Pulsatile mechanical and mathematical model of the cardiovascular system

Dagan, Jacob

doi:10.1007/bf02443408

Cited by 12 publications

(5 citation statements)

References 4 publications

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“…Pulsatility is crucial to certain cardiovascular phenomena [67][68][69][70][71][72][73]. For example, pulsatile arterial blood flow results in a fairly steady distribution of blood to all tissues of the body, which could not occur otherwise.…”

Section: Computational and Mathematical Methods In Medicinementioning

confidence: 99%

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Seven Mathematical Models of Hemorrhagic Shock

Curcio

D’Orsi

Gaetano

2021

Computational and Mathematical Methods in Medicine

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Although mathematical modelling of pressure-flow dynamics in the cardiocirculatory system has a lengthy history, readily finding the appropriate model for the experimental situation at hand is often a challenge in and of itself. An ideal model would be relatively easy to use and reliable, besides being ethically acceptable. Furthermore, it would address the pathogenic features of the cardiovascular disease that one seeks to investigate. No universally valid model has been identified, even though a host of models have been developed. The object of this review is to describe several of the most relevant mathematical models of the cardiovascular system: the physiological features of circulatory dynamics are explained, and their mathematical formulations are compared. The focus is on the whole-body scale mathematical models that portray the subject’s responses to hypovolemic shock. The models contained in this review differ from one another, both in the mathematical methodology adopted and in the physiological or pathological aspects described. Each model, in fact, mimics different aspects of cardiocirculatory physiology and pathophysiology to varying degrees: some of these models are geared to better understand the mechanisms of vascular hemodynamics, whereas others focus more on disease states so as to develop therapeutic standards of care or to test novel approaches. We will elucidate key issues involved in the modeling of cardiovascular system and its control by reviewing seven of these models developed to address these specific purposes.

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Section: Computational and Mathematical Methods In Medicinementioning

confidence: 99%

“…Zenker et al thus define a discrete dynamical system to describe V ED , or V ES , on a beat-to-beat basis. In particular, from the current enddiastolic volume V n ED , we can apply equation (67) to compute V n ES =Ṽ ES ðV n ED Þ as well as equation ( 76) to obtainṼ ED ðV n ES Þ. In aggregate, these yield the following [13]:…”

mentioning

confidence: 99%

Seven Mathematical Models of Hemorrhagic Shock

Curcio

D’Orsi

Gaetano

2021

Computational and Mathematical Methods in Medicine

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“…The heart was com- posed of a four compartment element with the corresponding valves represented as diodes [43][44][45][46][47][48][49][50][51]. The relation of pressure (P), volume (V) and flow (Q) was used in relation to the neighbor component considering resistance (R), compliance (C) and inductance (L) elements.…”

Section: Cardiovascular Modelmentioning

confidence: 99%

Automation of a portable extracorporeal circulatory support system with adaptive fuzzy controllers

García

Krane

Baumgartner

et al. 2014

Medical Engineering & Physics

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ZusammenfassungDie frühe Behandlung mit Extrakorporalen Kreislauf-Unterstützungssystemen bei Patienten mit kardiogenem Schock wirkt sich positiv auf den weiteren Verlauf aus und kann einem Multi-Organversagen entgegenwirken. Um eine frühe Behandlung zu ermöglichen, ist eine kontinuierlicheÜberwachung des Patienten durch geschulte Kardiotechniker notwendig. Unter Notfallbedingungen kann eine ungeteilte Aufmerksamkeit für den Patienten nicht garantiert werden womit es zu Behandlungsfehlern kommen kann.Durch AbstractPatients suffering from cardiogenic shock may benefit with an early application of a portable Extracorporeal Circulatory Support System (ECSS) preventing multi organ failure. This however requires the presence and constant supervision of the patient by trained personal at the emergency site. Under these circumstances full attention to the patient may not be guaranteed and operation errors may occur.With the automation of the portable ECSS optimal perfusion may be achieved with minimal workload for the human operator allowing the safe transportation of the patient to the hospital.The focus of this thesis is the development of an adaptive and robust control system that regulates perfusion based on online data of the patient. While the system needs to be highly dynamic, so that it is able to adapt to different situations, it must ensure maximal patient safety at all times.To develop such control system first an animal model was used to analyze the type of signals acquired during extracorporeal circulation. This information was used as a reference for the creation of a mathematical model. The model includes a cardiovascular system undergoing extracorporeal circulation, a gas exchange model and a medication model. This was integrated into a simulation system that could be used for the creation and evaluation of the designed controller.Fuzzy logic was considered as a control mechanism allowing the easy creation of rules based on the knowledge of trained perfusionists. Since patient pre-conditions and reactions will be different from one case to another an adaptive mechanism is proposed to modify the existing controller and adapt to the specific needs of the patient.A software framework was developed allowing a fast implementation of the control system. This framework was created not only focusing on the automation of the ECSS but also to serve as a basis for the development of control systems for other medical devices with similar requirements.Several simulations are presented showing the performance of the fuzzy controller with the proposed adaptive mechanism. Additional simulations show the response of the designed ECSS controller under different patient scenarios.vii Acknowledgments I want to give thanks to my advisor Prof. Dr. Alois Knoll for giving me the opportunity of working in this thesis, for his support and confidence. I would also like to thank Prof. Dr. Robert Bauernschmitt for taking the time to review my work and acting as a second advisor. From the department of Robotics and Embedded Systems ...

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“…There is a wide variety of such models, which depends on their purpose and the methodology used [2][3][4][5][6][7][8][9][10]. Researchers have approached the modeling problem from several different perspectives.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling of Cardiovascular System Dynamics Using a Lumped Parameter Method

Shim

Sah

Youn³

2004

Jpn.J.Physiol

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parameter models. We also discuss the nonlinear characteristics of the pressure-volume relationship in veins. Then the control pathways that participate in feedback mechanisms (baroreceptors and cardiopulmonary receptors) are described to explain the interaction between hemodynamics and autonomic nerve control in the circulation. Based on a set-point model, the computational aspects of reflex control are explained. Japanese Journal of Physiology Vol. 54, [545][546][547][548][549][550][551][552][553] 2004 REVIEW Abstract: This work reviews the main aspects of cardiovascular system dynamics with an emphasis on modeling hemodynamic characteristics by the use of a lumped parameter approach. The methodological and physiological aspects of the circulation dynamics are summarized with the help of existing mathematical models. The main characteristics of the hemodynamic elements, such as the heart and arterial and venous systems, are first described. Distributed models of an arterial network are introduced, and their characteristics are compared with those of lumped Key words: lumped parameter model, dynamics of the cardiovascular system, autonomic nerve control.

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Pulsatile mechanical and mathematical model of the cardiovascular system

Cited by 12 publications

References 4 publications

Seven Mathematical Models of Hemorrhagic Shock

Seven Mathematical Models of Hemorrhagic Shock

Automation of a portable extracorporeal circulatory support system with adaptive fuzzy controllers

Mathematical Modeling of Cardiovascular System Dynamics Using a Lumped Parameter Method

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