The Internet of Things is an inter-networking of physical devices that communicate with each other through the Internet. The technological progress of the last few decades and more efficient wireless protocols led to an exponential growth of devices connected with an increasing amount of data exchanged across the globe. The birth of the IoT caused significant changes in different sectors, among which e-Health, involving big innovations in medical care, prevention and remote diagnosis. The goal of our project is to plan and implement an IoT node to collect clinical data and to detect atrial fibrillation through the analysis of electrocardiogram. We chose to focus on this particular arrhythmia because it represents one of the most common heart diseases. Additionally, it is often asymptomatic and associated with more dangerous illnesses. The device validation has been realized on a sample of patients affected by atrial fibrillation and other heart diseases, in order to evaluate the reliability of the obtained data and the efficiency of the algorithm. Finally, we have analyzed the advantages and limitations of the device, introducing potential future adjustments that could improve its functionality.

Implementation of an IoT Node for Biomedical Applications

Gruosso, Giambattista
2018-01-01

Abstract

The Internet of Things is an inter-networking of physical devices that communicate with each other through the Internet. The technological progress of the last few decades and more efficient wireless protocols led to an exponential growth of devices connected with an increasing amount of data exchanged across the globe. The birth of the IoT caused significant changes in different sectors, among which e-Health, involving big innovations in medical care, prevention and remote diagnosis. The goal of our project is to plan and implement an IoT node to collect clinical data and to detect atrial fibrillation through the analysis of electrocardiogram. We chose to focus on this particular arrhythmia because it represents one of the most common heart diseases. Additionally, it is often asymptomatic and associated with more dangerous illnesses. The device validation has been realized on a sample of patients affected by atrial fibrillation and other heart diseases, in order to evaluate the reliability of the obtained data and the efficiency of the algorithm. Finally, we have analyzed the advantages and limitations of the device, introducing potential future adjustments that could improve its functionality.
2018
IEEE 4th International Forum on Research and Technologies for Society and Industry, RTSI 2018 - Proceedings
9781538662823
Artificial Intelligence; Computer Networks and Communications; Computer Science Applications1707 Computer Vision and Pattern Recognition; Energy Engineering and Power Technology; Renewable Energy, Sustainability and the Environment; Industrial and Manufacturing Engineering; Instrumentation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1088387
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