An Early Warning of Atrial Fibrillation Based on Short-Time ECG Signals

This study introduces a method to classify single-lead ECG signals by extracting features through traditional methods and deep neural network methods. At first step, the statistical type features of the ECG signals are exacted by traditional methods, including time domain features, frequency domain...

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Detalles Bibliográficos
Autores principales: Zhao, Tianxia, Wang, Xin'an, Qiu, Changpei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789462/
https://www.ncbi.nlm.nih.gov/pubmed/35087647
http://dx.doi.org/10.1155/2022/2205460

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789462/
https://www.ncbi.nlm.nih.gov/pubmed/35087647
http://dx.doi.org/10.1155/2022/2205460

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