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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">epilepsia</journal-id><journal-title-group><journal-title xml:lang="en">Epilepsy and paroxysmal conditions</journal-title><trans-title-group xml:lang="ru"><trans-title>Эпилепсия и пароксизмальные состояния</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2077-8333</issn><issn pub-type="epub">2311-4088</issn><publisher><publisher-name>IRBIS LLC</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.17749/2077-8333/epi.par.con.2025.212</article-id><article-id custom-type="elpub" pub-id-type="custom">epilepsia-1216</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>EEG РRACTICAL AND TECHNICAL ASPECTS</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ПРАКТИЧЕСКИЕ И ТЕХНИЧЕСКИЕ АСПЕКТЫ ЭЭГ</subject></subj-group></article-categories><title-group><article-title>ABCD microstates: a new word in EEG mathematical analysis</article-title><trans-title-group xml:lang="ru"><trans-title>Микросостояния ABCD: новое слово в математическом анализе ЭЭГ</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-2605-6830</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Иванов</surname><given-names>А. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Ivanov</surname><given-names>A. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Иванов Алексей Алексеевич</p><p>ул. Воронина, д. 5, Иваново 153032</p></bio><bio xml:lang="en"><p>Alexey A. Ivanov</p><p>5 Voronin Str., Ivanovo 153032</p></bio><email xlink:type="simple">iva@neurosoft.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Общество с ограниченной ответственностью «Нейрософт»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Neurosoft LLC</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>18</day><month>07</month><year>2025</year></pub-date><volume>17</volume><issue>2</issue><fpage>243</fpage><lpage>250</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Ivanov A.A., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Иванов А.А.</copyright-holder><copyright-holder xml:lang="en">Ivanov A.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.epilepsia.su/jour/article/view/1216">https://www.epilepsia.su/jour/article/view/1216</self-uri><abstract><p>With the advent of computer electroencephalographs, mathematical methods for EEG processing began to actively develop, some of which have found their application in current clinical practice, others – in brain-computer systems, some algorithms are used only in scientific research, whereas the remaining have shown inefficiency and become undemanded. Here, a fairly new approach to the mathematical processing of EEG signals is overviewed that allows not only to diagnose brain functional state, but also to predict the treatment outcomes in critically ill patients in intensive care units. Particularly, ABCD microstates will be discussed.</p></abstract><trans-abstract xml:lang="ru"><p>Электроэнцефалография (ЭЭГ) – эффективный метод изучения электрофизиологии мозга с высоким временным разрешением. С появлением компьютерных электроэнцефалографов начали активно развиваться и математические методы обработки ЭЭГ. Некоторые из них нашли применение в современной клинической практике, часть используется в системах «мозг – компьютер», отдельные алгоритмы подходят только для научных исследований, другие вовсе не показали свою эффективность и сейчас не востребованы. В данном материале представлен обзор довольно нового подхода к математической обработке ЭЭГ-сигналов, который позволяет не только проводить диагностику функционального состояния головного мозга, но и прогнозировать исходы лечения пациентов в критическом состоянии в отделениях реанимации и интенсивной терапии. Речь пойдет о микросостояниях ABCD.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>микросостояния ABCD</kwd><kwd>электроэнцефалография</kwd><kwd>количественная электроэнцефалография</kwd><kwd>математический анализ</kwd><kwd>программное обеспечение</kwd></kwd-group><kwd-group xml:lang="en"><kwd>ABCD microstates</kwd><kwd>electroencephalography</kwd><kwd>quantitative electroencephalography</kwd><kwd>mathematical analysis</kwd><kwd>software</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Рекомендации экспертного совета по нейрофизиологии Российской Противоэпилептической Лиги по проведению рутинной ЭЭГ. Эпилепсия и пароксизмальные состояния. 2016; 8 (4): 99–108.</mixed-citation><mixed-citation xml:lang="en">Guidelines for carrying out of routine EEG of Neurophysiology Expert Board of Russian League Against Epilepsy. 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