System, apparatus and control method thereof for simulating physical characteristics of blood vessels

Abstract

The present disclosure provides a system, device, control method and storage medium for simulating physical characteristics of blood vessels. The method for simulating physical characteristics of blood vessels comprises determining blood vessel types of a lesion to be studied, collecting clinical medical data of the lesion blood vessels, performing isolated modeling on each blood vessel branch, setting initial reference values of the model, connecting the blood vessel model and the device for simulating physical characteristics of blood vessels to an in-vitro test device, operating the in-vitro test device based on the initial reference values, and calculating blood vessel resistance, compliance and test temperature in the blood vessel model in real time according to sensor collected data, and calculating differences between target values and corresponding measured values. The in-vitro test device is adjusted through a simulated neural feedback mechanism and a direct coordination mechanism of each blood vessel branch until the differences between the target values and the corresponding measured values meet predetermined conditions.

Description

Technical Field

[0001] This disclosure relates to the simulation of vascular properties, and more specifically, to systems, devices, and control methods for simulating the physical properties of blood vessels. Background Technology

[0002] Cardiovascular disease has become the leading cause of disease threatening human physical and mental health, making its research a hot topic of common concern in the medical and academic communities. With the development of various medical diagnostic and treatment technologies, numerous studies have shown that the occurrence and development of vascular diseases are closely related to hemodynamics, and various fluid dynamics research methods and equipment have been widely applied in vascular hemodynamics research.

[0003] Originating from in vitro heart valve testing devices, the Mock Circulation Loop (MCL) system, as a research tool for vascular disease research, has been widely used in in vitro hemodynamic studies of various cardiovascular diseases. The core of the MCL system lies in simulating and replicating the physiological parameters of the target blood vessel, such as vascular compliance and resistance, using tubing, physical components, and incorporating methods such as ex vivo vascular tissue and 3D-printed in vitro vascular models. It also incorporates multi-physical sensors to acquire pressure and flow parameters. In simulating vascular physical characteristics, current MCL systems mostly use fixed-volume cavities to simulate vascular compliance. For example, external rotary valves or single proportional valves are used to adjust the tubing diameter to simulate the overall resistance of the target blood vessel. Furthermore, physical sensors are used to acquire hemodynamic parameters at the target location, thus serving the study of the mechanical parameters of vascular diseases.

[0004] However, existing methods for simulating the physical properties of blood vessels in in vitro biomimetic circulatory systems are relatively simple. In simulating vascular resistance, the resistance value of the target blood vessel's branches is often adjusted by setting the opening and closing degree of a proportional valve in the initial system state or by turning a screw valve during testing. This method has low precision in setting the vascular resistance value. On the other hand, regarding vascular compliance, current methods mostly simulate vascular compliance characteristics by mechanically adjusting the air-to-liquid volume ratio within the compliance lumen. As an important evaluation parameter for vascular elasticity and blood storage function, traditional techniques are insufficient to reflect the compliance of the target blood vessel. Therefore, existing devices cannot accurately reproduce the physical properties of blood vessels and thus struggle to precisely control the boundary conditions of fluid dynamics.

[0005] In existing vascular physical property simulation technologies, the model flow curve is often used as input, without considering the real-time dynamic relationship between pressure and flow at vascular branches. It is also impossible to establish a continuous equation for the complete human blood circulation system based on flow, pressure and vascular characteristic parameters to accurately reproduce the hemodynamic environment. Therefore, it is difficult to consider the influence of blood vessels at other locations in the blood circulation system on the pressure and flow of the target blood vessel during in vitro simulation testing.

[0006] Therefore, a new system for simulating the physical properties of blood vessels and a corresponding control method are needed to improve the above-mentioned technical problems. Summary of the Invention

[0007] To address the aforementioned problems, this disclosure provides a system, device, and control method for simulating the physical properties of blood vessels.

[0008] According to one aspect of this disclosure, a method for controlling a system simulating the physical properties of blood vessels is provided, comprising: determining a target blood vessel to be simulated, and isolating and modeling each branch of the target blood vessel according to clinical medical data of the target blood vessel to obtain a target blood vessel model; calculating the physical characteristics of the target blood vessel according to a human circulatory system model, setting initial reference values ​​for a vascular physical property simulation device and an in vitro testing device in the system simulating the physical properties of blood vessels according to the calculated physical characteristics of the target blood vessel, and connecting the target blood vessel model to the vascular physical property simulation device and the in vitro testing device; operating the in vitro testing device based on the initial reference values, determining measured values ​​of vascular resistance, compliance, and test temperature in the vascular model according to sensor-collected data, and calculating the difference between the target value and the corresponding measured value; and adjusting the vascular physical property simulation device using a proportional-integral-derivative (PID) control algorithm until the difference between the target value and the corresponding measured value meets a predetermined condition.

[0009] According to one aspect of this disclosure, the human blood circulation system model includes a systemic circulation model, a pulmonary circulation model, and a neurofeedback model, wherein the systemic circulation model is associated with the left atrium and left ventricle; the pulmonary circulation model is associated with the right atrium and right ventricle; and the systemic circulation model and the pulmonary circulation model are connected by a vascular network to form a closed loop.

[0010] According to one aspect of this disclosure, the human blood circulation system model includes a systemic circulation model, a pulmonary circulation model, and a neural feedback model, wherein the neural feedback model includes afferent nerves and efferent nerves; wherein the afferent nerves are associated with aortic pressure, the efferent nerves can be divided into sympathetic nerves and vagus nerves, and the efferent nerves are associated with left ventricular elasticity, right ventricular elasticity, and peripheral resistance.

[0011] According to one aspect of this disclosure, the vascular physical property simulation device includes a temperature control device, a flow sensor, a compliance chamber, a level device, a solenoid valve connection component, a proportional valve, a temperature sensor, and a pressure sensor for adjusting peripheral resistance and / or simulating vascular compliance.

[0012] According to one aspect of this disclosure, adjusting the vascular physical characteristics simulation device using a proportional-integral-derivative (PID) control algorithm until the difference between the target value and the corresponding measured value meets a predetermined condition includes: calculating an initial parameter of at least one of vascular resistance, compliance, and test temperature in the current stage of the system simulating vascular physical characteristics based on a step response curve, and preliminarily tuning the initial parameter, wherein the initial parameter includes gain, time constant, and lag time; inputting the preliminarily tuned initial parameter into the human circulatory system model to obtain test results of the preliminarily tuned initial parameter in the human circulatory system model; and adjusting the vascular physical characteristics simulation device according to the test results until the difference between the target value and the corresponding measured value meets a predetermined condition.

[0013] According to one aspect of this disclosure, the target blood vessel includes multiple blood vessel branches, and the method further includes: adjusting the blood vessel physical characteristic simulation device according to a preset cooperative control strategy for indicating coupling compensation of physical parameters of each blood vessel branch.

