Method for testing myocardial tissue bionic unit model

Abstract

The invention provides a test method of a myocardial tissue bionic unit model, and relates to the technical field of bionic model test. The method comprises the following steps: acquiring myocardial tissue measurement big data, and establishing a contraction performance-based myocardial tissue digital model according to a myocardial tissue bionic unit model; acquiring shrinkage performance parameters of the myocardial tissue bionic unit model, and performing shrinkage matching analysis in combination with the myocardial tissue digital model to form shrinkage matching verification information; obtaining mechanical property parameters of the myocardial tissue bionic unit model, and performing mechanical property matching analysis in combination with the myocardial tissue digital model to form mechanical matching verification information; and extracting electrocardio activity data in the myocardial tissue measurement big data, and forming electrocardio activity matching verification information in combination with the electrocardio activity information of the myocardial tissue bionic unit model. According to the method, verification tests in multiple aspects are carried out by using measurement big data of the myocardial tissue, so that the reliable working performance of the myocardial tissue bionic unit model is effectively ensured.

Description

Technical Field

[0001] The invention relates to the technical field of bionic model testing, and in particular to a testing method for a myocardial tissue bionic unit model. Background Art

[0002] With the advancement of medical technology, the treatment of heart diseases is becoming more and more advanced and comprehensive. In the case of myocardial damage that cannot be functionally restored, it is possible to provide a bionic replacement product that can achieve better myocardial function.

[0003] At present, the development of myocardial tissue bionic models is becoming more and more in-depth, and gradually a model structure that can completely replace the overall function of the myocardium has been produced, which provides the possibility for myocardial replacement. Considering the different movements of myocardial tissue under normal conditions, it is relatively difficult to achieve its motion performance, and how to verify the reliability and performance of the designed myocardial tissue bionic model has become an important difficulty in the current research and development of myocardial tissue bionic models.

[0004] Therefore, designing a test method for the myocardial tissue bionic unit model and using the measurement big data of myocardial tissue to conduct verification tests in multiple aspects to effectively ensure the reliability of the working performance of the myocardial tissue bionic unit model is an urgent problem to be solved. Summary of the invention

[0005] The purpose of the present invention is to provide a testing method for a myocardial tissue bionic unit model, by acquiring big data of myocardial tissue measurements to establish a digital model of myocardial tissue for comparative verification testing with the myocardial tissue bionic unit model, and by matching and verifying the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model to determine its performance and functionality in many aspects, thereby effectively ensuring the performance of the myocardial tissue bionic unit model, and also forming a systematic method for performance testing of the myocardial tissue bionic unit model, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model.

[0006] In a first aspect, the present invention provides a testing method for a myocardial tissue bionic unit model, comprising: obtaining myocardial tissue measurement big data, extracting myocardial tissue contraction performance test data and myocardial tissue scanning data, and establishing a myocardial tissue digital model based on contraction performance according to the myocardial tissue bionic unit model; obtaining contraction performance parameters of the myocardial tissue bionic unit model, and performing contractility matching analysis in combination with the myocardial tissue digital model to form contractility matching verification information; obtaining mechanical performance parameters of the myocardial tissue bionic unit model based on the contractility matching verification information, and performing mechanical performance matching analysis in combination with the myocardial tissue digital model to form mechanical matching verification information; extracting electrocardiographic activity data from the myocardial tissue measurement big data based on the mechanical matching verification information, and performing electrocardiographic activity matching analysis in combination with the electrocardiographic activity information of the myocardial tissue bionic unit model to form electrocardiographic activity matching verification information.

[0007] In the present invention, the method acquires big data of myocardial tissue measurements to establish a digital model of myocardial tissue for comparative verification testing with the myocardial tissue bionic unit model, and determines its performance and functionality in many aspects by matching and verifying the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model, thereby effectively ensuring the performance of the myocardial tissue bionic unit model. At the same time, a systematic method for performance testing of the myocardial tissue bionic unit model is formed, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model.

[0008] As a possible implementation method, myocardial tissue measurement big data is obtained, myocardial tissue contraction performance test data and myocardial tissue scanning data are extracted, and a myocardial tissue digital model based on contraction performance is established according to the myocardial tissue bionic unit model, including: establishing a basic digital model of myocardial tissue according to the myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model; performing feature extraction based on contraction performance according to the myocardial tissue contraction performance test data and in combination with the basic digital model of myocardial tissue to form model contraction performance characteristic data; using the model contraction performance characteristic data as a design indicator, adjusting the model performance of the basic digital model of myocardial tissue based on secondary development to establish a digital model of myocardial tissue.

[0009] In the present invention, a digital model of myocardial tissue that matches the myocardial tissue bionic unit model is established based on the big data of myocardial tissue measurements. Three aspects need to be considered. One is the basic data of the model. The basic data here is the basic information required to generate a digital model, such as size, structure and other information. Based on this information, a digital model can be quickly established. The other is the performance data of the model. Considering that the performance of cardiac tissue is mainly obtained through its motion information, this application mainly considers establishing the corresponding model characteristic performance by obtaining the contraction performance characteristic data.

