CN109567317B - Distribution method of barefoot information acquisition sensors - Google Patents

Distribution method of barefoot information acquisition sensors Download PDF

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CN109567317B
CN109567317B CN201710903907.2A CN201710903907A CN109567317B CN 109567317 B CN109567317 B CN 109567317B CN 201710903907 A CN201710903907 A CN 201710903907A CN 109567317 B CN109567317 B CN 109567317B
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distribution
barefoot
sensor
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CN109567317A (en
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董波
张吉昌
于昕晔
孙晰锐
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Dalian Everspry Sci & Tech Co ltd
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    • AHUMAN NECESSITIES
    • A43FOOTWEAR
    • A43DMACHINES, TOOLS, EQUIPMENT OR METHODS FOR MANUFACTURING OR REPAIRING FOOTWEAR
    • A43D1/00Foot or last measuring devices; Measuring devices for shoe parts
    • A43D1/02Foot-measuring devices

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Abstract

The invention discloses a distribution method of barefoot information acquisition sensors, which comprises the following steps: s1: determining the number and the distribution mode of the sole sensors; s2: determining the number and distribution mode of the foot surface sensors; the application also provides an installation step based on the position condition of the sensor; the method for acquiring the barefoot information is improved, the acquired barefoot information is more comprehensive and complete, the quantitative acquisition of various footprint information can be met, and a firmer foundation is laid for the three-dimensional reconstruction of the barefoot.

Description

Distribution method of barefoot information acquisition sensors
Technical Field
The invention relates to a distribution method of sensors, in particular to a distribution method of barefoot information acquisition sensors.
Background
As is well known, wearable devices are known as a new industry growth point after a smart phone and a tablet computer, typical smart wearable products in the market at present include smart bracelets, smart watches and smart glasses, the wearable devices are used on the upper half of the human body, and smart shoes are effective supplements in order to perfect the application range of the smart wearable devices. Meanwhile, the wearable plantar pressure testing technology is a novel medical monitoring technology which is rapidly developed in recent years, breaks through the space range limitation of monitoring and diagnosis of the traditional medical institution, can conveniently realize the daily monitoring of dynamic human plantar pressure, and can provide a basis for the medical care, the correction of motion postures and the scientific shoemaking of the feet of the human body; therefore, data acquisition of plantar pressure is extremely important. Only research on plantar pressure sensors exists in the prior art, but research on distribution of plantar pressure sensors still leaves a blank.
Disclosure of Invention
The application provides a distribution method of a barefoot information acquisition sensor, which can meet the quantitative acquisition of various footprint information.
The first technical scheme of the application is as follows: a distribution method of barefoot information acquisition sensors comprises the following steps:
s1: determining the number and the distribution mode of the sole sensors;
s2: and determining the number and distribution mode of the foot surface sensors.
Further, the following formula is adopted for determining the number of the sole sensors:
Figure BDA0001423621820000021
n denotes the number of sensors and S denotes the average footprint area in mm of an adult2(ii) a d is the average diameter of the collection unit with the smallest footprint, in mm.
Further, the distribution mode of sole sensor specifically is:
A. dividing the region of the sole according to the distribution condition of the acupuncture points;
B. constructing a region distribution optimal method with the objective function as a reference to solve;
C. each acupoint area distributes sensors by a method of gradually calculating a binary image area skeleton.
Further, the sole is divided into three types of regions: the acupuncture point detection device comprises a large acupuncture point area, a small acupuncture point area and a blank acupuncture point area, wherein the number of sensors in the large acupuncture point area is x, the number of sensors in the small acupuncture point area is y, and the number of sensors in the blank acupuncture point area is z.
