Blood pressure waveform analysis by means of wavelet transform (original) (raw)

Abstract

The assessment of cardiovascular function by means of arterial pulse wave analysis (PWA) is well established in clinical practice. PWA is applied to study risk stratification in hypertension, with emphasis on the measurement of the augmentation index as a measure of aortic pressure wave reflections. Despite the fact that the prognostic power of PWA, in its current form, still remains to be demonstrated in the general population, there is general agreement that analysis and interpretation of the waveform might provide a deeper insight in cardiovascular pathophysiology. We propose here the use of wavelet analysis (WA) as a tool to quantify arterial pressure waveform features, with a twofold aim. First, we discuss a specific use of wavelet transform in the study of pressure waveform morphology, and its potential role in ascertaining the dynamics of temporal properties of arterial pressure waveforms. Second, we apply WA to evaluate a database of carotid artery pressure waveforms of healthy middle-aged women and men. Wavelet analysis has the potential to extract specific features (wavelet details), related to wave reflection and aortic valve closure, from a measured waveform. Analysis showed that the fifth detail, one of the waveform features extracted applying the wavelet decomposition, appeared to be the most appropriate for the analysis of carotid artery pressure waveforms. What remains to be assessed is how the information embedded in this detail can be further processed and transformed into quantitative data, and how it can be rendered useful for automated waveform classification and arterial function parameters with potential clinical applications.

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References

  1. Aboy M, McNames J, Thong T, Tsunami D, Ellenby MS, Goldstein B (2005) An automatic beat detection algorithm for pressure signals. IEEE Trans Biomed Eng 52(10):1662–1670
    Article Google Scholar
  2. Bera AK, Jarque CM (1981) Efficient tests for normality, homoscedasticity and serial independence of regression residuals: Monte Carlo evidence. Econ Lett 7(4):313–318
    Article Google Scholar
  3. Chui KC (1992) An introduction to wavelets. Wavelet analysis and its applications,vol I. Academic Press, New York
  4. Chui CK (1992) An introduction to wavelets. Academic Press Limited, San Diego
    MATH Google Scholar
  5. Daubechies I (1988) Orthonormal bases of compactly supported wavelets. Commun Pure Appl Math 41:909–996
    Article MATH MathSciNet Google Scholar
  6. Davies JI, Struthers AD (2003) Pulse wave analysis and pulse wave velocity: a critical review of their strengths and weaknesses. J Hypertens 21(3):463–472
    Article Google Scholar
  7. European Society of Hypertension/European Society of Cardiology Guidelines Committee (2003) Guidelines for the management of arterial hypertension. J Hypertens 21:1011–1053
    Article Google Scholar
  8. Gabe IT (1972) Pressure measurement in experimental physiology. In: Bergel DH (ed) Cardiovascular fluid dynamics. London Academic Press, London, pp 11–50
    Google Scholar
  9. Grigioni M, Carotti A, Del Gaudio C, Morbiducci U, Albanese SB, D’Avenio G (2006) Multiresolution analysis of heart rate variability as investigational tool in experimental fetal cardiac surgery. Ann Biomed Eng 34(5):799–809
    Article Google Scholar
  10. Kelly RP, Hayward CS, Ganis J et al (1989) Non-invasive registration of the arterial pressure pulse waveform using high-fidelity applanation tonometry. J Vasc Med Biol 1:142–149
    Google Scholar
  11. Kelly RP, Hayward CS, Avolio AP, O’Rourke MF (1989) Non-invasive determination of age-related changes in human arterial pulse. Circulation 80:1652–1659
    Google Scholar
  12. Kelly RP, Hayward CS, Avolio AP, O’Rourke MF (1989) Non-invasive determination of age-related changes in human arterial pulse. Circulation 80:1652–1659
    Google Scholar
  13. Kelly RP, Gibbs HH, O’Rourke MF et al (1990) Nitroglycerine has more favourable effects on left ventricular afterload than apparent from measurement of pressure in a peripheral artery. Eur Heart J 11:328–333
    Google Scholar
  14. Kolmogorov AN (1956) Foundations of the theory of probability, 2nd english edn, translation edited by Nathan Morrison, Chelsea Publishing Company, New York
  15. Korotkoff NS (1905) On methods of studying blood pressure. Bull Imp Mil Med Acad 11:365–367 (in Russian with discussions)
    Google Scholar
  16. Li JK-J (2004) Dynamics of the cardiovascular system. World Scientific Publishing, Singapore
    Google Scholar
  17. Mackenzie J (1902) The study of the pulse: arterial, venous and hepatic, and of the movements of the heart. Young J Pentland, Edinburgh
    Google Scholar
  18. Mager DE, Abernethy DR (2007) Use of wavelet and fast Fourier transforms in pharmacodynamics. J Pharmacol Exp Ther 321:423–430
    Article Google Scholar
  19. Mallat S (1987) A compact multiresolution representation: the wavelet model. In: Proceedings of IEEE computer society workshop on computer vision, IEEE. Computer Society Press, Washington, pp 2–7
  20. Meyer Y (1993) Wavelets: algorithms and applications. Society for industrial and applied mathematics, Philadelphia, pp 13–31, 101–105
  21. Mitchell GF, Parise H, Benjamin EJ, Larson MG, Keyes MJ, Vita JA et al (2004) Changes in arterial stiffness and wave reflection with advancing age in healthy men and women: the Framingham heart study. Hypertension 43:1239–1245
    Article Google Scholar
  22. Murgo JP, Westerhof N, Giolma JP, Altobelli SA (1980) Aortic input impedance in normal man: relationship to pressure wave forms. Circulation 62:105–116
    Google Scholar
  23. Nichols WW, O’Rourke MF (1998) McDonald’s blood flow in arteries. Arnold, London
  24. Nichols WW, Nicolini FA, Pepine CJ (1992) Determinants of isolated systolic hypertension in the elderly. J Hypertens 10: S73–S77
    Google Scholar
  25. O’Rourke MF (2002) From theory into practice: arterial hemodynamics in clinical hypertension. J Hypertens 20:1901–1915
    Article Google Scholar
  26. O’Rourke MF (2004) Pulse waveform analysis and arterial stiffness: realism can replace evangelism and scepticism. J Hypertens 22(8):1633–1634
    Article Google Scholar
  27. Percival DP (1995) On estimation of the wavelet variance. Biomedika 82:619–631
    Google Scholar
  28. Pichot V, Gaspoz JM, Molliex S, Antoniadis A, Busso T, Roche F et al (1999) Wavelet transform to quantify heart rate variability and to assess its instantaneous changes. J Appl Physiol 86:1081–1091
    Google Scholar
  29. Postel-Vinay NA (1996) Century of arterial hypertension 1896–1996. Wiley, Chichester
    Google Scholar
  30. Rietzschel ER, De Buyzere ML, Bekaert S, Segers P, De Bacquer D, Cooman L et al (2007) Rationale, design, methods and baseline characteristics of the Asklepios Study. Eur J Cardiovasc Prev Rehabil 14(2):179–191
    Article Google Scholar
  31. Segers P, Rietzschel ER, De Buyzere ML, Vermeersch SJ, De Bacquer D, Van Bortel LM et al (2007) R and on behalf of the Asklepios investigators, noninvasive (input) impedance, pulse wave velocity, and wave reflection in healthy middle-aged men and women. Hypertension 49(6):1248–1255
    Article Google Scholar
  32. Takazawa K, Tanaka N, Takeda K, Kurosu F, Ibukiyama C (1995) Underestimation of vasodilator effects of nitroglycerin by upper limb blood pressure. Hypertension 26:520–523
    Google Scholar
  33. Unser M (1996) Vanishing moments and the approximation power of wavelet expansions, image processing, 1996. In: Proceedings of international conference, vol 1, Issue, 16–19 September 1996, pp 629–632
  34. Wainer H (1976) Robust statistics: a survey and some prescriptions. J Educ Stat 1(4): 285–312 (Winter, 1976)
    Google Scholar
  35. Westerhof N, Sipkema P, van den Bos CG, Elzinga G (1972) Forward and backward waves in the arterial system. Cardiovasc Res 6:648–656
    Article Google Scholar
  36. Wilkinson IB, Mac Callum H, Flint L, Cockcroft JR, Newby DE, Webb DJ (2000) The influence of heart rate on augmentation index and central arterial pressure in humans. J Physiol 525(Pt 1):263–270
    Article Google Scholar
  37. Williams S (2004) Pulse wave analysis and hypertension: evangelism versus scepticism. J Hypertens 22(3):447–449
    Article Google Scholar

