Design method of sleep pillow for preventing pillow and neck pressure sores of bedridden people

Abstract

The application discloses a design method of a sleep pillow for preventing pillow and neck pressure sores of bedridden people, and particularly relates to the field of medical rehabilitation auxiliary design, which comprises the following steps: introducing medical image data of bedridden people, extracting structure information of the skull, cervical vertebra and soft tissue, performing surface fitting operation on the structure information in three-dimensional reconstruction software, forming a head and neck geometric model and outputting the head and neck geometric model, introducing the head and neck geometric model into finite element modeling software, and setting the skull and vertebra as rigid materials and setting the soft tissue as super-elastic materials; the application establishes a time accumulation model of soft tissue pressure on the basis of finite element simulation and time domain calculation, and combines the time accumulation model with the surface parameterization and slow-release layer construction process, so that corresponding adjustment between the sleep pillow surface geometry and the soft tissue pressure accumulation law is realized, and the problem that the prior art cannot control the long-term pressure accumulation of soft tissue to cause pressure sores is solved.

Description

Technical Field

[0001] This invention relates to the field of medical rehabilitation assistive design technology, and more specifically, to a pillow design method for preventing pressure sores on the neck of bedridden disabled persons. Background Technology

[0002] Under the current technological approach, research on preventing pressure sores on the neck and back of bedridden disabled people mainly focuses on geometric optimization and pressure distribution improvement under static working conditions: finite element models of the head and neck, soft tissues, and pillow body are established through CT or surface reconstruction, displacement loading and gravity boundary conditions are set, the influence of different surface parameters on contact pressure and support is compared, and parameterization and multi-objective optimization are carried out on this basis. However, this approach assumes that instantaneous pressure distribution is the main source of danger, ignoring the real nursing scenario of prolonged bed rest. Patients are subjected to continuous pressure in the same posture due to limited mobility, which obstructs microvascular perfusion and interstitial fluid return in the tissue. Low to moderate levels of pressure accumulate over time, coupled with the shear and compression-shear coupling effects caused by minute posture drift, leading to a progressive chain of subcutaneous soft tissue fatigue, ischemia, and necrosis. At the same time, even if the occipital geometry achieves a reduction in peak pressure in a static manner, it is difficult to actively manage time factors such as the duration of pressure, recovery intervals, and local unloading rhythm. This results in tissue danger not being a one-time peak in spatial distribution, but rather a cumulative dose and insufficient recovery in the time dimension. Therefore, in the existing design system centered on static distribution, there is a lack of controllable and verifiable mechanisms for contact stress and shear in the time dimension, making it difficult to interrupt the problem of time-domain damage accumulation caused by long-term static pressure without relying on the patient to actively turn over. Summary of the Invention

[0003] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a pillow design method for preventing pressure sores on the neck of bedridden disabled individuals. By establishing a time-cumulative model of soft tissue pressure based on finite element simulation and time-domain calculation, and combining it with surface parameterization and the process of constructing a slow-release layer, the corresponding adjustment between the pillow surface geometry and the law of soft tissue pressure accumulation is achieved. This solves the problem that existing design methods centered on static pressure distribution cannot control the formation of pressure sores caused by long-term pressure accumulation on soft tissue.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a pillow design method for preventing pressure sores on the neck of bedridden disabled persons, comprising: S1. By importing medical imaging data of bedridden disabled persons, extract the structural information of the skull, cervical spine and soft tissues, perform surface fitting operation on the structural information in the three-dimensional reconstruction software, form a head and neck geometric model and output it. S2. Import the head and neck geometric model into the finite element modeling software, set the skull and vertebrae as rigid materials, set the soft tissue as hyperelastic materials, and form a contact state by applying gravity load and downward displacement load. Perform static simulation calculation and output the pressure distribution data, strain distribution data and contact area data of the contact area between the occipital region and the back of the neck. S3. Perform continuous calculations on the pressure distribution data according to the time step to form the stress time series of each pressure region; perform integral calculations on the stress time series to solve for the cumulative stress of the soft tissue under pressure; S4. Correspond the accumulated stress to the spatial coordinates of the head and neck geometric model, perform surface parametric construction in the modeling software, divide the pillow surface into the head region, neck region and back region, define the geometric curvature of each region with length and height parameters, set a slow elastic release layer in the neck region, and form a controlled support process by controlling the deformation and recovery rate of the release layer, and connect the geometric curvature of each region with a continuous curve to form the overall S-shaped pillow surface model; S5. Import the S-shaped pillow surface model into the optimization calculation program, input the length parameter, height parameter and deformation of the slow-release layer into the multi-objective optimization program, execute the optimization calculation with soft tissue equivalent stress, shear strain and cumulative stress as objective functions, and solve the design parameter combination. S6. Import the design parameters into the 3D printing software to generate a 3D printing model file. Set the printing layer thickness, infill rate, printing speed and nozzle temperature. Use thermoplastic polyurethane material to perform the printing operation to form the finished anti-pressure sore pillow.

[0005] In a preferred embodiment, S1 further includes performing region segmentation operations in medical image processing software by importing medical image data of a bedridden disabled person; The region segmentation operation includes extracting the skull boundary, cervical spine boundary, and soft tissue boundary in the image based on the grayscale threshold range of the skull, cervical spine, and soft tissue, and outputting the segmented image dataset; Import the image dataset into the 3D reconstruction software to perform volume reconstruction calculation. The volume reconstruction calculation includes calculating the spatial coordinate position relationship of each layer boundary point in the 3D coordinate system based on the spatial resolution and pixel spacing between image layers, and generating a spatial data set of the skull surface, cervical spine surface and soft tissue surface. The spatial data set is imported into the modeling software to perform surface fitting operations. The surface fitting operations include establishing a spatial surface function with boundary points as control points, calculating the spatial coordinate distribution of the skull surface, cervical spine surface and soft tissue surface based on the control point positions, and generating continuous head and neck surface model data. The head and neck surface model data is imported into the geometry processing software to perform boundary trimming operations. The boundary trimming operations include identifying the opening edges between surfaces, performing edge closure and normal correction calculations, generating a closed head and neck geometric model and outputting it.

