Department of Biomedical Engineering, University of Tabriz, Tabriz, Iran
Research Article
Epileptic seizure prediction using one channel EEG signal and 2 D-convolutional neural networks
Author(s): Golamali Alizadeh*, Tohidy Yousefi Rezaii and Saeed Meshgini
Purpose: Epilepsy is a neurological disorder affecting more than 55 million people worldwide. Predicting epileptic seizures will improve the lives of people with epileptic seizures. Currently, the diagnosis of an epileptic attack and the analysis of recorded brain activity is performed by a neurologist, which is often accompanied by human error. Recently, researchers have been looking to design and build an automatic system to detect and estimate the occurrence of epilepsy.
Methods: In the present study, two new-fangled methods were proposed based on brain signals and a Convolutional Neural Network (CNN). In this research, Pulse Width Modulation (PWM) is used to create features.
Results and conclusion: Numerous experiments were performed and the accuracy of estimating epilepsy of the proposed methods was achieved i.. Read More»
Neurological Disorders received 1343 citations as per Google Scholar report