In obstructive sleep apnea patients, automatic determination of respiratory arrests by photoplethysmography signal and heart rate variability

Author:

Bozkurt Mehmet Recep,Uçar Muhammed KürşadORCID,Bozkurt Ferda,Bilgin Cahit

Funder

Türkiye Bilimsel ve Teknolojik Arastirma Kurumu

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,Biomedical Engineering,Biophysics,General Physics and Astronomy

Reference42 articles.

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2. Al-Khammasi S, Aboalayon KAI, Daneshzand M, Faezipour M, Faezipour M (2017) Hardware-based FIR filter implementations for ECG signal denoising: A monitoring framework from industrial electronics perspective. In: 2016 annual connecticut conference on industrial electronics, technology and automation, CT-IETA 2016, IEEE, pp 1–6

3. Changyue S, Kaibo L, Xi Z, Lili C, Xiaochen X (2015) An obstructive sleep apnea detection approach using a discriminative hidden markov model from ECG signals. IEEE Trans Biomed Eng 63:1532

4. Bruyneel M, Ninane V (2014) Unattended home-based polysomnography for sleep disordered breathing: current concepts and perspectives. Sleep Med Rev 18(4):341–7

5. Uçar MK, Bozkurt MR, Bilgin C, Polat K (2016) Automatic detection of respiratory arrests in OSA patients using PPG and machine learning techniques. Neural Comput Appl 28:2931–2945

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