A differential autoregressive modeling approach within a point process framework for non-stationary heartbeat intervals analysis

Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3567-70. doi: 10.1109/IEMBS.2010.5627462.


Modeling heartbeat variability remains a challenging signal-processing goal in the presence of highly non-stationary cardiovascular control dynamics. We propose a novel differential autoregressive modeling approach within a point process probability framework for analyzing R-R interval and blood pressure variations. We apply the proposed model to both synthetic and experimental heartbeat intervals observed in time-varying conditions. The model is found to be extremely effective in tracking non-stationary heartbeat dynamics, as evidenced by the excellent goodness-of-fit performance. Results further demonstrate the ability of the method to appropriately quantify the non-stationary evolution of baroreflex sensitivity in changing physiological and pharmacological conditions.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms*
  • Baroreflex / physiology*
  • Computer Simulation
  • Electrocardiography / methods*
  • Heart Rate / physiology*
  • Humans
  • Models, Cardiovascular*
  • Models, Statistical
  • Regression Analysis
  • Stochastic Processes
  • Tilt-Table Test / methods*