Artificial Intelligence in Medicine
Volume 43, Issue 2 , Pages 151-165 , June 2008

Complexity and spectral analysis of the heart rate variability dynamics for distant prediction of paroxysmal atrial fibrillation with artificial intelligence methods

  • Yuriy V. Chesnokov

      Affiliations

    • Corresponding Author InformationPresent address: 112/1, Room 14, Krasnoarmeyskaya Street, Krasnodar 350015, Russia. Tel.: +7 918 048 8394; fax: +7 861 231 6103.

Received 18 August 2007 ,Revised 28 February 2008 ,Accepted 18 March 2008.

References 

  1. Benjamin EJ, Wolf PA, D’Agostino RB, Silbershatz H, Kannel WB, Levy D. Impact of atrial fibrillation on the risk of death. Circulation. 1998;98:946–952
  2. Kannel WB, Abbott RD, Savage DD, McNamara OM. Epidemiologic features of chronic atrial fibrillation: The Framingham study. N Engl J Med. 1982;306:1018–1022
  3. Wheldon NM. Atrial fibrillation and anticoagulant therapy. Eur Heart J. 1995;16:302–312
  4. Go AS, Hylek EM, Phillips KA, Chang Y-C, Henault LE, Selby JV, et al. Prevalence of diagnosed atrial fibrillation in adults. J Am Med Assoc. 2001;286:2370–2375
  5. Prakash A, Saksena S, Hill M, Krol RB, Munsif AN, Giorgberidze I, et al. Acute effects of dual site right atrial pacing in patients with spontaneous and inducible atrial flutter and fibrillation. J Am Coll Cardiol. 1997;29(5):1007–1014
  6. Daubert JC, Pavin D, Victor F, Mabo P. Cardiac pacing for terminating and preventing atrial flutter and fibrillation. In:  Saoudi N,  Schoels W,  El-Sherif N editor. Armonk, atrial flutter and fibrillation: from basic to clinical applications. NY: Futura; 1998;
  7. Papageorgiou P, Anselme F, Kirchhof HJ, Epstein LM, Josephson MR. Coronary sinus pacing prevents induction of atrial fibrillation. Circulation. 1997;96(6):1893–1898
  8. Levy T, Fotopoulos G, Walker S, Rex S, Octave M, Paul V, et al. Randomized controlled study investigating the effect of biatrial pacing in prevention of atrial fibrillation after coronary artery bypass grafting. Circulation. 2000;102(12):1382–1387
  9. Kutarski A, Wojcik M, Oleszczak K, Schaldach M. What is the optimal configuration for permanent biatrial pacing. Prog Biomed Res. 2000;5(2):73–83
  10. Thong T, McNames J, Aboy M, Goldstein B. Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes. IEEE Trans Biomed Eng. 2004;51(4):561–570
  11. Physionet AFPDB database. http://www.physionet.org/physiobank/database/afpdb [accessed December 5, 2007].
  12. Moody G, Goldberger S, McClennen S, Swiryn S. Predicting the onset of paroxysmal atrial fibrillation: the computers in cardiology challenge 2001. Comput Cardiol. 2001;113–116
  13. Shin D-G, Yoo C-S, Yi S-H, Bae J-H, Kim Y-J, Park J-S, et al. Prediction of paroxysmal atrial fibrillation using nonlinear analysis of the R-R interval dynamics before the spontaneous onset of atrial fibrillation. Circ J. 2006;70(1):94–99
  14. Vikman S, Mäkikallio TH, Yli-Mäyry S, Pikkujämsä S, Koivisto A-M, Reinikainen P, et al. Altered complexity and correlation properties of R–R interval dynamics before the spontaneous onset of paroxysmal atrial fibrillation. Circulation. 1999;100(20):2079–2084
  15. Bettoni M, Zimmermann M. Autonomic tone variations before the onset of paroxysmal atrial fibrillation. Circulation. 2002;105(23):2753–2759
  16. Amar D, Zhang H, Miodownik S, Kadish AH. Competing autonomic mechanisms precede the onset of postoperative atrial fibrillation. J Am Coll Cardiol. 2003;42(7):1262–1268
  17. Tomita T, Takei M, Saikawa Y, Hanaoka T, Uchikawa S-I, Tsutsui H, et al. Role of autonomic tone in the initiation and termination of paroxysmal atrial fibrillation in patients without structural heart disease. J Cardiovasc Electrophysiol. 2003;14(6):559–564
  18. Tomoda Y, Uemura S, Fujimoto S, Yamamoto H, Matsukura Y, Hashimoto T, et al. Assessment of autonomic nervous activity before the onset of paroxysmal atrial fibrillation. J Cardiol. 1998;31(1):11–17
  19. Huang JL, Wen Z-C, Lee W-L, Chang M-S, Chen S-A. Changes of autonomic tone before the onset of paroxysmal atrial fibrillation. Int J Cardiol. 1998;66(3):275–283
  20. Vincenti A, Brambilla R, Fumagalli MG, Merola R, Pedretti S. Onset mechanism of paroxysmal atrial fibrillation detected by ambulatory Holter monitoring. Europace. 2006;8(3):204–210
  21. Fioranelli M, Piccoli M, Mileto GM, Sgreccia F, Azzolini P, Risa MP, et al. Analysis of heart rate variability five minutes before the onset of paroxysmal atrial fibrillation. Pacing Clin Electrophysiol. 1999;22(5):743–749
