High frequency oscillations have been recently proposed as a new biomarker of seizure onset zone. Marking epileptic discharge is highly time-consuming

easy to get false detection

and the relation between discharge and seizure still leaves much to define. This paper presents a fast automated detection method based on the difference of power spectral density in each channel

and similarity of filtered signal enveloped on epilepsy propagation path

and also the combination with complex Morlet wavelet transform to classify high frequency oscillations.The results obtained in 4 clinical cases show high performance in terms of sensitivity and specificity which can be considered as an effective method in preoperative localization.