[0010] As a possible implementation method, a basic digital model of myocardial tissue is established based on myocardial tissue scanning data and in combination with a myocardial tissue bionic unit model, including: collecting size contour information of the myocardial tissue bionic unit model to form size contour feature information of a target model; using the size contour feature information of the target model as a reference, extracting matching scanning information corresponding to myocardial tissue whose size contour information in the myocardial tissue scanning data matches the size contour feature information of the target model, and determining the matching myocardial tissue as the matching myocardial tissue; determining the average basic parameter value of different basic model parameters based on all matching scanning information; and combining the size contour feature information of the target model and different average basic parameter values ​​to form a basic digital model of myocardial tissue.

[0011] In the present invention, the basic digital model of myocardial tissue is mainly used to obtain the contour data of the size and structure of myocardial tissue in the measurement big data. What needs to be considered here is that since myocardial tissue is a biological tissue, there are certain individual differences, so the myocardial tissue bionic unit model must also have a range of use for different groups. Therefore, when establishing the basic digital model of myocardial tissue, it is necessary to consider the impact of individual differences on the measurement data to avoid the inaccurate impact of the data of the bionic unit model of myocardial tissue on the subsequent verification test results caused by the mismatch. The individual differences of myocardial tissue are mainly manifested in age. The size of myocardial tissue corresponding to individuals of different ages is different. Therefore, the size contour feature information required for establishing the basic digital model of myocardial tissue needs to be clustered and obtained with reference to the size contour feature information of the bionic unit model of myocardial tissue. This reference can be based on the size contour feature information of the bionic unit model of myocardial tissue to cover a certain range, or it can be the same set of single parameters. After determining the matching data, the size contour feature information of the myocardial tissue measurement data of different individuals in these clustered measurement big data can be extracted. Considering that the feature information has a certain volatility, the average value of different feature information is used as the input parameter for data model establishment to adapt well to the characteristics of the corresponding group. It should be noted that the size profile information can be obtained by providing scanning information in the measurement big data, such as X-ray, nuclear magnetic resonance, etc., and other important parameter information such as average density can also be obtained.

[0012] As a possible implementation method, based on the myocardial tissue contraction performance test data and in combination with the basic digital model of the myocardial tissue, feature extraction based on contraction performance is performed to form model contraction performance feature data, including: based on the myocardial tissue contraction performance test data, different relevant contraction parameter values ​​in all matching myocardial tissues are extracted, and different relevant contraction parameter values ​​are clustered to form different relevant contraction parameter sets; for different relevant contraction parameter sets, corresponding average relevant contraction parameter values ​​and relevant contraction parameter ranges are determined; different average relevant contraction parameter values ​​and corresponding relevant contraction parameter ranges are combined to form model contraction performance feature data.

[0013] In the present invention, the contractility of myocardial tissue can be measured by parameters such as the rate of change of ventricular pressure, the slope of the rise of arterial pressure, the ejection fraction, and the isovolumetric contraction period. Therefore, when the array model performance characteristics of the basic digital model of myocardial tissue are established based on the measurement of big data, the data of different contraction performance parameters can be used as input to establish it. It should be noted that contractility mainly reflects the operating state and situation of myocardial tissue during movement, and is a comprehensive indicator that reflects the operating performance of myocardial tissue. Therefore, the characteristics of the basic digital model are given based on contractility, which can basically ensure that the formed data model has a complete consideration of performance. In addition, the different contraction performance parameters obtained are more reasonable in the form of average values ​​due to the large amount of data, and the corresponding parameter range is also provided, which is used to consider the certain correlation between different contraction performance parameters during analysis, which leads to the adjustment of a single contraction performance parameter affecting the adjustment of other contraction performance parameters and provides a reasonable adjustment range reference.

[0014] As a possible implementation method, the model contraction performance characteristic data is used as the design indicator, and the model performance adjustment based on the secondary development of the basic digital model of myocardial tissue is performed to establish the digital model of myocardial tissue, including: for the basic digital model of myocardial tissue, different average related contraction parameter values ​​are used as the initial development and design targets, and different related contraction parameter ranges are used as the target allowable adjustment range, and the secondary development model performance adjustment is performed in the following manner: the basic digital model of myocardial tissue is secondary developed according to the initial development and design targets, and if the secondary development result matches all the average related contraction parameter values, the model formed by the secondary development is determined as the digital model of myocardial tissue; if the secondary development result does not match all the average related contraction parameter values, the unmatched average related contraction parameter values ​​are adjusted within the corresponding target allowable adjustment range, so that the secondary development result matches all the average related contraction parameter values, and the model formed by the secondary development is determined as the digital model of myocardial tissue.

[0015] In the present invention, when the digital model is endowed with functionality by the shrinkage performance parameters, the parameter data cannot be directly implemented under the original or initial digital software or model parameters, but needs to be implemented by secondary development of the shrinkage performance parameters using the digital software or model. This secondary development mainly establishes the relationship between the multiple adjustable basic parameters of the digital model and the shrinkage performance parameters, and then autonomously optimizes the design with the shrinkage performance parameters as the target. Since the correlation between the shrinkage performance itself will be reflected through the adjustable basic parameters, it is not necessarily reasonable to initially use the average value of different shrinkage performance parameters as input. Through the optimization process of secondary development, it can be determined whether the change of the adjustable basic parameters can match all the shrinkage performance parameters. If they cannot match all, they can be adjusted based on the allowed adjustment range.

