Skin intrinsic parameter inversion method, system, device and storage medium

Abstract

The application belongs to the technical field of biological tissue mechanics, and discloses a skin intrinsic parameter inversion method, system, device and storage medium. In view of the problems that an existing model is difficult to accurately characterize a skin structure and parameter inversion stability is insufficient, creep compliance data of a target skin is acquired, a multistage structure viscoelastic model constructed based on a skin histological structure is used, theoretical creep compliance is generated according to a candidate parameter vector, parameter inversion is carried out based on a matching relationship between the theoretical creep compliance and the creep compliance data, viscoelastic intrinsic parameters of the target skin are obtained, and an inversion result is output.

Description

Technical Field

[0001] This application belongs to the field of biomechanics technology, specifically relating to a method, system, device, and storage medium for inverting intrinsic parameters of skin. Background Technology

[0002] Skin is a typical viscoelastic biological tissue, and its mechanical response is determined by multiple structures, including cells, the cytoskeleton, and the extracellular matrix. The purpose of in vivo skin biomechanical testing is not only to obtain macroscopic deformation information but also to invert intrinsic parameters that characterize the internal structural state of the skin. Existing negative pressure suction in vivo skin testing technology is relatively mature; however, current commercial equipment typically outputs empirical indicators based on the curve morphology of the skin after it is drawn into the probe, lacking clear physical meaning and making it difficult to establish a direct correlation with the actual biomechanical structure within the skin. On the other hand, while some studies have attempted to solve for parameters from skin test data using viscoelastic models, they often directly apply classical models designed for homogeneous materials, failing to accurately characterize the multi-level heterogeneous structure of the skin, resulting in unclear correspondences between the obtained parameters and the internal structure of the skin. Furthermore, existing multi-parameter nonlinear solution processes are prone to problems such as parameter coupling, non-unique solutions, and sensitivity to initial values, leading to insufficient stability and repeatability of the parameter inversion results. Summary of the Invention

[0003] The purpose of this application is to provide a method, system, device and storage medium for inverting intrinsic parameters of skin, so as to overcome the technical problem that the existing technology is difficult to obtain intrinsic parameters related to skin structure due to the difficulty of accurately representing skin structure by the model and the insufficient stability of parameter inversion.

[0004] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, this application provides a method for inverting intrinsic parameters of skin, including: Obtain creep flexibility data of the target skin; Based on the creep compliance data, the viscoelastic intrinsic parameters of the target skin are obtained by parameter inversion through a multi-level structural viscoelastic model. The multi-level structural viscoelastic model is constructed based on the skin histological structure and is used to generate theoretical creep compliance based on candidate parameter vectors. The parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data. Based on the viscoelastic intrinsic parameters, the skin intrinsic parameters inversion results are output.

[0005] In one embodiment, obtaining the viscoelastic intrinsic parameters of the target skin by performing parameter inversion based on the creep compliance data and a multi-level structural viscoelastic model includes: Generate multiple sets of candidate parameter vectors within a preset parameter range; Substitute each set of candidate parameter vectors into the multi-level structure viscoelastic model to obtain the theoretical creep compliance corresponding to each set of candidate parameter vectors. Based on the matching relationship between the theoretical creep compliance and the creep compliance data, the viscoelastic intrinsic parameters of the target skin are determined.

[0006] In one embodiment, the step of generating multiple sets of candidate parameter vectors within a preset parameter range is achieved by performing a global search within the preset parameter range using a differential evolution algorithm. The determination of the viscoelastic intrinsic parameters of the target skin based on the matching relationship between the theoretical creep compliance and the creep compliance data includes: Based on the matching relationship between the theoretical creep compliance and the creep compliance data, a parameter vector for local optimization is determined from the multiple sets of candidate parameter vectors. The parameter vector used for local optimization is locally optimized using the nonlinear least squares method to obtain the optimized parameter vector; The optimized parameter vector is used as the viscoelastic intrinsic parameters of the target skin.

[0007] In one embodiment, the multi-level structure viscoelastic model is a two-level self-similar multi-level structure viscoelastic model, which characterizes the skin creep response through a first-level compliance and a second-level compliance. The first level of flexibility corresponds to the mechanical response of the cytoskeleton and microfilament network, while the second level of flexibility corresponds to the mechanical response of the extracellular collagen fiber network. The candidate parameter vector includes a first elastic modulus, a second elastic modulus, and a characteristic relaxation time of the skin's viscoelastic response. The first elastic modulus is related to the skin cytoskeleton and rapid response network, and the second elastic modulus is related to the skin's extracellular matrix.

[0008] In one embodiment, substituting each set of candidate parameter vectors into the multi-level structure viscoelastic model to obtain the theoretical creep compliance corresponding to each set of candidate parameter vectors includes: The first-order compliance is calculated based on the first elastic modulus in the candidate parameter vector and the characteristic relaxation time of the skin's viscoelastic response. The second-level compliance is calculated based on the first-level compliance and the second elastic modulus in the candidate parameter vector. The second-level compliance is taken as the theoretical creep compliance. The expression for the first-level flexibility is:

[0009] The expression for the second-order flexibility is:

[0010] The theoretical creep compliance expression is as follows:

[0011] in, This represents the theoretical creep compliance. Indicates the first level of flexibility. Indicates the second level of flexibility. Indicates the first elastic modulus. This represents the second elastic modulus. The characteristic relaxation time represents the skin's viscoelastic response. This indicates the creep response time.

[0012] In one embodiment, the viscoelastic intrinsic parameters include a first elastic modulus, a second elastic modulus, the characteristic relaxation time of the skin's viscoelastic response, and a total elastic modulus, wherein the total elastic modulus satisfies:

[0013] in, Represents the total elastic modulus. Indicates the first elastic modulus. This represents the second elastic modulus.

[0014] In one embodiment, before performing parameter inversion using a multi-level structural viscoelastic model based on the creep compliance data, the method further includes: The creep compliance data is preprocessed to obtain preprocessed creep compliance data; the preprocessing includes smoothing the creep compliance data and uniform resampling on the logarithmic time coordinate; the smoothing is cubic spline interpolation smoothing; the parameter inversion is based on the preprocessed creep compliance data.

[0015] Secondly, this application provides a skin intrinsic parameter inversion system, comprising: The acquisition module is used to acquire creep flexibility data of the target skin. The parameter inversion module is used to perform parameter inversion based on the creep compliance data using a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin. The multi-level structural viscoelastic model is constructed based on the skin histological structure and is used to generate theoretical creep compliance based on candidate parameter vectors. The parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data. The output module is used to output the skin intrinsic parameter inversion results based on the viscoelastic intrinsic parameters.

