Detection singularity value of character wave in epileptic EEG by wavelet

Human epilepsy is an intrinsic brain pathology, whose activity varies depending on the type of epilepsy and is characterized by repetitive high-amplitude activity. The wavelet transform provides an important tool in signal analysis and feature extraction. The modulus maximum pair of the wavelet transform method is used to detect the singularity value of the sharps and spikes embedded in the background activities of the epilepsy electroencephalograph (EEG) signal. The wavelet transforms of singularities with fast oscillations have a particular behavior that is studied separately; they are measured from the modulus maxima of the wavelet transform. The efficacy of the proposed method has been tested with clinical EEG.