Prosthetic socket shape optimization method and device

Abstract

The present invention provides a method and device for optimizing the shape of a prosthetic receiving cavity, the method comprising the following steps: constructing a residual limb model, dividing the residual limb surface into multiple regions, and setting an extrusion center in each of the regions; setting the shape characteristics of the prosthetic receiving cavity as an extrusion strategy, and performing an extrusion test on each region of the residual limb surface to obtain test indicators of the extrusion center of each region; wherein the test indicators include at least two of the residual limb compression rate, the suspension force gap deviation value, the support force gap deviation value, and the bone movement limiting force gap deviation value; taking the stress bearing capacity of each part of the residual limb as a constraint condition, performing multi-objective optimization on the test indicators, and solving the minimum values ​​of multiple test indicators at the same time, and finally determining the optimal shape characteristics of the receiving cavity. The present invention utilizes computational simulation and multi-objective optimization technology, and can achieve a prosthetic receiving cavity shape design that takes into account both comfort and functionality by performing detailed extrusion analysis and extrusion strategy testing on the residual limb model.

Description

Technical Field

[0001] The present invention relates to the technical field of rehabilitation assistive devices, and in particular to a method and device for optimizing the shape of a prosthetic receiving cavity. Background Art

[0002] Amputation is a surgery that is taken out of necessity to save or prolong the life of the injured. Common causes of amputation include: irreparable damage to limb blood supply or tissue, including severe trauma such as mechanical injury, burns, frostbite and electric shock; drugs, incision and drainage cannot control, or even life-threatening infections and some long-term recurring attacks cannot be cured, which have caused severe limb deformity, loss of function, and even chronic infections that may induce malignant tumors; limb ischemia and necrosis caused by peripheral vascular disease: common in occlusive arteritis with or without diabetes. Prosthesis is an important way for the amputee group to compensate for the loss of limb function and restore normal life. However, at present, amputees still often refuse prostheses or show quite low satisfaction, which is mainly due to the unsatisfactory wearing effect of the socket. The socket is the human-machine interface connecting the prosthesis and the residual limb, and is often the key factor in the success or failure of prosthetic assembly. Amputees often do not often use prostheses due to problems with the socket. When wearing prostheses, amputees often suffer from skin damage, pain or airtightness, resulting in a high rate of prosthetic abandonment. To date, optimal socket design remains one of the most important bottlenecks in the field of prosthetics.

[0003] The receiving cavity has the functions of accommodating the residual limb, supporting the body weight, transmitting movement and suspension. The receiving cavity relies on the interface stress distribution to perform its functions. The shape is the main content of the receiving cavity design, and the shape of the receiving cavity determines the strain of the residual limb soft tissue. The relationship between function and shape is stress and strain. The existing receiving cavity design technology only simply distinguishes the force application area and the load-free area on the surface of the residual limb, and cannot well construct the corresponding relationship between stress and strain. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a method and device for optimizing the shape of a prosthetic socket to eliminate or improve one or more defects existing in the prior art.

[0005] In a first aspect, an aspect of the present invention provides a method for optimizing the shape of a prosthetic socket, the method comprising the following steps:

[0006] Constructing a residual limb model, dividing the residual limb surface into a plurality of regions, and setting an extrusion center in each of the regions;

[0007] By setting the shape characteristics of the prosthetic receiving cavity as an extrusion strategy and performing an extrusion test on each area on the residual limb surface, a test index of the extrusion center of each area is obtained; wherein the test index includes at least two of the residual limb compression rate, the suspension force gap deviation value, the support force gap deviation value and the bone movement limiting force gap deviation value;

[0008] Taking the stress bearing capacity of each part of the residual limb as a constraint condition, multi-objective optimization is performed on the test indicators, and the minimum values ​​of multiple test indicators are solved at the same time, and finally the optimal shape characteristics of the receiving cavity are determined.

[0009] In some embodiments, the step of setting the shape characteristics of the prosthetic socket as a squeezing strategy includes:

[0010] The squeezing centers of multiple regions form an array, and the characteristics of the squeezing center array are weighted and expressed as individual X, individual X = (x 1 , x 2 , ..., x n ) is the decision vector, X∈Ω is the decision space, and the features include: position, shape, inclination, depth and area on the residual limb surface.

