Review of Techniques for Predicting Epileptic Seizure using EEG Signals

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Raj A. Sadaye, Sagar J. Parekh

Abstract

Epilepsy is a disorder that is characterized by seizures. Seizures are caused due to unusual electrical activity in the brain. Electroencephalogram (EEG) is used to read brain signal in form of 5 sub-bands viz. Alpha, Beta, Gamma, Theta and Delta. The features within each of theses sub-bands can be analysed and processed upon to predict the onset of a seizure. By accurate prediction of seizures, we can take preventive measures such as providing medication to reduce the severity of suffering of the patient. This pape r reviews the different techniques by which we can predict the onset of epileptic seizure using EEG signals. Each method utilizes one or more sub-bands of the EEG signal and classifies the patient records based on the features extracted through that set of sub-bands. Every method uses a different way to extract the sub bands. Also different classification algorithms are used in every method. We compare t e performance of each technique and analyse their efficacy.

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How to Cite
, R. A. S. S. J. P. “Review of Techniques for Predicting Epileptic Seizure Using EEG Signals”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 4, no. 11, Nov. 2016, pp. 09 -, doi:10.17762/ijritcc.v4i11.2594.
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