Multiclass Arrhythmia Detection and Classification From Photoplethysmography Signals Using a Deep Convolutional Neural Network

Multiclass Arrhythmia Detection and Classification From Photoplethysmography Signals Using a Deep Convolutional Neural Network

Background Studies have reported the use of photoplethysmography signals to detect atrial fibrillation; however, the use of photoplethysmography signals in classifying multiclass arrhythmias has rarely been reported. Our study investigated the feasibility of using photoplethysmography signals and a...

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Bibliographic Details
Main Authors: Zengding Liu, Bin Zhou, Zhiming Jiang, Xi Chen, Ye Li, Min Tang, Fen Miao
Format: Article
Language:English
Published: Wiley 2022-04-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
arrhythmias
deep convolutional neural networks
photoplethysmography
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.121.023555

Internet

https://www.ahajournals.org/doi/10.1161/JAHA.121.023555

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