Simulation of an Outpatient ECG Monitor with Adaptive Signal Processing

Tyulepberdinova G. Kunelbayev M. Amirkhanova G. Toiganbayeva N. Tolepberdinova A.
2026 World Scientific and Engineering Academy and Society

WSEAS Transactions on Systems
2026 #25 31 - 43 pp.

This study proposes an original methodology for modeling an outpatient electrocardiographic monitor with a focus on adaptive processing of biomedical signals. A mathematical model of the device has been constructed, incorporating signal parameterization, suppression of noise artifacts, extraction of informative features (RR intervals, heart rate, and heart rate variability indices), and intelligent arrhythmia classification using machine learning algorithms. A distinctive feature of the system is the implementation of a variable sampling rate that automatically adjusts according to signal quality and functional load, thereby optimizing power consumption while maintaining high monitoring accuracy. Computer-based simulations were carried out in the MATLAB/Simulink environment and complemented with experimental validation on both real and synthetic ECG recordings. The obtained results demonstrated reliable detection of QRS complexes (with an accuracy of up to 98.7) and robust calculation of HRV metrics under noise and artifact distortions. The developed model can serve as a foundation for further optimization of portable ECG monitors, their integration into telemedicine platforms, and the design of intelligent algorithms for early arrhythmia detection. Creative Commons Attribution License 4.0 (Attribution 4.0 International, CC BY 4.0) This article is published under the terms of the Creative Commons Attribution License 4.0 https://creativecommons.org/licenses/by/4.0/deed.en_US

Deep Learning , Heart Rate Variability HRV , Machine Learning SVM , Outpatient ECG Monitor , QRS detection , Signal Processing , Telemedicine

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Department of Artificial Intelligence and Big Data, Al-Farabi Kazakh National University, Almaty, Kazakhstan

Department of Artificial Intelligence and Big Data

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026