A technique for detecting diagnostic events in video channel of synchronous video and electroencephalographic monitoring data

In this paper, a technique for automated detecting diagnostic events in the video channel of video and electroencephalographic monitoring data is presented. The technique is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed at detecting a group of frames characterized by high activity of frame regions. For detecting the frames, a criterion computed from the optical flow is proposed. The preliminary results of the analysis of real clinical data are presented. The intervals of synchronous muscle and brain activity, which may correspond to an epileptic seizure, are detected. These intervals can be used for diagnosing epileptic seizures and distinguishing them from non-epileptic events. Requirements for video shooting conditions are formulated.