[0011] In some embodiments, the step of performing multi-objective optimization on the test indicators and simultaneously solving the minimum values ​​of multiple test indicators includes:

[0012] The test index includes residual limb compression rate f 1 , suspension force gap deviation value f 2 , support force gap deviation value f 3 And the bone movement limiting force gap deviation value f 4 , the multi-objective optimization formula of the test index is:

[0013] min F(X)=(f 1 (X), f 2 (X), f 3 (X), f 4 (X) T

[0014] Among them, the residual limb compression rate f 1 (X) is the ratio of the volume reduction of the individual residual limb to the initial value of the residual limb volume. The volume reduction of the individual residual limb is obtained by adding the soft tissue strains of each compression center;

[0015] Suspension force gap deviation value f 2 (X) is obtained by subtracting the suspension force required by the suspension function from the individual suspension force; the suspension force vector is determined by the weight of the prosthesis, the swing speed of the residual limb, and the range of motion of the residual limb, and the individual suspension force is obtained by adding the downward stress values ​​corresponding to the soft tissue strain of each compression center;

[0016] Support force gap deviation value f 3(X) is obtained by subtracting the support force required by the support function from the support force generated by the individual; the support force vector is determined according to the user's weight and movement impulse, and the support force generated by the individual is obtained by adding the stress values ​​in the upward direction corresponding to the soft tissue strain of each compression center;

[0017] Bone movement limiting force gap deviation value f 4 (X) is obtained by subtracting the bone movement restriction force required for transmitting motion function from the individual bone movement restriction force; the bone movement restriction force is determined by the soft tissue hardness and soft tissue thickness, and the individual bone movement restriction force is obtained by adding the stress values ​​opposite to the bone movement direction corresponding to the soft tissue strain at each compression center.

[0018] In some embodiments, the step of dividing the residual limb surface into a plurality of regions comprises:

[0019] The residual limb surface is meshed and divided into different regions according to the anatomy of up and down, front and back, or inside and outside, and the number of the regions is set to 3 to 32.

[0020] In some embodiments, the stress of the constraint condition includes compressive stress and shear stress.

[0021] In some embodiments, the local part of the residual limb includes at least one of the ligaments / nerves / lymphatic / vascular courses, muscle belly, bone protrusions, end and bone body on the surface of the residual limb.

[0022] In some embodiments, the step of performing multi-objective optimization on the test indicators and simultaneously solving the minimum values ​​of multiple test indicators further includes:

[0023] Genetic algorithm or particle swarm optimization algorithm is used to update the solution, and the Pareto optimal solution is obtained through fast non-dominated sorting and crowding calculation; the crowding calculation formula is:

[0024]

[0025] Among them, i d Represents the squeeze center individual x i The congestion level, Represents the squeeze center individual x i+1 The function value of the jth objective function, Represents the squeeze center individual x i-1 is the function value of the j-th objective function, and m represents the number of objective functions.

[0026] In some embodiments, the step of determining the optimal shape characteristics of the receiving cavity includes:

[0027] According to the individual coding rules of the extrusion center, the final shape characteristics of the receiving cavity are determined, and the design scheme of the receiving cavity is obtained.

[0028] In a second aspect, the present invention also provides a device for optimizing the shape of a prosthetic socket, comprising a processor, a memory, and a computer program / instructions stored in the memory, wherein the processor is used to execute the computer program / instructions, and when the computer program / instructions are executed, the device implements the steps of the aforementioned method.

[0029] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program / instruction stored thereon, which implements the steps of the aforementioned method when the computer program / instruction is executed by a processor.

[0030] In a fourth aspect, the present invention further provides a computer program product, comprising a computer program / instruction, characterized in that the computer program / instruction implements the steps of the aforementioned method when executed by a processor.

[0031] The prosthetic socket shape optimization method and device in the embodiment of the present invention utilizes computational simulation and multi-objective optimization technology, and through detailed extrusion analysis and testing of the residual limb model, can achieve a prosthetic socket shape design that takes into account both comfort and functionality.

[0032] Additional advantages, purposes, and features of the present invention will be described in part in the following description, and will become apparent to those skilled in the art after studying the following, or may be learned from the practice of the present invention. The purposes and other advantages of the present invention may be achieved and obtained by the structures specifically indicated in the specification and the accompanying drawings.

