Automatc Detection of Epileptic Seizure using Time-Frequency Distributions

The aim of this work is to introduce a new method based on time frequency distribution for classifying the EEG signals. Some parameters are extracted using time-frequency distribution as inputs to a Feed-Forward Backpropagation Neural Networks (FBNN). The proposed method had better results with 98.25% accuracy compared to previously studied methods such as Wavelet transform, Entropy, Logistic regression and Lyapanov Exponent.