Automated Detection of Epilepsy using Wavelet Features
Published in Research Journal of Pharmacy and Technology, 2015
This paper is about application of Machine Learning based supervised learning approach in order to classify the Ictal and EEG signals. Neural network classifier is used for the purpose of classification and set of EEG signals are taken from the large medical database. Discrete Wavelet transform is used for feature extraction and confusion matrices are computed in terms of sensitivity,specifity and accuracy once the classification is done.