A new algorithm for epilepsy seizure onset detection and spread estimation from EEG signals

Antonio Quintero-Rincón, Marcelo Pereyra, Carlos D’Giano, Hadj Batatia, Marcelo Risk

Research output: Contribution to journalArticle

9 Citations (Scopus)
54 Downloads (Pure)

Abstract

Appropriate diagnosis and treatment of epilepsy is a main public health issue. Patients suffering from this disease often exhibit different physical characterizations, which result from the synchronous and excessive discharge of a group of neurons in the cerebral cortex. Extracting this information using EEG signals is an important problem in biomedical signal processing. In this work we propose a new algorithm for seizure onset detection and spread estimation in epilepsy patients. The algorithm is based on a multilevel 1-D wavelet decomposition that captures the physiological brain frequency signals coupled with a generalized gaussian model. Preliminary experiments with signals from 30 epilepsy crisis and 11 subjects, suggest that the proposed methodology is a powerful tool for detecting the onset of epilepsy seizures with his spread across the brain.
Original languageEnglish
Article number012032
JournalJournal of Physics: Conference Series
Volume705
Issue numberconference 1
DOIs
Publication statusPublished - Apr 2016

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