Enhancing obstructive apnea disease detection using dual-tree complex wavelet transform-based features and the hybrid “K-means, recursive least-squares” learning for the radial basis function network

Enhancing obstructive apnea disease detection using dual-tree complex wavelet transform-based features and the hybrid “K-means, recursive least-squares” learning for the radial basis function network

Background: The obstructive sleep apnea (OSA) detection has become a hot research topic because of the high risk of this disease. In this paper, we tested some powerful and low computational signal processing techniques for this task and compared their results with the recent achievements in OSA det...

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Bibliographic Details
Main Authors: Javad Ostadieh, Mehdi Chehel Amirani, Morteza Valizadeh
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2020-01-01
Series:Journal of Medical Signals and Sensors
Subjects:
classification
feature reduction
hybrid k-means recursive least-squares
multi-cluster feature selection
obstructive sleep apnea
single-lead electrocardiogram
Online Access:http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2020;volume=10;issue=4;spage=219;epage=227;aulast=Ostadieh

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