Monitoring of obstructive sleep apnea in heart failure patients

Abhilash Patangay, Prashanthi Vemuri, Ahmed Tewfik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

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.

Original languageEnglish (US)
Title of host publication29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Pages1043-1046
Number of pages4
DOIs
StatePublished - 2007
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: Aug 23 2007Aug 26 2007

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Other

Other29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Country/TerritoryFrance
CityLyon
Period8/23/078/26/07

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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