Mixed reality-based simulated medical visualization system, method and device

Abstract

The present invention discloses a simulated medical visualization system, method and equipment based on mixed reality, which belongs to the field of medical testing technology. The system and method include: establishing the internal organ structure of a virtual patient according to the size information of a simulated person, positioning and overlapping the internal organs of the virtual patient with the internal organs of the simulated person, and establishing data communication between the virtual patient and the simulated person; transmitting cardiopulmonary compression data to a computer host, visually displaying the cardiopulmonary compression data, and synchronously transmitting it to a control end and a display end; obtaining a modeling image evaluation value according to modeling image data processing, obtaining a modeling performance index according to modeling performance data processing, obtaining a modeling state evaluation value through comprehensive analysis, and obtaining an allowable deviation cardiopulmonary compression quality evaluation value according to matching of the modeling state evaluation value; analyzing the cardiopulmonary compression data to obtain a cardiopulmonary compression quality evaluation value, and specifying training content according to the cardiopulmonary compression quality evaluation value.

Description

Technical Field

[0001] The present invention relates to the field of medical testing technology, and in particular to a simulated medical visualization system, method and device based on mixed reality. Background Art

[0002] The simulated medical visualization system based on mixed reality is developed with the support of mixed reality technology, medical imaging technology, high-performance computing and graphics rendering technology to meet the needs of digital transformation of the medical industry, precision medicine and medical education.

[0003] Existing simulated medical visualization systems use computer graphics, image processing technology, virtual reality and extended reality technology to achieve functions such as three-dimensional reconstruction, registration, segmentation, interactive operation and data analysis, providing strong support for clinical diagnosis, medical education and medical research.

[0004] For example, the invention patent announcement with announcement number: CN109470822B discloses a testing device and evaluation method for the occluding performance of large artery trauma hemostatic materials and devices, including: adjusting pressure and flow rate to quantitatively control and simulate bleeding from blood vessels in different parts of the human body and bleeding from wounds of different degrees, and making qualitative and quantitative evaluations on the occluding pressure and maximum occluding pressure of the hemostatic material, the quality of the hemostatic material, the occluding efficiency of the hemostatic material, the occluding time, the occluding time, etc., and conducting scientific testing and evaluation. The evaluation content meets the requirements for hemostatic materials in clinical medicine and emergency medicine, and provides a reliable and practical method for evaluating the occluding performance of hemostatic materials, and also provides a basis for developing hemostatic materials with occluding performance.

[0005] For example, the invention patent with announcement number: CN112213502B announces a dual-level quality control material for reproductive medicine sex hormone detection based on clinical samples and its preparation and operation method, including: the dual-level quality control material for sex hormone detection includes a low-level quality control material and a high-level quality control material, which can be prepared by regulating the levels of various sex hormones using blood samples of clinical patients. The preparation method is simple to operate and low in cost; and the dual-level quality control material for sex hormone detection can completely simulate the matrix effect in the serum of different patient populations, and the results are more accurate. It is superior to traditional methods and is suitable for evaluating the quality control of the medically determined levels of sex hormones in the reproductive department, and can better express clinical needs.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] The medical visualization systems in the existing technology are unable to simulate the complexity and uncertainty of real scenes, resulting in insufficient experience for medical students in practical operations and emergency response, and unsatisfactory teaching results. Summary of the invention

[0008] The embodiments of the present application provide a simulated medical visualization system, method and equipment based on mixed reality, thereby solving the problem that the medical visualization system in the prior art cannot simulate the complexity and uncertainty of real scenes, resulting in insufficient experience of medical students in actual operation and emergency response, and unsatisfactory teaching results, thereby enhancing the practical operation ability and emergency response ability of medical students.

[0009] The embodiment of the present application provides a simulated medical visualization system, method and device based on mixed reality, including: a data connection module, a system adjustment module, a data display module, a data statistics module and a simulated medical database; wherein the data connection module is used to collect the size information and data parameters of the simulated person, establish the internal organ structure of the virtual patient according to the size information of the simulated person, and overlap the internal organs of the virtual patient with the internal organs of the simulated person, and establish data communication between the virtual patient and the simulated person according to the data parameters of the simulated person; the data display module is used to collect the cardiopulmonary compression data of the simulated person, and transmit the cardiopulmonary compression data to a computer host, visualize the cardiopulmonary compression data, and synchronously transmit it to the control end and the display end; the system adjustment module is used to obtain modeling performance data and modeling image data, obtain a modeling image evaluation value according to the modeling image data processing, obtain a modeling performance index according to the modeling performance data processing, obtain a modeling state evaluation value by comprehensive analysis, and obtain a cardiopulmonary compression quality evaluation value with an allowable deviation according to the matching of the modeling state evaluation value; the data statistics module is used to analyze the cardiopulmonary compression data to obtain a cardiopulmonary compression quality evaluation value, and specify training content according to the cardiopulmonary compression quality evaluation value.

[0010] Furthermore, the step of obtaining a modeling image evaluation value based on modeling image data processing includes: the modeling image data includes frame rate, resolution and delay; obtaining a critical frame rate, reference resolution, allowable deviation resolution and critical delay from a simulation medical database; and obtaining a modeling image evaluation value through comprehensive analysis.

[0011] Furthermore, the step of obtaining a modeling performance index based on modeling performance data processing includes: the modeling performance data includes position tracking deviation values ​​and volume tracking deviation values ​​at each time monitoring point; obtaining critical position tracking deviation values ​​and critical volume tracking deviation values ​​from a simulation medical database; and obtaining a modeling performance index through comprehensive analysis.

