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