Epileptic seizure prediction based on EEG spikes detection of ictal-preictal states.

Itaf Ben Slimen,Larbi Boubchir,Hassene Seddik

doi:10.7555/jbr.34.20190097

Itaf Ben Slimen, Larbi Boubchir + Show 1 more

Open Access

https://doi.org/10.7555/jbr.34.20190097

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Abstract

Epileptic seizures are known for their unpredictable nature. However, recent research provides that the transition to seizure event is not random but the result of evidence accumulations. Therefore, a reliable method capable to detect these indications can predict seizures and improve the life quality of epileptic patients. Seizures periods are generally characterized by epileptiform discharges with different changes including spike rate variation according to the shapes, spikes, and the amplitude. In this study, spike rate is used as the indicator to anticipate seizures in electroencephalogram (EEG) signal. Spikes detection step is used in EEG signal during interictal, preictal, and ictal periods followed by a mean filter to smooth the spike number. The maximum spike rate in interictal periods is used as an indicator to predict seizures. When the spike number in the preictal period exceeds the threshold, an alarm is triggered. Using the CHB-MIT database, the proposed approach has ensured 92% accuracy in seizure prediction for all patients.

Highlights

Epilepsy is a neurological disorder disease characterized by sudden and disturbed movements of the body, and can be accompanied by excessive electrical discharges, loss of consciousness, and loss of muscle control[1,2]
Epileptiform in electroencephalogram (EEG) activity has been categorized by three periods that the ictal period refers to a seizure event; the preictal period is the state immediately before the epileptic seizure, and the interictal period refers the state between seizures
We proposed a prediction approach for epileptic seizures based on the spike number of EEG signals

Summary

Introduction

Epilepsy is a neurological disorder disease characterized by sudden and disturbed movements of the body, and can be accompanied by excessive electrical discharges, loss of consciousness, and loss of muscle control[1,2]. Seizures can be controlled by anticonvulsant therapy. While for about 25% of epileptic cases, no treatment is available, yet. A reliable and effective prediction method to anticipate the onset of seizures could improve the quality of life of these patients who are constantly facing the fear of random seizure occurrences. Prediction of epileptic seizures has been the goal of many researchers since the 1990s. Researchers have claimed that epileptic seizures were not abrupt, but were manifested a few minutes before the seizure onset. Epileptiform in electroencephalogram (EEG) activity has been categorized by three periods that the ictal period refers to a seizure event; the preictal period is the state immediately before the epileptic seizure, and the interictal period refers the state between seizures (seizure free)

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