A method of measuring in-vivo elastic fabric deformation and pressure distribution characteristics

Abstract

The application discloses a kind of measurement methods for measuring elastic fabric deformation and pressure distribution characteristics in vivo, it is related to elastic fabric in vivo pressure measurement technical field, comprising the following steps: step S1, build three-dimensional image correlation method measurement system, and respectively obtain the image of elastic fabric without pressure state and in vivo wearing state image;Step S2, calculate the global deformation of elastic fabric, and construct the three-dimensional geometry of human body surface to obtain global curvature;Step S3, the global pressure measurement of elastic fabric is carried out.The application adopts the above-mentioned measurement method for measuring elastic fabric deformation and pressure distribution characteristics in vivo, realizes the global accurate pressure measurement when human body part wears elastic fabric, significantly improves the efficiency of measurement and the spatial resolution of measurement result, provides reliable data support and decision optimization direction for the development scheme of medical health elastic fabric.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of body pressure measurement, and in particular to a method for measuring the deformation and pressure distribution characteristics of elastic fabric. BACKGROUND

[0002] With the development of economic level and the improvement of national health consciousness, medical health elastic fabric is playing an increasingly important role in people's life. Effective measurement of the medical health effect of elastic fabric is of great significance to the protection of national health. On the one hand, medical elastic fabric is the most widely used treatment and prevention means for lower limb venous disease, and on the other hand, it has excellent effect on cosmetic body shaping and improving the sports performance of athletes. The decisive factor affecting the medical health effect of elastic fabric is the size of the pressure value applied at a specific position and the distribution of the pressure gradient, and due to the differences in region, living habits, race, etc., there are great individual differences in the shape of the body part in the population. The main reason for the lack of compliance of existing elastic fabric users is the inaccuracy of pressure measurement. Excessive pressure leads to insufficient comfort of the user, uneven skin pressure along the cross section of the body part, such as excessive or peak local pressure, has caused side effects, and too low pressure of the body part leads to weak medical health effect. This puts forward an urgent need for fine pressure measurement of elastic fabric.

[0003] The pressure measurement of elastic fabric is complex, the diversity of local shape of human body part, the difficulty of accurate measurement of geometric parameters of human body surface and the lack of spatial resolution of pressure measurement result make accurate global pressure measurement a great challenge. The existing technology has the following problems:

[0004] 1) There are great individual differences in the shape of the body part, and the protrusions of the skeleton and the irregularities of the muscles make the pressure distribution of the elastic fabric extremely complex.

[0005] 2) It is difficult to obtain the geometric parameters of the surface of the body part, such as circumference and curvature, and existing means such as 3D scanning instrument is expensive and requires high technical level of personnel.

[0006] 3) The deformation of elastic fabric after wearing has a decisive influence on the final applied pressure, and existing means considers that the deformation distribution on the cross section of the body part is uniform, and there is a lack of effective deformation measurement means.

[0007] 4) The selection of fitting range of curvature data of human body part mostly relies on manual selection of range, and there is a lack of effective error measurement and automatic calculation process.

[0008] 5) The spatial resolution of existing elastic fabric pressure measurement method is insufficient, and most of them only involve scattered data of limited points, and cannot obtain global pressure measurement result.

[0009] As a new visual-based measurement method, three-dimensional image correlation method has the advantages of less interference to the measurement target, the ability to measure the deformation information of the elastic body, high spatial resolution, and is an ideal tool for measuring the deformation of elastic fabric.

[0010] In summary, due to the high individual difference of human body part morphology, the insufficient spatial resolution and accuracy of human body surface geometric parameter acquisition, and the difficulty of elastic fabric deformation measurement, there are still great challenges in the in-vivo global pressure measurement method of elastic fabric used in medical care. At present, the pressure measurement method for elastic fabric has not met the existing measurement requirements, and cannot effectively improve the compliance of the user and effectively guarantee the expected effect of the elastic fabric. SUMMARY

[0011] The purpose of the present application is to provide a measurement method for measuring the deformation and pressure distribution characteristics of elastic fabric in vivo, to solve the problems raised in the above background art, to efficiently, comprehensively and accurately acquire human body surface geometric data, collect elastic fabric deformation data and measure global pressure, to provide accurate and reliable results for users and medical care practitioners, and to provide solid data support and decision guidance for optimizing and customizing personalized pressure application solutions.

