Bispectrum Features and Multilayer Perceptron Classifier to Enhance Seizure Prediction

The ability to accurately forecast seizures could significantly improve the quality of life of patients with drug-refractory epilepsy. Prediction capabilities rely on the adequate identification of seizure activity precursors from electroencephalography recordings. Although a long list of features h...

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Published in:Scientific reports 2018-10, Vol.8 (1), p.15491-8, Article 15491
Main Authors: Bou Assi, Elie, Gagliano, Laura, Rihana, Sandy, Nguyen, Dang K., Sawan, Mohamad
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Language:English
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631/378/116/2396
692/617/375/178
Convulsions & seizures
Data processing
EEG
Entropy
Epilepsy
Humanities and Social Sciences
multidisciplinary
Quality of life
Science
Science (multidisciplinary)
Seizures
Signal processing
Statistical analysis
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description The ability to accurately forecast seizures could significantly improve the quality of life of patients with drug-refractory epilepsy. Prediction capabilities rely on the adequate identification of seizure activity precursors from electroencephalography recordings. Although a long list of features has been proposed, none of these is able to independently characterize the brain states during transition to a seizure. This work assessed the feasibility of using the bispectrum, an advanced signal processing technique based on higher order statistics, as a precursor of seizure activity. Quantitative features were extracted from the bispectrum and passed through two statistical tests to check for significant differences between preictal and interictal recordings. Results showed statistically significant differences (p 
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subjects 631/378/116/2396
692/617/375/178
Convulsions & seizures
Data processing
EEG
Entropy
Epilepsy
Humanities and Social Sciences
multidisciplinary
Quality of life
Science
Science (multidisciplinary)
Seizures
Signal processing
Statistical analysis
title Bispectrum Features and Multilayer Perceptron Classifier to Enhance Seizure Prediction
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