[0016] As a possible implementation method, the contraction performance parameters of the myocardial tissue bionic unit model are obtained, and a contractility matching analysis is performed in combination with the myocardial tissue digital model to form contractility matching verification information, including: setting the contraction matching allowable deviation corresponding to different contraction performance parameters, and determining the bionic contraction performance parameter values ​​of the different contraction performance parameters of the myocardial tissue bionic unit model; obtaining the model contraction performance parameter values ​​corresponding to different contraction performance parameters in the myocardial tissue digital model, and performing the following matching analysis in combination with the different bionic contraction performance parameter values ​​corresponding to the myocardial tissue bionic unit model: if for all contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value does not exceed the corresponding contraction matching allowable deviation, then contractility matching verification pass information is formed; if for all contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value exceeds the corresponding contraction matching allowable deviation, then contractility matching verification failure information is formed.

[0017] In the present invention, the digital model of myocardial tissue determined through secondary development has contraction performance that matches big data, so that comparative data that can be matched with the bionic unit model of myocardial tissue is established for verification testing. The first thing to verify and test the bionic unit model of myocardial tissue is the contraction performance, so the contraction performance is a comprehensive manifestation and has a certain macroscopicity. This matching takes into account the certain differences between the digital model of myocardial tissue and the bionic unit model of myocardial tissue, so the comparative verification test is controlled by the allowable deviation, which can be set according to the actual situation, or determined based on big data analysis.

[0018] As a possible implementation method, the mechanical performance parameters of the myocardial tissue bionic unit model are obtained according to the contractility matching verification information, and a mechanical performance matching analysis is performed in combination with the myocardial tissue digital model to form mechanical matching verification information, including: when the contractility matching verification information is the contractility matching verification pass information, the bionic mechanical performance parameter values ​​corresponding to the different mechanical performance parameters of the myocardial tissue bionic unit model are collected; the model mechanical performance parameter values ​​corresponding to the different mechanical performance parameters of the myocardial tissue digital model are obtained, and a mechanical performance matching analysis is performed in combination with the bionic mechanical performance parameter values ​​corresponding to the different mechanical performance parameters of the myocardial tissue bionic unit model to form mechanical matching verification information.

[0019] In the present invention, the movement of myocardial tissue is a process of force change. Therefore, after the contractility matching verification is confirmed, in order to ensure that its performance meets the standard, it is important and necessary to perform matching analysis on the mechanical properties, which can reflect the characteristics of the myocardial tissue bionic unit model in terms of mechanical properties. Of course, the matching analysis is still performed with the data of each mechanical performance parameter of the digital model as the comparison object.

[0020] As a possible implementation method, the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the digital model of myocardial tissue are obtained, and the mechanical performance matching analysis is performed in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the bionic unit model of myocardial tissue to form mechanical matching verification information, including: determining the model mechanical comprehensive performance value corresponding to the digital model of myocardial tissue based on the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the digital model of myocardial tissue ,in: , n is the number of different mechanical properties parameters, is an important contributing factor to the mechanical property parameter value numbered n, is the model mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; for the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model, determine the bionic mechanical comprehensive performance value corresponding to the myocardial tissue bionic unit model ,in: , is the bionic mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; and bionic mechanics comprehensive performance value :like , then the mechanical matching verification information is formed; if , then the mechanical matching verification fails. Allowable offset for mechanical matching.

[0021] In the present invention, it should be noted that for the mechanical properties of the myocardial tissue bionic unit model, since there is an inherent connection between mechanical parameters, such as stress and strain, and the transmission of force flow also has regularity and correlation on different structures, the verification test of the mechanical properties is a comprehensive comparative analysis of the mechanical performance parameters under consideration. The important contribution factors are the embodiment of the importance of different mechanical performance parameters in the verification test or in the myocardial tissue on the movement of myocardial tissue. They can be set according to actual conditions or determined based on big data analysis. The allowable deviation is to provide a reasonable verification test range after comprehensive consideration of the differences. It can be set according to actual conditions or determined based on big data analysis.

[0022] As a possible implementation method, based on the mechanical matching verification information, the ECG activity data in the myocardial tissue measurement big data is extracted, and combined with the ECG activity information of the myocardial tissue bionic unit model, the ECG activity matching analysis is performed to form the ECG activity matching verification information, including: when the mechanical matching verification information is the mechanical matching verification pass information, then the ECG measurement change function within the analysis period is formed according to the ECG activity data According to the ECG activity information of the myocardial tissue bionic unit model, the bionic ECG change function corresponding to the myocardial tissue bionic unit model during the analysis period is determined. ; According to the ECG measurement change function and bionic ECG function , perform ECG activity matching analysis and form ECG activity matching verification information.

[0023] In the present invention, the movement of myocardial tissue is mainly displayed through ECG data information. The contractility and mechanics verification tests basically determine that the bionic unit model of myocardial tissue has performance and functional integrity, while the continuous reliability of its movement work needs to be determined separately. By comparing and analyzing the digital model and the ECG data of the measured big data over a certain period of time, the verification test of the movement reliability can be accurately performed.

