Fatigue wear test system for cardiovascular implant

Abstract

The invention relates to the technical field of cardiovascular implant wear test, and discloses a cardiovascular implant fatigue wear test method, which comprises the following steps: simulating an in-vivo environment model of a cardiovascular implant, identifying biological tissue elements in the in-vivo environment model, and calculating the fatigue wear of the cardiovascular implant. According to biomechanical characteristics of biological tissue elements and daily activity rules of a treated object, physiological conditions of the in-vivo environment model are set, a mounting cavity and a circulating flow channel of the cardiovascular implant in the in-vivo environment model are set, a circulating loading test is performed on the cardiovascular implant in the in-vivo environment model, and the in-vivo environment model is obtained. And the operation state of the cardiovascular implant is monitored in real time so as to analyze the fatigue life and the wear degree of the cardiovascular implant, and a fatigue wear test result of the cardiovascular implant in the in-vivo environment model is generated. The reliability of the fatigue wear test result of the cardiovascular implant can be improved.

Description

Technical Field

[0001] The invention relates to the technical field of cardiovascular implant wear test, in particular to a cardiovascular implant fatigue wear test system. Background Art

[0002] Cardiovascular implants refer to medical devices that are surgically implanted into the human body for the treatment of cardiovascular diseases. These devices are surgically implanted into the patient's body to improve or restore the patient's cardiovascular function. Cardiovascular disease, as the leading cause of death worldwide, has seriously affected the patient's quality of life and life expectancy. Cardiovascular implants, as an effective treatment method, have been widely used in clinical practice. However, these implants need to be used in the human body for a long time and withstand the mechanical stress caused by the continuous beating of the heart and blood flow. In order to ensure that the implants can operate stably in the human body for a long time, fatigue wear tests need to be performed on cardiovascular implants.

[0003] In the prior art, fatigue wear tests on cardiovascular implants are mainly carried out using dynamic fatigue testing machines, which apply periodic radial displacements to the ends of the implants to simulate the cyclic loads that the cardiovascular implants are subjected to in actual use. Although this method can evaluate the safety and effectiveness of the implants to a certain extent, it is difficult to fully simulate the complex biomechanical environment in the human body, resulting in low credibility of the test results. Summary of the invention

[0004] The present invention provides a fatigue wear test system and method for cardiovascular implants, the main purpose of which is to increase the credibility of the results of the fatigue wear test of cardiovascular implants.

[0005] To achieve the above-mentioned purpose, the present invention provides a fatigue wear test system for cardiovascular implants, comprising: an environment simulation module, a condition setting module, a cavity configuration module, a state monitoring module, and a result output module;

[0006] The environmental simulation module is used to obtain the cardiovascular implant to be tested and its corresponding treatment object, schedule the physiological data of the treatment object, and identify the patient group characteristics of the cardiovascular implant according to the treatment object and the physiological data, and simulate the in vivo environmental model of the treatment object based on the patient group characteristics;

[0007] The condition setting module is used to identify the biological tissue elements of the in vivo environment model, identify the daily activity patterns of the treatment object based on the patient group characteristics, analyze the biomechanical properties of the biological tissue elements, set the physiological conditions of the in vivo environment model based on the biomechanical properties and the daily activity patterns, and simulate the working mechanism of the biological tissue elements under the physiological conditions;

[0008] The cavity configuration module is used to set the installation cavity of the cardiovascular implant in the in vivo environment model according to the working mechanism, set the circulation channel of the in vivo environment model based on the installation cavity, analyze the fluid flow pattern of the circulation channel, and identify the cardiorespiratory movement law of the treatment object according to the physiological data;

[0009] The state monitoring module is used to set the cyclic load of the in vivo environment model based on the cardiac respiratory movement law, determine the frequency range of the cyclic load, extract the blood parameters of the fluid flow pattern, set the cyclic loading test of the cardiovascular implant in the in vivo environment model based on the cyclic load, the frequency range and the blood parameters, and monitor the operating state of the cardiovascular implant under the cyclic loading test in real time;

[0010] The result output module is used to analyze the fatigue life and wear degree of the cardiovascular implant based on the operating state, and generate fatigue wear test results of the cardiovascular implant in the in vivo environment model according to the fatigue life and the wear degree.

[0011] Optionally, identifying patient population characteristics of the cardiovascular implant according to the treatment object and the physiological data includes:

[0012] Analyzing physiological characteristics of the subject according to the physiological data;

[0013] Extracting indicator elements from the physiological data and identifying abnormal factors of the indicator elements;

[0014] Analyzing the lifestyle characteristics of the treatment subject based on the abnormal factors and the indicator elements;

[0015] Analyzing the type of cardiovascular disease of the subject according to the abnormal factors;

[0016] Based on the physiological characteristics, the lifestyle characteristics and the type of cardiovascular disease, identifying common frequency characteristics of the treatment subject;

[0017] Calculating the cluster center of the common frequency features;

[0018] Based on the cluster centers, patient population characteristics of the cardiovascular implants are identified.

[0019] Optionally, simulating the in vivo environment model of the treatment subject based on the patient population characteristics includes:

[0020] Analyzing the physiological status and cardiovascular function of the subject based on the patient population characteristics;

[0021] constructing a cardiovascular model of the subject according to the physiological state and the cardiovascular function;

[0022] Meshing the cardiovascular model to obtain a mesh model;

[0023] Identifying organizational elements of the mesh model and setting material property definitions of the organizational elements;

[0024] Based on the material property definition, setting boundary conditions of the mesh model;

[0025] The in vivo environment model of the treatment subject is simulated according to the cardiovascular model and the boundary conditions.

[0026] Optionally, the setting of the physiological conditions of the in vivo environment model based on the biomechanical characteristics and the daily activity pattern includes:

[0027] scheduling biological tissue elements of the in vivo environment model based on the biomechanical properties;

[0028] simulating a fluid pattern of the biological tissue element according to the biomechanical properties;

[0029] Based on the daily activity pattern, setting the activity state of the in-vivo environment model;

[0030] Analyzing the comprehensive performance of the biological tissue element in the in vivo environment model according to the biomechanical properties and the fluid pattern;

[0031] The physiological conditions of the in vivo environment model are set in combination with the activity state and the comprehensive performance.

