Samara University Repository
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| Title: | Auto- and cross-correlation patterns in the diagnosis of obsessive-compulsive disorder using electroencephalogram analysis |
| Keywords: | diagnostics living systems electroencephalograms time signal analysis obsessive-compulsive disorder memory function formalism |
| Issue Date: | 2023 |
| Citation: | Elenev, A. Auto- and cross-correlation patterns in the diagnosis of obsessive-compulsive disorder using electroencephalogram analysis / A. Elenev, S. Demin, O. Panischev // Информационные технологии и нанотехнологии (ИТНТ-2023) : сб. тр. по материалам IX Междунар. конф. и молодеж. шк. (г. Самара, 17-23 апр. 2023 г.): в 6 т. / М-во науки и высш. образования Рос. Федерации, Самар. нац. исслед. ун-т им. С. П. Королева (Самар. ун-т), Ин-т систем обраб. изобр. РАН - Фил. Федер. науч.-исслед. центра "Кристаллография и фотоника" Рос. акад. наук. - Самара : Изд-во Самар. ун-та, 2023Т. 6: Информационные технологии в биомедицине / под ред. В. П. Захарова. - 2023. - С. 061612. |
| Abstract: | In this work auto- and cross-correlation patterns in the diagnosis of obsessive-compulsive disorder are investigated. Analysis of electroencephalograms was made bythe author's method: Memory Functions Formalism. For autocorrelations, the subject of the study was the non-Markov parameter. The most informative electrodes were found for 30 subjects, in which the greatest difference was observed between the non-Markov parameter for the group of patients and conditionally healthy people. For cross-correlations,synchronization effects were investigated, which were significantly different for the patients and conditionally healthy group. The results obtained will be of interest to sciences such as data sciences, computational biophysics, physics of living systems and psychiatry. |
| URI: | http://repo.ssau.ru/jspui/handle/123456789/13205 |
| Appears in Collections: | Информационные технологии и нанотехнологии |
| File | Size | Format | |
|---|---|---|---|
| 978-5-7883-1922-3_2023-061612.pdf | 400.01 kB | Adobe PDF | View/Open |
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