Three-dimensional parametric design method for brain position fixation device

Abstract

The present invention relates to the field of data mining technology, and in particular to a three-dimensional parametric design method for a cranial and cerebral position fixation device. The method comprises the following steps: obtaining design requirement data of the cranial and cerebral position fixation device, including patient body shape data, body shape requirement data, comfort data, and fixation accuracy data; collecting clinical application information and usage scenario information to obtain preliminary design parameters; constructing a preliminary three-dimensional model of the cranial and cerebral position fixation device according to the design requirement data and the preliminary design parameters; constructing a basic structural model of the device according to the preliminary three-dimensional model, including a support frame model, a fixing component model, and an adjustment mechanism model; and generating an adjustable three-dimensional parametric model according to the basic structural model through a parametric design method. The present invention adjusts and optimizes the design parameters in real time according to the body shape data and clinical needs of individual patients, ensuring that the device can accurately adapt to the patient and provide a high-precision fixation effect.

Description

Technical Field

[0001] The invention relates to the technical field of data mining, and in particular to a three-dimensional parameterized design method for a cranial and brain position fixing device. Background Art

[0002] The cranial and brain position fixation device is a medical device used in neurosurgery. It is mainly used to fix the patient's head to ensure that the head remains stable during the operation and to avoid the accuracy and safety of the operation affected by the movement of the head. This device usually consists of a head frame, a neck clamp and a bracket. It can be adjusted to adapt to different head shapes and surgical needs, reduce the operation time and the risk of complications, and improve the surgical effect and the patient's treatment experience. In clinical applications, the cranial and brain surgical fixator can effectively reduce the workload of medical care, is simple to bandage, easy to use, and effectively protects the incision and brain tissue under the bone window, improving clinical safety.

[0003] The three-dimensional parametric design of brain position fixation devices is an advanced design method specifically used to develop and optimize head and neck fixation devices used in neurosurgery. Traditional three-dimensional parametric design methods for brain position fixation devices often have the following problems: the fixation devices often ignore the patient's comfort in order to ensure the firmness of the fixation, causing the patient to be in an uncomfortable state for a long time during surgery or treatment, which may affect the treatment effect and even cause the patient to move during treatment. Traditional fixation devices are usually designed based on standard models, which are difficult to effectively adjust according to different clinical application scenarios and individual differences of patients, resulting in insufficient adaptability in actual use. Summary of the invention

[0004] Based on this, it is necessary for the present invention to provide a three-dimensional parametric design method for a cranial and brain position fixation device to solve at least one of the above technical problems.

[0005] To achieve the above object, a three-dimensional parametric design method for a cranial and brain position fixation device comprises the following steps:

[0006] Step S1: obtaining design requirement data of the cranial and cerebral position fixation device, including patient body shape data, position requirement data, comfort data, and fixation accuracy data; collecting clinical application information and usage scenario information to obtain preliminary design parameters; using CAD software to construct a preliminary three-dimensional model of the cranial and cerebral position fixation device according to the design requirement data and preliminary design parameters;

[0007] Step S2: constructing a basic structural model of the device according to the preliminary three-dimensional model, including a supporting frame model, a fixed component model, and an adjustment mechanism model; generating an adjustable three-dimensional parametric model according to the basic structural model by a parametric design method;

[0008] Step S3: performing mechanical property analysis on the three-dimensional parameterized model to obtain mechanical property analysis data; performing structural design optimization processing on the three-dimensional parameterized model according to the mechanical property analysis data, and adjusting the structural parameters in real time according to a preset fixed accuracy to obtain structural parameter adjustment data;

[0009] Step S4: acquiring device usage data in different clinical application scenarios; performing adaptability evaluation on the device usage data, thereby obtaining adaptability evaluation data; performing adaptive correction on the structural parameter adjustment data according to the adaptability evaluation data, and obtaining the optimal design scheme through multi-objective optimization technology, thereby obtaining the optimal design window data;

[0010] Step S5: using 3D printing technology to produce a device prototype according to the optimized design window data, and conducting clinical simulation tests to collect feedback information, thereby obtaining prototype device feedback data; performing function and adaptability evaluation on the prototype according to the prototype device feedback data, thereby obtaining prototype evaluation data;

[0011] Step S6: updating the design parameters and constraints of the three-dimensional parametric model according to the prototype evaluation data, thereby obtaining a final parametric model; converting the final parametric model into a production drawing, thereby obtaining model production drawing data.

[0012] The present invention establishes the basis of design and ensures that the device can meet the specific needs of patients, including body shape adaptation, body position requirements, comfort and fixation accuracy. At the same time, collecting clinical application and usage scenario information helps to design products that better meet actual usage needs. By building a basic structural model, the various components and functions of the device can be clarified. The use of parametric design methods improves the flexibility and adaptability of the design, so that the design can be quickly adjusted according to different patient needs. Mechanical performance analysis ensures the stability and safety of the device. Structural design optimization and real-time adjustment improve the performance of the device, making it more in line with the preset fixation accuracy requirements and enhancing the reliability of the product. By evaluating the usage data in different clinical scenarios, it can be ensured that the device can maintain good performance in various situations. The application of multi-objective optimization technology helps to find the optimal design solution and improves the overall performance and applicability of the device. The application of 3D printing technology accelerates the transformation process from design to physical object, so that the design can be quickly iterated. The collection of clinical simulation tests and feedback information provides a practical basis for further optimization and ensures the practicality and effectiveness of the final product. The final design update based on the prototype evaluation data ensures that the final form of the product can meet all design requirements. Converting parametric models into production drawings is a key step in the transition of products from the design stage to the production stage, laying the foundation for large-scale production. The entire process reflects a systematic and iterative product development process, and each step is closely linked to ensure that the final product can meet the high standards of the medical field while being highly personalized and adaptable. Through continuous testing, evaluation and optimization, this process helps to improve the quality of medical devices and the patient experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0014] Figure 1 It is a schematic diagram of the steps of the three-dimensional parameterized design method for the cranial and brain position fixation device of the present invention;

[0015] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0016] Figure 3 for Figure 1 Detailed step flow chart of step S2 in FIG. DETAILED DESCRIPTION

[0017] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0018] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0019] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0020] To achieve this, please refer to Figures 1 to 3 The present invention provides a three-dimensional parametric design method for a cranial and brain position fixation device, the method comprising the following steps:

[0021] Step S1: obtaining design requirement data of the cranial and cerebral position fixation device, including patient body shape data, position requirement data, comfort data, and fixation accuracy data; collecting clinical application information and usage scenario information to obtain preliminary design parameters; using CAD software to construct a preliminary three-dimensional model of the cranial and cerebral position fixation device according to the design requirement data and preliminary design parameters;

[0022] Step S2: constructing a basic structural model of the device according to the preliminary three-dimensional model, including a supporting frame model, a fixed component model, and an adjustment mechanism model; generating an adjustable three-dimensional parametric model according to the basic structural model by a parametric design method;

[0023] Step S3: performing mechanical property analysis on the three-dimensional parameterized model to obtain mechanical property analysis data; performing structural design optimization processing on the three-dimensional parameterized model according to the mechanical property analysis data, and adjusting the structural parameters in real time according to a preset fixed accuracy to obtain structural parameter adjustment data;

[0024] Step S4: acquiring device usage data in different clinical application scenarios; performing adaptability evaluation on the device usage data, thereby obtaining adaptability evaluation data; performing adaptive correction on the structural parameter adjustment data according to the adaptability evaluation data, and obtaining the optimal design scheme through multi-objective optimization technology, thereby obtaining the optimal design window data;

[0025] Step S5: using 3D printing technology to produce a device prototype according to the optimized design window data, and conducting clinical simulation tests to collect feedback information, thereby obtaining prototype device feedback data; performing function and adaptability evaluation on the prototype according to the prototype device feedback data, thereby obtaining prototype evaluation data;

[0026] Step S6: updating the design parameters and constraints of the three-dimensional parametric model according to the prototype evaluation data, thereby obtaining a final parametric model; converting the final parametric model into a production drawing, thereby obtaining model production drawing data.

[0027] In the embodiment of the present invention, reference Figure 1 The above is a schematic flow chart of the steps of a three-dimensional parametric design method for a cranial and brain position fixing device of the present invention. In this example, the three-dimensional parametric design method for a cranial and brain position fixing device includes the following steps:

[0028] Step S1: obtaining design requirement data of the cranial and cerebral position fixation device, including patient body shape data, position requirement data, comfort data, and fixation accuracy data; collecting clinical application information and usage scenario information to obtain preliminary design parameters; using CAD software to construct a preliminary three-dimensional model of the cranial and cerebral position fixation device according to the design requirement data and preliminary design parameters;

[0029] In the embodiment of the present invention, three-dimensional data of the patient's head is obtained through medical imaging equipment (such as CT and MRI). Detailed body shape information of the patient is collected in combination with body shape features, such as head size and skull shape. According to the needs of surgery or treatment, the precise position requirements of the patient's head are determined. These data may include head tilt angle, rotation angle, etc. to ensure the accuracy of surgery or treatment. Comfort requirements are defined in combination with patient feedback and ergonomic principles. Including the contact pressure of the head in the fixture, material selection of the fixture, etc., to ensure comfort during long-term use. According to clinical requirements, the accuracy standard of the fixture is determined, which usually involves the range of head movement allowed during operation, and the response speed to different body positions. Through communication with clinicians and medical technicians, the use scenario information of the fixture in different surgical or treatment environments is collected; for example, different positioning requirements of the device on the operating table and in the radiotherapy room. Preliminary design parameters are formulated by integrating the patient's personalized data and clinical application information. These parameters are input using CAD software to create a preliminary three-dimensional model, which will contain the approximate shape and key dimensions of the fixture.

[0030] Step S2: constructing a basic structural model of the device according to the preliminary three-dimensional model, including a supporting frame model, a fixed component model, and an adjustment mechanism model; generating an adjustable three-dimensional parametric model according to the basic structural model by a parametric design method;

[0031] The embodiment of the present invention designs the basic structure of the fixing device to provide overall support. It is usually made of strong materials, and the balance between strength and weight should be considered during design. Specific fixing components, such as chin support, headband, etc., are designed according to the patient's body shape data. These components are in direct contact with the patient's head, and their connection method with the support frame should be considered during design. Adjustment mechanisms that can achieve fine-tuning of the patient's head, such as rotating joints, sliding guides, etc., are designed. These mechanisms allow necessary adjustments to be made during surgery or treatment. Through parametric design tools, the basic structure model is converted into a three-dimensional parametric model. This model allows designers to make real-time adjustments and optimizations based on different input parameters (such as body shape data, fixation accuracy). This process includes setting key parameters and variables for optimization and adjustment in subsequent steps.

[0032] Step S3: performing mechanical property analysis on the three-dimensional parameterized model to obtain mechanical property analysis data; performing structural design optimization processing on the three-dimensional parameterized model according to the mechanical property analysis data, and adjusting the structural parameters in real time according to a preset fixed accuracy to obtain structural parameter adjustment data;

[0033] The embodiment of the present invention uses mechanical analysis tools such as finite element analysis (FEA) to simulate and test the three-dimensional parametric model, focusing on analyzing the deformation, stress distribution, etc. of the fixation device under stress. Ensure that the device can remain stable and accurate during the patient's position adjustment and fixation process. According to the results of the mechanical performance analysis, adjust and optimize the structural design of the three-dimensional model; for example, enhance the strength of key parts, adjust the thickness of the support frame, improve the geometry of the fixed parts, etc. Ensure the reliability and durability of the device in actual use. According to the preset fixing accuracy requirements, the structural parameters of the three-dimensional model are adjusted in real time; by modifying the design variables of the parametric model, such as angle, length, material thickness, etc., ensure that the final model can achieve the required fixing accuracy.

