Medical Engineering & Physics
Volume 28, Issue 8 , Pages 809-815 , October 2006

Cardiac state diagnosis using adaptive neuro-fuzzy technique

  • N. Kannathal

      Affiliations

    • ECE Division, NgeeAnn Polytechnic, 535, Clementi Road, Singapore 599489, Singapore
    • Department of Electrical and Computer Engineering Division, National University of Singapore, Singapore
    • Corresponding Author InformationCorresponding author. Tel.: +65 64606482.
  • ,
  • C.M. Lim

      Affiliations

    • ECE Division, NgeeAnn Polytechnic, 535, Clementi Road, Singapore 599489, Singapore
  • ,
  • U. Rajendra Acharya

      Affiliations

    • ECE Division, NgeeAnn Polytechnic, 535, Clementi Road, Singapore 599489, Singapore
  • ,
  • P.K. Sadasivan

      Affiliations

    • Department of Electrical and Computer Engineering Division, National University of Singapore, Singapore

Received 8 December 2004 ,Revised 22 November 2005 ,Accepted 25 November 2005.

References 

  1. Sokolow M, Mcllroy MB, Chiethin MD. Clinical cardiology VLANGE Medical Book; 1990.
  2. Akselrod S, Gordon D, Ubel FA, Shannon DC, Barger MA, Cohen RJ. Power spectrum analysis of heart rate fluctuation. Science. 1981;213:220–222
  3. Pomeranz B, Macaulay RJB, Caudill MA, Kutz I, Adam D, Gordon D, et al. Assessment of autonomic function in humans by heart rate spectral analysis. Am J Physiol. 1985;H151–H153
  4. Eckberg DL. Human sinus arrhythmia as an index of vagal cardiac outflow. J Appl Physiol. 1983;54:961–966
  5. Pagani M, Lombardi F, Guzzetti S, Rimoldi O, Furlan R, Pizzinelli P, et al. Power spectral analysis of heart rate and arterial pressure variability as a marker of sympatho-vagal interaction in man and conscious dog. Circ Res. 1986;59:178–193
  6. Task Force of the Task Force of the European Society of Cardiology and North American Society of Pacing and Electrophysiology . Heart Rate Variability: Standards of measurement, physiological interpretation and clinical use. Eur Heart J. 1996;17:354–381
  7. Malliani A, Pagani M, Lombardi F, Cerutti F. Cardiovascular neural regulation explored in the frequency domain. Circulation. 1991;84:482–492
  8. Malik M. Heart rate variability. Curr Opin Cardiol. 1998;13:36–44
  9. Kantz H, Kurths J, Mayer-Kress G. Nonlinear Analysis of Physiological Data. 1st ed.. Berlin: Springer; 1998;
  10. Grossberger P, Procassia I. Measuring the strangeness of strange attractors. Physica D. 1983;9:189–208
  11. Cysarz D, Bettermann H, van leeuwen P. Entropies of short binary sequences in heart period dynamics. Am J Physiol Heart Circ Physiol. 2000;278:H2163–H2172
  12. Peng CK, Halvin S, Stanley HE, Goldberger AL. Quantification of scaling and crossover phenomena in nonstationary heartbeat time series. CHAOS. 1995;1:82–87
  13. Pincus SM. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci USA. 1991;88:2297–2301
  14. Goldberger AL. Nonlinear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside. Lancet. 1996;347:1312–1314
  15. Bigger JT, Steinman RC, Rolnitzky LM, Fleiss JL, Albrecht P, Cohen RJ. Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants. Circulation. 1996;93:2142–2151
  16. Makkikallio TH, Seppanen T, Niemela M, Airaksinen KEJ , Koistinen JM, Tulppo M, et al. Abnormalities in beat to beat complexity of heart rate dynamics in patients with a previous myocardial infarction. J Am Coll Cardiol. 1996;28:1005–1011
  17. Makikallio TH, Seppanen T, Airaksinen KEJ, Koistinen JM, Tulppo MP, Peng CK, et al. Dynamic analysis of heart rate may predict subsequent ventricular tachycardia after myocardial infarction. Am J Cardiol. 1997;80:779–783
  18. Fell J, Mann K, Roschke J, Gopinathan MS. Nonlinear analysis of continuous ECG during sleep I. Reconstruction. Biol Cybernat. 2000;82:477–483
  19. Radhakrishna Rao KA, Kumar Yergani V, Narayana Dutt D, Vedavathy TS. Characterizing Chaos in heart rate variability time series of panic disorder patients. In: Proceedings of Proceedings of ICBME, Biovision. Bangalore, India, December. 2001;p. 163–167
  20. Mohamed I, Owis , Ahmed H, Abou-Zied , Abou-Bakr M, Youssef , et al. Study of features on nonlinear dynamical modeling in ECG arrhythmia detection and classification. IEEE Trans Biomed Eng. July 2002;49(7):733–736
  21. Dingfei G, Narayanan S, Shankar MK. Cardiac arrhythmia classification using autoregressive modeling. Biomed Eng OnLine. 2002;1(1):5
  22. Rajendra Acharya U, Kumar A, Bhat PS, Lim Choo Min, Iyengar SS, Natarajan K, et al. Classification of cardiac abnormalities using heart rate signals. Med. Biol. Eng. Comput. 2004;42(3):288–293
  23. Jang Roger JS. ANFIS—Adaptive-network-based neuro-fuzzy inference systems. IEEE Trans Syst Man Cybernetics. 1993;20(03):665–685
  24. MIT-BIH Arrhythmia Database. 3rd ed., 1997. MA, USA: Harward-MIT Division of Health Science Technology, Biomedical Medical Centre.
  25. Pan J, Tompkins WJ. Real time QRS detector algorithm. IEEE Trans. Biomed. Eng. 1985;32(3):230–233
  26. Froyland J. Chaos and Coherence. Institute of Physics Publications; 1992;
  27. Das A, Das P, Roy AB. Applicability of Lyapunov exponent in EEG data analysis. Complexity Int. 2002;9:1–8
  28. Rezek IA, Roberts SJ. Complexity measures for physiological signal analysis. IEEE Trans Biomed Eng. 1993;1186–1190
  29. Woo MA, Stevenson WG, Moser DK, Trelease RB, Harper RH. Patterns of beat-to-beat heart rate variability in advanced heart failure. Am Heart J. 1992;123:704–710
  30. Kamen PW, Krum H, Tonkin AM. Poincare plot of heart rate variability allows quantitative display of parasympathetic nervous activity. Clin Sci. 1996;91:201–208
  31. Brennan M, Palaniswami , Kamen P. Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability?. IEEE Trans Biomed Eng. 2001;48(11):1342–1347
  32. Tulppo M, Makikallio TH, Takala TES, Seppanen , Kuikuri H. Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am J Physiol. 1996;71:244–252
  33. Theiler J, Eubank S, Longtin A, Galdrikian B, Farmer JD. Testing for nonlinearity in time series: the method of surrogate data. Physica D. 1992;58:77–94

 A complete complex of an ECG, starting with the P-wave, followed by the QRS-complex and the T-wave

PII: S1350-4533(05)00253-5

doi: 10.1016/j.medengphy.2005.11.011

Medical Engineering & Physics
Volume 28, Issue 8 , Pages 809-815 , October 2006