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Comparative Study of Time Frequency Analysis Application on Abnormal EEG Signals

Abstract : This paper presents a time-frequency analysis for some pathological Electroencephalogram (EEG) signals. The proposed method is to characterize some pathological EEG signals using some time-frequency distributions (TFD). TFDs are useful tools for analyzing the non-stationary signals such as EEG signals. We have used spectrogram (SP), Choi-Williams Distribution (CWD) and Smoothed Pseudo Wigner Ville Distribution (SPWVD) in conjunction with Rényi entropy (RE) to calculate the best value of their parameters. The study is conducted on some case of epileptic seizure of EEG signals collected on a known database. The best values of the analysis parameters are extracted by the evaluation of the minimization of the RE values. The results have permit to visualize in time domain some pathological EEG signals. Also, the Rényi marginal entropy (RME) has been used in order to identify the peak seizure. The characterization is achieved by evaluating the frequency bands using the marginal frequency (MF).
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Submitted on : Thursday, January 26, 2017 - 10:54:43 AM
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A. Ridouh, Daoud Boutana, Messaoud Benidir. Comparative Study of Time Frequency Analysis Application on Abnormal EEG Signals. Mohammed Chadli, Sofiane Bououden, Ivan Zelinka. Recent Advances in Electrical Engineering and Control Applications , 411, Springer International Publishing, pp.355-368, 2016, Lecture Notes in Electrical Engineering 978-3-319-48928-5. ⟨10.1007/978-3-319-48929-2_28⟩. ⟨hal-01446636⟩



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