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Android-based ECG monitoring system for atrial fibrillation detection using a BITalino® ECG sensor

2022Conference paper Open access
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dc.contributor.authorLazaretti, Gabriel Saatkamp
dc.contributor.authorTeixeira, João Paulo
dc.contributor.authorKuhn, Eduardo Vinicius
dc.contributor.authorBorghi, Pedro Henrique
dc.date.accessioned2022-05-19T09:55:33Z
dc.date.available2022-05-19T09:55:33Z
dc.date.issued2022
dc.description.abstractCardiac 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 Android™ operating system. The signal processing is carried out through an application developed using the IDE Android™ 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.pt_PT
dc.description.sponsorshipThis work has supported by Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/05757/2020, and by the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020), under Portugal 2020 in the framework of the NanoID (NORTE-01-0247-FEDER-046985) Project.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBorghi, Pedro; Kuhn, Eduardo; Teixeira, João Paulo; Lazaretti, Gabriel (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). Vol. 1 p. 177-184. ISBN 978-989-758-552-4pt_PT
dc.identifier.doi10.5220/0010905400003123pt_PT
dc.identifier.isbn978-989-758-552-4
dc.identifier.urihttp://hdl.handle.net/10198/25488
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSCITEPRESSpt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAndroidpt_PT
dc.subjectAtrial fibrillationpt_PT
dc.subjectBITalinopt_PT
dc.subjectECGpt_PT
dc.subjectSmartphonept_PT
dc.titleAndroid-based ECG monitoring system for atrial fibrillation detection using a BITalino® ECG sensorpt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.citation.endPage184pt_PT
oaire.citation.startPage177pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameTeixeira
person.givenNameJoão Paulo
person.identifier663194
person.identifier.ciencia-id4F15-B322-59B4
person.identifier.orcid0000-0002-6679-5702
person.identifier.ridN-6576-2013
person.identifier.scopus-author-id57069567500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication33f4af65-7ddf-46f0-8b44-a7470a8ba2bf
relation.isAuthorOfPublication.latestForDiscovery33f4af65-7ddf-46f0-8b44-a7470a8ba2bf
relation.isProjectOfPublication6e01ddc8-6a82-4131-bca6-84789fa234bd
relation.isProjectOfPublication.latestForDiscovery6e01ddc8-6a82-4131-bca6-84789fa234bd

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