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Relevant bibliographies by topics / Windkessel model

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Academic literature on the topic 'Windkessel model'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Windkessel model"

1

Burkhoff, D., J. Alexander, and J. Schipke. "Assessment of Windkessel as a model of aortic input impedance." American Journal of Physiology-Heart and Circulatory Physiology 255, no. 4 (October 1, 1988): H742—H753. http://dx.doi.org/10.1152/ajpheart.1988.255.4.h742.

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To facilitate the analysis of aortic-ventricular coupling, simplified models of aortic input properties have been developed, such as the three-element Windkessel. Even though the impedance spectrum of the Windkessel reproduces the gross features of the real aortic input impedance, it fails to reproduce many of its details. In the present study we assessed the physiological significance of the differences between real and Windkessel impedance. We measured aortic input impedance spectra from five anesthetized open-chest dogs under a wide range of conditions. For each experimentally determined spectrum we estimated the corresponding values of the best-fit Windkessel parameters. By computer simulation we imposed both the real and best-fit Windkessel impedances on a model left ventricle and assessed the differences in seven different coupling variables. The analysis indicated that the Windkessel model provides a reasonable representation of afterload for purposes of predicting stroke volume, stroke work, oxygen consumption, and systolic and diastolic aortic pressures. However, the Windkessel model significantly underestimates peak aortic flow, slightly underestimates mean arterial pressure, and, of course, does not provide realistic aortic pressure and flow waveforms.

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Stergiopulos, Nikos, Berend E. Westerhof, and Nico Westerhof. "Total arterial inertance as the fourth element of the windkessel model." American Journal of Physiology-Heart and Circulatory Physiology 276, no. 1 (January 1, 1999): H81—H88. http://dx.doi.org/10.1152/ajpheart.1999.276.1.h81.

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In earlier studies we found that the three-element windkessel, although an almost perfect load for isolated heart studies, does not lead to accurate estimates of total arterial compliance. To overcome this problem, we introduce an inertial term in parallel with the characteristic impedance. In seven dogs we found that ascending aortic pressure could be predicted better from aortic flow by using the four-element windkessel than by using the three-element windkessel: the root-mean-square errors and the Akaike information criterion and Schwarz criterion were smaller for the four-element windkessel. The three-element windkessel overestimated total arterial compliance compared with the values derived from the area and the pulse pressure method ( P = 0.0047, paired t-test), whereas the four-element windkessel compliance estimates were not different ( P = 0.81). The characteristic impedance was underestimated using the three-element windkessel, whereas the four-element windkessel estimation differed marginally from the averaged impedance modulus at high frequencies ( P = 0.0017 and 0.031, respectively). When applied to the human, the four-element windkessel also was more accurate in these same aspects. Using a distributed model of the systemic arterial tree, we found that the inertial term results from the proper summation of all local inertial terms, and we call it total arterial inertance. We conclude that the fourelement windkessel, with all its elements having a hemodynamic meaning, is superior to the three-element windkessel as a lumped-parameter model of the entire systemic tree or as a model for parameter estimation of vascular properties.

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Wang, Jiun-Jr, Jacqueline A. Flewitt, Nigel G. Shrive, Kim H. Parker, and John V. Tyberg. "Systemic venous circulation. Waves propagating on a windkessel: relation of arterial and venous windkessels to systemic vascular resistance." American Journal of Physiology-Heart and Circulatory Physiology 290, no. 1 (January 2006): H154—H162. http://dx.doi.org/10.1152/ajpheart.00494.2005.

