Decision Fusion in Automated Sleep Apnea Classification Using Multple Polysomnography Sensors and Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Decision Fusion in Automated Sleep Apnea Classification Using Multple Polysomnography Sensors and Convolutional Neural Networks

Published:2023-07-18 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Sensors Applications Symposium (SAS)
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Author:

Stewart Matthew¹,Higginson Caitlin²,Larivière-Chartier Julien³,Robillard Rebecca⁴,Green James¹,Goubran Rafik¹,Knoefel Frank⁵

Affiliation:

1. Carleton University,Systems and Computer Engineering,Ottawa,Canada

2. University of Ottawa Institute of Mental Health Research at The Royal,Sleep Research Unit,Ottawa,Canada

3. Bruyere Research Institute,Ottawa,Canada

4. School of Psychology, University of Ottawa,Ottawa,Canada

5. University of Ottawa,Faculty of Medicine,Ottawa,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10253663/10253664/10254145.pdf?arnumber=10254145

Reference41 articles.

1. Electrocardiogram-based detection of central sleep apnea: a full-record signal processing approach

2. A 2D convolutional neural network to detect sleep apnea in children using airflow and oximetry

3. Sleep Apnea and Cardiovascular Disease

4. A fused-image-based approach to detect obstructive sleep apnea using a single-lead ECG and a 2D convolutional neural network

5. An algorithm for sleep apnea detection from single-lead ECG using Hermite basis functions

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Classification of Central and Obstructive Sleep Apnea Using Respiratory Inductance Plethysmography and Convolutional Neural Networks;2024 IEEE Sensors Applications Symposium (SAS);2024-07-23

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