Detection singularity value of character wave in epileptic EEG by Wavelet

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