Further, the objective function comprises information content, acupoint importance quantification degree and distribution uniformity; the solving mode based on the information quantity is as follows:
the information amount per square millimeter of the blank hole region is hA,hAV, total area SA(ii) a The large acupoint region comprises P acupoint regions with an area of SBiMinimum area SBminMaximum area is SBmaxThe smaller the area, the larger the information quantity, according to the formula
Figure BDA0001423621820000022
Calculating the information quantity; the small acupoint region comprises Q acupoint regions, and the area of one region is SCjMinimum area SCminMaximum area is SCmaxThe smaller the area, the larger the information quantity, according to the formula
Figure BDA0001423621820000023
Calculating the information amount, here constructing an objective function H:
Figure BDA0001423621820000031
1≤i≤P
1≤j≤Q
when given the number of sensors N,
Figure BDA0001423621820000032
in addition, the sensor density per area must not be less than an average of d per square millimeter, i.e., x, yi,zjD, the two points are considered as constraint conditions c1,c2Then, combining with the objective function, the following relationship is obtained:
Figure BDA0001423621820000033
satisfy c1,c2Constraint terms, there are infinite groups of solutions in the state, and here, the optimal solution is obtained by adopting a neighbor method, an interpolation method, a genetic algorithm or a neural network algorithm.
Furthermore, each acupoint area distributes sensors by a method of calculating a binary image area skeleton step by step, which is as follows:
assuming that the number of sensors in the cave region is K, the sensors are arranged for at least T times (the skeleton can be obtained by carrying out corrosion for T times), K/T sensors are required to be distributed each time, and the method comprises the following specific steps:
i. defining a binary image of a certain cave region as I, and the initial corrosion count is 0;
extracting edges of the I, and uniformly distributing K/T sensors on the edges of the I;
etching I and adding 1 to the etching count;
iv, judging whether the corrosion times reach T, if so, finishing the distribution of the sensors;
if not, continue with ii.
Further, the following equation is used to determine the number of foot sensors:
m=f(C,Δ)
Figure BDA0001423621820000041
dividing the barefoot into n circles, wherein delta is the error of the polygon circumference approaching the circumference, C is the circumference of the circle, m is the minimum number of sides meeting the error condition, L is the reference metatarsophalangeal circumference, and LiFor the perimeter of each circle, M is the number of sensors.
Furthermore, the distribution mode of the foot surface sensors is a uniform distribution mode.
As a further step, there are two prototypes carried by the above-mentioned sensors, one of which is an insole; the installation method of the sensor on the insole comprises the following steps:
a. an average foot model is constructed by acquiring a large number of barefoot footprints, and the method for constructing the average foot comprises the following steps: the key points after size normalization are average, and the pressure footprints are average and equal;
b. coinciding the bisector of the insole with the average bisector of the heel, and confirming that the heel back edge of the insole is 5mm away from the heel back edge of the average heel;
c. the area outside the average foot is as follows:
i. each area is uniformly distributed with sensors;
distributing the sensors in such a way that the number of average foot edge sensors is gradually reduced (morphological skeleton processing);
d. and in the average foot, the sensors are distributed according to the number of the sensors provided by different partitions and different optimizing modes.
As a further step, there are two prototypes carried by the above-mentioned sensors, the other being a shoe; the method for installing the sensor on the sole part of the shoe is to install the sensor by taking the insole as a bearing installation method, and the method for installing the sensor on the vamp comprises the following steps: constructing a coordinate system, wherein the z axis is the direction of a ground normal, the y axis is the direction of the center line of the footprint foot, and the x axis is the direction vertical to the zy plane;
a. measuring the maximum perimeter L of the vamp from the heel according to the vamp with the fixed code, and calculating the step length D of the sensor distribution through L/the minimum sensor number; the positive vertical distance D of the intersection point of the center line of the shoe and the heel is used as a reference point O1Shoe upper and O1Mounting a sensor at every distance D at the intersection position of the xy planes;
b. the positive vertical distance of the intersection point of the shoe center line and the heel is 2D and is used as a reference point O2Shoe upper and O2The position where the xy planes intersect is provided with a sensor every a distance D, and so on, the vamp and the O2The xy plane has no point of intersection.
The invention has the beneficial effects that: the invention provides a sensor distribution calculation method for barefoot information acquisition and an installation step based on the position condition of a sensor, so that the method for acquiring barefoot information is improved, the acquired barefoot information is more comprehensive and complete, the quantitative acquisition of various footprint information can be met, and a more solid foundation is laid for three-dimensional barefoot reconstruction.