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Compared with arterial hemodynamics, there has been relatively little study of venous hemodynamics. We propose that the venous system behaves just like the arterial system: waves propagate on a time-varying reservoir, the windkessel, which functions as the reverse of the arterial windkessel. During later diastole, pressure increases exponentially to approach an asymptotic value as inflow continues in the absence of outflow. Our study in eight open-chest dogs showed that windkessel-related arterial resistance was ∼62% of total systemic vascular resistance, whereas windkessel-related venous resistance was only ∼7%. Total venous compliance was found to be 21 times larger than arterial compliance ( n = 3). Inferior vena caval compliance (0.32 ± 0.015 ml·mmHg−1·kg−1; mean ± SE) was ∼14 times the aortic compliance (0.023 ± 0.002 ml·mmHg−1·kg−1; n = 8). Despite greater venous compliance, the variation in venous windkessel volume (i.e., compliance × windkessel pulse pressure; 7.8 ± 1.1 ml) was only ∼32% of the variation in aortic windkessel volume (24.3 ± 2.9 ml) because of the larger arterial pressure variation. In addition, and contrary to previous understanding, waves generated by the right heart propagated upstream as far as the femoral vein, but excellent proportionality between the excess pressure and venous outflow suggests that no reflected waves returned to the right atrium. Thus the venous windkessel model not only successfully accounts for variations in the venous pressure and flow waveforms but also, in combination with the arterial windkessel, provides a coherent view of the systemic circulation.

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Sridharan, Sarup S., Lindsay M. Burrowes, J. Christopher Bouwmeester, Jiun-Jr Wang, Nigel G. Shrive, and John V. Tyberg. "Classical electrical and hydraulic Windkessel models validate physiological calculations of Windkessel (reservoir) pressure." Canadian Journal of Physiology and Pharmacology 90, no. 5 (May 2012): 579–85. http://dx.doi.org/10.1139/y2012-027.

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Our “reservoir–wave approach” to arterial hemodynamics holds that measured arterial pressure should be considered to be the sum of a volume-related pressure (i.e., reservoir pressure, Preservoir) and a wave-related pressure (Pexcess). Because some have questioned whether Preservoir (and, by extension, Pexcess) is a real component of measured physiological pressure, it was important to demonstrate that Preservoir is implicit in Westerhof’s classical electrical and hydraulic models of the 3-element Windkessel. To test the validity of our Preservoir determinations, we studied a freeware simulation of the electrical model and a benchtop recreation of the hydraulic model, respectively, measuring the voltage and the pressure distal to the proximal resistance. These measurements were then compared with Preservoir, as calculated from physiological data. Thus, the first objective of this study was to demonstrate that respective voltage and pressure changes could be measured that were similar to calculated physiological values of Preservoir. The second objective was to confirm previous predictions with respect to the specific effects of systematically altering proximal resistance, distal resistance, and capacitance. The results of this study validate Preservoir and, thus, the reservoir–wave approach.

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Chan, Gregory S. H., Philip N. Ainslie, Chris K. Willie, Chloe E. Taylor, Greg Atkinson, Helen Jones, Nigel H. Lovell, and Yu-Chieh Tzeng. "Contribution of arterial Windkessel in low-frequency cerebral hemodynamics during transient changes in blood pressure." Journal of Applied Physiology 110, no. 4 (April 2011): 917–25. http://dx.doi.org/10.1152/japplphysiol.01407.2010.

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The Windkessel properties of the vasculature are known to play a significant role in buffering arterial pulsations, but their potential importance in dampening low-frequency fluctuations in cerebral blood flow has not been clearly examined. In this study, we quantitatively assessed the contribution of arterial Windkessel (peripheral compliance and resistance) in the dynamic cerebral blood flow response to relatively large and acute changes in blood pressure. Middle cerebral artery flow velocity (MCAV; transcranial Doppler) and arterial blood pressure were recorded from 14 healthy subjects. Low-pass-filtered pressure-flow responses (<0.15 Hz) during transient hypertension (intravenous phenylephrine) and hypotension (intravenous sodium nitroprusside) were fitted to a two-element Windkessel model. The Windkessel model was found to provide a superior goodness of fit to the MCAV responses during both hypertension and hypotension ( R2 = 0.89 ± 0.03 and 0.85 ± 0.05, respectively), with a significant improvement in adjusted coefficients of determination ( P < 0.005) compared with the single-resistance model ( R2 = 0.62 ± 0.06 and 0.61 ± 0.08, respectively). No differences were found between the two interventions in the Windkessel capacitive and resistive gains, suggesting similar vascular properties during pressure rise and fall episodes. The results highlight that low-frequency cerebral hemodynamic responses to transient hypertension and hypotension may include a significant contribution from the mechanical properties of vasculature and, thus, cannot solely be attributed to the active control of vascular tone by cerebral autoregulation. The arterial Windkessel should be regarded as an important element of dynamic cerebral blood flow modulation during large and acute blood pressure perturbation.

