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Dr. Eman Ahmed Abdel Ghaffar :: Publications:

Effect of Tuning TQWT Parameters on Epileptic Seizure Detection From EEG Signals
Authors: Eman A. Abdel Ghaffar
Year: 2017
Keywords: EEG signals, TQWT
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: IEEE international conference
Local/International: International
Paper Link: Not Available
Full paper Not Available
Supplementary materials Not Available

In this paper, we study the effect of tuning the tunable-Q wavelet transform (TQWT) parameters on analyzing the Electroencephalogram (EEG) signals used for detecting epileptic seizure. Publicly available Bonn University database is used in this study, fifteen different combinations were examined. TQWT is used to decompose each EEG signal into a valuable set of band limited signals (sub-bands), the value of the Q parameter is tuned from one to four and the number of sub-bands (J) from six to twenty two. Two statistical features were extracted from the subbands having the highest percentage of total signal energy. Knearest neighbor (K-NN) was used for classifying the EEG signals into either seizure or seizure-free. Our results clarify that, increasing the value of Q enhance the classification accuracy and best results were achieved at Q equals two.

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