[0012] Furthermore, the step of comprehensively analyzing to obtain a modeling status evaluation value includes: obtaining a critical modeling image evaluation value and a critical modeling performance index from a simulated medical database; and comprehensively analyzing the modeling image evaluation value, the modeling performance index, the critical modeling image evaluation value and the critical modeling performance index to obtain a modeling status evaluation value.

[0013] Furthermore, the step of obtaining the allowable deviation cardiopulmonary compression quality assessment value according to the matching of the modeling state assessment value includes: matching the modeling state assessment value with the allowable deviation cardiopulmonary compression quality assessment value corresponding to each modeling state assessment value interval preset in the simulation medicine database to obtain the allowable deviation cardiopulmonary compression quality assessment value.

[0014] Furthermore, the step of analyzing the cardiopulmonary compression data to obtain a cardiopulmonary compression quality assessment value includes: the cardiopulmonary compression data includes compression depth, compression frequency, blowing volume and blowing frequency; obtaining a reference compression depth, an allowable deviation compression depth, a reference compression frequency, an allowable deviation compression frequency, a reference blowing volume, an allowable deviation blowing volume, a reference blowing frequency and an allowable deviation blowing frequency from a simulated medical database; and comprehensively analyzing to obtain a cardiopulmonary compression quality assessment value.

[0015] Furthermore, the cardiopulmonary compression quality assessment value is obtained as follows:

[0016] ;

[0017] In the formula, Indicates the cardiopulmonary compression quality assessment value. Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to compression depth, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to compression frequency, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to the blowing volume, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to the blowing frequency, Indicates the compression depth. Indicates the reference compression depth, Indicates the allowable deviation pressing depth, Indicates the compression frequency, Indicates the reference compression frequency, Indicates the allowable deviation pressing frequency, Indicates the blowing volume. Indicates the reference blowing volume, Indicates the allowable deviation of the blowing volume. Indicates the blowing frequency, Indicates the reference blowing frequency, It indicates the allowable deviation blowing frequency, and e is a natural constant.

[0018] Furthermore, the step of specifying training content based on the cardiopulmonary compression quality assessment value includes: obtaining a cardiopulmonary compression quality assessment threshold from a simulated medical database; summing the cardiopulmonary compression quality assessment value and the allowable deviation cardiopulmonary compression quality assessment value, marking it as a reference cardiopulmonary compression quality assessment value, comparing the reference cardiopulmonary compression quality assessment value with the cardiopulmonary compression quality assessment threshold, if the reference cardiopulmonary compression quality assessment value is greater than or equal to the cardiopulmonary compression quality assessment threshold, marking the score as a qualified score, if the reference cardiopulmonary compression quality assessment value is less than the cardiopulmonary compression quality assessment threshold, marking the score as an unqualified score, and specifying training content based on the cardiopulmonary compression data.

[0019] Furthermore, a simulated medical visualization method based on mixed reality includes: collecting simulator size information and simulator data parameters, establishing a virtual patient's internal organ structure based on the simulator size information, and positioning and overlapping the virtual patient's internal organs with the simulator's internal organs, and establishing data communication between the virtual patient and the simulator based on the simulator data parameters; collecting the simulator's cardiopulmonary compression data, and transmitting the cardiopulmonary compression data to a computer host, visually displaying the cardiopulmonary compression data, and synchronously transmitting it to a control terminal and a display terminal; acquiring modeling performance data and modeling image data, obtaining a modeling image evaluation value based on modeling image data processing, obtaining a modeling performance index based on modeling performance data processing, obtaining a modeling state evaluation value through comprehensive analysis, and obtaining an allowable deviation cardiopulmonary compression quality evaluation value based on matching of the modeling state evaluation value; analyzing the cardiopulmonary compression data to obtain a cardiopulmonary compression quality evaluation value, and specifying training content based on the cardiopulmonary compression quality evaluation value.

[0020] Furthermore, a simulated medical visualization device based on mixed reality includes: a processor and a memory for storing instructions executable by the processor; when the processor is configured to execute the instructions, the simulated medical visualization device realizes a simulated medical visualization system based on mixed reality.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. The present invention provides a simulated medical visualization system, method and device based on mixed reality, thereby providing comprehensive simulated medical scenarios, realizing data intercommunication and visualization, providing modeling status evaluation and feedback, and personalized training and guidance, thereby significantly improving the quality and effect of medical education and training;

[0023] 2. The present invention obtains the allowable deviation cardiopulmonary compression quality evaluation value by matching the modeling state evaluation value, so as to more accurately evaluate the cardiopulmonary compression operation of the simulated person, thereby enhancing the effectiveness of training and improving the flexibility and adaptability of the system;

[0024] 3. The present invention specifies training content according to the cardiopulmonary compression quality assessment value, so that targeted training can be carried out for the specific deficiencies of individuals in cardiopulmonary resuscitation skills, thereby improving the individual's self-confidence and ability to deal with emergencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of the structure of a mixed reality-based simulated medical visualization system provided in an embodiment of the present application;

[0026] Figure 2 A graph showing changes in modeling state evaluation values ​​of a mixed reality-based simulated medical visualization system provided in an embodiment of the present application;

[0027] Figure 3 A flowchart of a mixed reality-based simulated medical visualization method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The embodiments of the present application provide a simulated medical visualization system, method and equipment based on mixed reality, which solves the problem that the medical visualization system in the prior art cannot simulate the complexity and uncertainty of real scenes, resulting in insufficient experience of medical students in practical operations and emergency response, and unsatisfactory teaching results. By acquiring modeling performance data and modeling image data, a modeling image evaluation value is obtained according to modeling image data processing, a modeling performance index is obtained according to modeling performance data processing, a modeling state evaluation value is obtained by comprehensive analysis, and an allowable deviation cardiopulmonary compression quality evaluation value is obtained according to matching of the modeling state evaluation value; cardiopulmonary compression quality evaluation value is obtained by analysis according to cardiopulmonary compression data, and training content is specified according to the cardiopulmonary compression quality evaluation value, thereby enhancing the practical operation ability and emergency response ability of medical students.