[0016] Thirdly, this application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the skin intrinsic parameter inversion method as described above.

[0017] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the skin intrinsic parameter inversion method described above.

[0018] Compared with the prior art, this application has the following beneficial technical effects: Firstly, this application provides a method for inverting intrinsic skin parameters. By acquiring creep compliance data of the target skin and constructing a multi-level structural viscoelastic model based on the skin's histological structure, the multi-level structural viscoelastic model can generate theoretical creep compliance from candidate parameter vectors. Then, based on the matching relationship between the theoretical creep compliance and the creep compliance data, parameter inversion is performed to obtain the intrinsic viscoelastic parameters of the target skin. Compared to methods that only output empirical indicators based on curve morphology or directly use homogeneous material models for solving, this application establishes a correspondence between measured creep compliance data, the theoretical creep compliance generated by the model, and candidate parameter vectors. This allows the inverted parameters to better correspond to the structural characteristics of the skin tissue and improves the stability of the intrinsic skin parameter inversion results.

[0019] Secondly, this application provides a skin intrinsic parameter inversion system. The system acquires creep compliance data of the target skin through an acquisition module, performs parameter inversion based on a multi-level structural viscoelastic model through a parameter inversion module, and outputs the skin intrinsic parameter inversion results through an output module. Because the parameter inversion module uses a multi-level structural viscoelastic model constructed based on skin histological structure and generates theoretical creep compliance based on candidate parameter vectors, and then obtains the viscoelastic intrinsic parameters of the target skin based on the matching relationship between the theoretical creep compliance and the creep compliance data, this system can achieve continuous processing of creep compliance data acquisition, parameter inversion, and result output, which is beneficial for stably obtaining intrinsic parameters related to skin structure.

[0020] Thirdly, this application provides a computer device that executes a specific computer program through a processor, enabling efficient implementation of the steps of the method of this application. When performing data processing tasks, the computer device can accurately perform numerical calculations and logical judgments, avoiding errors caused by human factors. At the same time, since the computer program has high stability and reliability, it can ensure the accuracy and consistency of the data processing results.

[0021] Fourthly, this application provides a computer-readable storage medium. By programming the steps of the method of this application into a computer program and storing it on a computer-readable storage medium, users can easily load these programs onto any compatible computer device and execute them without rewriting or converting the code, which greatly improves the convenience and flexibility of program execution. Attached Figure Description

[0022] Figure 1 This is a flowchart of the skin intrinsic parameter inversion method in this application embodiment.

[0023] Figure 2 This is a diagram of the original skin creep flexibility sequence in the embodiments of this application.

[0024] Figure 3 This is a schematic diagram of the fitting results of the multi-level structure viscoelastic model in the embodiments of this application.

[0025] Figure 4 This is a schematic diagram comparing the intrinsic viscoelastic parameters of skin at different locations of the same test subject in this application embodiment. Figure 4 (a) represents the characteristic relaxation time of the skin's viscoelastic response. Comparison chart, Figure 4 (b) in the figure represents the first elastic modulus. Comparison chart, Figure 4 (c) in the figure represents the second elastic modulus. Comparison chart, Figure 4 (d) in the figure represents the total elastic modulus. Comparison chart.

[0026] Figure 5 This is a schematic diagram of the skin intrinsic parameter inversion system in an embodiment of this application. Detailed Implementation

[0027] Skin is a typical viscoelastic biological tissue, and its mechanical response is influenced by multiple structures, including cells, the cytoskeleton, and the extracellular matrix. While existing in vivo skin mechanical testing can obtain information on the deformation curves of the skin after stress, current methods mostly output empirical indicators or directly apply classical models established for homogeneous materials to solve for parameters. This results in unclear correspondence between the obtained parameters and the internal structure of the skin, and insufficient stability of parameter inversion.

[0028] Based on the above background, this application proposes a method, system, device, and storage medium for inverting intrinsic skin parameters. This scheme utilizes a multi-level structural viscoelastic model constructed based on skin histological structure to generate theoretical creep compliance from candidate parameter vectors. Then, based on the matching relationship between the theoretical creep compliance and the creep compliance data of the target skin, parameter inversion is performed to obtain the viscoelastic intrinsic parameters of the target skin. This enhances the correspondence between the obtained parameters and the internal structure of the skin, and improves the stability of the skin intrinsic parameter inversion results.

[0029] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0030] To facilitate understanding, some key terms used in the specific implementation methods will be explained first, in order to unify terminology and ensure clarity in the following descriptions: Differential Evolution (DE) is an optimization algorithm used for global search.

[0031] Nonlinear Least Squares (NLS): refers to a parameter-solving method used for local optimization.

[0032] Levenberg-Marquardt algorithm (LM): refers to a specific implementation algorithm of nonlinear least squares method.

[0033] Example 1: like Figure 1 As shown, this embodiment provides a method for inverting intrinsic skin parameters. The method includes: acquiring creep compliance data of the target skin; performing parameter inversion based on the creep compliance data using a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin; and outputting the skin intrinsic parameter inversion results based on the viscoelastic intrinsic parameters. The multi-level structural viscoelastic model is constructed based on skin histological structure and is used to generate theoretical creep compliance from candidate parameter vectors. The parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data. The candidate parameter vector represents a parameter combination consisting of multiple parameter values ​​to be evaluated. During the parameter inversion process, the candidate parameter vector is substituted into the multi-level structural viscoelastic model to generate the corresponding theoretical creep compliance.

[0034] In this embodiment, the creep compliance data of the target skin refers to the compliance response data of the target skin as a function of time after being subjected to force. Obtaining the creep compliance data of the target skin provides a data foundation related to the actual mechanical response of the target skin for subsequent parameter inversion. Compared to outputting empirical indicators solely based on the skin deformation curve, creep compliance data reflects the time response characteristics of the target skin during loading, which is beneficial for subsequent quantitative analysis of the mechanical properties of the target skin using a multi-level structure viscoelastic model.

