Training Convolutional Neural Networks on Simulated Photoplethysmography Data: Application to Bradycardia and Tachycardia Detection

Training Convolutional Neural Networks on Simulated Photoplethysmography Data: Application to Bradycardia and Tachycardia Detection

Objective: To develop a method for detection of bradycardia and ventricular tachycardia using the photoplethysmogram (PPG).Approach: The detector is based on a dual-branch convolutional neural network (CNN), whose input is the scalograms of the continuous wavelet transform computed in 5-s segments....

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Bibliographic Details
Main Authors: Andrius Sološenko , Birutė Paliakaitė , Vaidotas Marozas , Leif Sörnmo 
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Physiology
Subjects:
photoplethysmogram
bradycardia
tachycardia
convolutional neural networks
detection
simulated signals
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2022.928098/full

Internet

https://www.frontiersin.org/articles/10.3389/fphys.2022.928098/full

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