Book
Epileptic Seizure Prediction and the Dimensionality Reduction Problem.
| Title: | Epileptic Seizure Prediction and the Dimensionality Reduction Problem. |
|---|---|
| Authors: | Ventura, André, Franco, João M., Ramos, João P., Direito, Bruno, Dourado, António |
| Source: | Artificial Neural Networks - ICANN 2009 (9783642042768); 2009, p1-9, 9p |
| Abstract: | Seizures prediction may substantially improve the quality of life of epileptic patients. Processing EEG signals, by extracting a convenient set of features, is the most promising way to classify the brain state and to predict with some antecedence its evolution to a seizure condition. In this work neural networks are proposed as effective classifiers 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 classifications are achieved, for dataset with several patients from the Freiburg database. [ABSTRACT FROM AUTHOR] |
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| DOI: | 10.1007/978-3-642-04277-5_1 |
| Database: | Complementary Index |
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