Atrial fibrillation classification based on the 2D representation of minimal subset ECG and a non-deep neural network

Atrial fibrillation classification based on the 2D representation of minimal subset ECG and a non-deep neural network

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and its early detection is critical for preventing complications and optimizing treatment. In this study, a novel AF prediction method is proposed, which is based on investigating a subset of the 12-lead ECG data using a recurrent plot...

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Bibliographic Details
Main Authors: Hua Zhang, Chengyu Liu, Fangfang Tang, Mingyan Li, Dongxia Zhang, Ling Xia, Stuart Crozier, Hongping Gan, Nan Zhao, Wenlong Xu, Feng Liu
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-02-01
Series:Frontiers in Physiology
Subjects:
atrial fibrillation identification
electrocardiogram
recurrence plot
non-deep neural network
optimal subset
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2023.1070621/full

Internet

https://www.frontiersin.org/articles/10.3389/fphys.2023.1070621/full

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