[0033] Those skilled in the art will appreciate that the objectives and advantages that can be achieved with the present invention are not limited to the above specific description, and the above and other objectives that can be achieved by the present invention will be more clearly understood from the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of this application, and do not constitute a limitation of the present invention. The components in the drawings are not drawn to scale, but are only for illustrating the principles of the present invention. In order to facilitate the illustration and description of some parts of the present invention, the corresponding parts in the drawings may be enlarged, that is, they may become larger relative to other components in the exemplary device actually manufactured according to the present invention. In the drawings:

[0035] Figure 1 Schematic diagram of the flow of a method for optimizing the shape of a prosthetic socket in one embodiment of the present invention.

[0036] Figure 2 It is a schematic structural diagram of a residual limb and a prosthesis in one embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0038] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only structures and / or processing steps closely related to the solutions according to the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0039] It should be emphasized that the term “include / comprises” when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0040] It should also be noted that, unless otherwise specified, the term “connection” herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0041] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0042] In a first aspect, the present invention provides a method for optimizing the shape of a prosthetic socket, which uses a multi-objective optimization algorithm to optimize test indicators, comprehensively considers the functionality and comfort of the prosthesis, and improves the overall performance of the prosthesis and the user experience.

[0043] In some embodiments, Figure 1 As shown, the shape optimization method of the prosthetic receiving cavity includes the following steps:

[0044] S10: Construct a residual limb model, divide the residual limb surface into multiple regions, and set an extrusion center in each region. The residual limb surface can be meshed and then divided into regions, such as Figure 2 As shown; the residual limb surface is divided into multiple small areas, each of which can be subjected to separate extrusion tests or optimization operations. This grid design helps to more finely analyze and optimize the shape of the prosthetic socket.

[0045] S20: By setting the shape feature of the prosthetic receiving cavity as the extrusion strategy, and performing an extrusion test on each area of ​​the residual limb surface, the test index of the extrusion center of each area is obtained; wherein the test index includes at least two of the residual limb compression rate, the suspension force gap deviation value, the support force gap deviation value and the bone movement limiting force gap deviation value. At least two of the test indicators are used to evaluate the effects of various extrusion strategies. These indicators are indicators that affect comfort and functionality, and are also key criteria for the design quality and performance of the receiving cavity in the present invention. Through effective shape feature and extrusion strategy optimization, these indicators can be significantly improved, thereby improving the comfort, functionality and overall experience of the prosthetic user.

[0046] S30: Taking the stress bearing capacity of each part of the residual limb as a constraint condition, multi-objective optimization is performed on the test index, and the minimum value of multiple test indexes is solved at the same time, and the optimal shape characteristics of the receiving cavity are finally determined. The goal of the optimization is to find the shape characteristics of the receiving cavity that make multiple test indicators reach the optimal value; through the optimization process, the optimal shape characteristics of the prosthetic receiving cavity are determined to provide the best comfort, support and functionality.

[0047] The prosthetic socket shape optimization method in the embodiment of the present invention utilizes computational simulation and multi-objective optimization technology, and through detailed extrusion analysis and testing of the residual limb model, can achieve a prosthetic socket shape design that takes into account both comfort and functionality.

[0048] Advantages of the prosthetic socket shape optimization method in the embodiment of the present invention include, but are not limited to: personalized adaptation, improved comfort, increased stability and control, reduced residual limb movement, and enhanced functionality of the prosthesis.

[0049] By optimizing the shape of the receiving cavity, the present invention can achieve a personalized design that better fits the user's residual limb, thereby providing more comfortable and effective support. The optimized shape of the receiving cavity can reduce pressure points and friction, and reduce the discomfort that may occur when the user wears it for a long time. The appropriate shape of the receiving cavity can improve the stability and controllability of the prosthesis, making it easier for the user to master and use the function of the prosthesis. Optimizing the shape of the receiving cavity can reduce the movement of the residual limb inside the prosthesis, thereby reducing pain and skin damage caused by friction. Through shape optimization, the functional performance of the prosthesis can be improved, such as improving its load-bearing capacity and support capacity, and increasing the convenience and efficiency of daily activities. This method allows precise optimization of the shape of the receiving cavity based on individual anatomical data and computational simulation, thereby achieving customized production to meet the specific needs of each user.

