A stochastic nonlinear autoregressive algorithm reflects nonlinear dynamics of heart-rate fluctuations
Research output: Contribution to journal › Journal article › Research › peer-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.
|Journal||Annals of Biomedical Engineering|
|Number of pages||10|
|Publication status||Published - 27 Apr 2002|
- Heart-rate variability, Lyapunov exponent, Nonlinear dynamics, Stochastic nonlinear autoregressive model