Classification of Cardiac Arrhythmias Using Fractal Dimensions

Fractals are an intriguing mathematical tool that enables us to model the intricate structures found in nature and comprehend the complexity of such objects. They serve as a valuable resource for better understanding our world. Fractal objects are typically characterized by their fractal dimension, which plays a vital role in the analysis of fractal signals. In this study, we define the concept of fractal dimension and present various methods for its calculation. We demonstrate that the electrocardiogram (ECG) is a fractal signal, allowing us to classify heartbeats based on fractal theory. Our goal is to develop a digital technique for ECG signal analysis, with the aim of achieving accurate diagnosis of cardiovascular diseases.

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Publication Details

Journal
The Journal of Tehran University Heart Center
Published
2025-04-26
DOI
https://doi.org/10.18502/jthc.v19is1.18474
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
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article

Classification of Cardiac Arrhythmias Using Fractal Dimensions

Ben Ali Sabrine, Taoufik Aguili
The Journal of Tehran University Heart Center
Complex Systems and Time Series Analysis
article

Classification of Cardiac Arrhythmias Using Fractal Dimensions

Ben Ali Sabrine, Taoufik Aguili
article en

Abstract

Fractals are an intriguing mathematical tool that enables us to model the intricate structures found in nature and comprehend the complexity of such objects. They serve as a valuable resource for better understanding our world. Fractal objects are typically characterized by their fractal dimension, which plays a vital role in the analysis of fractal signals. In this study, we define the concept of fractal dimension and present various methods for its calculation. We demonstrate that the electrocardiogram (ECG) is a fractal signal, allowing us to classify heartbeats based on fractal theory. Our goal is to develop a digital technique for ECG signal analysis, with the aim of achieving accurate diagnosis of cardiovascular diseases.

The Journal of Tehran University Heart CenterVol. 19(Suppl 1)
National Engineering School of Tunis (TN), Tunis El Manar University (TN)
Openalex Percentile: Top 87%
Complex Systems and Time Series Analysis
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