[0006] In a preferred embodiment, S2 further includes importing a head and neck geometric model into finite element modeling software, and importing a pillow geometric model generated based on external parametric modeling; the pillow geometric model is generated by setting the length and height parameters of the head, neck and back, and connecting them with continuous curves. The head and neck geometry model is meshed by setting node spacing and boundary constraints. The node spacing range is adjusted according to the local curvature. Fixed constraints are applied at the boundary between the skull and cervical vertebrae, and free constraints are applied at the outer boundary of the soft tissue to generate and output a continuous mesh model. Perform material property setting operations in the mesh model, set the skull and cervical spine regions as rigid materials, and input density, elastic modulus and Poisson's ratio parameters; set the soft tissue region as a hyperelastic material, input fitting parameters according to the strain energy function, calculate material stress response data, and bind material properties to the corresponding mesh nodes; Perform load and contact settings between the mesh model and the pillow geometry model after setting material properties; Gravity load is applied to the bottom surface of the head and neck geometric model, and vertical displacement load is applied to the top surface of the head and neck geometric model to establish the overall force boundary conditions; frictional contact relationship is established between the lower surface of the head and neck geometric model and the upper surface of the pillow geometric model, and the friction coefficient, normal stiffness and tangential penalty parameters are input to generate contact constraint data. Static simulation calculations are performed under contact constraint data. The load step size and convergence conditions are set, the stress and strain values ​​of each mesh node are calculated, and the pressure distribution data, strain distribution data and contact area data of the contact area between the occiput and the back of the neck are output.

[0007] In a preferred embodiment, step S3 further includes importing pressure distribution data into the computing environment, setting a time step sequence according to the simulation time interval, extracting pressure distribution data of each pressure area at each time step, and establishing a time index according to the time sequence. Perform pressure change calculations under time index: calculate the pressure difference of the same pressure area within adjacent time steps, and obtain the pressure change rate with the time step length as the denominator; sort the obtained pressure change rates by spatial coordinates to generate an instantaneous stress change sequence for each pressure area; Based on the instantaneous stress change sequence, time accumulation calculation is performed: with the time step as the integration interval, the stress change of each compressed area is gradually accumulated using the trapezoidal integration method, and the compression integration result of the soft tissue over the entire simulation cycle is calculated to obtain the cumulative stress of the soft tissue under pressure. The cumulative stress is mapped to the spatial coordinates of the head and neck geometric model. The mapping relationship of the cumulative stress on the spatial coordinates is calculated in each pressure region to generate and output the cumulative stress of soft tissue under pressure with spatial distribution characteristics.

[0008] In a preferred embodiment, S4 further includes performing a one-to-one mapping between the cumulative stress of the soft tissue under pressure and the spatial coordinates of the head and neck geometric model, binding the cumulative stress of each grid node to the corresponding geometric coordinates by establishing a spatial index table; after the mapping is completed, performing interpolation smoothing calculation on the mapping result to generate a continuously distributed pressure field; In the 3D modeling environment, surface parameterization is performed based on the pressure field. By calculating the local pressure gradient at each node position, the gradient change is introduced into the surface parameter function as a curvature correction term. During the parameterization process, the head, neck and posterior regions are defined as independent parameter domains. The geometric curvature of each parameter domain is determined by the combination of length and height parameters, forming a surface parameter system under pressure feedback. The morphological response calculation is performed under the parameter system. By establishing a curvature feedback channel between adjacent parameter domains, the curvature radius of each region is adjusted according to the inverse relationship of pressure intensity. The curvature radius of the high-pressure region is reduced to enhance local support capacity, while the curvature radius of the low-pressure region is increased to maintain overall smoothness. The output is a parameterized surface after curvature feedback adjustment.

[0009] In a preferred embodiment, S4 further includes constructing a slow elastic sustained-release layer model in the neck parameter domain, establishing a functional relationship between the material nonlinear parameters of the sustained-release layer and the cumulative stress of the corresponding node in the pressure field, and calculating the deformation distribution and recovery rate curve of the sustained-release layer based on the function. Adaptive thickness adjustment is performed in regions with uneven deformation distribution. The thickness gradient distribution of the slow-release layer is calculated based on the compressive strength of each node, so that the deformation stroke of the slow-release layer is proportional to the pressure strength, thereby realizing buffer response control based on pressure distribution. After the parametric surface and the slow-release layer are constructed, curvature harmonization and boundary continuity trimming are performed. By calculating the difference in normal angle at the intersection of adjacent parameter domains and applying curvature balance constraints, the rate of curvature change of the transition zone is controlled, so that the surfaces of the head region, neck region and back region remain geometrically and mechanically continuous, generating and outputting the overall S-shaped pillow surface model.

[0010] In a preferred embodiment, S5 further includes importing the S-shaped pillow surface model into the optimization calculation environment, and constructing a design variable vector by extracting the length parameters, height parameters, and deformation of the slow-release layer of the head region, neck region, and back region. Import the cumulative stress data of soft tissue compression, and establish a node index table based on the spatial coordinates of the head and neck geometric model; Calculate the equivalent stress and shear strain values ​​at each node location: using the stress tensor at the node as input, the equivalent stress value is obtained through principal stress decomposition; using the strain tensor at the node as input, the shear strain value is obtained through shear components. The calculated equivalent stress value, shear strain value and the cumulative stress of soft tissue under pressure are stored in the node index table to form a set of target indicators.

