels set of 26 features is extracted. By correlation analysis
and by extracting the principal components, a reduced features space is
obtained where, by an appropriate neural network, over 90% successful
classi cations are achieved, for dataset with several patients from the
Freiburg database

Keywords

Classification, Neural Networks, Feature Selection, PCA,Correlation, Epilepsy, Seizure Prediction, EEG Processing

Subject

epilepsy; seizure prediction; Fp7 projec

Related Project

EPILEPSIAE- Evolving Platform for Improving Living Expectation of Patients

Conference

19th International Conference on Artificial Neural Networks, September 2009


Cited by

Year 2015 : 1 citations

 Online epileptic seizure prediction using wavelet-based bi-phase correlation of electrical signals tomography
Z Vahabi, R Amirfattahi, F Shayegh… - International journal of …, 2015 - World Scientific
Considerable efforts have been made in order to predict seizures. Among these methods,
the ones that quantify synchronization between brain areas, are the most important methods.
However, to date, a practically acceptable result has not been reported. In this paper, we ...