[0032] Optionally, the setting of the activity state of the in-vivo environment model based on the daily activity pattern includes:

[0033] Based on the daily activity pattern, identifying active patients in the in-vivo environment simulation model;

[0034] Calculating the coefficient of variation of the physical signs of the active patients according to the daily activity patterns;

[0035] Extracting patient physical sign attributes under the physical sign variation coefficient;

[0036] Analyze the changing trend of the patient's physical sign attributes under the daily activity pattern;

[0037] Based on the patient's vital sign attributes and the change trend, the activity state of the in-vivo environment model is set.

[0038] Optionally, the step of setting the installation cavity of the cardiovascular implant in the in vivo environment model according to the working mechanism includes:

[0039] identifying functional factors of the cardiovascular implant according to the working mechanism;

[0040] analyzing an implant type of the cardiovascular implant;

[0041] Determining the location and installation point of the cardiovascular implant based on the functional factor and the implant type;

[0042] Based on the position installation point, a mounting cavity of the cardiovascular implant in the in vivo environment model is set.

[0043] Optionally, the setting of the circulation channel of the in-vivo environment model based on the installation cavity includes:

[0044] Identifying an installation position of the installation cavity in the in vivo environment model;

[0045] analyzing a blood flow path in the in-vivo environment model, and positioning a blood use pump of the in-vivo environment model according to the blood flow path;

[0046] Setting a blood flow inlet of the in vivo environment model based on the blood usage pump;

[0047] According to the installation position, setting a blood flow outlet of the in-vivo environment model;

[0048] Based on the blood flow outlet and the blood flow inlet, a circulation flow channel of the in-vivo environment model is set.

[0049] Optionally, setting a cyclic loading test of the cardiovascular plant in the in vivo environment model based on the cyclic load, the frequency range and the blood parameter includes:

[0050] Based on the cyclic load and the frequency range, obtaining a fatigue testing machine for the cardiovascular implant;

[0051] Identifying a loading unit of the fatigue testing machine, and setting a load waveform of the loading unit according to the cyclic load;

[0052] Based on the frequency range, setting the loading frequency of the loading unit;

[0053] According to the blood parameter, setting the load amplitude of the loading unit;

[0054] In combination with the loading frequency, the load amplitude and the load waveform, a cyclic loading test of the cardiovascular plant in the in vivo environment model is set.

[0055] Optionally, analyzing the fatigue life and wear degree of the cardiovascular implant based on the operating state includes:

[0056] identifying fatigue performance and fatigue strength of the cardiovascular implant under the operating condition;

[0057] calculating the fatigue life of the cardiovascular implant based on the fatigue performance and the fatigue strength;

[0058] analyzing stress and strain conditions of the cardiovascular implant according to the operating state;

[0059] identifying material properties of the cardiovascular implant;

[0060] The wear degree of the cardiovascular implant is analyzed according to the material properties and the stress-strain conditions.

[0061] A fatigue wear test method for cardiovascular implants, characterized in that the method comprises:

[0062] Acquire a cardiovascular implant to be tested and its corresponding treatment subject, schedule physiological data of the treatment subject, and identify patient group characteristics of the cardiovascular implant according to the treatment subject and the physiological data, and simulate an in vivo environment model of the treatment subject based on the patient group characteristics;

[0063] Identify biological tissue elements of the in vivo environment model, identify the daily activity patterns of the treatment subject based on the patient population characteristics, analyze the biomechanical properties of the biological tissue elements, set the physiological conditions of the in vivo environment model based on the biomechanical properties and the daily activity patterns, and simulate the working mechanism of the biological tissue elements under the physiological conditions;

[0064] According to the working mechanism, the cardiovascular implant is arranged in a mounting cavity of the in vivo environment model, a circulation channel of the in vivo environment model is arranged based on the mounting cavity, a fluid flow pattern of the circulation channel is analyzed, and the cardiorespiratory movement law of the treatment subject is identified according to the physiological data;

[0065] Based on the cardiac respiratory movement law, a cyclic load of the in vivo environment model is set, and a frequency range of the cyclic load is determined, blood parameters of the fluid flow pattern are extracted, and based on the cyclic load, a cyclic loading test of the cardiovascular implant in the in vivo environment model is set, and the operating state of the cardiovascular implant under the cyclic loading test is monitored in real time;

[0066] Based on the operating status, the fatigue life and the degree of wear of the cardiovascular implant are analyzed, and according to the fatigue life and the degree of wear, fatigue and wear test results of the cardiovascular implant in the in vivo environment model are generated.

[0067] The embodiment of the present invention can simulate the real working state of the cardiovascular implant in the body in a controlled virtual environment by simulating the in vivo environmental model of the treatment object based on the characteristics of the patient group, so as to more accurately evaluate the fatigue wear performance of the implant; secondly, the embodiment of the present invention can ensure that the cardiovascular implant has the best performance when subjected to various mechanical loads by analyzing the biomechanical properties of the biological tissue elements, reduce stress concentration and fatigue damage, so as to improve the biocompatibility of the cardiovascular implant, and by setting the physiological conditions of the in vivo environmental model, a more personalized in vivo environmental model can be established to ensure that the simulation results are closer to the actual situation; further, the embodiment of the present invention can set the installation cavity of the cardiovascular implant in the in vivo environmental model, and set a circulating flow channel based on the cavity, and then analyze the fluid flow pattern in the circulating flow channel, which is helpful to evaluate the hemodynamic impact of the cardiovascular implant in actual use, and test the cardiovascular implant through the circulating flow channel. The embodiment of the present invention can evaluate the durability and reliability of the cardiovascular implant in long-term use by setting the cyclic loading test of the cardiovascular implant in the in vivo environment model based on the cyclic load, the frequency range and the blood parameters, and ensure that the parameters such as the load waveform, frequency and amplitude during the test process meet the predetermined test conditions, thereby ensuring the accuracy and reliability of the test results, and by real-time monitoring of the experimental process, any abnormal situation that may occur in the cardiovascular implant can be discovered in time; finally, the embodiment of the present invention can evaluate the durability and reliability of the cardiovascular implant in long-term use by analyzing the fatigue life and wear degree of the cardiovascular implant based on the operating state, and ensure its long-term performance under physiological conditions, and by calculating the wear degree, the wear of the cardiovascular implant in long-term use can be evaluated, ensuring its safety and effectiveness under physiological conditions, and improving the credibility of the test results. Therefore, the fatigue wear test method of a cardiovascular implant proposed in the embodiment of the present invention can increase the credibility of the fatigue wear test results of the cardiovascular implant. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 A functional module diagram of a fatigue wear test system for cardiovascular implants provided by one embodiment of the present invention;

[0069] Figure 2 A schematic flow chart of a fatigue wear test method for a cardiovascular implant provided in one embodiment of the present invention.

