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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wolters Kluwer Medknow Publications
2020-01-01
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| Series: | Journal of Medical Signals and Sensors |
| Subjects: | |
| Online Access: | http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2020;volume=10;issue=4;spage=219;epage=227;aulast=Ostadieh |