loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Gabriel Saatkamp Lazaretti 1 ; 2 ; João Paulo Teixeira 1 ; Eduardo Vinicius Kuhn 2 and Pedro Henrique Borghi 3

Affiliations: 1 Research Centre in Digitalization and Intelligent Robotics (CEDRI), Instituto Politécnico de Bragança (IPB), Portugal ; 2 Federal University of Technology - Paraná (UTFPR), Toledo, Brazil ; 3 Faculty of Engineering of University of Porto (FEUP), Porto, Portugal

Keyword(s): Android, Atrial Fibrillation, BITalino, ECG, Smartphone.

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. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.136.22.50

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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) - BIODEVICES; ISBN 978-989-758-552-4; ISSN 2184-4305, SciTePress, pages 177-184. DOI: 10.5220/0010905400003123

@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) - BIODEVICES},
year={2022},
pages={177-184},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010905400003123},
isbn={978-989-758-552-4},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - BIODEVICES
TI - Android-based ECG Monitoring System for Atrial Fibrillation Detection using a BITalino® ECG Sensor
SN - 978-989-758-552-4
IS - 2184-4305
AU - Lazaretti, G.
AU - Teixeira, J.
AU - Kuhn, E.
AU - Borghi, P.
PY - 2022
SP - 177
EP - 184
DO - 10.5220/0010905400003123
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic