Photoplethysmography-Based Heart Action Monitoring Using a Growing Multilayer Network-Reference-Cited by-同舟云学术

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Photoplethysmography-Based Heart Action Monitoring Using a Growing Multilayer Network

Published:2023-02-15 Issue:4 Volume:23 Page:3756-3765
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wang Lu¹^ORCID,Zhao Chunhui¹^ORCID,Huang Lei²^ORCID,Mathiopoulos P. Takis³^ORCID

Affiliation:

1. College of Information and Communication Engineering, Harbin Engineering University, Harbin, China

2. College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China

3. Department of Telecommunications and Signal Processing, National and Kapodistrian University of Athens, Athens, Greece

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10043099/09989407.pdf?arnumber=9989407

Reference34 articles.

1. Deep Convolutional Neural Networks and Learning ECG Features for Screening Paroxysmal Atrial Fibrillation Patients

2. Photoplethysmography-Based Heart Rate Monitoring Using Asymmetric Least Squares Spectrum Subtraction and Bayesian Decision Theory

3. A real-time QRS detection algorithm;pan;IEEE Trans Biomed Eng,1985

4. A Novel Approach for ECG-Based Human Identification Using Spectral Correlation and Deep Learning

5. An Improved Deep Learning Model for Automated Detection of BBB Using S-T Spectrograms of Smoothed VCG Signal

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