Drawings
The invention has the following figures 3:
fig. 1 is a schematic view of the acupoint partition;
FIG. 2 is a schematic view showing the split of the barefoot into 4 circles in the example;
fig. 3 is a schematic diagram of a coordinate system constructed in the embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
Example 1
The embodiment provides a distribution method of barefoot information acquisition sensors, and the sensor requirements are as follows:
1) the sensor comprises a pressure sensing resistor, a capacitor or a power supply, and has high pressure sensing sensitivity, small volume, low power consumption and low pressure sensing noise level;
2) the sensor has long service life, wear resistance and corrosion resistance;
3) the analog-to-digital conversion noise level is low, and the quantization digit of voltage or current is more than 8 digits;
4) the bearing prototype of the integral sensor is a shoe and the bearing prototype of the sole sensor is an insole.
1. Sole:
1) the problems are solved:
(1) the quantity of information (resolution, number of sensors and number of pressure sensing element points) collected by feet with different sizes is inconsistent;
(2) it makes no sense to ensure that the point position of the sensor is defined.
2) Distribution pattern (dotted distribution):
(1) confirmation of the number of sensors:
Figure BDA0001423621820000061
n denotes the number of sensors (in mega pixels) and S denotes the average footprint area (in mm) of an adult male2) And d is the average diameter per unit of collection (in mm) with the smallest footprint.
According to the particle size (the average diameter of the millet particles is about 1 mm) reflected by the focus of traditional Chinese medicine, the sole acquisition information points in the minimum area are acquired at least more than 2 points every 1mm, and the resolution is converted into 66PPI, so that the distribution density of the whole sole acquisition equipment sensor is at least 4 per square millimeter, and the average footprint size of an adult male is about 23400mm2Within (foot length is 25cm, foot width is about 9 cm), at least 963600 points are needed, considering that low-resolution footprint information is not enough to collect partial men with large feet, the distribution of sensors is not pure two-dimensional simple arrangement, and extra points are needed to ensure that the footprints can be completely collected in a collection area, the resolution is increased to more than twice of a theoretical value to 200 ten thousand points (the area of the foot of an adult female is smaller than that of the foot of a male, so that the foot area can be required according to the resolution of the foot footprint of the male), namely, the foot information of each person is collected by 200 ten thousand points regardless of the sex and the foot condition. This is the minimum requirement for the number of sensors per sole information collection.
(2) The distribution mode of the sensors is as follows:
according to the theory of traditional Chinese medicine, the important acupuncture points of each foot of a human body are 66, the important acupuncture points of the left foot and the right foot are 33 respectively, the reflection areas of focuses are greatly different in area, the ratio of the maximum area to the minimum area exceeds 10:1, the larger the reflection area is, the more the collected points are, the smaller the area is, the more the data which needs to be collected actually (according to the information quantity), and the sensor distribution method based on the acupuncture point areas is provided, which specifically comprises the following steps:
A. according to the distribution of acupuncture points, the sole is divided into three types of areas: big acupoint region, small acupoint region, and blank acupoint region, referring to the acupoint division diagram of fig. 1, light gray is the small acupoint region, dark gray is the big acupoint region, and black is the blank acupoint region.