[0034] Step S4: acquiring device usage data in different clinical application scenarios; performing adaptability evaluation on the device usage data, thereby obtaining adaptability evaluation data; performing adaptive correction on the structural parameter adjustment data according to the adaptability evaluation data, and obtaining the optimal design solution through multi-objective optimization technology, thereby obtaining optimal design window data;

[0035] The embodiments of the present invention test the preliminarily designed fixation device in different clinical application scenarios and collect usage data; these data include the performance of the device in actual operation, such as fixation effect, ease of adjustment, patient comfort, etc. Analyze the device usage data, evaluate its adaptability in different scenarios, confirm whether the device can work effectively in various clinical environments and meet the requirements of different surgeries or treatments. According to the adaptability evaluation results, the structural parameters of the three-dimensional parametric model are modified; use multi-objective optimization technology to find the optimal design parameter combination under the premise of considering various clinical needs and design constraints. Comprehensively analyze and optimize the results to generate an optimal design window. The parameter combination within this window can provide the best fixation effect, comfort and adaptability.

[0036] Step S5: using 3D printing technology to produce a device prototype according to the optimized design window data, and conducting clinical simulation tests to collect feedback information, thereby obtaining prototype device feedback data; performing function and adaptability evaluation on the prototype according to the prototype device feedback data, thereby obtaining prototype evaluation data;

[0037] The embodiment of the present invention uses 3D printing technology to manufacture a prototype of the fixation device according to the parameters in the optimal design window; 3D printing technology can quickly and accurately generate physical models, which is convenient for subsequent clinical testing and evaluation. The 3D printed prototype is simulated and tested in a clinical environment. The actual performance of the prototype is tested by simulating surgery or treatment scenarios, and feedback from patients and doctors is collected. Based on the results of the simulation test, the prototype is evaluated for function and adaptability, including the evaluation of the performance in terms of fixation accuracy, ease of adjustment, and patient comfort.

[0038] Step S6: updating the design parameters and constraints of the three-dimensional parametric model according to the prototype evaluation data, thereby obtaining a final parametric model; converting the final parametric model into a production drawing, thereby obtaining model production drawing data.

[0039] According to the prototype evaluation results, the embodiment of the present invention makes final corrections and improvements to the three-dimensional parametric model, adjusts the design parameters and model constraints, and ensures that all functions and requirements are met. The final corrected three-dimensional parametric model is converted into production drawings, which contain all the detailed designs of the fixture and can be directly used for manufacturing. The final generated production drawing data will be used for mass production to ensure that each manufactured fixture meets the design requirements and can provide reliable performance in clinical practice.

[0040] The present invention establishes the basis of design and ensures that the device can meet the specific needs of patients, including body shape adaptation, body position requirements, comfort and fixation accuracy. At the same time, collecting clinical application and usage scenario information helps to design products that better meet actual usage needs. By building a basic structural model, the various components and functions of the device can be clarified. The use of parametric design methods improves the flexibility and adaptability of the design, so that the design can be quickly adjusted according to different patient needs. Mechanical performance analysis ensures the stability and safety of the device. Structural design optimization and real-time adjustment improve the performance of the device, making it more in line with the preset fixation accuracy requirements and enhancing the reliability of the product. By evaluating the usage data in different clinical scenarios, it can be ensured that the device can maintain good performance in various situations. The application of multi-objective optimization technology helps to find the optimal design solution and improves the overall performance and applicability of the device. The application of 3D printing technology accelerates the transformation process from design to physical object, so that the design can be quickly iterated. The collection of clinical simulation tests and feedback information provides a practical basis for further optimization and ensures the practicality and effectiveness of the final product. The final design update based on the prototype evaluation data ensures that the final form of the product can meet all design requirements. Converting parametric models into production drawings is a key step in the transition of products from the design stage to the production stage, laying the foundation for large-scale production. The entire process reflects a systematic and iterative product development process, and each step is closely linked to ensure that the final product can meet the high standards of the medical field while being highly personalized and adaptable. Through continuous testing, evaluation and optimization, this process helps to improve the quality of medical devices and the patient experience.

[0041] Preferably, step S1 comprises the following steps:

[0042] Step S11: using 3D scanning technology to obtain accurate three-dimensional information of the patient's head and neck, thereby obtaining the patient's three-dimensional scanning data; performing image segmentation on the patient's three-dimensional scanning data, extracting key anatomical feature points, and establishing a personalized digital model of the patient, thereby obtaining the patient's body shape data;

[0043] Step S12: collecting information on the type of surgery, duration of surgery, and surgical position, and analyzing the requirements of different types of surgery for cranial and brain position fixation devices, thereby generating position requirement data;

[0044] Step S13: establishing a comfort evaluation model according to a preset comfort evaluation table and collecting the patient's physiological indicators in real time through an intelligent sensor system, thereby obtaining comfort data;

[0045] Step S14: collecting the interaction requirements between the surgical instrument and the fixation device and the accuracy requirements of different types of neurosurgery, so as to obtain fixation accuracy data;

[0046] Step S15: integrating the patient's body shape data, body position requirement data, comfort data, and fixation accuracy data, thereby obtaining design requirement data for the cranial body position fixation device;

[0047] Step S16: Collect clinical application information and usage scenario information to obtain preliminary design parameters;

[0048] Step S17: Using CAD software to construct a preliminary three-dimensional model of the cranial and brain position fixation device according to the design requirement data and preliminary design parameters.

[0049] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in the embodiment of the present invention, step S1 includes the following steps:

[0050] Step S11: using 3D scanning technology to obtain accurate three-dimensional information of the patient's head and neck, thereby obtaining the patient's three-dimensional scanning data; performing image segmentation on the patient's three-dimensional scanning data, extracting key anatomical feature points, and establishing a personalized digital model of the patient, thereby obtaining the patient's body shape data;

[0051] The embodiment of the present invention uses a high-precision 3D scanning device (such as a structured light scanner or a laser scanner) to capture the three-dimensional information of the patient's head and neck, ensuring that the scanning device can accurately capture the subtle anatomical structure. The patient needs to maintain a fixed position and the device performs a full-range scan around the patient's head and neck to obtain complete three-dimensional surface data. The scanning process needs to be fast and accurate to reduce errors caused by patient movement. Use professional three-dimensional image processing software to cut and clean the scanned data, remove noise and unnecessary parts, and extract key areas related to the design, such as surface data of the head and neck. Extract key anatomical feature points such as ears, nose tips, eye sockets, etc. through algorithms or manual annotations. These feature points are used for precise registration and personalized design of subsequent models. The cleaned three-dimensional data and feature points are integrated to construct a personalized digital model that reflects the patient's specific body shape, which will serve as the basis for subsequent design.

[0052] Step S12: collecting information on the type of surgery, duration of surgery, and surgical position, and analyzing the requirements of different types of surgery for cranial and brain position fixation devices, thereby generating position requirement data;

[0053] The embodiment of the present invention collects the type of neurosurgery that the patient is going to undergo (such as craniotomy, brain tumor resection, etc.), because different types of operations have different requirements for body position. The estimated operation time is recorded. Longer operations have higher requirements for the comfort and fixation stability of the body position fixation device. According to the type of operation, the body position that the patient's head and neck need to maintain during the operation is determined, which may include prone, lateral or supine positions. In combination with the type of operation, duration and body position, the specific requirements that the cranial body position fixation device needs to meet are analyzed; considering the fixation accuracy, stability and possible adjustment needs of the patient's head during the operation, the body position requirement data is generated, and these data are used to guide the design of the shape and adjustment mechanism of the fixation device.

[0054] Step S13: establishing a comfort evaluation model according to a preset comfort evaluation table and collecting the patient's physiological indicators in real time through an intelligent sensor system, thereby obtaining comfort data;

[0055] The embodiment of the present invention designs a comfort evaluation form, which includes multiple dimensions related to patient comfort, such as head pressure distribution, support point comfort, skin contact feeling of materials, etc. The evaluation form will be used to quantify the impact of different designs on patient comfort. During the design evaluation stage, by installing pressure sensors, temperature sensors, etc. at key contact points on the patient's head and neck, the impact of the fixation device on the patient's physiological indicators is monitored in real time. The data collected by the intelligent sensing system will be uploaded and processed in real time to evaluate the comfort performance of different designs. The data includes pressure, temperature changes, etc., which can directly reflect the comfort of the device. Based on the collected data and the content of the comfort evaluation form, a comprehensive comfort evaluation model is constructed; the model can automatically evaluate the comfort of the device based on the input sensor data and patient feedback, and generate comfort data to provide a basis for design optimization.

[0056] Step S14: collecting the interaction requirements between the surgical instrument and the fixation device and the accuracy requirements of different types of neurosurgery, so as to obtain fixation accuracy data;

[0057] The embodiment of the present invention collects information about the main instruments to be used in the operation, especially their operating space and possible interaction areas with the fixture. This information will help design the shape and position of the fixture to avoid affecting the operation of the instrument during the operation. Analyze the interaction between the instrument and the fixture to determine the amplitude and accuracy of the head position adjustment that may be required during the operation; ensure that the fixture can provide sufficient fixing force without hindering the use of surgical instruments. With reference to existing neurosurgery accuracy standards, determine the accuracy requirements of the fixture in different surgical scenarios, which usually include the allowable range of movement of the head, the stability of the head position after fixation, etc. Integrate the instrument interaction requirements and surgical accuracy requirements to generate fixation accuracy data, which are used to guide the design of the adjustment mechanism of the fixture to ensure that the accuracy requirements can be met during the operation.

[0058] Step S15: integrating the patient's body shape data, body position requirement data, comfort data, and fixation accuracy data, thereby obtaining design requirement data for the cranial body position fixation device;

[0059] The embodiment of the present invention integrates and analyzes the acquired patient body shape data, body position requirement data, comfort data and fixation accuracy data to generate a comprehensive design requirement report; the report includes detailed analysis results of various types of data, clarifies the design goals and functional indicators that need to be achieved. Based on the results of the integrated analysis, the final design requirement data is generated, which will serve as the basis for the preliminary three-dimensional model design of the fixture to ensure that the design can meet all functional requirements and comfort requirements.

[0060] Step S16: Collect clinical application information and usage scenario information to obtain preliminary design parameters;

[0061] The embodiments of the present invention collect information about the use of fixation devices in actual surgical scenarios through communication with clinicians and technicians, as well as on-site observations, including the performance of the fixation devices in different surgical positions, the ease of adjustment, etc. The performance data of fixation devices used in similar surgeries in the past are collected and analyzed to identify areas that need improvement in the current design. Based on the collected clinical application information, preliminary design parameters are generated, which may include material selection, adjustment range, fixation strength, etc., as input parameters for the preliminary three-dimensional model design.

[0062] Step S17: Using CAD software to construct a preliminary three-dimensional model of the cranial and brain position fixation device according to the design requirement data and preliminary design parameters.