[0050] In some embodiments, the residual limb surface is meshed and divided into different regions according to the anatomy of up and down, front and back, inside and outside, and extrusion centers are set respectively. The grid layout of the entire residual limb surface should be uniform and fully covered to ensure a comprehensive analysis and optimization of the overall shape. Reasonable grid layout can provide effective data support in the optimization process and help determine the optimal shape characteristics of the receiving cavity. The size and shape of each region can be determined, and it can be reasonably divided according to the geometric shape and surface characteristics of the residual limb. Furthermore, some regions can be divided in more detail to capture the tiny curves and bumps on the residual limb surface. Extrusion centers are set in each region, and these extrusion centers are used to simulate and test different extrusion strategies. The location selection of the extrusion center should be based on the structural characteristics of the residual limb surface to ensure that the impact of extrusion on each region can be effectively evaluated. The degree of meshing refinement directly affects the complexity of the calculation and the accuracy of the results. Therefore, when designing the meshed region, the utilization of computing resources and the required optimization accuracy can be balanced.

[0051] As at least one achievable method, the step of dividing the residual limb surface into multiple regions includes: meshing the residual limb surface and dividing it into different regions according to the anatomical up-down, front-back, or inside-outside directions, and the number of regions is set to 3 to 32. Meshing can ensure that the segmentation of the residual limb surface is accurate and conforms to the anatomical structure. The residual limb surface is segmented according to the anatomical up-down, front-back, or inside-outside directions, and can be divided along the direction perpendicular to the surface according to the anatomical structural characteristics of the residual limb. For example, the residual limb can be divided into several horizontal levels from top to bottom, or into several regions in the front-back direction. The number of segmented regions is determined according to specific needs and design goals. The number of regions ranges from 3 to 32, which is suitable for residual limbs of different sizes and complexities. A smaller number of regions can simplify the design process, but may sacrifice precision; a larger number of regions can provide more precise control and adjustment.

[0052] In some embodiments, the step of setting the shape characteristics of the prosthetic socket as a squeezing strategy includes:

[0053] The squeezing centers of multiple regions form an array, and the characteristics of the squeezing center array are weighted and expressed as individual X, individual X = (x 1 , x 2 , ..., x n) is the decision vector, X∈Ω is the decision space, and the features include: position on the residual limb surface (such as position coordinates), shape, inclination, depth and area. The value range of the decision vector X defines the decision space Ω, which describes all possible combinations of prosthetic receiving cavity shapes. The shape characteristics of the prosthesis are optimized by finding the optimal solution in this space. Furthermore, according to design requirements and user needs, different weights can be assigned to each feature so as to adjust the influence of each feature during the optimization process. In this embodiment, the present invention finds the optimal prosthetic receiving cavity shape by defining and weighing the characteristics of the extrusion strategy in detail, combined with the design and optimization of the decision vector, so as to improve the comfort and functionality of the user. This method combines the analysis of multiple regions and the optimization of multiple features to adjust and optimize the shape of the prosthesis in a comprehensive and precise manner.

[0054] In some embodiments, the step of performing multi-objective optimization on the test indicators and simultaneously solving the minimum values ​​of multiple test indicators includes:

[0055] The test index includes residual limb compression rate f 1 , suspension force gap deviation value f 2 , support force gap deviation value f 3 And the bone movement limiting force gap deviation value f 4 , the multi-objective optimization formula of the test index is:

[0056] min F(X)=(f 1 (X), f 2 (X), f 3 (X), f 4 (X) T

[0057] In this embodiment, the simultaneous minimization of these test indicators can be used as the purpose of multi-objective optimization. The objective function can be expressed in a vector form, f(X) is the objective, and in the representation of vectors and matrices, T represents the transposition of a row vector or column vector into a corresponding column vector or row vector. Constraints may include various design restrictions and performance requirements; an appropriate multi-objective optimization algorithm may be selected to handle the problem of minimizing the objective function. Multi-objective optimization algorithms include, but are not limited to, multi-objective genetic algorithms (MOGA), multi-objective particle swarm optimization algorithms (MOPSO), multi-objective differential evolution algorithms (MODE), etc., which can effectively balance and optimize between multiple objectives. The selected optimization algorithm is used to perform calculations to find the optimal design variable vector f(X) so that the objective function vector F(X) reaches the minimum value. This process may involve multiple iterations and evaluations until a satisfactory optimization result is achieved.

