A strong adaptive and comprehensive evaluation of wavelet based epileptic EEG spike detection methods

Based on the ability of wavelet transform to detection of transient waves; recently it´s so usage to apply of wavelet transform detecting biomedical transient waves. On the other hand the best usual way in order to diagnosis, control and therapy different kinds of Epilepsy is to refer to patient´s EEG signals. Usually, in normal conditions of a patient, Epilepsy shows itself through EEG signals in the shape of transient waves. Identification of these waves using human eyes is so difficult that automatic detection methods based on signal processing, should have been applied as an auxiliary tool to help physician identify this waves. The most significant transient epileptic waves in EEG are spikes. Up to now, various methods are presented for detection of spikes, but a quantitative and comparative comprehensive evaluation hasn´t been performed. In this work, we have considered three wavelet based methods for detecting spike waves. Using simulated EEG signals and defined evaluation criterions; we have accurately evaluate these methods in comparison with together.