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Age-related Upper Limb Vascular System Windkessel Model using Photoplethysmography

  • Conference paper
3rd Kuala Lumpur International Conference on Biomedical Engineering 2006

Part of the book series: IFMBE Proceedings ((IFMBE,volume 15))

Abstract

Arterial stiffness is known to be affected by aging, leading to changes in peripheral pulse propagation speed and shape. In this paper, the heart-finger segment of the upper- limb vascular system of six subjects in two age-groups (below 30 and above 55 years) is modeled using a modified Windkessel model. Actual left-ventricle pressure (LVP) data has been used as the input to the model. Circuit simulation results show a significantly higher amplitude for the dicrotic notch and a lower second peak in younger subjects. Among the older subjects, there was a gradual disappearance of dicrotic notch while the second peak appeared later. Comparison of the characteristics of the model output with measured peripheral pulse shows a good degree of conformity with the actual pulse signal. The parameters in the Windkessel model provide a simple, noninvasive means for studying changes in the elastic properties of the vascular system, depending on the age and potentially state of health.

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References

  1. McDonald DA (1974) Blood Flow in Arteries. 2nd ed. Arnold, London

    Google Scholar 

  2. John A, Alan M. (1999) Modeling the relationship between peripheral blood pressure and blood volume pulses using linear and neural network system identification techniques. Physiological Measurement 20: 287–301

    Article  Google Scholar 

  3. John A, Alan M (2003) Age-related changes in the characteristics of the photoplethysmographic pulse shape at various body sites. Physiology Measurement. Vol. 24. 297–307

    Article  Google Scholar 

  4. Nichols W M, O’Rourke M F (1998) McDonald’s blood flow in arteries: theoretical, experimental and clinical principles. Arnold, London

    Google Scholar 

  5. Avolio A et al (1985) Noninvasive determination of aging changes in the arterial pulse. Fed. Amer. Soc. Exp. Bio. Vol. 2:No. 4: A125

    Google Scholar 

  6. Nichols W W et al (1990) Effects of age on ventricular vascular. Am J Cardiol. 55: 1179–1184

    Article  Google Scholar 

  7. Sherebrin M H, Sherebrin R Z (1990) Frequency-analysis of the peripheral pulse-wave detected in the finger with photoplethysmography. IEEE Trans. Biomed. Eng. 37:313–317

    Article  CAS  PubMed  Google Scholar 

  8. Oliva I, Roztocil K (1976) Fourier analysis of the pulse wave in obliterating arteriolerosis. VASA 5: 95–100

    CAS  PubMed  Google Scholar 

  9. Millasseau et al (2002) Determination on age-related increases in large artery stiffness by digital pulse contour analysis. Clinical. Science. 103: 371–329

    Article  CAS  PubMed  Google Scholar 

  10. K. Chellappan, Zahedi E, Ali MAM (2006) Windkessel Model Of The Arterial Vascular System Using Photoplethysmography. SPS2006, Universiti Kebangsaan Malaysia, Bangi, Malaysia, 29–30 August 2006.

    Google Scholar 

  11. Devasahayam, S. R. 2000. Signals and Systems in Biomedical Engineering (Signal Processing and Physiological Systems Modeling). New York: Kluwer Academic/Plenium Publishers.

    Book  Google Scholar 

  12. Milnor, W.R. 1992. Hemodynamics. Baltimore/London: Williams & Wilkins.

    Google Scholar 

  13. Snyder, M.F. & Rideout, V.C. 1968. Computer Modeling of The Human Systemic Arterial Tree. Pergamon Press. Great Britain 1: 341–353.

    CAS  Google Scholar 

  14. Walter J. P et al. (1995) Paracrine Coronary Endothelial Control of Left Ventricular Function in Humans. Circulation. 92:2119–2126

    Article  Google Scholar 

  15. Westerhof, N E, Van Den Bos GC. 1973. Influence of central and peripheral changes on the hydraulic input impedance of the systemic arterial tree. Med & Biology, Vol: 11: 710–723.

    CAS  Google Scholar 

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© 2007 Springer-Verlag Berlin Heidelberg

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Chellappan, K., Zahedi, E., Mohd Ali, M.A. (2007). Age-related Upper Limb Vascular System Windkessel Model using Photoplethysmography. In: Ibrahim, F., Osman, N.A.A., Usman, J., Kadri, N.A. (eds) 3rd Kuala Lumpur International Conference on Biomedical Engineering 2006. IFMBE Proceedings, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68017-8_141

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  • DOI: https://doi.org/10.1007/978-3-540-68017-8_141

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68016-1

  • Online ISBN: 978-3-540-68017-8

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