Detection and Prediction of Epileptic Seizures Based on EEG and Deep Learning - A review

Epilepsy is a pathology of the central neural system that is characterised by an abnormality in electrical activity within the brain. This aberrant electrical activity causes a variety of symptoms, including convulsions, aberrant behavior, unusual sensations, and, on occasion, loss of consciousness. It has been identified as one of the most common neurological disorders that have been observed by electroencephalograms (EEGs) in the past five years. It can occur suddenly and cause serious life-threatening complications. Therefore, their prediction and detection of these phenomena are imperative and of significant importance. Our literature review explores the use of deep learning from signals provided by electroencephalography (EEG). It is submitted that this technique would be greatly facilitated by the recording of brain activity using electrodes to be placed on the scalp. This analysis is based on 43 searches that are selected from various digital libraries. These searches are designed to evaluate the performance of the detection and prediction of epileptic seizures. Finally, an analysis of current challenges and prospects was carried out, leading to relevant recommendations.