[0011] In a preferred embodiment, S5 further includes establishing an objective function system based on a set of objective indicators in an optimization calculation environment. The objective function system includes a stress objective function with the mean equivalent stress, a deformation objective function constructed with the sum of squared shear strains, and a compression objective function constructed with the cumulative stress of soft tissue under pressure. Weight coefficients are established for the stress objective function, deformation objective function, and compression objective function respectively, forming a weight coefficient vector. The weight coefficient vector, together with the stress objective function, deformation objective function, and compression objective function, constitutes a set of multi-objective optimization functions. In the multi-objective optimization function set, the design variable vector is used as input, and the value range of the design variable is set according to the physical constraints of the design variable. Iterative optimization calculation is performed under the multi-objective optimization function set, and the design variable is updated generation by generation using a non-dominated sorting genetic algorithm. In each iteration, the objective function value is calculated and the solution set is selected and retained according to the non-dominated sorting criterion to form the Pareto candidate solution set; Perform comprehensive decision analysis on the Pareto candidate solution set. Calculate the proximity value of each candidate solution by constructing an entropy weighted model. After sorting the proximity values, select the design variable combination that ranks first, solve for the design parameter combination, and output it.

[0012] In a preferred embodiment, S6 further includes importing the design parameter combination into the 3D printing software and loading the S-shaped pillow surface model in the modeling environment. The length and height parameters of the head, neck, and posterior regions, as well as the deformation of the slow-release layer, are updated based on the combination of design parameters to generate a three-dimensional geometric data model for printing. In the 3D printing software, the printing parameters are set, including the printing layer thickness, path spacing, infill rate, printing speed, and nozzle temperature. The printing layer thickness is calculated based on the curvature of the surface geometry to determine the layer height range, the path spacing is calculated based on the infill density function to determine the distance between adjacent paths, and the nozzle temperature is determined based on the flow viscosity characteristics of the thermoplastic polyurethane material. Under set parameter conditions, the printing path generation calculation is performed. The three-dimensional geometric data model is divided into continuous layers through a layer slicing algorithm. The coordinate sequence of the contour path and the internal filling path of each layer is calculated. The three-dimensional printing model file is generated according to the printing direction and the material deposition rate, and the corresponding printing control instructions are generated. The 3D printing model file and printing control instructions are imported into the printing equipment control system. The printing operation is performed using thermoplastic polyurethane material, and layer forming, path scanning and material melting deposition are performed in sequence. During the printing process, the nozzle temperature, material flow rate and layer thickness parameters are monitored in real time, and the stability and forming accuracy of the printing process are maintained through feedback adjustment. After printing, cooling and demolding operations are performed. The shape and geometric dimensions of the printed part are checked to see if they meet the limits of the design parameter combination, thus forming the finished anti-pressure sore pillow and outputting it.

[0013] The technical effects and advantages of this invention are as follows: This invention establishes a three-dimensional geometric model of the skull, cervical spine and soft tissues, and combines finite element simulation with time integration calculation to realize the quantitative calculation of soft tissue compression in the time dimension, thus solving the problem that existing methods can only analyze static pressure distribution and cannot reflect long-term pressure accumulation. By establishing a contact pair between the head and neck geometric model and the pillow geometric model in finite element modeling software, and setting material parameters, boundary conditions and contact relationships, the stress state between the head and neck and the pillow body can be simulated and calculated, providing basic data for subsequent pressure and deformation analysis. By setting the time step sequence and pressure change rate calculation steps, the pressure change during the simulation process is integrated to obtain the cumulative stress of soft tissue under pressure, so that the design process can adjust the pillow structure parameters according to the cumulative law of pressure on the time axis. By establishing a correspondence between the cumulative stress of soft tissue under pressure and spatial coordinates, and introducing curvature correction in the parametric construction of the surface, the surface of the pillow produces corresponding curvature changes in different pressure areas, thus realizing a functional relationship between the surface shape and the pressure distribution. By constructing a slow-elasticity sustained-release layer model within the neck parameter domain and calculating the thickness gradient and deformation distribution of the sustained-release layer based on the compressive strength, the sustained-release layer can generate corresponding deformation strokes in different pressure regions, forming a controlled support corresponding to the pressure strength. Attached Figure Description

[0014] Figure 1This is a flowchart of the method steps of the present invention.

[0015] Figure 2 A schematic diagram illustrating the use of the pressure ulcer prevention pillow by the user of this invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Refer to the instruction manual appendix Figure 1-2 An embodiment of the present invention provides a pillow design method for preventing pressure sores on the neck of bedridden disabled persons, comprising: S1. By importing medical imaging data of bedridden disabled persons, extract the structural information of the skull, cervical spine and soft tissues, perform surface fitting operation on the structural information in the three-dimensional reconstruction software, form a head and neck geometric model including the occipital region and the posterior cervical region and output it. S2. Import the head and neck geometric model into the finite element modeling software, set the skull and vertebrae as rigid materials, set the soft tissue as hyperelastic materials, and form a contact state by applying gravity load and downward displacement load. Perform static simulation calculation and output the pressure distribution data, strain distribution data and contact area data of the contact area between the occipital region and the back of the neck. S3. Perform continuous calculations on the pressure distribution data according to the time step to form the stress time series of each pressure region; perform integration on the stress time series to solve for the cumulative stress of the soft tissue; the cumulative stress is the result of integrating stress with respect to time, which is used to characterize the degree of pressure accumulation of the soft tissue in the time dimension. S4. Correspond the accumulated stress to the spatial coordinates of the head and neck geometric model, perform surface parametric construction in the modeling software, divide the pillow surface into the head region, neck region and back region, define the geometric curvature of each region with length and height parameters, set a slow elastic release layer in the neck region, and form a controlled support process by controlling the deformation and recovery rate of the release layer, and connect the geometric curvature of each region with a continuous curve to form the overall S-shaped pillow surface model; S5. Import the S-shaped pillow surface model into the optimization calculation program, input the length parameter, height parameter and deformation of the slow-release layer into the multi-objective optimization program, execute the optimization calculation with soft tissue equivalent stress, shear strain and cumulative stress as objective functions, and solve the design parameter combination. S6. Import the design parameters into the 3D printing software to generate a 3D printing model file. Set the printing layer thickness, infill rate, printing speed and nozzle temperature. Use thermoplastic polyurethane material to perform the printing operation to form the finished anti-pressure sore pillow.

