A Novel Framework for ECG Signal Processing and Robust Arrhythmia Detection

Volume 19, Issue 2,  2025

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Author(s):

Gautam Sharma Department of Biomedical Engineering, Ziauddin University (FESTM), Karachi, Pakistan, gautam.17192@zu.edu.pk

Safia Tahir Department of Biomedical Engineering, Ziauddin University (FESTM), Karachi, Pakistan, safia.16462@zu.edu.pk

Mehwish Faiz* Department of Biomedical Engineering, Ziauddin University (FESTM), Karachi , Pakistan, mehwish.faiz@zu.edu.pk

Huzaifa Ahmed Department of Biomedical Engineering, Ziauddin University (FESTM), Karachi , Pakistan, Huzaifa.16559@zu.edu.pk

Abdul Moiz Afridi Department of Biomedical Engineering, Ziauddin University (FESTM), Karachi, Pakistan, abdul.16551@zu.edu.pk

Aneela Kiran The begum Nusrat Bhutto Women University, Sukkur, Pakistan, aneelakiranansari73@gmail.com

Shahzad Nasim The begum Nusrat Bhutto Women University, Sukkur, Pakistan, shahzadnasim@live.com

Abstract Cardiovascular diseases are still one of the most important public health issues that the world is facing today. Early identification of heart problems can help with early diagnosis. Analyzing the electrical signals created by the heart can provide important insight into how well a person's heart is functioning. The electrical signals generated by the heart can be disrupted by noise and interference, which effects the interpretation of these signals. This paper reveals a novel approach to process bio signals to uncover the presence of abnormal heart rhythms based on abnormally fast, slow, or irregular heartbeat patterns. The results of the experimental evaluations demonstrate that out of total 10 participants, 6 individuals have a normal heart pattern while the heart rate analysis of remaining 4 individuals indicates that they are having arrhythmia. Thus, the method used in this study successfully distinguishes between normal and abnormal cardiac conditions. This publication provides an overview of the potential use of signal processing to assist with early diagnosis of heart problems and improve ongoing monitoring of patients' health in both clinical and remote settings.
Keywords Cardiovascular Disease (CVD), ECG, Abnormal heart rhythms, filtration, Reducing noise, Analyzing features
Year 2025
Volume 19
Issue 2
Type Research paper, manuscript, article
Journal Name Journal of Information & Communication Technology
Publisher Name ILMA University
Jel Classification -
DOI -
ISSN no (E, Electronic) 2075-7239
ISSN no (P, Print) 2415-0169
Country Pakistan
City Karachi
Institution Type University
Journal Type Open Access
Manuscript Processing Blind Peer Reviewed
Format PDF
Paper Link https://jict.ilmauniversity.edu.pk/journal/jict/19.2/2.pdf
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