[0014] According to one aspect of this disclosure, a system for simulating the physical properties of blood vessels is provided, comprising: a target blood vessel model acquisition unit configured to determine a target blood vessel to be simulated and to perform isolated modeling of each vascular branch of the target blood vessel based on clinical medical data of the target blood vessel to obtain a target blood vessel model; a blood vessel physical property simulation device; an in vitro testing device; and a control device configured to: calculate the physical characteristics of the target blood vessel based on a human blood circulation system model; set initial reference values ​​for the blood vessel physical property simulation device and the in vitro testing device in the system for simulating the physical properties of blood vessels based on the calculated physical characteristics of the target blood vessel; and connect the target blood vessel model to the blood vessel physical property simulation device and the in vitro testing device; operate the in vitro testing device based on the initial reference values; determine the measured values ​​of vascular resistance, compliance, and test temperature in the blood vessel model based on sensor-collected data; and calculate the difference between the target value and the corresponding measured value; and adjust the blood vessel physical property simulation device using a proportional-integral-derivative (PID) control algorithm until the difference between the target value and the corresponding measured value meets a predetermined condition.

[0015] According to one aspect of this disclosure, the vascular physical property simulation device includes a temperature control device, a flow sensor, a compliance chamber, a level device, a solenoid valve connection component, a proportional valve, a temperature sensor, and a pressure sensor for adjusting peripheral resistance and / or simulating vascular compliance.

[0016] According to one aspect of this disclosure, the control device is further configured to: calculate, based on a step response curve, an initial parameter of at least one of vascular resistance, compliance, and test temperature in the current stage of the system simulating vascular physical properties, and preliminarily tune the initial parameter, wherein the initial parameter includes gain, time constant, and hysteresis time; input the preliminarily tuned initial parameter into the human circulatory system model to obtain test results of the preliminarily tuned initial parameter in the human circulatory system model; and adjust the vascular physical property simulation device according to the test results until the difference between the target value and the corresponding measured value meets a predetermined condition.

[0017] According to one aspect of this disclosure, an electronic device is provided, comprising: a processor, a storage medium, and a bus, the storage medium storing machine-readable instructions executable by the processor, wherein when the electronic device is in operation, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the method described above for controlling a system simulating the physical properties of blood vessels.

[0018] The system, device, and control method for simulating vascular physical properties according to embodiments of the present invention integrate and couple a "mathematical model of the blood circulation system" with an "in vitro experimental device capable of simulating vascular physical properties." This technical solution can dynamically reproduce the real, personalized hemodynamic boundary conditions in vivo for target lesions (such as stenosis, aneurysm, and dissection) in in vitro experiments. This allows for a more realistic revelation of the pathological nature of vascular diseases and their hemodynamic relationship. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some exemplary embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0020] Figure 1 This is a flowchart illustrating a method for controlling a system simulating the physical properties of blood vessels according to an embodiment of the present disclosure;

[0021] Figure 2 This is a schematic diagram showing the equivalent circuit corresponding to an elastic lumen blood vessel;

[0022] Figure 3 This is a schematic diagram illustrating a system for simulating the physical properties of blood vessels according to an embodiment of the present disclosure;

[0023] Figure 4This is a schematic diagram illustrating a human blood circulation system model according to an embodiment of the present disclosure.

[0024] Figure 5 This is a schematic diagram illustrating a vascular physical characteristics simulation device according to an embodiment of the present disclosure;

[0025] Figure 6 A schematic diagram of a system for simulating the physical properties of blood vessels according to an embodiment of the present disclosure is shown;

[0026] Figure 7 This is a schematic diagram illustrating the hardware structure of a device according to an embodiment of the present disclosure. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0028] Unless otherwise defined, the technical or scientific terms used in this disclosure shall have the ordinary meaning understood by one of ordinary skill in the art to which this disclosure pertains. The terms "first," "second," and similar terms used in this disclosure do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships, and these relative positional relationships may change accordingly when the absolute position of the described object changes. To keep the following description of the embodiments of this disclosure clear and concise, detailed descriptions of some known functions and components are omitted.

[0029] This disclosure uses flowcharts to illustrate the steps of a method according to embodiments of this disclosure. It should be understood that the preceding or following steps are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0030] In the specification and drawings of this disclosure, elements are described in singular or plural forms according to embodiments. However, the singular and plural forms are suitably chosen for the presented cases merely for ease of explanation and are not intended to limit the disclosure thereto. Thus, a singular form may include a plural form, and a plural form may include a singular form, unless the context clearly indicates otherwise.

[0031] The system, equipment, and control method for simulating the physical properties of blood vessels provided in this disclosure will now be described in detail with reference to the accompanying drawings.

[0032] Figure 1 This is a flowchart illustrating a method for controlling a vascular physical property simulation system according to an embodiment of the present disclosure. Figure 1 As shown, in step S101, the lesion blood vessel to be simulated is determined, and each blood vessel branch of the lesion blood vessel is isolated and modeled according to the clinical medical data of the lesion blood vessel to obtain the target blood vessel model.

[0033] In the examples according to this disclosure, the lesion vessel under study may also be referred to as the target vessel, which refers to a vascular model prepared for a specific testing purpose and can be used to simulate the geometry and pathological state of blood vessels in different anatomical locations of the human circulatory system. In the examples of this disclosure, the target vessel may be made of ex vivo animal blood vessels or various synthetic materials. For example, the materials may include ex vivo animal biomaterials, elastic polymer materials (such as polyurethane TPU, silicone rubber), hydrogels, or decellularized biological tissue scaffolds. The materials should be able to simulate the mechanical properties of blood vessels to a certain extent, such as compliance and nonlinear behavior. The wall structure of the vascular model may be homogeneous or may be constructed to simulate a multilayer structure of the intima, media, and adventitia.

[0034] If using ex vivo animal blood vessels, collect the animal blood vessel model at its current location. To maintain the viability of the blood vessel model tissue, the blood vessel tissue can be preserved at -80°C. If using personalized lesion blood vessels, clinical medical data of the lesion blood vessels, such as CT, MRI, ultrasound, and vital signs parameters such as heart rate and blood pressure, must be collected under ethical approval to prepare data for subsequent model reconstruction and 3D reconstruction.

[0035] Furthermore, if animal blood vessels are used, a target lesion model needs to be constructed. If personalized lesion blood vessels are used, the model reconstruction mainly relies on medical information processing software to complete the reconstruction of the 3D digital model of the lesion blood vessels, simultaneously completing the model processing work before 3D printing, and selecting model manufacturing materials to complete the 3D printing of the blood vessel model for subsequent in vitro fluid experiments.