[0018] S1 also includes performing region segmentation operations in medical image processing software by importing medical image data of bedridden disabled persons; The region segmentation operation includes extracting the skull boundary, cervical spine boundary, and soft tissue boundary in the image based on the grayscale threshold range of the skull, cervical spine, and soft tissue, and outputting the segmented image dataset; Import the image dataset into the 3D reconstruction software to perform volume reconstruction calculation. The volume reconstruction calculation includes calculating the spatial coordinate position relationship of each layer boundary point in the 3D coordinate system based on the spatial resolution and pixel spacing between image layers, and generating a spatial data set of the skull surface, cervical spine surface and soft tissue surface. The spatial data set is imported into the modeling software to perform surface fitting operations. The surface fitting operations include establishing a spatial surface function with boundary points as control points, calculating the spatial coordinate distribution of the skull surface, cervical spine surface and soft tissue surface based on the control point positions, and generating continuous head and neck surface model data. Import the head and neck surface model data into the geometry processing software to perform boundary trimming operations. The boundary trimming operations include identifying the opening edges between surfaces, performing edge closure and normal correction calculations, generating a closed head and neck geometric model and outputting it. It should be further explained that by importing medical image data of bedridden disabled persons, region segmentation operations are performed in a medical image processing environment. This operation is based on the structural features of the skull, cervical spine and soft tissue in the images, extracts their boundary contours and outputs the segmented image dataset. The image dataset is then imported into 3D reconstruction software. Based on the spatial resolution and pixel spacing between image layers, the positional relationship of the boundary points in the 3D coordinate system is calculated. Volume reconstruction operations are performed to generate a spatial data set containing the skull surface, cervical spine surface and soft tissue surface. Subsequently, a spatial surface function is established with the boundary points as control points. Surface fitting and boundary trimming are performed to finally form a closed head and neck geometric model and output it. This step completes structural segmentation and volume reconstruction under the spatial resolution constraints between continuous layers, so that the generated head and neck geometric model retains the anatomical accuracy of the original image and has continuity and closure that can be used for simulation calculation, providing a stable geometric basis for subsequent stress analysis and parametric design.

[0019] S2 also includes importing the head and neck geometric model into the finite element modeling software, and importing the pillow geometric model generated based on external parametric modeling; the pillow geometric model is generated by setting the length and height parameters of the head, neck and back and connecting them with continuous curves, and is used to establish contact pairing with the head and neck geometric model. Mesh generation is performed on the head and neck geometry model by setting node spacing and boundary constraints. The node spacing range is adjusted according to the local curvature. The node spacing is determined based on the local curvature of the head and neck geometry model. A lower limit for node spacing is set for regions with high curvature, and an upper limit for node spacing is set for regions with low curvature. Fixed constraints are applied at the boundary between the skull and cervical vertebrae, and free constraints are applied at the outer boundary of the soft tissue. A continuous mesh model is generated and output. Perform material property setting operations in the mesh model, set the skull and cervical spine regions as rigid materials, and input density, elastic modulus and Poisson's ratio parameters; set the soft tissue region as a hyperelastic material, input fitting parameters according to the strain energy function, calculate material stress response data, and bind material properties to the corresponding mesh nodes; Perform load and contact settings between the mesh model and the pillow geometry model after setting material properties; Gravity load is applied to the bottom surface of the head and neck geometric model, and vertical displacement load is applied to the top surface of the head and neck geometric model to establish the overall force boundary conditions; frictional contact relationship is established between the lower surface of the head and neck geometric model and the upper surface of the pillow geometric model, and the friction coefficient, normal stiffness and tangential penalty parameters are input to generate contact constraint data. Static simulation calculations were performed under contact constraint data. The load step size and convergence conditions were set, and the stress and strain values ​​of each mesh node were calculated. The pressure distribution data, strain distribution data and contact area data of the contact area between the occiput and the back of the neck were output. It should be further explained that this step involves importing the head and neck geometry model and the parametrically generated pillow geometry model into the finite element modeling environment, meshing the head and neck model by setting node spacing and boundary constraints, and adaptively adjusting the node density based on local curvature. Fixed constraints are applied at the boundary between the skull and cervical vertebrae, and free constraints are applied at the outer boundary of the soft tissue. Then, material properties are set, with the skull and cervical vertebrae defined as rigid materials and the soft tissue defined as hyperelastic materials. The stress response of the materials is calculated by inputting density, elastic modulus, Poisson's ratio, and strain energy function parameters. Finally, gravity load, displacement load, and friction contact conditions are applied between the two models, and static simulation calculations are performed to obtain the pressure distribution, strain distribution, and contact area data of the occipital and posterior neck regions. A finite element calculation framework for multi-layer material properties and complex contact boundaries was established, and the simulation of the stress on the head, neck and pillow body under bed rest conditions was realized, providing mechanical input for subsequent pressure accumulation and optimization.

