Relationship analysis system between foot shape information of elderly and chronic disease patients and standard foot shape information

Abstract

The present invention relates to the technical field of relationship analysis, and specifically discloses a relationship analysis system for foot shape information of the elderly and chronic disease patients and standard foot shape information, including: a foot shape abnormality determination module: scanning the feet of the elderly and chronic disease patients respectively, obtaining the foot shape models of the elderly and chronic disease patients, and then determining the foot shape abnormality data according to the foot shape models; an abnormal data analysis module: based on the foot shape abnormality data, outputting the elderly foot shape abnormality value and the chronic disease foot shape abnormality value; a relationship model construction module: based on the elderly foot shape abnormality value and the chronic disease foot shape abnormality value, respectively extracting the elderly foot shape abnormality maximum value and the chronic disease foot shape abnormality maximum value, constructing a relationship model, and evaluating the degree of association between elderly and chronic diseases; the present invention can accurately analyze the relationship between the foot shape information of the elderly and chronic disease patients and the standard foot shape information; and will improve the accuracy of the model for comparing and analyzing the foot shapes of the elderly and chronic disease patients.

Description

Technical Field

[0001] The present invention relates to the technical field of model analysis, and in particular to a system for analyzing the relationship between foot shape information of elderly patients and patients with chronic diseases and standard foot shape information. Background Art

[0002] As the population ages, the health of the elderly is receiving increasing attention. As an important supporting structure of the human body, the shape and health of the foot directly affect the individual's walking, standing and quality of life. Especially for the elderly and patients with chronic diseases, such as diabetes and cardiovascular disease, changes in foot shape may indicate potential health risks. Therefore, comparing and analyzing the foot shape information of the elderly and chronic disease patients with the standard foot shape information has important medical and rehabilitation value.

[0003] In the prior art, the analysis of the foot shape information of the elderly and chronic disease patients usually adopts subjective means (observation based on experience) to make judgments and analyses. Therefore, the data of the foot shape information of the elderly and chronic disease patients cannot be accurately collected and analyzed, which will affect the accuracy of the construction of the foot shape model of the elderly and chronic disease patients. Summary of the invention

[0004] The purpose of the present invention is to provide a system for analyzing the relationship between the foot shape information of the elderly and chronic disease patients and the standard foot shape information, so as to solve the technical problems in the above background.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] The present invention is a system for analyzing the relationship between foot shape information of elderly patients and patients with chronic diseases and standard foot shape information, comprising:

[0007] Foot shape abnormality determination module: scan the feet of the elderly and chronic disease patients respectively to obtain the foot shape models of the elderly and chronic disease patients, and then determine the foot shape abnormality data based on the foot shape models;

[0008] Among them, the abnormal foot shape data include: abnormal values ​​of elderly foot shape and abnormal values ​​of chronic disease foot shape; abnormal values ​​of elderly foot shape include: total abnormal values ​​of elderly floating area and total abnormal values ​​of elderly sunken area; abnormal values ​​of chronic disease foot shape include: total abnormal values ​​of chronic disease floating area and total abnormal values ​​of chronic disease sunken area;

[0009] Abnormal data analysis module: Based on the abnormal foot shape data, the output is the abnormal values ​​of elderly foot shape and chronic disease foot shape;

[0010] Relationship model building module: Based on the abnormal values ​​of foot shape in the elderly and the abnormal values ​​of foot shape due to chronic diseases, the maximum values ​​of abnormal foot shape in the elderly and the maximum values ​​of abnormal foot shape due to chronic diseases are extracted respectively, and a relationship model is built to evaluate the degree of correlation between elderly and chronic diseases.

[0011] As a further solution of the present invention: the process of obtaining the total outliers in the elderly floating area is:

[0012] Analyze each old floating area, output the old floating area volume old abnormal factor and abnormal convex peak value, multiply the old floating area volume abnormal factor and the old abnormal convex peak value to obtain the old floating area abnormal value;

[0013] Sum up all the outliers in the elderly floating area to get the total outlier in the elderly floating area;

[0014] Among them, the output process of the volume anomaly factor of the old floating area is:

[0015] The volume of each elderly floating area is obtained, and the ratio of the volume of the elderly floating area to the volume of the standard foot shape model is calculated to obtain the elderly volume abnormality factor;

[0016] The output process of the abnormal convex peak value of old age is:

[0017] Obtain the farthest point of each elderly floating area from the standard foot shape model in vertical distance, mark it as the elderly floating peak point, measure the vertical distance between the elderly floating peak point and the standard foot shape model, mark it as the elderly abnormal convex peak point.

