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<p>12-Lead Electrocardiography (ECG) is an essential diagnostic tool for detecting Cardiac Arrhythmias (CAs). In this study, Arrhythmia Detection (AD) was conducted using a 12-Lead ECG dataset. The dataset underwent specific preprocessing, and a hybrid 2-Phase Feature Extraction (2-PFE) method was proposed: (1) QRS detection using the Pan-Tompkins algorithm, and (2) P-Peak detection using windowing. The study specifically focused on analyzing Atrial Fibrillation (AFIB) separately from other arrhythmia types. This approach was evaluated through three classification models: SR and NON-SR, SR and NON-SR without AFIB, SR and AFIB.</p>

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Arrhythmia detection from 12-Lead ECG with 2-phase feature extraction: by presenting the evaluation of atrial fibrillation

  • 期刊论文

  • 发表日期：

    2025年11月17日

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  • Gizemnur Erol Doğan,
  • Gülay Tezel,
  • Fatma Zehra Solak,
  • Betül Uzbaş

摘要

12-Lead Electrocardiography (ECG) is an essential diagnostic tool for detecting Cardiac Arrhythmias (CAs). In this study, Arrhythmia Detection (AD) was conducted using a 12-Lead ECG dataset. The dataset underwent specific preprocessing, and a hybrid 2-Phase Feature Extraction (2-PFE) method was proposed: (1) QRS detection using the Pan-Tompkins algorithm, and (2) P-Peak detection using windowing. The study specifically focused on analyzing Atrial Fibrillation (AFIB) separately from other arrhythmia types. This approach was evaluated through three classification models: SR and NON-SR, SR and NON-SR without AFIB, SR and AFIB.