[0063] The embodiment of the present invention uses CAD software to input the design requirement data and preliminary design parameters into the software to start building a preliminary three-dimensional model of the fixture, which includes the overall shape of the device, the support frame, the fixing components and the adjustment mechanism. During the modeling process, the model is adjusted in detail according to the requirement data, such as determining the shape of the fixing components to adapt to the patient's personalized head contour, and adjusting the range of the adjustment mechanism to meet the requirements of different surgical positions. After the preliminary model is completed, preliminary verification and evaluation are carried out to confirm whether the model can meet the basic functional requirements, laying the foundation for subsequent mechanical performance analysis and structural optimization.

[0064] The present invention uses 3D scanning technology to accurately obtain the shape of the patient's head and neck, ensuring that the device design can perfectly fit the patient's anatomical structure. Through image cutting and extraction of key anatomical feature points, a more accurate and personalized patient digital model can be established, which helps to improve the adaptability of the fixation device and the comfort of the patient. Collecting information on the type, duration and position of surgery helps to understand the specific requirements of different surgeries for fixation devices; this analysis ensures that the design can meet the needs of specific surgeries. Through the comfort evaluation table and the intelligent sensor system, the patient's physiological indicators can be monitored and evaluated in real time, so as to establish a comfort evaluation model, which helps to design a fixation device that is both safe and comfortable, and reduces the patient's discomfort during surgery. Accurate fixation accuracy is crucial for neurosurgery. By collecting the interaction requirements between surgical instruments and fixation devices and the accuracy requirements of different surgeries, it can be ensured that the device design meets high-precision fixation standards. By integrating the data on patient body shape, position requirements, comfort and fixation accuracy, a comprehensive data set of design requirements for cranial and brain position fixation devices can be obtained. This integration ensures that the design can comprehensively consider all key factors and improve the applicability and effectiveness of the device. Collecting clinical application information and usage scenario information can help generate preliminary design parameters that meet actual application needs, which helps ensure that the designed device is not only feasible in theory, but also performs optimally in actual applications. Using CAD software and design requirement data to build a preliminary three-dimensional model can intuitively display the design concept of the device. This step is a key link in converting abstract design requirements into specific models, laying the foundation for subsequent design optimization and prototyping. Overall, these steps ensure that the cranial and brain position fixation device can meet high medical standards while providing customized solutions for patients through precise data collection, personalized design, and in-depth understanding of surgical needs.

[0065] Preferably, step S17 comprises the following steps:

[0066] Step S171: importing the design requirement data and preliminary design parameters into the CAD software, establishing a design parameter library, and thus obtaining a design parameter data set;

[0067] The embodiment of the present invention imports the design requirement data (including patient body shape data, body position requirement data, comfort data and fixed precision data) and preliminary design parameters (such as material selection, support structure, etc.) collected and sorted in the early stage into the CAD software. The software needs to support the classification and management of data to ensure that these data can be effectively used for modeling. Create a design parameter library in the CAD software to classify and manage the imported data. The parameter library includes specific parameter values ​​of each data, such as geometric dimensions, shape characteristics, adjustment range, etc. This library will serve as the basis for subsequent modeling and design optimization, and provide support for parametric modeling.

[0068] Step S172: using a parametric modeling tool of the CAD software to create a basic geometric structure of the device according to the design parameter data set, thereby obtaining a basic geometric model;

[0069] The embodiment of the present invention uses the parametric modeling tool in the CAD software to create the basic geometric structure of the cranial and cerebral position fixation device according to the data set in the design parameter library. The basic geometric structure mainly includes the support frame of the device, the basic shape of the fixing parts, the preliminary structure of the adjustment mechanism, etc. According to the requirements in the design requirement data, the geometric models of the support frame, the fixing parts, etc. are established in turn. The model at this stage focuses on the overall geometric shape and basic functional layout, laying the foundation for subsequent detail optimization.

[0070] Step S173: adjusting the size and optimizing the shape of the basic geometric model based on the digital model of the patient's head and neck according to the patient's body shape data, thereby obtaining a matching optimized model;

[0071] The embodiment of the present invention imports the patient's personalized digital model (including accurate three-dimensional information of the head and neck) into the CAD software and matches it with the basic geometric model. The size and shape of the basic geometric model are adjusted to match the patient's body shape data. According to the patient's three-dimensional anatomical data, the various dimensional parameters of the basic geometric model, such as the curvature of the fixed parts, the size of the support frame, etc., are adjusted. Ensure that each part of the model is highly matched with the shape of the patient's head and neck to improve the stability and comfort of the device. After completing the matching optimization, a geometric model that is highly matched with the patient's personalized needs is generated, that is, a matching optimization model. This model will be used for subsequent structural function optimization.

[0072] Step S174: adding adjustable structures and mechanisms to the matching optimization model according to the body position requirement data, thereby obtaining a comfort optimization model;

[0073] The embodiment of the present invention adds adjustment structures and mechanisms to the matching optimization model according to different surgical types and body position requirements; these structures and mechanisms include adjustable fixed arms, flexible connecting parts, etc., which can adjust the patient's head position according to surgical needs to ensure comfort during the operation. Through parametric modeling tools, the size and position of each adjustment structure are finely adjusted to ensure that it can maintain optimal comfort within the adjustment range. Considering the changes in the patient's body position during long-term surgery, the design structure should have sufficient flexibility and stability. After completing the comfort optimization, a three-dimensional model with good comfort and adaptability is generated, namely the comfort optimization model. This model will continue to be improved in subsequent precision optimization.

[0074] Step S175: finely designing the comfort optimization model according to the fixed precision data, and adding precise positioning and fine-tuning mechanisms to obtain a precision optimization model;

[0075] The embodiment of the present invention introduces fixing accuracy data, and performs refined design for the comfort optimization model, especially adding precise positioning and fine-tuning mechanisms at key locations (such as the connection points of the fixing components, the positioning devices of the adjustment mechanisms, etc.), to ensure that the device can maintain extremely high fixing accuracy during surgery. According to the fixing accuracy requirements, the structural details of each component are optimized, including adding positioning scales, adjusting screws, etc., to ensure that the device can achieve millimeter-level precise adjustment during fine-tuning. The stability and durability of the adjustment mechanism should be fully considered during the design process. After completing the refined design, a model that can meet the surgical fixation accuracy requirements, namely the precision optimization model, is generated. This model is not only comfortable, but also ensures the high stability of the patient's head position during surgery.

[0076] Step S176: Perform assembly simulation and interference check processing on the precision optimized model to obtain a preliminary three-dimensional model of the cranial and brain position fixation device.

[0077] The embodiment of the present invention performs virtual assembly simulation in CAD software, and assembles the various components according to the design requirements; during the assembly process, the interfaces and connection points of the various components are checked to ensure that they can be smoothly spliced ​​and operated. Interference checks are performed to analyze the operating space of each component after assembly to ensure that no physical interference occurs; interference checks include checking the gaps between components of the device in different positions and adjustment states to avoid unnecessary friction or jamming during surgery. After completing the assembly simulation and interference checks, it is confirmed that the model has no design defects and a final preliminary three-dimensional model is generated; the model has complete functionality and can be used for subsequent mechanical analysis and production preparation.

[0078] The present invention imports the design requirement data and preliminary design parameters into the CAD software and establishes a design parameter library, which can ensure the consistency and traceability of the parameters in the design process; the creation of the design parameter data set provides a standardized input for subsequent model creation, which helps to improve the design efficiency and accuracy. Using the parametric modeling tool of the CAD software, the basic geometric structure of the device can be quickly created according to the design parameter data set; this step lays the foundation for subsequent personalized adjustment and optimization, and ensures the scalability and flexibility of the design. The basic geometric model is sized and optimized in shape according to the patient's body shape data, so that the device can better match the patient's head and neck anatomical structure. This personalized matching optimization model improves the adaptability of the device and the comfort of the patient. Adding adjustable structures and mechanisms to the matching optimization model can be fine-tuned according to the different needs of the patient to improve the comfort during the operation. This comfort optimization model helps to reduce the discomfort of the patient during long-term surgery. The comfort optimization model is refined according to the fixed accuracy data, and precise positioning and fine-tuning mechanisms are added to ensure that the fixing accuracy of the device meets the high standards of neurosurgery. Assembly simulation and interference checking of the precision-optimized model can identify and resolve assembly problems and interferences that may exist in the model. This step helps ensure the reliability and stability of the device in actual applications and avoids surgical risks caused by design defects. Overall, these steps ensure that the design of the cranial position fixation device meets both the patient's personalized needs and the high-precision requirements of surgery through precise parametric design, personalized adjustment, comfort and precision optimization, as well as assembly simulation and interference checking.

[0079] Preferably, step S2 comprises the following steps:

[0080] Step S21: extracting key geometric features of the support frame according to the preliminary three-dimensional model, and establishing a skeleton model of the support frame, thereby obtaining skeleton data of the support frame;

[0081] Step S22: constructing a three-dimensional model of the support frame based on the support frame skeleton data, thereby obtaining support frame model data, wherein the three-dimensional model of the support frame includes a main structure, connection nodes, and an adjustment mechanism interface;

[0082] Step S23: determining the position and shape of the fixed component according to the preliminary three-dimensional model, and establishing a basic model of the fixed component, thereby obtaining basic data of the fixed component;

[0083] Step S24: designing the precise structure of the fixing component based on the basic data of the fixing component, thereby obtaining the model data of the fixing component, wherein the precise structure of the fixing component includes the shape of the contact surface, the pressure distribution area and the fixing mechanism;

[0084] Step S25: analyzing the motion requirements of the regulating mechanism on the preliminary three-dimensional model, establishing a kinematic model of the regulating mechanism, and thereby obtaining kinematic data of the regulating mechanism;

[0085] Step S26: Designing a specific structure of the adjustment mechanism according to the kinematic data of the adjustment mechanism, thereby obtaining adjustment mechanism model data, wherein the specific structure of the adjustment mechanism includes an adjustment shaft, a locking device, and a fine adjustment mechanism;

[0086] Step S27: Integrate the supporting frame model data, the fixed component model data and the adjustment mechanism model data into a basic structure model;

[0087] Step S28: Generate an adjustable three-dimensional parametric model according to the basic structural model through a parametric design method.

[0088] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S2 in the embodiment of the present invention, step S2 includes the following steps:

[0089] Step S21: extracting key geometric features of the support frame according to the preliminary three-dimensional model, and establishing a skeleton model of the support frame, thereby obtaining skeleton data of the support frame;

[0090] The embodiment of the present invention extracts the key geometric features of the support frame from the preliminary three-dimensional model. The key features include the main structural lines of the frame, the positions of the connection nodes, the force paths, etc. These geometric features will be used to define the skeleton structure of the support frame. The CAD software's curve and point tools are used to create a skeleton model of the support frame based on the extracted key geometric features. The skeleton model is a simplified version of the support frame, which is mainly used to represent the overall structure and main stress-bearing parts of the frame. After the skeleton model is created, the skeleton data of the support frame is generated. This data will be used to construct a three-dimensional model of the support frame, providing a basis for the next detailed design.

