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Blood pressure waveform analysis by means of wavelet transform

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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.
Keywords
EVANGELISM, VELOCITY, SKEPTICISM, WOMEN, REFLECTION, HYPERTENSION, INPUT IMPEDANCE, PULSE, ARTERIAL STIFFNESS, HEART-RATE-VARIABILITY

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Chicago
De Melis, M, U Morbiducci, Ernst Rietzschel, MARC DE BUYZERE, A Qasem, Lucas Van Bortel, T Claessens, FM Montevecchi, A Avolio, and Patrick Segers. 2009. “Blood Pressure Waveform Analysis by Means of Wavelet Transform.” Medical & Biological Engineering & Computing 47 (2): 165–173.
APA
De Melis, M, Morbiducci, U., Rietzschel, E., DE BUYZERE, M., Qasem, A., Van Bortel, L., Claessens, T., et al. (2009). Blood pressure waveform analysis by means of wavelet transform. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 47(2), 165–173.
Vancouver
1.
De Melis M, Morbiducci U, Rietzschel E, DE BUYZERE M, Qasem A, Van Bortel L, et al. Blood pressure waveform analysis by means of wavelet transform. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING. HEIDELBERG: SPRINGER HEIDELBERG; 2009;47(2):165–73.
MLA
De Melis, M, U Morbiducci, Ernst Rietzschel, et al. “Blood Pressure Waveform Analysis by Means of Wavelet Transform.” MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 47.2 (2009): 165–173. Print.
@article{973435,
  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.},
  author       = {De Melis, M and Morbiducci, U and Rietzschel, Ernst and De Buyzere, Marc and Qasem, A and Van Bortel, Lucas and Claessens, T and Montevecchi, FM and Avolio, A and Segers, Patrick},
  issn         = {0140-0118},
  journal      = {MEDICAL \& BIOLOGICAL ENGINEERING \& COMPUTING},
  language     = {eng},
  number       = {2},
  pages        = {165--173},
  publisher    = {SPRINGER HEIDELBERG},
  title        = {Blood pressure waveform analysis by means of wavelet transform},
  url          = {http://dx.doi.org/10.1007/s11517-008-0397-9},
  volume       = {47},
  year         = {2009},
}

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