A Deep Learning Approach for Featureless Robust Quality Assessment of Intermittent Atrial Fibrillation Recordings from Portable and Wearable Devices.

Herraiz, Álvaro Huerta; Martínez-Rodrigo, Arturo; Bertomeu-González, Vicente; Quesada, Aurelio; Rieta, José J; Alcaraz, Raúl

Herraiz, Álvaro Huerta; Martínez-Rodrigo, Arturo; Bertomeu-González, Vicente; Quesada, Aurelio; Rieta, José J; Alcaraz, Raúl.

Afiliação

Herraiz ÁH; Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 16071 Cuenca, Spain.
Martínez-Rodrigo A; Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 16071 Cuenca, Spain.
Bertomeu-González V; Clinical Medicine Department, Miguel Hernandez University, 03202 Elche, Spain.
Quesada A; Cardiology Department, Hospital General Universitario de Valencia, 46014 Valencia, Spain.
Rieta JJ; BioMIT.org, Electronic Engineering Department, Universitat Politecnica de Valencia, 46022 Valencia, Spain.
Alcaraz R; Research Group in Electronic, Biomedical and Telecommunication Engineering, University of Castilla-La Mancha, 16071 Cuenca, Spain.

Entropy (Basel) ; 22(7)2020 Jul 01.

Article em En | MEDLINE | ID: mdl-33286505

Palavras-chave

atrial fibrillation; continuous wavelet transform; convolutional neural network; deep learning; quality assessment; single-lead ECG

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Screening_studies Idioma: En Revista: Entropy (Basel) Ano de publicação: 2020 Tipo de documento: Article

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