A Novel Approach on Epileptic Seizures Detection Using Convolutional Neural Network

Epileptic seizures are observed in almost all age groups and has become a predominant issue. Electroencephalogram (EEG) is a very common modality used to record the brain signals. Understanding the cortical connectivity of brain is still remaining as a challenging task and needs highly skilled neuro specialists. Humans are prone to error and so as doctors too, hence the automatic detection of such seizures is very important in order to take proper action. Although many approaches have been tried by many researchers to achieve a better accuracy and the robustness is still a challenging task. In this work, convolutional neural network (CNN) is used to achieve a better accuracy with robustness using EEG signals. Very few convolutional layers are used along with Relu as activation function. CNN is fed with these EEG signals for classification purpose. This model works well in contrast to the present traditional models.