Autonomic cardiac control in animal models of cardiovascular diseases. I. Methods of variability analysis

Biomed Tech (Berl). 2007 Feb;52(1):43-9. doi: 10.1515/BMT.2007.009.


Analysis of heart rate variability (HRV) and blood pressure variability (BPV) and baroreceptor sensitivity (BRS) has become a proven tool in clinical cardiovascular diagnostics and risk stratification. In the present work, traditional and new methodological approaches for analysis of HRV, BPV, and BRS data are summarized. HRV, BPV, and BRS parameters were obtained from animal studies designed to study pathogenetic mechanisms of distinct cardiovascular diseases. Different non-linear approaches for HRV and BPV analysis are presented here, in particular measures of complexity based on symbolic dynamics. The dual sequence method (DSM) was employed for BRS analysis. In comparison to the classical measure of BRS using the average slope [ms/mm Hg], DSM offers additional information about the time-variant coupling between BPV and HRV. Since cardiovascular regulation shares common features among different species, data on HRV and BPV, as well as BRS, in animal models might be useful for understanding the pathogenetic mechanisms of cardiovascular diseases in humans and in the development of new diagnostic approaches.

Publication types

  • Evaluation Study

MeSH terms

  • Algorithms
  • Animals
  • Autonomic Nervous System / physiopathology
  • Baroreflex*
  • Blood Pressure*
  • Cardiovascular Diseases / diagnosis*
  • Cardiovascular Diseases / physiopathology*
  • Computer Simulation
  • Diagnosis, Computer-Assisted / methods*
  • Disease Models, Animal
  • Feedback / physiology
  • Heart Rate*
  • Models, Cardiovascular*
  • Reproducibility of Results
  • Sensitivity and Specificity