[0070] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] In fact, the server-side device deployed by the fatigue and wear test system for cardiovascular implants may be composed of one or more devices. The above-mentioned fatigue and wear test system for cardiovascular implants can be implemented as: business instances, virtual machines, and hardware devices. For example, the fatigue and wear test system for cardiovascular implants can be implemented as a business instance deployed on one or more devices in a cloud node. Simply put, the live broadcast service system can be understood as a software deployed on a cloud node, which is used to provide fatigue and wear test services for cardiovascular implants to each user terminal. Alternatively, the fatigue and wear test system for cardiovascular implants can also be implemented as a virtual machine deployed on one or more devices in a cloud node. Application software for managing each user terminal is installed in the virtual machine. Alternatively, the fatigue and wear test system for cardiovascular implants can also be implemented as a server composed of many hardware devices of the same or different types, and one or more hardware devices are set to provide fatigue and wear test services for cardiovascular implants to each user terminal.

[0073] In terms of implementation, the fatigue wear test system for cardiovascular implants and the user end are adapted to each other. That is, the fatigue wear test system for cardiovascular implants is an application installed on the cloud service platform, and the user end is a client that establishes a communication connection with the application; or the fatigue wear test system for cardiovascular implants is implemented as a website, and the user end is implemented as a web page; or the fatigue wear test system for cardiovascular implants is implemented as a cloud service platform, and the user end is implemented as a small program in an instant messaging application.

[0074] Reference Figure 1 , which is a functional module diagram of a fatigue wear testing system for cardiovascular implants provided in one embodiment of the present invention.

[0075] The cardiovascular implant fatigue wear test system 100 of the present invention can be set in a cloud server. In terms of implementation, it can be used as one or more service devices, or as an application installed on the cloud (such as a server, server cluster, etc. for fatigue wear test of cardiovascular implants), or it can also be developed as a website. According to the functions implemented, the cardiovascular implant fatigue wear test system 100 includes an environment simulation module 101, a condition setting module 102, a cavity configuration module 103, a state monitoring module 104, and a result output module 105.

[0076] In the embodiment of the present invention, in the tracking of fatigue wear test based on cardiovascular implants, each of the above modules can be independently implemented and called with other modules. The call here can be understood as that a certain module can connect multiple modules of another type and provide corresponding services to the multiple modules connected to it. In the fatigue wear test system of cardiovascular implants provided by the embodiment of the present invention, the scope of application of the fatigue wear test architecture of cardiovascular implants can be adjusted by adding modules and directly calling them without modifying the program code, so as to achieve cluster-type horizontal expansion, so as to achieve the purpose of quickly and flexibly expanding the fatigue wear test system of cardiovascular implants. In practical applications, the above modules can be set in the same device or different devices, or they can be set in virtual devices, such as service instances in cloud servers.

[0077] In the following, various components and specific workflows of the fatigue wear test system for cardiovascular implants are described in conjunction with specific embodiments.

[0078] The environmental simulation module 101 is used to obtain the cardiovascular implant to be tested and its corresponding treatment object, schedule the physiological data of the treatment object, and identify the patient group characteristics of the cardiovascular implant based on the treatment object and the physiological data, and simulate the in vivo environmental model of the treatment object based on the patient group characteristics.

[0079] The embodiment of the present invention can provide sufficient data support for subsequent analysis and processing by obtaining the cardiovascular implant to be tested and the corresponding treatment object, wherein the treatment object refers to a patient group that needs to receive cardiovascular implant treatment.

[0080] Furthermore, the embodiments of the present invention can more accurately simulate the patient's real physiological state in the simulation model of the in vivo environment by scheduling the physiological data of the treatment object and identifying the patient group characteristics of the cardiovascular implant based on the treatment object and the physiological data, thereby improving the accuracy and reliability of the simulation. The physiological data refers to the biological and physical data of the treatment object, such as heart rate data, and the patient group characteristics refer to specific physiological, pathological or demographic characteristics shared among a group of patients receiving cardiovascular implant treatment.

[0081] Optionally, the scheduling of the physiological data of the treatment subject may be achieved using an electronic health system.

[0082] As an embodiment of the present invention, the identifying the patient group characteristics of the cardiovascular implant based on the treatment object and the physiological data includes: analyzing the physiological characteristics of the treatment object based on the physiological data; extracting indicator elements in the physiological data and identifying abnormal factors of the indicator elements; analyzing the lifestyle characteristics of the treatment object based on the abnormal factors and the indicator elements; analyzing the type of cardiovascular disease of the treatment object based on the abnormal factors; identifying the common frequency characteristics of the treatment object based on the physiological characteristics, the lifestyle characteristics and the type of cardiovascular disease; calculating the cluster center of the common frequency characteristics; and identifying the patient group characteristics of the cardiovascular implant based on the cluster center.

[0083] Among them, the physiological characteristics refer to the biological and physical characteristics of the treatment object, such as heart rate, blood pressure, electrocardiogram, blood oxygen saturation, etc., the indicator elements refer to the physiological parameters that can be quantified in the physiological data, such as blood pressure value, heart rate, hemodynamic parameters, etc., the abnormal factors refer to the indicator elements that deviate from the normal range in the physiological data, such as abnormal heart rate, the lifestyle characteristics refer to the patient's living habits and behavior patterns, such as diet, exercise, smoking and drinking habits, etc., the cardiovascular disease type refers to the specific cardiovascular disease suffered by the patient, such as coronary artery disease, heart failure, valvular heart disease, etc., the cluster center refers to the central position point representing all the points in the cluster of a single physiological characteristic, lifestyle characteristic and cardiovascular disease type, the common frequency feature refers to the feature with relatively high similarity in the treatment object summarized based on the physiological characteristics, lifestyle characteristics and cardiovascular disease type, and the cluster center refers to the point representing the center or average position of all points of the characteristic parameters.

[0084] Optionally, the abnormal factor identification of the indicator element can be obtained by statistical methods, such as the Z-score method, and the analysis of the type of cardiovascular disease of the treatment object based on the abnormal factor can be achieved using the patient's medical history data.

