A novel algorithm to assess the quality of 12-lead ECG recordings: validation in a real telecardiology application

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dc.creatorJermana Lopes de Moraes
dc.creatorGabriela Paixão
dc.creatorPaulo Rodrigues Gomes
dc.creatorEduardo Mazoni Andrade Marçal Mendes
dc.creatorAntônio Luiz Ribeiro
dc.creatorAlessandro Beda
dc.date.accessioned2025-05-26T12:39:31Z
dc.date.accessioned2025-09-09T00:43:50Z
dc.date.available2025-05-26T12:39:31Z
dc.date.issued2023
dc.identifier.doihttps://doi.org/10.1088/1361-6579/acbc09
dc.identifier.issn0967-3334
dc.identifier.urihttps://hdl.handle.net/1843/82485
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofPhysiological measurement
dc.rightsAcesso Restrito
dc.subjectSistemas elétricos de potência
dc.subject.otherElectrocardiogram
dc.subject.otherBeat template
dc.subject.otherSignal quality assessment
dc.subject.otherClass imbalance
dc.subject.otherReal-world application
dc.titleA novel algorithm to assess the quality of 12-lead ECG recordings: validation in a real telecardiology application
dc.typeArtigo de periódico
local.citation.issue3
local.citation.spage035006
local.citation.volume44
local.description.resumoObjective. Automatic detection of Electrocardiograms (ECG) quality is fundamental to minimize costs and risks related to delayed diagnosis due to low ECG quality. Most algorithms to assess ECG quality include non-intuitive parameters. Also, they were developed using data non-representative of a real-world scenario, in terms of pathological ECGs and overrepresentation of low-quality ECG. Therefore, we introduce an algorithm to assess 12-lead ECG quality, Noise Automatic Classification Algorithm (NACA) developed in Telehealth Network of Minas Gerais (TNMG).Approach. NACA estimates a signal-to-noise ratio (SNR) for each ECG lead, where 'signal' is an estimated heartbeat template, and 'noise' is the discrepancy between the template and the ECG heartbeat. Then, clinically-inspired rules based on SNR are used to classify the ECG as acceptable or unacceptable. NACA was compared with Quality Measurement Algorithm (QMA), the winner of Computing in Cardiology Challenge 2011 (ChallengeCinC) by using five metrics: sensitivity (Se), specificity (Sp), positive predictive value (PPV),F2, and cost reduction resulting from adoption of the algorithm. Two datasets were used for validation: TestTNMG, consisting of 34 310 ECGs received by TNMG (1% unacceptable and 50% pathological); ChallengeCinC, consisting of 1000 ECGs (23% unacceptable, higher than real-world scenario).Main results. Both algorithms reached a similar performance on ChallengeCinC, although NACA performed considerably better than QMA in TestTNMG (Se = 0.89 versus 0.21; Sp = 0.99 versus 0.98; PPV = 0.59 versus 0.08;F2= 0.76 versus 0.16 and cost reduction 2.3 ± 1.8% versus 0.3 ± 0.3%, respectively).Significance. Implementing of NACA in a telecardiology service results in evident health and financial benefits for the patients and the healthcare system.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.departmentMED - DEPARTAMENTO DE CLÍNICA MÉDICA
local.publisher.initialsUFMG
local.url.externahttps://iopscience.iop.org/article/10.1088/1361-6579/acbc09

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