B. The distribution quantity of sensors per square millimeter in the blank acupoint area is x, the distribution quantity of sensors per square millimeter in the large acupoint area is y (the distribution of the sensors in different acupoints can be different or the same, and therefore the sensor distribution can be represented in a vector mode, no acupoint exists in the blank acupoint area, and therefore a single variable can be represented), the distribution quantity of sensors per square millimeter in the small acupoint area is z, an area distribution optimal method with an objective function as a reference is constructed for solving, the objective function comprises but is not limited to information quantity, acupoint importance quantification degree, distribution uniformity and the like, and the solving method based on the information quantity is given here: defining the information quantity of each load:
the information amount per square millimeter of the blank hole region is hA,hAV, total area SAThe area of a region (P acupuncture points in total) in the large acupuncture point region is SBiMinimum area SBminMaximum area is SBmaxThe smaller the area, the larger the information quantity, according to the formula
Figure BDA0001423621820000081
Calculating information amount, small acupoint region (Q acupoints in total), and area of certain region SCjMinimum area SCminMaximum area is SCmaxThe smaller the area, the larger the information quantity, according to the formula
Figure BDA0001423621820000082
Calculating the information amount, here constructing an objective function H:
Figure BDA0001423621820000083
1≤i≤P
1≤j≤Q
when given the number of sensors N,
Figure BDA0001423621820000084
in addition, the sensor density per area must not be less than an average of d per square millimeter, i.e., x, yi,zjD, the two points are considered as constraint conditions c1,c2Then, in combination with the objective function, the following relationship can be obtained:
Figure BDA0001423621820000085
satisfy c1,c2Constraint terms, in which there are infinite groups of solutions, are an NP-hard problem, and here, such a problem can be solved by adopting a neighbor method, an interpolation method, a genetic algorithm or a neural network algorithm;
C. sensors are distributed in each cave area by a method of gradually calculating a binary image area skeleton, the number of the sensors in the cave area is assumed to be K, the sensors are arranged for the least T times (the skeleton can be obtained by carrying out T times of corrosion), K/T sensors are distributed every time, and the specific mode is as follows:
i. defining a binary image of a certain cave region as that the corrosion count is initially 0;
for the extraction edge, uniformly distributing the sensors on the edge;
etching and adding 1 to the etching count;
iv, judging whether the corrosion times are reached, if so, finishing the distribution of the sensors;
if not, continue with ii.
2. Foot surface:
1) the problems are solved: the error of the sensor for collecting information is too large, and the shoe size and the weight cannot be carefully obtained.
2) The distribution mode is as follows:
(1) confirmation of the number of sensors:
m=f(C,Δ)
Figure BDA0001423621820000091
delta is the error of the polygon perimeter approaching the circumference, C is the circle perimeter, m is the minimum number of sides satisfying the error condition, L is the reference metatarsophalangeal perimeter, LiThe circumference of each circle in fig. 2, M is the number of sensors.
Since each person's barefoot instep has a high similarity in a static environment, the shape difference is not very obvious, and the degree of change is limited, but considering that each person measures stable characteristics (metatarsophalangeal circumference, anterior tarsal circumference, pocket heel circumference, etc.) during walking, a sufficient number of sensors are needed to ensure the error between the digitized characteristics and the real characteristics, when making shoes, each 3.5mm of the metatarsophalangeal circumference is a shoe number (distinguishing point), so the number of sensors on the instep must ensure that the measurement error of each circumference characteristic does not exceed 3.5mm, the metatarsophalangeal circumference is about 246.5mm (shoe designer), when measuring accuracy is less than 3.5mm, each circumference characteristic measurement needs at least 9 points (calculating error by a polygon approximating to a circle method), at most 12 points are needed, namely, each 27.38mm is collected, and the index is also applicable in the vertical direction of the circumference characteristic, the bare feet are divided into 4 circles (as shown in fig. 2), the radius of each circle is 45/90/70/60mm, the number of acquisition points in the vertical direction is 11/21/17/14, the total acquisition number is about 35 considering the common part of each circle, and therefore, the judgment is that for a person with a 25 th foot, the number of sensors required for acquiring the instep information is at least 35 × 12 — 420, and the number of sensors in the measuring direction and the vertical measuring direction is doubled to 70 × 24 considering that the footprint information with low resolution is not enough to acquire a part of men with large feet, and the total number is 1680.
(2) The distribution mode of the sensors is as follows: the sensor points are uniformly distributed, and are distributed according to one sensor point every 13.69 mm.
Example 2
The present embodiment provides a sensor mounting method, including:
two sensor-bearing prototypes are presented here:
1) shoe-pad:
(1) the insole can only be installed with a sensor on the sole of the foot, and according to the provided insole with a fixed shoe size, the known quantity is as follows:
a. overall minimum number of sensors that need to be distributed;
b. fixing the minimum number of sensors in the critical area of the footprint;
c. minimum number of sensors per area.
