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.

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 techniques described in the literature and emphasizes newly proposed techniques. The book includes 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 predictionDiscusses recent trends in seizure detection, prediction, and classification methodologiesProvides engineering solutions to severity or risk analysis of detected seizures at remote placesPresents wearable solutions to seizure predictionIncludes details of the use of deep learning for epileptic seizure prediction using EEGThis 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.