[0058] Among them, the residual limb compression rate f 1(X) is the ratio of the volume reduction of the individual residual limb to the initial value of the residual limb volume. The volume reduction of the individual residual limb is obtained by adding the soft tissue strains of each compression center;

[0059] Suspension force gap deviation value f 2 (X) is obtained by subtracting the suspension force required by the suspension function from the individual suspension force; the suspension force vector is determined by the weight of the prosthesis, the swing speed of the residual limb, and the range of motion of the residual limb, and the individual suspension force is obtained by adding the downward stress values ​​corresponding to the soft tissue strain of each compression center;

[0060] Support force gap deviation value f 3 (X) is obtained by subtracting the support force required by the support function from the support force generated by the individual; the support force vector is determined according to the user's weight and movement impulse, and the support force generated by the individual is obtained by adding the stress values ​​in the upward direction corresponding to the soft tissue strain of each compression center;

[0061] Bone movement limiting force gap deviation value f 4 (X) is obtained by subtracting the bone movement restriction force required for transmitting motion function from the individual bone movement restriction force; the bone movement restriction force is determined by the soft tissue hardness and soft tissue thickness, and the individual bone movement restriction force is obtained by adding the stress values ​​opposite to the bone movement direction corresponding to the soft tissue strain at each compression center.

[0062] As at least one achievable method, by querying the soft tissue stress-strain curve or obtaining the corresponding stress-strain curve experimentally, a comparison table of soft tissue strain and stress of each part of the residual limb is established to quickly obtain f(X). Specifically, the obtained soft tissue stress-strain data is organized into a comparison table or a mathematical model. These tables or models can reflect the strain level and corresponding stress value of different parts of the residual limb when subjected to force. For example, the residual limb can be divided into multiple parts according to the anatomical region, and a corresponding stress-strain relationship can be established for each part. In the process of multi-objective optimization, the design variable X can include parameters such as the shape of the prosthesis receiving cavity or the extrusion strategy. Through the stress-strain comparison table, the soft tissue stress under each design variable configuration can be quickly calculated. For example, for a specific prosthesis design (X), the corresponding soft tissue stress can be quickly estimated using the comparison table according to its strain at each part. The established stress-strain comparison table is integrated into the selected multi-objective optimization algorithm. The algorithm will evaluate the advantages and disadvantages of each design variable configuration based on the calculated soft tissue stress, and find the best design solution that minimizes the objective function F(X).

[0063] In some embodiments, the stress of the constraint condition includes compressive stress and shear stress; compressive stress is the force acting on a unit area perpendicular to the surface. In prosthetic design, compressive stress appears significantly between the contact surface between the prosthesis and the residual limb, such as the contact area between the bottom of the prosthesis and the skin of the residual limb. Shear stress refers to the force acting on a unit area parallel to the surface. When the prosthetic receiving cavity undergoes inevitable slight movement or abnormal piston movement, shear stress occurs to varying degrees between the inner wall of the prosthetic receiving cavity and the contact surface of the residual limb. In addition, shear stress can also occur inside soft tissues, such as between muscles and skin or at the contact between bones and soft tissues.

[0064] On the residual limb, different parts of the force and stress distribution will be different. Specifically, the local part of the residual limb includes at least one of the ligament / nerve / lymph / blood vessel running on the surface of the residual limb, the muscle belly, the bone protrusion, the end and the bone body. For example, the muscle belly, the bone body plane, a part of the ligament and the end area on the surface of the residual limb generally experience higher compressive stress, especially when supporting body weight. At this time, attention should be paid to the problem of increased shear stress that may be caused. The bearing capacity of these areas where nerves / lymph / blood vessels run is generally poor, and high stress should be avoided as much as possible. Their surfaces may require additional protection and support to reduce the risk of pressure concentration and injury. Bone protrusions and part of the ligaments can be used as key points for prosthetic fixation, and special attention should be paid to pressure distribution to avoid discomfort or injury caused by excessive pressure. In the design of prostheses, pressure and shear stress limitations in different parts should be considered. These constraints are integrated into the multi-objective optimization algorithm to find the best prosthetic design solution while ensuring that the forces on various parts of the residual limb are within a safe range.

[0065] Through the above method, the present invention can more accurately consider the physiological characteristics and stress conditions of various parts of the residual limb, thereby optimizing the design of the prosthetic receiving cavity and improving its comfort, functionality and reliability in long-term use.