[0024] As a possible implementation method, according to the ECG measurement change function and bionic ECG function , perform ECG activity matching analysis to form ECG activity matching verification information, including: ECG measurement change function and bionic ECG function :If both , , then the ECG activity matching verification information is formed, is the permissible ECG variation deviation per unit time, W is the cumulative permissible ECG variation deviation, Indicates that it will obtain The maximum difference corresponding to all time points in the analysis period, T is the duration of the analysis period; if not satisfied at the same time , , then the information of ECG activity matching verification failure is generated.

[0025] In the present invention, for the reliability verification test based on ECG activity data, two aspects are mainly considered. One is the fluctuation difference of ECG data at each time point, which reflects whether the transient stability meets the requirements. The other is whether the cumulative difference in the total observation time, that is, the analysis period, exceeds the allowable amount, which reflects the cumulative effect of stability. Only when both requirements are met can it be determined that the myocardial tissue bionic unit model is reliable.

[0026] The testing method of the myocardial tissue bionic unit model provided by the present invention has the following beneficial effects: This method obtains big data of myocardial tissue measurements to establish a digital myocardial tissue model for comparative verification testing with the myocardial tissue bionic unit model, and determines its performance and functionality in many aspects through matching and verification of the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model, effectively ensuring the performance of the myocardial tissue bionic unit model, and also forming a systematic method for performance testing of the myocardial tissue bionic unit model, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 A step diagram of a method for testing a myocardial tissue bionic unit model provided by an embodiment of the present invention; Figure 2 A schematic structural diagram of a testing system for a myocardial tissue bionic unit model provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present invention will be described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0030] With the advancement of medical technology, the treatment of heart diseases is becoming more and more advanced and comprehensive. In the case of myocardial damage that cannot be functionally restored, it is possible to provide a bionic replacement product that can achieve better myocardial function.

[0031] At present, the development of myocardial tissue bionic models is becoming more and more in-depth, and gradually a model structure that can completely replace the overall function of the myocardium has been produced, which provides the possibility for myocardial replacement. Considering the different movements of myocardial tissue under normal conditions, it is relatively difficult to achieve its motion performance, and how to verify the reliability and performance of the designed myocardial tissue bionic model has become an important difficulty in the current research and development of myocardial tissue bionic models.

[0032] refer to Figure 1~Figure 2 The embodiment of the present invention provides a testing method for a myocardial tissue bionic unit model. The method establishes a myocardial tissue digital model for comparative verification testing with the myocardial tissue bionic unit model by acquiring myocardial tissue measurement big data, and determines its performance and function in many aspects through matching and verification of the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model, thereby effectively ensuring the performance of the myocardial tissue bionic unit model. At the same time, a systematic method for performance testing of the myocardial tissue bionic unit model is formed, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model.

[0033] The testing method of the myocardial tissue bionic unit model specifically includes the following steps: S1: Obtain big data on myocardial tissue measurement, extract myocardial tissue contraction performance test data and myocardial tissue scanning data, and establish a digital model of myocardial tissue based on contraction performance according to the myocardial tissue bionic unit model.

[0034] Acquire big data of myocardial tissue measurement, extract myocardial tissue contraction performance test data and myocardial tissue scanning data, and establish a myocardial tissue digital model based on contraction performance according to the myocardial tissue bionic unit model, including: establishing a basic digital model of myocardial tissue according to the myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model; extracting features based on contraction performance according to the myocardial tissue contraction performance test data and in combination with the basic digital model of myocardial tissue to form model contraction performance characteristic data; using the model contraction performance characteristic data as a design indicator, adjusting the model performance of the basic digital model of myocardial tissue based on secondary development to establish a digital model of myocardial tissue.

[0035] In order to establish a digital model of myocardial tissue that matches the myocardial tissue bionic unit model based on the big data of myocardial tissue measurements, three aspects need to be considered. One is the basic data of the model. The basic data here is the basic information required to generate a digital model, such as size, structure and other information. Based on this information, a digital model can be quickly established. The other is the performance data of the model. Considering that the performance of cardiac tissue is mainly obtained through its motion information, this application mainly considers establishing the corresponding model characteristic performance by obtaining the contraction performance characteristic data.

[0036] According to the myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model, a basic digital model of myocardial tissue is established, including: collecting the size contour information of the myocardial tissue bionic unit model to form the size contour feature information of the target model; taking the size contour feature information of the target model as a reference, extracting the matching scanning information corresponding to the myocardial tissue whose size contour information in the myocardial tissue scanning data matches the size contour feature information of the target model, and determining the matching myocardial tissue as the matching myocardial tissue; determining the average basic parameter value of different basic model parameters according to all matching scanning information; and combining the size contour feature information of the target model and the different average basic parameter values ​​to form the basic digital model of myocardial tissue.