[0020] In S3, the process also includes importing pressure distribution data into the computational environment, setting a time step sequence based on the simulation time interval, extracting pressure distribution data for each pressure zone at each time step, and establishing a time index based on the time sequence to control subsequent continuous calculations. Perform pressure change calculations under time index: calculate the pressure difference of the same pressure area within adjacent time steps, and obtain the pressure change rate with the time step length as the denominator; sort the obtained pressure change rates by spatial coordinates to generate an instantaneous stress change sequence for each pressure area; Based on the instantaneous stress change sequence, time accumulation calculation is performed: with the time step as the integration interval, the stress change of each compressed area is gradually accumulated using the trapezoidal integration method, and the compression integration result of the soft tissue over the entire simulation cycle is calculated to obtain the cumulative stress of the soft tissue under pressure. The cumulative stress is mapped to the spatial coordinates of the head and neck geometric model. The mapping relationship of the cumulative stress on the spatial coordinates is calculated in each pressure region to generate and output the cumulative stress of soft tissue under pressure with spatial distribution characteristics. Furthermore, this step involves importing the pressure distribution data into the computational environment according to the time step sequence after the simulation calculation, and continuously calculating the pressure changes in each pressure-bearing region. By calculating the pressure difference within adjacent time steps and its rate of change, an instantaneous stress change sequence is formed. Then, using the time step as the integration interval, the trapezoidal integration method is used to perform time accumulation calculations on each pressure-bearing region to obtain the pressure integration results of the soft tissue throughout the entire simulation cycle. Finally, the obtained accumulated stress is correlated with spatial coordinates to generate soft tissue pressure accumulation data with spatial distribution characteristics. This extends traditional static contact analysis to the time domain accumulation dimension, realizing the quantitative modeling of the chronic pressure process. This allows the pillow design to not only reflect the instantaneous support force but also optimize the slow-release effect based on stress accumulation in the time dimension.

[0021] In S4, the cumulative stress of soft tissue under pressure is mapped one-to-one with the spatial coordinates of the head and neck geometric model. A spatial index table is established to bind the cumulative stress of each grid node to the corresponding geometric coordinates. After the mapping is completed, interpolation smoothing calculation is performed on the mapping results to generate a continuously distributed pressure field to eliminate the influence of local load discretization on the surface construction. In the 3D modeling environment, surface parameterization is performed based on the pressure field. By calculating the local pressure gradient at each node position, the gradient change is introduced into the surface parameter function as a curvature correction term. During the parameterization process, the head, neck and posterior regions are defined as independent parameter domains. The geometric curvature of each parameter domain is determined by the combination of length and height parameters, forming a surface parameter system under pressure feedback. Morphological response calculations are performed under a parameter system. By establishing curvature feedback channels between adjacent parameter domains, the curvature radius of each region is adjusted according to the inverse relationship of pressure intensity. The curvature radius of the high-pressure region is reduced to enhance local support capacity, while the curvature radius of the low-pressure region is increased to maintain overall smoothness. This forms an adaptive adjustment mechanism between the pressure distribution and the surface geometry, and outputs a parameterized surface after curvature feedback adjustment, providing an input basis for the construction of the slow-release layer and the subsequent generation of the S-shaped pillow surface model. It should be noted that in this step, a continuous pressure field is generated by mapping the cumulative pressure on the soft tissue to the spatial coordinates of the head and neck geometric model. Based on the pressure field, surface parametric construction is performed in the 3D modeling environment. The local pressure gradient is calculated at each node and introduced into the parametric function as a curvature correction term. By establishing a curvature feedback channel, the curvature radius of the high-pressure area is reduced and the curvature radius of the low-pressure area is increased, so that the surface geometry can automatically adjust with the pressure distribution. This realizes the mechanical feedback correlation between the pillow surface shape and the pressure distribution, so that the pillow geometry can adaptively adjust the stress state, thereby dispersing local high-pressure points at the structural level and improving the uniformity of neck support.

[0022] In S4, a slow elastic release layer model is also constructed in the neck parameter domain. By establishing a functional relationship between the material nonlinear parameters of the release layer and the cumulative stress of the corresponding nodes of the compressive field, the deformation distribution and recovery rate curve of the release layer are calculated based on the function. Adaptive thickness adjustment is performed in regions with uneven deformation distribution. The thickness gradient distribution of the slow-release layer is calculated based on the compressive strength of each node, so that the deformation stroke of the slow-release layer is proportional to the pressure strength, thereby realizing buffer response control based on pressure distribution. After the parametric surface and the slow-release layer are constructed, curvature harmonization and boundary continuity trimming are performed. By calculating the difference in normal angle at the intersection of adjacent parameter domains and applying curvature balance constraints, the rate of curvature change of the transition zone is controlled, so that the surfaces of the head region, neck region and back region remain geometrically and mechanically continuous. The overall S-shaped pillow surface model is generated and output as the input model for subsequent optimization calculations. Furthermore, in this step, a slow-elasticity sustained-release layer model is established within the neck parameter domain. The material nonlinear parameters of the sustained-release layer are functionally correlated with the cumulative stress of the compressive field. Based on the function, the deformation distribution and recovery rate curve of the sustained-release layer are calculated. Then, the thickness gradient of the sustained-release layer is determined by the compressive strength of each node, so that the deformation stroke is proportional to the pressure intensity. After the construction is completed, curvature harmonization and boundary continuity trimming are performed. The difference in the normal angle between adjacent regions is calculated and curvature balance constraints are applied to ensure the geometric and mechanical continuity of the head, neck, and posterior regions. This forms a sustained-release structure that adaptively adjusts with the compressive strength, which can absorb deformation energy under high pressure while maintaining the continuity of the overall surface, achieving a unity of dynamic pressure buffering and mechanical compliance.

[0023] In S5, the S-shaped pillow surface model is also imported into the optimization calculation environment. By extracting the length parameters, height parameters and deformation of the slow-release layer of the head region, neck region and back region, a design variable vector is constructed. Import the cumulative stress data of soft tissue compression, and establish a node index table based on the spatial coordinates of the head and neck geometric model; Calculate the equivalent stress and shear strain values ​​at each node location: using the stress tensor at the node as input, the equivalent stress value is obtained through principal stress decomposition; using the strain tensor at the node as input, the shear strain value is obtained through shear components. The calculated equivalent stress value, shear strain value and cumulative stress of soft tissue under pressure are stored in the node index table to form a set of target indicators for multi-objective optimization. Furthermore, in this step, by importing the S-shaped pillow surface model and the accumulated pressure of soft tissue into the optimization calculation environment, a node index table is established based on spatial coordinates. The equivalent stress and shear strain values ​​are calculated at each node, obtained through principal stress decomposition and shear component analysis, respectively. The equivalent stress, shear strain, and accumulated pressure are stored in the node index table to form a complete set of target indicators. An evaluation basis is established in both geometric and mechanical dimensions, enabling the optimization algorithm to comprehensively consider three types of indicators: pillow support, soft tissue deformation, and accumulated pressure, providing accurate input for multi-objective optimization.