[0091] Step S22: constructing a three-dimensional model of the support frame based on the support frame skeleton data, thereby obtaining support frame model data, wherein the three-dimensional model of the support frame includes a main structure, connection nodes, and an adjustment mechanism interface;

[0092] The embodiment of the present invention uses the support frame skeleton data to perform three-dimensional modeling in the CAD software, and constructs the main structure of the support frame, including support rods, cross beams, longitudinal beams, etc., by extending and expanding the skeleton lines. On the basis of the main structure of the support frame, the connection nodes and the adjustment mechanism interface are designed. The connection nodes need to ensure the stability and durability of the frame, while the adjustment mechanism interface needs to be compatible with the subsequent adjustment device to ensure that the device can be flexibly adjusted. After completing the three-dimensional modeling, the three-dimensional model data of the support frame is generated, and the model data includes the main structure of the frame, the connection nodes and the adjustment mechanism interface to ensure that the entire frame structure has sufficient stability and adaptability.

[0093] Step S23: determining the position and shape of the fixed component according to the preliminary three-dimensional model, and establishing a basic model of the fixed component, thereby obtaining basic data of the fixed component;

[0094] The embodiment of the present invention determines the specific position and approximate shape of the fixing component in the entire device according to the design requirements in the preliminary three-dimensional model. The design of the fixing component should comply with the principles of ergonomics to ensure that it can effectively fix the patient's head and neck. Use CAD software to create a basic geometric model of the fixing component, including the basic outline and preliminary structure of the fixing component, such as a fixing clamp, a support pad, etc. These basic models will serve as the basis for subsequent refined design. After completing the basic model design, the basic data of the fixing component is generated, which is used for the detailed design and optimization of the fixing component.

[0095] Step S24: designing the precise structure of the fixing component based on the basic data of the fixing component, thereby obtaining the model data of the fixing component, wherein the precise structure of the fixing component includes the shape of the contact surface, the pressure distribution area and the fixing mechanism;

[0096] The embodiment of the present invention performs precise structural design based on the basic data of the fixing component. The shape of the contact surface, the pressure distribution area, and the layout of the fixing mechanism need to be considered during the design to ensure that the fixing component can stably and comfortably fix the patient's head and neck. The shape of the contact surface is optimized to make it more consistent with the shape of the patient's head and neck to reduce pressure concentration and discomfort; the pressure distribution area is evaluated using finite element analysis (FEA) tools, and the design is adjusted to achieve optimal pressure distribution. Effective fixing mechanisms such as locking screws, buckles, or spring clamps are designed and integrated on the fixing component to ensure that the fixing component can be firmly locked during use and is easy to adjust and disassemble. After completing the precise structural design, detailed model data of the fixing component is generated, which will be used for integration and verification of the overall model.

[0097] Step S25: analyzing the motion requirements of the regulating mechanism on the preliminary three-dimensional model, establishing a kinematic model of the regulating mechanism, and thereby obtaining kinematic data of the regulating mechanism;

[0098] The embodiment of the present invention performs motion demand analysis on the adjustment mechanism in the preliminary three-dimensional model to determine the type and range of motion that needs to be achieved, such as rotation, translation, tilt, etc. The analysis needs to consider the patient's position adjustment requirements and possible adjustment requirements during the operation. Use the motion simulation tool in the CAD software to establish a kinematic model of the adjustment mechanism based on the results of the motion demand analysis; the model should simulate the actual motion behavior of the adjustment mechanism, including each degree of freedom of motion and possible adjustment paths. After the kinematic model is established, the kinematic data of the adjustment mechanism is output, and these data will be used for specific structural design to ensure that the adjustment mechanism can be flexibly adjusted within the expected range.

[0099] Step S26: Designing a specific structure of the adjustment mechanism according to the kinematic data of the adjustment mechanism, thereby obtaining adjustment mechanism model data, wherein the specific structure of the adjustment mechanism includes an adjustment shaft, a locking device, and a fine adjustment mechanism;

[0100] According to the kinematic data, the embodiment of the present invention performs the specific structural design of the adjustment mechanism in the CAD software, and the design content includes the adjustment shaft, the locking device and the fine adjustment mechanism; the adjustment shaft needs to have sufficient strength and rigidity, the locking device needs to be able to quickly and stably lock the adjustment position, and the fine adjustment mechanism is used for precise fine-tuning. The adjustment structure is optimized to ensure that it can be adjusted smoothly during operation and has good durability; the operation effect of the adjustment mechanism is checked by simulation tools, and the design is adjusted to meet the actual use requirements. After the design is completed, the detailed model data of the adjustment mechanism is generated, and these data will be used for the overall integration of the model.

[0101] Step S27: Integrate the supporting frame model data, the fixed component model data and the adjustment mechanism model data into a basic structure model;

[0102] The embodiment of the present invention integrates the support frame model data, the fixed component model data and the adjustment mechanism model data in the CAD software to ensure that the structure and function of each part model match after assembly and realize integrated design. During the data integration process, the interface matching, motion range and assembly tolerance of each part are checked, and necessary adjustments and optimizations are made to ensure that the structure of the entire device is complete and the functions are coordinated. After the integration is completed, the basic structural model of the device is generated, which provides the basis for the subsequent parametric design.

[0103] Step S28: Generate an adjustable three-dimensional parametric model according to the basic structural model through a parametric design method.

[0104] The embodiment of the present invention uses the parametric design function in the CAD software to convert the basic structural model into an adjustable three-dimensional parametric model, which allows the size, shape and function of the device to be quickly changed by adjusting the parameters to meet the needs of different patients. The generated three-dimensional parametric model is functionally verified to simulate the usage scenarios under different parameters to ensure the stability and adaptability of the model. After the verification, the model can be used for actual production and application. After completing the parametric design and verification, the final three-dimensional parametric model is output as the basis for subsequent model optimization and production.

[0105] The present invention can ensure the structural strength and stability of the support frame by extracting key geometric features. The skeleton model provides a clear and scalable foundation for subsequent design, so that designers can make more detailed adjustments and optimizations on this basis. The constructed three-dimensional model defines the main structure, connection nodes and adjustment mechanism interfaces in detail, which are the key to the functionality and stability of the support frame. The accuracy of the model data directly affects the accuracy of subsequent manufacturing and assembly, thereby ensuring the quality and performance of the final product. The establishment of the basic model is the starting point for the design of the fixed component, which determines the initial form of the fixed component in contact with the patient, which helps to evaluate the adaptability and possible improvement direction of the fixed component at an early stage. The precise structural design focuses on the contact surface shape, pressure distribution and fixation mechanism, which are key factors to ensure patient comfort and device stability. By optimizing these details, patient discomfort can be reduced and the fixation effect during surgery can be improved. The kinematic model analyzes the motion requirements of the adjustment mechanism and provides a dynamic perspective for the design; this helps to predict and optimize the mechanical properties during the adjustment process and ensure that the adjustment mechanism can respond smoothly and accurately to the doctor's operation. The specific structural design includes the adjustment axis, locking device and fine adjustment mechanism, which are the key components for precise control of the adjustment mechanism. By carefully designing these components, the reliability of the adjustment mechanism and the accuracy of operation can be ensured. The integrated model is to merge all the individually designed components into a coordinated system. This step ensures the compatibility between the components and the consistency of the overall design, and provides a complete blueprint for subsequent manufacturing and testing. The generation of parametric models is an innovation in the design process, which allows the design to be dynamically adjusted according to specific input parameters. This flexibility enables the design to quickly adapt to different patient needs and surgical conditions, improving the adaptability and practicality of the design. Through these steps, designers are able to create a highly customized, precisely controlled and user-friendly cranial position fixation device; each step contributes to the performance, safety and patient experience of the final product, ensuring the innovation and practicality of the design.

[0106] Preferably, step S28 comprises the following steps:

[0107] Step S281: defining key parameters of the basic structure model and establishing association relationships between the parameters, thereby obtaining parameter association data, wherein the key parameters include size parameters, angle parameters and shape parameters;

[0108] In the basic structural model of the embodiment of the present invention, key parameters are identified and defined, which generally include but are not limited to size parameters (such as length, width, height), angle parameters (such as rotation angle, tilt angle), and shape parameters (such as curvature radius, cross-sectional shape). Using the parametric design tool in the CAD software, these key parameters are set as adjustable variables so that they can be flexibly modified in the subsequent design process. Define the association relationship between the key parameters, which includes direct association (such as a fixed size ratio between two components) and indirect association (such as the effect of angle changes on the overall structural shape). Use the association tool in the CAD software to set the mathematical or geometric relationship between these parameters, so as to ensure that when a parameter is adjusted, the associated parameters will be automatically updated to maintain the overall consistency of the model. After completing the parameter definition and association relationship setting, the parameter association data is output. The data set includes all key parameters and their interrelated information to ensure the consistency and controllability of the parameters during subsequent model adjustment.

[0109] Step S282: constructing a parameter-driven three-dimensional model capable of automatic updating and adjustment functions according to the parameter association data, thereby obtaining parameterized model basic data;

[0110] The embodiment of the present invention uses CAD software to construct a parameter-driven three-dimensional model based on the parameter association data generated in step S281. This model should have automatic update and adjustment functions, and can update the geometric structure in real time according to different input parameter values. In the modeling process, key parameters are associated with various geometric features of the model so that when the parameters are modified, the model can automatically respond and make corresponding adjustments. Verify the automatic update function of the model, and check whether the geometric shape of the model can be correctly updated by adjusting the parameter values; ensure that the integrity and design goals of the model structure are maintained when the parameters change. Test for possible parameter limit conditions (such as maximum or minimum size) to ensure that the model can still maintain a reasonable structure and function under extreme conditions. After the modeling is completed and verified, the basic data of the parameterized model is output; these data include the geometric information of the model and the corresponding parameter control logic, which provide a basis for subsequent optimization and application.

[0111] Step S283: verify and test the reflection of parameter changes and model changes on the basic data of the parametric model, and perform optimization and adjustment to obtain an adjustable three-dimensional parametric model.

[0112] The embodiment of the present invention verifies the basic data of the parametric model. The specific steps include running the model under different parameter settings to observe whether the geometric structure changes of the model meet the expected design goals. Use simulation tools to simulate the impact of parameter changes on model performance, especially to check the mechanical properties, stability and operability of the model under different configurations. According to the verification results, the parameter association relationship and geometric structure of the model are optimized and adjusted. The goal of the optimization is to ensure that the model can exhibit stable performance under various possible parameter settings, while simplifying the user's parameter adjustment operations; correct possible parameter conflicts or unreasonable associations in the model to ensure the flexibility and accuracy of parameter adjustment. After completing the verification and optimization, an adjustable three-dimensional parametric model is finally generated. The model has a high degree of flexibility and can adapt to different design requirements by adjusting key parameters, and provides a reliable foundation for practical applications and manufacturing.

[0113] The present invention can ensure that the most critical influencing factors are paid attention to during the design process by defining key parameters of the basic structure model, including size, angle and shape parameters. Establishing the association relationship between parameters to form parameter association data lays the foundation for subsequent parametric modeling. This approach improves the flexibility and adjustability of the design, enables the design to quickly respond to changes in demand, and also facilitates design iteration and optimization. The parameter-driven three-dimensional model constructed using parameter association data realizes the automatic update and adjustment function of the model. Obtaining the basic data of the parametric model means that the designer can drive the change of the model by adjusting the parameter value without having to re-design the complex geometry. This method significantly improves the design efficiency, reduces the workload when modifying the design, and helps to realize the automation and intelligence of the design. The parameter change-model change reflection verification and testing of the basic data of the parametric model ensure that the response of the model to the parameter adjustment is correct and expected. Through optimization and adjustment, a more stable and reliable adjustable three-dimensional parametric model is obtained. This step is a key link to ensure the quality of the design, which helps to discover and correct potential problems of the model, thereby improving the accuracy and performance of the final product. Through these steps, the designer can create a highly flexible and configurable cranial and brain position fixation device model. The parametric design method makes the design process more efficient and provides a powerful tool for personalized customization and rapid iteration of products. This parameter-based design method is particularly important in engineering design and CAD modeling because it allows different design solutions to be generated by modifying parameters to meet the specific needs of different patients and surgeries.

