Obstructive sleep apnoea detection using convolutional neural network based deep learning framework-Reference-Cited by-同舟云学术

Obstructive sleep apnoea detection using convolutional neural network based deep learning framework

Published:2017-12-14 Issue:1 Volume:8 Page:95-100
ISSN:2093-9868
Container-title:Biomedical Engineering Letters
language:en
Short-container-title:Biomed. Eng. Lett.

Author:

Dey Debangshu,Chaudhuri Sayanti^ORCID,Munshi Sugata

Funder

University Grants Commission

Publisher

Springer Science and Business Media LLC

Subject

Biomedical Engineering

Link

http://link.springer.com/article/10.1007/s13534-017-0055-y/fulltext.html

Reference12 articles.

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2. Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PC, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101(23):e215–20.

3. Hassan AR. Computer-aided obstructive sleep apnoea detection using normal inverse Gaussian parameters and adaptive boosting. Biomed Signal Proc Control. 2016;29:22–30.

4. Varon C, Caicedo A, Testelmans D, et al. A novel algorithm for the automatic detection of sleep apnea from single-lead ECG. IEEE Trans Biomed Eng. 2015;62(9):2269–78.

5. Hassan AR, Haque MA. Computer-aided obstructive sleep apnea screening from single-lead electrocardiogram using statistical and spectral features and bootstrap aggregating. Biocybern Biomed Eng. 2016;36(1):256–66.

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