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A Matlab®-based software package, EPILAB, was developed for supporting researchers in performing studies on the prediction of epileptic seizures. It provides an intuitive and convenient graphical user interface. Fundamental concepts that are crucial for epileptic seizure prediction studies were implemented. This includes, for example, the development and statistical validation of prediction methodologies in long-term continuous recordings. Seizure prediction is usually based on electroencephalography (EEG) and electrocardiography (ECG) signals. EPILAB is able to process both EEG and ECG data stored in different formats. More than 35 time and frequency domain measures (features) can be extracted based on univariate and multivariate data analysis. These features can be post-processed and used for prediction purposes. The predictions may be conducted based on optimized thresholds or by applying classifications methods such as artificial neural networks, cellular neuronal networks, and support vector machines. EPILAB proved to be an efficient tool for seizure prediction, and aims to be a way to communicate, evaluate, and compare results and data among the seizure prediction community.

Original publication

DOI

10.1016/j.jneumeth.2011.07.002

Type

Journal article

Journal

J Neurosci Methods

Publication Date

15/09/2011

Volume

200

Pages

257 - 271

Keywords

Electrocardiography, Electroencephalography, Epilepsy, Humans, Predictive Value of Tests, Sensitivity and Specificity, Signal Processing, Computer-Assisted, Software, Support Vector Machine, Time Factors