[0114] Preferably, step S3 comprises the following steps:

[0115] Step S31: defining material properties required for mechanical analysis according to the three-dimensional parameterized model, thereby obtaining material property data, wherein the material properties include elastic modulus, Poisson's ratio and density;

[0116] The embodiment of the present invention selects suitable material types, such as metal, composite materials, plastics, etc., according to the design requirements and actual application scenarios of the cranial and brain position fixation device; considers the strength, stiffness, weight, comfort and other requirements that the device needs to meet, and selects suitable materials in the material database. In the finite element analysis (FEA) software, the specific property data of the selected material is input, mainly including: Elastic Modulus: represents the stiffness of the material, usually in Pascal (Pa); Poisson's Ratio: describes the ratio of the lateral strain caused by the longitudinal strain of the material; Density: affects the weight and inertia of the structure, usually in kilograms per cubic meter (kg / m³). The defined material properties are input into the FEA software, and the corresponding material property data is generated for subsequent mechanical analysis.

[0117] Step S32: determining the boundary conditions and load conditions of the mechanical analysis according to the preliminary design parameters, thereby obtaining boundary condition data, wherein the boundary conditions and load conditions include fixed support points, external forces and gravity;

[0118] The embodiment of the present invention determines the fixed support points of the device during use, which are usually areas where forces are concentrated, such as the contact points of the head and neck. In the FEA software, these fixed support points are set as the boundary conditions of the model to ensure that these points do not displace or rotate during analysis. Based on the preliminary design parameters, determine the external forces that the device may be subjected to during use, including operating force, patient's head weight, external forces during surgery, etc.; consider gravity as a constant load, and enter these load data in the FEA software. Import all determined boundary conditions and load conditions into the FEA software to generate corresponding boundary condition data for subsequent mechanical analysis.

[0119] Step S33: using finite element analysis software to mesh the three-dimensional parameterized model and generate a finite element model, thereby obtaining mesh model data;

[0120] In the FEA software of the embodiment of the present invention, the three-dimensional parametric model is meshed. The degree of detail of the meshing will affect the accuracy and calculation amount of the analysis. Usually, a finer mesh is used for key parts. Select a suitable mesh type (such as a tetrahedral mesh or a hexahedral mesh) and divide it to ensure that each part of the model can accurately reflect the mechanical properties. Based on the meshing results, a complete finite element model is generated. This model will be used for subsequent mechanical analysis and contains all nodes, units and their interrelated information. Export the generated mesh model data to ensure its integrity and accuracy, and prepare to enter the static and dynamic analysis stage.

[0121] Step S34: performing static analysis on the mesh model data according to the material property data and the boundary condition data, and calculating the stress distribution and deformation, thereby obtaining static analysis data;

[0122] In the embodiment of the present invention, in the FEA software, a static analysis is performed on the mesh model according to the input material property data and boundary condition data; the stress distribution and deformation of the model under static load are calculated, with a focus on stress concentration areas and parts with the largest deformation. The static calculation results are analyzed to evaluate the safety and reliability of the device under static load. The main focus is on whether there are stress points that exceed the yield strength of the material and whether the deformation is within the allowable range; the static analysis results are exported to generate detailed stress distribution diagrams, deformation diagrams and other data for subsequent analysis and optimization.

[0123] Step S35: performing a dynamic analysis based on vibration characteristics and dynamic response on the grid model data according to the material property data and the boundary condition data, thereby obtaining dynamic analysis data;

[0124] The embodiment of the present invention combines material property data and boundary condition data to perform dynamic analysis on the grid model, analyze the response of the model under vibration loads or dynamic external forces; focus on calculating the natural frequency, modal shape and dynamic response of the model at different frequencies. Evaluate the performance of the device under dynamic loads, especially to avoid the coincidence of the natural frequency and the external excitation frequency, which leads to resonance, and analyze the stability and comfort of the device under dynamic conditions. Export the dynamic analysis results, including modal analysis diagrams, frequency response diagrams, etc., to form dynamic analysis data.

[0125] Step S36: performing fatigue analysis on the reliability of the device under long-term use on the static analysis data and the dynamic analysis data, thereby obtaining fatigue analysis data;

[0126] The embodiment of the present invention performs fatigue analysis on the device based on static and dynamic analysis data, calculates the fatigue life of the device under long-term use, especially the cumulative damage under repeated loads; uses the stress life method or strain life method for analysis to predict possible fatigue damage locations of the device. Evaluate the reliability of the device within its designed service life to determine whether there is a potential risk of fatigue failure; if the fatigue life is found to be insufficient, consider optimizing the material or structural design. Export the fatigue analysis results to form a fatigue life curve and damage distribution diagram, providing a basis for subsequent optimization.

[0127] Step S37: performing stiffness and stability analysis of the device under various load conditions according to the fixed precision data and the material property data, thereby obtaining stiffness analysis data;

[0128] The embodiment of the present invention combines material property data and boundary condition data to analyze the stiffness and overall stability of the device under various load conditions, calculate the displacement and deformation of the device under external force, and determine whether its stiffness meets the design requirements. Evaluate the stiffness and stability performance of the device in different usage scenarios to ensure that it will not deform or become unstable in actual applications. If the stiffness is insufficient, it is necessary to consider strengthening the structure or adjusting the material. Export the stiffness analysis results to form data such as stiffness-deformation relationship diagrams and stability assessment reports.

[0129] Step S38: merging the static analysis data, dynamic analysis data, fatigue analysis data and stiffness analysis data into mechanical performance analysis data;

[0130] The embodiment of the present invention combines the static analysis data, dynamic analysis data, fatigue analysis data and stiffness analysis data to form a complete mechanical performance analysis report, and combines the various analysis results to form a comprehensive evaluation of the overall mechanical performance of the device. Based on the combined data, a comprehensive summary of the mechanical performance of the device is made, including the performance of the device in terms of strength, stiffness, stability, fatigue life, etc.

[0131] Step S39: Perform structural design optimization processing on the three-dimensional parameterized model according to the mechanical performance analysis data, and adjust the structural parameters in real time according to a preset fixed accuracy, so as to obtain structural parameter adjustment data.

[0132] The embodiment of the present invention performs structural design optimization processing on the three-dimensional parametric model based on the combined mechanical performance analysis data; adjusts the structural parameters of the model, such as material thickness, support layout, etc., based on the results of statics, dynamics, and fatigue analysis. During the optimization process, the structural parameters of the model are adjusted in real time to ensure that the optimized model can meet the design requirements and fixed accuracy requirements; the model is analyzed iteratively for multiple times until all performance indicators reach the expected goals. The final optimized model data is exported to generate structural parameter adjustment data to provide accurate design parameters for subsequent production and manufacturing.

[0133] The present invention provides necessary input parameters for finite element analysis by defining the material properties required for mechanical analysis, including elastic modulus, Poisson's ratio and density, to ensure the accuracy and reliability of the analysis results. Clarify the boundary conditions and load conditions of mechanical analysis, such as fixed support points, external forces and gravity, which are key factors in simulating the stress conditions of the device under actual working conditions, and help to obtain more realistic analysis data. The three-dimensional parametric model is meshed using finite element analysis software to generate a finite element model. This step is to convert the continuous geometric model into a discrete numerical model, laying the foundation for subsequent mechanical analysis. Static analysis is performed to calculate stress distribution and deformation, which helps to evaluate the mechanical properties of the device under static load and ensure its stability and safety in long-term fixed use. Based on dynamic analysis of vibration characteristics and dynamic response, the performance of the device under dynamic load, such as vibration resistance and dynamic strength, can be evaluated, which is essential for designing to resist external shocks and vibrations. Through fatigue analysis, the reliability of the device under long-term use is evaluated and possible fatigue damage is predicted, which is of great significance for improving the durability of the device and reducing maintenance costs. Performing stiffness and stability analysis to ensure that the device can maintain the predetermined shape and position under various load conditions and avoid instability is particularly important for ensuring accuracy and safety during surgery. The data from statics, dynamics, fatigue analysis, and stiffness analysis are combined to form a comprehensive mechanical performance analysis data set, which provides comprehensive feedback for design optimization and helps to make more reasonable design decisions. The three-dimensional parametric model is structurally optimized based on the mechanical performance analysis data, and the structural parameters are adjusted in real time according to the preset fixation accuracy, which helps to improve the overall performance of the device, meet the specific requirements of clinical use, and ensure patient comfort and surgical accuracy. Through these steps, it can be ensured that the actual needs of mechanical properties and clinical applications are fully considered during the design, analysis, and optimization of the cranial and brain position fixation device, and ultimately a safe and effective medical device is achieved.

[0134] Preferably, step S39 includes the following steps:

[0135] Step S391: identifying weak points and over-designed areas in the structure based on the mechanical performance analysis data, and generating optimization suggestions based on preset expert knowledge, thereby obtaining structural optimization suggestion data;

[0136] The embodiment of the present invention focuses on analyzing stress concentration areas, large deformation areas, and areas showing short fatigue life in fatigue analysis based on mechanical performance analysis data; using the post-processing function of the finite element analysis software, stress distribution diagrams, deformation diagrams, and fatigue life diagrams are generated to identify weak points in the structure. Analyze areas in the structure where the stress level is far below the material yield strength, as well as areas where the stiffness and strength far exceed the design requirements; by comparing with the design requirements, it is determined that these areas may be over-designed, resulting in material waste or excessive structural weight. Based on the identified weak points and over-designed areas, combined with a preset expert knowledge base, structural optimization suggestions are generated; the expert knowledge base may contain optimization methods for common structural problems, such as adding stiffeners, adjusting wall thickness, changing materials, etc., and outputs structural optimization suggestion data as a basis for subsequent structural modifications.

[0137] Step S392: performing local geometric modification on the three-dimensional parameterized model by adding reinforcing ribs and adjusting wall thickness according to the structural optimization suggestion data, thereby obtaining structural modification data;

[0138] In the embodiment of the present invention, in the identified weak point area, according to the optimization suggestion, reinforcing ribs are added. The function of the reinforcing ribs is to disperse the stress and increase the strength and rigidity of the structure. In the CAD or FEA software, parametric modeling tools are used to design and add reinforcing ribs of appropriate shape and position to ensure that the reinforcing ribs can effectively improve the mechanical properties. For the over-designed area, the wall thickness is adjusted. Reducing the wall thickness can reduce material usage and weight and optimize structural performance. In the CAD software, the wall thickness of the over-designed area is gradually reduced, and the impact on the structural performance is observed to ensure that the mechanical requirements can still be met after adjustment. The results of the local geometric modification are exported to generate structural modification data, including the added reinforcing rib information and the adjusted wall thickness data.