[0036] Based on clinical medical data of the target blood vessel, each vascular branch can be modeled in isolation. Optionally, a double-lumen model can be used to model the aorta and pulmonary artery, while a single-lumen model can be used to simulate SVRs (small arteries, etc.) in the systemic circulation. Single-lumen models can be used for small arteries, capillaries, and veins in the pulmonary circulation.

[0037] Figure 2 This is a schematic diagram showing the equivalent circuit corresponding to an elastic lumen blood vessel. For example... Figure 2 As shown, vascular resistance can be correlated with electrical resistance, using proximal R... p and remote R d Two resistors simulate the resistance characteristics of blood vessels before and after. The compliance of blood vessels can be correlated with capacitance, and thus, based on Kirchhoff's laws, ordinary differential equations of the equivalent circuit of blood vessels can be established. By establishing equivalent circuit models of blood vessels at different locations in the human body, modeling of the main branch blood vessels in the systemic and pulmonary circulations can be completed. Hemodynamic states can be simulated by solving the state equations. Equations (1) to (3) are solved as follows:

[0038]

[0039]

[0040]

[0041] in, and These represent the proximal and distal pressures, respectively. and These represent the proximal and distal compliance of blood vessels, respectively. Where is the inlet flow rate and Q is the flow rate towards the distal end of the blood vessel. Due to the compliance of blood vessels, some blood flow is stored within the lumen. This is due to blood flow inertia.

[0042] For example, in the case where the target vessel is the aorta and branch vessels 1 and 2 connected to the aorta, the hemodynamic state in the corresponding vessels can be simulated according to the above formulas (1)-(3) for the aorta, branch vessels 1 and 2 respectively.

[0043] On the other hand, in step S102, the physical characteristics of the target blood vessel can be calculated based on the human blood circulation system model, the initial reference values ​​of the blood vessel physical characteristic simulation device and the in vitro testing device can be set according to the calculated physical characteristics of the target blood vessel, and the target blood vessel model can be connected to the blood vessel physical characteristic simulation device and the in vitro testing device.

[0044] Figure 3 This is a schematic diagram of a system for simulating the physical properties of blood vessels (hereinafter also referred to as a "vascular physical property simulation system") according to an embodiment of this disclosure. Figure 3 As shown, the vascular physical property simulation system 300 according to an embodiment of this disclosure may include an in vitro testing device 310, a target vascular model 320, a vascular physical property simulation device 330, and a control device 340. Figure 3 In the example shown, a human blood circulation system model and a software control module for adjusting the physical properties of blood vessels 330 can be loaded into the control device 340.

[0045] According to one example of this disclosure, the in vitro testing device may include a fluid drive unit, a tubing connection system, and a control system. For example, the fluid drive unit may typically be a drive pump (e.g., a pulse pump) capable of precisely controlling flow and pressure to simulate the periodic beating function of the heart, generating blood pressure and blood flow similar to physiological states. The tubing connection system is used to physically connect the drive pump, the target blood vessel segment, and the vascular physical property simulation device to form a complete closed-loop or open-loop circuit.

[0046] It can be obtained according to step S101 Figure 3 The target blood vessel model 320 is shown. In step S102, the physical characteristics of the target blood vessel can be calculated based on the human blood circulation system model loaded in the control device 340. The initial reference values ​​of the vascular physical characteristic simulation device 330 are set according to the calculated physical characteristics of the target blood vessel, and the target blood vessel model 320 is connected to the vascular physical characteristic simulation system 300. For example, if the research object is aortic dissection, the model can be divided into three vascular region branches. One vascular physical characteristic simulation device 330 can be set for each of the three vascular region branches; alternatively, separate vascular physical characteristic simulation devices 330 can be set for each of the three vascular region branches.

[0047] Figure 4 This is a schematic diagram illustrating a model of the human circulatory system according to an embodiment of the present disclosure. The human circulatory system can be summarized as a dynamic equilibrium system involving the heart, blood vessels, and neural feedback. Figure 4As shown, the human circulatory system can be divided into three parts: systemic circulation (hereinafter referred to as "systemic circulation"), pulmonary circulation (hereinafter referred to as "pulmonary circulation"), and neurofeedback (hereinafter referred to as "neuroferring"). The left atrium (left atrium and left ventricle) is responsible for systemic circulation, while the right atrium (right atrium and right ventricle) is responsible for pulmonary circulation. The two are connected by a vascular network, forming a closed loop. During the cardiac cycle, the left and right ventricles contract and relax periodically according to their elastic properties, propelling blood flow. The left ventricle pumps oxygenated blood into the aorta, creating aortic pressure. Blood then flows through various tissues and organs via systemic circulation, returning to the right atrium through peripheral resistance and venous return. Pulmonary circulation involves the right ventricle pumping venous blood into the pulmonary artery. After gas exchange in the lungs, oxygenated blood returns to the left atrium via the pulmonary veins, completing a full cycle. Throughout this process, pressure and flow rate are key physiological variables. Changes in chamber pressures such as left atrial pressure, right atrial pressure, and aortic pressure reflect the heart's pumping function and the state of vascular resistance. Pulmonary venous flow and pulmonary arterial flow reflect the input and output status of the pulmonary circulation, respectively. These variables change over time, forming a dynamic system. Furthermore, the human circulatory system can also be regulated by neural feedback mechanisms.

[0048] According to an example of this disclosure, the atria and ventricles of the heart can be modeled based on an elastic time-varying model. The core of the elastic time-varying model is to construct the corresponding elastic time-varying function. The elastic time-varying performance of the ventricle can be described as the reciprocal of the time-varying capacitance corresponding to the ventricle. The calculation formulas (4) and (5) are as follows:

[0049]

[0050]

[0051] in , These represent the pressures of the left ventricle (LV) and right ventricle (RV), respectively. , This is the pressure corresponding to the minimum volume of LV and RV, for example, it can be 1 mmHg; The volumes of LV and RV can be represented by the difference between the flow rate through the corresponding valve in the ventricle and the flow rate through the aorta and pulmonary artery, respectively. Let LV and RV be the initial volumes, which are fixed constants, for example, both can be 5 mL; and Let be the time-varying elastic functions of LV and RV. According to an example of this disclosure, initial values ​​of parameters such as aortic pressure, left and right atrial pressures, ventricular elasticity, and cardiac cycle can be determined based on measurements of a patient.

[0052]

[0053]

[0054] Activation functions are primarily used to describe the contraction and relaxation states of the myocardium. Assuming that the left ventricular (LV) and right ventricular (RV) muscles move synchronously, i.e., using the same activation function, this can be expressed as a piecewise function as follows:

[0055]

[0056] in, and These represent the time points of systole and diastole in the cardiac cycle, respectively, and can be determined based on the patient's specific condition.

