Prediction and Detection of Epilepsy Seizures Using Deep Learning Based Convolutional Neural Networks Models

Epilepsy is a disorderliness of nervous system in which person behaves abnormally and brain activity becomes unusual. Epilepsy problems are identified by electroencephalogram (EEG) that is recording of brain activity which is recorded in the form of electrical signals from machine and observed by Doctors. The Deep learning domain introduces a radical change in Computer Science Community, with the growth of Artificial Neural Network. These models are inspired from the structure of human brain and give the state of the art performance as compare to conventional Artificial Intelligence based Machine learning models. Convolution Neural Network (CNN) is the most exciting and effective type of Deep learning based Artificial Neural Network that works very precisely on image based EEG data sets. A literature survey to be made up of a systematic review of Convolution neural network in medical image analysis is presented to better understand the applications, benefits and challenges. This review article provides a concise introduction to CNN, its architecture and models. We discuss the benefits of Convolution neural Network for epileptic seizure detection. We will also discuss the challenges and future scope of Convolution neural Network in medical science.