O. O. Savkov, V. V. Moroz


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.


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


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