Android-based ECG Monitoring System for Atrial Fibrillation Detection using a BITalino® ECG Sensor

Gabriel Saatkamp Lazaretti, Gabriel Saatkamp Lazaretti, João Paulo Teixeira, Eduardo Vinicius Kuhn, Pedro Henrique Borghi

2022

Abstract

Cardiac arrhythmias are disorders that affect the rate and/or rhythm of the heartbeats. The diagnosis of most arrhythmias is made through the analysis of the electrocardiogram (ECG), which consists of a graphical representation of the electrical activity of the heart. Atrial fibrillation (AF) is the most present type of arrhythmia in the world population. In this context, this work deals with the implementation of a system for automatic analysis of ECG signals aiming to identify AF episodes. The system consists of a signal acquisition step performed by an ECG sensor connected to an acquisition platform. The acquired signal is transmitted via bluetooth to a smartphone with AndroidTM operating system. The signal processing is carried out through an application developed using the IDE AndroidTM Studio. When assessed over signals from the MIT-BIH Atrial Fibrillation database, the R-wave peak detection algorithm showed mean values of sensitivity and positive predictivity of 98.99% and 95.95%, respectively. The classification model used is based on a long short-term memory (LSTM) neural network and had an average accuracy of 94.94% for identifying AF episodes.

Paper Citation

in Harvard Style

Lazaretti G., Teixeira J., Kuhn E. and Borghi P. (2022). Android-based ECG Monitoring System for Atrial Fibrillation Detection using a BITalino® ECG Sensor. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 1: BIODEVICES; ISBN 978-989-758-552-4, SciTePress, pages 177-184. DOI: 10.5220/0010905400003123

in Bibtex Style

@conference{biodevices22,
author={Gabriel Saatkamp Lazaretti and João Paulo Teixeira and Eduardo Vinicius Kuhn and Pedro Henrique Borghi},
title={Android-based ECG Monitoring System for Atrial Fibrillation Detection using a BITalino® ECG Sensor},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 1: BIODEVICES},
year={2022},
pages={177-184},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010905400003123},
isbn={978-989-758-552-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 1: BIODEVICES
TI - Android-based ECG Monitoring System for Atrial Fibrillation Detection using a BITalino® ECG Sensor
SN - 978-989-758-552-4
AU - Lazaretti G.
AU - Teixeira J.
AU - Kuhn E.
AU - Borghi P.
PY - 2022
SP - 177
EP - 184
DO - 10.5220/0010905400003123
PB - SciTePress