[0029] The technical solution in the embodiment of the present application is to solve the problem that the above-mentioned medical visualization system cannot simulate the complexity and uncertainty of the real scene, resulting in insufficient experience of medical students in actual operation and emergency response, and unsatisfactory teaching effect. The overall idea is as follows:

[0030] By collecting the simulator size information and simulator data parameters, the virtual patient's internal organ structure is established according to the simulator size information, and the virtual patient's internal organs are positioned and overlapped with the simulator's internal organs, and data communication is established between the virtual patient and the simulator according to the simulator data parameters; the simulator's cardiopulmonary compression data is collected, and the cardiopulmonary compression data is transmitted to the computer host, the cardiopulmonary compression data is visualized and synchronously transmitted to the control end and the display end; the modeling performance data and the modeling image data are obtained, and the modeling image evaluation value is obtained according to the modeling image data processing, and the modeling performance index is obtained according to the modeling performance data processing. The modeling state evaluation value is obtained by comprehensive analysis, and the allowable deviation cardiopulmonary compression quality evaluation value is obtained according to the matching of the modeling state evaluation value; the cardiopulmonary compression quality evaluation value is obtained by analysis based on the cardiopulmonary compression data, and the training content is specified according to the cardiopulmonary compression quality evaluation value, so as to realize a highly simulated simulation environment, thereby improving the quality of medical education and training.

[0031] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0032] like Figure 1 As shown, it is a structural schematic diagram of a simulated medical visualization system based on mixed reality provided in an embodiment of the present application. The simulated medical visualization system based on mixed reality provided in an embodiment of the present application includes: a data connection module, a system adjustment module, a data display module, a data statistics module and a simulated medical database; wherein the data connection module is used to collect the size information and data parameters of the simulated person, establish the internal organ structure of the virtual patient according to the size information of the simulated person, and position and overlap the internal organs of the virtual patient with the internal organs of the simulated person, and establish data communication between the virtual patient and the simulated person according to the data parameters of the simulated person; the data display module is used to collect the size information of the simulated person and the data parameters of the simulated person The system adjusts the module to obtain the modeling performance data and the modeling image data, obtains the modeling image evaluation value according to the modeling image data processing, obtains the modeling performance index according to the modeling performance data processing, obtains the modeling state evaluation value by comprehensive analysis, and obtains the allowable deviation cardiopulmonary compression quality evaluation value according to the matching of the modeling state evaluation value; the data statistics module is used to analyze the cardiopulmonary compression data to obtain the cardiopulmonary compression quality evaluation value, and specify the training content according to the cardiopulmonary compression quality evaluation value.

[0033] In this embodiment, the data parameters of the simulated person include the heart rate, blood pressure and respiratory rate of the simulated person. The simulated person is an artificial intelligence device that simulates humans and can simulate the physiological and pathological states of real patients. The virtual patient is a digital model that simulates real patients based on computer technology and medical knowledge. When establishing the internal organ structure of the virtual patient, high-precision measurement tools (such as laser scanners, three-dimensional coordinate measuring instruments, etc.) are used to accurately measure the external dimensions of the simulated person. According to anatomical knowledge, the morphological characteristics and size range of each organ are determined, and three-dimensional modeling software (such as Maya, 3D Max, Blender, etc.) is used to perform three-dimensional modeling of each organ according to the size information of the simulated person. Then, the internal organ structure of the virtual patient is integrated with the external size information of the simulated person, and the internal organ structure of the virtual patient is verified and corrected using medical imaging technology, so that the internal organs of the virtual patient and the internal organs of the simulated person are in the same position, that is, positioning overlap. At the same time, a data interface is designed for data exchange between the virtual patient and the simulator. The data interface is used to establish a mapping relationship between the simulator and the virtual patient according to the simulator data parameters, so as to realize data synchronization of the simulator data parameters. That is, to achieve data exchange between the virtual patient and the simulator, so that medical students can obtain physiological parameters, pathological characteristics and other information related to the virtual patient in real time when performing simulation operations.

[0034] In addition, the simulated medical database is used to store relevant data of the simulated medical visualization system based on mixed reality, including: critical frame rate, reference resolution, allowable deviation resolution, critical delay, modeling image evaluation influencing factor corresponding to resolution, allowable deviation cardiopulmonary compression quality evaluation value and cardiopulmonary compression quality evaluation threshold corresponding to each modeling state evaluation interval, etc. The data in the simulated medical database can be obtained through existing medical public databases such as SEER, MIMIC or professional medical databases such as Pharnexcloud, PubMed, etc., and can also be obtained by fusing and integrating data from different channels (such as public database resources, simulated human data and clinical data, etc.).

