Epileptic Seizure Prediction Using Electroencephalogram Signals

This book presents an innovative method of EEG-based feature extraction and classification of seizures using EEG signals. It describes the methodology required for EEG analysis, seizure detection, seizure prediction and seizure classification. It contains a compilation of all techniques used in the literature and emphasises on newly proposed techniques. The book concentrates on a brief discussion of existing methods for epileptic seizure diagnosis and prediction, and introduces new efficient methods specifically for seizure prediction. Focuses on the mathematical models and machine learning algorithms from a perspective of clinical deployment of EEG-based Epileptic Seizure Prediction Discusses recent trends in seizure detection, prediction and classification methodologies Provides engineering solutions to severity or risk analysis of detected seizures at remote places Presents wearable solutions to seizure prediction Includes details of the use of deep learning for Epileptic Seizure Prediction using EEG This book acts as a reference for academicians and professionals who are working in the field of Computational Biomedical Engineering and are interested in the domain of EEG-based disease prediction.