[0037] The basic digital model of myocardial tissue mainly obtains the contour data of the size and structure of myocardial tissue in the measurement big data. What needs to be considered here is that since myocardial tissue is a biological tissue, there are certain individual differences. Therefore, the myocardial tissue bionic unit model must also have a range of use for different groups. Therefore, when establishing the basic digital model of myocardial tissue, it is necessary to consider the impact of individual differences on the measurement data to avoid the inaccurate impact of the data that does not match the myocardial tissue bionic unit model on the subsequent verification test results. The individual differences of myocardial tissue are mainly manifested in age. The size of myocardial tissue corresponding to individuals of different ages is different. Therefore, the size contour feature information required to establish the basic digital model of myocardial tissue needs to be clustered and obtained with reference to the size contour feature information of the myocardial tissue bionic unit model. This reference can be based on the size contour feature information of the myocardial tissue bionic unit model to include a certain range, or it can be the same set of single parameters. After determining the matching data, the size contour feature information of the myocardial tissue measurement data of different individuals in these clustered measurement big data can be extracted. Considering that the feature information has a certain volatility, the average value of different feature information is used as the input parameter for data model establishment to adapt well to the characteristics of the corresponding group. It should be noted that the size profile information can be obtained by providing scanning information in the measurement big data, such as X-ray, nuclear magnetic resonance, etc., and other important parameter information such as average density can also be obtained.

[0038] According to the myocardial tissue contraction performance test data and in combination with the basic digital model of myocardial tissue, feature extraction based on contraction performance is performed to form model contraction performance feature data, including: according to the myocardial tissue contraction performance test data, different relevant contraction parameter values ​​in all matching myocardial tissues are extracted, and different relevant contraction parameter values ​​are clustered to form different relevant contraction parameter sets; for different relevant contraction parameter sets, corresponding average relevant contraction parameter values ​​and relevant contraction parameter ranges are determined; different average relevant contraction parameter values ​​and corresponding relevant contraction parameter ranges are combined to form model contraction performance feature data.

[0039] The contractility of myocardial tissue can be measured by parameters such as the rate of change of ventricular pressure, the slope of arterial pressure rise, the ejection fraction, and the isovolumetric contraction period. Therefore, when establishing the array model performance characteristics of the basic digital model of myocardial tissue based on the measurement big data, the data of different contraction performance parameters can be used as input to establish it. It should be noted that contractility mainly reflects the operating state and situation of myocardial tissue during movement, and is a comprehensive indicator reflecting the operating performance of myocardial tissue. Therefore, the characteristics of the basic digital model are given based on contractility, which can basically ensure that the formed data model has a complete consideration of performance. In addition, due to the large amount of data, the different contraction performance parameters obtained are more reasonably expressed in the form of average values, and the corresponding parameter range is also provided. It is used to consider the relationship between different contraction performance parameters during analysis, which leads to the adjustment of a single contraction performance parameter affecting the adjustment of other contraction performance parameters and provides a reasonable adjustment range reference.

[0040] Taking the model contraction performance characteristic data as the design index, the model performance adjustment based on secondary development is performed on the basic digital model of myocardial tissue to establish the digital model of myocardial tissue, including: taking different average relevant contraction parameter values ​​as the initial development and design targets, taking different relevant contraction parameter ranges as the target allowable adjustment ranges, and performing the following secondary development model performance adjustment: according to the initial development and design targets, the basic digital model of myocardial tissue is secondary developed, and if the secondary development result matches all the average relevant contraction parameter values, the model formed by the secondary development is determined as the digital model of myocardial tissue; if the secondary development result does not match all the average relevant contraction parameter values, the unmatched average relevant contraction parameter values ​​are adjusted within the corresponding target allowable adjustment range, so that the secondary development result matches all the average relevant contraction parameter values, and the model formed by the secondary development is determined as the digital model of myocardial tissue.

[0041] When the digital model is given functionality by shrinkage performance parameters, the parameter data cannot be directly implemented under the original or initial digital software or model parameters, but it is necessary to use the digital software or model for secondary development of shrinkage performance parameters. This secondary development mainly establishes the relationship between multiple adjustable basic parameters of the digital model and the shrinkage performance parameters, and then autonomously optimizes the design with the shrinkage performance parameters as the target. Since the correlation between the shrinkage performance itself will be reflected through the adjustable basic parameters, it may not be reasonable to initially use the average value of different shrinkage performance parameters as input. Through the optimization process of secondary development, it can be determined whether the change of the adjustable basic parameters can match all the shrinkage performance parameters. If not, it can be adjusted based on the allowed adjustment range.

[0042] S2: Obtain the contractile performance parameters of the myocardial tissue bionic unit model, and perform contractile matching analysis in combination with the myocardial tissue digital model to form contractile matching verification information.

[0043] The contraction performance parameters of the myocardial tissue bionic unit model are obtained, and contractility matching analysis is performed in combination with the myocardial tissue digital model to form contractility matching verification information, including: setting the contraction matching allowable deviation corresponding to different contraction performance parameters, and determining the bionic contraction performance parameter values ​​of the different contraction performance parameters of the myocardial tissue bionic unit model; obtaining the model contraction performance parameter values ​​corresponding to different contraction performance parameters in the myocardial tissue digital model, and performing the following matching analysis in combination with the different bionic contraction performance parameter values ​​corresponding to the myocardial tissue bionic unit model: if for all contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value does not exceed the corresponding contraction matching allowable deviation, then contractility matching verification pass information is formed; if for all contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value exceeds the corresponding contraction matching allowable deviation, then contractility matching verification failure information is formed.

