Monitoring of Obstructive Sleep Apnea in Heart Failure Patients

Author

Patangay, A. ; Vemuri, P. ; Tewfik, A.

Author_Institution

Univ. of Minnesota, Inver Grove Heights

fYear

2007

fDate

22-26 Aug. 2007

Firstpage

1043

Lastpage

1046

Abstract

This research aims to develop a non-intrusive system to monitor obstructive sleep apnea (OSA) in heart failure patients. Heart sounds and ECG are used to develop a support vector machine (SVM) based classifier. The RMS energy in wavelet sub-bands are used as feature vectors. Feature reduction is performed to minimize complexity without loss of performance. Data from 17 patients is parsed into two minute epochs and randomly partitioned into training and test datasets. The training set is used for parameter optimization of the SVM algorithm and a test data set is used to estimate the generalization error of the algorithm. The proposed algorithm has a 85.5% sensitivity and 92.2% specificity for the detection of OSA epochs.

Keywords

bioacoustics; diseases; electrocardiography; medical signal processing; patient monitoring; signal classification; sleep; support vector machines; ECG; RMS energy; SVM based classifier; feature reduction; feature vectors; generalization error estimation; heart failure patients; heart sounds; nonintrusive system; obstructive sleep apnea monitoring; parameter optimization; support vector machine; wavelet sub-bands; Condition monitoring; Electrocardiography; Heart; Partitioning algorithms; Patient monitoring; Performance loss; Sleep apnea; Support vector machine classification; Support vector machines; Testing; Aged; Algorithms; Artificial Intelligence; Diagnosis, Computer-Assisted; Electrocardiography; Female; Heart Auscultation; Heart Failure; Humans; Male; Middle Aged; Pattern Recognition, Automated; Polysomnography; Reproducibility of Results; Sensitivity and Specificity; Sleep Apnea, Obstructive;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE

Conference_Location

Lyon

ISSN

1557-170X

Print_ISBN

978-1-4244-0787-3

Type

conf

DOI

10.1109/IEMBS.2007.4352473

Filename

4352473