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Acknowledgments

The authors wish to thank Sara Assecondi (MEDISIP, IBBT, IBitech, Ghent University) for the insightful suggestions and the valuable support in the manuscript preparation. The authors wish also to thank Enrico Primo Tomasini and Lorenzo Scalise (Department of Mechanics, Politechnic University of Marche) for the support to the research activity.

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Authors and Affiliations

  1. Cardiovascular Mechanics and Biofluid Dynamics, IBiTech, Ghent University, Ghent, Belgium
    Mirko De Melis, Tom Claessens & Patrick Segers
  2. Department of Mechanics, Polytechnic University in Turin, Turin, Italy
    Umberto Morbiducci & Franco M. Montevecchi
  3. Department of Cardiovascular Diseases, Ghent University Hospital, Ghent, Belgium
    Ernst R. Rietzschel & Marc De Buyzere
  4. AtCor Medical, Sydney, Australia
    Ahmad Qasem
  5. Heymans Institute of Pharmacology, Ghent University, Ghent, Belgium
    Luc Van Bortel
  6. Australian School of Advanced Medicine, Macquarie University, Sydney, Australia
    Albert Avolio
  7. Institute Biomedical Technology, Ghent University, De Pintelaan 185, Block B, 5th floor, 9000, Ghent, Belgium
    Mirko De Melis

Authors

  1. Mirko De Melis
  2. Umberto Morbiducci
  3. Ernst R. Rietzschel
  4. Marc De Buyzere
  5. Ahmad Qasem
  6. Luc Van Bortel
  7. Tom Claessens
  8. Franco M. Montevecchi
  9. Albert Avolio
  10. Patrick Segers

Corresponding author

Correspondence toMirko De Melis.

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De Melis, M., Morbiducci, U., Rietzschel, E.R. et al. Blood pressure waveform analysis by means of wavelet transform.Med Biol Eng Comput 47, 165–173 (2009). https://doi.org/10.1007/s11517-008-0397-9

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