An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries
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...
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| Format: | Article |
| Language: | English |
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Samara National Research University
2021-04-01
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| Series: | Компьютерная оптика |
| Subjects: | |
| Online Access: | http://computeroptics.ru/eng/KO/Annot/KO45-2/450218e.html |
| _version_ | 1818409533696901120 |
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| author | D.M. Murashov Y.V. Obukhov I.A. Kershner M.V. Sinkin |
| author_facet | D.M. Murashov Y.V. Obukhov I.A. Kershner M.V. Sinkin |
| author_sort | D.M. Murashov |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-14T10:01:08Z |
| format | Article |
| id | doaj.art-369eb1ef20f2426a843ae687eb69e2ce |
| institution | Directory Open Access Journal |
| issn | 0134-2452 2412-6179 |
| language | English |
| last_indexed | 2024-12-14T10:01:08Z |
| publishDate | 2021-04-01 |
| publisher | Samara National Research University |
| record_format | Article |
| series | Компьютерная оптика |
| spelling | doaj.art-369eb1ef20f2426a843ae687eb69e2ce2022-12-21T23:07:16ZengSamara National Research UniversityКомпьютерная оптика0134-24522412-61792021-04-0145230130510.18287/2412-6179-CO-798An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuriesD.M. Murashov0Y.V. Obukhov1I.A. Kershner2M.V. Sinkin3Federal Research Center "Computer Science and Control" of Russian Academy of Sciences, 119333, Russia, Moscow, Vavilov st., 40Kotel'nikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences, 125009, Russia, Moscow, Mokhovaya str., 11-7Kotel'nikov Institute of Radio Engineering and Electronics of Russian Academy of Sciences, 125009, Russia, Moscow, Mokhovaya str., 11-7Sklifosovsky Research Institute for Emergency Medicine of Moscow Healthcare Department, 129090, Russia, Moscow, Bolshaya Sukharevskaya Square, 3One 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.http://computeroptics.ru/eng/KO/Annot/KO45-2/450218e.htmlvideo eeg monitoring dataepileptic seizureoptical flowwaveletsridges of wavelet spectrogramsclinical applications |
| spellingShingle | D.M. Murashov Y.V. Obukhov I.A. Kershner M.V. Sinkin An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries Компьютерная оптика video eeg monitoring data epileptic seizure optical flow wavelets ridges of wavelet spectrograms clinical applications |
| title | An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries |
| title_full | An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries |
| title_fullStr | An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries |
| title_full_unstemmed | An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries |
| title_short | An algorithm for detecting events in video EEG monitoring data of patients with craniocerebral injuries |
| title_sort | algorithm for detecting events in video eeg monitoring data of patients with craniocerebral injuries |
| topic | video eeg monitoring data epileptic seizure optical flow wavelets ridges of wavelet spectrograms clinical applications |
| url | http://computeroptics.ru/eng/KO/Annot/KO45-2/450218e.html |
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