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<article 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" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="other" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Digital Diagnostics</journal-id><journal-title-group><journal-title xml:lang="en">Digital Diagnostics</journal-title><trans-title-group xml:lang="ru"><trans-title>Digital Diagnostics</trans-title></trans-title-group><trans-title-group xml:lang="zh"><trans-title>Digital Diagnostics</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2712-8490</issn><issn publication-format="electronic">2712-8962</issn><publisher><publisher-name xml:lang="en">Eco-Vector</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">701945</article-id><article-id pub-id-type="doi">10.17816/DD701945</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>Short communications</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Краткие сообщения</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="zh"><subject>短通讯</subject></subj-group><subj-group subj-group-type="article-type"><subject></subject></subj-group></article-categories><title-group><article-title xml:lang="en">Towards new quantitative features of Parkinson’s disease and essential tremor in electrooculographic signals: a cross-sectional population-based experimental study</article-title><trans-title-group xml:lang="ru"><trans-title>Поиск новых количественных признаков болезни Паркинсона и эссенциального тремора с применением анализа электроокулограмм: одномоментное популяционное экспериментальное исследование</trans-title></trans-title-group><trans-title-group xml:lang="zh"><trans-title/></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-1960-7289</contrib-id><name-alternatives><name xml:lang="en"><surname>Sushkova</surname><given-names>Olga S.</given-names></name><name xml:lang="ru"><surname>Сушкова</surname><given-names>Ольга Сергеевна</given-names></name><name xml:lang="zh"><surname></surname><given-names></given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>PhD, senior research associate</p></bio><bio xml:lang="ru"><p>кандидат технических наук, старший научный сотрудник</p></bio><email>o.sushkova@mail.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0811-7548</contrib-id><name-alternatives><name xml:lang="en"><surname>Morozov</surname><given-names>Alexei A.</given-names></name><name xml:lang="ru"><surname>Морозов</surname><given-names>Алексей Александрович</given-names></name><name xml:lang="zh"><surname></surname><given-names></given-names></name></name-alternatives><email>morozov@cplire.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0003-2736-5974</contrib-id><name-alternatives><name xml:lang="en"><surname>Vasilega</surname><given-names>Anastasia M.</given-names></name><name xml:lang="ru"><surname>Василега</surname><given-names>Анастасия Михайловна</given-names></name><name xml:lang="zh"><surname></surname><given-names></given-names></name></name-alternatives><email>logika0007@gmail.com</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0005-1685-673X</contrib-id><name-alternatives><name xml:lang="en"><surname>Vinarsky</surname><given-names>Alexander A.</given-names></name><name xml:lang="ru"><surname>Винарский</surname><given-names>Александр Анатольевич</given-names></name><name xml:lang="zh"><surname></surname><given-names></given-names></name></name-alternatives><email>vinarskii.aa@phystech.edu</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-2345-7145</contrib-id><name-alternatives><name xml:lang="en"><surname>Chigaleichik</surname><given-names>Larisa A.</given-names></name><name xml:lang="ru"><surname>Чигалейчик</surname><given-names>Лариса Анатольевна</given-names></name><name xml:lang="zh"><surname></surname><given-names></given-names></name></name-alternatives><email>chigalei4ick.lar@yandex.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-7986-1430</contrib-id><name-alternatives><name xml:lang="en"><surname>Poleschuk</surname><given-names>Vsevolod V.</given-names></name><name xml:lang="ru"><surname>Полещук</surname><given-names>Всеволод Владимирович</given-names></name><name xml:lang="zh"><surname></surname><given-names></given-names></name></name-alternatives><email>pol82@yandex.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2174-2412</contrib-id><name-alternatives><name xml:lang="en"><surname>Karabanov</surname><given-names>Alexei V.</given-names></name><name xml:lang="ru"><surname>Карабанов</surname><given-names>Алексей Вячеславович</given-names></name><name xml:lang="zh"><surname></surname><given-names></given-names></name></name-alternatives><email>doctor.karabanov@mail.ru</email><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Kotelnikov IRE RAS</institution></aff><aff><institution xml:lang="ru">ИРЭ им. В.А. Котельникова РАН</institution></aff><aff><institution xml:lang="zh"></institution></aff></aff-alternatives><aff id="aff2"><institution></institution></aff><pub-date date-type="preprint" iso-8601-date="2026-05-19" publication-format="electronic"><day>19</day><month>05</month><year>2026</year></pub-date><volume>7</volume><issue>2</issue><issue-title xml:lang="ru"/><history><date date-type="received" iso-8601-date="2026-01-30"><day>30</day><month>01</month><year>2026</year></date><date date-type="accepted" iso-8601-date="2026-04-23"><day>23</day><month>04</month><year>2026</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; , Eco-Vector</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; , Эко-вектор</copyright-statement><copyright-statement xml:lang="zh">Copyright ©; , Eco-Vector</copyright-statement><copyright-holder xml:lang="en">Eco-Vector</copyright-holder><copyright-holder xml:lang="ru">Эко-вектор</copyright-holder><copyright-holder xml:lang="zh">Eco-Vector</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by-nc-nd/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://jdigitaldiagnostics.com/DD/article/view/701945">https://jdigitaldiagnostics.com/DD/article/view/701945</self-uri><abstract xml:lang="en"><p><bold><italic>BACKGROUND:</italic></bold> Developing highly sensitive diagnostic methods for the widespread neurodegenerative diseases Parkinson’s disease (PD) and essential tremor (ET) is an important research challenge. Despite the rapid development of various diagnostic tools, including functional radioisotope neuroimaging, differential diagnosis of PD and ET is often challenging. The study of electrooculographic (EOG) signals is a promising approach to the development of new diagnostic methods for PD and ET. This paper is devoted to the search for new quantitative features of PD and ET.