Hybrid CNN-LSTM Network for Real-Time Apnea-Hypopnea Event Detection Based on IR-UWB Radar-Reference-Cited by-同舟云学术

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Hybrid CNN-LSTM Network for Real-Time Apnea-Hypopnea Event Detection Based on IR-UWB Radar

Published:2021 Issue: Volume: Page:1-1
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kwon Hyun Bin,Son Dongyeon,Lee Dongseok,Yoon Heenam,Lee Mi Hyun,Lee Yu Jin,Choi Sang Ho,Park Kwang Suk

Funder

Kwangwoon University

National Research Foundation of Korea

Seoul National University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/6514899/09435330.pdf?arnumber=9435330

Cited by 24 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. A novel deep learning model for obstructive sleep apnea diagnosis: hybrid CNN-Transformer approach for radar-based detection of apnea-hypopnea events;SLEEP;2024-08-08

2. A multi-task learning model using RR intervals and respiratory effort to assess sleep disordered breathing;BioMedical Engineering OnLine;2024-05-05

3. A Robust Super-resolution Algorithm in a Low SNR Environment for Vital Sign Radar;Radioengineering;2024-04

4. A low-complexity sleep apnea detection method using millimeter-wave radar;Fifteenth International Conference on Signal Processing Systems (ICSPS 2023);2024-03-28

5. SST: a snore shifted-window transformer method for potential obstructive sleep apnea patient diagnosis;Physiological Measurement;2024-03-01

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