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Campbell, K. B., R. Burattini, D. L. Bell, R. D. Kirkpatrick, and G. G. Knowlen. "Time-domain formulation of asymmetric T-tube model of arterial system." American Journal of Physiology-Heart and Circulatory Physiology 258, no. 6 (June 1, 1990): H1761—H1774. http://dx.doi.org/10.1152/ajpheart.1990.258.6.h1761.

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An asymmetric T-tube model of the arterial system with complex terminal loads was formulated in the time domain. The model was formulated to allow it to be fitted to the aortic pressure waveform, the aortic flow waveform, or simultaneously to both the aortic and descending aortic flow waveforms. Pressure and flow measurements were taken in anesthetized open-chest dogs under basal, vasoconstricted, and vasodilated states. It was found that the T-tube model fitted the data well in all formulations and in all vasoactive states. However, all parameters were estimated accurately in all vasoactive states only with the formulation that fitted to both aortic and descending aortic flow simultaneously. The T-tube model was compared with the three-element windkessel model with regard to the respective models' ability to recreate specific aspects of the pressure waveform and with regard to the estimates of global arterial parameters. The T-tube model recremated those features of the pressure waveform, such as diastolic waves, that the windkessel model could not. Also, the T-tube model systematically estimated lower global arterial compliance and higher characteristic impedance than the windkessel. It was argued that the T-tube model accurately represented important wave transmission features of the arterial loading system. The model is recommended for use in characterizing the arterial load and for merging with representations of the left ventricle in studies of left ventricle-systemic arterial interaction.

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Mohiuddin, Mohammad W., Glen A. Laine, and Christopher M. Quick. "Increase in pulse wavelength causes the systemic arterial tree to degenerate into a classical windkessel." American Journal of Physiology-Heart and Circulatory Physiology 293, no. 2 (August 2007): H1164—H1171. http://dx.doi.org/10.1152/ajpheart.00133.2007.

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Two competing schools of thought ascribe vascular disease states such as isolated systolic hypertension to fundamentally different arterial system properties. The “windkessel school” describes the arterial system as a compliant chamber that distends and stores blood and relates pulse pressure to total peripheral resistance ( Rtot) and total arterial compliance ( Ctot). Inherent in this description is the assumption that arterial pulse wavelengths are infinite. The “transmission school,” assuming a finite pulse wavelength, describes the arterial system as a network of vessels that transmits pulses and relates pulse pressure to the magnitude, timing, and sites of pulse-wave reflection. We hypothesized that the systemic arterial system, described by the transmission school, degenerates into a windkessel when pulse wavelengths increase sufficiently. Parameters affecting pulse wavelength (i.e., heart rate, arterial compliances, and radii) were systematically altered in a realistic, large-scale, human arterial system model, and the resulting pressures were compared with those assuming a classical (2-element) windkessel with the same Rtot and Ctot. Increasing pulse wavelength as little as 50% (by changing heart rate −33.3%, compliances −55.5%, or radii +50%) caused the distributed arterial system model to degenerate into a classical windkessel ( r2 = 0.99). Model results were validated with analysis of representative human aortic pressure and flow waveforms. Because reported changes in arterial properties with age can markedly increase pulse wavelength, results suggest that isolated systolic hypertension is a manifestation of an arterial system that has degenerated into a windkessel, and thus arterial pressure is a function only of aortic flow, Rtot, and Ctot.

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Dutra, Maurício dos S., Walter C. de Lima, and Jorge M. Barreto. "Ventricular Ejection Simulation with Active Atrium using Windkessel Model." IFAC Proceedings Volumes 30, no. 2 (March 1997): 25–28. http://dx.doi.org/10.1016/s1474-6670(17)44536-8.

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Karamanoglu, M., D. E. Gallagher, A. P. Avolio, and M. F. O'Rourke. "Pressure wave propagation in a multibranched model of the human upper limb." American Journal of Physiology-Heart and Circulatory Physiology 269, no. 4 (October 1, 1995): H1363—H1369. http://dx.doi.org/10.1152/ajpheart.1995.269.4.h1363.