[0044] The digital model of myocardial tissue determined through secondary development has contraction performance that matches big data, so comparative data that can be matched with the myocardial tissue bionic unit model is established. The first thing to verify and test the myocardial tissue bionic unit model is the contraction performance, so the contraction performance is a comprehensive manifestation and has a certain macroscopicity. This matching takes into account the certain differences between the digital model of myocardial tissue and the myocardial tissue bionic unit model, so the comparative verification test is controlled by the allowable deviation, which can be set according to the actual situation or determined based on big data analysis.

[0045] S3: According to the contractility matching verification information, the mechanical performance parameters of the myocardial tissue bionic unit model are obtained, and the mechanical performance matching analysis is performed in combination with the myocardial tissue digital model to form mechanical matching verification information.

[0046] According to the contractility matching verification information, the mechanical performance parameters of the myocardial tissue bionic unit model are obtained, and a mechanical performance matching analysis is performed in combination with the myocardial tissue digital model to form mechanical matching verification information, including: when the contractility matching verification information is contractility matching verification pass information, the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model are collected; the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model are obtained, and a mechanical performance matching analysis is performed in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form mechanical matching verification information.

[0047] The movement of myocardial tissue is a process of force change. Therefore, after the contractility matching verification is confirmed, in order to ensure that its performance meets the standard, it is important and necessary to conduct a matching analysis of the mechanical properties, which can reflect the characteristics of the myocardial tissue bionic unit model in terms of mechanical properties. Of course, the matching analysis is still carried out based on the data of each mechanical performance parameter of the digital model as the comparison object.

[0048] Obtain the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the digital model of myocardial tissue, and perform mechanical performance matching analysis in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the bionic unit model of myocardial tissue to form mechanical matching verification information, including: determining the model mechanical comprehensive performance value corresponding to the digital model of myocardial tissue based on the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the digital model of myocardial tissue ,in: , n is the number of different mechanical properties parameters, is an important contributing factor to the mechanical property parameter value numbered n, is the model mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; for the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model, determine the bionic mechanical comprehensive performance value corresponding to the myocardial tissue bionic unit model ,in: , is the bionic mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; and bionic mechanics comprehensive performance value :like , then the mechanical matching verification information is formed; if , then the mechanical matching verification fails. Allowable offset for mechanical matching.

[0049] It should be noted that for the mechanical properties of the myocardial tissue bionic unit model, since there is an inherent connection between mechanical parameters, such as stress and strain, and the transmission of force flow also has regularity and correlation with different structures, the verification test of mechanical properties is a comprehensive comparative analysis of the mechanical performance parameters under consideration. The important contribution factors are the reflection of the importance of different mechanical performance parameters in the verification test or in the myocardial tissue on the movement of myocardial tissue. They can be set according to actual conditions or determined based on big data analysis. The allowable deviation is to provide a reasonable verification test range after comprehensive consideration of differences. It can be set according to actual conditions or determined based on big data analysis.

[0050] S4: Based on the mechanical matching verification information, the ECG activity data in the myocardial tissue measurement big data is extracted, and the ECG activity matching analysis is performed in combination with the ECG activity information of the myocardial tissue bionic unit model to form the ECG activity matching verification information.

[0051] According to the mechanical matching verification information, the ECG activity data in the myocardial tissue measurement big data is extracted, and the ECG activity matching analysis is performed in combination with the ECG activity information of the myocardial tissue bionic unit model to form the ECG activity matching verification information, including: when the mechanical matching verification information is the mechanical matching verification pass information, the ECG measurement change function within the analysis period is formed according to the ECG activity data According to the ECG activity information of the myocardial tissue bionic unit model, the bionic ECG change function corresponding to the myocardial tissue bionic unit model during the analysis period is determined. ; According to the ECG measurement change function and bionic ECG function , perform ECG activity matching analysis and form ECG activity matching verification information.

[0052] The movement of myocardial tissue is mainly displayed through ECG data information. The verification tests of contractility and mechanics basically confirm that the bionic unit model of myocardial tissue has performance and functional integrity, while the continuous reliability of its movement work needs to be determined separately. By comparing and analyzing the digital model and the ECG data of the measured big data over a certain period of time, the verification test of movement reliability can be accurately performed.

[0053] According to the ECG measurement function and bionic ECG function , perform ECG activity matching analysis to form ECG activity matching verification information, including: ECG measurement change function and bionic ECG function :If both meet , , then the ECG activity matching verification information is formed, is the permissible ECG variation deviation per unit time, W is the cumulative permissible ECG variation deviation, Indicates that it will obtain The maximum difference corresponding to all time points in the analysis period, is the duration of the analysis cycle; if not met at the same time , , then the information of ECG activity matching verification failure is generated.

[0054] For the reliability verification test based on ECG activity data, two aspects are mainly considered. One is the fluctuation difference of ECG data at each time point, which reflects whether the transient stability meets the requirements. The other is whether the cumulative difference in the total observation time, that is, the analysis period, exceeds the allowable amount, which reflects the cumulative effect of stability. Only when both requirements are met can it be determined that the myocardial tissue bionic unit model is reliable.

