RAPIDEST: A Framework for Obstructive Sleep Apnea Detection-Reference-Cited by-同舟云学术

RAPIDEST: A Framework for Obstructive Sleep Apnea Detection

Published:2023 Issue: Volume:31 Page:387-397
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Lin Xin-Xue¹^ORCID,Lin Phone²^ORCID,Yeh En-Hau¹,Liu Gi-Ren³,Lien Wan-Ching⁴,Fang Yuguang⁵^ORCID

Affiliation:

1. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

2. Department of Computer Science and Information Engineering, Internet of Things Research Center, Graduate Institute of Networking and Multimedia, and the Institute of Medical Device and Imaging, National Taiwan University, Taipei, Taiwan

3. Department of Mathematics, National Cheng Kung University, Tainan City, Taiwan

4. Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan

5. Department of Computer Science, City University of HongKong, HongKong, China

Funder

Ministry of Science and Technology (MOST) of Taiwan

Ministry of Education Higher Education Sprout Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/10031624/09963631.pdf?arnumber=9963631

Reference55 articles.

1. Two-group classification of patients with obstructive sleep apnea based on analysis of brain recurrence

2. Sleep apnea detection: accuracy of using automated ECG analysis compared to manually scored polysomnography (apnea hypopnea index)

3. Home monitoring of sleep with a temporary-tattoo EEG, EOG and EMG electrode array: a feasibility study

4. EEG Recording and Analysis for Sleep Research

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