[0085] In an optional embodiment of the present invention, the cluster center of the common frequency feature is calculated using the following formula:

[0086]

[0087] Among them, A i represents the cluster center of the common frequency features in the i-th cluster, M i represents the number of data points with common features in the i-th cluster, X j represents the jth common frequency feature in the i-th cluster, X represents the common frequency feature, i represents the cluster index of the cluster center, and j represents the index of the common frequency feature within the i-th cluster.

[0088] The embodiment of the present invention simulates the in vivo environmental model of the treatment object based on the characteristics of the patient group, and can simulate the real working state of the cardiovascular implant in the body in a controlled virtual environment, so as to more accurately evaluate the fatigue and wear performance of the implant. The in vivo environmental model refers to a system that simulates the internal environment of the human body, which includes a complex environment composed of simulated blood circulation, interstitial fluid, extracellular fluid, etc.

[0089] As an embodiment of the present invention, the simulation of the in vivo environment model of the treatment object based on the patient group characteristics includes: analyzing the physiological state and cardiovascular function of the treatment object based on the patient group characteristics; constructing a cardiovascular model of the treatment object according to the physiological state and the cardiovascular function; meshing the cardiovascular model to obtain a mesh model; identifying tissue elements of the mesh model and setting material property definitions of the tissue elements; setting boundary conditions of the mesh model based on the material property definitions; and simulating the in vivo environment model of the treatment object according to the cardiovascular model and the boundary conditions.

[0090] Among them, the physiological state refers to the biological and physical characteristics of patients with cardiovascular diseases, such as heart rate, blood pressure, blood composition, metabolic level, etc., the cardiovascular function refers to the function of the heart and vascular system, including the heart's pumping ability, the elasticity and compliance of blood vessels, the dynamics of blood flow, etc., the cardiovascular model refers to a cardiovascular virtual model constructed according to the patient's anatomical structure and physiological data, the grid model refers to a model obtained by gridding the cardiovascular model, the tissue elements refer to different tissue parts that constitute the cardiovascular system, such as the myocardium, vascular wall, blood, etc., the material property definition refers to the physical and biomechanical parameters assigned to the tissue elements in the grid model, such as elastic modulus, Poisson's ratio, density, viscosity, etc., and the boundary conditions refer to the external constraints and loads when the cardiovascular system actually works in the body.

[0091] Optionally, the physiological state and cardiovascular function analysis of the treatment object based on the patient group characteristics can be implemented using the PhysioData toolbox, the cardiovascular model construction of the treatment object based on the physiological state and the cardiovascular function can be obtained through computer-aided design (CAD) software, the meshing of the cardiovascular model can be implemented using ANSYS simulation software, and the material property definition of the tissue elements and the boundary condition setting of the mesh model can be obtained through the CRI MSON software framework.

[0092] The condition setting module 102 is used to identify the biological tissue elements of the in vivo environment model, identify the daily activity patterns of the treatment object based on the patient group characteristics, analyze the biomechanical properties of the biological tissue elements, set the physiological conditions of the in vivo environment model based on the biomechanical properties and the daily activity patterns, and simulate the working mechanism of the biological tissue elements under the physiological conditions.

[0093] The embodiment of the present invention can provide test subjects for subsequent simulation tests by identifying biological tissue elements of the in vivo environment model, wherein the biological tissue elements refer to different tissue parts constituting the cardiovascular system, such as the myocardium, blood vessel wall, blood, etc.

[0094] Optionally, the biological tissue element identification of the in vivo environment model can be obtained through a simulation model.

[0095] Furthermore, the embodiments of the present invention can understand the mechanical loads of the daily activities of patients with cardiovascular diseases on biological tissues by identifying the daily activity patterns of the treatment subjects based on the characteristics of the patient group, thereby improving the accuracy and reliability of the in vivo environment simulation. The daily activity patterns refer to the activity patterns and behavioral habits of the treatment subjects in their daily activities.

[0096] Optionally, the identification of the daily activity patterns of the treatment subjects based on the patient group characteristics can be achieved using wearable devices, such as smart watches.

[0097] The embodiments of the present invention can ensure that the cardiovascular implant has the best performance when subjected to various mechanical loads by analyzing the biomechanical properties of the biological tissue elements, reduce stress concentration and fatigue damage, and improve the biocompatibility of the cardiovascular implant. The biomechanical properties refer to the mechanical properties and behaviors of biological tissues, such as fracture toughness.

[0098] Optionally, the biomechanical properties of the biological tissue elements can be achieved using a biomechanical testing platform.

[0099] Furthermore, the embodiments of the present invention can establish a more personalized in vivo environment model by setting the physiological conditions of the in vivo environment model based on the biomechanical characteristics and the daily activity patterns, thereby ensuring that the simulation results are closer to the actual situation. The physiological conditions refer to various physiological parameters and environmental factors related to the performance of biological tissues and implants, such as blood pressure parameters, which are simulated in the in vivo environment model.

[0100] As an embodiment of the present invention, setting the physiological conditions of the in vivo environment model based on the biomechanical characteristics and the daily activity patterns includes: scheduling the biological tissue elements of the in vivo environment model based on the biomechanical characteristics; simulating the fluid patterns of the biological tissue elements according to the biomechanical characteristics; setting the activity state of the in vivo environment model based on the daily activity patterns; analyzing the comprehensive performance of the biological tissue elements in the in vivo environment model according to the biomechanical characteristics and the fluid patterns; and setting the physiological conditions of the in vivo environment model in combination with the activity state and the comprehensive performance.

[0101] Among them, the fluid mode refers to the fluid flow characteristics within the biological tissue elements simulated in the simulation model, including blood flow velocity, direction, pressure distribution, etc.; the activity state refers to the movement and deformation state of the biological tissue elements in the in vivo environment model; and the comprehensive performance refers to the overall performance of the structure and material properties of the biological tissue elements when subjected to biomechanical effects, including strength, toughness, durability, etc.

[0102] Optionally, the fluid pattern simulation of the biological tissue element based on the biomechanical characteristics can be implemented using fluid dynamics (CFD) software, and the comprehensive performance analysis of the biological tissue element in the in vivo environment model based on the biomechanical characteristics and the fluid pattern can be obtained through multi-physical field coupling simulation.

