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Abstract
In this paper, an algorithm for automated detecting diagnostic events in video channel of video and electroencephalographic (EEG) monitoring data is presented. The analysis of video sequences is focused on identifying a group of frames with high or very low (depending on the type of seizure) dynamics of informative areas according to a criterion calculated during processing of the optical flow. The preliminary results of the analysis of real clinical data are given and compared with data obtained from the synchronous EEG. The results showed the possibility in principle of reliable diagnosing epileptic seizures and distinguishing them from non-epileptic events.
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1 Federal Research Center “Computer Science and Control” of RAS, 119333, Moscow, Russia; Federal Research Center “Computer Science and Control” of RAS, 119333, Moscow, Russia
2 Kotel'nikov Institute of Radio Engineering and Electronics of RAS, 125009, Moscow, Russia; Kotel'nikov Institute of Radio Engineering and Electronics of RAS, 125009, Moscow, Russia
3 N.V. Sklifosovsky Research Institute for Emergency Medicine of Moscow Healthcare Department, 129090, Moscow, Russia; N.V. Sklifosovsky Research Institute for Emergency Medicine of Moscow Healthcare Department, 129090, Moscow, Russia