[0012] To achieve the above purpose, the present application provides a measurement method for measuring the deformation and pressure distribution characteristics of elastic fabric in vivo, comprising the following steps:

[0013] Step S1, a three-dimensional image correlation method measurement system is built, and images of the elastic fabric in a pressure-free state and in a body-worn state are acquired respectively;

[0014] Step S2, global deformation of the elastic fabric is calculated, and a three-dimensional geometric morphology of the human body surface is constructed to obtain the global curvature;

[0015] Step S3, global pressure measurement of the elastic fabric is performed.

[0016] Preferably, the specific steps of step S1 are as follows:

[0017] Step S11, two industrial cameras with fixed focus lenses and two diffuse reflection fill light lamps are selected, the two industrial cameras are fixed on an optical platform according to a predetermined target distance, a camera distance and a solid angle, the diffuse reflection fill light lamps are turned on, and a calibration program is performed;

[0018] Step S12, a washable speckle is made on the surface of the elastic fabric by a paint spraying method, the elastic fabric is sleeved on a human body simulation cylinder to obtain an initial image of the elastic fabric in a pressure-free state;

[0019] Step S13, the elastic fabric with the water-washable speckle patch in step S12 is put on the human body part to obtain the deformation image of the elastic fabric in the wearing state.

[0020] Preferably, the specific steps of step S2 are as follows:

[0021] Step S21, the size and step length of the sub-region measured by the three-dimensional image correlation method are set in the calculation, and the global deformation value of the elastic fabric in the wearing state and the three-dimensional coordinates of the surface of the human body wearing part are obtained by calculation;

[0022] Step S22, based on the three-dimensional surface of the human body, a spherical region with a constantly iterated radius is used for three-dimensional surface fitting, the calculation results of the fitting curvature radius before and after iteration are compared, and the iteration is terminated when the result error meets the error requirement to obtain the final curvature calculation result.

[0023] Preferably, the fitting function of the three-dimensional surface fitting in step S22 is as follows:

[0024] z=f(x,y)=a0+a1x+a2y+a3x 2 +a4y 2 ;

[0025] Wherein, a0 represents the constant term coefficient, a1 represents the first term coefficient of x, a2 represents the first term coefficient of y, a3 represents the second term coefficient of x, and a4 represents the second term coefficient of y.

[0026] Preferably, step S3 uses Laplace's law to combine the mechanical parameters of the elastic fabric, the global deformation of the elastic fabric and the curvature of the human body part to measure the global pressure.

[0027] Preferably, in step S3, the calculation formula for obtaining the pressure measurement value is as follows:

[0028]

[0029] Wherein, t is the thickness of the elastic fabric, E is the elastic modulus of the elastic fabric, ε is the deformation of the surface of the elastic fabric, and R is the radius of curvature.

[0030] Therefore, the measurement method for measuring the deformation and pressure distribution characteristics of the elastic fabric in the body is adopted, the global accurate pressure measurement of the elastic fabric when worn on the human body part is realized, the efficiency of the measurement and the spatial resolution of the measurement result are significantly improved, and reliable data support and decision optimization direction are provided for the development scheme of the medical health elastic fabric.

[0031] The technical solutions of the present application are further described in detail below through the drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0032] Figure 1 Fig. 1 is a schematic diagram of a three-dimensional image correlation method measurement system for measuring the deformation and pressure distribution characteristics of an elastic fabric in accordance with the present application;

[0033] Figure 2 Fig. 2 is a schematic diagram of an image of an elastic fabric under a near zero and negligible pressure state measured using a hollow human body part elastic model in accordance with the present application;

[0034] Figure 3 Fig. 3 is a schematic diagram of a human body part geometric parameter iterative calculation model in accordance with the present application;

[0035] Reference signs: 1, computer; 2, diffuse reflection light supplement lamp; 3, industrial camera; 4, elastic fabric; 5, un-deformed elastic fabric; 6, air pump; 7, un-inflated deformable human body simulation cylinder; 8, elastic fabric under no pressure initial state; 9, inflated human body simulation cylinder. DETAILED DESCRIPTION

[0036] The technical solutions of the present application are further described below with reference to the accompanying drawings and examples.

