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Generation of realistic atrial to atrial interval series during atrial fibrillation

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Abstract

The aim of the this study is to describe a methodological architecture for the generation of realistic atrial to atrial activation intervals (AA) during atrial fibrillation (AF), which can be used to investigate the role of the fibrillatory process in the ventricular response during AF. In this study, a methodology for the generation of AA interval series with a desired probability density function and autocorrelation function is presented. The methodology was evaluated on 2000 AA interval series from 20 endocardial recordings. The results showed that synthetic AA series presented the same statistical characteristics as the real AA series, with a correlation higher than 0.94 (P < 0.01) for all measured statistical parameters. In addition, the role of each statistical characteristic of the AA interval series in the ventricular response during AF is examined using a mathematical model of the atrioventricular node. The statistical characteristics of the AA series influenced the position of more probable RR intervals and the shape of the RR histogram, demonstrating the importance of an accurate characterization and generation of AA interval series during AF. The use of the present methodology may help in understanding the role of the atrial fibrillatory process in the ventricular response during AF.

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References

  1. Chen S, Nie H, Ayers-Glassey B (2008) Lognormal sum approximation with a variant of type IV Pearson distribution. IEEE Commun Lett 12:630–632

    Article  Google Scholar 

  2. Chorro FJ, Kirchhof CJHJ, Brugada J, Allessie MA (1990) Ventricular response during irregular atrial-pacing and atrial-fibrillation. Am J Physiol Heart Circ Physiol 259:H1015–H1021

    CAS  Google Scholar 

  3. Chorro FJ, Sanchis J, Lopez-Merino V, Such L, Avellana JA, Valentin V (1991) Effects of atrial impulse timing on AV concealed conduction in the rabbit heart. Pacing Clin Electrophysiol 14(5 Pt 1):842–853

    Article  PubMed  CAS  Google Scholar 

  4. Climent AM, Guillem MS, Husser D, Castells F, Millet J, Bollmann A (2009) Poincare surface profiles of RR intervals. A novel noninvasive method for the evaluation of preferential AV nodal conduction during atrial fibrillation. IEEE Trans Biomed Eng 56(2):433–442

    Article  PubMed  Google Scholar 

  5. Climent AM, Guillem MS, Husser D, Castells F, Millet J, Bollmann A (2010) Role of the atrial rate as a factor modulating ventricular response during atrial fibrillation. Pacing Clin Electrophysiol 33:1510–1517

    Article  PubMed  Google Scholar 

  6. Climent AM, Guillem MS, Zhang Y, Millet J, Mazgalev T (2011) Functional mathematical model of dual pathway AV nodal conductions. Am J Physiol Heart Circ Physiol 300(4):H1393–H1401

    Article  PubMed  CAS  Google Scholar 

  7. Cohen RJ, Berger RD (1983) A quantitative model for the ventricular response during atrial-fibrillation. IEEE Trans Biomed Eng 30:769–781

    Article  PubMed  CAS  Google Scholar 

  8. Cover TM, Thomas JA (2006) Elements of information theory. Wiley, New York

    Google Scholar 

  9. Devroye L (1989) On random variate generation when only moments or Fourier coefficients are known. Math Comput Simul 31:71–89

    Article  Google Scholar 

  10. Faes L, Nollo G, Antolini R, Gaita F, Ravelli F (2002) A method for quantifying atrial fibrillation organization based on wave-morphology similarity. IEEE Trans Biomed Eng 49:1504–1513

    Article  PubMed  Google Scholar 

  11. Fuster V, Ryden LE, Cannom DS, Crijns HJ, Curtis AB, Ellenbogen KA, Halperin JL, Le Heuzey JY, Kay GN, Lowe JE, Olsson SB, Prystowsky EN, Tamargo JL, Wann S (2006) ACC/AHA/ESC 2006 guidelines for the management of patients with atrial fibrillation. Europace 8:651–745