[0103] As another embodiment of the present invention, setting the activity state of the in-vivo environment model based on the daily activity pattern includes: identifying active patients in the in-vivo environment simulation model based on the daily activity pattern; calculating the coefficient of variation of vital signs of the active patients according to the daily activity pattern; extracting patient vital sign attributes under the coefficient of variation of vital signs; analyzing the changing trend of the patient vital sign attributes under the daily activity pattern; and setting the activity state of the in-vivo environment model based on the patient vital sign attributes and the changing trend.

[0104] Among them, the active patients refer to patients with cardiovascular diseases whose daily activities are simulated and considered in the simulation model, the vital signs variation coefficient refers to the influence coefficient of daily activities on the vital signs of patients with cardiovascular diseases, such as the heart rate variation coefficient, the patient vital signs attributes refer to the specific attributes of the vital signs of patients with cardiovascular diseases, such as heart rate, blood pressure, etc., and the changing trend refers to the changing pattern of the vital signs attributes of patients with cardiovascular diseases under the influence of daily activities.

[0105] Optionally, the change trend analysis of the patient's vital sign attributes under the daily activity pattern can be implemented using a machine learning algorithm, such as a Scikit-Learn algorithm.

[0106] In an optional embodiment of the present invention, according to the daily activity pattern, the coefficient of variation of the physical signs of the active patient is calculated using the following formula:

[0107]

[0108] Where k represents the coefficient of variation of the signs of active patients, R e represents the length of the e-th sign cycle of an active patient, represents the average sign cycle length of active patients, q represents the number of sign cycles of active patients, and e represents the sign index of active patients.

[0109] The embodiments of the present invention can better understand the interaction between implants and biological tissues by simulating the working mechanism of the biological tissue elements under the physiological conditions, thereby optimizing the design of implants and reducing wear and potential complications. The working mechanism refers to how biological tissues respond and perform their physiological functions under specific physiological conditions.

[0110] Optionally, the simulation of the working mechanism of the biological tissue element under the physiological conditions can be implemented using simulation software, such as ANSYS simulation software.

[0111] The cavity configuration module 103 is used to set the installation cavity of the cardiovascular implant in the in vivo environment model according to the working mechanism, set the circulation channel of the in vivo environment model based on the installation cavity, analyze the fluid flow pattern of the circulation channel, and identify the cardiorespiratory movement law of the treatment object according to the physiological data.

[0112] The embodiment of the present invention sets the installation cavity of the cardiovascular implant in the in vivo environment model according to the working mechanism, and can set a circulation channel based on the cavity, and then analyze the fluid flow pattern in the circulation channel. The installation cavity refers to a specific space set in the model simulating the internal environment of the human body for placing the cardiovascular implant.

[0113] As an embodiment of the present invention, setting the installation cavity of the cardiovascular implant in the in vivo environment model according to the working mechanism includes: identifying functional factors of the cardiovascular implant according to the working mechanism; analyzing the implant type of the cardiovascular implant; determining a position installation point of the cardiovascular implant in combination with the functional factors and the implant type; and setting the installation cavity of the cardiovascular implant in the in vivo environment model based on the position installation point.

[0114] Among them, the functional factor refers to the key factor for the cardiovascular implant to play a specific function in the cardiovascular system, the implant type refers to the type of cardiovascular implant with different functions and uses, such as heart valves, vascular stents, pacemakers, etc., and the installation point refers to the specific installation position of the cardiovascular implant in the cardiovascular system.

[0115] Optionally, the combination of the functional factors and the implant type can be achieved by determining the location and installation point of the cardiovascular implant using imaging data such as MRI to understand the anatomical structure of the cardiovascular system.

[0116] Furthermore, the embodiments of the present invention help evaluate the hemodynamic impact of cardiovascular implants in actual use by setting up the circulating flow channel of the in vivo environment model based on the installation cavity, and test the performance of the cardiovascular implant in a simulated in vivo environment through the circulating flow channel, wherein the circulating flow channel refers to the path of blood circulation in the body.

[0117] As an embodiment of the present invention, setting the circulation flow channel of the in vivo environment model based on the installation cavity includes: identifying the installation position of the installation cavity in the in vivo environment model; analyzing the blood flow path in the in vivo environment model, and positioning the blood use pump of the in vivo environment model according to the blood flow path; setting the blood flow inlet of the in vivo environment model based on the blood use pump; setting the blood flow outlet of the in vivo environment model according to the installation position; and setting the circulation flow channel of the in vivo environment model based on the blood flow outlet and the blood flow inlet.

[0118] Among them, the installation position refers to the specific position of the cardiovascular implant in the in vivo environment model, the blood flow path refers to the flow route of blood in the in vivo environment model, the blood flow outlet refers to the part of the circulation channel that simulates blood leaving the vascular system, the blood flow inlet refers to the part of the circulation channel that simulates blood entering the vascular system, and the blood pump refers to a device that simulates the heart's blood pumping function.

[0119] Optionally, the blood flow path analysis in the in vivo environment model can be obtained through physiological data and anatomical structure of patients with cardiovascular diseases, and according to the blood flow path, the blood pump positioning of the in vivo environment model can be achieved using blood flow rate and flow parameters.

[0120] The embodiment of the present invention can monitor the blood parameters of the cardiovascular implant in the in vivo environment model in real time and improve the environmental stability of the in vivo environment model by analyzing the fluid flow pattern of the circulation channel. The fluid flow pattern refers to the fluid flow characteristics in the biological tissue elements simulated in the simulation model, including blood flow velocity, direction, pressure distribution, etc.

[0121] Optionally, the fluid flow pattern analysis of the circulation channel can be implemented using ANSYS Fluent software.

[0122] Furthermore, the embodiments of the present invention can simulate more realistic in vivo physiological conditions by identifying the cardiac respiratory movement pattern of the treatment subject based on the physiological data to predict the fatigue and wear characteristics of cardiovascular implants in long-term use. The cardiac respiratory movement pattern refers to the regular activities of contraction and relaxation of the heart in the cardiac cycle, such as the rapid ejection phase of the heart.

[0123] Optionally, the identification of the cardiorespiratory movement pattern of the treatment subject based on the physiological data can be achieved by using cardiac magnetic resonance imaging technology, such as phase contrast MRI (PCMRI) technology.

