IOT Platform for Remote Monitoring of Patients with Heart Failureand AI techniques for the early detection of Atrial Fibrillation
DOI:
https://doi.org/10.59471/raia202383Keywords:
REMOTE PATIENT MONITORING (RPM), ECG, MACHINE LEARNING, IOT, ATRIAL FIBRILATION (AF)Abstract
Telemonitoring allows routine information to be obtained about the patient’s condition for
monitoring and remote care purposes. Telemonitoring platforms implement mechanisms through software systems that read alterations in vital signs and allow decompensations to be detected in incipient stages to facilitate their treatment. In this article we describe the first telemonitoring platform that combines IoT and AI and that is being developed in the country. This platform allows patients with different chronic pathologies - currently heart failure - to
receive appropriate care from home. The project comprises two specific technical objectives:
a) develop a mobile application that controls measurement devices, including a single-channel
ECG, b) produce biomedical signal processing algorithms like atrial fibrillation detection
that are included in the platform. This article reports the preliminary results of the project,focusing on describing the design and evaluation of Atrial Fibrillation detection algorithms, which have achieved encouraging results in terms of Accuracy, Precision, Specificity and Sensitivity
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Copyright (c) 2023 Sergio Javier Liberczuk (Autor/a)

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.