[0018] As a further solution of the present invention: the process of obtaining the total outliers of the aged depression area is as follows:

[0019] Analyze each elderly depression area, output the elderly depression volume abnormality factor and the elderly abnormal depression peak value, perform product operation on the elderly depression volume abnormality factor and the elderly abnormal depression peak value, and obtain the elderly depression area abnormal value;

[0020] The total outlier value of the elderly depression area is calculated by summing up all outliers in the elderly depression area;

[0021] Among them, the output process of the abnormal volume factor of the elderly depression is:

[0022] The volume of each elderly depression area is obtained, and the ratio of the volume of the elderly depression area to the volume of the standard foot shape model is calculated to obtain the abnormal factor of the elderly depression volume;

[0023] The output process of the abnormal concave peak of old age is:

[0024] Obtain the farthest point of each elderly depression area from the standard foot shape model in vertical distance, mark it as the elderly depression peak point, measure the vertical distance between the elderly depression peak point and the standard foot shape model, mark it as the elderly abnormal depression peak point.

[0025] As a further solution of the present invention: performing an overlap analysis on the foot shape model of the elderly patient and the standard foot shape model to obtain the elderly non-overlapping area;

[0026] Extract the volume of each non-overlapping area of ​​the elderly and mark it as the non-overlapping area volume of the elderly;

[0027] If the volume of the elderly non-heavy area is greater than the elderly non-heavy area volume threshold, the elderly non-overlapping area is marked as an elderly analysis area;

[0028] All the elderly analysis areas are divided according to the concave-convex features to obtain elderly floating areas and elderly sunken areas.

[0029] As a further solution of the present invention: the process of obtaining the total abnormal value of the chronic disease floating area is:

[0030] Analyze each chronic disease floating area, output the chronic disease floating area volume chronic disease abnormal factor and abnormal convex peak value, multiply the chronic disease floating area volume abnormal factor and chronic disease abnormal convex peak value to obtain the chronic disease floating area abnormal value;

[0031] Sum up all the outliers in the chronic disease emerging areas to get the total outliers in the chronic disease emerging areas;

[0032] Among them, the output process of the abnormal volume factor of the chronic disease floating area is:

[0033] The volume of each chronic disease floating area is obtained, and the ratio of the volume of the chronic disease floating area to the volume of the standard foot shape model is calculated to obtain the chronic disease volume abnormality factor;

[0034] The output process of abnormal convex peak value of chronic diseases is:

[0035] Obtain the farthest point of each chronic disease floating area from the standard foot shape model in vertical distance, mark it as the chronic disease floating peak point, measure the vertical distance between the chronic disease floating peak point and the standard foot shape model, mark it as the chronic disease abnormal convex peak value.

[0036] As a further solution of the present invention: the process of obtaining the total outliers of the chronic disease depression area is as follows:

[0037] Analyze each chronic disease depression area, output the chronic disease depression volume abnormality factor and the chronic disease abnormal depression peak value, multiply the chronic disease depression volume abnormality factor and the chronic disease abnormal depression peak value to obtain the chronic disease depression area outlier;

[0038] The total outlier value of the chronic disease depression area is calculated by summing up all outliers in the chronic disease depression area;

[0039] Among them, the output process of the chronic disease depression volume abnormality factor is:

[0040] The volume of each chronic disease depression area is obtained, and the ratio of the volume of the chronic disease depression area to the volume of the standard foot shape model is calculated to obtain the chronic disease depression volume abnormality factor;

[0041] The output process of abnormal concave peak of chronic disease is as follows:

[0042] Obtain the farthest point of each chronic disease depression area from the standard foot shape model in vertical distance, mark it as the chronic disease depression peak point, measure the vertical distance between the chronic disease depression peak point and the standard foot shape model, mark it as the chronic disease abnormal depression peak point.

[0043] As a further solution of the present invention: performing an overlap analysis on the foot shape model of a chronic disease patient and the standard foot shape model to obtain a non-overlapping area of ​​the chronic disease;

[0044] Extract the volume of each non-overlapping area of ​​chronic diseases and mark it as the volume of non-overlapping area of ​​chronic diseases;

[0045] If the volume of the non-serious chronic disease area is greater than the volume threshold of the non-serious chronic disease area, the non-overlapping chronic disease area is marked as a chronic disease analysis area;

[0046] All chronic disease analysis areas are divided according to concave and convex features to obtain chronic disease floating areas and chronic disease sunken areas.