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The influence of the large arteries and the peripheral load on pressure wave propagation in the human upper limb was investigated in an anatomically realistic multibranched model based on linear transmission theory. To mimic vascular changes seen in life, the viscoelastic properties of large arteries and the peripheral load properties (represented as modified windkessels) were altered as follows: Young's modulus (from 10.9 x 10(6) to 15.3 x 10(6) dyn/cm2) and phase (from 0 to 15 degrees) of the complex elastance, windkessel time constant (from 0 to 0.6 s), and peripheral reflection coefficient (from 0 to 0.95). The relationship between the central aortic and peripheral radial pressure waveforms was analyzed in the time and the frequency domain. Results indicate that the large arterial properties have less influence (peak systolic pressure changed by 3% and peak of transfer function changed by 29%) than the properties of the peripheral load (systolic pressure changed by 14% and peak of transfer function changed by 74%) on the pressure wave propagation in the upper limb.

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Kong, Yazhuo, Ying Zheng, David Johnston, John Martindale, Myles Jones, Steve Billings, and John Mayhew. "A Model of the Dynamic Relationship between Blood Flow and Volume Changes during Brain Activation." Journal of Cerebral Blood Flow & Metabolism 24, no. 12 (December 2004): 1382–92. http://dx.doi.org/10.1097/01.wcb.0000141500.74439.53.

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The temporal relationship between changes in cerebral blood flow (CBF) and cerebral blood volume (CBV) is important in the biophysical modeling and interpretation of the hemodynamic response to activation, particularly in the context of magnetic resonance imaging and the blood oxygen level–dependent signal. Grubb et al. (1974) measured the steady state relationship between changes in CBV and CBF after hypercapnic challenge. The relationship CBVαCBFΦ has been used extensively in the literature. Two similar models, the Balloon ( Buxton et al., 1998 ) and the Windkessel ( Mandeville et al., 1999 ), have been proposed to describe the temporal dynamics of changes in CBV with respect to changes in CBF. In this study, a dynamic model extending the Windkessel model by incorporating delayed compliance is presented. The extended model is better able to capture the dynamics of CBV changes after changes in CBF, particularly in the return-to-baseline stages of the response.

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Dissertations / Theses on the topic "Windkessel model"

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Sethaput, Thunyaseth. "Mathematical Model for Hemodynamic and Intracranial Windkessel Mechanism." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1363149368.

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Diourté, Badié. "Modélisation et simulation du système cardio-vasculaire par analogie électrique." Grenoble 1, 1998. http://www.theses.fr/1998GRE10222.

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Le modele de windkessel a ete propose pour identifier a partir de l'analyse du contour de l'onde de pression arterielle (pa), les parametres hemodynamiques du systeme arteriel comme la compliance arterielle (ca), l'inertie du volume sanguin (l), et les resistances vasculaires du systeme (r). Il s'agit d'un modele lineaire qui ne tient pas compte des variations structurales et fonctionnelles des arteres liees a la pulsatilite de la pa de ses variations entre la systole et la diastole et de la complexite de l'impedance cardiaque. L'objectif de la these est d'analyser les performances d'un modele de windkessel modifie ou les parametres ca, l et r sont ajustes de facon dynamique selon la relation non-lineaire des proprietes arterielles (compliance, diametre) en fonction de la pa. Dans un simulateur electrique reproduisant le modele les parametres suivants sont introduits : au niveau cardiaque le volume d'ejection systolique et au niveau radial les valeurs dynamiques de compliance et de diametre arteriel. Nous comparons les formes des ondes de pa lineaire ou la ca (compliance constante en fonction de la pression) et non-lineaire (compliance fonction de la pression) aux donnees experimentales. La forme de l'onde de pa obtenue par le modele non-lineaire n'est significativement pas differente de l'experimentale, tandis que dans le modele lineaire la pa systolique est sous estimee. Ce travail montre les limites de la modelisation du systeme cardio-vasculaire par le modele lineaire.