[0024] In S5, it also includes establishing an objective function system based on the set of objective indicators in the optimization calculation environment. The objective function system includes a stress objective function with the mean equivalent stress, a deformation objective function with the sum of squared shear strains, and a compression objective function with the cumulative stress of soft tissue under pressure. Weight coefficients are established for the stress objective function, deformation objective function, and compression objective function respectively, forming a weight coefficient vector. The weight coefficient vector, together with the stress objective function, deformation objective function, and compression objective function, constitutes a set of multi-objective optimization functions. In the multi-objective optimization function set, the design variable vector is used as input, and the value range of the design variable is set according to the physical constraints of the design variable. Iterative optimization calculation is performed under the multi-objective optimization function set, and the design variable is updated generation by generation using a non-dominated sorting genetic algorithm. In each iteration, the objective function value is calculated and the solution set is selected and retained according to the non-dominated sorting criterion to form the Pareto candidate solution set; Perform comprehensive decision analysis on the Pareto candidate solution set, calculate the closeness value of each candidate solution by constructing an entropy weighted model, sort the closeness values ​​and select the design variable combination that ranks first, solve for the design parameter combination and output it; It should be further explained that this step establishes an objective function system based on the set of target indicators, including stress, deformation, and compressive objective functions constructed using the mean equivalent stress, the sum of squared shear strains, and the cumulative compressive stress, respectively. A weighted coefficient vector is then set to form a joint optimization function set. Using the design variable vector as input, a non-dominated sorting genetic algorithm is executed iteratively under constraints. An entropy-weighted model is used to evaluate the closeness of each candidate solution, selecting the closest combination of design parameters. This achieves a multi-objective, strongly constrained parallel optimization process, establishing an equilibrium relationship among various mechanical indicators, and ensuring that the final design achieves a stable combination of design parameters under mechanical equilibrium conditions between compressive stress mitigation and deformation compatibility.

[0025] S6 also includes importing design parameter combinations into 3D printing software and loading the S-shaped pillow surface model in the modeling environment; The length and height parameters of the head, neck, and posterior regions, as well as the deformation of the slow-release layer, are updated based on the combination of design parameters to generate a three-dimensional geometric data model for printing. In the 3D printing software, the printing parameters are set, including the printing layer thickness, path spacing, infill rate, printing speed, and nozzle temperature. The printing layer thickness is calculated based on the curvature of the surface geometry to determine the layer height range, the path spacing is calculated based on the infill density function to determine the distance between adjacent paths, and the nozzle temperature is determined based on the flow viscosity characteristics of the thermoplastic polyurethane material. Under set parameter conditions, the printing path generation calculation is performed. The three-dimensional geometric data model is divided into continuous layers through a layer slicing algorithm. The coordinate sequence of the contour path and the internal filling path of each layer is calculated. The three-dimensional printing model file is generated according to the printing direction and the material deposition rate, and the corresponding printing control instructions are generated. The 3D printing model file and printing control instructions are imported into the printing equipment control system. The printing operation is performed using thermoplastic polyurethane material, and layer forming, path scanning and material melting deposition are performed in sequence. During the printing process, the nozzle temperature, material flow rate and layer thickness parameters are monitored in real time, and the stability and forming accuracy of the printing process are maintained through feedback adjustment. After printing, cooling and demolding operations are performed. The shape and geometric dimensions of the printed part are checked to see if they meet the limits of the design parameter combination, thus forming the finished anti-pressure sore pillow and outputting it. It should be noted that in this step, by importing the design parameters into the 3D printing environment, loading the S-shaped pillow surface model into the modeling software, and updating the length, height, and slow-release layer deformation parameters of the head, neck, and back areas according to the design parameters, a 3D geometric data model for printing is generated. Based on the model's curvature and material performance parameters, the printing layer thickness, path spacing, and nozzle temperature are calculated. A layer-by-layer slicing algorithm is used to generate a printing control command file, which is then input into the 3D printing equipment control system. Thermoplastic polyurethane material is used to perform layer-by-layer melt deposition and real-time feedback adjustment. During the printing process, nozzle temperature, material flow rate, and layer thickness are monitored. The printing process is controlled by parameterizing the layer thickness, path spacing, temperature, and deposition rate. This ensures the stability of the printing process and the conformity of the geometry. After printing, cooling and demolding operations are performed. The shape and geometry of the formed part are checked to see if they meet the range of the design parameter combination. The finished anti-pressure sore pillow is then output. This step achieves consistency between digital design data and physical forming process by parameterizing the layer thickness, path spacing, temperature, and deposition rate during the printing process. This ensures that the formed part conforms to the design results in terms of geometry, structural continuity, and slow-release layer performance, thereby achieving the forming output of an anti-pressure sore pillow under controllable manufacturing conditions.

[0026] In practical applications, this pressure-relief pillow is suitable for head and neck support in long-term supine or lateral lying positions for bedridden disabled individuals. The geometric curvature distribution and slow-release layer deformation of the pressure-relief pillow obtained through the above steps correspond to the pressure distribution in the head, neck, and posterior regions, creating a controlled support effect at different head and neck positions. In high-pressure areas, the slow-release layer deformation increases to form a pressure buffer, while in low-pressure areas, geometric continuity and support stability are maintained, thereby reducing the cumulative effect of long-term pressure on the soft tissues behind the neck. Through the optimized balance of the cumulative stress, equivalent stress value, and shear strain value of the soft tissues under pressure, the generated S-shaped pillow surface model and slow-release layer model can achieve a correspondence between force and deformation.

