DIAGNOSING SLEEP APNEA VIA FEATURE SELECTION ON SINGLE CHANNEL ECG

GURULER, Huseyin and FERIKOGLU, Abdullah (2014) DIAGNOSING SLEEP APNEA VIA FEATURE SELECTION ON SINGLE CHANNEL ECG. International Symposium on Sustainable Development. ISSN 978-9958-834-36-3

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Abstract

This article is based on a combination of time-frequency domain functions, and nonlinear techniques in the analysis of heart rate variability (HRV) for diagnosing obstructive sleep apnea (OSA) using only single-lead electrocardiography (ECG) signals. The contribution of the presented study to earlier ones is that it enables numerically determining what type of HRV features better represent the aforementioned target by using correlation matrices and neural networks (NNs). Keywords: Diagnosing disease, neural network, sleep apnea, heart rate variability, feature selection, correlation matrices

Item Type: Article
Subjects: Q Science > Q Science (General)
Q Science > QH Natural history > QH301 Biology
Q Science > QH Natural history > QH426 Genetics
Divisions: International Symposium on Sustainable Development
Depositing User: Mr. Edis Bulic
Date Deposited: 23 Jun 2014 13:44
Last Modified: 23 Jun 2014 13:44
URI: http://eprints.ibu.edu.ba/id/eprint/2516

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