[0124] The state monitoring module 104 is used to set the cyclic load of the in vivo environment model based on the cardiac respiratory movement law, determine the frequency range of the cyclic load, extract the blood parameters of the fluid flow pattern, set the cyclic loading test of the cardiovascular implant in the in vivo environment model based on the cyclic load, the frequency range and the blood parameters, and monitor the operating state of the cardiovascular implant under the cyclic loading test in real time.

[0125] The embodiment of the present invention sets the cyclic load of the in vivo environment model based on the law of cardiac respiratory movement and determines the frequency range of the cyclic load, so as to more realistically reproduce the actual working environment of the cardiovascular implant in the body. By setting the frequency range of the cyclic load, the cyclic load experienced by the implant within a certain period of time can be simulated, so as to evaluate its long-term performance and fatigue life. The cyclic load refers to the load that simulates the load change of the heart during the contraction and relaxation process in the fatigue wear test of the cardiovascular implant. The frequency range refers to the repetition frequency of the cyclic load in the fatigue wear test, such as the typical heart rate.

[0126] Optionally, the cyclic load setting of the in vivo environment model based on the cardiorespiratory motion law can be performed by using COMSOL The software obtains that the frequency range of the cyclic load can be determined by using experimental data or clinical data.

[0127] Furthermore, the embodiment of the present invention can identify the blood stability of the in vivo environment model by extracting the blood parameters of the fluid flow pattern, where the blood parameters refer to parameters such as flow velocity, flow direction, and flow rate during the blood flow process.

[0128] Optionally, the blood parameter extraction of the fluid flow pattern can be achieved using a cardiac hemodynamics simulation device.

[0129] The embodiment of the present invention can evaluate the durability and reliability of the cardiovascular implant in long-term use by setting a cyclic loading test of the cardiovascular implant in the in vivo environmental model based on the cyclic load, the frequency range and the blood parameters. The cyclic loading test refers to simulating the cyclic load and environmental conditions that the cardiovascular implant is subjected to in the human body in the in vivo environmental model.

[0130] As an embodiment of the present invention, the cyclic loading test of the cardiovascular plant in the in vivo environment model is set based on the cyclic load, the frequency range and the blood parameters, including: obtaining a fatigue testing machine of the cardiovascular implant based on the cyclic load and the frequency range; identifying a loading unit of the fatigue testing machine, and setting a load waveform of the loading unit according to the cyclic load; setting a loading frequency of the loading unit based on the frequency range; setting a load amplitude of the loading unit according to the blood parameters; and setting a cyclic loading test of the cardiovascular plant in the in vivo environment model in combination with the loading frequency, the load amplitude and the load waveform.

[0131] Among them, the fatigue testing machine refers to a device used to evaluate the durability and reliability of materials or components under repeated loads, the loading unit refers to the key component in the fatigue testing machine used to apply cyclic loads, the load waveform refers to the shape of the load applied by the loading unit changing over time, the loading frequency refers to the frequency of the load applied by the loading unit, that is, the number of loads per unit time, and the load amplitude refers to the difference between the maximum and minimum values ​​of the load applied by the loading unit.

[0132] Optionally, the fatigue test of the cardiovascular implant based on the cyclic load and the frequency range may be achieved using a universal testing machine.

[0133] Furthermore, the embodiments of the present invention can ensure that the parameters such as load waveform, frequency and amplitude during the test meet the predetermined test conditions by real-time monitoring of the operating state of the cardiovascular implant under the cyclic loading test, thereby ensuring the accuracy and reliability of the test results, and can promptly discover any abnormal conditions that may occur in the cardiovascular implant by real-time monitoring of the experimental process. The operating state refers to the behavior and performance of the implant under simulated in vivo environment and physiological conditions.

[0134] Optionally, real-time monitoring of the operating status of the cardiovascular implant under the cyclic loading test may be obtained by a sensor device, such as a load sensor.

[0135] The result output module 105 is used to analyze the fatigue life and wear degree of the cardiovascular implant based on the operating status, and generate fatigue wear test results of the cardiovascular implant in the in vivo environment model according to the fatigue life and the wear degree.

[0136] The embodiment of the present invention analyzes the fatigue life and wear degree of the cardiovascular implant based on the operating state, thereby evaluating the durability and reliability of the cardiovascular implant in long-term use, ensuring its long-term performance under physiological conditions, and by calculating the wear degree, evaluating the wear condition of the cardiovascular implant in long-term use, ensuring its safety and effectiveness under physiological conditions, wherein the fatigue life refers to the maximum number of cycles under which the cardiovascular implant does not suffer fatigue failure under repeated loads, and the wear degree refers to the degree of damage to the surface or internal structure of the cardiovascular implant under repeated loads.

[0137] As an embodiment of the present invention, analyzing the fatigue life and wear degree of the cardiovascular implant based on the operating state includes: identifying the fatigue performance and fatigue strength of the cardiovascular implant under the operating state; calculating the fatigue life of the cardiovascular implant based on the fatigue performance and the fatigue strength; analyzing the stress-strain condition of the cardiovascular implant according to the operating state; identifying the material properties of the cardiovascular implant; and analyzing the wear degree of the cardiovascular implant according to the material properties and the stress-strain condition.

[0138] Among them, the fatigue performance refers to the ability of cardiovascular implants to resist fatigue failure under repeated loads, the fatigue strength refers to the maximum stress of cardiovascular implants without fatigue failure under a certain number of cycles, the stress-strain condition refers to the stress and strain distribution of cardiovascular implants under load, and the material properties refer to the mechanical, chemical, physical and other characteristics of the materials of cardiovascular implants.

[0139] Optionally, the stress-strain analysis of the cardiovascular implant according to the operating state may be achieved using finite element analysis, and the identification of the material properties of the cardiovascular implant may be obtained through standard material testing methods, such as a tensile test method.

[0140] In an optional embodiment of the present invention, based on the fatigue performance and the fatigue strength, the fatigue life of the cardiovascular implant is calculated using the following formula:

[0141]

[0142] Among them, B f represents the fatigue life of cardiovascular implants, r max represents the maximum stress of cardiovascular implants in fatigue performance, s f represents the strength coefficient of fatigue strength and g represents the fatigue index of cardiovascular implants.