(2) The installation method comprises the following steps:
a. an average foot model is constructed by acquiring a large number of barefoot footprints, and the method for constructing the average foot comprises the following steps: the key points after size normalization are average, and the pressure footprints are average and equal;
b. coinciding the bisector of the insole with the average bisector of the heel, and confirming that the heel back edge of the insole is 5mm away from the heel back edge of the average heel;
c. the area outside the average foot is as follows:
i. the sensors are uniformly distributed in each area with the least number of the sensors;
distributing the sensors in such a way that the number of average foot edge sensors is gradually reduced (morphological skeleton processing);
d. and in the average foot, the sensors are distributed according to the number of the sensors provided by different partitions and different optimizing modes.
2) Shoes are as follows:
(1) the method for installing the sensors on the sole part of the shoe can refer to the method for installing the sensors by taking the insole as a bearing, and the known quantity of the sensors on the upper part of the shoe before installation is as follows according to the provided fixed shoe size:
a. a minimum number of overall sensors that need to be distributed;
b. sensor distribution requirements.
(2) The installation method comprises the following steps:
a. measuring the maximum perimeter L of the vamp from the heel according to the vamp of the shoe with the fixed shoe size, and calculating the step length D of the distribution of the sensors through L/the minimum number of sensors so as to obtain the length of the shoeThe positive vertical distance D of the intersection point of the center line and the heel is used as a reference point O1Constructing a coordinate system in the direction shown in FIG. 3, wherein z is the direction of the ground normal, y is the direction of the center line of the footprint foot, and x is the direction vertical to the zy plane; shoe upper and O1Installing a sensor at every distance D at the intersection position of the xy planes;
b. using the positive vertical distance of the intersection point of the shoe center line and the heel as 2D as a reference point O2Shoe upper and O2Mounting a sensor at the intersection position of the xy planes at intervals of a distance D, and so on, wherein the shoe upper is connected with the O2The xy plane has no point of intersection.
The application provides a sensor distribution calculation method for barefoot information acquisition and an installation step based on the position condition of the sensor, so that the method for acquiring barefoot information is improved, the acquired barefoot information is more comprehensive and complete, quantitative acquisition of various footprint information can be met, and a more solid foundation is laid for three-dimensional barefoot reconstruction.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be able to cover the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.

Claims (9)

1. A distribution method of barefoot information acquisition sensors is characterized by comprising the following steps:
s1: determining the number and the distribution mode of the sole sensors;
s2: determining the number and distribution mode of the foot surface sensors;
the following formula is adopted for determining the number of the sole sensors:
Figure FDA0002632915730000011
n denotes the number of sensors and S denotes the average footprint area in mm of an adult2(ii) a d is the average diameter of the collection unit with the smallest footprint, in mm.
2. The distribution method of the barefoot information acquisition sensors according to claim 1, wherein the distribution mode of the sole sensors is specifically as follows:
A. dividing the region of the sole according to the distribution condition of the acupuncture points;
B. constructing a region distribution optimal method with the objective function as a reference to solve;
C. each acupoint area distributes sensors by a method of gradually calculating a binary image area skeleton.
3. The distribution method of the barefoot information acquisition sensors as claimed in claim 2, wherein the sole of the foot is divided into three types of regions: the acupuncture point detection device comprises a large acupuncture point area, a small acupuncture point area and a blank acupuncture point area, wherein the number of sensors in the large acupuncture point area is x, the number of sensors in the small acupuncture point area is y, and the number of sensors in the blank acupuncture point area is z.
4. The distribution method of the barefoot information acquisition sensors as claimed in claim 3, wherein the objective function comprises information amount, acupoint importance quantification degree and distribution uniformity; the solving mode based on the information quantity is as follows:
the information amount per square millimeter of the blank hole region is hA,hAV, total area SA(ii) a The large acupoint region comprises P acupoint regions with an area of SBiMinimum area SBminMaximum area is SBmaxThe smaller the area, the larger the information quantity, according to the formula
Figure FDA0002632915730000021
Calculating the information quantity; the small acupoint region comprises Q acupoint regions, and the area of one region is SCjMinimum area SCminMaximum area is SCmaxThe smaller the area, the larger the information quantity, according to the formula
Figure FDA0002632915730000022
Calculating the information amount, here constructing an objective function H:
Figure FDA0002632915730000023
when given the number of sensors N,
Figure FDA0002632915730000024
in addition, the sensor density per area must not be less than an average of d per square millimeter, i.e.
x,yi,zj>d;
The above two points are considered as constraint conditions c1,c2Then, combining with the objective function, the following relationship is obtained:
Figure FDA0002632915730000025
satisfy c1,c2There are infinite groups of solutions under the constraint condition, and the optimal solution is obtained by adopting a neighbor method, an insertion method, a genetic algorithm or a neural network algorithm.