[0055] The present invention also provides a testing system for a myocardial tissue bionic unit model, the system comprising: a data acquisition unit, used to obtain big data on myocardial tissue measurements; a modeling unit, used to obtain the big data on myocardial tissue measurements obtained by the data acquisition unit, and establish a digital model of myocardial tissue in combination with the myocardial tissue bionic unit model; a verification and analysis unit, used to perform matching verification and analysis on contractility, mechanics and electrocardiographic activity data based on the digital model of myocardial tissue established by the modeling unit and in combination with the myocardial tissue bionic unit model, to form corresponding matching verification information.

[0056] In summary, the testing method of the myocardial tissue bionic unit model provided by the embodiment of the present invention has the following beneficial effects: This method obtains big data of myocardial tissue measurements to establish a digital myocardial tissue model for comparative verification testing with the myocardial tissue bionic unit model, and determines its performance and functionality in many aspects through matching and verification of the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model, effectively ensuring the performance of the myocardial tissue bionic unit model, and also forming a systematic method for performance testing of the myocardial tissue bionic unit model, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model.

[0057] In the embodiments of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein there is an association between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each piece of information agreed in advance (for example, specified by the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0058] In addition, the specific indication method may also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can refer to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, different indication methods may be used for different information. In the specific implementation process, the desired indication method can be selected according to specific needs. The embodiment of the present application does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0059] It should be understood that the information to be indicated can be sent as a whole, or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiment of the present application. Among them, the sending period and / or sending time of these sub-information can be pre-defined, for example, pre-defined according to a protocol, or can be configured by the sending end device by sending configuration information to the receiving end device.

[0060] "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in the device, and the embodiments of the present application do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately or integrated in an encoder or decoder, a processor, or a communication device. The one or more memories can also be partially set separately and partially integrated in a decoder, a processor, or a communication device. The type of memory can be any form of storage medium, which is not limited by the embodiments of the present application.

[0061] The "protocol" involved in the embodiments of the present application may refer to a protocol family in the communication field, a standard protocol with a similar protocol family frame structure, or a related protocol used in future communication systems, and the embodiments of the present application do not make specific limitations on this.

[0062] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device will make corresponding processing under certain objective circumstances. It does not limit the time, nor does it require the device to have a judgment action when implementing it, nor does it mean that there are other limitations.

[0063] In the description of the embodiments of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship. For example, A / B can represent A or B; "and / or" in the embodiments of the present application is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. These three situations, where A and B can be singular or plural. In addition, in the description of the embodiments of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solution of the embodiments of the present application, in the embodiments of the present application, the words "first" and "second" are used to distinguish the same or similar items with basically the same functions and effects. Those skilled in the art will appreciate that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0064] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0065] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0066] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0067] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0068] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0069] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0070] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0071] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0072] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0073] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0074] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0075] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0076] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for testing a myocardial tissue bionic unit model, characterized in that: include: Obtain big data on myocardial tissue measurements, extract myocardial tissue contraction performance test data and myocardial tissue scanning data, and establish a digital model of myocardial tissue based on contraction performance according to the myocardial tissue bionic unit model; Acquiring the contraction performance parameters of the myocardial tissue bionic unit model, and performing contractility matching analysis in combination with the myocardial tissue digital model to form contractility matching verification information; According to the contractility matching verification information, the mechanical performance parameters of the myocardial tissue bionic unit model are obtained, and a mechanical performance matching analysis is performed in combination with the myocardial tissue digital model to form mechanical matching verification information; According to the mechanical matching verification information, the electrocardiographic activity data in the myocardial tissue measurement big data is extracted, and combined with the electrocardiographic activity information of the myocardial tissue bionic unit model, an electrocardiographic activity matching analysis is performed to form the electrocardiographic activity matching verification information.

2. The method for testing the myocardial tissue bionic unit model according to claim 1, characterized in that: The method of obtaining the myocardial tissue measurement big data, extracting the myocardial tissue contraction performance test data and the myocardial tissue scanning data, and establishing a myocardial tissue digital model based on contraction performance according to the myocardial tissue bionic unit model includes: Establishing a basic digital model of myocardial tissue according to the myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model; According to the myocardial tissue contraction performance test data and in combination with the myocardial tissue basic digital model, feature extraction based on contraction performance is performed to form model contraction performance feature data; The contraction performance characteristic data of the model is used as a design indicator, the model performance of the basic digital model of myocardial tissue is adjusted based on secondary development, and the digital model of myocardial tissue is established.

3. The method for testing the myocardial tissue bionic unit model according to claim 2, characterized in that: The step of establishing a basic digital model of myocardial tissue based on the myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model comprises: Collecting the size profile information of the myocardial tissue bionic unit model to form size profile feature information of the target model; Taking the target model size contour feature information as a reference, extracting matching scan information corresponding to the myocardial tissue whose size contour information in the myocardial tissue scan data matches the target model size contour feature information, and determining the matching myocardial tissue as the matching myocardial tissue; Determining average basic parameter values ​​of different basic model parameters based on all the matching scan information; The target model size contour feature information and the different average basic parameter values ​​are collected to form the myocardial tissue basic digital model.

