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.