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Francis, Said Elias. "Continuous estimation of cardiac output and arterial resistance from arterial blood pressure using a third-order Windkessel model." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41641.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (p. 85-89).
Intensive Care Units (ICUs) have high impact on the survival of critically-ill patients in hospitals. Recent statistics have shown that only 10% of the 5 million patients admitted to ICUs in the United States die each year. In modern ICUs, the heart's electrical and mechanical activity is routinely monitored using various sensors. Arterial blood pressure (ABP) and heart rate (HR) are the most commonly recorded waveforms which provide key information to the ICU clinical staff. However, clinicians find themselves in many cases unable to determine the causes behind abnormal behavior of the cardiovascular system because they lack frequent measures of cardiac output (CO), the average blood flow out of the left ventricle. CO is monitored via intermittent thermodilution measurements which are highly invasive and only applied to the sickest ICU patients. The lack of frequent CO measurements has encouraged researchers to develop estimation methods for cardiac output from routinely measured arterial blood pressure waveforms. The prospects of estimating cardiac output from minimally-invasive blood pressure measurements has resulted in numerous estimation algorithms, however, there is no consensus on the performance of the algorithms that have been proposed. In this thesis, we investigate the use of a third-order variation of the Windkessel model, which is referred to as the modified Windkessel model. We validate its ability to generate well-behaved proximal and distal pressure waveforms for a given flow waveform and thus characterize the arterial tree. We also develop a model-based CO estimation algorithm which uses central and peripheral blood pressure waveforms to obtain reliable estimates of CO and the total peripheral resistance (TPR). We applied the estimation algorithm to a porcine data set.
(cont.) The results of our estimation algorithm are promising: the weighted-mean root-mean-squared-normalized-error (RMSNE) is about 13.8% over four porcine records. In each porcine experiment, intravenous drug infusions were used to vary CO, ABP, and HR over wide ranges. Our results suggest that the modified Windkessel model is a good representation of the arterial tree and that the estimation algorithm yields reliable estimates of CO and TPR under various hemodynamic conditions.
by Said Elias Francis.
M.Eng.

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Dutra, Maurício dos Santos. "Modelo de ejeção ventricular tipo "Windkessel" com átrio ativo /." Florianópolis, SC, 1999. http://repositorio.ufsc.br/xmlui/handle/123456789/80522.

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Dissertação (Mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico.
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Abdul-Nour, Faraj. "Étude et conception des pompes implantables mécaniques pour l'administration de médicaments." Compiègne, 1988. http://www.theses.fr/1988COMPD149.

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Book chapters on the topic "Windkessel model"

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Cioffi, William G., Michael D. Connolly, Charles A. Adams, Mechem C. Crawford, Aaron Richman, William H. Shoff, Catherine T. Shoff, et al. "The 3-Element Windkessel Model." In Encyclopedia of Intensive Care Medicine, 2206. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-00418-6_3334.

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Chellappan, Kalaivani, E. Zahedi, and M. A. Mohd Ali. "Age-related Upper Limb Vascular System Windkessel Model using Photoplethysmography." In 3rd Kuala Lumpur International Conference on Biomedical Engineering 2006, 563–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-68017-8_141.

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Tavera, M. M., J. F. Remolina, S. Wray, L. J. Cymberknop, and R. L. Armentano. "Windkessel Model in the Qualitative Analysis of the Circulatory System of Smokers." In VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná, Argentina 29, 30 & 31 October 2014, 880–83. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13117-7_223.

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Lungu, A., D. R. Hose, D. G. Kiely, D. Capener, J. M. Wild, and A. J. Swift. "Three Element Windkessel Model to Non-Invasively Assess PAH Patients: One Year Follow-up." In International Conference on Advancements of Medicine and Health Care through Technology; 12th - 15th October 2016, Cluj-Napoca, Romania, 151–54. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52875-5_34.

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Ismail, Mahmoud, Michael W. Gee, and Wolfgang A. Wall. "CFD Challenge: Hemodynamic Simulation of a Patient-Specific Aortic Coarctation Model with Adjoint-Based Calibrated Windkessel Elements." In Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges, 44–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36961-2_6.

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Silva, Andrew Guimarães, Daniel G. Goroso, and Robson Rodrigues Silva. "SCHSim: A Simulator of Elastic Arterial Vessels Using Windkessel Models." In IFMBE Proceedings, 709–17. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30648-9_94.

