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Design and Implementation of an Ultralow-Power ECG Patch and Smart Cloud-Based Platform

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posted on 21.04.2022, 19:52 by Bardia BaraeinejadBardia Baraeinejad, Masood Fallah Shayan, Amir Reza VazifehAmir Reza Vazifeh, Diba Rashidi, Mohammad Saberi Hamedani, Hamed Tavolinejad, Pouya Gorji, Parsa Razmara, Kiarash Vaziri, Daryoosh Vashaee, Mohammad Fakharzadeh

This paper reports a new device for electrocardiogram (ECG) signal monitoring and software for signal analysis and artificial intelligence (AI) assisted diagnosis.

The hardware mitigates the signal loss common in previous products by enhancing the ergonomy, flexibility, and battery life. The power efficiency is optimized by design using switching converters, ultra-low-power components, and efficient signal processing. It enables 14-day of uninterrupted ECG monitoring and connectivity with a smartphone and microSD card storage.

The software is implemented in Android app and web-based platforms via Internet of Things (IoT). This component provides cloud-based and local storage and uses AI for arrhythmia detection. The arrhythmia detection algorithm shows 98.7% accuracy using Artificial Neural Network and K-Nearest Neighbors methods, and 98.1% using Decision Tree method on test data set.

History

Email Address of Submitting Author

bardiabarai@gmail.com

ORCID of Submitting Author

0000-0003-1554-9883

Submitting Author's Institution

Sharif University of Technology

Submitting Author's Country

Iran