[0139] Step S393: updating the parameters of the three-dimensional parameterized model based on the structural modification data based on the structural optimization, thereby obtaining parameter update data;

[0140] The embodiment of the present invention updates the relevant parameters of the three-dimensional parametric model according to the structural modification data; it mainly involves the adjustment of the size and position parameters of the reinforcement ribs, as well as the wall thickness parameters; it ensures that the correlation between the parameters remains consistent, and the updated model can automatically adapt to these local geometric modifications. The updated parametric model is reversely verified to ensure that the modified model still meets the design requirements when other parameters change; the effectiveness of the structural modification is verified through simulation tests to ensure that the model is improved in both performance and accuracy. The model parameter data that has passed the verification is exported to form parameter update data, which provides a basis for subsequent accuracy evaluation and iterative optimization.

[0141] Step S394: establishing an accuracy evaluation model according to the preset fixed accuracy requirement, and analyzing the impact of structural parameter changes on the fixed accuracy according to the accuracy evaluation model, thereby obtaining accuracy impact data;

[0142] The embodiment of the present invention establishes an accuracy evaluation model according to the preset fixed accuracy requirements. The accuracy evaluation model includes the geometric accuracy, assembly accuracy, and positioning accuracy of the model during operation; in FEA or CAD software, the specific parameters of the fixed accuracy requirements are input to generate an accuracy evaluation model. Using the accuracy evaluation model, the impact of structural parameter changes on the fixed accuracy is analyzed, focusing on whether the model after structural modification can still meet the preset fixed accuracy requirements; comparing the accuracy changes before and after the modification, identifying parameter adjustments that may cause a decrease in accuracy, and analyzing their impact. The analysis results are exported to form accuracy impact data, and the specific impact of parameter changes on accuracy is recorded to provide a basis for subsequent iterative optimization.

[0143] Step S395: performing iterative optimization based on a preset fixed precision on the three-dimensional parameterized model according to the precision influencing data and the precision evaluation model, thereby obtaining iterative optimization data;

[0144] The embodiment of the present invention performs iterative precision optimization on the three-dimensional parametric model based on the precision influencing data, and adjusts the model parameters to reduce or eliminate the adverse effects on the precision. In each iteration, the mechanical properties analysis and precision evaluation are re-performed to ensure that the optimized model still has excellent mechanical properties while meeting the precision requirements. Combined with multi-objective optimization technology, the mechanical properties and fixed precision of the model are balanced, and the best optimization solution is found by adjusting the position of the reinforcement ribs, the wall thickness distribution or the material properties; gradually converge to the optimal parameter combination to ensure that the model reaches the preset goals in all performance indicators. The final optimized parametric model is exported to generate iterative optimization data to provide optimization results for the final data integration and alignment.

[0145] Step S396: integrating and aligning the mechanical performance analysis data, structural optimization suggestion data, structural modification data, parameter update data, precision impact data, and iterative optimization data based on the three-dimensional parametric model to obtain structural parameter adjustment data.

[0146] The embodiment of the present invention integrates mechanical property analysis data, structural optimization suggestion data, structural modification data, parameter update data, precision impact data and iterative optimization data; ensures that all data are aligned in a unified model to avoid model inconsistency due to differences in different data sources. In the three-dimensional parametric model, the integrated data is aligned, especially to ensure that the parametric model is consistent with the actual design requirements, and all modifications and optimizations can be accurately reflected in the final model. The final model verification is performed using the verification tool of the CAD software to ensure that the integrated model meets the design goals in terms of precision, mechanical properties, structural optimization, etc. The aligned final model data is exported to form complete structural parameter adjustment data as the final design output, providing a reference basis for actual production.

[0147] By identifying weak points and over-designed areas in the structure, the present invention can propose targeted improvement measures to avoid material waste, enhance the performance of the device in key parts, and improve the overall mechanical efficiency and safety. Local geometric modification of the three-dimensional parametric model, such as adding reinforcing ribs or adjusting wall thickness, can improve the mechanical properties of the structure, enhance the bearing capacity of key areas, and reduce the weight of non-key areas. The model parameters are updated based on the structural modification data to ensure that the design reflects the latest optimization results and provide accurate data support for subsequent analysis and manufacturing. By establishing an accuracy evaluation model and analyzing the impact of structural parameter changes on the fixation accuracy, it can be ensured that the device can still meet the preset accuracy requirements after adjustment, and ensure stability and reliability during surgery. Iterative optimization is performed according to the accuracy impact data, and the design is gradually adjusted until all design requirements are met. This method helps to find the optimal solution and optimize the design performance. All relevant data are integrated and aligned to ensure the consistency and coordination of the design, avoid problems caused by data inconsistency, and provide a solid data foundation for the final design confirmation and manufacturing. Through these steps, the design team can ensure that the design of the cranial position fixation device achieves structural optimization while meeting clinical needs, and improves the market competitiveness of the product and the success rate of clinical application.

[0148] Preferably, step S4 comprises the following steps:

[0149] Step S41: Acquire device usage data in different clinical application scenarios;

[0150] The embodiments of the present invention collect the actual usage data of the device in multiple different clinical application scenarios, including but not limited to neurosurgery, head imaging examination, rehabilitation treatment, etc.; use sensors, cameras, operation logs and other tools to record the device's operating status, usage frequency, device adjustment and response, and patient feedback in different scenarios. The collected usage data is classified by scenario, such as surgery type, surgery duration, patient size, operation difficulty, etc.; ensure that the data of each clinical scenario is fully recorded for subsequent analysis.

[0151] Step S42: cleaning and preprocessing the original usage data to obtain effective usage data;

[0152] The embodiments of the present invention remove noise, outliers, and incomplete records from the original usage data; for example, delete erroneous data caused by sensor failure or incomplete operation steps, and format the data to unify it into a format that is easy to analyze. Standardize or normalize the processed data to ensure comparability between different data sources; interpolate or remove missing data to ensure data integrity; store the cleaned and preprocessed data as valid usage data for subsequent adaptability evaluation.

[0153] Step S43: constructing a device adaptability evaluation index system according to the effective use data, thereby obtaining adaptability evaluation index data, wherein the device adaptability evaluation index system includes functional adaptability, operational adaptability and comfort adaptability;

[0154] The embodiment of the present invention establishes an adaptability evaluation index system according to different clinical application scenarios and functional requirements of the device. The index system includes key evaluation dimensions such as functional adaptability, operational adaptability, and comfort adaptability. Functional adaptability: evaluates the adaptability of the device in various surgeries, such as positioning accuracy, fixation effect, etc.; operational adaptability: evaluates the ease of use of the device in the hands of different operators, including operation complexity, adjustment difficulty, etc.; comfort adaptability: evaluates the impact of the device on the patient's comfort during use, including pressure distribution, head fixation feeling, etc. Quantitative indicators are set for each evaluation dimension, and their weights are determined; for example, functional adaptability may include positioning accuracy (accounting for 30%), fixation effect (accounting for 20%), etc. The rationality and scientificity of these indicators are determined through expert consultation or literature research; the constructed index system and its quantitative indicators are converted into adaptability evaluation index data as input to the evaluation model.

[0155] Step S44: quantitatively scoring the performance of the device in various clinical scenarios according to the adaptability evaluation index data and the effective use data, thereby obtaining adaptability evaluation data;

[0156] The embodiment of the present invention quantitatively scores each adaptability evaluation indicator based on effective use data; for example, by analyzing the positioning accuracy data of the device during surgery, its score in terms of functional adaptability is obtained. Data statistical tools are used to comprehensively score the adaptability performance in different scenarios and generate a score table. The quantitative scores are combined according to the weights in the indicator system to obtain the overall adaptability score of the device in different clinical scenarios, and the scoring results are organized into adaptability evaluation data for subsequent analysis.

[0157] Step S45: Analyze the advantages and disadvantages of the device in different scenarios on the adaptability evaluation data, so as to obtain adaptability analysis data; compare and analyze the structural parameter adjustment data according to the adaptability analysis data, and determine the specific parameters and adjustment ranges that need to be adjusted, so as to obtain parameter adjustment solution data;

[0158] The embodiment of the present invention analyzes the adaptability assessment data to identify the advantages and disadvantages of the device in different clinical scenarios; for example, if the operational adaptability score of the device is low in a specific type of surgery, it may indicate that the operation is difficult in this scenario and design optimization is required. Combined with the adaptability analysis results, compared with the current structural parameter adjustment data, determine the specific parameters that need to be adjusted (such as structural size, material selection, fixing method, etc.); determine the range and direction of each adjustment parameter (such as increasing / decreasing a certain size or increasing the flexibility of a certain component), form a detailed parameter adjustment plan, and organize all analysis and adjustment suggestions into parameter adjustment plan data as a basis for subsequent design corrections.

[0159] Step S46: Adaptively modifying the structural parameter adjustment data according to the parameter adjustment scheme data to generate multiple design schemes, thereby obtaining multi-scheme design data;

[0160] The embodiment of the present invention adaptively modifies the current structural parameter adjustment data according to the parameter adjustment scheme data, and the modification content includes adjusting the geometric structure of the device, optimizing the operation interface, improving the comfort, etc.; multiple design schemes are generated for different modification schemes to cover all possible optimization directions. CAD software or other design tools are used to apply the modified parameters to the three-dimensional model to generate multiple different design schemes; each design scheme should have high operability and be able to be tested in actual applications; all generated design schemes are organized into multi-scheme design data as input for subsequent multi-objective optimization.

[0161] Step S47: Perform multi-objective optimization calculations on the multi-scheme design data using multi-objective optimization technology, and use the Pareto optimal solution to optimize the results, thereby obtaining the optimal design window data.

[0162] The embodiment of the present invention uses a multi-objective optimization algorithm (such as genetic algorithm, particle swarm optimization, etc.) to optimize the multi-scheme design data; the optimization objectives include but are not limited to structural strength, operational convenience, comfort, cost control, etc. Through optimization calculation, the best balance point between these objectives is found. Through the concept of Pareto optimal solution, multiple non-inferior solutions are screened out, representing the optimal solution set under different weights; the optimal solution is compared with the design requirements, and the most suitable design solution is finally determined. The optimal design solution is refined into the optimal design window data as a reference for the final design solution, and provides data support for subsequent prototyping and practical application.

[0163] By collecting the device usage data in different clinical application scenarios, the present invention can fully understand the performance and existing problems of the device in actual use, and provide the original basis for subsequent data analysis and optimization. Data cleaning and preprocessing of the original usage data can remove invalid, erroneous or incomplete data, improve data quality, and ensure the accuracy and reliability of the analysis results. According to the effective use data, a device adaptability evaluation index system is constructed, covering functional adaptability, operational adaptability and comfort adaptability, which can systematically evaluate the comprehensive performance of the device and provide direction for improvement. The performance of the device in various clinical scenarios is quantitatively scored to obtain adaptability evaluation data, which can objectively evaluate the adaptability level of the device and provide a basis for subsequent optimization. By analyzing the adaptability evaluation data, the advantages and disadvantages of the device in different scenarios are determined, the structural parameter adjustment data is compared and analyzed, the specific parameters and ranges that need to be adjusted are clarified, and the parameter adjustment scheme data is obtained to provide specific guidance for the optimization design. According to the parameter adjustment scheme data, the structural parameters are adapted and corrected, multiple design schemes are generated, and multi-scheme design data is obtained to provide options for the final optimization decision. Multi-objective optimization technology is used to calculate the design data of multiple schemes, and the optimization results are selected in combination with the Pareto optimal solution to obtain the optimal design window data, optimize the design performance, and ensure that the device can achieve the best performance in different clinical scenarios. Through these steps, it can be ensured that the design of the cranial and brain position fixation device not only meets clinical needs, but also can show good adaptability and performance in different application scenarios.