[0037] Unless otherwise defined, technical terms or scientific terms used in the present application shall have the usual meaning understood by a person with ordinary skill in the art to which the present application pertains. The terms "first", "second", and similar terms used in the present application do not indicate any order, number, or importance, but are only used to distinguish different components. The terms "include" or "contain" and similar terms mean that the elements or objects before the terms encompass the elements or objects listed after the terms and their equivalents, and do not exclude other elements or objects. The terms "connect" or "connected" and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "up", "down", "left", "right", and the like are only used to indicate relative positional relationships, and when the absolute positions of the described objects change, the relative positional relationships can also change accordingly.

[0038] EMBODIMENT

[0039] Reference is made to Figures 1-3 The present application provides a measurement method for measuring the deformation and pressure distribution characteristics of an elastic fabric in vivo, comprising the following steps:

[0040] Step S1, build a three-dimensional image correlation method measurement system, and obtain the image of the elastic fabric 4 in the state of no pressure and the image in the state of wearing. The three-dimensional image correlation method measurement system can capture the three-dimensional geometric information of the surface of the elastic fabric 4 through two industrial cameras 3 in the principle of binocular vision, so as to calculate the high-precision human body part geometric parameters such as the curvature radius and the deformation information of the elastic fabric 4 in the wearing state. The steps are as follows:

[0041] Step S11, select two industrial cameras 3 with fixed focus lenses and two diffuse reflection fill light lamps 2, fix the two industrial cameras 3 on the optical platform according to the predetermined target distance, camera distance and solid angle, turn on the diffuse reflection fill light lamp 2, and perform the calibration procedure. According to the predetermined target distance, camera distance and solid angle, fix the two industrial cameras 3 on the optical platform, turn on the diffuse reflection fill light lamp 2, and arrange the diagram as shown in Figure 1 The specific steps are as follows:

[0042] Fix the two industrial cameras 3 on the tripod with horizontal and vertical calibrators. In order to obtain accurate results, the lens fixing system needs to have enough degrees of freedom to accurately adjust the position and attitude of the camera / lens. After determining the final position, target distance, camera distance and attitude that meet the target solid angle, lock all adjustable parts on the lens fixing system, such as the focusing ring, aperture adjustment ring and zoom knob.

[0043] Turn on the diffuse reflection fill light lamp 2, and observe whether the contrast of the collected image meets the requirements. There should be no overexposure and underexposure in the target area, and there should be no glare. The zero-mean normalized error sum of squares correlation function is used to determine the appropriate contrast parameters.

[0044] Connect the industrial camera 3 to the computer 1 equipped with calculation software, set the image acquisition frame rate and camera synchronization settings, and perform the calibration procedure. Turn on the camera and set it to the target frame rate, and heat it to a stable working temperature. The time required for the camera to preheat to a stable temperature depends on the camera, laboratory environment and image acquisition frame rate, and the preheating time usually varies from a few minutes to a few hours. Before using a new camera, the camera temperature during preheating should be monitored at the expected (or similar) laboratory environment at the required image acquisition rate, and the time required for temperature stabilization should be recorded.

[0045] After the above device and program are set up, open the synchronization setting in the computer 1 installed with the three-dimensional image correlation method calculation software, and ensure that the synchronization setting of the two industrial cameras 3 is correct. Then, perform the calibration program, select the calibration plate corresponding to the field of view range, and perform the static, rotation, tilt, and translation operations as needed to complete the requirements of the calibration program. Note that the spacing between the feature points of the calibration plate here should be accurate to within 0.1 pixel points, and sufficient high-quality calibration images should be collected here and input into the calculation software to complete the calibration calculation. After calibration, perform parameter checking to ensure the correctness of the calibration results, and the main calibration results to be checked should include the lens focal length and image center in the intrinsic parameters, and the angle and distance between the two cameras in the extrinsic parameters.