</p> <p><bold><italic>AIM:</italic></bold> The aim of the study is to identify specific quantitative features of saccadic eye movements in patients with PD and ET using a new method for statistical analysis of signals.</p> <p><bold><italic>METHODS:</italic></bold> The patients were examined during an outpatient examination. A visual stimulus was demonstrated on a monitor. A small white square moved upward on a black background within a 15°visual field. The stimulus was presented 8 times. The duration of the stimulus was 3 seconds. EOG signals were analyzed as is, without selection of segments in the signal. The following method and software were used for statistical signal analysis: a program for analysis of macrosaccade attributes and a program for a wave train analysis based on AUC diagrams.</p> <p><bold><italic>RESULTS:</italic></bold> The PD group included 17 patients with PD stages 1‑3. The ET group included 10 patients. A decrease in EOG macrosaccade latency was observed in both PD and ET patients in left and right eyes during the presentation of a series of the visual stimuli (Kendall’s tau-b,<italic> p</italic>≤0.031). The analysis of EOG microsaccades revealed wave trains that differentiated PD and ET patient groups (two-tailed Brunel-Munzel test; <italic>p</italic>≤0.03 for both eyes). A correlation was found between the number of wave trains in EOG of the left and right eyes in PD patients (Kendall’s tau-b is 0.515; <italic>p</italic>=0.011).</p> <p><bold><italic>CONCLUSION</italic></bold><italic>:</italic> The new methods of statistical signal analysis enabled the identification of new quantitative features in EOG in PD and ET patients. These new features were found in both macrosaccade and microsaccade parameters of EOG. The identified features are prospective for the development of new methods for differential diagnosis of PD and ET.</p></abstract><trans-abstract xml:lang="ru"><p><bold>Обоснование.</bold> Разработка высокочувствительных методов диагностики распространённых нейродегенеративных заболеваний – болезни Паркинсона (БП) и эссенциального тремора (ЭТ) – является важной научно-исследовательской задачей. Поскольку моторные симптомы этих заболеваний похожи, дифференциальная диагностика БП и ЭТ часто вызывает сложности, особенно на начальных стадиях болезни, несмотря на интенсивное развитие различных инструментальных методов диагностики, включая функциональную радиоизотопную нейровизуализацию. Анализ электроокулографических (ЭОГ) сигналов является перспективным подходом к разработке новых методов диагностики БП и ЭТ. Статья посвящена поиску новых количественных признаков БП и ЭТ в ЭОГ-сигналах.</p> <p><bold>Цель.</bold> Целью исследования является поиск специфичных количественных признаков саккадических движений глаз у пациентов с БП и ЭТ с применением нового, разработанного авторами метода статистического анализа биомедицинских сигналов.</p> <p><bold>Методы. </bold>Пациенты исследовались в рамках амбулаторного обследования. В ходе электроокулографического исследования пациентам демонстрировался визуальный стимул на экране монитора, а именно, белый квадратик на чёрном фоне, движущийся снизу вверх в поле зрения 15°. Стимул подавался 8 раз, длительность каждого предъявления стимула составляла 3 секунды. ЭОГ-сигналы анализировались «как есть», без выделения участков сигнала. Для статистического анализа сигналов использовались методы и программное обеспечение, разработанные авторами, а именно, программа анализа макросаккад и программа анализа всплескообразной электрической активности с помощью AUC-диаграмм.</p> <p><bold>Результаты. </bold>Группа пациентов с БП включала 17 пациентов с БП на 1‑3 стадиях. Группа пациентов с ЭТ включала 10 пациентов. Обнаружено явление уменьшения латентности макросаккад ЭОГ при подаче серии визуальных стимулов у пациентов с БП и у пациентов с ЭТ на левом и правом глазах (корреляция<italic> </italic>Кендалла,<italic> </italic><italic>p</italic>≤0,031). При анализе микросаккад ЭОГ обнаружены всплески, отличающие группу пациентов с БП от группы пациентов с ЭТ (двухсторонний тест Бруннера-Мюнцеля, для обоих глаз <italic>p</italic>≤0,03). Обнаружена корреляция между количеством всплесков в ЭОГ левого и правого глаз у пациентов с БП (корреляция Кендалла 0,515, <italic>p</italic>=0,011).</p> <p><bold>Выводы.</bold> Применение новых методов статистического анализа сигналов позволило выявить в сигналах ЭОГ новые количественные признаки, характеризующие пациентов с БП и пациентов с ЭТ. Новые признаки обнаружены как в параметрах макросаккад, так и в микросаккадах ЭОГ. Выявленные признаки могут быть использованы для разработки новых методов дифференциальной диагностики БП и ЭТ.</p></trans-abstract><trans-abstract xml:lang="zh"><p/></trans-abstract><kwd-group xml:lang="en"><kwd>Electrooculography</kwd><kwd>Parkinson’s disease</kwd><kwd>essential tremor</kwd><kwd>microsaccade</kwd><kwd>macrosaccade</kwd><kwd>AUC diagrams</kwd><kwd>wave train electrical activity analysis method.</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>Электроокулография</kwd><kwd>болезнь Паркинсона</kwd><kwd>эссенциальный тремор</kwd><kwd>микросаккада</kwd><kwd>макросаккада</kwd><kwd>AUC-диаграмма</kwd><kwd>метод анализа всплескообразной электрической активности.</kwd></kwd-group><funding-group><award-group><funding-source><institution-wrap><institution xml:lang="ru">Российский научный фонд</institution></institution-wrap></funding-source><award-id>22-75-10079-П</award-id></award-group></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Mei J, Desrosiers C, Frasnelli J. 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