Learning Explainable Time-Morphology Patterns for Automatic Arrhythmia Classification from Short Single-Lead ECGs

Learning Explainable Time-Morphology Patterns for Automatic Arrhythmia Classification from Short Single-Lead ECGs

Automatic detection of abnormal heart rhythms, including atrial fibrillation (AF), using signals obtained from a single-lead wearable electrocardiogram (ECG) device, is useful for daily cardiac health monitoring. In this study, we propose a novel image-based deep learning framework to classify singl...

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Bibliographic Details
Main Authors: Hyeonjeong Lee, Miyoung Shin
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Sensors
Subjects:
arrhythmia classification
atrial fibrillation (AF)
electrocardiogram (ECG)
convolutional neural network (CNN)
deep learning
Online Access:https://www.mdpi.com/1424-8220/21/13/4331

Internet

https://www.mdpi.com/1424-8220/21/13/4331

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