[0164] Preferably, step S5 comprises the following steps:

[0165] Step S51: Generate a 3D printing file according to the optimized design window data, and select 3D printing materials and processes to obtain 3D printing manufacturing data;

[0166] The embodiment of the present invention uses 3D modeling software to import the optimized design window data to generate a three-dimensional model file consistent with the final design; export the model file to a format suitable for 3D printing (such as STL, OBJ, etc.), and perform layered slicing processing of the file according to the requirements of the printing device to generate a G code file readable by the 3D printer. According to the functional requirements, mechanical performance requirements, and use conditions of the clinical environment of the device, select suitable 3D printing materials; commonly used materials include biocompatible materials (such as medical grade resins), high-strength plastics (such as nylon), metal alloys, etc., and strength, durability, comfort and weight need to be considered when selecting materials. According to the complexity of the material and the device, select a suitable 3D printing process, such as SLA (stereolithography), SLS (selective laser sintering), FDM (fused deposition modeling), etc.; determine the printing parameters (such as layer thickness, printing speed, filling rate, etc.) to ensure printing accuracy and surface quality; combine the above materials and process parameters to generate complete 3D printing manufacturing data, ready for use in the printing stage.

[0167] Step S52: using high-precision 3D printing equipment to produce a device prototype according to the 3D printing manufacturing data, and performing support removal, surface treatment and fine processing to obtain a finished prototype;

[0168] The embodiment of the present invention uses high-precision 3D printing equipment to print the device prototype according to the generated 3D printing manufacturing data; during the printing process, the parameters such as temperature, speed and material consumption in the printing process are monitored to ensure the printing quality and accuracy. After the printing is completed, the support structure generated during the printing process is removed to ensure that the appearance and function of the prototype are not affected; the support removal can be done by hand tools or mechanical equipment to ensure the integrity of the details of the prototype. The prototype is surface treated, including grinding, polishing and cleaning, to ensure that the surface is smooth and flawless, and meets the hygiene requirements of medical devices; for the prototype of metal materials, the surface can be oxidized or electroplated to improve corrosion resistance and biocompatibility. Necessary finishing treatments are carried out, such as drilling, grooving, assembly, etc., to ensure that the various components of the prototype can be accurately matched; special coatings or coatings are added to the required parts to enhance the functionality of the prototype (such as antibacterial coatings, wear-resistant coatings, etc.), and the prototypes that have been processed and surface treated are sorted into finished prototypes, ready for the next step of clinical simulation testing.

[0169] Step S53: Perform clinical simulation tests using the finished prototype and collect feedback information to obtain prototype device feedback data, wherein the prototype device feedback data includes simulation test data and user feedback data;

[0170] The embodiment of the present invention uses the finished prototype for clinical simulation testing, simulating real surgical or treatment scenarios, and evaluating the performance of the device under various conditions; the test content includes fixation accuracy, stability, ease of operation, and comfort for patients. Invite doctors, surgical nurses and other relevant personnel to use the finished prototype, and collect their feedback on use, and collect feedback from patients or subjects, especially the comfort and fixation effect of the device during use. The performance data and user feedback obtained in the simulation test are organized into prototype device feedback data, including specific simulation test data (such as mechanical data, operation time, etc.) and user subjective evaluation.

[0171] Step S54: Perform function and adaptability evaluation on the finished prototype according to the prototype device feedback data, so as to obtain the final prototype evaluation data, wherein the adaptability evaluation includes fixation effect, adjustment accuracy, ease of operation and adaptability to different clinical scenarios.

[0172] The embodiment of the present invention evaluates the core functions of the device based on the feedback data of the prototype device to determine whether its performance in terms of fixation effect, adjustment accuracy, etc. meets expectations; if some functions perform poorly, analyze the reasons and record possible directions for improvement. The adaptability of the device in different clinical scenarios is evaluated, especially the matching degree with actual surgical operations, compatibility with different types of patients, etc.; the stability of the fixation effect, the ease of adjustment accuracy, the comfort of the device, and its applicability in various types of surgeries. The results of the functional evaluation and adaptability evaluation are organized into the final prototype evaluation data, recording the various performance indicators of the device and its performance in actual applications; based on the evaluation results, decide whether further design improvements are needed or whether to enter the large-scale production stage.

[0173] The present invention generates a 3D printing file according to the optimized design window data, ensuring seamless connection from design to manufacturing. Selecting appropriate 3D printing materials and processes is crucial to ensuring the quality and performance of the prototype, and can ensure that the printed prototype meets specific mechanical and physical requirements. Using high-precision 3D printing equipment to make a device prototype can achieve accurate presentation of design details; support removal, surface treatment and finishing can improve the appearance quality of the prototype, ensure its surface finish and dimensional accuracy, and thus obtain a high-quality finished prototype. Through clinical simulation testing, the performance of the prototype can be evaluated under conditions close to the real surgical environment. Collecting simulation test data and user feedback can fully understand the performance of the prototype in actual use and provide a basis for further optimization. Functional and adaptability evaluation of the finished prototype, including fixation effect, adjustment accuracy, ease of operation, and adaptability to different clinical scenarios, can ensure the effectiveness and applicability of the prototype in actual surgery; the evaluation data provides key feedback for the design of the final product, helps to improve the design, and improves the patient's surgical experience. Through these steps, it can be ensured that the prototype of the cranial position fixation device meets high standards in the design, manufacturing and testing process, meets clinical needs, and provides a solid foundation for the development of the final product.

[0174] Preferably, step S6 comprises the following steps:

[0175] Step S61: identifying the improvement needs of key design parameters and structural features according to the prototype evaluation data, thereby obtaining model optimization direction data;

[0176] The embodiment of the present invention conducts a detailed analysis of the prototype evaluation data, including the functional evaluation and adaptability evaluation results; identifies key problem areas in the design, such as insufficient functionality, comfort issues, structural instability, etc. Determine which design parameters (such as size, material, shape) and structural features (such as support components, fixing mechanisms) need to be improved; and determine the priority and goals of improvement based on the evaluation data. Based on the identified improvement needs, generate model optimization direction data, specifically specifying the design parameters and structural features that need to be improved, and this data will serve as the basis for subsequent adjustments and optimizations.

[0177] Step S62: systematically adjusting the design parameters of the three-dimensional parameterized model according to the model optimization direction data, thereby obtaining parameter adjustment data;

[0178] The embodiment of the present invention formulates a systematic parameter adjustment plan, including the adjustment range, adjustment method and expected effect; determines specific parameter adjustment targets, such as changing the thickness of the material, adjusting the geometric shape of the structure, etc. According to the model optimization direction data, adjust the design parameters in the three-dimensional parametric model; use CAD software to modify the model, including size adjustment, shape optimization, etc. Perform preliminary verification to ensure that the model after parameter adjustment meets the expected improvement goals; perform necessary analysis and testing on the adjusted model to confirm the improvement effect; record the adjusted parameters and generate parameter adjustment data for subsequent constraint updates and final model confirmation.

[0179] Step S63: updating the constraint conditions of the three-dimensional parameterized model based on the parameter adjustment data, thereby obtaining constraint update data, wherein the constraint conditions include geometric constraints, assembly constraints, and performance constraints;

[0180] The embodiment of the present invention analyzes the current constraints, including geometric constraints (such as size restrictions), assembly constraints (such as component matching), performance constraints (such as load capacity), etc., and identifies the constraints that need to be updated based on the parameter adjustment data. In the three-dimensional parametric model, the constraints are updated to match the new design parameters; including adjusting the geometric constraints (such as size range), assembly constraints (such as matching tolerance), performance constraints (such as stress limits), etc., recording the updated constraints, and generating constraint update data for the final confirmation of the model.

[0181] Step S64: performing final parameter locking and model confirmation on the three-dimensional parametric model according to the parameter adjustment data and the constraint update data, thereby obtaining a final parametric model;

[0182] The embodiment of the present invention locks the final design parameters of the three-dimensional parametric model based on the parameter adjustment data and the constraint update data, ensuring that all design parameters and constraint conditions meet the actual needs and there is no need for further modification. The final locked parametric model is comprehensively checked and confirmed, including functions, structures, performance, etc., ensuring that the model meets all design requirements and meets production and use standards; the confirmed model is saved as the final three-dimensional parametric model data to prepare for the subsequent generation of engineering drawings.

[0183] Step S65: converting the final parametric model data into a standardized engineering drawing format, including assembly drawings, parts drawings, and dimension annotations, thereby obtaining engineering drawing data;

[0184] The embodiment of the present invention uses CAD software to convert the final parametric model data into a standardized engineering drawing format; including generating detailed assembly drawings, parts drawings, dimension annotations, etc.; making assembly drawings to display the overall structure of the device and the relative positions of each component, marking key dimensions and assembly sequence; making parts drawings to display the detailed design of each component, including size, shape, hole position, etc., to ensure that each part has clear guidance for manufacturing and assembly; marking all necessary dimensions on the drawings, including tolerances and precision requirements, to ensure the accuracy and completeness of the drawings, and to facilitate production and assembly. All drawings are merged into standardized engineering drawing data and saved in a format suitable for production (such as PDF, DWG, etc.).

[0185] Step S66: Generate technical documents required for production based on the engineering drawing data, thereby obtaining final model production drawing data.

[0186] The embodiment of the present invention compiles the technical documents required for production based on the engineering drawing data, including production process description, material specifications, quality control standards, etc.; including the production process, processing requirements, assembly guidelines, testing standards, etc. of the device, to ensure that the documents are detailed and accurate, covering all technical requirements for production and assembly; integrates the technical documents with the engineering drawing data to generate the final model production drawing data; ensures that all information in the production process is fully supported to facilitate production, quality control and assembly.

[0187] The present invention analyzes prototype evaluation data, identifies the improvement requirements of key design parameters and structural features, and provides a clear direction for model optimization. This helps to improve the pertinence and effectiveness of the design. The design parameters of the three-dimensional parametric model are adjusted according to the optimization direction data, ensuring the systematicness and consistency of the design parameters, thereby improving the performance and reliability of the model. The constraints of the three-dimensional parametric model are updated, including geometric, assembly and performance constraints, providing the necessary design restrictions for the model, ensuring the manufacturability and functionality of the design. The final parameter locking and confirmation of the three-dimensional parametric model marks the completion of the design stage and provides a deterministic basis for the final manufacture of the model. The final parametric model data is converted into a standardized engineering drawing format, including assembly drawings, part drawings and dimensioning, which provides detailed technical guidance and basis for production. The technical documents required for production are generated according to the engineering drawing data, ensuring the standardization and systematization of the production process, and improving production efficiency and product quality. Through these steps, the design of the cranial and brain position fixation device is systematically optimized and confirmed, laying a solid foundation for the production of high-quality medical equipment.

