On improvement of detection of Obstructive Sleep Apnea by partial least square-based extraction of dynamic features

Author

Sepúlveda-Cano, L.M. ; Travieso-González, C.M. ; Godino-Llorente, J.I. ; Castellanos-Domínguez, G.

Author_Institution

Control & Digital Signal Process. Group, Univ. Nac. de Colombia, Manizales, Colombia

fYear

2010

fDate

Aug. 31 2010-Sept. 4 2010

Firstpage

6321

Lastpage

6324

Abstract

This paper presents a methodology for Obstructive Sleep Apnea (OSA) detection based on the HRV analysis, where as a measure of relevance PLS is used. Besides, two different combining approaches for the selection of the best set of contours are studied. Attained results can be oriented in research focused on finding alternative methods minimizing the HRV-derived parameters used for OSA diagnosing, with a diagnostic accuracy comparable to a polysomnogram. For two classes (normal, apnea) the results for PLS are: specificity 90%, sensibility 91% and accuracy 93.56%.

Keywords

biomedical measurement; cardiology; feature extraction; least squares approximations; medical disorders; medical signal processing; patient diagnosis; sleep; HRV analysis; HRV derived parameter minimization; OSA detection improvement; dynamic feature extraction; heart rate variability; obstructive sleep apnea; partial least squares; relevance PLS; Accuracy; Databases; Feature extraction; Heart rate variability; Sleep apnea; Time frequency analysis; Algorithms; Electrocardiography; Heart Rate; Least-Squares Analysis; Signal Processing, Computer-Assisted; Sleep Apnea, Obstructive;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Conference_Location

Buenos Aires

ISSN

1557-170X

Print_ISBN

978-1-4244-4123-5

Type

conf

DOI

10.1109/IEMBS.2010.5627710

Filename

5627710