[0035] After obtaining the creep compliance data of the target skin, parameter inversion is performed based on this data using a multi-level structural viscoelastic model. This multi-level structural viscoelastic model is constructed based on skin histological structure and is used to characterize the mechanical responses related to the internal structure of the skin. Since the skin's mechanical response is influenced by multiple structures such as cells, the cytoskeleton, and the extracellular matrix, using a multi-level structural viscoelastic model based on skin histological structure allows for the establishment of a correspondence between the multi-level structural viscoelastic model and the characteristics of the internal skin structure, avoiding the problem of unclear correspondence between parameters and skin structure caused by directly applying a homogeneous material model.

[0036] In this embodiment, the multi-level structure viscoelastic model is used to generate theoretical creep compliance based on candidate parameter vectors. The theoretical creep compliance is the theoretical response result obtained by the multi-level structure viscoelastic model under the candidate parameter vector conditions, and the creep compliance data of the target skin is data obtained from actual testing. Parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data; that is, by the correspondence between the theoretical response result and the actual test data, viscoelastic intrinsic parameters characterizing the mechanical properties of the target skin are obtained. Therefore, the parameter inversion process no longer relies solely on empirical curve indices, but obtains the viscoelastic intrinsic parameters of the target skin through the correspondence between the model response and the measured data.

[0037] After obtaining the viscoelastic intrinsic parameters of the target skin, the skin intrinsic parameter inversion results are output based on these parameters. These inversion results can be used to characterize the mechanical properties of the target skin and provide parameter basis for subsequent analysis of the target skin's condition.

[0038] In summary, this embodiment obtains the creep compliance data of the target skin, uses a multi-level structural viscoelastic model based on skin histological structure to generate theoretical creep compliance based on candidate parameter vectors, and performs parameter inversion based on the matching relationship between theoretical creep compliance and creep compliance data to obtain the viscoelastic intrinsic parameters of the target skin. This helps to enhance the correspondence between the inverted parameters and the internal structure of the skin and improve the stability of the skin intrinsic parameter inversion results.

[0039] Example 2: The skin intrinsic parameter inversion method provided in this embodiment, based on Embodiment 1, further explains the process of obtaining the viscoelastic intrinsic parameters of the target skin by performing parameter inversion based on creep compliance data and a multi-level structural viscoelastic model.

[0040] In this embodiment, based on the creep compliance data, parameter inversion is performed using a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin. This includes: generating multiple sets of candidate parameter vectors within a preset parameter range; substituting each set of candidate parameter vectors into the multi-level structural viscoelastic model to obtain the theoretical creep compliance corresponding to each set of candidate parameter vectors; and determining the viscoelastic intrinsic parameters of the target skin based on the matching relationship between the theoretical creep compliance and the creep compliance data.

[0041] In this embodiment, the candidate parameter vectors are combinations of parameters used in the parameter inversion process to be substituted into the multi-level structural viscoelastic model. Each set of candidate parameter vectors corresponds to a set of parameter values ​​to be evaluated. Since the multi-level structural viscoelastic model is used to generate theoretical creep compliance based on the candidate parameter vectors, different candidate parameter vectors substituted into the multi-level structural viscoelastic model will yield corresponding theoretical creep compliance. The theoretical creep compliance is used to characterize the theoretical compliance response generated by the multi-level structural viscoelastic model under the corresponding candidate parameter vector conditions.

[0042] After obtaining the theoretical creep compliance values ​​corresponding to multiple sets of candidate parameter vectors, these theoretical creep compliance values ​​are correlated with the creep compliance data of the target skin to determine the matching relationship between them. This matching relationship reflects the degree of closeness between the theoretical creep compliance values ​​generated by substituting the candidate parameter vectors into a multi-level viscoelastic model and the actual creep response of the target skin. Based on this matching relationship, parameter results that can better characterize the creep compliance data of the target skin can be determined from the theoretical responses corresponding to the candidate parameter vectors, thereby obtaining the viscoelastic intrinsic parameters of the target skin.

[0043] With the above settings, the parameter inversion process no longer outputs empirical indicators solely based on the curve morphology of the target skin. Instead, it establishes a correspondence between the candidate parameter vector, the theoretical creep compliance generated by the multi-level structure viscoelastic model, and the creep compliance data of the target skin. This enables a clearer correspondence between the obtained intrinsic viscoelastic parameters and the actual creep response of the target skin, providing a parameter basis for subsequent quantitative characterization of the target skin's mechanical properties.

[0044] Example 3: The skin intrinsic parameter inversion method provided in this embodiment, based on embodiment 2, further explains the process of generating multiple sets of candidate parameter vectors within a preset parameter range, and determining the viscoelastic intrinsic parameters of the target skin based on the matching relationship between theoretical creep compliance and creep compliance data.

[0045] In this embodiment, multiple sets of candidate parameter vectors are generated within a preset parameter range, and a global search is performed within this range using a differential evolution algorithm. The preset parameter range defines the search range for each parameter in the candidate parameter vectors, ensuring the parameter inversion process operates within a reasonable parameter space. The differential evolution algorithm performs a global search within the preset parameter range and generates multiple sets of candidate parameter vectors. By employing a differential evolution algorithm for a global search, candidate parameter vectors can be searched within a wider parameter range, reducing the dependence of the parameter inversion process on a single initial value and minimizing the possibility of the parameter solution getting stuck in a localized region.

[0046] In this embodiment, determining the viscoelastic intrinsic parameters of the target skin based on the matching relationship between the theoretical creep compliance and the creep compliance data includes: determining a parameter vector for local optimization from the multiple sets of candidate parameter vectors based on the matching relationship between the theoretical creep compliance and the creep compliance data; performing local optimization on the parameter vector for local optimization using a nonlinear least squares method to obtain an optimized parameter vector; and using the optimized parameter vector as the viscoelastic intrinsic parameters of the target skin.

[0047] In this embodiment, each set of candidate parameter vectors is substituted into the multi-level structural viscoelastic model to generate a corresponding theoretical creep compliance. Based on the matching relationship between each theoretical creep compliance and the creep compliance data of the target skin, a parameter vector for local optimization can be determined from multiple sets of candidate parameter vectors. The parameter vector for local optimization can be understood as the optimal parameter combination obtained in the global search stage, which serves as the basis for subsequent local optimization.

[0048] After determining the parameter vector for local optimization, a nonlinear least squares method is used to perform local optimization on the parameter vector. The nonlinear least squares method is used to further adjust the parameter values ​​near the parameter vector obtained from the global search, so that the theoretical creep compliance corresponding to the optimized parameter vector has a better matching relationship with the creep compliance data of the target skin. Thus, the global search stage can provide a more reasonable parameter basis, and the local optimization stage can further improve the accuracy of parameter solution.