[0188] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0189] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A three-dimensional parametric design method for a cranial and brain position fixation device, characterized in that: The following steps are involved: Step S1: obtaining design requirement data of the cranial and brain position fixation device, including patient body shape data, position requirement data, comfort data, and fixation accuracy data; Collect clinical application information and usage scenario information to obtain preliminary design parameters; use CAD software to construct a preliminary three-dimensional model of the cranial and brain position fixation device according to the design requirement data and preliminary design parameters; Step S2: constructing a basic structural model of the device according to the preliminary three-dimensional model, including a supporting frame model, a fixed component model, and an adjustment mechanism model; generating an adjustable three-dimensional parametric model according to the basic structural model by a parametric design method; Step S3: performing mechanical property analysis on the three-dimensional parameterized model to obtain mechanical property analysis data; Perform structural design optimization processing on the three-dimensional parametric model according to the mechanical performance analysis data, and adjust the structural parameters in real time according to the preset fixed accuracy to obtain structural parameter adjustment data; Step S4: Acquire device usage data in different clinical application scenarios; Conduct an adaptability assessment on the device usage data to obtain adaptability assessment data; adapt and correct the structural parameter adjustment data based on the adaptability assessment data, and obtain the optimal design solution through multi-objective optimization technology to obtain the optimal design window data; Step S5: using 3D printing technology to produce a device prototype according to the optimized design window data, and conducting clinical simulation tests to collect feedback information, thereby obtaining prototype device feedback data; performing function and adaptability evaluation on the prototype according to the prototype device feedback data, thereby obtaining prototype evaluation data; Step S6: updating the design parameters and constraints of the three-dimensional parametric model according to the prototype evaluation data, thereby obtaining a final parametric model; converting the final parametric model into a production drawing, thereby obtaining model production drawing data.

2. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: using 3D scanning technology to obtain accurate three-dimensional information of the patient's head and neck, thereby obtaining the patient's three-dimensional scanning data; performing image segmentation on the patient's three-dimensional scanning data, extracting key anatomical feature points, and establishing a personalized digital model of the patient, thereby obtaining the patient's body shape data; Step S12: collecting information on the type of surgery, duration of surgery, and surgical position, and analyzing the requirements of different types of surgery for cranial and brain position fixation devices, thereby generating position requirement data; Step S13: establishing a comfort evaluation model according to a preset comfort evaluation table and collecting the patient's physiological indicators in real time through an intelligent sensor system, thereby obtaining comfort data; Step S14: collecting the interaction requirements between the surgical instrument and the fixation device and the accuracy requirements of different types of neurosurgery, so as to obtain fixation accuracy data; Step S15: integrating the patient's body shape data, body position requirement data, comfort data, and fixation accuracy data, thereby obtaining design requirement data for the cranial body position fixation device; Step S16: Collect clinical application information and usage scenario information to obtain preliminary design parameters; Step S17: Using CAD software to construct a preliminary three-dimensional model of the cranial and brain position fixation device according to the design requirement data and preliminary design parameters.

3. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 2, characterized in that: Step S17 includes the following steps: Step S171: importing the design requirement data and preliminary design parameters into the CAD software, establishing a design parameter library, and thus obtaining a design parameter data set; Step S172: using a parametric modeling tool of the CAD software to create a basic geometric structure of the device according to the design parameter data set, thereby obtaining a basic geometric model; Step S173: adjusting the size and optimizing the shape of the basic geometric model based on the digital model of the patient's head and neck according to the patient's body shape data, thereby obtaining a matching optimized model; Step S174: adding adjustable structures and mechanisms to the matching optimization model according to the body position requirement data, thereby obtaining a comfort optimization model; Step S175: finely designing the comfort optimization model according to the fixed precision data, and adding precise positioning and fine-tuning mechanisms to obtain a precision optimization model; Step S176: Perform assembly simulation and interference check processing on the precision optimized model to obtain a preliminary three-dimensional model of the cranial and brain position fixation device.

4. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 3, characterized in that: Step S2 includes the following steps: Step S21: extracting key geometric features of the support frame according to the preliminary three-dimensional model, and establishing a skeleton model of the support frame, thereby obtaining skeleton data of the support frame; Step S22: constructing a three-dimensional model of the support frame based on the support frame skeleton data, thereby obtaining support frame model data, wherein the three-dimensional model of the support frame includes a main structure, connection nodes, and an adjustment mechanism interface; Step S23: determining the position and shape of the fixed component according to the preliminary three-dimensional model, and establishing a basic model of the fixed component, thereby obtaining basic data of the fixed component; Step S24: designing the precise structure of the fixing component based on the basic data of the fixing component, thereby obtaining the model data of the fixing component, wherein the precise structure of the fixing component includes the shape of the contact surface, the pressure distribution area and the fixing mechanism; Step S25: analyzing the motion requirements of the regulating mechanism on the preliminary three-dimensional model, establishing a kinematic model of the regulating mechanism, and thereby obtaining kinematic data of the regulating mechanism; Step S26: Designing a specific structure of the adjustment mechanism according to the kinematic data of the adjustment mechanism, thereby obtaining adjustment mechanism model data, wherein the specific structure of the adjustment mechanism includes an adjustment shaft, a locking device, and a fine adjustment mechanism; Step S27: Integrate the supporting frame model data, the fixed component model data and the adjustment mechanism model data into a basic structure model; Step S28: Generate an adjustable three-dimensional parametric model according to the basic structural model through a parametric design method.

5. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 4, characterized in that: Step S28 includes the following steps: Step S281: defining key parameters of the basic structure model and establishing association relationships between the parameters, thereby obtaining parameter association data, wherein the key parameters include size parameters, angle parameters and shape parameters; Step S282: constructing a parameter-driven three-dimensional model capable of automatic updating and adjustment functions according to the parameter association data, thereby obtaining parameterized model basic data; Step S283: verify and test the reflection of parameter changes and model changes on the basic data of the parametric model, and perform optimization and adjustment to obtain an adjustable three-dimensional parametric model.

6. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 5, characterized in that: Step S3 includes the following steps: Step S31: defining material properties required for mechanical analysis according to the three-dimensional parameterized model, thereby obtaining material property data, wherein the material properties include elastic modulus, Poisson's ratio and density; Step S32: determining the boundary conditions and load conditions of mechanical analysis according to the preliminary design parameters, thereby obtaining boundary condition data, wherein the boundary conditions and load conditions include fixed support points and external forces; Step S33: using finite element analysis software to mesh the three-dimensional parameterized model and generate a finite element model, thereby obtaining mesh model data; Step S34: performing static analysis on the mesh model data according to the material property data and the boundary condition data, and calculating the stress distribution and deformation, thereby obtaining static analysis data; Step S35: performing a dynamic analysis based on vibration characteristics and dynamic response on the grid model data according to the material property data and the boundary condition data, thereby obtaining dynamic analysis data; Step S36: performing fatigue analysis on the reliability of the device under long-term use on the static analysis data and the dynamic analysis data, thereby obtaining fatigue analysis data; Step S37: performing stiffness and stability analysis of the device under various load conditions according to the fixed precision data and the material property data, thereby obtaining stiffness analysis data; Step S38: merging the static analysis data, dynamic analysis data, fatigue analysis data and stiffness analysis data into mechanical performance analysis data; Step S39: Perform structural design optimization processing on the three-dimensional parameterized model according to the mechanical performance analysis data, and adjust the structural parameters in real time according to a preset fixed accuracy, so as to obtain structural parameter adjustment data.

7. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 6, characterized in that: Step S39 includes the following steps: Step S391: identifying weak points and over-designed areas in the structure based on the mechanical performance analysis data, and generating optimization suggestions based on preset expert knowledge, thereby obtaining structural optimization suggestion data; Step S392: performing local geometric modification on the three-dimensional parameterized model by adding reinforcing ribs and adjusting wall thickness according to the structural optimization suggestion data, thereby obtaining structural modification data; Step S393: updating the parameters of the three-dimensional parameterized model based on the structural modification data based on the structural optimization, thereby obtaining parameter update data; Step S394: establishing an accuracy evaluation model according to the preset fixed accuracy requirement, and analyzing the impact of structural parameter changes on the fixed accuracy according to the accuracy evaluation model, thereby obtaining accuracy impact data; Step S395: performing iterative optimization based on a preset fixed precision on the three-dimensional parameterized model according to the precision influencing data and the precision evaluation model, thereby obtaining iterative optimization data; Step S396: integrating and aligning the mechanical performance analysis data, structural optimization suggestion data, structural modification data, parameter update data, precision impact data, and iterative optimization data based on the three-dimensional parametric model to obtain structural parameter adjustment data.

8. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 7, characterized in that: Step S4 includes the following steps: Step S41: Acquire device usage data in different clinical application scenarios; Step S42: cleaning and preprocessing the original usage data to obtain effective usage data; Step S43: constructing a device adaptability evaluation index system according to the effective use data, thereby obtaining adaptability evaluation index data, wherein the device adaptability evaluation index system includes functional adaptability, operational adaptability and comfort adaptability; Step S44: quantitatively scoring the performance of the device in various clinical scenarios according to the adaptability evaluation index data and the effective use data, thereby obtaining adaptability evaluation data; Step S45: Analyze the advantages and disadvantages of the device in different scenarios on the adaptability evaluation data, so as to obtain adaptability analysis data; compare and analyze the structural parameter adjustment data according to the adaptability analysis data, and determine the specific parameters and adjustment ranges that need to be adjusted, so as to obtain parameter adjustment solution data; Step S46: Adaptively modifying the structural parameter adjustment data according to the parameter adjustment scheme data to generate multiple design schemes, thereby obtaining multi-scheme design data; Step S47: Perform multi-objective optimization calculations on the multi-scheme design data using multi-objective optimization technology, and use the Pareto optimal solution to optimize the results, thereby obtaining the optimal design window data.

9. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 8, characterized in that: Step S5 includes the following steps: Step S51: Generate a 3D printing file according to the optimized design window data, and select 3D printing materials and processes to obtain 3D printing manufacturing data; Step S52: using high-precision 3D printing equipment to produce a device prototype according to the 3D printing manufacturing data, and performing support removal, surface treatment and fine processing to obtain a finished prototype; Step S53: Perform clinical simulation tests using the finished prototype and collect feedback information to obtain prototype device feedback data, wherein the prototype device feedback data includes simulation test data and user feedback data; Step S54: Perform function and adaptability evaluation on the finished prototype according to the prototype device feedback data, so as to obtain the final prototype evaluation data, wherein the adaptability evaluation includes fixation effect, adjustment accuracy, ease of operation and adaptability to different clinical scenarios.

10. The three-dimensional parameterized design method for a cranial and brain position fixation device according to claim 9, characterized in that: Step S6 includes the following steps: Step S61: identifying the improvement needs of key design parameters and structural features according to the prototype evaluation data, thereby obtaining model optimization direction data; Step S62: systematically adjusting the design parameters of the three-dimensional parameterized model according to the model optimization direction data, thereby obtaining parameter adjustment data; Step S63: updating the constraint conditions of the three-dimensional parameterized model based on the parameter adjustment data, thereby obtaining constraint update data, wherein the constraint conditions include geometric constraints, assembly constraints, and performance constraints; Step S64: performing final parameter locking and model confirmation on the three-dimensional parametric model according to the parameter adjustment data and the constraint update data, thereby obtaining a final parametric model; Step S65: converting the final parametric model data into a standardized engineering drawing format, including assembly drawings, parts drawings, and dimension annotations, thereby obtaining engineering drawing data; Step S66: Generate technical documents required for production based on the engineering drawing data, thereby obtaining final model production drawing data.

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