Epileptic seizures had been considered unpredictable and sudden events until a few years ago. Recent results in literature showed that these seizures are likely to be stage of an epileptogenic process rather than an unpredictable and sudden event, and a predictable preictal phase has been hypothesized to occur between interictal and ictal periods. Indeed different studies endorsed this new hypothesis. Most of the researches have been focused on intracranial EEG analysis, whereas just few studies were carried out on scalp EEG. Our aim was to study the predictability of different kinds of seizures recorded from scalp EEG using the Adaptive Threshold Seizure Warning Algorithm (ATSWA). This technique is based on the estimation of the Short Term Maximun Lyapunov Exponent (STLmax) and on entrainment between critical electrodes.

Epileptic Seizures Prediction in Patients with Partial or Generalized Seizures

LA FORESTA, Fabio;Mammone N;MORABITO, Francesco Carlo
2008

Abstract

Epileptic seizures had been considered unpredictable and sudden events until a few years ago. Recent results in literature showed that these seizures are likely to be stage of an epileptogenic process rather than an unpredictable and sudden event, and a predictable preictal phase has been hypothesized to occur between interictal and ictal periods. Indeed different studies endorsed this new hypothesis. Most of the researches have been focused on intracranial EEG analysis, whereas just few studies were carried out on scalp EEG. Our aim was to study the predictability of different kinds of seizures recorded from scalp EEG using the Adaptive Threshold Seizure Warning Algorithm (ATSWA). This technique is based on the estimation of the Short Term Maximun Lyapunov Exponent (STLmax) and on entrainment between critical electrodes.
EEG; STLmax; Epileptic Seizures Prediction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/6650
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