[0057] Furthermore, the left and right atria can also be described using elastic time-varying functions. During blood circulation, the atria always complete their contraction action earlier than the ventricles, and their mathematical models are shown in formulas (6) and (7):

[0058]

[0059]

[0060] , These represent the pressures in the left atrium (LA) and right atrium (LA), respectively. , The pressure corresponding to the minimum volume of LA and RA is 1 mmHg; Let LA and RA be the volumes; LA and LA's initial volumes are fixed constants, 3 mL; and Let LA and RA be time-varying elastic functions.

[0061] The mitral, tricuspid, and aortic valves in the heart function to prevent backflow of blood pressure in the blood circulation. They can be represented by diodes. The forward resistance can be set according to the valve performance, while the reverse resistance is considered to be infinite. The state equation is shown in formula (8):

[0062]

[0063] in Representing the mitral valve and aortic valve, This represents the pressure difference between the atrial and ventricular sides of the valve.

[0064] According to an example of this disclosure, the human body's regulatory reflex function to vascular pressure can also be considered to establish a pressure reflex mathematical model that integrates aortic baroreceptors, afferent nerves, efferent nerves, and different effectors, so as to establish a complete mathematical model of the blood circulation system. Aortic afferent nerves can transmit the dynamic relationship between nerve impulses and aortic pressure. Efferent nerves can be divided into sympathetic nerves and vagus nerves. When they receive stimulation signals from afferent nerves, their response effects are opposite. The mathematical model can be shown in formula (9):

[0065]

[0066] in Sympathetic nerve frequency, and All are constants, and < .

[0067] The activity frequency of the vagus nerve is positively correlated with the activity frequency of the sinus nerve, and its mathematical model can be expressed as formula (10):

[0068]

[0069] in The frequency of nerve impulses in the vagus nerve. and All are constants, namely 0.0675, 6.3, and 3.2, and... < . The central value of the afferent neural function is 25. The effector in the pressure feedback can adjust the peripheral resistance, ventricular elasticity, and cardiac cycle. The effector function of peripheral resistance can be composed of a delay part representing neural transmission, a monotonic logarithmic function, and a first-order linear dynamic function, as shown in the following formula (11):

[0070]

[0071] in It can be represented as Elasticity values ​​of the left and right ventricles and cardiac cycle T1; This represents the change in the corresponding effector per unit time. All are constants. , , The values ​​are 0.36, 0.475, and 0.282, respectively. The neural conduction delay time for each effector is 2 seconds.

[0072] The cardiac cycle effector function consists of a delay element, a monotonic linear function, and a first-order linear differential equation:

[0073]

[0074]

[0075] in This represents the delay time for vagal nerve signal transmission, with a default value of 0.2s. The change in cardiac cycle under the influence of ES. The amount of change in cardiac cycle under the influence of EV needs to be determined from the patient's clinical data; The cardiac cycle is a fixed value of 0.58 seconds. The autonomic nervous system (such as the sympathetic and parasympathetic nervous systems) regulates cardiac elasticity and peripheral resistance in real time to adapt to the body's metabolic needs and changes in the external environment, maintaining stable blood pressure and blood flow.

[0076] Alternatively, an equivalent circuit of the heart can be used to better simulate the physiological environment. For example, in the equivalent circuit of the heart, time-varying capacitors can be used to simulate the four chambers of the heart, diodes can be used to simulate the unidirectional action of the valves, and the established pressure feedback model can be added to the overall model to establish an equivalent circuit model of blood circulation with pressure feedback regulation. Based on Kirchhoff's laws, the corresponding set of state equations can be established, and the fluid dynamics can be solved by setting the values ​​of the state variables as initial conditions.

[0077] Furthermore, according to one example of this disclosure, the physical characteristics of the target blood vessel may include vascular branch resistance, vascular compliance parameters (e.g., vascular volume, etc.). In step S102, the physical characteristics of the target blood vessel may be determined according to... Figure 4 The human circulatory system model shown combines collected clinical physiological parameters to obtain the physical characteristics of target vascular branches. For example, patient blood pressure and ultrasound flow velocity data, as well as imaging vascular morphology data, can be substituted into the human circulatory mathematical model to obtain patient-specific peripheral resistance and vascular compliance parameters. As another example, flow data for each branch can be obtained through MRI imaging data, thereby yielding theoretical parameter values ​​for branch vascular characteristics—the target parameters that the vascular physical characteristic simulation device aims to achieve.

[0078] Figure 5 This is a schematic diagram illustrating a vascular physical property simulation device 330 according to an embodiment of the present disclosure. The vascular physical property simulation device 330 can simulate vascular physical properties in an optional number of devices, including but not limited to adjustable peripheral resistance modules and / or vascular compliance simulation modules, to reproduce the resistance and compliance of a target blood vessel and its branches in the circuit.

[0079] like Figure 5As shown, the vascular physical property simulation device 330 may include a temperature control device 501, a flow sensor 502, a compliance chamber 503, a liquid level device 504, a solenoid valve connection component 505, a proportional valve 506, a temperature sensor 507, and a pressure sensor (not shown). The resistance of the target vascular branch can be controlled via the proportional valve 506, and vascular compliance can be simulated using the closed compliance chamber 503. Different vascular compliance levels can be simulated by controlling the gas-to-liquid volume ratio in the container. According to an example of this disclosure, the relationship between compliance magnitude and pressure can be determined based on the Bowles model, as shown in the following formula 14:

[0080]

[0081] C a Indicates aortic compliance, V o0 P represents the initial volume of air within the cavity. a This represents the average target vascular pressure. Under normal physiological conditions, SP is 120 mmHg, DP is 90 mmHg, and mean pressure is 100 mmHg. k is the gas constant with a value of 1.1, and P... atm The standard atmospheric pressure is 760 mmHg. As can be seen from formula (14), the compliance is directly proportional to the air volume. Under the condition that the bottom area of ​​the compliance chamber is constant, the compliance is directly proportional to the gas height.

[0082] In the vascular physical characteristic simulation device 330, pressure and flow sensors 502 are used to detect intraluminal pressure and simulate branch flow, respectively, to calculate the real-time resistance of branch vessels based on the detection results. A level sensor 504 monitors the liquid level in the compliance cavity to obtain corresponding compliance parameters. A temperature sensor 507 detects the temperature within the tubing to better simulate the physiological environment. The pressure within the compliance cavity 503 can be controlled by adjusting the airflow through three channels at the top that can be connected to solenoid valves. Two of these channels are connected to a vacuum line (0~-0.5 kPa), and one is connected to a high-pressure line (3~5 kPa). Specifically, the pressure, flow, and temperature sensors deployed in the vascular characteristic simulation device can collect key operating parameters of the system in real time, and transmit the signals to the central control terminal through a high-precision data acquisition device, enabling continuous monitoring and recording of dynamic parameters. Furthermore, the proportional valve 506 and solenoid valve 507, among other actuators configured in the device 330, are connected to the control module to facilitate bidirectional communication between the device 330 and the control module.

