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Campo Dublin Core | Valor | Idioma |
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dc.contributor.author | Dias, Felipe Meneguitti | - |
dc.contributor.author | Monteiro, Henrique Luis Moreira | - |
dc.contributor.author | Cabral, Thales Wulfert | - |
dc.contributor.author | Naji, Rayen | - |
dc.contributor.author | Kuehni, Michael | - |
dc.contributor.author | Luz, Eduardo José da Silva | - |
dc.date.accessioned | 2022-02-07T19:45:38Z | - |
dc.date.available | 2022-02-07T19:45:38Z | - |
dc.date.issued | 2021 | pt_BR |
dc.identifier.citation | DIAS, F. M. et al. Arrhythmia classification from single-lead ECG signals using the inter-patient paradigm. Computer Methods and Programs in Biomedicine, v. 1, artigo 105948, 2021. Disponível em: <https://www.sciencedirect.com/science/article/abs/pii/S0169260721000225>. Acesso em: 25 ago. 2021. | pt_BR |
dc.identifier.issn | 0169-2607 | - |
dc.identifier.uri | http://www.repositorio.ufop.br/jspui/handle/123456789/14453 | - |
dc.description.abstract | Background 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. | pt_BR |
dc.language.iso | en_US | pt_BR |
dc.rights | restrito | pt_BR |
dc.subject | Electrocardiogram | pt_BR |
dc.subject | Machine learning | pt_BR |
dc.subject | Segmentation error | pt_BR |
dc.subject | Jitter | pt_BR |
dc.title | Arrhythmia classification from single-lead ECG signals using the inter-patient paradigm. | pt_BR |
dc.type | Artigo publicado em periodico | pt_BR |
dc.identifier.uri2 | https://www.sciencedirect.com/science/article/abs/pii/S0169260721000225 | pt_BR |
dc.identifier.doi | https://doi.org/10.1016/j.cmpb.2021.105948 | pt_BR |
Aparece nas coleções: | DECOM - Artigos publicados em periódicos |
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ARTIGO_ArrhythmiaClassificationSingle.pdf Restricted Access | 880,55 kB | Adobe PDF | Visualizar/Abrir |
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