[0066] In some embodiments, the step of performing multi-objective optimization on the test indicators and solving the minimum values ​​of multiple test indicators at the same time also includes: updating the solution using a genetic algorithm or a particle swarm optimization algorithm, and obtaining a Pareto optimal solution through fast non-dominated sorting and congestion calculation; the calculation formula of the congestion is:

[0067]

[0068] Among them, i d Represents the squeeze center individual x i The crowding degree of the individual (x) is represented by i, i represents the index of the current individual, (i+1) and (i-1) represent the squeeze center individual (x i ) before and after the individual, Represents the squeeze center individual x i+1The function value of the jth objective function, Represents the squeeze center individual x i-1 The function value of the j-th objective function, m represents the number of objective functions. If the test indicators use the aforementioned four indicators, m is 4.

[0069] In the above embodiment, in multi-objective optimization, crowding calculation is an important step in the Pareto front update process, which is used to help maintain the diversity of the population and avoid premature convergence to the local optimal solution. The purpose of crowding calculation is to measure the distribution density of individuals in the target space so as to maintain the diversity of the population when selecting the next generation solution. A high crowding value indicates that the distance between individuals in the target space is large, which is conducive to maintaining the diversity in the population and avoiding the aggregation of individuals in a certain area. In the iterative process of genetic algorithm or particle swarm optimization, crowding is used as one of the bases for selecting the next generation solution. For example, individuals with large crowding can be preferentially selected to ensure the balance and integrity of the Pareto front. By encouraging the dispersed distribution of individuals in the population, crowding helps prevent the algorithm from converging to the local Pareto front too early and improves the possibility of finding the global Pareto front. In practical applications, crowding calculation can be used in combination with Fast Non-dominated Sorting to determine the Pareto level of each individual. When updating the population, selection is made based on the value of crowding to ensure that individuals with appropriate distribution are selected.

[0070] In some embodiments, the step of determining the optimal shape characteristics of the receiving cavity includes: determining the final shape characteristics of the receiving cavity according to the coding rules of the extrusion center individual, and obtaining the design scheme of the receiving cavity. For example, using the design parameters of the extrusion center individual, the final shape characteristics of the receiving cavity are determined according to the predefined coding rules. This step can obtain specific design parameter values ​​by decoding the coding values ​​of the extrusion center individual. Based on the determined shape characteristics, an actual receiving cavity design scheme is generated using engineering design tools or three-dimensional design software. The design scheme should meet the requirements of actual engineering applications and meet the multi-objective performance indicators set during the optimization process.

[0071] Through the above steps, the process of socket shape optimization can be systematically implemented to ensure that the best socket design solution is obtained within the framework of multi-objective optimization to improve the prosthetic socket performance and design and optimization efficiency.

[0072] Example 1

[0073] The prosthetic socket shape optimization method in the embodiment of the present invention can be implemented with the help of Python to complete the modeling, solution and visualization of multi-objective optimization problems.

[0074] Use Python language to call five modules: numpy, openpyxl, matplotlib, scikit-learn and Pymoo.

[0075] in:

[0076] The openpyxl library called is used to read and process the data set data in Excel; for example, using the openpyxl library to read the data set from an Excel file can be achieved by reading the data in the Excel table row by row, ensuring that the data is loaded into Python for subsequent processing.

[0077] The NumPy library is an open source science and technology library in Python, which is mainly used to process dimensional arrays and matrices and operations; the extrusion center array features are properly encoded so that they can be used as variables in the optimization process. Define and set the functions of residual limb compression rate, suspension force gap deviation value, support force gap deviation value and bone movement restriction force gap deviation value. These functions will calculate the corresponding values ​​according to the optimization variables, and can use mathematical functions and matrix operations in the NumPy library.

[0078] The Pymoo (Python Multi-Objective Optimization) library is called to model, solve, and analyze multi-objective optimization problems. For example, use the Pymoo library to define a custom problem that inherits from the Problem class. This problem can include variables (encoding of squeezed center array features), objectives (multiple objective functions to be minimized), and constraints (such as bounds on variables). Instantiate the NSGA2 algorithm object and configure the algorithm's parameters such as population size, crossover and mutation operations, which may affect the algorithm's behavior and performance during the optimization process. Use the minimize function to run the NSGA-Ⅱ algorithm. This function will accept the defined optimization problem and algorithm object, as well as other necessary parameters such as the maximum number of evolution generations and population initialization strategy. Use methods such as res.non_dominated_sort() to obtain information about non-dominated solution sets. These methods will help identify the optimal solution sets found during the optimization process that are non-dominated on multiple optimization objectives.

