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An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries
D.M. Murashov 1, Y.V. Obukhov 2, I.A. Kershner 2, M.V. Sinkin 3

Federal Research Center "Computer Science and Control" of Russian Academy of Sciences,
119333, Russia, Moscow, Vavilov st., 40

Kotel'nikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences,
125009, Russia, Moscow, Mokhovaya str., 11-7,

Sklifosovsky Research Institute for Emergency Medicine of Moscow Healthcare Department
129090, Russia, Moscow, Bolshaya Sukharevskaya Square, 3

 PDF, 1748 kB

DOI: 10.18287/2412-6179-CO-798

Страницы: 301-305.

Язык статьи: English

One of the problems solved by analyzing the data of long-term Video EEG monitoring is the differentiation of epileptic and artifact events. For this, not only multichannel EEG signals are used, but also video data analysis, since traditional methods based on the analysis of EEG wavelet spectrograms cannot reliably distinguish an epileptic seizure from a chewing artifact. In this paper, we propose an algorithm for detecting artifact events based on a joint analysis of the level of the optical flow and the ridges of wavelet spectrograms. The preliminary results of the analysis of real clinical data are given. The results show the possibility in principle of reliable distinguishing non-epileptic events from epileptic seizures.

Ключевые слова:
video EEG monitoring data, epileptic seizure, optical flow, wavelets, ridges of wavelet spectrograms, clinical applications.

The work was carried out within the framework of the state task and partially was supported by the Russian Foundation for Basic Research, the project No 18-29-02035.

Murashov DM, Obukhov YV, Kershner IA, Sinkin MV. An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries. Computer Optics 2021; 45(2): 301-305. DOI: 10.18287/2412-6179-CO-798.


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