AFVP - A Realistic Ventricular Rhythm Model During AF

[Schematic of Model]

AFVP generates a synthesized beat-to-beat interval sequence of ventricular excitations with a realistic structure observed during AF. The AV junction (AVJ) is treated as a lumped structure characterized by refractoriness and automaticity. Bombarded by random AF impulses, the AVJ can also be invaded by the VP-induced retrograde wave. The model includes bi-directional conduction delays in the AVJ and ventricle. Both refractory period and conduction delay of the AVJ are dependent upon its recovery time. The electrotonic modulation by blocked impulses is also considered in the model. With proper parameter settings, the model can account for most principal statistical properties of the RR intervals during AF.

AFVP was contributed to PhysioNet by Jie Lian, Dirk Müssig, and Volker Lang, all from Micro Systems Engineering, Inc., a subsidiary of Biotronik GmbH. The code is freely available under the GNU GPL (General Public License), and can be downloaded as a single gzip-compressed tar archive, afvp.tar.gz, or as individual files.

The routines used by AFVP are described in

Lian J., Müssig D., Lang V. Computer Modeling of Ventricular Rhythm During Atrial Fibrillation and Ventricular Pacing [external link, subscription required] IEEE Transactions on Biomedical Engineering 53(8): 1512-1520; 2006.

Lian, J., Clifford, G.D., Muessig, D. and Lang, V., Open source model for generating RR intervals in atrial fibrillation and beyond. BioMedical Engineering OnLine 6:9, doi:10.1186/1475-925X-6-9; 2007.

Of related interest is the set of RR interval generators entered in the PhysioNet/Computers in Cardiology Challenge 2002. These C-code algorithms were attempts to address the questions: Can you construct a simulation of the RR interval time series spanning a full 24 hours with sufficient verisimilitude to be taken as real? Can you classify a mixed set of real and simulated RR interval time series?

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Updated Tuesday, 11 October 2016 at 18:01 BRT

PhysioNet is supported by the National Institute of General Medical Sciences (NIGMS) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH grant number 2R01GM104987-09.