[0079] The called scikit-learn is used to experiment with different algorithms, such as multi-objective genetic algorithm (MOGA), multi-objective particle swarm optimization algorithm (MOPSO), multi-objective differential evolution algorithm (MODE), etc.; scikit-learn is a Python library for machine learning that provides a variety of simple and effective tools for data mining and data analysis.

[0080] The matplotlib library is used to draw scatter plots and decision boundaries to visualize the data; the matplotlib library can be used to draw scatter plots and other graphics to show the non-dominated solution set and the progress of the optimization process. This can help intuitively understand the effects and results of the optimization algorithm.

[0081] By combining these five Python modules, the present invention can achieve a complete multi-objective optimization problem modeling, solving and analysis process. The specific implementation of each step will depend on the characteristics of the specific problem and data set, and needs to be appropriately adjusted and expanded according to the actual situation.

[0082] In other embodiments, other languages, libraries, or modules may be used to implement the method for optimizing the shape of the receiving cavity. However, the specific steps are mainly as follows:

[0083] 1) Data conversion and processing: Encode the extrusion center array feature, set the residual limb compression rate, suspension force gap deviation value, support force gap deviation value and bone movement restriction force gap deviation value function; in this step, the original data is converted into a format suitable for optimization algorithm processing. The residual limb compression rate, suspension force gap deviation value, support force gap deviation value and bone movement restriction force gap deviation value function are all objective functions or constraints to be optimized. The objective function can be an indicator to be minimized or maximized, and the constraint condition is a condition that must be met.

[0084] 2) Instantiate an NSGA-II object: In this step, an optimizer object is instantiated using the NSGA-II class in the Pymoo library; the optimization problem is set by defining the objective function, constraints, and the range of optimization variables.

[0085] 3) Run the optimization algorithm: You can call the minimize function of NSGA-II to run the optimization algorithm and set the running parameters, including setting the maximum evolutionary generation, initializing the population, and constraint encoding conversion. The maximum evolutionary generation is used to control the number of iterations of the algorithm, affecting the convergence of the optimization results; the initialization population can be randomly initialized or based on a specific heuristic method; the constraint encoding conversion can ensure that the constraints are met during the optimization process. The minimize function can also set other parameters, such as population size, crossover rate, mutation rate, etc.

[0086] 4) Obtain information about the non-dominated solution set: Use the result object returned by the optimization algorithm to obtain information about the non-dominated solution set. The non-dominated solution set contains all solutions that are non-inferior under multiple optimization objectives.

[0087] 5) Data visualization (optional): You can draw scatter plots or decision boundary plots to visualize the optimization results; this can help analyze the distribution of results and solutions, as well as the trade-offs between different solutions.

[0088] In the second aspect, the present invention also provides a prosthetic socket shape optimization device, including a processor, a memory and a computer program / instruction stored in the memory, wherein the processor is used to execute the computer program / instruction, and when the computer program / instruction is executed, the device implements the steps of the aforementioned method. The processor may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components and other chips, or a combination of the above-mentioned types of chips. The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs, non-transient computer executable programs and modules.

[0089] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program / instruction stored thereon, which implements the steps of the aforementioned prosthetic socket shape optimization method when the computer program / instruction is executed by a processor. The computer-readable storage medium may be a tangible storage medium, such as a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a floppy disk, a hard disk, a removable storage disk, a CD-ROM, or any other form of storage medium known in the art.

[0090] In a fourth aspect, the present invention further provides a computer program product, comprising a computer program / instruction, characterized in that the computer program / instruction, when executed by a processor, implements the steps of the aforementioned prosthetic socket shape optimization method.

[0091] It should be understood by those skilled in the art that the exemplary components, systems and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software or a combination of the two. Whether it is performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present invention are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier.

[0092] It should be clear that the present invention is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present invention.

[0093] In the present invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with features of other embodiments or replace features of other embodiments.