  22. Herweg B, Dalal P, Nagy B, Schweitzer P. Power spectral analysis of heart period variability of preceding sinus rhythm before initiation of paroxysmal atrial fibrillation. Am J Cardiol. 1998;82(7):869–874
  23. Physionet AFDB database. http://www.physionet.org/physiobank/database/afdb [accessed December 5, 2007].
  24. Chesnokov YV, Nerukh D, Glen RC. Individually adaptable automatic QT detector. Comput Cardiol. 2006;33
  25. Kamath M, Fallen E. Power spectral analysis of heart rate variability: a noninvasive signature of cardiac autonomic function. Crit Rev Biomed Eng. 1993;21(3):245–311
  26. van Ravenswaaij-Arts C, Kollee LAA, Hopman JCW, Stoelinga GBA, van Geijn HP. Heart rate variability, review. Ann Intern Med. 1993;118(6):436–447
  27. Kitney R, Fulton T, McDonald A, Linkens D. Transient interactions between blood pressure, respiration and heart rate in man. J Biomed Eng. 1985;7:217–224
  28. Malliani A, Pagani M, Lombardi F, Cerutti S. Cardiovascular neural regulation explored in the frequency domain. Circulation. 1991;84(2):482–492
  29. Pagani M, Lombardi F, Guzzetti S, Rimoldi O, Furlan R, Pizzinelli P, et al. Power spectral analysis of heart rate and arterial pressure as a marker of sympathovagal interaction in man and conscious dog. Circ Res. 1986;59:178–193
  30. Akselrod S, Gordon D, Madved J, Snidman N, Shannon D, Cohen R. Hemodynamic regulation: investigation by spectral analysis. Am J Physiol. 1985;249:867–875
  31. Pomeranz B, Macaulay R, Caudill M, Kutz I, Adam D, Gordon D, et al. Assessment of autonomic function in man by heart rate spectral analysis. Am J Physiol. 1985;248:151–153
  32. Baselli G, Cerutti S, Civardi S, Lombardi F, Malliani A, Merri M, et al. Heart rate variability signal processing: a quantitative approach as an aid to diagnosis in cardiovascular pathologies. Int J Bio Med Comput. 1987;20:51–70
  33. Novak P, Novak V. Time/frequency mapping of the heart rate, blood pressure and respiratory signals. Med Biol Eng Comput. 1993;31:103–110
  34. Novak P, Novak V, Champlain JD, Blanc AL, Martin R, Nadeau R. Influence of respiration on heart rate and blood pressure fluctuations. J Appl Physiol. 1993;74(2):617–626
  35. Katona P, Jih F. Respiratory sinus arrhythmia: noninvasive measure of parasympathetic cardiac control. J Appl Physiol. 1975;39(5):801–805
  36. Wiklund U, Akay M, Niklasson U. Short-term analysis of heart-rate variability by adapted wavelet transforms. IEEE Eng Med Biol. 1997;16:113–118
  37. Richman JS, Moorman JR. Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol. 2000;278:2039–2049
  38. Cysarz D, Bettermann H, van Leeuwen P. Entropies of short binary sequences in heart period dynamics. AJP Heart. 2000;278:2163–2172
  39. Eckmann J-P, Ruelle D. Ergodic theory of chaos and strange attractors. Rev Mod Phys. 1985;57:617–654
  40. Pincus SM. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci USA. 1991;88:2297–2301
  41. Pincus SM. Assessing serial irregularity and its implications for health. Ann NY Acad Sci. 2002;954:245–267
  42. Grassberger P, Schreiber T, Schaffrath C. Nonlinear time sequence analysis. Int J Bifurcation Chaos Appl Sci Eng. 1991;1:547
  43. Ary M-C, Goldberger L, Peng C-K. Multiscale entropy analysis of complex physiologic time series. Phys Rev Lett. 2002;89(6):
  44. Muller B, Reinhardt J. Neural networks. Berlin: Springer Verlag; 1990;
  45. Welstead ST. Neural network and fuzzy logic applications in C/C++. New York, NY: John Wiley & Sons, Inc.; 1994;
  46. Haykin S. Neural networks: a comprehensive foundation. New York, NY: Macmillan; 1994;
  47. Gilles C, Hilario M, Sax H, Hugonnet S, Geissbuhler A. Learning from imbalanced data in surveillance of nosocomial infection. Artif Intell Med. 2006;37:7–18
  48. Kohonen T. Self-organization and associative memory. 2nd edition. Berlin: Springer-Verlag; 1987;
  49. Kohonen T. Self-organized formation of topologically correct feature maps. Biol Cybern. 1982;43:141–152
  50. Vapnik VN. The nature of statistical learning theory. New York: Springer-Verlag; 1995;
  51. Vapnik VN, Lerner A. Pattern recognition using generalized portrait method. Automat Remote Control. 1963;24:774–780

PII: S0933-3657(08)00038-9

doi: 10.1016/j.artmed.2008.03.009

Artificial Intelligence in Medicine
Volume 43, Issue 2 , Pages 151-165 , June 2008

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