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Conference papers on the topic "Windkessel model"

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Baselli, Giuseppe, and Maria Marcella Lagana. "The Strange Cerebrovascular Windkessel: a Simplified Model." In 2020 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO). IEEE, 2020. http://dx.doi.org/10.1109/esgco49734.2020.9158030.

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Choudhury, Anirban Dutta, Rohan Banerjee, Aniruddha Sinha, and Shaswati Kundu. "Estimating blood pressure using Windkessel model on photoplethysmogram." In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2014. http://dx.doi.org/10.1109/embc.2014.6944640.

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Bahloul, Mohamed A., and Taous Meriem Laleg-Kirati. "Three-Element Fractional-Order Viscoelastic Arterial Windkessel Model." In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2018. http://dx.doi.org/10.1109/embc.2018.8513473.

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Sijian Zhang, Finkelstein, and Cohn. "Verification of the Modified Windkessel Model of the Arterial Vasculature." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.595840.

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Zhang, Sijian, Stanley M. Finkelstein, and Jay N. Cohn. "Verification of the modified Windkessel model of the arterial vasculature." In 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.5761206.

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Baxevanaki, Kleoniki, Stavroula Kapoulea, Costas Psychalinos, and Ahmed S. Elwakil. "Electronically Tunable Realization of the Three-Element Arterial Windkessel Model." In 2021 44th International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2021. http://dx.doi.org/10.1109/tsp52935.2021.9522593.

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Perkins, Lucy E., and Brooke N. Steele. "Comparison of Methods for RCR Component Selection From Computational Model Impedance Spectra." In ASME 2009 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2009. http://dx.doi.org/10.1115/sbc2009-206533.

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Vascular impedance represents the opposition to periodic blood flow though a network of vessels and is a good choice for use as a boundary condition for hemodynamic modeling. Vascular impedance can be computed using electrical analogs, such as two or three element Windkessel models, or computed from geometry using Womersley’s input impedance equations [3]. The challenges associated with using electrical analogs are the need for experimental data to determine appropriate component values and in determining an appropriate methodology to fit the experimental data to the simplified model. The challenges associated with using a geometry-based method are the necessity of knowing the geometry being modeled and the requirement of a periodic solution. While Windkessel models are routinely used in analyses, little detail is provided as to how these R and C parameters are extracted from the impedance spectra. Therefore, we examine the relative importance of matching different characteristics of impedance spectra to the resulting pressure and flow relationships.

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Liu, Shing-Hong, and Jia-Jung Wang. "Notice of Retraction: Using Windkessel Model to Measure Brachial Blood Flow." In 2011 5th International Conference on Bioinformatics and Biomedical Engineering. IEEE, 2011. http://dx.doi.org/10.1109/icbbe.2011.5780308.

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Yasuda, Kazuma, and Shigehiko Kaneko. "Numerical Simulation of Pulse Wave Propagation in Arteries With Structured-Tree Outflow Conditions." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71013.

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When constructing the one-dimensional systemic artery tree, the Windkessel model based on parameters describing the total resistance and compliance is generally applied as outflow boundary conditions. However, the Windkessel model does not include wave propagation effects, and moreover, it is not obvious how the parameters should be estimated. Hence, the main purpose of this study is to develop an outflow boundary condition based on the underlying physiology of the arterioles, enabling the prediction of blood flow and pressure in the systemic arteries including the arterioles. The obtained numerical results show the followings. Firstly, we verified that applying the structured tree model as an outflow boundary condition can reproduce the essential characteristics of the arterial pulse better than applying the Windkessel model. Secondly, by analyzing the pulse wave velocity in aorta, we found a correlation between pulse wave velocity and the degree of arteriosclerosis which correspond to the clinical observation.

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Stiukhina, Elena S., Maxim A. Kurochkin, Victor A. Klochkov, Ivan V. Fedosov, and Dmitry E. Postnov. "Tissue perfusability assessment from capillary velocimetry data via the multicompartment Windkessel model." In Saratov Fall Meeting 2014, edited by Elina A. Genina, Vladimir L. Derbov, Kirill V. Larin, Dmitry E. Postnov, and Valery V. Tuchin. SPIE, 2015. http://dx.doi.org/10.1117/12.2179870.

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