    Article  PubMed  Google Scholar 

  12. Garrigue S, Mowrey KA, Fahy G, Tchou PJ, Mazgalev TN (1999) Atrioventricular nodal conduction during atrial fibrillation: role of atrial input modification. Circulation 99:2323–2333

    PubMed  CAS  Google Scholar 

  13. Garrigue S, Tchou PJ, Mazgalev TN (1999) Role of the differential bombardment of atrial inputs to the atrioventricular node as a factor influencing ventricular rate during high atrial rate. Cardiovasc Res 44:344–355

    Article  PubMed  CAS  Google Scholar 

  14. Gerstenfeld EP, Sahakian AV, Swiryn S (1992) Evidence for transient linking of atrial excitation during atrial fibrillation in humans. Circulation 86:375–382

    PubMed  CAS  Google Scholar 

  15. Heethaar RM, Denier van der Gon JJ, Meijler FL (1973) Mathematical model of A-V conduction in the rat heart. Cardiovasc Res 7:105–114

    Article  PubMed  CAS  Google Scholar 

  16. Heethaar RM, van der Gon JJ, Meijler FL (1973) Interpretation of some properties of A-V conduction with the help of analog simulation. Eur J Cardiol 1:87–93

    PubMed  CAS  Google Scholar 

  17. Heinrich J (2004) A guide to the Pearson type IV distribution. http://www-cdf.fnal.gov

  18. Inada S, Hancox JC, Zhang H, Boyett MR (2009) One-dimensional mathematical model of the atrioventricular node including atrio-nodal, nodal, and nodal-his cells. Biophys J 97:2117–2127

    Article  PubMed  CAS  Google Scholar 

  19. Izrailev FM, Krokhin AA, Makarov NM, Usatenko OV (2007) Generation of correlated binary sequences from white noise. Phys Rev E 76:1–4

    Article  Google Scholar 

  20. Jorgensen P, Schafer C, Guerra PG, Talajic M, Nattel S, Glass L (2002) A mathematical model of human atrioventricular nodal function incorporating concealed conduction. Bull Math Biol 64:1083–1099

    Article  PubMed  Google Scholar 

  21. Kwan R, Leung C (2007) On the applicability of the Pearson method for approximating distributions in wireless communications. IEEE Trans Commun 55:2065–2069

    Article  Google Scholar 

  22. Lian J, Mussig D, Lang V (2006) Computer modeling of ventricular rhythm during atrial fibrillation and ventricular pacing. IEEE Trans Biomed Eng 53:1512–1520

    Article  PubMed  Google Scholar 

  23. Makse HA, Havlin S, Schwartz M, Stanley HE (1996) Method for generating long-range correlations for large systems. Phys Rev E 53:5445–5449

    Article  CAS  Google Scholar 

  24. Mangin L, Vinet A, Page P, Glass L (2005) Effects of antiarrhythmic drug therapy on atrioventricular nodal function during atrial fibrillation in humans. Europace 7(Suppl 2):71–82

    Article  PubMed  Google Scholar 

  25. Mazgalev TN, Garrigue S, Mowrey KA, Yamanouchi Y, Tchou PJ (1999) Autonomic modification of the atrioventricular node during atrial fibrillation: role in the slowing of ventricular rate. Circulation 99:2806–2814

    PubMed  CAS  Google Scholar 

  26. Meijler FL, Jalife J, Beaumont J, Vaidya D (1996) AV nodal function during atrial fibrillation: the role of electrotonic modulation of propagation. J Cardiovasc Electrophysiol 7:843–861

    Article  PubMed  CAS  Google Scholar 

  27. Meurling CJ, Waktare JE, Holmqvist F, Hedman A, Camm AJ, Olsson SB, Malik M (2001) Diurnal variations of the dominant cycle length of chronic atrial fibrillation. Am J Physiol Heart Circ Physiol 280:H401–H406