[0049] In some embodiments of this application, the nonlinear least squares method can be implemented using the Levenberg-Marquardt algorithm. By using the parameter vector obtained by the differential evolution algorithm as the basis for local optimization, and then using the nonlinear least squares method for local optimization, both global search capability and local convergence capability can be taken into account, thereby improving the stability and repeatability of the viscoelastic intrinsic parameter inversion process of the target skin.

[0050] Through the aforementioned hybrid optimization process, the differential evolution algorithm is used to generate multiple sets of candidate parameter vectors within a preset parameter range and determine the basis for local optimization. The nonlinear least squares method is used to further optimize the parameter vectors used for local optimization. Finally, the optimized parameter vectors are used as the viscoelastic intrinsic parameters of the target skin. This reduces the sensitivity of the parameter inversion process to the selection of initial parameters and improves the stability of solving for the viscoelastic intrinsic parameters.

[0051] Example 4: The skin intrinsic parameter inversion method provided in this embodiment, based on Embodiment 2, further explains the composition of the multi-level structure viscoelastic model and candidate parameter vectors.

[0052] In this embodiment, the multi-level viscoelastic model is a two-level self-similar multi-level viscoelastic model. This model characterizes the skin's creep response through a first-level compliance and a second-level compliance. The first-level compliance corresponds to the mechanical response of the cytoskeleton and microfilament network, while the second-level compliance corresponds to the mechanical response of the extracellular collagen fiber network. By dividing the skin's creep response into first-level and second-level compliance, a correspondence can be established between the two-level self-similar multi-level viscoelastic model and the multi-level structure within the skin, thus avoiding the problem of difficulty in characterizing the skin's multi-level heterogeneous structure when directly using a homogeneous material model.

[0053] In this embodiment, the first-order compliance is used to characterize the mechanical response associated with the cytoskeleton and microfilament network. The cytoskeleton and microfilament network are structural components in skin tissue related to rapid mechanical responses, influencing both the initial and short-term responses of the skin after stress. By setting the first-order compliance, a compliance response related to this type of rapid-response structure can be introduced into the multi-level viscoelastic model, allowing the generation process of the theoretical creep compliance to reflect the influence of the skin's internal structure on the mechanical response.

[0054] In this embodiment, the second-order compliance is used to characterize the mechanical response associated with the extracellular collagen fiber network. The extracellular collagen fiber network is a structural component of skin tissue related to overall elastic support and slower mechanical response, and it influences the skin's sustained deformation process after being subjected to stress. By setting the second-order compliance, the mechanical response related to the extracellular structure can be further described based on the first-order compliance, enabling a two-level self-similar multi-level viscoelastic model to characterize the creep behavior of the target skin from different structural levels.

[0055] In this embodiment, the candidate parameter vector includes a first elastic modulus, a second elastic modulus, and a characteristic relaxation time of the skin's viscoelastic response. The first elastic modulus is related to the skin cytoskeleton and fast-response network, the second elastic modulus is related to the skin's extracellular matrix, and the characteristic relaxation time of the skin's viscoelastic response is used to characterize the changes in the skin's viscoelastic response over time. The parameters in the candidate parameter vector collectively participate in the generation of the theoretical creep compliance and serve as a parameter combination that needs to be evaluated and optimized during parameter inversion.

[0056] During the parameter inversion process, different candidate parameter vectors correspond to different values ​​of the first elastic modulus, the second elastic modulus, and the characteristic relaxation time of the skin's viscoelastic response. Substituting these different candidate parameter vectors into a two-level self-similar multi-level viscoelastic model yields different theoretical creep compliances. By evaluating the matching relationship between the theoretical creep compliance and the creep compliance data of the target skin, a parameter combination that better characterizes the actual mechanical response of the target skin can be determined. Therefore, the candidate parameter vectors are not only input parameters in the generation of theoretical creep compliance but also objects to be determined in the inversion process of the target skin's viscoelastic intrinsic parameters.

[0057] Through the above settings, this embodiment utilizes the first-level and second-level compliance in the two-level self-similar multi-level viscoelastic model to correspond to the mechanical responses related to different structures inside the skin, and uses candidate parameter vectors to carry the characteristic relaxation time of the first elastic modulus, the second elastic modulus, and the skin viscoelastic response, so that the generation process of theoretical creep compliance has a clearer correspondence with the skin histological structure, thereby providing a model basis for obtaining the viscoelastic intrinsic parameters of the target skin.

[0058] Example 5: The skin intrinsic parameter inversion method provided in this embodiment, based on embodiment 4, further explains the calculation process of obtaining the theoretical creep compliance by substituting the candidate parameter vector into the multi-level structure viscoelastic model.

[0059] In this embodiment, each set of candidate parameter vectors is substituted into the multi-level structure viscoelastic model to obtain the theoretical creep compliance corresponding to each set of candidate parameter vectors, including: calculating the first-level compliance based on the first elastic modulus in the candidate parameter vectors and the characteristic relaxation time of the skin viscoelastic response; calculating the second-level compliance based on the first-level compliance and the second elastic modulus in the candidate parameter vectors; and using the second-level compliance as the theoretical creep compliance.

[0060] In this embodiment, the first-order compliance is used to characterize the first-order response quantity in a two-level self-similar multi-level viscoelastic model. The first-order compliance is determined by the first elastic modulus in the candidate parameter vector, the characteristic relaxation time of the skin's viscoelastic response, and the creep response time. The expression for the first-order compliance is:

[0061] In the formula, Indicates the first level of flexibility. Indicates the first elastic modulus. The characteristic relaxation time represents the skin's viscoelastic response. This represents the creep response time. Using the above expression, the first-order compliance at the corresponding creep response time can be obtained based on the first elastic modulus in the candidate parameter vector and the characteristic relaxation time of the skin's viscoelastic response.

[0062] After obtaining the first-level compliance, the second-level compliance is calculated based on the first-level compliance and the second elastic modulus in the candidate parameter vector. The expression for the second-level compliance is:

[0063] In this expression, Indicates the second level of flexibility. This represents the second elastic modulus. This represents the first-order compliance. The second-order compliance is calculated based on the aforementioned first-order compliance and in conjunction with the second elastic modulus in the candidate parameter vector, thereby enabling further characterization of the mechanical response related to the extracellular collagen fiber network based on the first-order response.

