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

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Abstract
This paper reports the development of a new smart ECG monitoring system, consisting of the related hardware, firmware, and IoT-based web service for AI assisted arrhythmia detection and a complementary Android application for data streaming. The hardware aspect of this research proposes an ultra-low power patch sampling ECG data at 256 samples/s with 16-bit resolution. The battery life of the device is two weeks per charging, which alongside the flexible and slim (193.7 mm × 62.4 mm × 8.6 mm) and lightweight (43 g) allows the user to continue real life activities while the real-time monitoring is being done without interruption. The power management is achieved through the usage of switching converters, ultra-low power component choice as well as intermittent usage of them through firmware optimization. A novel data encoding method is also proposed to allow compression of data and lower the runtime. The software aspect, in addition to the web ECG analysis platform and the Android streaming and monitoring application, provides an arrhythmia detection service. The key innovations in this regard are the usage of a set of new factors in determining arrhythmia that grants higher accuracy while retaining the detection near-real-time. 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.

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