New feature extraction approach for epileptic EEG signal detection using time-frequency distributions.

This paper describes a new method to identify seizures in electroencephalogram (EEG) signals using feature extraction in time-frequency distributions (TFDs). Particularly, the method extracts features from the Smoothed Pseudo Wigner-Ville distribution using tracks estimated from the McAulay-Quatieri sinusoidal model. The proposed features are the length, frequency, and energy of the principal track.