[0064] In this embodiment, the second-level compliance is used as the theoretical creep compliance. The expression for the theoretical creep compliance is:

[0065] in, This represents the theoretical creep compliance. This represents the second-order compliance. In other words, in the two-level self-similar multi-level structural viscoelastic model provided in this embodiment, the first-order compliance is an intermediate response quantity, and the second-order compliance is a further response quantity obtained based on the first-order compliance, and serves as the theoretical creep compliance generated by the multi-level structural viscoelastic model based on the candidate parameter vector.

[0066] In the actual parameter inversion process, for each set of candidate parameter vectors, the corresponding theoretical creep compliance can be calculated according to the above expression based on the corresponding first elastic modulus, second elastic modulus, and characteristic relaxation time of the skin's viscoelastic response. Different candidate parameter vectors generate different theoretical creep compliance, which can be used to evaluate the matching relationship with the creep compliance data of the target skin, thereby providing a basis for determining the viscoelastic intrinsic parameters of the target skin.

[0067] Through the above calculation process, this embodiment introduces the first elastic modulus, the second elastic modulus, and the characteristic relaxation time of the skin's viscoelastic response from the candidate parameter vector into a two-level self-similar multi-level viscoelastic model. The first-level compliance and the second-level compliance are calculated sequentially, with the second-level compliance output as the theoretical creep compliance. Therefore, the generation process of the theoretical creep compliance has a clear parameter source and hierarchical calculation relationship, which helps improve the interpretability of the parameter inversion process and provides support for subsequently determining the viscoelastic intrinsic parameters of the target skin based on matching relationships.

[0068] Example 6: The skin intrinsic parameter inversion method provided in this embodiment, based on embodiment 4, further explains the output content of viscoelastic intrinsic parameters.

[0069] In this embodiment, the viscoelastic intrinsic parameters include a first elastic modulus, a second elastic modulus, the characteristic relaxation time of the skin's viscoelastic response, and the total elastic modulus. The first elastic modulus, the second elastic modulus, and the characteristic relaxation time of the skin's viscoelastic response can be obtained through a parameter inversion process, while the total elastic modulus can be calculated based on the first and second elastic moduli. By outputting these viscoelastic intrinsic parameters, the skin intrinsic parameter inversion results can be transformed from single empirical indicators into a combination of parameters with structural correspondences.

[0070] In this embodiment, the first elastic modulus is used to characterize the elastic characteristics related to the skin cytoskeleton and rapid response network, the second elastic modulus is used to characterize the elastic characteristics related to the skin extracellular matrix, and the characteristic relaxation time of the skin viscoelastic response is used to characterize the characteristics of the target skin viscoelastic response changing over time. Since the first elastic modulus, the second elastic modulus, and the characteristic relaxation time of the skin viscoelastic response all participate in the generation process of theoretical creep compliance, the above parameters can reflect the mechanical response characteristics of the target skin under a multi-level structure viscoelastic model.

[0071] In this embodiment, the total elastic modulus satisfies:

[0072] in, Represents the total elastic modulus. Indicates the first elastic modulus. This represents the second elastic modulus. The total elastic modulus is obtained by adding the first and second elastic moduli and is used to characterize the overall elastic response level of the target skin. By setting the total elastic modulus, it is possible to obtain a quantitative result of the overall elastic characteristics of the target skin based on the elastic parameters related to different structural levels.

[0073] In this embodiment, the skin intrinsic parameter inversion results may include a first elastic modulus, a second elastic modulus, the characteristic relaxation time of the skin's viscoelastic response, and the total elastic modulus. As one implementation, the skin intrinsic parameter inversion results can be output in the form of parameter combinations, tables, curves, or graphs to facilitate comparison of the skin's mechanical state at different locations of the same test subject or between different test subjects. It should be noted that the output format can be set according to actual analysis needs, and this application does not limit it in this regard.

[0074] With the above settings, this embodiment, based on obtaining the first elastic modulus, the second elastic modulus, and the characteristic relaxation time of the skin's viscoelastic response, further calculates the total elastic modulus, so that the skin intrinsic parameter inversion results can simultaneously reflect the elastic characteristics, time response characteristics, and overall elasticity level related to different structural levels of the skin, thereby providing parameter basis for the quantitative analysis of the target skin's mechanical properties.

[0075] Example 7: The skin intrinsic parameter inversion method provided in this embodiment, based on Embodiment 1, further explains the preprocessing of creep compliance data before parameter inversion.

[0076] In this embodiment, before performing parameter inversion based on the creep compliance data using a multi-level structural viscoelastic model, the method further includes: preprocessing the creep compliance data to obtain preprocessed creep compliance data; the preprocessing includes smoothing the creep compliance data and uniformly resampling it on a logarithmic time coordinate; the smoothing is cubic spline interpolation smoothing; the parameter inversion is performed based on the preprocessed creep compliance data.

[0077] In this embodiment, creep compliance data can be measured compliance response data of the target skin over time after being subjected to force. Since creep compliance data may be affected by the testing environment, local fluctuations, or uneven data sampling distribution during acquisition, directly using the raw creep compliance data for parameter inversion may affect the determination of the matching relationship between theoretical creep compliance and the actual creep compliance data. Preprocessing the creep compliance data can improve data continuity and the balance of its time-scale distribution, providing a more stable data foundation for subsequent parameter inversion.

[0078] In this embodiment, the smoothing process is cubic spline interpolation smoothing. Cubic spline interpolation smoothing can construct a continuous and smooth data curve based on the changing trend of the creep compliance data, reducing the impact of local fluctuations on the parameter inversion process while preserving the main changing characteristics of the target skin's creep response. Therefore, the preprocessed creep compliance data is more suitable for subsequent evaluation of its matching relationship with the theoretical creep compliance.

[0079] After obtaining the smoothed creep compliance data, this embodiment also performs uniform resampling on the logarithmic time coordinate. Skin creep response typically contains both short-time and long-time response information. By performing uniform resampling on the logarithmic time coordinate, the data from the short-time and long-time intervals can be more evenly represented in the subsequent parameter inversion process, avoiding the parameter inversion process being overly affected by the data distribution of a certain time interval.

[0080] In some embodiments of this application, uniform resampling can be performed on the logarithmic time axis according to a preset interval and a preset number of sampling points. As one implementation, 200 points can be uniformly sampled from log(0.1) to log(10) on the log(t) axis to obtain preprocessed creep compliance data. It should be noted that the resampling interval and the number of resampling points can be set according to the test conditions of the target skin, the sampling density of the original creep compliance data, and the parameter inversion accuracy requirements, and this application does not limit them.

