EGG SIGNAL ANALYSIS BASED ON PSEUDO WIGNER-VILLE DISTRIBUTION

Authors

  • O. O. Savkov Computational Mathematics Department of I. I. Mechnikov Odessa National University, Ukraine, Ukraine
  • V. V. Moroz Computational Mathematics Department of I. I. Mechnikov Odessa National University, Ukraine, Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2015-1-4

Keywords:

EEG signal, time-frequency analysis, short-time Fourier transform, Wigner-Ville distribution.

Abstract

The problem of selection of electroencephalographic rhythms and epileptiform activity search was investigated. The object of study is the
process of extracting the EEG phenomena. The subject of study is time-frequency analysis methods of EEG signals. The purpose of the work is to improve the accuracy of diagnosis of psychological, psycho-somatic, neurotic and cognitive disorders. A review of electroencephalographic process and EEG artifacts was given. Types of EEG rhythms and phenomena, that have specific timefrequency characteristics, were considered. A method for electroencephalographic phenomena selection that is based on the extreme values analysis of spectral density function of smoothed pseudo Wigner-Ville distribution was proposed. Proposed method was compared with the short-time Fourier transform. As a quality criteria for analyzed methods was chosen the time-frequency resolution of obtained spectral density functions. Computational experiments on EEG epochs set that contains high-frequency phenomena were made. Software that automates EEG
analysis process and builds results visualization was developed.
The experimental results show the advantages of this approach in the time-frequency resolution compared with short-time Fourier transform, and allow to recommend the proposed method for practical use for EEG rhythms separation and high-frequency phenomena selection.

References

Collura F. T. History and Evolution of Electroencephalographic Instruments and Techniques / F. T. Collura // Journal of Clinical Neurophysiology. – 1993. – № 10 (4).– P. 476–504. 2. Sanei S. EEG signal processing / S. Sanei, J. Chambers. – Chichester : John Wiley & Sons Ltd, 2007. – 312 p. 3. Juozapavicius A. EEG analysis – automatic spike detection / A. Juozapavicius, G. Bacevicius, D. Bugelskis, R. Samaitiene // Nonlinear Analysis : Modelling and Control. – 2011. – Vol. 16, № 4. – P. 375–386. 4. Tzallas A. T. Epileptic Seizure Detection in EEGs Using Time-Frequency Analysis / A. T. Tzallas, M. G. Tsipouras, D. I. Fotiadis // IEEE Transactions On Information Technology In Biomedicine. – 2009. – Vol. 13, № 5. – P. 703–710. 5. Costaab J. Sleep Spindles Detection : a Mixed Method using STFT and WMSD / J. Costaab, M. Ortigueirab, A. Batistab, T. Paiva // International Journal of Bioelectromagnetism. – 2012. – Vol. 14, № 4. – P. 229–233. 6. Вишнивецкий О. В. Вигнер-анализ в задачах космической радиофизики / О. В. Вишнивецкий, О. В. Лазоренко // Вісник Харківського національного університету. Серія «Радіофізи- ка та електроніка». – 2010. – № 927, Вип. 16. – С. 89–95. 7. Лупов С. Ю. Модификация преобразования Вигнера-Виля для анализа интерферометрических данных газодинамических процессов / С. Ю. Лупов, В. И. Кривошеев // Вестник Нижегородского университета. – 2011. – № 5 (3). – С. 95–103. 8. Вишневецкий О. В. Анализ нелинейных волновых процессов при помощи преобразования Вигнера / О. В. Вишневецкий, О. В. Лазоренко, Л. Ф. Черногор // Радиофизика и радиоастрономия. – 2007. – T. 12, № 3. – С. 295–310. 9. Mohseni H. R. Automatic Detection of Epileptic Seizure using Time-Frequency Distributions / H. R. Mohseni, A. Maghsoudi, M. H. Kadbi, J. Hashemi, A. Ashourvan // Conference Paper : Advances in Medical, Signal and Information Processing. – Tehran : Sharif University of Technology, 2006. – Access mode : http://www. r e s e a r c h g a t e . n e t / p u b l i c a t i o n / 4 2 5 1 9 6 0 _Automatc_Detection_of_Epileptic_Seizure_using_TimeFrequency_Distributions 10. Guerrero-Mosquera C. New feature extraction approach for epileptic EEG signal detection using time-frequency distributions / C. Guerrero-Mosquera, A. Malanda Trigueros, J. I. Franco, Á. Navia-Vázquez // Medical & Biological Engineering & Computing. – April 2010. – Vol. 48 (4). – P. 321–330.

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Published

2014-11-17

How to Cite

Savkov, O. O., & Moroz, V. V. (2014). EGG SIGNAL ANALYSIS BASED ON PSEUDO WIGNER-VILLE DISTRIBUTION. Radio Electronics, Computer Science, Control, (1). https://doi.org/10.15588/1607-3274-2015-1-4

Issue

No. 1 (2015): Radio Electronics, Computer Science, Control

Section

Mathematical and computer modelling

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Copyright (c) 2015 O. O. Savkov, V. V. Moroz

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