[0035] Furthermore, the step of obtaining a modeling image evaluation value based on modeling image data processing includes: the modeling image data includes frame rate, resolution and delay; obtaining a critical frame rate, reference resolution, allowable deviation resolution and critical delay from a simulation medical database; and obtaining a modeling image evaluation value through comprehensive analysis.

[0036] The method for obtaining the modeling image evaluation value is as follows:

[0037] ;

[0038] In the formula, represents the modeling image evaluation value, Indicates the impact factor of modeling image evaluation corresponding to the frame rate, Indicates the impact factor of modeling image evaluation corresponding to the resolution, represents the modeling image assessment impact factor corresponding to the delay, Indicates the frame rate, represents the critical frame rate, Indicates resolution, Indicates the reference resolution, Indicates the allowable deviation resolution, Indicates delay, Indicates critical delay;

[0039] , and The modeling image evaluation influencing factors corresponding to the frame rate, resolution and delay preset in the simulation medicine database respectively represent the numerical values ​​of the degree of influence of the frame rate, resolution and delay on the modeling image evaluation value, and can be directly obtained from the simulation medicine database when used. For example, the frame rate and the modeling image evaluation influencing factors corresponding to the frame rate preset in the simulation medicine database form a mapping set, and the modeling image evaluation influencing factors corresponding to the frame rate are obtained according to the frame rate input mapping set; the resolution and the modeling image evaluation influencing factors corresponding to the resolution preset in the simulation medicine database form a mapping set, and the modeling image evaluation influencing factors corresponding to the resolution are obtained according to the resolution input mapping set; the delay and the modeling image evaluation influencing factors corresponding to the delay preset in the simulation medicine database form a mapping set, and the modeling image evaluation influencing factors corresponding to the delay are obtained according to the delay input mapping set, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0040] In this embodiment, the frame rate refers to the number of frames rendered on the screen per second, which is an important indicator for measuring the smoothness of the model animation and can be directly measured by special testing tools such as Fraps; the resolution refers to the clarity and detail of the model image (the product of the number of horizontal scan lines in a frame and the number of pixels on each scan line), which can be directly set by the user when exporting or rendering the model; the delay refers to the time lag phenomenon in the model operation process, that is, the time interval between the signal being sent and the response being received, which can be directly obtained using special testing tools such as performance testing software and game testing software. Frame rate, resolution and delay are interrelated in video or image processing and jointly affect the final visual quality and user experience. In medical image processing, high resolution and low delay can ensure that doctors can accurately and promptly diagnose the disease; the modeling image evaluation value obtained by comprehensive analysis can evaluate the accuracy and reliability of video or image processing, which helps to optimize the video or image processing algorithm and improve processing efficiency and quality.

[0041] Furthermore, the step of obtaining a modeling performance index based on modeling performance data processing includes: the modeling performance data includes position tracking deviation values ​​and volume tracking deviation values ​​at each time monitoring point; obtaining critical position tracking deviation values ​​and critical volume tracking deviation values ​​from a simulation medical database; and obtaining a modeling performance index through comprehensive analysis.

[0042] The modeling performance index is obtained as follows:

[0043] ;

[0044] In the formula, represents the modeling performance index, Indicates the modeling performance index impact factor corresponding to the position tracking deviation value, Indicates the modeling performance index impact factor corresponding to the volume tracking deviation value, represents the position tracking deviation value of the i-th time monitoring point, Indicates the critical position tracking deviation value, represents the volume tracking deviation value at the i-th time monitoring point, represents the critical volume tracking deviation value, where i is the number of each time monitoring point, i=1,2,3,...,N, N is the total number of time monitoring points;

[0045] and The modeling performance index influencing factors corresponding to the position tracking deviation value and the volume tracking deviation value preset in the simulation medicine database respectively represent the numerical values ​​of the degree of influence of the position tracking deviation value and the volume tracking deviation value on the modeling performance index, and can be directly obtained from the simulation medicine database when used. For example, the position tracking deviation value and the modeling performance index influencing factors corresponding to the position tracking deviation value preset in the simulation medicine database form a mapping set, and the modeling performance index influencing factors corresponding to the position tracking deviation value are obtained by inputting the mapping set according to the position tracking deviation value; the volume tracking deviation value and the modeling performance index influencing factors corresponding to the volume tracking deviation value preset in the simulation medicine database form a mapping set, and the modeling performance index influencing factors corresponding to the volume tracking deviation value are obtained by inputting the mapping set according to the volume tracking deviation value, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0046] In this embodiment, the position tracking deviation value is obtained by: deploying several key position points (including the heart center position point, the lung center position point and the oral center position point) and several time monitoring points, and obtaining the data synchronization delay time of the simulator and the virtual patient, and moving each time monitoring point backward by a data synchronization delay time to obtain each delayed time point. Select a certain characteristic point of the simulator (such as the navel) as the coordinate origin, and use the coordinate origin to point perpendicular to the ground and below the simulator as the y-axis, perpendicular to the y-axis and pointing to the head of the simulator as the z-axis, and use the right side of the simulator as the positive direction as the x-axis to establish a three-dimensional coordinate system. Collect the coordinates of each key position point of the simulator at each time monitoring point, and obtain the coordinates of each key position point of the virtual patient at each delayed time point. Obtain the straight-line distance between the coordinates of each key position point of the simulator at each time monitoring point and the coordinates of each key position point of the virtual patient corresponding to each delayed time point, and extract the average straight-line distance of the coordinates of each key position point, which is marked as the position tracking deviation value of each time monitoring point. The volume tracking deviation value is obtained by: establishing a three-dimensional coordinate system according to the above steps, obtaining the volume of each key organ of the simulated person (including the volume of the heart, the volume of the lungs and the volume of the oral cavity), and using the numerical integration method to calculate the volume of each key organ of the virtual patient (in the mixed reality environment, the surface of each key organ of the virtual patient is divided into small patches of the same area, and the volume of the micro-element surrounded by each small patch is calculated, and the volume of all micro-element is summed to obtain the volume of each key organ of the virtual patient), and the absolute value of the difference between the volume of each key organ of the virtual patient and the volume of each key organ of the simulated person is marked as the volume tracking deviation value. The position tracking deviation value and the volume tracking deviation value are interrelated in the monitoring process. The accumulation of position deviation may lead to an increase in volume deviation, especially in monitoring objects involving complex shapes or dynamic changes. The size of the position tracking deviation value and the volume tracking deviation value directly reflects the precision and accuracy of the monitoring system. The smaller the deviation, the better the performance of the monitoring system, and it can more accurately reflect the actual situation of the monitored object; the comprehensive analysis of the position tracking deviation value and the volume tracking deviation value can derive the modeling performance index, which is used to measure the overall performance of the monitoring system in a specific application scenario. Based on the modeling performance index, targeted optimization suggestions can be made. For example, when the position tracking deviation value is greater than or equal to the preset position tracking deviation threshold, it may be necessary to improve the monitoring equipment or algorithm to improve the accuracy; when the volume tracking deviation value is greater than or equal to the preset volume tracking deviation threshold, it may be necessary to more accurately define the calculation method and standard of volume change.