5. The distribution method of the barefoot information acquisition sensors as claimed in claim 4, wherein each acupoint area distributes the sensors by gradually calculating a binary image area skeleton, specifically as follows:
assuming that the number of sensors in the acupoint area is K, K/T sensors are required to be distributed for the least T times, and the method comprises the following specific steps:
i. defining a binary image of a certain cave region as I, and the initial corrosion frequency is 0;
extracting edges of the I, and uniformly distributing K/T sensors on the edges of the I;
etching I, and adding 1 to the etching times;
iv, judging whether the corrosion times reach T, if so, finishing the distribution of the sensors; if not, continuing to step ii.
6. The distribution method of the barefoot information acquisition sensors as claimed in claim 1, wherein the following formula is adopted for determining the number of the sensors on the foot surface:
m=f(C,Δ);
Figure FDA0002632915730000031
dividing the barefoot into n circles, wherein delta is the error of the polygon circumference approaching the circumference, C is the circumference of the circle, m is the minimum number of sides meeting the error condition, L is the reference metatarsophalangeal circumference, and LiFor the perimeter of each circle, M is the number of sensors.
7. The method as claimed in claim 6, wherein the distribution of the sensors is uniform.
8. The method of claim 4, 6 or 7, wherein the sensor carries two types of prototypes, one of which is an insole; the installation method of the sensor on the insole comprises the following steps:
a. constructing an average foot model by acquiring a large number of barefoot footprints;
b. coinciding the bisector of the insole with the average bisector and confirming that the heel back edge of the insole has a certain distance from the heel back edge of the average heel;
c. the areas outside the average foot were treated as follows:
i. each area is uniformly distributed with sensors;
distributing the sensors in such a way that the number of average foot edge sensors decreases gradually;
d. and in the average foot, the sensors are distributed according to the number of the sensors provided by different partitions and different optimizing modes.
9. The method of claim 8, wherein the sensor carries two types of prototypes, the other type being a shoe; the method for installing the sensor on the sole part of the shoe is implemented by the method for installing the sensor on the insole, and the method for installing the sensor on the vamp comprises the following steps: constructing a coordinate system, wherein the z axis is the direction of a ground normal, the y axis is the direction of the center line of the footprint foot, and the x axis is the direction vertical to the zy plane;
a. measuring the maximum perimeter L of the vamp from the heel, and calculating the step length D of the distribution of the sensors through L/the minimum number of the sensors; the positive vertical distance D of the intersection point of the center line of the shoe and the heel is used as a reference point O1Shoe upper and O1Mounting a sensor at every distance D at the intersection position of the xy planes;
b. the positive vertical distance of the intersection point of the shoe center line and the heel is 2D and is used as a reference point O2Shoe upper and O2Mounting a sensor at every distance D at the position where the xy planes intersect, and so on until the vamp and the O2The xy plane has no point of intersection.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3102534A (en) * 1962-06-21 1963-09-03 Du Pont Physiologic fluid pressure measuring apparatus
CN1344907A (en) * 2000-09-21 2002-04-17 李熙满 System and method for measuring sole of foot
CN205947243U (en) * 2016-07-29 2017-02-15 孟朝琳 Special shoes of diabetes

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3102534A (en) * 1962-06-21 1963-09-03 Du Pont Physiologic fluid pressure measuring apparatus
CN1344907A (en) * 2000-09-21 2002-04-17 李熙满 System and method for measuring sole of foot
CN205947243U (en) * 2016-07-29 2017-02-15 孟朝琳 Special shoes of diabetes

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