[0081] Example 8: This embodiment provides a specific testing and verification process for a method to invert intrinsic skin parameters. This embodiment is used to fully explain the method for inverting intrinsic skin parameters described in the foregoing embodiments, and to verify the repeatability of the obtained intrinsic skin viscoelastic parameters and the ability to distinguish between different skin locations. Figures 2 to 4 Table 1 is used to illustrate the test data, model calculation results, and parameter comparison results in this embodiment.

[0082] In this embodiment, a negative pressure suction test was performed on the cheek skin of a 25-year-old male subject to obtain the skin's creep flexibility data. The obtained raw skin creep flexibility sequence is as follows: Figure 2As shown. Figure 2 In the diagram, the horizontal axis represents the creep response time in seconds (s); the vertical axis represents the creep compliance in Pa. -1 .Depend on Figure 2 It can be seen that, within the test time range, the creep compliance of the target skin gradually increases with the increase of creep response time, and shows a trend of gradually decreasing growth rate. The original skin creep compliance data is used to characterize the compliance response process of the target skin over time under test conditions, and serves as the data basis for subsequent preprocessing and parameter inversion.

[0083] In this embodiment, the creep compliance data is preprocessed before parameter inversion based on the creep compliance data. Specifically, the creep compliance data of the target skin is smoothed by cubic spline interpolation and uniformly resampled on the logarithmic time axis to obtain the preprocessed creep compliance data. As one implementation, 200 points can be uniformly sampled from log(0.1) to log(10) on the log(t) axis. Through the above preprocessing, the creep compliance data can be logarithmically uniformly distributed on the time axis, thereby balancing the contributions of short-time response data and long-time response data in the subsequent parameter inversion process and reducing the adverse effects of local fluctuations or long-tailed data on the parameter inversion results.

[0084] After obtaining the preprocessed creep compliance data, parameter inversion is performed based on the preprocessed creep compliance data using a multi-level structural viscoelastic model. In this embodiment, the multi-level structural viscoelastic model is a two-level self-similar multi-level structural viscoelastic model, which includes a first-level compliance and a second-level compliance. The first-level compliance corresponds to the mechanical response of the cytoskeleton and microfilament network, and the second-level compliance corresponds to the mechanical response of the extracellular collagen fiber network.

[0085] In this embodiment, multiple candidate parameter vectors are generated within a preset parameter range. The candidate parameter vectors include a first elastic modulus, a second elastic modulus, and the characteristic relaxation time of the skin's viscoelastic response. As one implementation, the preset parameter range for the first and second elastic moduli can be from 1 kPa to 100 kPa, and the preset parameter range for the characteristic relaxation time of the skin's viscoelastic response can be from 0.01 s to 50 s. Different candidate parameter vectors correspond to different values ​​for the first elastic modulus, the second elastic modulus, and the characteristic relaxation time of the skin's viscoelastic response.

[0086] In this embodiment, each set of candidate parameter vectors is substituted into a two-level self-similar multi-level viscoelastic model to obtain the theoretical creep compliance corresponding to each set of candidate parameter vectors. Specifically, the first-level compliance is calculated based on the first elastic modulus in the candidate parameter vectors and the characteristic relaxation time of the skin's viscoelastic response; the second-level compliance is calculated based on the first-level compliance and the second elastic modulus in the candidate parameter vectors; and the second-level compliance is used as the theoretical creep compliance.

[0087] In this embodiment, the first-level compliance expression is:

[0088] The expression for the second-order flexibility is:

[0089] The theoretical creep compliance expression is as follows:

[0090] in, This represents the theoretical creep compliance. Indicates the first level of flexibility. Indicates the second level of flexibility. Indicates the first elastic modulus. This represents the second elastic modulus. The characteristic relaxation time represents the skin's viscoelastic response. This indicates the creep response time.

[0091] In this embodiment, parameter inversion is achieved based on the matching relationship between theoretical creep compliance and preprocessed creep compliance data. As one implementation method, a differential evolution algorithm is used to perform a global search within a preset parameter range, generating multiple sets of candidate parameter vectors. Based on the matching relationship between the theoretical creep compliance and the preprocessed creep compliance data, parameter vectors for local optimization are determined from the multiple sets of candidate parameter vectors. Nonlinear least squares method is used to locally optimize the parameter vectors used for local optimization, obtaining optimized parameter vectors. The optimized parameter vectors are then used as the viscoelastic intrinsic parameters of the target skin.

[0092] In this embodiment, the fitting result of the multi-level structure viscoelastic model is as follows: Figure 3 As shown. Figure 3 In the diagram, the horizontal axis represents the creep response time in seconds (s); the vertical axis represents the creep compliance in Pa. -1 The fitted curve in the figure is the model curve corresponding to the theoretical creep compliance, and the original data is the creep compliance data obtained from target skin testing. Figure 3 It can be seen that the fitted curve has a good correspondence with the original data, and the goodness of fit R is [value missing]. 2The mean square error (MSE) is 0.99, and the mean square error (MSE) is 1.2 × 10⁻⁶. -12 This demonstrates that parameter inversion based on the matching relationship between theoretical creep compliance and creep compliance data can obtain viscoelastic intrinsic parameters that match the actual creep response of the target skin.

[0093] After obtaining the first elastic modulus, the second elastic modulus, and the characteristic relaxation time of the skin's viscoelastic response, the total elastic modulus is further calculated. The total elastic modulus satisfies:

[0094] in, Represents the total elastic modulus. Indicates the first elastic modulus. This represents the second elastic modulus.

[0095] Therefore, the inversion results of the intrinsic parameters of the skin include the first elastic modulus, the second elastic modulus, the characteristic relaxation time of the skin's viscoelastic response, and the total elastic modulus.

[0096] To verify the repeatability of the method in this application, in this embodiment, the same test site (cheek area) of the same test subject was tested three times repeatedly. The test results are shown in Table 1. In Table 1, Test-1, Test-2, and Test-3 represent the first, second, and third repeated tests performed on the same test site of the same test subject, respectively. CV represents the coefficient of variation, used to characterize the dispersion of the results of the three repeated tests. Table 1. Results of three tests on the same test site of the same subject.

[0097] As shown in Table 1, the coefficient of variation of each parameter in the three tests did not exceed 15%, indicating that the skin intrinsic parameter inversion method of this application can achieve good repeatability and stability.

