Epilepsy is a chronic neurological disorder of the brain that affects around 50 million people
worldwide. The early detection of epileptic seizures using electroencephalogram (EEG) …

Automated seizure prediction has a potential in epilepsy monitoring, diagnosis, and
rehabilitation. Electroencephalogram (EEG) is widely used for seizure detection and …

In this paper, a robust algorithm for disease type determination in brain magnetic resonance
image (MRI) is presented. The proposed method classifies MRI into normal or one of the …

In this study, a seizure prediction method is proposed based on a patient-specific approach
by extracting undulated global and local features of preictal/ictal and interictal periods of …

Epilepsy is the most common disorder of human brain. The goal of this paper is to present a
new method for classification of epileptic phases based on the sub-bands of …

Electroencephalogram (EEG) has a great potential for diagnosis and treatment of brain
disorders like epileptic seizure. Feature extraction and classification of EEG signals is the …

This paper provides a procedure to analyze and model EEG (electroencephalogram) signal
as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity …

Epilepsy is a continual disorder, the characteristic of which is recurrent, motiveless seizures.
Many people with epilepsy have more than one type of seizure and may have other …

This paper explores the data-driven properties of the empirical mode decomposition (EMD)
for detection of epileptic seizures. A new method in frequency domain is presented to …

This paper presents a method to characterize, identify and classify some pathological
Electroencephalogram (EEG) signals. We use some Time Frequency Distributions (TFDs) to …