[0047] As a further solution of the present invention: in the abnormal data analysis module, the total abnormal values ​​of the elderly floating area and the total abnormal values ​​of the elderly sunken area obtained for the foot shape model of the elderly patients are marked as ZFG and ZAG respectively, and the formula , calculate the abnormal value ZYG of the elderly foot shape;

[0048] The total outliers of the chronic disease floating area and the chronic disease sunken area obtained by the foot shape model of chronic disease patients are marked as ZFM and ZAM respectively. , calculate the abnormal value ZYM of chronic disease foot shape;

[0049] Among them, a1 and a2 are weight ratio coefficients, a1+a2=1.

[0050] As a further solution of the present invention: in the relationship model building module, all the foot shape models of the elderly patients are divided according to age ranges to obtain the foot shape models of the elderly patients of different age groups;

[0051] Obtain the abnormal values ​​of the foot shape of elderly patients in different age groups, extract the maximum value and the minimum value of the abnormal foot shape, mark them as ZYGmax and ZYGmin respectively, and construct the abnormal foot shape interval [ZYGmin, ZYGmax];

[0052] The foot shape models of all chronic disease patients are divided according to the severity of their disease, and the foot shape models of elderly patients in different disease stages are obtained;

[0053] Obtain chronic disease foot shape abnormality values ​​of the foot shape models of chronic disease patients in different disease stages, extract the maximum value and minimum value of chronic disease foot shape abnormality, mark them as ZYMmax and ZYMmin respectively, and construct the chronic disease foot shape abnormality interval [ZYMmin, ZYMmax];

[0054] A relationship model analysis was conducted on the abnormal foot shape intervals in the elderly [ZYGmin, ZYGmax] and the abnormal foot shape intervals in chronic diseases [ZYMmin, ZYMmax], and the degree of correlation between advanced age and chronic diseases was evaluated.

[0055] As a further solution of the present invention: the relationship model analysis process is:

[0056] By formula , calculate the minimum value ZJmin; through the formula , the calculated maximum value is close to the value ZJmax;

[0057] Compare the minimum proximity value ZJmin and the maximum proximity value ZJmax with the corresponding proximity thresholds respectively;

[0058] If the minimum approach value ZJmin and the maximum approach value ZJmax are both less than the approach threshold, it means that the degree of abnormality of the foot shape of the elderly patient is similar to that of the chronic disease patient, and a signal of similar correlation between the degree of influence of elderly and chronic disease is generated;

[0059] Otherwise, it means that the degree of abnormal foot shape of elderly patients is not similar to that of patients with chronic diseases, and a signal of different degrees of correlation between elderly and chronic disease effects is generated.

[0060] Beneficial effects of the present invention:

[0061] (1) The present invention scans the feet of the elderly and chronic disease patients respectively to obtain the foot shape models of the elderly and chronic disease patients, and then determines the foot shape abnormality data according to the foot shape models; based on the foot shape abnormality data, outputs the elderly foot shape abnormality value and the chronic disease foot shape abnormality value; the present invention analyzes the feet of the elderly and chronic disease patients and the standard foot shape model respectively, and completes the concrete representation of the abnormal relationship degree through abnormal area extraction and calculation, so as to accurately analyze the relationship between the foot shape information of the elderly and chronic disease patients and the standard foot shape information; and improves the accuracy of the model for comparing the foot shapes of the elderly and chronic disease patients with each other;

[0062] (2) Based on the abnormal values ​​of foot shape in the elderly and the abnormal values ​​of foot shape in chronic diseases, the present invention extracts the maximum abnormal values ​​of foot shape in the elderly and the maximum abnormal values ​​of foot shape in chronic diseases, respectively, constructs a relationship model, and evaluates the degree of correlation between elderly and chronic diseases; the present invention further analyzes the concrete representation of the abnormal relationship between the elderly and chronic disease patients, and more accurately judges the degree of correlation between the influence of foot shape on elderly and chronic disease patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The present invention will be further described below in conjunction with the accompanying drawings.