[0083] For example, in step S102, it can be based on Figure 4The human circulatory system model shown, combined with collected clinical physiological parameters, adjusts the proportional valve 506 in the vascular physical characteristic simulation device 330 to simulate peripheral resistance of blood circulation. Furthermore, flow data for each branch can be obtained through MRI imaging data, thereby yielding theoretical parameter values ​​for branch vascular characteristics—the target parameters to be achieved by the vascular physical characteristic simulation device 330. Additionally, the aortic ultrasound flow velocity curve can be fitted to the mathematical model input curve, thus obtaining the flow input curve for the in vitro testing device.

[0084] In step S103, the in vitro testing device is operated based on initial reference values, and the measured values ​​of vascular resistance, compliance, and test temperature in the vascular model are determined according to the sensor data, and the difference between the target value and the corresponding measured value is calculated. According to an example of this disclosure, after the initial resistance and compliance of the target vascular vessel, as well as the overall pressure and peripheral resistance of the remaining vessels other than the target vessel, are set and the system parameters meet physiological reference values, the in vitro testing device can start operating. Information from the multi-pressure sensor system in the vascular physical characteristic simulation system is collected. After the system stabilizes, the vascular resistance, compliance, and system temperature can be determined based on the sensor data, and the difference parameters between the target value and the measured value are calculated simultaneously to determine whether the difference between the target value and the measured value meets predetermined conditions. For example, the difference parameters may include the normalized root mean square, root mean square deviation coefficient, and normalized mean absolute error. As another example, the system simulating vascular physical characteristics may also include another vascular physical characteristic simulation device to simulate the characteristics of the remaining vessels in the entire human body, excluding the target vessel.

[0085] In step S104, the proportional-integral-derivative (PID) control algorithm is used to adjust the vascular physical characteristic simulation device until the difference between the real-time vascular characteristic values ​​(vascular resistance, compliance) collected by the pressure sensor and flow sensor and the target value meets the predetermined conditions.

[0086] When the difference between the target value and the measured value does not meet the predetermined conditions, the in vitro testing device is adjusted by simulating the neural feedback mechanism and the synergistic mechanism between various vascular branches until the difference between the target value and the corresponding measured value meets the predetermined conditions.

[0087] For example, based on each blood vessel branch isolated in step S101, an approximate model of the system can be obtained using the step response method. Based on the step response curve, the initial parameters of the current stage of the blood vessel physical property simulation system can be calculated. For example, the initial parameters may include the gain, time constant, and lag time of various parameters in the system. According to an example of this disclosure, the calculated initial parameters can be initially tuned using the Ziegler-Nichols method or other frequency domain methods. For example, a step input is given to the system (e.g., a sudden change in the opening of a proportional valve), and the system's response curve (e.g., a change in blood vessel pressure) is recorded.

[0088] In the digital proportional-integral-derivative (PID) controller during the tuning phase, Kp is the proportional gain, Ki is the integral coefficient, Ti is the integral time constant, and Td is the derivative time constant, Ki = Kp * (Ts / Ti), where Ts is the sampling time, and Kd is the derivative coefficient, Kd = Kp * (Td / Ts). During the parameter tuning phase, taking the simulated vascular branch pressure value as an example, the output is the pressure change ΔP, and the input is the proportional valve opening change ΔV, where...

[0089] K = ΔP / ΔV (Unit: mmHg / % opening)

[0090] K = 2.0 mmHg / % (1% change in valve opening corresponds to a 2 mmHg change in pressure)

[0091] L = 0.5 s (System response lag is 0.5 seconds)

[0092] T = 3.0 s (System time constant 3 seconds)

[0093] Furthermore, the parameters in the PID controller can be tuned according to the following conditions:

[0094] Kp = 1.2 × T / (K × L) = 3.6

[0095] Ti = 2 × L = 1.0 s

[0096] Td = 0.5 × L = 0.25 s

[0097] Then, the pre-tuned parameters (e.g., Kp, Ti, etc.) are input into the human blood circulation system model for testing, and the parameters are adjusted to meet the performance indicators (e.g., overshoot, settling time, steady-state error).

[0098] Because coupling may exist between target vessel branches, regulation of one branch may affect other branches. Therefore, one aspect of this disclosure is to set a collaborative control strategy to achieve coupling compensation of the physical parameters of each branch vessel. For example, a strategy combining distributed control, centralized control, cascaded control, and feedforward compensation can be adopted. Taking distributed control as an example, in the distributed regulation process of an in vitro fluid experimental platform, the operator first sets the overall target of the system (such as total flow rate and reference pressure). Subsequently, the control device dynamically calculates and allocates the flow rate and pressure setpoints for each branch based on the setpoints and the real-time status and resistance characteristics of the target vessel branches. The control device regulates actuators such as solenoid valve connecting components and proportional valves, performing independent, rapid, and precise PID regulation while compensating for the fluid coupling effect between branches through information exchange. During this process, flow sensors and pressure sensors continuously collect flow and pressure data of the entire system and the local flow of the target vessel branches, and feed them back to the control device in real time.

[0099] This allows for the integration of feedback regulation within the mathematical model of the circulatory system to adapt to the influence of different physical property values ​​of blood vessel models on the peripheral resistance of the system, thereby better simulating the physiological response characteristics of real blood vessels. For example, in step S104, the in vitro testing device can be adjusted using a simulated neural feedback mechanism until the difference between the target value and the corresponding measured value meets predetermined conditions.

[0100] Furthermore, for example, when the normalized root mean square error between the real-time values ​​and set values ​​of vascular characteristic experiments remains unchanged and the monitored peripheral resistance of the system is stable, the system adjustment can be considered complete, and in vitro fluid dynamics experiments can be conducted in a stable state. For example, when the mutual influence of vascular physical characteristic parameters between branches is <5%, the time difference between each branch reaching steady state is <1 second, and the matching degree between branch flow distribution and resistance setting is >90%, the overall system adjustment can be considered to have reached a stable state.

[0101] The above combination Figure 1-5 The control method of the system for simulating the physical properties of blood vessels provided in this disclosure is described below, in conjunction with... Figure 6 A system for simulating the physical properties of blood vessels, as provided in this disclosure, is described. Because... Figure 6 The system 600 shown, which simulates the physical properties of blood vessels, is combined with the above. Figure 1-5 The control methods described correspond to this, so for simplicity, detailed descriptions of the same content are omitted here.

[0102] Figure 6 A schematic diagram of a system simulating the physical properties of blood vessels according to an embodiment of the present disclosure is shown. Figure 6As shown, the system 600 for simulating the physical properties of blood vessels according to an embodiment of the present disclosure may include a target blood vessel model acquisition unit 610, a control device 620, a blood vessel physical property simulation device 630, and an in vitro testing device 640.

