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The article presents an IoT-enabled device designed for continuous ECG monitoring, based on which real time heart disease detection is done using machine learning. Cardiovascular diseases are highly responsible for deaths all over the world, and thus early diagnosis is of extreme importance. The IoT system acquires physiological information in terms of ECG signals to be processed and analyzed by machine learning algorithms. This allows the system to detect early signs of potential heart diseases offering users an affordable, efficient, and non-invasive method for continuous heart health monitoring.

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IoT-Enabled Wearable System for Real-Time ECG Monitoring with Machine Learning-Based Heart Disease Detection

  • 会议论文

  • 发表日期：

    2026年

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  • Archana Reddy Penumada,
  • Divya Jyothi Gundapaneni,
  • Akshitha Chennupati,
  • Meena Belwal

摘要

The article presents an IoT-enabled device designed for continuous ECG monitoring, based on which real time heart disease detection is done using machine learning. Cardiovascular diseases are highly responsible for deaths all over the world, and thus early diagnosis is of extreme importance. The IoT system acquires physiological information in terms of ECG signals to be processed and analyzed by machine learning algorithms. This allows the system to detect early signs of potential heart diseases offering users an affordable, efficient, and non-invasive method for continuous heart health monitoring.