[0046] Step S12, a suitable size of washable speckle patch is made on the surface of the elastic fabric 4 by a paint spraying method, and the elastic fabric 4 is sleeved on the inflatable human body simulation cylinder to obtain the initial image of the elastic fabric 4 in the pressure-free state. The operation process is as shown in Figure 2 , and the specific steps are as follows:

[0047] A suitable size of washable speckle patch is made on the surface of the elastic fabric 4 by a paint spraying method. First, in order to attach the speckle required by the three-dimensional image correlation method on the surface of the elastic fabric 4, a washable speckle patch with good adhesion is sprayed. The predetermined speckle size occupies 3-5 pixels in the image, and in order to ensure the accuracy of the calculation results, the speckle is randomly optimized designed to ensure the uniqueness of the speckle features in different areas and firmly paste on the surface of the elastic fabric 4. After the speckle is made, the undeformed elastic fabric 5 is sleeved in the deformable human body simulation cylinder 7, and the human body simulation cylinder is slowly inflated by the inflation pump 6 to make the human body simulation cylinder expand to form the inflated human body simulation cylinder 9, which can just support the elastic fabric 4. The elastic fabric 4 is in the initial state of no pressure, which is considered as the initial state of the elastic fabric 4 without tension (i.e. zero pressure or pressure can be ignored). Open the three-dimensional image correlation method calculation software, take and save the image of the elastic fabric 4 at this time as the initial contrast image.

[0048] Step S13, the elastic fabric 4 sprayed with the washable speckle patch in step S12 is sleeved on the real human body part to obtain the deformation image of the elastic fabric 4 in the wearing state. The specific process is as follows: first, the elastic fabric 4 with speckle is taken off from the human body part simulation model, and directly worn on the human body part. After wearing, the three-dimensional image correlation method calculation software is opened to take the image at this time as the target image for deformation calculation. Note that the environmental lighting conditions and the parameters of the three-dimensional image correlation method measurement system at this time should be completely consistent with those in step S12.

[0049] Step S2, calculate the global deformation of the elastic fabric 4 and automatically construct the three-dimensional geometry of the human body surface to obtain the global curvature. The steps are as follows:

[0050] Step S21, set the sub-area size and step size in the three-dimensional image correlation method in the calculation, and start the calculation to obtain the global deformation value of the elastic fabric 4 in the wearing state and the three-dimensional coordinates of the surface of the human body wearing part. The sub-area size is an important user-defined parameter in the three-dimensional image correlation method, and the size of a sub-area should be large enough to contain sufficient information to distinguish it from other sub-areas. The standard selected in this embodiment is that at least three speckles are contained in a sub-area, and the ideal speckle size is 3-5 pixels and the speckle density is about 50%, so the sub-area size is about 15*15 square pixels. In order to improve practicability, the sub-area size of 21*21 square pixels is selected in this embodiment.

[0051] The step size controls the density of the data points calculated by the three-dimensional image correlation method, and to some extent affects the spatial resolution of the measurement. Generally, it is recommended to select the step size between one-third and one-half of the sub-area size, so that the adjacent sub-areas partially overlap, and the step size can be changed according to the specific application. In this embodiment, one-half of the sub-area size is selected as the step size. After the sub-area size and the step size are selected, the remaining parameters are kept at the default values, and the reference image and the calculation target image taken in step S1 are used to calculate the global deformation value of the elastic fabric 4 in the wearing state and the three-dimensional coordinate value of the surface of the human body part.

[0052] Step S22, based on the three-dimensional topography of the human body surface, a spherical region with an iteratively changing radius is used to perform three-dimensional surface fitting, and the fitting curvature radius calculation results before and after iteration are compared, and when the result error meets the error requirement, the iteration is terminated to obtain the final curvature calculation result. The calculation process is shown in Figure 3 .

[0053] Generally, the three-dimensional surface data obtained directly is stored in a specific data format in the form of a large number of discrete points, and the curvature of the human body part needs to be defined on a continuous curve or surface, which cannot be obtained by directly calculating the discrete points, and the large number of discrete points obtained need to be continuous, i.e. fitting to form a surface to represent the original data. The least square method is a basic calculation method for solving optimization problems, and the principle of the least square method is used for surface fitting in this embodiment. In order to improve the efficiency of calculation and the convenience of parameter adjustment, a quadratic function is used as the function form of surface fitting. First, the quadratic function has a simple property, which can simplify the calculation of curvature and is conducive to efficient processing of a large amount of data. Second, the surface fitting performed in this embodiment is in a local range and can be dynamically iteratively adjusted according to the error, which can ensure the accuracy of the final calculation result. The fitting function form used is as follows:

[0054] z = f(x, y) = a0 + a1x + a2y + a3x 2 +a4y 2 ;

[0055] Wherein, a0 represents constant term coefficient, a1 represents x one term coefficient, a2 represents y one term coefficient, a3 represents x quadratic term coefficient, a4 represents y quadratic term coefficient, x represents x axis coordinate of data point, y represents y axis coordinate of data point.