[0064] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0065] Figure 2 It is a system block diagram of embodiment 2 of the present invention. DETAILED DESCRIPTION

[0066] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] Example 1

[0068] See also Figure 1 As shown, the relationship analysis system of the foot shape information of the elderly and chronic disease patients and the standard foot shape information according to the embodiment of the present invention includes the following modules:

[0069] Foot shape abnormality determination module: scan the feet of the elderly and chronic disease patients respectively to obtain the foot shape models of the elderly and chronic disease patients, and then determine the foot shape abnormality data based on the foot shape models;

[0070] Among them, the abnormal foot shape data include: abnormal values ​​of elderly foot shape and abnormal values ​​of chronic disease foot shape;

[0071] In some implementation schemes, a three-dimensional foot laser scanner is used to scan the feet of the elderly and chronic disease patients, and the foot shape models of the elderly patients and the chronic disease patients are obtained by analysis;

[0072] The foot shape models of the elderly and chronic disease patients were compared and analyzed with the standard foot shape model to obtain abnormal values ​​of the elderly and chronic disease foot shapes.

[0073] Among them, the abnormal values ​​of the foot shape of the elderly include: the total abnormal values ​​of the floating area of ​​the elderly and the total abnormal values ​​of the sunken area of ​​the elderly;

[0074] The abnormal values ​​of chronic disease foot shape include: the total abnormal values ​​of chronic disease floating area and the total abnormal values ​​of chronic disease sunken area;

[0075] It should be explained that the standard foot shape model is determined by technicians in this field by scanning the feet of a large number of healthy adults using a three-dimensional foot laser scanner, and then collecting statistics on all scanned foot shape models; the determination process is: the data with the most foot shape data is used as the standard foot shape data, and then the standard foot shape model is constructed by combining the standard foot shape data;

[0076] Among them, the foot shape data includes: length data: foot length: the distance from the heel to the longest toe tip; width data: foot width: the measurement value of the widest part of the foot, which may include the width of different parts, such as forefoot width, midfoot width or full foot width; plantar circumference: the circumference around the forefoot, used to evaluate the looseness and comfort of the shoe; arch height: the degree of concavity of the sole, that is, the height of the arch; heel height: the distance from the sole to the highest point of the heel; circumference data: ankle circumference: the circumference around the ankle; instep height: the distance from the sole to the highest point of the instep; angle data: toe angle: the relative angle between the toes, which may include the hallux valgus angle, etc.; arch angle: the angle between the arch and the ground, reflecting the flatness or arch of the sole, etc.

[0077] First, specifically, the process of obtaining the abnormal value of the elderly foot shape is as follows:

[0078] The foot shape model of the elderly patient is overlapped with the standard foot shape model to obtain the elderly non-overlapping area;

[0079] The volume of each non-overlapping area of ​​the elderly is extracted and marked as the volume of the elderly non-heavy area. All the volumes of the elderly non-heavy area are compared and analyzed with the threshold of the volume of the elderly non-heavy area.

[0080] If the volume of the elderly non-overlapping area is less than or equal to the elderly non-overlapping area volume threshold, it means that the volume feature of the elderly non-overlapping area is small, and the abnormal impact it produces is also small, that is, an ignore signal is generated;

[0081] If the volume of the elderly non-overlapping area is greater than the elderly non-overlapping area volume threshold, it means that the volume feature of the elderly non-overlapping area is larger, and the abnormal impact it produces is also larger, and the elderly non-overlapping area is marked as an elderly analysis area;

[0082] All the elderly analysis areas are divided according to the concave-convex features to obtain the elderly floating area and the elderly sunken area, wherein the elderly floating area is the area outside the standard foot shape model, and the elderly sunken area is the area inside the standard foot shape model;

[0083] Analyze each old floating area, output the old floating area volume old abnormal factor and abnormal convex peak value, multiply the old floating area volume abnormal factor and the old abnormal convex peak value to obtain the old floating area abnormal value;

[0084] Sum up all the outliers in the elderly floating area to get the total outlier in the elderly floating area;

[0085] Furthermore, the output process of the volume anomaly factor of the old floating area is:

[0086] The volume of each elderly floating area is obtained, and the ratio of the volume of the elderly floating area to the volume of the standard foot shape model is calculated to obtain the elderly volume abnormality factor;

[0087] The output process of the abnormal convex peak value of old age is:

[0088] Obtain the farthest point of each elderly floating area from the standard foot shape model in vertical distance, mark it as the elderly floating peak point, measure the vertical distance between the elderly floating peak point and the standard foot shape model, mark it as the elderly abnormal convex peak value;

