A new approach to eliminating EOG artifacts from the sleep EEG signals for the automatic sleep stage classification-Reference-Cited by-同舟云学术

A new approach to eliminating EOG artifacts from the sleep EEG signals for the automatic sleep stage classification

Published:2016-09-09 Issue:10 Volume:28 Page:3095-3112
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Dursun Mehmet^ORCID,Özşen Seral,Yücelbaş Cüneyt,Yücelbaş Şule,Tezel Gülay,Küççüktürk Serkan,Yosunkaya Şebnem

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/article/10.1007/s00521-016-2578-z/fulltext.html

Reference37 articles.

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2. Acharya UR, Chua Ec-P, Chua KC et al (2010) Analysis and automatic identification of sleep stages using higher order spectra. Int J Neural Syst 20:509–521. doi: 10.1142/S0129065710002589

3. Vural C, Yildiz M (2010) Determination of sleep stage separation ability of features extracted from eeg signals using principle component analysis. J Med Syst 34(1):83–89

4. Acharya UR, Bhat S, Faust O et al (2015) Nonlinear dynamics measures for automated EEG-based sleep stage detection. Eur Neurol 74:268–287. doi: 10.1159/000441975

5. Doroshenkov LG, Konyshev VA, Selishchev SV (2007) Classification of human sleep stages based on EEG processing using hidden markov models. Biomed Eng 41:25. doi: 10.1007/s10527-007-0006-5

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