Simulation of cardiovascular physiology: the diastolic function(s) of the heart

Podnar, Tomaž; Runovc, Franc; Kordaš, M.

doi:10.1016/s0010-4825(02)00026-4

Cited by 17 publications

(16 citation statements)

References 10 publications

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“…5. This graph shows that aorta pressure varies between 80-120 mmHg (diastole-systole) and the results are in agreement with physiological article 16 . Fig.…”

supporting

confidence: 89%

Simulation of the Cardiovascular System Using Equivalent Electronic System

Hassani¹,

Navidbakhsh²,

Rostami³

2006

Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub

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This paper describes simulation of the cardiovascular system using a complex electronic circuit. In this study we have taken a slightly different approach to the modeling of the system and tried to advance existing electrical models by increasing more segments and parameters. The model consists of 42 segments representing the arterial system. Anatomical and physiological data for circuit parameters have been extracted from medical articles and textbooks. The frequency of heart is 1 Hz and the system operates in steady state condition. Each artery is modeled by one capacitor, resistor and inductor. The left and right ventricles are modeled using AC power suppliers and diodes. The results of the simulation including pressure and volume graphs exhibit operation of the cardiovascular system under normal condition. The results of the simulation have been compared with the relevant experimental observation and are in good agreement with them.

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“…5. This graph shows that aorta pressure varies between 80-120 mmHg (diastole-systole) and the results are in agreement with physiological article 16 . Fig.…”

supporting

confidence: 89%

Simulation of the Cardiovascular System Using Equivalent Electronic System

Hassani¹,

Navidbakhsh²,

Rostami³

2006

Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub

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“…This model estimated a cardiac output at rest of 8171.15 ml/min, averagely for all subjects, can be compared to predictions 7500 ml/min (Korakianitis & Shi, 2006;Kim et al, 2009). Such assessments have applied a finite element technique coupled a lumped parameter method, a Wind-Kassel approach (Korakianitis & Shi, 2006), as well as an electrical integration circuit (Podnar et al, 2002). Data derived from Christie et al (1987) agrees with our results.…”

Section: Comparison To Literaturesupporting

confidence: 73%

Numerical method to measure velocity integration, stroke volume and cardiac output while rest: using 2D fluid-solid interaction model

Khosravi¹,

Bahraseman²,

Hassani³

et al. 2014

10.5267/j.esm

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Development of knowledge of cardiovascular diseases and treatments strongly depends on understanding of hemodynamic measurements. Hemodynamic parameters, therefore, have been investigated using simulation-based methods. A two-dimensional model was applied for seven healthy subjects with echo-Doppler at rest. Echocardiography imaging was also utilized to gain the geometry of the aortic valve. Fluid-Structure Interaction (FSI) model was carried out, coupling an Arbitrary Lagrangian-Eulerian mesh. Pressure loads were used as boundary conditions on the valve's ventricular and aortic sides. Pressure loads used were the calculated brachial pressures plus differences between brachial, central and left ventricular pressures. The FSI model predicted the velocity integration, stroke volume and cardiac output over a range of heart rates while rest. Numerical results generally had a difference of 5.4 to 15.87% with Doppler results. Linear correlations between numerical and clinical approaches have been applied. This makes possible predictions achieved from the FSI model to be gained which are highly accurate (e.g. correlation factor r = 0.995, 0.990 and 0.990 for velocity integration, stroke volume and cardiac output, respectively). The obtained numerical results showed that numerical methods can be combined with clinical measurements to provide good estimates of patient specific hemodynamics for different subjects.

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“…In steady state conditions AoP, MAoP, CO and heart rate are about 150/95 mm Hg, 109 mm Hg, 10100 ml/min and 90/min, respectively. This is because in this model the heart rate/cardiac output curve is very flat, as shown earlier (Podnar et al, 2002); an increase in heart rate from 90/min to 120/min results in a comparatively small increase in CO. Table 1. The effect of aortic stenosis (at rest and in exercise) on heart rate (HR), pressure in the left ventricle (LVP: ventricular maximum/end-distolic), mean aortic pressure (MAoP), aortic pressure (systolic/diastolic; AoP) and cardiac output (CO).…”

Section: Specific Commentssupporting

confidence: 54%

“…However, in analog modelling physical electrical models have been replaced by computer analysis of electronic analog circuitry. Then they have been applied to various physiological systems (Bošnjak & Kordaš, 2002;Dolenšek et al, 2005), to study also cardiovascular physiology (Rupnik et al, 2002), including mechanisms of compensation (Podnar et al, 2002) and principles of homeostasis, i. e. negative feedback mechanisms (Podnar et al, 2004). Recently, the equivalent circuit simulating the cardiovascular system was further upgraded to simulate, as close as possible, conditions in man in vivo.…”

Section: Introductionmentioning

confidence: 99%