[0056] For the selection of the fitting range adjacent point, the embodiment establishes a spherical value range with the target point as the center and the radius as the initial value r0, and the data points in the value range are used for the calculation of the fitting function.

[0057] The embodiment uses error to control the selection of adjacent points. Specifically, first, an error threshold is selected, then surface fitting is performed, and the error of fitting is calculated. If the calculated error is greater than the error threshold, the radius of the fitting area is gradually increased. Then the new points are fitted and the error is calculated, and this recursion is continued until the error is less than the error threshold. In this way, a more accurate local fitting surface with an error less than the error threshold is obtained, and the circumference C and the radius of curvature R of the leg surface can be calculated.

[0058] Step S3, using Laplace law combined with the mechanical parameters of the elastic fabric 4 and the curvature of the human body part to perform global pressure measurement. Specifically, first, the thickness t and the elastic modulus E of the elastic fabric 4 are obtained through a simple mechanical tensile test, and then the pressure measurement value of each point of the surface elastic fabric 4 of the human body part is obtained by combining the deformation ε and the curvature radius R of the elastic fabric 4 obtained in the above steps, and the specific formula is as follows:

[0059]

[0060] Therefore, the present application adopts the above-mentioned measurement method for measuring the deformation and pressure distribution characteristics of the elastic fabric in vivo, realizes the global accurate pressure measurement of the human body part when wearing the elastic fabric, significantly improves the efficiency of the measurement and the spatial resolution of the measurement results, and provides reliable data support and decision optimization direction for the development scheme of medical health elastic fabric.

[0061] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application but not to limit them, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can still be modified or replaced by equivalents, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.

Claims

1. A method of measuring in-vivo elastic fabric deformation and pressure distribution characteristics, the method comprising: The method comprises the following steps: Step S1, a three-dimensional image correlation method measurement system is built, and images of the elastic fabric in a non-pressure state and in a wearing state are obtained respectively; Step S2, global deformation of the elastic fabric is calculated, and a three-dimensional geometric appearance of a human body surface is constructed to obtain global curvature; Step S3, global pressure measurement of the elastic fabric is performed; The specific steps of the step S1 are as follows: Step S11, two industrial cameras with fixed focus lenses and two diffuse reflection fill light lamps are selected, the two industrial cameras are fixed on an optical platform according to a predetermined target distance, a distance between the cameras and a solid angle, the diffuse reflection fill light lamps are turned on, and a calibration program is performed; Step S12, a washable speckle is made on the surface of the elastic fabric by a paint spraying method, the elastic fabric is sleeved on a human body simulation cylinder to obtain an initial image of the elastic fabric in a non-pressure state; Step S13, the elastic fabric with the washable speckle in step S12 is sleeved on a human body part to obtain a deformation image of the elastic fabric in a wearing state; The step S3 uses Laplace's law to perform global pressure measurement in combination with mechanical parameters of the elastic fabric, global deformation of the elastic fabric and curvature of the human body part; A calculation formula for obtaining a pressure measurement value is as follows: ； wherein, is the thickness of the elastic fabric, is the modulus of elasticity of the elastic fabric, is the deformation of the surface of the elastic fabric, is the radius of curvature; The specific steps of the step S2 are as follows: Step S21, a size of a sub-region and a step length of the three-dimensional image correlation method measurement are set in calculation, and calculation is started to obtain global deformation numerical value of the elastic fabric in the wearing state and three-dimensional coordinates of a surface of a human body wearing part; Step S22, based on the three-dimensional appearance of the human body surface, a spherical region with a constantly iterated radius is used to perform three-dimensional surface fitting, a calculation result of a fitting curvature radius before and after iteration is compared, and when a result error meets an error requirement, iteration is terminated to obtain a final curvature calculation result.

2. The method of measuring elastic fabric deformation and pressure distribution characteristics in-vivo according to claim 1, wherein, A fitting function of the three-dimensional surface fitting in the step S22 is as follows: ； wherein represents the constant term coefficient, represents the linear term coefficient of represents the linear term coefficient of represents the quadratic term coefficient of represents the quadratic term coefficient of represents the axis coordinate of a data point, represents the axis coordinate of a data point.

Images