[0047] Furthermore, the step of comprehensively analyzing to obtain a modeling status evaluation value includes: obtaining a critical modeling image evaluation value and a critical modeling performance index from a simulated medical database; and comprehensively analyzing the modeling image evaluation value, the modeling performance index, the critical modeling image evaluation value and the critical modeling performance index to obtain a modeling status evaluation value.

[0048] The method for obtaining the modeling status evaluation value is as follows:

[0049] ;

[0050] In the formula, represents the modeling status evaluation value, Indicates the modeling status assessment impact factor corresponding to the modeling image assessment value, represents the modeling status assessment impact factor corresponding to the modeling performance index, represents the modeling image evaluation value, represents the critical modeling image assessment value, represents the modeling performance index, represents the critical modeling performance index;

[0051] and The modeling state assessment influencing factors corresponding to the modeling image assessment value and the modeling performance index preset in the simulation medicine database respectively represent the numerical values ​​of the degree of influence of the modeling image assessment value and the modeling performance index on the modeling state assessment value, and can be directly obtained from the simulation medicine database when used. For example, the modeling image assessment value and the modeling state assessment influencing factors corresponding to the modeling image assessment value preset in the simulation medicine database form a mapping set, and the modeling state assessment influencing factors corresponding to the modeling image assessment value are obtained by inputting the mapping set according to the modeling image assessment value; the modeling performance index and the modeling state assessment influencing factors corresponding to the modeling performance index preset in the simulation medicine database form a mapping set, and the modeling state assessment influencing factors corresponding to the modeling performance index are obtained by inputting the mapping set according to the modeling performance index, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0052] In this embodiment, the modeling image evaluation value and the modeling performance index play a complementary role in the modeling status evaluation. Usually, high-quality modeling images (i.e., high evaluation values) often mean more accurate model representation and higher visual fidelity, which helps to improve the modeling performance index. The level of the modeling performance index also reflects the efficiency and accuracy of the modeling system in processing image data, which in turn affects the evaluation value of the modeling image. The modeling status evaluation value obtained by comprehensively analyzing the modeling image evaluation value and the modeling performance index can comprehensively and accurately evaluate the modeling status. The modeling status evaluation value can provide important guidance for subsequent modeling work. For example, in the early stage of modeling, the effectiveness of the current modeling strategy can be judged by the evaluation value, and adjusted as needed; during the modeling process, the changes in the evaluation value can be monitored in real time to promptly discover and solve potential problems; after the modeling is completed, the evaluation value can also be used to verify whether the quality and performance of the model meet the expected requirements.

[0053] The modeling state evaluation impact factor corresponding to the modeling image evaluation value is set to 0.6, the modeling state evaluation impact factor corresponding to the modeling performance index is set to 0.4, the modeling image evaluation value is set to 1.26, the critical modeling image evaluation value is set to 1.2, and the critical modeling performance index is set to 1.5. When the modeling performance index continues to increase, the modeling state evaluation value is calculated. As shown in Table 1, the modeling state evaluation value data table of the simulated medical visualization system based on mixed reality.

[0054] Table 1 Modeling status evaluation value data table of simulated medical visualization system based on mixed reality:

[0055] .

[0056] like Figure 2 As shown in Table 1 and Figure 2 It can be seen that the modeling state assessment influence factor corresponding to the modeling image assessment value, the modeling state assessment influence factor corresponding to the modeling performance index, the modeling image assessment value, the critical modeling image assessment value and the critical modeling performance index remain unchanged. When the modeling performance index continues to increase, the modeling state assessment value also continues to increase.

[0057] Furthermore, the step of obtaining the allowable deviation cardiopulmonary compression quality assessment value according to the matching of the modeling state assessment value includes: matching the modeling state assessment value with the allowable deviation cardiopulmonary compression quality assessment value corresponding to each modeling state assessment value interval preset in the simulation medicine database to obtain the allowable deviation cardiopulmonary compression quality assessment value.

