A stochastic nonlinear autoregressive algorithm reflects nonlinear dynamics of heart-rate fluctuations

Research output: Contribution to journalJournal articleResearchpeer-review

Antonis A. Armoundas, Kihwan Ju, Nikhil Iyengar, Jorgen K. Kanters, Philip J. Saul, Richard J. Cohen, Ki H. Chon

A new computational algorithm to quantify nonlinear heart-rate dynamics was developed. The term stochastic nonlinear autoregressive (SNAR) model was coined to emphasize that the method models both the deterministic and the stochastic components of the system. Finally, the applicability and reliability of the SNAR algorithm to predict the outcome of cardiac electrophysiologic study (EPS) were demonstrated.

Original languageEnglish
JournalAnnals of Biomedical Engineering
Volume30
Issue number2
Pages (from-to)192-201
Number of pages10
ISSN0090-6964
DOIs
Publication statusPublished - 27 Apr 2002

    Research areas

  • Heart-rate variability, Lyapunov exponent, Nonlinear dynamics, Stochastic nonlinear autoregressive model

ID: 204300058