RUDN Journal of Engineering ResearchRUDN Journal of Engineering ResearchВестник Российского университета дружбы народов. Серия: Инженерные исследования2312-81432312-8151Peoples’ Friendship University of Russia named after Patrice Lumumba (RUDN University)4834710.22363/2312-8143-2025-26-4-447-456BLXPCYArticlesСтатьиResearch ArticleDigital Modelling of Low-Frequency ECG Signals DenoisingЦифровое моделирование снижения шума низкочастотных сигналов ЭКГhttps://orcid.org/0009-0005-6632-91021127-5326KurbanovSinan V.КурбановСинан Владимирович

Postgraduate student of the Department of Mechanics and Control Processes, Academy of Engineering

аспирант кафедры механики и процессов управления, инженерная академия

ya.sinan@yandex.ruhttps://orcid.org/0000-0003-0359-08978247-7310AndrikovDenis A.АндриковДенис Анатольевич

Ph.D. (Technical Sciences), Associate Professor of the Department of Mechanics and Control Processes, Academy of Engineering

кандидат технических наук, доцент кафедры механики процессов и управления, инженерная академия

andrikovdenis@mail.ruhttps://orcid.org/0000-0002-9089-14119696-6864AgasievaSvetlana V.АгасиеваСветлана Викторовна

Ph.D. (Technical Sciences), Associate Professor of the Department of Nanotechnology and Microsystem Engineering, Academy of Engineering

кандидат технических наук, доцент кафедры нанотехнологий и микросистемной техники, инженерная академия

agasieva-sv@rudn.ruhttps://orcid.org/0009-0009-8379-622XIaroshenkoArtem V.ЯрошенкоАртём Вадимович

Postgraduate student of the Department of Mechanics and Control Processes, Academy of Engineering

аспирант кафедры механики и процессов управления, инженерная академия

1142240338@pfur.ruRUDN UniversityРоссийский университет дружбы народов2512202526444745602022026Copyright ©; 2025, Kurbanov S.V., Andrikov D.A., Agasieva S.V., Iaroshenko A.V.Copyright ©; 2025, Курбанов С.В., Андриков Д.А., Агасиева С.В., Ярошенко А.В.2025Kurbanov S.V., Andrikov D.A., Agasieva S.V., Iaroshenko A.V.Курбанов С.В., Андриков Д.А., Агасиева С.В., Ярошенко А.В.https://creativecommons.org/licenses/by-nc/4.0https://journals.rudn.ru/engineering-researches/article/view/48347

The problem of low-frequency noise (baseline wander) in long-duration digital electrocardiogram (ECG) signals, which can distort critical diagnostic features such as the ST-segment and T-wave morphology, is considered. Digital filtering methods are studied with an emphasis on low-frequency noise extraction and correction using Chebyshev type II and Butterworth filters synthesized in Python. The results show that a 7th-order high-pass filter with a cutoff frequency of 1 Hz effectively isolates the zero-potential line, whereas the filtfilt function is essential to avoid phase distortions. The success of the filtering method depends on the rate of change of the zero-potential line, and further work is required to develop quantitative criteria for evaluating and correcting filter-induced distortions. The proposed approach aims to improve automated ECG analysis and reduce false alarms in cardiac-monitoring systems.

Рассмотрена проблема низкочастотного шума - дрейфа базовой линии - в сигналах цифровой электрокардиограммы (ЭКГ) большой длительности, который может искажать критические диагностические признаки, такие как морфология ST-сегмента и T-зубца. Изучены методы цифровой фильтрации с упором на извлечение и коррекцию низкочастотных помех с использованием фильтров Чебышева II типа и Баттерворта, синтезированных на Python. Результаты исследования продемонстрировали, что фильтр верхних частот 7-го порядка с частотой среза 1 Гц эффективно изолирует линию нулевого потенциала, тогда как функция filtfilt необходима для предотвращения фазовых искажений. Успех метода фильтрации зависит от скорости изменения линии нулевого потенциала, и требуется дальнейшая разработка количественных критериев оценки и коррекции искажений, вызванных фильтром. Предлагаемый подход направлен на улучшение автоматизированного анализа ЭКГ и снижение ложных тревог в системах мониторинга сердца.

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