[0098] To further verify the ability of the method in this application to characterize the differences in skin mechanics at different locations, this embodiment also tested the skin on three locations—the cheek, arm, and fingertips—of the same subject. The comparison results of the intrinsic viscoelastic parameters of the skin at different locations are as follows: Figure 4 As shown, where, Figure 4 (a) in the figure is a comparison of characteristic relaxation times of the skin's viscoelastic response. Figure 4 (b) in the figure is a comparison chart of the first elastic modulus. Figure 4 (c) in the figure is a comparison chart of the second elastic modulus. Figure 4 (d) in the figure is a comparison chart of total elastic modulus.

[0099] Depend on Figure 4It can be seen that the characteristic relaxation time of the skin viscoelastic response is basically the same in different parts of the body. The skin of the fingertips has higher values ​​for the first elastic modulus, the second elastic modulus, and the total elastic modulus than the skin of the arm and cheek, while the elastic moduli of the cheek skin are relatively lower. This indicates that the intrinsic viscoelastic parameters of the skin obtained by the method of this application can effectively distinguish the mechanical differences of the skin in different parts of the body.

[0100] In summary, this embodiment obtains the intrinsic viscoelastic parameters of the target skin by performing negative pressure suction tests on the skin of the cheek area of ​​the test subject, combined with creep compliance data preprocessing, candidate parameter vector generation, theoretical creep compliance calculation, matching relationship evaluation, and parameter optimization process. The method of this application has good repeatability, stability, and discrimination ability through repeated tests on the same site and comparative tests on different sites.

[0101] Example 9: like Figure 5 As shown, this embodiment provides a skin intrinsic parameter inversion system. The skin intrinsic parameter inversion system includes an acquisition module, a parameter inversion module, and an output module. The acquisition module is used to acquire creep compliance data of the target skin; the parameter inversion module is used to perform parameter inversion based on the creep compliance data using a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin; the output module is used to output the skin intrinsic parameter inversion results based on the viscoelastic intrinsic parameters.

[0102] In this embodiment, the acquisition module is used to acquire creep compliance data of the target skin. The target skin can be the skin of the test subject's cheek, arm, fingertips, etc. The creep compliance data can be derived from compliance response data obtained during in vivo skin biomechanical testing. The creep compliance data output by the acquisition module serves as the input data for the parameter inversion module. By setting the acquisition module, the compliance response process of the target skin under external load over time can be transformed into a data basis that can be processed for subsequent parameter inversion.

[0103] In this embodiment, the parameter inversion module is used to perform parameter inversion based on creep compliance data using a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin. The multi-level structural viscoelastic model is constructed based on skin histological structure and is used to generate theoretical creep compliance from candidate parameter vectors. The parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data. Because the parameter inversion module uses a multi-level structural viscoelastic model constructed based on skin histological structure, it can establish a correspondence between the generation process of theoretical creep compliance and the internal structural features of the skin, and helps to ensure that the inverted viscoelastic intrinsic parameters have a clear structural orientation.

[0104] In this embodiment, the parameter inversion module can generate multiple sets of candidate parameter vectors within a preset parameter range, and substitute each set of candidate parameter vectors into a multi-level structural viscoelastic model to obtain the theoretical creep compliance corresponding to each set of candidate parameter vectors. The parameter inversion module can also determine the viscoelastic intrinsic parameters of the target skin based on the matching relationship between the theoretical creep compliance and the creep compliance data. Through the above settings, the parameter inversion module can realize the correspondence processing between candidate parameter vectors, theoretical creep compliance, and target skin creep compliance data, thereby completing the determination of the viscoelastic intrinsic parameters of the target skin.

[0105] In some embodiments of this application, the parameter inversion module can be further used to execute a hybrid optimization strategy. As one implementation, the parameter inversion module employs a differential evolution algorithm to perform a global search within a preset parameter range, generating multiple sets of candidate parameter vectors; based on the matching relationship between theoretical creep compliance and creep compliance data, it determines the parameter vectors for local optimization from the multiple sets of candidate parameter vectors; it then uses a nonlinear least squares method to locally optimize the parameter vectors used for local optimization, obtaining the optimized parameter vectors; finally, it uses the optimized parameter vectors as the viscoelastic intrinsic parameters of the target skin. Thus, the parameter inversion module can balance global search capability and local optimization capability, which is beneficial for improving the stability of the parameter inversion process.

[0106] In some embodiments of this application, the parameter inversion module may further include a preprocessing unit, a candidate parameter generation unit, a theoretical creep compliance calculation unit, a matching relationship evaluation unit, and a parameter output unit. The preprocessing unit preprocesses the creep compliance data to obtain preprocessed creep compliance data. The candidate parameter generation unit generates multiple sets of candidate parameter vectors within a preset parameter range. The theoretical creep compliance calculation unit substitutes each set of candidate parameter vectors into a multi-level structural viscoelastic model to obtain the corresponding theoretical creep compliance. The matching relationship evaluation unit determines the parameter inversion result based on the matching relationship between the theoretical creep compliance and the creep compliance data. The parameter output unit outputs the viscoelastic intrinsic parameters of the target skin. It should be noted that the above unit division is only one implementation of the parameter inversion module. Provided that the parameter inversion function can be achieved, the internal unit division of the parameter inversion module can be adjusted according to actual needs.

[0107] In this embodiment, the output module is used to output the skin intrinsic parameter inversion results based on the viscoelastic intrinsic parameters. The skin intrinsic parameter inversion results may include a first elastic modulus, a second elastic modulus, the characteristic relaxation time of the skin's viscoelastic response, and the total elastic modulus. As one implementation, the output module can output the skin intrinsic parameter inversion results in numerical, tabular, graphical, or graphical form to facilitate the analysis of the mechanical properties of the target skin.

[0108] Through the coordinated operation of the acquisition module, parameter inversion module, and output module described above, the skin intrinsic parameter inversion system provided in this embodiment can acquire target skin creep compliance data, perform parameter inversion based on a multi-level structure viscoelastic model, and output the skin intrinsic parameter inversion results. Therefore, this system can achieve the technical effects corresponding to the aforementioned skin intrinsic parameter inversion methods and is beneficial for stably obtaining viscoelastic intrinsic parameters related to skin structure.