[0058] In this embodiment, the allowable deviation cardiopulmonary compression quality assessment value reflects the acceptable range of cardiopulmonary compression quality under different modeling states. By introducing the concepts of modeling state assessment value and allowable deviation cardiopulmonary compression quality assessment value, the cardiopulmonary compression quality of the trainee can be evaluated more accurately, and the setting of the allowable deviation cardiopulmonary compression quality assessment value can provide a reasonable fault tolerance range for the trainee, within which even if the trainee's compression operation has a certain deviation, it can still be considered qualified. This helps to reduce the training pressure of the trainee and improve the training effect. At the same time, the compression standard of the trainee can be flexibly adjusted according to the modeling state, which has high adaptability.

[0059] Furthermore, the step of analyzing the cardiopulmonary compression data to obtain a cardiopulmonary compression quality assessment value includes: the cardiopulmonary compression data includes compression depth, compression frequency, blowing volume and blowing frequency; obtaining a reference compression depth, an allowable deviation compression depth, a reference compression frequency, an allowable deviation compression frequency, a reference blowing volume, an allowable deviation blowing volume, a reference blowing frequency and an allowable deviation blowing frequency from a simulated medical database; and comprehensively analyzing to obtain a cardiopulmonary compression quality assessment value.

[0060] In this embodiment, the compression depth refers to the depth of the sternum during chest compression. Adequate compression depth can effectively promote blood flow in the heart and blood vessels. The compression frequency refers to the number of chest compressions per minute. Maintaining an appropriate compression frequency is crucial to the effect of cardiopulmonary resuscitation. The two together determine the efficiency of blood being pushed and perfused during cardiopulmonary resuscitation; the blowing volume refers to the amount of gas blown into the patient's lungs through mouth-to-mouth blowing or artificial respiration equipment during cardiopulmonary resuscitation. The blowing frequency refers to the number of times blowing is performed per minute. The two together determine the adequacy of the patient's lung oxygen supply. These four parameters are interrelated during cardiopulmonary resuscitation, and they jointly determine the overall effect of cardiopulmonary resuscitation. By comprehensively analyzing the values ​​of these four parameters, a cardiopulmonary compression quality evaluation value can be obtained, which can measure the overall quality and effect of compression and blowing during cardiopulmonary resuscitation, and provide important guidance for cardiopulmonary resuscitation operations. For example, during cardiopulmonary resuscitation, parameters such as compression depth and frequency, blowing volume and frequency can be adjusted in real time according to the evaluation value to ensure that the effect of cardiopulmonary resuscitation is optimal.

[0061] Furthermore, the cardiopulmonary compression quality assessment value is obtained as follows:

[0062] ;

[0063] In the formula, Indicates the cardiopulmonary compression quality assessment value. Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to compression depth, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to compression frequency, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to the blowing volume, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to the blowing frequency, Indicates the compression depth. Indicates the reference compression depth, Indicates the allowable deviation pressing depth, Indicates the compression frequency, Indicates the reference compression frequency, Indicates the allowable deviation pressing frequency, Indicates the blowing volume. Indicates the reference blowing volume, Indicates the allowable deviation of the blowing volume. Indicates the blowing frequency, Indicates the reference blowing frequency, It indicates the allowable deviation blowing frequency, and e is a natural constant;

[0064] In this embodiment, , , and They are the cardiopulmonary compression quality assessment influencing factors corresponding to the compression depth, compression frequency, blowing volume and blowing frequency preset in the simulation medical database, respectively representing the numerical values ​​of the influence of the compression depth, compression frequency, blowing volume and blowing frequency on the cardiopulmonary compression quality assessment value, and can be directly obtained from the simulation medical database when used. For example, the compression depth and the cardiopulmonary compression quality assessment influencing factors corresponding to the compression depth preset in the simulation medical database form a mapping set, and the cardiopulmonary compression quality assessment influencing factors corresponding to the compression depth are obtained by inputting the mapping set according to the compression depth; the compression frequency and the cardiopulmonary compression quality assessment influencing factors corresponding to the compression frequency preset in the simulation medical database form a mapping set, and the cardiopulmonary compression quality assessment influencing factors corresponding to the compression frequency are obtained by inputting the mapping set according to the compression frequency; the insufflation volume and the cardiopulmonary compression quality assessment influencing factors corresponding to the insufflation volume preset in the simulation medical database form a mapping set, and the cardiopulmonary compression quality assessment influencing factors corresponding to the insufflation volume are obtained by inputting the mapping set according to the insufflation volume; the insufflation frequency and the cardiopulmonary compression quality assessment influencing factors corresponding to the insufflation frequency preset in the simulation medical database form a mapping set, and the cardiopulmonary compression quality assessment influencing factors corresponding to the insufflation frequency are obtained by inputting the mapping set according to the insufflation frequency, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the influencing factor in this embodiment is between 0 and 1.

[0065] Furthermore, the step of specifying training content based on the cardiopulmonary compression quality assessment value includes: obtaining a cardiopulmonary compression quality assessment threshold from a simulated medical database; summing the cardiopulmonary compression quality assessment value and the allowable deviation cardiopulmonary compression quality assessment value, marking it as a reference cardiopulmonary compression quality assessment value, comparing the reference cardiopulmonary compression quality assessment value with the cardiopulmonary compression quality assessment threshold, if the reference cardiopulmonary compression quality assessment value is greater than or equal to the cardiopulmonary compression quality assessment threshold, marking the score as a qualified score, if the reference cardiopulmonary compression quality assessment value is less than the cardiopulmonary compression quality assessment threshold, marking the score as an unqualified score, and specifying training content based on the cardiopulmonary compression data.