4. The method for testing the myocardial tissue bionic unit model according to claim 3, characterized in that: The method of extracting features based on contraction performance according to the myocardial tissue contraction performance test data and combining the myocardial tissue basic digital model to form model contraction performance feature data includes: According to the myocardial tissue contractility test data, extracting different relevant contractility parameter values ​​in all the matching myocardial tissues, and clustering the different relevant contractility parameter values ​​to form different relevant contractility parameter sets; For different sets of the relevant shrinkage parameters, determining corresponding average relevant shrinkage parameter values ​​and relevant shrinkage parameter ranges; Different average relevant shrinkage parameter values ​​and corresponding relevant shrinkage parameter ranges are collected to form the model shrinkage performance characteristic data.

5. The method for testing the myocardial tissue bionic unit model according to claim 4, characterized in that: The method of using the model contraction performance characteristic data as a design indicator, adjusting the model performance of the basic digital model of myocardial tissue based on secondary development, and establishing the digital model of myocardial tissue includes: For the myocardial tissue basic digital model, with different average related contraction parameter values ​​as initial development design targets and different related contraction parameter ranges as target allowable adjustment ranges, secondary development model performance adjustment is performed in the following manner: Performing secondary development on the basic digital model of myocardial tissue according to the initial development design goal, and if the secondary development result matches all the average relevant contraction parameter values, determining the model formed by the secondary development as the digital model of myocardial tissue; If the secondary development result does not match all the average related contraction parameter values, the unmatched average related contraction parameter values ​​are adjusted within the allowable adjustment range of the corresponding target so that the secondary development result matches all the average related contraction parameter values, and the model formed by the secondary development is determined as the digital model of myocardial tissue.

6. The method for testing the myocardial tissue bionic unit model according to claim 5, characterized in that: The step of acquiring the contraction performance parameters of the myocardial tissue bionic unit model and performing contractility matching analysis in combination with the myocardial tissue digital model to form contractility matching verification information includes: Setting the contraction matching allowable deviations corresponding to different contraction performance parameters, and determining the bionic contraction performance parameter values ​​of the myocardial tissue bionic unit model for different contraction performance parameters; The model contraction performance parameter values ​​corresponding to different contraction performance parameters in the myocardial tissue digital model are obtained, and the following matching analysis is performed in combination with the different bionic contraction performance parameter values ​​corresponding to the myocardial tissue bionic unit model: If for all the contraction performance parameters, if the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value does not exceed the corresponding contraction matching allowable deviation, then contraction matching verification pass information is generated; If for all the contraction performance parameters, if the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value exceeds the corresponding contraction matching allowable deviation, a contraction matching verification failure information is generated.

7. The method for testing the myocardial tissue bionic unit model according to claim 6, characterized in that: The step of obtaining the mechanical performance parameters of the myocardial tissue bionic unit model according to the contractility matching verification information, and performing mechanical performance matching analysis in combination with the myocardial tissue digital model to form mechanical matching verification information includes: When the contractility matching verification information is the contractility matching verification pass information, then collecting bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model; The model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model are obtained, and the mechanical performance matching analysis is performed in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form the mechanical matching verification information.

8. The method for testing the myocardial tissue bionic unit model according to claim 7, characterized in that: The obtaining of model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model, and performing mechanical performance matching analysis in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form the mechanical matching verification information includes: The model mechanical comprehensive performance value corresponding to the myocardial tissue digital model is determined by the model mechanical performance parameter values ​​corresponding to the different mechanical performance parameters of the myocardial tissue digital model. ,in: , n is the number of different mechanical property parameters, is an important contributing factor to the mechanical property parameter value numbered n, is the model mechanical property parameter value corresponding to the mechanical property parameter numbered n; The bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model are used to determine the bionic mechanical comprehensive performance value corresponding to the myocardial tissue bionic unit model. ,in: , is the bionic mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; The comprehensive mechanical performance value of the model And the bionic mechanical comprehensive performance value : like , then the mechanical matching verification pass information is formed; like , then the mechanical matching verification fails. Allowable deviation for mechanical matching.

9. The method for testing the myocardial tissue bionic unit model according to claim 8, characterized in that: The method of extracting the electrocardiographic activity data from the myocardial tissue measurement big data according to the mechanical matching verification information, and performing electrocardiographic activity matching analysis in combination with the electrocardiographic activity information of the myocardial tissue bionic unit model to form electrocardiographic activity matching verification information includes: When the mechanical matching verification information is the mechanical matching verification pass information, an electrocardiogram measurement change function within the analysis period is formed according to the electrocardiogram activity data. ; According to the electrocardiographic activity information of the myocardial tissue bionic unit model, the bionic electrocardiographic change function corresponding to the myocardial tissue bionic unit model in the analysis period is determined. ; According to the electrocardiographic measurement variation function and the bionic ECG variation function , perform ECG activity matching analysis to form the ECG activity matching verification information.

10. The method for testing the myocardial tissue bionic unit model according to claim 9, characterized in that: The electrocardiogram measurement variation function and the bionic ECG variation function , performing ECG activity matching analysis to form the ECG activity matching verification information, including: The ECG measurement variation function and the bionic ECG variation function : If both meet , , then the ECG activity matching verification information is formed, is the permissible ECG variation deviation per unit time, W is the cumulative permissible ECG variation deviation, Indicates that it will obtain The maximum difference corresponding to all time points in the analysis period, T is the duration of the analysis period; if not satisfied at the same time , , then the information of ECG activity matching verification failure is generated.

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