[0027] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A pillow design method for preventing pressure sores on the neck of bedridden disabled persons, characterized in that, include: S1. By importing medical imaging data of bedridden disabled persons, extract the structural information of the skull, cervical spine and soft tissues, perform surface fitting operation on the structural information in the three-dimensional reconstruction software, form a head and neck geometric model and output it. S2. Import the head and neck geometric model into the finite element modeling software, set the skull and vertebrae as rigid materials, set the soft tissue as hyperelastic materials, and form a contact state by applying gravity load and downward displacement load. Perform static simulation calculation and output the pressure distribution data, strain distribution data and contact area data of the contact area between the occipital region and the back of the neck. S3. Perform continuous calculations on the pressure distribution data according to the time step to form the stress time series of each pressure region; perform integral calculations on the stress time series to solve for the cumulative stress of the soft tissue under pressure; S4. Correspond the accumulated stress to the spatial coordinates of the head and neck geometric model, perform surface parametric construction in the modeling software, divide the pillow surface into the head region, neck region and back region, define the geometric curvature of each region with length and height parameters, set a slow elastic release layer in the neck region, and form a controlled support process by controlling the deformation and recovery rate of the release layer, and connect the geometric curvature of each region with a continuous curve to form the overall S-shaped pillow surface model; S5. Import the S-shaped pillow surface model into the optimization calculation program, input the length parameter, height parameter and deformation of the slow-release layer into the multi-objective optimization program, execute the optimization calculation with soft tissue equivalent stress, shear strain and cumulative stress as objective functions, and solve the design parameter combination. S6. Import the design parameters into the 3D printing software to generate a 3D printing model file. Set the printing layer thickness, infill rate, printing speed and nozzle temperature. Use thermoplastic polyurethane material to perform the printing operation to form the finished anti-pressure sore pillow.

2. The pillow design method for preventing pressure sores on the neck of bedridden disabled persons according to claim 1, characterized in that: S1 also includes performing region segmentation operations in medical image processing software by importing medical image data of bedridden disabled persons; The region segmentation operation includes extracting the skull boundary, cervical spine boundary, and soft tissue boundary in the image based on the grayscale threshold range of the skull, cervical spine, and soft tissue, and outputting the segmented image dataset; Import the image dataset into the 3D reconstruction software to perform volume reconstruction calculation. The volume reconstruction calculation includes calculating the spatial coordinate position relationship of each layer boundary point in the 3D coordinate system based on the spatial resolution and pixel spacing between image layers, and generating a spatial data set of the skull surface, cervical spine surface and soft tissue surface. The spatial data set is imported into the modeling software to perform surface fitting operations. The surface fitting operations include establishing a spatial surface function with boundary points as control points, calculating the spatial coordinate distribution of the skull surface, cervical spine surface and soft tissue surface based on the control point positions, and generating continuous head and neck surface model data. The head and neck surface model data is imported into the geometry processing software to perform boundary trimming operations. The boundary trimming operations include identifying the opening edges between surfaces, performing edge closure and normal correction calculations, generating a closed head and neck geometric model and outputting it.

3. The pillow design method for preventing pressure sores on the neck of bedridden disabled persons according to claim 2, characterized in that: S2 also includes importing the head and neck geometric model into the finite element modeling software, and importing the pillow geometric model generated based on external parametric modeling; the pillow geometric model is generated by setting the length and height parameters of the head, neck and back, and connecting them with continuous curves. The head and neck geometry model is meshed by setting node spacing and boundary constraints. The node spacing range is adjusted according to the local curvature. Fixed constraints are applied at the boundary between the skull and cervical vertebrae, and free constraints are applied at the outer boundary of the soft tissue to generate and output a continuous mesh model. Perform material property setting operations in the mesh model, set the skull and cervical spine regions as rigid materials, and input density, elastic modulus and Poisson's ratio parameters; set the soft tissue region as a hyperelastic material, input fitting parameters according to the strain energy function, calculate material stress response data, and bind material properties to the corresponding mesh nodes; Perform load and contact settings between the mesh model and the pillow geometry model after setting material properties; Gravity load is applied to the bottom surface of the head and neck geometric model, and vertical displacement load is applied to the top surface of the head and neck geometric model to establish the overall force boundary conditions; frictional contact relationship is established between the lower surface of the head and neck geometric model and the upper surface of the pillow geometric model, and the friction coefficient, normal stiffness and tangential penalty parameters are input to generate contact constraint data. Static simulation calculations are performed under contact constraint data. The load step size and convergence conditions are set, the stress and strain values ​​of each mesh node are calculated, and the pressure distribution data, strain distribution data and contact area data of the contact area between the occiput and the back of the neck are output.

4. The pillow design method for preventing pressure sores on the neck of bedridden disabled persons according to claim 3, characterized in that: In S3, the process also includes importing pressure distribution data into the computational environment, setting the time step sequence according to the simulation time interval, extracting pressure distribution data of each pressure zone in each time step, and establishing a time index according to the time sequence. Perform pressure change calculations under time index: calculate the pressure difference of the same pressure area within adjacent time steps, and obtain the pressure change rate with the time step length as the denominator; sort the obtained pressure change rates by spatial coordinates to generate an instantaneous stress change sequence for each pressure area; Based on the instantaneous stress change sequence, time accumulation calculation is performed: with the time step as the integration interval, the stress change of each compressed area is gradually accumulated using the trapezoidal integration method, and the compression integration result of the soft tissue over the entire simulation cycle is calculated to obtain the cumulative stress of the soft tissue under pressure. The cumulative stress is mapped to the spatial coordinates of the head and neck geometric model. The mapping relationship of the cumulative stress on the spatial coordinates is calculated in each pressure region to generate and output the cumulative stress of soft tissue under pressure with spatial distribution characteristics.

