4.6 Article

Atrial fibrillation detection with and without atrial activity analysis using lead-I mobile ECG technology

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ELSEVIER SCI LTD
DOI: 10.1016/j.bspc.2021.102462

关键词

Atrial activity; Atrial fibrillation detection; Heart rhythm; Single-channel mobile electrocardiography

资金

  1. Hungarian Government [EFOP-3.6.1-16-2016-00015]
  2. European Social Fund [EFOP-3.6.1-16-2016-00015]
  3. National Research, Development and Innovation Fund of Hungary [TKP2020-IKA-07, 20204.1.1-TKP2020]

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This paper discusses a new AF detection algorithm that takes into account atrial activity in addition to heart rhythm to significantly reduce false positive cases caused by non-AF arrhythmias. The algorithm was tested on different databases, showing that P wave analysis can improve specificity, especially in records with frequent premature beats and marked sinus arrhythmia. These results suggest a more careful testing of AF detection methods on non-AF arrhythmia cases, and highlight the superior performance of the A2 version of the algorithm in the WIWE system.
Objective: This paper presents the performance of an atrial fibrillation (AF) detection algorithm in a lead-I mobile ECG setting. Our aim is to demonstrate that false positive cases occurring due to non-AF arrhythmias can be significantly reduced by taking atrial activity into account in addition to heart rhythm. Methods: AF detection was carried out in two ways: only by heart rhythm assessment based on Poincare plot of RR intervals (A1), and by also performing P wave analysis on the average majority cycle (A2). Results: The algorithm was tested on the PhysioNet MIT-BIH Atrial Fibrillation Database, Long-Term AF Database, MIT-BIH Arrhythmia Database, and MIT-BIH Normal Sinus Rhythm Database. A1 produced an average sensitivity (Se) of 97.64 % and specificity (Sp) of 93.06 %. A2 resulted Se = 96.52 % and Sp = 99.12 %. Additionally, clinical data acquisition was performed by the Sanatmetal WIWE mobile ECG system. On the latter records, Se = 100 % and Sp = 95.31 % were obtained with A1, while A2 resulted Se = 100 % and Sp = 100 %. Conclusion: Atrial activity analysis significantly increased Sp in records with frequent premature beats (by almost 12 %) and marked sinus arrhythmia (by 7.5 %). Based on our results and data from the literature, we suggest that AF detection methods should be tested more carefully on non-AF arrhythmia cases. Applied in WIWE, the A2 version of our algorithm outperforms the AF detectors of current single-channel mobile ECG systems. Significance: The results contribute to the significant reduction of false positive AF detections in lead-I mobile ECG technology.

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