[0066] In this embodiment, the cardiopulmonary compression quality assessment threshold is a numerical limit used to determine whether the trainee's cardiopulmonary compression operation meets the qualified standard during cardiopulmonary resuscitation training or assessment. When the reference cardiopulmonary compression quality assessment value is less than the cardiopulmonary compression quality assessment threshold, the absolute values ​​of the differences between the compression depth, compression frequency, blowing volume and blowing frequency and the reference compression depth, reference compression frequency, reference blowing volume and reference blowing frequency are marked as deviation compression depth, deviation compression frequency, deviation blowing volume and deviation blowing frequency, respectively. The deviation compression depth, deviation compression frequency, deviation blowing volume and deviation blowing frequency are compared with the allowable deviation compression depth, allowable deviation compression frequency, allowable deviation blowing volume and allowable deviation blowing frequency. If the deviation compression depth is greater than the allowable deviation compression depth, it means that the trainee's compression depth is abnormal, and the trainee is reminded to pay attention to controlling the strength, and it is recommended to use resistance bands or other strength training machines for practice; if the deviation compression frequency is greater than the allowable deviation compression frequency, a metronome or the frequency indicator on the simulation training device can be used to assist the trainee in adjusting the compression rhythm; if the deviation blowing volume is greater than the allowable deviation blowing volume, the blowing volume indicator on the simulation training device is used to practice multiple times and monitor the trainee's blowing volume; if the blowing frequency is greater than the allowable deviation blowing frequency, specific training scenarios can be set, such as single-person resuscitation and double-person resuscitation, so that trainees can practice and adjust in different situations. This personalized training method can more accurately improve the deficiencies of trainees, thereby improving training efficiency and effectiveness.

[0067] Furthermore, a simulated medical visualization method based on mixed reality includes: collecting simulator size information and simulator data parameters, establishing a virtual patient's internal organ structure based on the simulator size information, and positioning and overlapping the virtual patient's internal organs with the simulator's internal organs, and establishing data communication between the virtual patient and the simulator based on the simulator data parameters; collecting the simulator's cardiopulmonary compression data, and transmitting the cardiopulmonary compression data to a computer host, visually displaying the cardiopulmonary compression data, and synchronously transmitting it to a control terminal and a display terminal; acquiring modeling performance data and modeling image data, obtaining a modeling image evaluation value based on modeling image data processing, obtaining a modeling performance index based on modeling performance data processing, obtaining a modeling state evaluation value through comprehensive analysis, and obtaining an allowable deviation cardiopulmonary compression quality evaluation value based on matching of the modeling state evaluation value; analyzing the cardiopulmonary compression data to obtain a cardiopulmonary compression quality evaluation value, and specifying training content based on the cardiopulmonary compression quality evaluation value.

[0068] The embodiment of the present application also provides a simulated medical visualization device based on mixed reality, including: a processor and a memory for storing instructions executable by the processor; when the processor is configured to execute the instructions, the electronic device implements a simulated medical visualization system based on mixed reality.

[0069] In summary, this embodiment collects the simulator size information and simulator data parameters, establishes the virtual patient's internal organ structure according to the simulator size information, and overlaps the virtual patient's internal organs with the simulator's internal organs, and establishes data communication between the virtual patient and the simulator according to the simulator data parameters; collects the simulator's cardiopulmonary compression data, and transmits the cardiopulmonary compression data to the computer host, visualizes the cardiopulmonary compression data, and synchronously transmits it to the control end and the display end; obtains modeling performance data and modeling image data, obtains a modeling image evaluation value according to the modeling image data processing, obtains a modeling performance index according to the modeling performance data processing, obtains a modeling state evaluation value by comprehensive analysis, and obtains an allowable deviation cardiopulmonary compression quality evaluation value according to the matching of the modeling state evaluation value; analyzes the cardiopulmonary compression data to obtain a cardiopulmonary compression quality evaluation value, and specifies training content according to the cardiopulmonary compression quality evaluation value, thereby enhancing the medical students' practical operation ability and ability to respond to emergencies.

