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Comparison of techniques for time–frequency analysis of the ECG during human ventricular fibrillation

Comparison of techniques for time–frequency analysis of the ECG during human ventricular fibrillation

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Ventricular fibrillation (VF) is a catastrophic and potentially lethal breakdown of heart rhythm. Despite its importance, it remains poorly understood; there are no effective techniques for predicting or preventing VF, and it can only be reliably terminated by a large current pulse: defibrillation. There is currently great interest in using linear and nonlinear signal processing techniques to characterise recordings of VF. Five episodes of VF were recorded from patients in a Coronary Care Unit. Time–frequency distributions (TFDs) of the first 10 s of these recordings were estimated with the short-time Fourier transform, Wigner–Ville, smoothed Wigner–Ville and Choi–Williams algorithms. The smoothed Wigner distribution was found to give a TFD reasonably free of cross-terms, without the additional computational cost of the Choi–Williams algorithm. Used in tandem with the predictable short-time Fourier transform, the smoothed Wigner TFD is a valuable tool for characterising the TFD of human VF.

References

    1. 1)
      • B.L. Pentecost . (1995) The 1995 annual review.
    2. 2)
      • D. Durrer , R.T. v. Dam , G.E. Freud , M.J. Janse , F.L. Meijler , R.C. Arzbaecher . Total excitation of the isolated human heart. Circulation , 899 - 912
    3. 3)
      • M.J. Janse , F.J.L. Van-Cappelle , H. Morsink , A.G. Kleber , F. Wilms-Schopman , R. Cardinal , C.N. D'Alnoncourt , D. Durrer . Flow of ‘injury’ currents and patterns of excitation during early ventricular arrhythmias in acute regional myocardial ischaemia in isolated porcine and canine hearts. Evidence for two different arrhythmogenic mechanisms. Circ. Res. , 151 - 165
    4. 4)
      • S.M. Pogwizd , P.B. Corr . Mechanisms underlying the development of ventricular fibrillation during early myocardial ischaemia. Circ. Res. , 672 - 695
    5. 5)
      • R.S. Damle , N.M. Kanaan , N.S. Robinson , J.J. Goldberger , A.H. Kadish . Spatial and temporal linking of epicardial activation directions duringventricular fibrillation in dogs. Circulation , 1547 - 1558
    6. 6)
      • R.H. Clayton , A. Murray , R.W.F. Campbell . Evidence for electrical organization during ventricular fibrillation in the human heart. J. Cardiovasc. Electrophysiol. , 616 - 624
    7. 7)
      • A.V. Panfilov , A.V. Holden . (1996) Computational Biology of the Heart.
    8. 8)
      • J.N. Herbschleb , R.M. Heethaar , I.V.D. Tweel , A.N.E. Zimmerman , F.L. Meijler . (1979) Signal analysis of ventricular fibrillation, Computers in cardiology.
    9. 9)
      • R.H. Clayton , A. Murray , R.W.F. Campbell . Campbell, Changes in the surface electrocardiogram during the onset of spontaneous ventricular fibrillation in man. Eur. Heart J. , 184 - 188
    10. 10)
      • A.J. Stewart , J.D. Allen , A.A.J. Adgey . Frequency analysis of ventricular fibrillation andresuscitation success. Quarterly J. Med. , 761 - 769
    11. 11)
      • R. Dzwonczyk , C.G. Brown , H.A. Werman . The median frequency of the ECG during ventricular fibrillation: Its use in an algorithm for estimating the duration of cardiac arrest. IEEE Trans. Biomed. Eng. , 640 - 646
    12. 12)
      • L. Cohen . Time–frequency distributions – a review. Proc. IEEE , 941 - 981
    13. 13)
      • F. Hlawatsch , G.F. Boudreaux-Bartels . Linear and quadratic time–frequency signal representations. IEEE Signal Proc. Mag. , 21 - 67
    14. 14)
      • G.F. Boudreaux-Bartels , R. Murray , J.D. Bronzino . (1995) Time-frequency signal representations for biomedical signals, The biomedical engineering handbook.
    15. 15)
      • T.A.C.M. Claasen , W.F.G. Mecklenbrauker . The aliasing problem in discrete-time Wigner distributions. IEEE Trans. Acoust. Speech Signal Process. , 1067 - 1072
    16. 16)
      • W. Martin , P. Flandrin . Wigner–Ville analysis of nonstationary processes. IEEE Trans. Acoust. Speech Signal Process. , 1461 - 1469
    17. 17)
      • H. Choi , W.J. Williams . Improved time–frequency representation of multicomponent signalsusing exponential kernels. IEEE Trans. Acoust. Speech Signal Process. , 862 - 871
    18. 18)
      • R.H. Clayton , A. Murray , A.M. Whittam , R.W.F. Campbell . (1991) Automatic recording of ventricular fibrillation, Computers in cardiology.
    19. 19)
      • U. Eggenreich , P.H. Fleischmann , G. Stark , P. Wach . Effects of propafenone on the median frequency of ventricular fibrillationin Langendorff perfused guinea-pig hearts. Cardiovasc. Res. , 926 - 931
    20. 20)
      • R.H. Clayton , A. Murray , R.W.F. Campbell . Objective features of the surface electrocardiogram during ventricular tachyarrhythmias. Eur. Heart J. , 1115 - 1119
    21. 21)
      • V.X. Afonso , W.J. Tompkins . Detecting ventricular fibrillation. IEEE Eng. in Med. Biol. Mag. , 152 - 159
    22. 22)
      • Z.Y. Lin , J.D.Z. Chen . Time-frequency representation of the electrogastrogram. IEEE Trans. Biomed. Eng. , 267 - 275
    23. 23)
      • P. Novak , V. Novak . Time/frequency mapping of the heart rate, blood pressure and respiratorysignals. Med. Biol. Eng. Comp. , 103 - 110
    24. 24)
      • S. Kay , S.L. Marple . Spectrum analysis: a modern perspective. Proc. IEEE , 1380 - 1419
    25. 25)
      • R.H. Clayton , A. Murray , R.W.F. Campbell . (1993) Estimation of the ECG signal spectrum during ventricular fibrillationusing the fast Fourier transform and maximum entropy methods, Computers in cardiology.
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