(C language) Integrated dual-chamber heart and pacer (IDHP) model
Description
Modern cardiac pacemaker can sense electrical activity in both atrium and ventricle, and deliver precisely timed stimulations to one or both chambers on demand. However, little is known about how the external cardiac pacing interacts with the heart’s intrinsic activity. In this study, we present an integrated dual-chamber heart and pacer (IDHP) model to simulate atrial and ventricular rhythms in the presence of dual chamber cardiac pacing and sensing. The IDHP model is an extension and improvement of a previously developed open source model for simulating ventricular rhythms in atrial fibrillation and ventricular pacing. The new model takes into account more realistic properties of atrial and ventricular rhythm generators, as well as bi-directional conductions in atrium, ventricle, and the atrio-ventricular junction. Moreover, an industry-standard dual-chamber pacemaker timing control logic is incorporated in the model. We present examples to show that the new model can generate realistic cardiac rhythms in both physiologic and pathologic conditions, and simulate various interactions between intrinsic heart activity and extrinsic cardiac pacing. Among many applications, the IDHP model provides a new simulation platform where it is possible to bench test advanced pacemaker algorithms in the presence of different types of cardiac rhythms.
Model described in detail in:
Lian J, Mussig D ,"Heart Rhythm and Cardiac Pacing: An Integrated Dual-Chamber Heart and Pacer Model", Annals of Biomedical Engineering, Vol. 37, No. 1, January 2009, pp. 64–81 DOI: 10.1007/s10439-008-9585-x
Download Model files (zipped)
Setting up and running the model:
- Note: This model is designed to be compiled in a unix/linux type environment where a C compiler and make file support exists.
- Please see README.txt for more detailed notes about this model.
- To see model generated event markers you must have Matlab available on your system (or create your own graphing tool).
- Example config.txt files accompany the model to help you see examples similar to that shown in figures 6-11 of ABME 2009 paper. Note: figures were generated with random number seeds.
- To run the same simulation over and over, specify the seed at model run time.
- Example syntax using provided config.txt example:
./idhp ABME_DDI_Afib_Fig8_config.txt 10,
where '10' is the seed number.
Author(s)
JIE LIAN and DIRK MUSSIG
Micro Systems Engineering, Inc., 6024 SW Jean Road, Lake Oswego, OR 97035, USA
For questions concerning model, please email Jie Lian at:
jie.lian@biotronik.com
We welcome comments and feedback for this model. Please use the button below to send comments:
Abraham, W. T., and D. L. Hayes. Cardiac resynchronization therapy for heart failure. Circulation 108:2596–2603, 2003. doi:10.1161/01.CIR.0000096580.26969.9A. Asano, Y., J. Saito, T. Yamamoto, M. Uchida, Y. Yamada, K. Matsumoto, and H. Matsuo. Electrophysiologic determinants of ventricular rate in human atrial fibrillation. J. Cardiovasc. Electrophysiol. 6:343–349, 1995. doi:10.1111/ j.1540-8167.1995.tb00406.x. Chorro, F. J., C. J. Kirchhof, J. Brugada, and M. A. Allessie. Ventricular response during irregular atrial pacing and atrial fibrillation. Am. J. Physiol. 259:H1015–H1021, 1990. Cohen, R. J., R. D. Berger, and T. E. Dushane. A quantitative model for the ventricular response during atrial fibrillation. IEEE Trans. Biomed. Eng. 30:769–781, 1983. doi:10.1109/TBME.1983.325077. Ellenbogen, K. A., and M. A. Wood. Cardiac Pacing and ICDs. 4th ed. Malden: Blackwell Publishing, 2005. Goldberger, A. L., L. A. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C. K. Peng, and H. E. Stanley. