Performance Analysis of Epilepsy Risk Level From EEG Signals

This Book describes the epilepsy disorder and it is characterized by the existence of abnormal synchronous discharges in large ensembles of neurons in brain structures. These discharges appear either during seizures (interictal periods) or between seizures (interictal periods). Epileptic seizures are manifestations of epilepsy, which are recorded using the EEG. The objective of this work is to classify the risk level of Epileptic EEG using HMM. The dimensionality reduction of signal is done using various modules like Singular value Decomposition and vector quantization. Each of this method has its own methodology of data decomposition. Training sequence from the dimensionally reduced data is finally classified by the HMM. The HMM is used to classify the risk levels of epilepsy based on extracted parameters from EEG signals of the patient.