Arrhythmia classification from single-lead ECG signals using the inter-patient paradigm.

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorDias, Felipe Meneguitti-
Autor(es): dc.creatorMonteiro, Henrique Luis Moreira-
Autor(es): dc.creatorCabral, Thales Wulfert-
Autor(es): dc.creatorNaji, Rayen-
Autor(es): dc.creatorKuehni, Michael-
Autor(es): dc.creatorLuz, Eduardo José da Silva-
Data de aceite: dc.date.accessioned2025-08-21T15:30:56Z-
Data de disponibilização: dc.date.available2025-08-21T15:30:56Z-
Data de envio: dc.date.issued2022-02-06-
Data de envio: dc.date.issued2022-02-06-
Data de envio: dc.date.issued2020-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/jspui/handle/123456789/14453-
Fonte completa do material: dc.identifierhttps://www.sciencedirect.com/science/article/abs/pii/S0169260721000225-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.cmpb.2021.105948-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1017153-
Descrição: dc.descriptionBackground and objectives: Arrhythmia is a heart disease characterized by the change in the regularity of the heartbeat. Since this disorder can occur sporadically, Holter devices are used for continuous long-term monitoring of the subject’s electrocardiogram (ECG). In this process, a large volume of data is generated. Consequently, the use of an automated system for detecting arrhythmias is highly desirable. In this work, an automated system for classifying arrhythmias using single-lead ECG signals is proposed. Methods: The proposed system uses a combination of three groups of features: RR intervals, signal morphology, and higher-order statistics. To validate the method, the MIT-BIH database was employed using the inter-patient paradigm. Besides, the robustness of the system against segmentation errors was tested by adding jitter to the R-wave positions given by the MIT-BIH database. Additionally, each group of features had its robustness against segmentation error tested as well. Results: The experimental results of the proposed classification system with jitter show that the sensitivities for the classes N, S, and V are 93.7, 89.7, and 87.9, respectively. Also, the corresponding positive predictive values are 99.2, 36.8, and 93.9, respectively. Conclusions: The proposed method was able to outperform several state-of-the-art methods, even though the R-wave position was synthetically corrupted by added jitter. The obtained results show that our approach can be employed in real scenarios where segmentation errors and the inter-patient paradigm are present.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsrestrito-
Palavras-chave: dc.subjectElectrocardiogram-
Palavras-chave: dc.subjectMachine learning-
Palavras-chave: dc.subjectSegmentation error-
Palavras-chave: dc.subjectJitter-
Título: dc.titleArrhythmia classification from single-lead ECG signals using the inter-patient paradigm.-
Aparece nas coleções:Repositório Institucional - UFOP

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