[0103] The vascular model acquisition unit 610 can identify the lesion vessel to be simulated, collect clinical medical data of the lesion vessel, and perform isolated modeling of each vascular branch of the lesion vessel to obtain a target vascular model. In the examples according to this disclosure, the lesion vessel to be studied can also be referred to as the target vessel, which refers to a vascular model prepared for a specific testing purpose and can be used to simulate the geometric structure and pathological state of blood vessels in different anatomical locations in the human circulatory system. The vascular model acquisition unit 610 can perform isolated modeling of each vascular branch based on the clinical medical data of the target vessel. Optionally, a double-lumen model can be used to model the aorta and pulmonary artery, and a single-lumen model can be used to simulate SVRs (small arteries, etc.) in the systemic circulation, while single-lumen models can be used for small arteries, capillaries, and veins in the pulmonary circulation. The above combinations can be used. Figure 2 The equivalent circuit described is used to model the target blood vessel.

[0104] The control unit 620 can calculate the physical characteristics of the target blood vessel based on a human circulatory system model, set the initial reference values ​​for the vascular physical characteristic simulation device 630 based on the calculated physical characteristics of the target blood vessel, and connect the target blood vessel model to the vascular physical characteristic simulation device 630 and the in vitro testing device 640. For example, in the system simulating vascular physical characteristics, the control device 620, the vascular physical characteristic simulation device 630, and the in vitro testing device 640 can be implemented as follows: Figure 3 The vascular physical property simulation system 300 shown includes your control device 340, vascular physical property simulation device 330, and in vitro testing device 310.

[0105] A human circulatory system model and a software control module for adjusting the physical properties of blood vessels 630 can be loaded into the control device 620. The control device 620 can then adjust the load based on the loaded human circulatory system model (e.g., as described above). Figure 4 The model of the human circulatory system (described) calculates the physical characteristics of the target blood vessel, sets the initial reference values ​​of the vascular physical characteristic simulation device 630 based on the calculated physical characteristics of the target blood vessel, and connects the target blood vessel model obtained by the blood vessel model acquisition unit 610. For example, if the research object is aortic dissection, the model can be divided into three vascular region branches. One vascular physical characteristic simulation device 630 can be set for each of the three vascular region branches, or alternatively, separate vascular physical characteristic simulation devices 630 can be set for each of the three vascular region branches.

[0106] The vascular physical property simulation device 630 can simulate vascular physical properties in an optional number of devices, not limited to adjustable peripheral resistance modules and / or vascular compliance simulation modules, to reproduce the resistance and compliance of the target blood vessel and its branches in the circuit. (As described above...) Figure 5 The vascular physical characteristics simulation device 630 described may include a temperature control device, a flow sensor, a compliance chamber, a level device, a solenoid valve connection component, a proportional valve, a temperature sensor, and a pressure sensor.

[0107] The control device 620 can control the resistance of the target blood vessel branch by adjusting the proportional valve of the blood vessel physical property simulation device 630, and use a closed compliance cavity to simulate blood vessel compliance. Different blood vessel compliance can be simulated by controlling the volume ratio of gas to liquid in the container.

[0108] Furthermore, in the vascular physical characteristic simulation device 630, pressure and flow sensors can be used to detect intraluminal pressure and simulate branch flow, respectively, to calculate the real-time resistance of branch vessels based on the detection results. A level sensor monitors the liquid level in the compliance chamber to obtain corresponding compliance parameters. A temperature sensor detects the temperature within the tubing to better simulate the physiological environment. The pressure within the compliance chamber can be controlled by adjusting the airflow through three channels at the top that can be connected to solenoid valves; two are connected to a vacuum line (0 to -0.5 kPa), and one is connected to a high-pressure line (3 to 5 kPa). Specifically, through the pressure, flow, and temperature sensors deployed in the vascular characteristic simulation device, key operating parameters of the system can be collected in real time, and the signals are transmitted to the central control terminal via a high-precision data acquisition device, enabling continuous monitoring and recording of dynamic parameters. In addition, the proportional valves and solenoid valves configured in the vascular physical characteristic simulation device 630 are connected to the control module to facilitate bidirectional communication between the device and the control module.

[0109] For example, the control device 620 can be based on Figure 4 The human circulatory system model shown, combined with collected clinical physiological parameters, adjusts the proportional valve in the vascular physical characteristic simulation device 630 to simulate peripheral resistance of blood circulation. Furthermore, flow data for each branch can be obtained through MRI imaging data, leading to theoretical parameter values ​​for branch vascular characteristics—the target parameters to be achieved by the vascular physical characteristic simulation device 630. Additionally, the aortic ultrasound flow velocity curve can be fitted to the mathematical model input curve, thus obtaining the flow input curve for the in vitro testing device.

[0110] Furthermore, the control unit 620 can operate the in vitro testing device 640 based on initial reference values, and determine the measured values ​​of vascular resistance, compliance, and test temperature in the vascular model based on sensor data, and calculate the difference between the target value and the corresponding measured value. According to an example of this disclosure, after the initial resistance and compliance of the target vascular vessel, as well as the overall pressure and peripheral resistance of the remaining vessels outside the target vessel, are set and the system parameters meet physiological reference values, the in vitro testing device 640 can begin operation. It collects system information through multiple pressure sensors in the vascular physical characteristic simulation system. After the system stabilizes, the control unit 620 can also determine the vascular resistance, compliance, and system temperature based on sensor data and simultaneously calculate the difference parameters between the target value and the measured value to determine whether the difference between the target value and the measured value meets predetermined conditions. For example, the difference parameters may include the normalized root mean square, the root mean square deviation coefficient, and the normalized mean absolute error.

[0111] When the difference between the target value and the measured value does not meet the predetermined conditions, the control unit 620 can use a proportional-integral-derivative (PID) control algorithm to adjust the vascular physical characteristic simulation device 630 until the difference between the real-time vascular characteristic values ​​(vascular resistance, compliance) collected by the pressure sensor and the flow sensor and the target value meets the predetermined conditions.

[0112] When the difference between the target value and the measured value does not meet the predetermined conditions, the in vitro testing device is adjusted by simulating the neural feedback mechanism and the synergistic mechanism between various vascular branches until the difference between the target value and the corresponding measured value meets the predetermined conditions.

[0113] For example, the control unit 620 can obtain an approximate model of the system using the step response method based on each isolated vascular branch, and calculate the initial parameters of the current stage of the vascular physical property simulation system based on the step response curve. For example, the initial parameters may include the gain, time constant, and lag time of various parameters in the system. According to an example of this disclosure, the calculated initial parameters can be initially tuned using the Ziegler-Nichols method or other frequency domain methods. For example, a step input is given to the system (e.g., a sudden change in the opening of a proportional valve), and the system's response curve (e.g., a change in vascular pressure) is recorded.