[0070] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems and methods, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0071] The present invention is described with reference to the systems, methods and devices according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0072] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0073] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0074] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0075] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A simulated medical visualization system based on mixed reality, characterized in that: include: Data connection module, system adjustment module, data display module and data statistics module; The data connection module is used to collect the size information and data parameters of the simulated person, establish the internal organ structure of the virtual patient according to the size information of the simulated person, and overlap the internal organs of the virtual patient with the internal organs of the simulated person, and establish data communication between the virtual patient and the simulated person according to the data parameters of the simulated person; The data display module is used to collect the cardiopulmonary compression data of the simulated person, transmit the cardiopulmonary compression data to the computer host, visualize the cardiopulmonary compression data, and synchronously transmit it to the control end and the display end; The system adjustment module is used to obtain modeling performance data and modeling image data, obtain a modeling image evaluation value according to modeling image data processing, obtain a modeling performance index according to modeling performance data processing, obtain a modeling state evaluation value by comprehensive analysis, and obtain an allowable deviation cardiopulmonary compression quality evaluation value according to matching of the modeling state evaluation value; The data statistics module is used to analyze the cardiopulmonary compression data to obtain a cardiopulmonary compression quality assessment value, and to specify training content according to the cardiopulmonary compression quality assessment value; The step of obtaining a modeling image evaluation value based on modeling image data processing comprises: The modeled image data, including frame rate, resolution and latency; Obtain critical frame rate, reference resolution, allowable deviation resolution and critical delay from the simulated medical database; Comprehensive analysis was performed to obtain the modeling image assessment value; The step of obtaining the modeling performance index according to the modeling performance data processing comprises: The modeling performance data includes the position tracking deviation value and the volume tracking deviation value at each time monitoring point; Obtaining a critical position tracking deviation value and a critical volume tracking deviation value from a simulation medical database; The modeling performance index was obtained through comprehensive analysis; The steps of comprehensive analysis to obtain the modeling status assessment value include: Obtain critical modeling image assessment values ​​and critical modeling performance indices from a simulated medical database; The modeling status evaluation value is obtained by comprehensive analysis of the modeling image evaluation value, the modeling performance index, the critical modeling image evaluation value and the critical modeling performance index; The method for obtaining the position tracking deviation value is as follows: deploying a number of key position points and a number of time monitoring points, and obtaining the data synchronization delay time of the simulator and the virtual patient, shifting each time monitoring point backward by a data synchronization delay time to obtain each delayed time point, selecting a certain feature point of the simulator as the coordinate origin, establishing a three-dimensional coordinate system, obtaining the straight-line distance between the coordinates of each key position point of the simulator at each time monitoring point and the coordinates of each key position point of the virtual patient corresponding to each delayed time point, and the average value of the straight-line distance is marked as the position tracking deviation value of each time monitoring point; The volume tracking deviation value is obtained by marking the absolute value of the difference between the volume of each key organ of the virtual patient and the volume of each key organ of the simulated person as the volume tracking deviation value; The allowable deviation cardiopulmonary compression quality assessment value reflects the acceptable range of cardiopulmonary compression quality under different modeling states.

2. The mixed reality-based simulated medical visualization system according to claim 1, characterized in that: The step of analyzing the cardiopulmonary compression data to obtain a cardiopulmonary compression quality assessment value comprises: The cardiopulmonary compression data includes compression depth, compression frequency, blowing volume and blowing frequency; Obtaining reference compression depth, allowable deviation compression depth, reference compression frequency, allowable deviation compression frequency, reference insufflation volume, allowable deviation insufflation volume, reference insufflation frequency and allowable deviation insufflation frequency from a simulation medical database; Comprehensive analysis was performed to obtain the cardiopulmonary compression quality assessment value.

3. The mixed reality-based simulated medical visualization system according to claim 1, characterized in that: The cardiopulmonary compression quality assessment value is obtained as follows: ； In the formula, Indicates the cardiopulmonary compression quality assessment value, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to compression depth, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to compression frequency, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to the blowing volume, Indicates the impact factor of cardiopulmonary compression quality assessment corresponding to the blowing frequency, Indicates the compression depth. Indicates the reference compression depth, Indicates the allowable deviation pressing depth, Indicates the compression frequency, Indicates the reference compression frequency, Indicates the allowable deviation pressing frequency, Indicates the blowing volume. Indicates the reference blowing volume, Indicates the allowable deviation of the blowing volume. Indicates the blowing frequency, Indicates the reference blowing frequency, It indicates the allowable deviation blowing frequency, and e is a natural constant.

4. The mixed reality-based simulated medical visualization system according to claim 1, characterized in that: The step of specifying the training content according to the cardiopulmonary compression quality evaluation value comprises: Obtain the cardiopulmonary compression quality assessment threshold from the simulated medical database; The cardiopulmonary compression quality assessment value is summed with the allowable deviation cardiopulmonary compression quality assessment value, and marked as the reference cardiopulmonary compression quality assessment value. The reference cardiopulmonary compression quality assessment value is compared with the cardiopulmonary compression quality assessment threshold. If the reference cardiopulmonary compression quality assessment value is greater than or equal to the cardiopulmonary compression quality assessment threshold, it is marked as a qualified score. If the reference cardiopulmonary compression quality assessment value is less than the cardiopulmonary compression quality assessment threshold, it is marked as an unqualified score, and the training content is specified according to the cardiopulmonary compression data.

5. A simulated medical visualization method based on mixed reality, applied to a simulated medical visualization system based on mixed reality as claimed in any one of claims 1 to 4, characterized in that: The following steps are involved: Collecting the size information and data parameters of the simulator, establishing the internal organ structure of the virtual patient according to the size information of the simulator, positioning and overlapping the internal organs of the virtual patient with the internal organs of the simulator, and establishing data communication between the virtual patient and the simulator according to the data parameters of the simulator; Collect the cardiopulmonary compression data of the simulated person, transmit the cardiopulmonary compression data to the computer host, visualize the cardiopulmonary compression data, and synchronously transmit it to the control end and the display end; Acquire modeling performance data and modeling image data, obtain a modeling image evaluation value based on modeling image data processing, obtain a modeling performance index based on modeling performance data processing, obtain a modeling state evaluation value through comprehensive analysis, and obtain an allowable deviation cardiopulmonary compression quality evaluation value based on matching of the modeling state evaluation value; The cardiopulmonary compression data is analyzed to obtain a cardiopulmonary compression quality assessment value, and the training content is specified based on the cardiopulmonary compression quality assessment value.

6. A simulated medical visualization device based on mixed reality, characterized in that: include: a processor, a memory for storing instructions executable by the processor; When the processor is configured to execute the instructions, the simulated medical visualization device implements the simulated medical visualization system based on mixed reality as described in any one of claims 1 to 4.

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