[0143] Furthermore, the embodiments of the present invention generate fatigue wear test results of the cardiovascular implant in the in vivo environment model according to the fatigue life and the wear degree, so as to evaluate whether the cardiovascular implant can reach the expected safe service life under different operating conditions, thereby timely discovering potential safety hazards and avoiding the occurrence of adverse events. At the same time, by simulating the in vivo environment model of the cardiovascular implant, the real working state of the cardiovascular implant in the body can be simulated in a controlled virtual environment, so as to more accurately evaluate the fatigue wear performance of the implant. The fatigue wear test results refer to a series of data and conclusions obtained after a certain period of fatigue testing and wear testing of the cardiovascular implant in the simulated in vivo environment model.

[0144] The embodiment of the present invention can simulate the real working state of the cardiovascular implant in the body in a controlled virtual environment by simulating the in vivo environmental model of the treatment object based on the characteristics of the patient group, so as to more accurately evaluate the fatigue wear performance of the implant; secondly, the embodiment of the present invention can ensure that the cardiovascular implant has the best performance when subjected to various mechanical loads by analyzing the biomechanical properties of the biological tissue elements, reduce stress concentration and fatigue damage, so as to improve the biocompatibility of the cardiovascular implant, and by setting the physiological conditions of the in vivo environmental model, a more personalized in vivo environmental model can be established to ensure that the simulation results are closer to the actual situation; further, the embodiment of the present invention can set the installation cavity of the cardiovascular implant in the in vivo environmental model, and set a circulating flow channel based on the cavity, and then analyze the fluid flow pattern in the circulating flow channel, which is helpful to evaluate the hemodynamic impact of the cardiovascular implant in actual use, and test the cardiovascular implant through the circulating flow channel. The embodiment of the present invention can evaluate the durability and reliability of the cardiovascular implant in long-term use by setting the cyclic loading test of the cardiovascular implant in the in vivo environment model based on the cyclic load, the frequency range and the blood parameters, and ensure that the parameters such as the load waveform, frequency and amplitude during the test process meet the predetermined test conditions, thereby ensuring the accuracy and reliability of the test results, and by real-time monitoring of the experimental process, any abnormal situation that may occur in the cardiovascular implant can be discovered in time; finally, the embodiment of the present invention can evaluate the durability and reliability of the cardiovascular implant in long-term use by analyzing the fatigue life and wear degree of the cardiovascular implant based on the operating state, and ensure its long-term performance under physiological conditions, and by calculating the wear degree, the wear of the cardiovascular implant in long-term use can be evaluated, ensuring its safety and effectiveness under physiological conditions, and improving the credibility of the test results. Therefore, the fatigue wear test method of a cardiovascular implant proposed in the embodiment of the present invention can increase the credibility of the fatigue wear test results of the cardiovascular implant.

[0145] Reference Figure 2 FIG. 1 is a flow chart of a fatigue wear test method for a cardiovascular implant provided by an embodiment of the present invention. In this embodiment, the fatigue wear test method for a cardiovascular implant includes:

[0146] Acquire a cardiovascular implant to be tested and its corresponding treatment subject, schedule physiological data of the treatment subject, and identify patient group characteristics of the cardiovascular implant according to the treatment subject and the physiological data, and simulate an in vivo environment model of the treatment subject based on the patient group characteristics;

[0147] Identify biological tissue elements of the in vivo environment model, identify the daily activity patterns of the treatment subject based on the patient population characteristics, analyze the biomechanical properties of the biological tissue elements, set the physiological conditions of the in vivo environment model based on the biomechanical properties and the daily activity patterns, and simulate the working mechanism of the biological tissue elements under the physiological conditions;

[0148] According to the working mechanism, the cardiovascular implant is arranged in a mounting cavity of the in vivo environment model, a circulation channel of the in vivo environment model is arranged based on the mounting cavity, a fluid flow pattern of the circulation channel is analyzed, and the cardiorespiratory movement law of the treatment subject is identified according to the physiological data;

[0149] Based on the cardiac respiratory movement law, a cyclic load of the in vivo environment model is set, and a frequency range of the cyclic load is determined, blood parameters of the fluid flow pattern are extracted, and based on the cyclic load, a cyclic loading test of the cardiovascular implant in the in vivo environment model is set, and the operating state of the cardiovascular implant under the cyclic loading test is monitored in real time;

[0150] Based on the operating status, the fatigue life and the degree of wear of the cardiovascular implant are analyzed, and according to the fatigue life and the degree of wear, fatigue and wear test results of the cardiovascular implant in the in vivo environment model are generated.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A fatigue wear test system for cardiovascular implants, characterized in that: The fatigue wear test system of the cardiovascular implant comprises: an environment simulation module, a condition setting module, a cavity configuration module, a state monitoring module, and a result output module; The environmental simulation module is used to obtain the cardiovascular implant to be tested and its corresponding treatment object, schedule the physiological data of the treatment object, and identify the patient group characteristics of the cardiovascular implant according to the treatment object and the physiological data, and simulate the in vivo environmental model of the treatment object based on the patient group characteristics; The condition setting module is used to identify the biological tissue elements of the in vivo environment model, identify the daily activity patterns of the treatment object based on the patient group characteristics, analyze the biomechanical properties of the biological tissue elements, set the physiological conditions of the in vivo environment model based on the biomechanical properties and the daily activity patterns, and simulate the working mechanism of the biological tissue elements under the physiological conditions; The cavity configuration module is used to set the installation cavity of the cardiovascular implant in the in vivo environment model according to the working mechanism, set the circulation channel of the in vivo environment model based on the installation cavity, analyze the fluid flow pattern of the circulation channel, and identify the cardiorespiratory movement law of the treatment object according to the physiological data; The state monitoring module is used to set the cyclic load of the in vivo environment model based on the cardiac respiratory movement law, determine the frequency range of the cyclic load, extract the blood parameters of the fluid flow pattern, set the cyclic loading test of the cardiovascular implant in the in vivo environment model based on the cyclic load, the frequency range and the blood parameters, and monitor the operating state of the cardiovascular implant under the cyclic loading test in real time; The result output module is used to analyze the fatigue life and wear degree of the cardiovascular implant based on the operating state, and generate fatigue wear test results of the cardiovascular implant in the in vivo environment model according to the fatigue life and the wear degree.