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101:E215–E220, 2000. Goldstein, R. E., and G. O. Barnett. A statistical study of the ventricular irregularity of atrial fibrillation. Comput. Biomed. Res. 1:146–161, 1967. doi:10.1016/0010- 4809(67)90013-4. Heethaar, R. M., J. J. Denier van der Gon, and F. L. Meijler. Mathematical model of A-V conduction in the rat heart. Cardiovasc. Res. 7:105–114, 1973. doi:10.1093/cvr/ 7.1.105. Heethaar, R. M., R. M. De Vos Burchart, J. J. Denier Van Der Gon, and F. L. Meijler. A mathematical model of A-V conduction in the rat heart. II. Quantification of concealed conduction. Cardiovasc. Res. 7:542–556, 1973. doi:10.1093/ cvr/7.4.542. Honzikova, N., B. Fiser, and B. Semrad. Ventricular function in patients with atrial fibrillation. A simulation model study with the aid of a computer. Cor. Vasa. 15:257– 264, 1973. Jorgensen, P., C. Schafer, P. G. Guerra, M. Talajic, S. Nattel, and L. Glass. A mathematical model of human atrioventricular nodal function incorporating concealed conduction. Bull. Math. Biol. 64:1083–1099, 2002. doi:10.1006/bulm.2002.0313. Lian, J., D. Mu¨ ssig, and V. Lang. Computer modeling of ventricular rhythm during atrial fibrillation and ventricular pacing. IEEE Trans. Biomed. Eng. 53:1512–1520, 2006. doi:10.1109/TBME.2006.876627. Lian, J., D. Mu¨ ssig, and V. Lang. Validation of a novel atrial fibrillation model through simulated atrial pacing protocols. In: Proceedings of the 28th Annual International Conference of IEEE EMBS, 2006, pp. 4024–4027. Lian, J., D. Mu¨ ssig, and V. Lang. On the role of ventricular conduction time in rate stabilization for atrial fibrillation. Europace 9:289–293, 2007. doi:10.1093/europace/ eum006. Lian, J., D. Mu¨ ssig, and V. Lang. Ventricular rate smoothing for atrial fibrillation: a quantitative comparison study. Europace 9:506–513, 2007. doi:10.1093/europace/ eum088. Lian, J., G. Clifford, D. Mu¨ ssig, and V. Lang. Open source model for generating RR intervals in atrial fibrillation and beyond. Biomed. Eng. OnLine 6:9, 2007. doi:10.1186/1475- 925X-6-9. Meijler, F. L., J. Jalife, J. Beaumont, and D. Vaidya. AV nodal function during atrial fibrillation: the role of electrotonic modulation of propagation. J. Cardiovasc. Electrophysiol. 7:843–861, 1996. doi:10.1111/j.1540-8167.1996. tb00597.x. Moe, G. K., and J. A. Abildskov. Observations on the ventricular dysrhythmia associated with atrial fibrillation in the dog heart. Circ. Res. 14:447–460, 1964. Mond, H. G., M. Irwin, C. Morillo, and H. Ector. The world survey of cardiac pacing and cardioverter defibrillators: calendar year 2001. Pacing Clin. Electrophysiol. 27:955–964, 2004. doi:10.1111/j.1540-8159.2004.00565.x. Padeletti, L., F. Fantini, A. Michelucci, P. Pieragnoli, A. Colella, N. Musilli, G. Ricciardi, T. A. Buhr, and S. Valsecchi. Rate stabilization by right ventricular apex or His bundle pacing in patients with atrial fibrillation. Europace 7:454–459, 2005. doi:10.1016/j.eupc.2005.05.007. Talajic, M., D. Papadatos, C. Villemaire, L. Glass, and S. Nattel. A unified model of atrioventricular nodal conduction predicts dynamic changes in Wenckebach periodicity. Circ. Res. 68:1280–1293, 1991. Trohman, R. G., M. H. Kim, and S. L. Pinski. Cardiac pacing: the state of the art. Lancet 364:1701–1719, 2004. doi:10.1016/S0140-6736(04)17358-3. Vereckei, A., Z. Vera, H. P. Pride, and D. P. Zipes. Atrioventricular nodal conduction rather than automaticity determines the ventricular rate during atrial fibrillation and atrial flutter. J. Cardiovasc. Electrophysiol. 3:534–543, 1992. Wittkampf, F. H., and M. J. De Jongste. Rate stabilization by right ventricular pacing in patients with atrial fibrillation. Pacing Clin. Electrophysiol. 9:1147–1153, 1985. doi:10.1111/j.1540-8159.1986.tb06685.x. Wittkampf, F. H., M. J. de Jongste, H. I. Lie, and F. L. Meijler. Effect of right ventricular pacing on ventricular rhythm during atrial fibrillation. J. Am. Coll. Cardiol. 11:539–545, 1988. Zeng, W., and L. Glass. Statistical properties of heartbeat intervals during atrial fibrillation. Phys. Rev. E 54:1779– 1784, 1996. doi:10.1103/PhysRevE.54.1779
Model development and archiving support at https://www.imagwiki.nibib.nih.gov/physiome provided by the following grants: NIH U01HL122199 Analyzing the Cardiac Power Grid, 09/15/2015 - 05/31/2020, NIH/NIBIB BE08407 Software Integration, JSim and SBW 6/1/09-5/31/13; NIH/NHLBI T15 HL88516-01 Modeling for Heart, Lung and Blood: From Cell to Organ, 4/1/07-3/31/11; NSF BES-0506477 Adaptive Multi-Scale Model Simulation, 8/15/05-7/31/08; NIH/NHLBI R01 HL073598 Core 3: 3D Imaging and Computer Modeling of the Respiratory Tract, 9/1/04-8/31/09; as well as prior support from NIH/NCRR P41 RR01243 Simulation Resource in Circulatory Mass Transport and Exchange, 12/1/1980-11/30/01 and NIH/NIBIB R01 EB001973 JSim: A Simulation Analysis Platform, 3/1/02-2/28/07.