Analysis of Electrocardiogram Dynamic Features for Arrhythmia Classification

Authors

  • Yusril Ramadhan School of Computing, Telkom University; Human Centric (HUMIC) Engineering, Telkom University, Indonesia
  • Satria Mandala School of Computing, Telkom University; Human Centric (HUMIC) Engineering, Telkom University, Indonesia

DOI:

https://doi.org/10.15575/join.v8i2.1106

Keywords:

electrocardiogram, Feature Extraction, Arrhythmia, Dynamic Feature

Abstract

Arrhythmia is a deviation from the normal heart rate pattern. Arrhythmias are usually harmless, but they can cause heart problems. Some types of arrhythmias include Atrial Fibrillation (AF), Premature Atrial Contractions (PAC), and Premature Ventricular Contractions (PVC). Many studies have been conducted to identify the dynamic characteristics of electrocardiogram (ECG) irregular waves in the detection of arrhythmias. However, the accuracy obtained in these studies is less than optimal. This study aims to solve the problem by evaluating three main features of arrhythmias using ECG signals: RR interval, PR interval, and QRS complex. Experiments were conducted rigorously on these three features. The accuracy achieved was 98.21%, with a specificity of 98.65% and a sensitivity of 97.37%.

Author Biography

Yusril Ramadhan, School of Computing, Telkom University; Human Centric (HUMIC) Engineering, Telkom University

   

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Published

2023-12-28

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