Pre-determination of OSA degree using morphological features of the ECG signal

Author:

Yücelbaş Şule,Yücelbaş Cüneyt,Tezel Gülay,Özşen Seral,Küççüktürk Serkan,Yosunkaya Şebnem

Funder

Scientific and Technological Research Council of Turkey

Scientific Research Projects Coordination Unit

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference36 articles.

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4. SVM-based sleep apnea identification using optimal RR-interval features of the ECG signal;Almazaydeh;International Journal of Intelligent Systems and Applications in Engineering,2016

5. Tissue doppler atrial conduction times and electrocardiogram interlead P-wave durations with varying severity of obstructive sleep apnea;Cagirci;Journal of Electrocardiology,2011

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