Heart Rate Variability Analysis for Patients With Obstructive Sleep Apnea

Abstract

Obstructive sleep apnea (OSA) is a common health concern associated with serious implications and increased cardiovascular morbidity and mortality. This study approaches the problem of identification OSA patients and detection of OSA phases on the basis of heart rate variability (HRV) analysis. Only a single ECC-channel is required for this purpose. We used data from the apnea ECC database 6: 40 patients with documented OSA and 20 controls divided into a learning and a test set of equal size. Commonly used HRV measures as well as some novel parameters are tested. The results are compared by ROC-analysis and promising parameters are combined into a multidimensional vector and evaluated by means of a second order polynomial classifier. Best results are obtained from parameters calculated by time delay embedding and correlation analysis of the interbeat interval series. For the identification task, 95% sensitivity and 100% specificity are achieved on the independent test set. The detection task yields an average classification rate of almost 85%.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411852

Entities

People

  • Chris A. Maier
  • H. Dickhaus
  • M. Bauch

Organizations

  • Heidelberg University

Tags

DTIC Thesaurus Topics

  • Amplitude Modulation
  • Cardiac Arrhythmias
  • Cardiovascular System
  • Classification
  • Correlation Analysis
  • Detection
  • Eigenvalues
  • Electrocardiography
  • Embedding
  • Frequency Domain
  • Health Services
  • Heart
  • Heart Rate
  • Identification
  • Information Science
  • Intervals
  • Periodic Variations

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