[0114] In the digital proportional-integral-derivative (PID) controller during the tuning phase, Kp is the proportional gain, Ki is the integral coefficient, Ti is the integral time constant, and Td is the derivative time constant, Ki = Kp * (Ts / Ti), where Ts is the sampling time, and Kd is the derivative coefficient, Kd = Kp * (Td / Ts). During the parameter tuning phase, taking the simulated vascular branch pressure value as an example, the output is the pressure change ΔP, and the input is the proportional valve opening change ΔV, where...

[0115] K = ΔP / ΔV (Unit: mmHg / % opening)

[0116] K = 2.0 mmHg / % (1% change in valve opening corresponds to a 2 mmHg change in pressure)

[0117] L = 0.5 s (System response lag is 0.5 seconds)

[0118] T = 3.0 s (System time constant 3 seconds)

[0119] Furthermore, the parameters in the PID controller can be tuned according to the following conditions:

[0120] Kp = 1.2 × T / (K × L) = 3.6

[0121] Ti = 2 × L = 1.0 s

[0122] Td = 0.5 × L = 0.25 s

[0123] Then, the pre-tuned parameters (e.g., Kp, Ti, etc.) are input into the human blood circulation system model for testing, and the parameters are adjusted to meet the performance indicators (e.g., overshoot, settling time, steady-state error).

[0124] Because coupling may exist between the branches of the target blood vessel, regulation of one branch may affect other branches. Therefore, one aspect of this disclosure is to set a collaborative control strategy to achieve coupling compensation of the physical parameters of each branch blood vessel. For example, a strategy combining distributed control, centralized control, cascaded control, and feedforward compensation can be adopted. This allows for the integration of feedback regulation in the mathematical model of the circulatory system to adapt to the influence of different physical characteristic values ​​of the blood vessel model on the peripheral resistance of the system, thereby better simulating the physiological response characteristics of real blood vessels. For another example, the control unit 620 can regulate the in vitro testing device through a simulated neural feedback mechanism until the difference between the target value and the corresponding measured value meets a predetermined condition.

[0125] Furthermore, for example, when the normalized root mean square error between the real-time values ​​and set values ​​of vascular characteristic experiments remains unchanged and the monitored peripheral resistance of the system is stable, the system adjustment can be considered complete, and in vitro fluid dynamics experiments can be conducted in a stable state. For example, when the mutual influence of vascular physical characteristic parameters between branches is <5%, the time difference between each branch reaching steady state is <1 second, and the matching degree between branch flow distribution and resistance setting is >90%, the overall system adjustment can be considered to have reached a stable state.

[0126] Furthermore, the block diagrams used in the above embodiments illustrate blocks based on functionality. These functional blocks (structural units) are implemented through any combination of hardware and / or software. Moreover, the means of implementing each functional block are not particularly limited. That is, each functional block can be implemented using a single device that is physically and / or logically combined, or it can be implemented using multiple devices by directly and / or indirectly (e.g., via wired and / or wireless) connecting two or more physically and / or logically separate devices.

[0127] For example, the device of one embodiment of this disclosure can function as a computer executing the system of this disclosure to control simulated vascular physical properties. Figure 7 This is a schematic diagram illustrating the hardware structure of the device 700 according to an embodiment of the present disclosure. The device 700 described above can be configured as a computer device that physically includes a processor 710, a memory 720, an input / output device 730, a bus 740, etc.

[0128] Additionally, in the following description, the word "device" can be replaced with circuit, device, unit, etc. The hardware structure of the terminal may include one or more of the devices shown in the figures, or may not include some of the devices.

[0129] For example, only one processor 710 is shown, but there can also be multiple processors. Furthermore, processing can be performed by a single processor, or by more than one processor simultaneously, sequentially, or using other methods. Additionally, processor 710 can be mounted on more than one chip.

[0130] The functions of the device 700 are implemented, for example, by reading the instructions (programs) stored in the memory 720 into hardware such as the processor 710, thereby enabling the processor 710 to perform operations, control the input / output device 730, and control the reading and / or writing of data in the memory 720.

[0131] The processor 710, for example, enables the operating system to operate, thereby controlling the computer as a whole. The processor 710 may be composed of a central processing unit (CPU) that includes interfaces with peripheral devices, control devices, arithmetic devices, registers, etc. For example, the aforementioned processing units can be implemented by the processor 710.

[0132] Furthermore, the processor 710 reads programs (program code), data, etc., from the memory 720 and performs various processes accordingly. The program can be one that causes the computer to perform at least a portion of the actions described in the above embodiments. For example, the method executed by the first AP can be implemented using a control program stored in the memory 720 and operated by the processor 710. Similarly, the method executed by the second AP can also be implemented using a control program stored in the memory 720 and operated by the processor 710.

[0133] The memory 720 may be a computer-readable recording medium, such as at least one of a read-only memory (ROM), an erasable programmable read-only memory (EPROM), an electrically programmable read-only memory (EEPROM), a random access memory (RAM), or other suitable storage media. The memory 720 may include registers, caches, main memory (main storage device), etc. The memory 720 may store executable programs (program code), software modules, etc., for implementing the methods according to an embodiment of this disclosure.

[0134] In addition, the memory 720 may also include a computer-readable recording medium comprising, for example, at least one of a flexible disk, a floppy disk, a magneto-optical disk (e.g., a read-only optical disk (CD-ROM, etc.), a digital universal optical disk, a Blu-ray disc), a removable disk, a hard disk, a smart card, a flash memory device (e.g., a card, a stick, a key driver), a magnetic stripe, a database, a server, or other suitable storage media.

[0135] The input / output device 730 may include an input unit (e.g., keyboard, mouse, microphone, switch, button, sensor, etc.) that accepts input from the outside, and an output unit (e.g., display, speaker, light-emitting diode (LED) lamp, etc.) that performs output to the outside. Alternatively, the input unit and the output unit may be integrated into one structure (e.g., a touch panel).

[0136] Furthermore, the processor 710, memory 720, input / output device 730, and other devices are connected via a bus 740 for communication of information. The bus 740 can consist of a single bus or different buses between devices.

[0137] Furthermore, device 700 may include hardware such as a microprocessor, digital signal processor (DSP), application-specific integrated circuit (ASIC), programmable logic device (PLD), and field-programmable gate array (FPGA), which can be used to implement some or all of the functional blocks. For example, processor 710 can be installed using at least one of these hardware components.

[0138] The present disclosure has been described in detail above, but it will be apparent to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modifications and variations without departing from the spirit and scope of the invention as defined by the claims. Therefore, the description in this disclosure is for illustrative purposes and is not intended to be restrictive.