5. A pillow design method for preventing pressure sores on the neck of bedridden disabled persons according to claim 4, characterized in that: In S4, the cumulative stress of soft tissue compression is mapped one-to-one with the spatial coordinates of the head and neck geometric model. A spatial index table is established to bind the cumulative stress of each grid node to the corresponding geometric coordinates. After the mapping is completed, interpolation smoothing calculation is performed on the mapping results to generate a continuously distributed compression field. In the 3D modeling environment, surface parameterization is performed based on the pressure field. By calculating the local pressure gradient at each node position, the gradient change is introduced into the surface parameter function as a curvature correction term. During the parameterization process, the head, neck and posterior regions are defined as independent parameter domains. The geometric curvature of each parameter domain is determined by the combination of length and height parameters, forming a surface parameter system under pressure feedback. The morphological response calculation is performed under the parameter system. By establishing a curvature feedback channel between adjacent parameter domains, the curvature radius of each region is adjusted according to the inverse relationship of pressure intensity. The curvature radius of the high-pressure region is reduced to enhance local support capacity, while the curvature radius of the low-pressure region is increased to maintain overall smoothness. The output is a parameterized surface after curvature feedback adjustment.

6. A pillow design method for preventing pressure sores on the neck of bedridden disabled persons according to claim 5, characterized in that: In S4, a slow elastic release layer model is also constructed in the neck parameter domain. By establishing a functional relationship between the material nonlinear parameters of the release layer and the cumulative stress of the corresponding nodes of the compressive field, the deformation distribution and recovery rate curve of the release layer are calculated based on the function. Adaptive thickness adjustment is performed in regions with uneven deformation distribution. The thickness gradient distribution of the slow-release layer is calculated based on the compressive strength of each node, so that the deformation stroke of the slow-release layer is proportional to the pressure strength, thereby realizing buffer response control based on pressure distribution. After the parametric surface and the slow-release layer are constructed, curvature harmonization and boundary continuity trimming are performed. By calculating the difference in normal angle at the intersection of adjacent parameter domains and applying curvature balance constraints, the rate of curvature change of the transition zone is controlled, so that the surfaces of the head region, neck region and back region remain geometrically and mechanically continuous, generating and outputting the overall S-shaped pillow surface model.

7. A pillow design method for preventing pressure sores on the neck of bedridden disabled persons according to claim 6, characterized in that: In S5, the S-shaped pillow surface model is also imported into the optimization calculation environment. By extracting the length parameters, height parameters and deformation of the slow-release layer of the head region, neck region and back region, a design variable vector is constructed. Import the cumulative stress data of soft tissue compression, and establish a node index table based on the spatial coordinates of the head and neck geometric model; Calculate the equivalent stress and shear strain values ​​at each node location: using the stress tensor at the node as input, the equivalent stress value is obtained through principal stress decomposition; using the strain tensor at the node as input, the shear strain value is obtained through shear components. The calculated equivalent stress value, shear strain value and the cumulative stress of soft tissue under pressure are stored in the node index table to form a set of target indicators.

8. A pillow design method for preventing neck pressure sores in bedridden disabled persons according to claim 7, characterized in that: In S5, it also includes establishing an objective function system based on the set of objective indicators in the optimization calculation environment. The objective function system includes a stress objective function with the mean equivalent stress, a deformation objective function with the sum of squared shear strains, and a compression objective function with the cumulative stress of soft tissue under pressure. Weight coefficients are established for the stress objective function, deformation objective function, and compression objective function respectively, forming a weight coefficient vector. The weight coefficient vector, together with the stress objective function, deformation objective function, and compression objective function, constitutes a set of multi-objective optimization functions. In the multi-objective optimization function set, the design variable vector is used as input, and the value range of the design variable is set according to the physical constraints of the design variable. Iterative optimization calculation is performed under the multi-objective optimization function set, and the design variable is updated generation by generation using a non-dominated sorting genetic algorithm. In each iteration, the objective function value is calculated and the solution set is selected and retained according to the non-dominated sorting criterion to form the Pareto candidate solution set; Perform comprehensive decision analysis on the Pareto candidate solution set. Calculate the proximity value of each candidate solution by constructing an entropy weighted model. After sorting the proximity values, select the design variable combination that ranks first, solve for the design parameter combination, and output it.

9. A pillow design method for preventing pressure sores on the neck of bedridden disabled persons according to claim 8, characterized in that: S6 also includes importing design parameter combinations into 3D printing software and loading the S-shaped pillow surface model in the modeling environment; The length and height parameters of the head, neck, and posterior regions, as well as the deformation of the slow-release layer, are updated based on the combination of design parameters to generate a three-dimensional geometric data model for printing. In the 3D printing software, the printing parameters are set, including the printing layer thickness, path spacing, infill rate, printing speed, and nozzle temperature. The printing layer thickness is calculated based on the curvature of the surface geometry to determine the layer height range, the path spacing is calculated based on the infill density function to determine the distance between adjacent paths, and the nozzle temperature is determined based on the flow viscosity characteristics of the thermoplastic polyurethane material. Under set parameter conditions, the printing path generation calculation is performed. The three-dimensional geometric data model is divided into continuous layers through a layer slicing algorithm. The coordinate sequence of the contour path and the internal filling path of each layer is calculated. The three-dimensional printing model file is generated according to the printing direction and the material deposition rate, and the corresponding printing control instructions are generated. The 3D printing model file and printing control instructions are imported into the printing equipment control system. The printing operation is performed using thermoplastic polyurethane material, and layer forming, path scanning and material melting deposition are performed in sequence. During the printing process, the nozzle temperature, material flow rate and layer thickness parameters are monitored in real time, and the stability and forming accuracy of the printing process are maintained through feedback adjustment. After printing, cooling and demolding operations are performed. The shape and geometric dimensions of the printed part are checked to see if they meet the limits of the design parameter combination, thus forming the finished anti-pressure sore pillow and outputting it.

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