[0109] Example 10: This application also provides a computer device in its specific embodiments. Specifically, the computer device includes a processor and a memory. The memory is used to store a computer program, and the computer program includes program instructions. The processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve corresponding method flows or corresponding functions. The processor described in this embodiment can be used to acquire creep compliance data of the target skin; based on the creep compliance data, parameter inversion is performed through a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin; the multi-level structural viscoelastic model is constructed based on the skin histological structure and used to generate theoretical creep compliance based on candidate parameter vectors; the parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data; based on the viscoelastic intrinsic parameters, the skin intrinsic parameter inversion result is output.

[0110] Example 11: This application also provides a storage medium in its specific embodiments, specifically a computer-readable storage medium, which is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor; these instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the methods in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor to perform the following steps: acquiring creep compliance data of the target skin; based on the creep compliance data, performing parameter inversion through a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin; the multi-level structural viscoelastic model is constructed based on the skin histological structure and is used to generate theoretical creep compliance according to candidate parameter vectors; the parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data; based on the viscoelastic intrinsic parameters, the skin intrinsic parameter inversion result is output.

[0111] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0113] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0114] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0115] The foregoing has shown and described the basic principles, main features, and advantages of this application. It will be apparent to those skilled in the art that this application is not limited to the details of the exemplary embodiments described above, and that this application can be implemented in other specific forms without departing from the spirit or basic characteristics of this application. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of this application is not limited by the foregoing description. Thus, all changes falling within the meaning and scope of equivalents are intended to be included within this application. No reference numerals should be considered limiting.

[0116] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of this application and should not be used to limit the scope of protection of this application. Any modifications made to the technical solutions based on the technical concept proposed in this application fall within the scope of protection of this application.

Claims

1. A method for inverting intrinsic skin parameters, characterized in that, include: Obtain creep flexibility data of the target skin; Based on the creep compliance data, the viscoelastic intrinsic parameters of the target skin are obtained by parameter inversion through a multi-level structural viscoelastic model. The multi-level structure viscoelastic model is constructed based on skin histological structure and is used to generate theoretical creep compliance based on candidate parameter vectors; the parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data. Based on the viscoelastic intrinsic parameters, the skin intrinsic parameters inversion results are output.

2. The method for inverting intrinsic skin parameters according to claim 1, characterized in that, Based on the creep compliance data, parameter inversion is performed using a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin, including: Generate multiple sets of candidate parameter vectors within a preset parameter range; Substitute each set of candidate parameter vectors into the multi-level structure viscoelastic model to obtain the theoretical creep compliance corresponding to each set of candidate parameter vectors. Based on the matching relationship between the theoretical creep compliance and the creep compliance data, the viscoelastic intrinsic parameters of the target skin are determined.

3. The method for inverting intrinsic skin parameters according to claim 2, characterized in that, The process involves generating multiple candidate parameter vectors within a preset parameter range, and then performing a global search within that preset parameter range using a differential evolution algorithm. The determination of the viscoelastic intrinsic parameters of the target skin based on the matching relationship between the theoretical creep compliance and the creep compliance data includes: Based on the matching relationship between the theoretical creep compliance and the creep compliance data, a parameter vector for local optimization is determined from the multiple sets of candidate parameter vectors. The parameter vector used for local optimization is locally optimized using the nonlinear least squares method to obtain the optimized parameter vector; The optimized parameter vector is used as the viscoelastic intrinsic parameters of the target skin.

4. The method for inverting intrinsic skin parameters according to claim 2, characterized in that, The multi-level structure viscoelastic model is a two-level self-similar multi-level structure viscoelastic model. The two-level self-similar multi-level structure viscoelastic model characterizes the skin creep response through the first-level compliance and the second-level compliance. The first level of flexibility corresponds to the mechanical response of the cytoskeleton and microfilament network, while the second level of flexibility corresponds to the mechanical response of the extracellular collagen fiber network. The candidate parameter vector includes a first elastic modulus, a second elastic modulus, and a characteristic relaxation time of the skin's viscoelastic response. The first elastic modulus is related to the skin cytoskeleton and rapid response network, and the second elastic modulus is related to the skin's extracellular matrix.

5. The method for inverting intrinsic skin parameters according to claim 4, characterized in that, The step of substituting each set of candidate parameter vectors into the multi-level structure viscoelastic model to obtain the theoretical creep compliance corresponding to each set of candidate parameter vectors includes: The first-order compliance is calculated based on the first elastic modulus in the candidate parameter vector and the characteristic relaxation time of the skin's viscoelastic response. The second-level compliance is calculated based on the first-level compliance and the second elastic modulus in the candidate parameter vector. The second-level compliance is taken as the theoretical creep compliance. The expression for the first-level flexibility is: The expression for the second-order flexibility is: The theoretical creep compliance expression is as follows: in, This represents the theoretical creep compliance. Indicates the first level of flexibility. Indicates the second level of flexibility. Indicates the first elastic modulus. This represents the second elastic modulus. The characteristic relaxation time represents the skin's viscoelastic response. This indicates the creep response time.

6. The method for inverting intrinsic skin parameters according to claim 4, characterized in that, The intrinsic viscoelastic parameters include a first elastic modulus, a second elastic modulus, the characteristic relaxation time of the skin's viscoelastic response, and a total elastic modulus, wherein the total elastic modulus satisfies: in, This represents the total elastic modulus. Indicates the first elastic modulus. This represents the second elastic modulus.

7. The method for inverting intrinsic skin parameters according to claim 1, characterized in that, Before performing parameter inversion using a multi-level structural viscoelastic model based on the creep compliance data, the following steps are also included: The creep compliance data is preprocessed to obtain preprocessed creep compliance data; the preprocessing includes smoothing the creep compliance data and uniform resampling on the logarithmic time coordinate; the smoothing is cubic spline interpolation smoothing; the parameter inversion is based on the preprocessed creep compliance data.

8. A skin intrinsic parameter inversion system, characterized in that, include: The acquisition module is used to acquire creep flexibility data of the target skin. The parameter inversion module is used to perform parameter inversion based on the creep compliance data through a multi-level structural viscoelastic model to obtain the viscoelastic intrinsic parameters of the target skin. The multi-level structure viscoelastic model is constructed based on skin histological structure and is used to generate theoretical creep compliance based on candidate parameter vectors; the parameter inversion is achieved based on the matching relationship between the theoretical creep compliance and the creep compliance data. The output module is used to output the skin intrinsic parameter inversion results based on the viscoelastic intrinsic parameters.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the skin intrinsic parameter inversion method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the skin intrinsic parameter inversion method as described in any one of claims 1 to 7.

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