[0139] In this disclosure, whether the software is referred to as software, firmware, middleware, microcode, hardware description language, or any other name, it should be broadly interpreted as meaning instruction, instruction set, code, code segment, program code, program, subroutine, software module, application, software application, software package, routine, subroutine, object, executable file, execution thread, procedure, function, etc.

[0140] The information, signals, etc., described in this disclosure can also be represented using one of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc., which may be mentioned throughout the above description, can also be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or any combination thereof.

[0141] Furthermore, the terms used in this disclosure and those necessary for understanding this disclosure may be replaced with terms that have the same or similar meanings. For example, a signal may also be a message or signaling.

[0142] Furthermore, the information, parameters, etc., described in this disclosure can be represented using absolute values, relative values ​​with respect to a specific value, or other corresponding information. For example, wireless resources can also be indicated by an index.

[0143] The term "determine" as used in this disclosure sometimes encompasses a variety of operations. For example, "determine" or "obtain" may include actions such as making a judgment, calculating, deriving, processing, deriving, investigating, searching (e.g., searching in a table, database, or other data structure), confirming, etc. Furthermore, "determine" or "obtain" may include actions such as receiving (e.g., receiving information), sending (e.g., sending information), inputting, outputting, or accessing (e.g., accessing data in memory) as "judging" or "deciding," etc.

[0144] Unless otherwise expressly stated, the use of the word "based on" in this disclosure does not imply "based on only". In other words, the use of the word "based on" implies both "based on only" and "based on at least".

[0145] In this disclosure, the term "unit" in the structure of the above-mentioned devices may also be replaced with "circuit", "device", etc.

Claims

1. A method for controlling the physical properties of a simulated blood vessel, comprising: The target blood vessel to be simulated is identified, and each branch of the target blood vessel is modeled in isolation based on the clinical medical data of the target blood vessel to obtain a target blood vessel model; The physical characteristics of the target blood vessel are calculated based on the human blood circulation system model. The initial reference values ​​of the blood vessel physical characteristic simulation device and the in vitro testing device in the system of simulating blood vessel physical characteristics are set according to the calculated physical characteristics of the target blood vessel. The target blood vessel model is then connected to the blood vessel physical characteristic simulation device and the in vitro testing device. The in vitro testing device is operated based on the initial reference values. The measured values ​​of vascular resistance, compliance, and test temperature in the vascular model are determined according to the sensor data, and the differences between the target values ​​and the corresponding measured values ​​are calculated. The vascular physical property simulation device is adjusted using a proportional-integral-derivative (PID) control algorithm until the difference between the target value and the corresponding measured value meets a predetermined condition.

2. The method of claim 1, wherein The human circulatory system model includes a systemic circulation model, a pulmonary circulation model, and a neurofeedback model, among which... The systemic circulation model is associated with the left atrium and left ventricle; The pulmonary circulation model is associated with the right atrium and right ventricle; The systemic circulation model and the pulmonary circulation model are connected by a vascular network to form a closed loop.

3. The method of claim 2, wherein The human circulatory system model includes a systemic circulation model, a pulmonary circulation model, and a neurofeedback model. The neural feedback model includes afferent nerves and efferent nerves; wherein The afferent nerves are associated with aortic pressure. The efferent nerves can be divided into sympathetic nerves and vagus nerves. The efferent nerves are associated with left ventricular elasticity, right ventricular elasticity, and peripheral resistance.

4. The method of claim 1, wherein The vascular physical property simulation device includes a temperature control device, a flow sensor, a compliance chamber, a liquid level device, a solenoid valve connection component, a proportional valve, a temperature sensor, and a pressure sensor for adjusting peripheral resistance and / or simulating vascular compliance.

5. The method of claim 4, wherein adjusting the vascular physical characteristic simulation device using a proportional-integral-derivative (PID) control algorithm until the difference between the target value and the corresponding measured value meets a predetermined condition includes: Based on the step response curve, calculate the initial parameter of at least one of vascular resistance, compliance, and test temperature in the current stage of the system simulating vascular physical properties, and perform preliminary tuning of the initial parameter, wherein the initial parameter includes gain, time constant, and hysteresis time. The initially tuned parameters are input into the human blood circulation system model to obtain the test results of the initially tuned parameters in the human blood circulation system model. The vascular physical property simulation device is adjusted according to the test results until the difference between the target value and the corresponding measured value meets the predetermined conditions.

6. The method of claim 1, wherein the target blood vessel comprises a plurality of vascular branches, the method further comprising: The vascular physical characteristic simulation device is adjusted according to a preset collaborative control strategy for coupling compensation of physical parameters of each branch blood vessel.

7. A system for simulating the physical properties of blood vessels, comprising: The target blood vessel model acquisition unit is configured to determine the target blood vessel to be simulated, and to perform isolated modeling of each blood vessel branch of the target blood vessel based on the clinical medical data of the target blood vessel, so as to obtain the target blood vessel model. Vascular physical properties simulation device; In vitro testing device; The control device is configured as follows: The physical characteristics of the target blood vessel are calculated based on the human blood circulation system model. The initial reference values ​​of the blood vessel physical characteristic simulation device and the in vitro testing device in the system of simulating blood vessel physical characteristics are set according to the calculated physical characteristics of the target blood vessel. The target blood vessel model is then connected to the blood vessel physical characteristic simulation device and the in vitro testing device. The in vitro testing device is operated based on the initial reference values. The measured values ​​of vascular resistance, compliance, and test temperature in the vascular model are determined according to the sensor data, and the differences between the target values ​​and the corresponding measured values ​​are calculated. The vascular physical property simulation device is adjusted using a proportional-integral-derivative (PID) control algorithm until the difference between the target value and the corresponding measured value meets a predetermined condition.

8. The system of claim 7, wherein The vascular physical property simulation device includes a temperature control device, a flow sensor, a compliance chamber, a liquid level device, a solenoid valve connection component, a proportional valve, a temperature sensor, and a pressure sensor for adjusting peripheral resistance and / or simulating vascular compliance.

9. The system of claim 7, wherein the control device is further configured to: Based on the step response curve, calculate the initial parameter of at least one of vascular resistance, compliance, and test temperature in the current stage of the system simulating vascular physical properties, and perform preliminary tuning of the initial parameter, wherein the initial parameter includes gain, time constant, and hysteresis time. The initially tuned parameters are input into the human blood circulation system model to obtain the test results of the initially tuned parameters in the human blood circulation system model. The vascular physical property simulation device is adjusted according to the test results until the difference between the target value and the corresponding measured value meets the predetermined conditions.

10. An electronic device, comprising: The system includes a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is in operation, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the steps of the method for controlling the physical properties of a simulated blood vessel as described in any one of claims 1 to 6.

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