2. A fatigue wear testing system for cardiovascular implants as claimed in claim 1, characterized in that: The step of identifying patient population characteristics of the cardiovascular implant according to the treatment object and the physiological data comprises: Analyzing physiological characteristics of the subject according to the physiological data; Extracting indicator elements from the physiological data and identifying abnormal factors of the indicator elements; Analyzing the lifestyle characteristics of the treatment subject based on the abnormal factors and the indicator elements; Analyzing the type of cardiovascular disease of the subject according to the abnormal factors; Based on the physiological characteristics, the lifestyle characteristics and the type of cardiovascular disease, identifying common frequency characteristics of the treatment subject; Based on the cluster centers, patient population characteristics of the cardiovascular implants are identified.

3. A fatigue wear testing system for cardiovascular implants as claimed in claim 1, characterized in that: The simulating the in vivo environment model of the treatment subject based on the patient population characteristics comprises: Analyzing the physiological status and cardiovascular function of the subject based on the patient population characteristics; constructing a cardiovascular model of the subject according to the physiological state and the cardiovascular function; Meshing the cardiovascular model to obtain a mesh model; Identifying organizational elements of the mesh model and setting material property definitions of the organizational elements; Based on the material property definition, setting boundary conditions of the mesh model; The in vivo environment model of the treatment subject is simulated according to the cardiovascular model and the boundary conditions.

4. A fatigue wear testing system for cardiovascular implants as claimed in claim 1, characterized in that: The step of setting the physiological conditions of the in vivo environment model based on the biomechanical characteristics and the daily activity pattern includes: scheduling biological tissue elements of the in vivo environment model based on the biomechanical properties; simulating a fluid pattern of the biological tissue element according to the biomechanical properties; Based on the daily activity pattern, setting the activity state of the in-vivo environment model; Analyzing the comprehensive performance of the biological tissue element in the in vivo environment model according to the biomechanical properties and the fluid pattern; The physiological conditions of the in vivo environment model are set in combination with the activity state and the comprehensive performance.

5. A fatigue wear testing system for cardiovascular implants as claimed in claim 1, characterized in that: The step of setting the activity state of the internal environment model based on the daily activity pattern includes: Based on the daily activity pattern, identifying active patients in the in-vivo environment simulation model; Calculating the coefficient of variation of the physical signs of the active patients according to the daily activity patterns; Extracting patient physical sign attributes under the physical sign variation coefficient; Analyze the changing trend of the patient's physical sign attributes under the daily activity pattern; Based on the patient's vital sign attributes and the change trend, the activity state of the in-vivo environment model is set.

6. A fatigue wear testing system for cardiovascular implants as claimed in claim 1, characterized in that: According to the working mechanism, setting the installation cavity of the cardiovascular implant in the in vivo environment model includes: identifying functional factors of the cardiovascular implant according to the working mechanism; analyzing an implant type of the cardiovascular implant; Determining the location and installation point of the cardiovascular implant based on the functional factor and the implant type; Based on the position installation point, a mounting cavity of the cardiovascular implant in the in vivo environment model is set.

7. A fatigue wear testing system for cardiovascular implants as claimed in claim 1, characterized in that: The step of setting a circulation channel of the in-vivo environment model based on the installation cavity comprises: Identifying an installation position of the installation cavity in the in vivo environment model; analyzing a blood flow path in the in-vivo environment model, and positioning a blood use pump of the in-vivo environment model according to the blood flow path; Setting a blood flow inlet of the in vivo environment model based on the blood usage pump; According to the installation position, setting a blood flow outlet of the in-vivo environment model; Based on the blood flow outlet and the blood flow inlet, a circulation flow channel of the in-vivo environment model is set.

8. A fatigue wear testing system for cardiovascular implants as claimed in claim 1, characterized in that: The step of setting a cyclic loading test of the cardiovascular plant in the in vivo environment model based on the cyclic load, the frequency range and the blood parameter comprises: Based on the cyclic load and the frequency range, obtaining a fatigue testing machine for the cardiovascular implant; Identifying a loading unit of the fatigue testing machine, and setting a load waveform of the loading unit according to the cyclic load; Based on the frequency range, setting the loading frequency of the loading unit; According to the blood parameter, setting the load amplitude of the loading unit; In combination with the loading frequency, the load amplitude and the load waveform, a cyclic loading test of the cardiovascular plant in the in vivo environment model is set.

9. A fatigue wear testing system for cardiovascular implants as claimed in claim 1, characterized in that: The analyzing the fatigue life and wear degree of the cardiovascular implant based on the operating state includes: identifying fatigue performance and fatigue strength of the cardiovascular implant under the operating condition; calculating the fatigue life of the cardiovascular implant based on the fatigue performance and the fatigue strength; analyzing stress and strain conditions of the cardiovascular implant according to the operating state; identifying material properties of the cardiovascular implant; The wear degree of the cardiovascular implant is analyzed according to the material properties and the stress-strain conditions.

10. A fatigue wear test method for cardiovascular implants, characterized in that: The method comprises: Acquire a cardiovascular implant to be tested and its corresponding treatment subject, schedule physiological data of the treatment subject, and identify patient group characteristics of the cardiovascular implant according to the treatment subject and the physiological data, and simulate an in vivo environment model of the treatment subject based on the patient group characteristics; Identify biological tissue elements of the in vivo environment model, identify the daily activity patterns of the treatment subject based on the patient population characteristics, analyze the biomechanical properties of the biological tissue elements, set the physiological conditions of the in vivo environment model based on the biomechanical properties and the daily activity patterns, and simulate the working mechanism of the biological tissue elements under the physiological conditions; According to the working mechanism, the cardiovascular implant is arranged in a mounting cavity of the in vivo environment model, a circulation channel of the in vivo environment model is arranged based on the mounting cavity, a fluid flow pattern of the circulation channel is analyzed, and the cardiorespiratory movement law of the treatment subject is identified according to the physiological data; Based on the cardiac respiratory movement law, a cyclic load of the in vivo environment model is set, and a frequency range of the cyclic load is determined, blood parameters of the fluid flow pattern are extracted, and based on the cyclic load, a cyclic loading test of the cardiovascular implant in the in vivo environment model is set, and the operating state of the cardiovascular implant under the cyclic loading test is monitored in real time; Based on the operating status, the fatigue life and the degree of wear of the cardiovascular implant are analyzed, and according to the fatigue life and the degree of wear, fatigue and wear test results of the cardiovascular implant in the in vivo environment model are generated.

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