    PubMed  CAS  Google Scholar 

  28. Nagahara Y (2004) A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation. Comput Stat Data Anal 47:1–29

    Article  Google Scholar 

  29. Nie H, Chen SH (2007) Lognormal sum approximation with type IV Pearson distribution. IEEE Commun Lett 11:790–792

    Article  Google Scholar 

  30. Pearson K (1895) Contributions to the mathematical theory of evolution. II. Skew variation in homogeneous material. Philos Trans R Soc Lond A 186:343–414

    Article  Google Scholar 

  31. Richter U, Bollmann A, Husser D, Stridh M (2009) Right atrial organization and wavefront analysis in atrial fibrillation. Med Biol Eng Comput 47:1237–1246

    Article  PubMed  Google Scholar 

  32. Sandberg F, Bollmann A, Husser D, Stridh M, Sornmo L (2010) Circadian variation in dominant atrial fibrillation frequency in persistent atrial fibrillation. Physiol Meas 31:531–542

    Article  PubMed  Google Scholar 

  33. Schoenwald AT, Sahakian AV, Sih HJ, Swiryn S (1998) Further observations of “linking” of atrial excitation during clinical atrial fibrillation. Pacing Clin Electrophysiol 21:25–34

    Article  PubMed  CAS  Google Scholar 

  34. Tadros R, Billette J (2009) Rate-dependent AV nodal refractoriness: a new functional framework based on concurrent effects of basic and pretest cycle length. Am J Physiol Heart Circ Physiol 297:H2136–H2143

    Article  PubMed  CAS  Google Scholar 

  35. Tadros R, Lavallee M, Billette J (2006) Unified rate-dependent atrioventricular nodal function: consistent recovery and fatigue properties revealed with S1S2S3 protocols and different recovery indexes. Heart Rhythm 3:959–966

    Article  PubMed  Google Scholar 

  36. Tadros R, Lavallee M, Billette J (2007) Dependence of AV nodal function curves on the selected recovery index: pivotal role of pretest conduction time. J Cardiovasc Electrophysiol 18:978–984

    Article  PubMed  Google Scholar 

  37. Talajic M, Papadatos D, Villemaire C, Glass L, Nattel S (1991) A unified model of atrioventricular nodal conduction predicts dynamic changes in Wenckebach periodicity. Circ Res 68:1280–1293

    PubMed  CAS  Google Scholar 

  38. Vaya C, Rieta JJ (2009) Time and frequency series combination for non-invasive regularity analysis of atrial fibrillation. Med Biol Eng Comput 47:687–696

    Article  PubMed  Google Scholar 

  39. Zeng W, Glass L (1996) Statistical properties of heartbeat intervals during atrial fibrillation. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics 54:1779–1784

    Article  PubMed  CAS  Google Scholar 

  40. Zhang YH, Mazgalev TN (2004) Ventricular rate control during atrial fibrillation and AV node modifications: past, present, and future. Pacing Clin Electrophysiol 27:382–393

    Article  PubMed  Google Scholar 

  41. Zhang QT, Song SH (2008) A systematic procedure for accurately approximating lognormal-sum distributions. IEEE Trans Veh Technol 57:663–666

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by Spanish Ministry of Education and Science under TEC2009-13939; the Universitat Politecnica de Valencia through its research initiative program; and the Spanish Society of Cardiology.

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Authors and Affiliations

  1. Bio-ITACA, Universitat Politecnica de Valencia, Camino de Vera sn, 46022, Valencia, Spain

    Andreu M. Climent, Jose Millet & Maria S. Guillem

  2. Department of Cardiology, Hospital General Universitario Gregorio Marañon, Dr. Esquerdo, 46, 28007, Madrid, Spain

    Felipe Atienza

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  1. Andreu M. Climent
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  2. Felipe Atienza
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  3. Jose Millet
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  4. Maria S. Guillem
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Correspondence to Andreu M. Climent.

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Climent, A.M., Atienza, F., Millet, J. et al. Generation of realistic atrial to atrial interval series during atrial fibrillation. Med Biol Eng Comput 49, 1261–1268 (2011). https://doi.org/10.1007/s11517-011-0823-2

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  • DOI: https://doi.org/10.1007/s11517-011-0823-2

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