Development of a semi–real-time electrocardiogram monitoring system integrating artificial intelligence and wearable devices for atrial fibrillation screening - Takeaways - MDSpire

Development of a semi–real-time electrocardiogram monitoring system integrating artificial intelligence and wearable devices for atrial fibrillation screening

  • By

  • Si Van Nguyen

  • Minh Khac Ho

  • Dat Vu Nguyen

  • Canh Quang Nguyen

  • An Le Pham

  • Hung Thanh Quach

  • June 8, 2026

  • 0 min

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  • 1

    Atrial fibrillation (AF) increases the risk of thromboembolic events, making timely diagnosis crucial for reducing stroke risk.

  • 2

    Traditional Holter monitoring often misses paroxysmal AF episodes, necessitating improved detection methods using AI.

  • 3

    The study developed a deep learning model for AF detection using 1,489 Holter ECG recordings, enhancing diagnostic accuracy.

  • 4

    A semi-real-time monitoring framework was evaluated, integrating AI analysis with wearable ECG devices for high-risk populations.

  • 5

    The model utilized a Residual Network architecture to analyze ECG features, aiming to improve AF screening sensitivity.

Original Source(s)

Development of a semi–real-time electrocardiogram monitoring system integrating artificial intelligence and wearable devices for atrial fibrillation screening

  • by Si Van Nguyen, Minh Khac Ho, Dat Vu Nguyen, Canh Quang Nguyen, An Le Pham, Hung Thanh Quach

  • June 8, 2026

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