[0094] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the embodiments of the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing the shape of a prosthetic socket, characterized in that: The method comprises the following steps: Constructing a residual limb model, dividing the residual limb surface into a plurality of regions, and setting an extrusion center in each of the regions; By setting the shape characteristics of the prosthetic receiving cavity as the extrusion strategy, and performing extrusion tests on various areas of the residual limb surface, the test indicators of the extrusion center of each area are obtained; wherein, the test indicators include at least two of the residual limb compression rate, suspension force gap deviation value, support force gap deviation value and bone movement restriction force gap deviation value; wherein, the residual limb compression rate is the ratio of the individual residual limb volume reduction to the initial value of the residual limb volume, and the individual residual limb volume reduction is obtained by adding the soft tissue strains of each extrusion center; the suspension force gap deviation value is obtained by subtracting the suspension force required for the suspension function from the suspension force generated by the individual; the suspension force vector is determined by the prosthetic weight, the residual limb swing speed, and the residual limb mobility, and the individual generated The suspension force is obtained by adding the downward stress values ​​corresponding to the soft tissue strains of each extrusion center; the support force gap deviation value is obtained by subtracting the support force required by the support function from the support force generated by the individual; the support force vector is determined according to the user's weight and movement impulse, and the support force generated by the individual is obtained by adding the upward stress values ​​corresponding to the soft tissue strains of each extrusion center; the bone movement restriction force gap deviation value is obtained by subtracting the bone movement restriction force required for transmitting movement function from the bone movement restriction force generated by the individual; the bone movement restriction force is determined by the soft tissue hardness and soft tissue thickness, and the bone movement restriction force generated by the individual is obtained by adding the stress values ​​corresponding to the soft tissue strains of each extrusion center in the opposite direction of bone movement; Taking the stress bearing capacity of each part of the residual limb as a constraint condition, multi-objective optimization is performed on the test indicators, and the minimum values ​​of multiple test indicators are solved at the same time, and finally the optimal shape characteristics of the receiving cavity are determined.

2. The method for optimizing the shape of a prosthetic socket according to claim 1, characterized in that: The step of setting the shape characteristics of the prosthetic receiving cavity as an extrusion strategy comprises: The squeezing centers of multiple regions form an array, and the characteristics of the squeezing center array are weighted and represented as individual X, where individual X = (x1, x2, ..., x n ) is the decision vector, X∈Ω is the decision space, and the features include: position, shape, inclination, depth and area on the residual limb surface.

3. The method for optimizing the shape of a prosthetic socket according to claim 2, characterized in that: The step of performing multi-objective optimization on the test indicators and simultaneously solving the minimum values ​​of multiple test indicators includes: The test indicators include residual limb compression rate f1, suspension force gap deviation value f2, support force gap deviation value f3 and bone movement restriction force gap deviation value f4. The multi-objective optimization formula of the test indicators is: min F(X)=(f1(X),f2(X),f3(X),f4(X)) T Among them, f1(X)—compression rate of residual limb; f2(X)—suspension force gap deviation value; f3(X)—support force gap deviation value; f4(X)—bone movement limiting force gap deviation value.

4. The method for optimizing the shape of a prosthetic socket according to claim 1, characterized in that: The step of dividing the residual limb surface into a plurality of regions comprises: The residual limb surface is meshed and divided into different regions according to the anatomy of up and down, front and back, or inside and outside, and the number of the regions is set to 3 to 32.

5. The method for optimizing the shape of a prosthetic socket according to claim 1, characterized in that: The stress of the constraint condition includes compressive stress and shear stress.

6. The method for optimizing the shape of a prosthetic socket according to claim 5, characterized in that: The local part of the residual limb includes at least one of the ligaments / nerves / lymphatic / blood vessels on the surface of the residual limb, the muscle belly, the bone protrusion, the end and the bone body.

7. The method for optimizing the shape of a prosthetic socket according to claim 3, characterized in that: The step of performing multi-objective optimization on the test index and simultaneously solving the minimum value of multiple test indexes also includes: Genetic algorithm or particle swarm optimization algorithm is used to update the solution, and the Pareto optimal solution is obtained through fast non-dominated sorting and crowding calculation; the crowding calculation formula is: Among them, i d Represents the squeeze center individual x i The congestion level, Represents the squeeze center individual x i+1 The function value of the jth objective function, Represents the squeeze center individual x i-1 is the function value of the j-th objective function, and m represents the number of objective functions.

8. The method for optimizing the shape of a prosthetic socket according to claim 7, characterized in that: The steps to determine the optimal shape characteristics of the socket include: According to the individual coding rules of the extrusion center, the final shape characteristics of the receiving cavity are determined, and the design scheme of the receiving cavity is obtained.

9. A device for optimizing the shape of a prosthetic socket, comprising a processor, a memory, and a computer program / instruction stored in the memory, characterized in that: The processor is used to execute the computer program / instructions. When the computer program / instructions are executed, the device implements the steps of the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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