[0089] Analyze each elderly depression area, output the elderly depression volume abnormality factor and the elderly abnormal depression peak value, perform product operation on the elderly depression volume abnormality factor and the elderly abnormal depression peak value, and obtain the elderly depression area abnormal value;

[0090] The total outlier value of the elderly depression area is calculated by summing up all outliers in the elderly depression area;

[0091] Furthermore, the output process of the abnormal volume factor of the elderly depression is:

[0092] The volume of each elderly depression area is obtained, and the ratio of the volume of the elderly depression area to the volume of the standard foot shape model is calculated to obtain the abnormal factor of the elderly depression volume;

[0093] The output process of the abnormal concave peak of old age is:

[0094] Obtain the farthest point of each elderly depression area from the standard foot shape model in vertical distance, mark it as the elderly depression peak point, measure the vertical distance between the elderly depression peak point and the standard foot shape model, mark it as the elderly abnormal depression peak point;

[0095] Second, specifically, the process of obtaining the abnormal value of chronic disease foot shape is as follows:

[0096] Perform overlap analysis on the foot shape model of chronic disease patients and the standard foot shape model to obtain the non-overlapping area of ​​chronic disease;

[0097] The volumes of non-overlapping chronic disease areas are extracted and marked as non-serious chronic disease area volumes. All non-serious chronic disease area volumes are compared with the non-serious chronic disease area volume thresholds for analysis.

[0098] If the volume of the non-serious chronic disease area is less than or equal to the volume threshold of the non-serious chronic disease area, it means that the volume feature of the non-overlapping chronic disease area is small, and the abnormal impact it produces is also small, that is, an ignore signal is generated;

[0099] If the volume of the non-serious chronic disease area is greater than the volume threshold of the non-serious chronic disease area, it means that the volume feature of the non-overlapping chronic disease area is larger, and the abnormal impact it produces is also larger, and the non-overlapping chronic disease area is marked as a chronic disease analysis area;

[0100] All chronic disease analysis areas are divided according to the concave-convex features to obtain chronic disease floating areas and chronic disease sunken areas, where the chronic disease floating areas are areas outside the standard foot shape model, and the chronic disease sunken areas are areas inside the standard foot shape model;

[0101] Analyze each chronic disease floating area, output the chronic disease floating area volume chronic disease abnormal factor and abnormal convex peak value, multiply the chronic disease floating area volume abnormal factor and chronic disease abnormal convex peak value to obtain the chronic disease floating area abnormal value;

[0102] Sum up all the outliers in the chronic disease emerging areas to get the total outliers in the chronic disease emerging areas;

[0103] Furthermore, the output process of the abnormal volume factor of the chronic disease floating area is:

[0104] The volume of each chronic disease floating area is obtained, and the ratio of the volume of the chronic disease floating area to the volume of the standard foot shape model is calculated to obtain the chronic disease volume abnormality factor;

[0105] The output process of abnormal convex peak value of chronic diseases is:

[0106] Obtain the farthest point of each chronic disease floating area from the standard foot shape model in vertical distance, mark it as the chronic disease floating peak point, measure the vertical distance between the chronic disease floating peak point and the standard foot shape model, mark it as the chronic disease abnormal convex peak value;

[0107] Analyze each chronic disease depression area, output the chronic disease depression volume abnormality factor and the chronic disease abnormal depression peak value, multiply the chronic disease depression volume abnormality factor and the chronic disease abnormal depression peak value to obtain the chronic disease depression area outlier;

[0108] The total outlier value of the chronic disease depression area is calculated by summing up all outliers in the chronic disease depression area;

[0109] Furthermore, the output process of the chronic disease depression volume abnormality factor is:

[0110] The volume of each chronic disease depression area is obtained, and the ratio of the volume of the chronic disease depression area to the volume of the standard foot shape model is calculated to obtain the chronic disease depression volume abnormality factor;

[0111] The output process of abnormal concave peak of chronic disease is as follows:

[0112] Obtain the farthest point of each chronic disease depression area from the standard foot shape model in vertical distance, mark it as the chronic disease depression peak point, measure the vertical distance between the chronic disease depression peak point and the standard foot shape model, mark it as the chronic disease abnormal depression peak value;

[0113] Abnormal data analysis module: Based on the abnormal foot shape data, the output is the abnormal values ​​of elderly foot shape and chronic disease foot shape;

[0114] In some embodiments, the total abnormal value of the elderly floating area and the total abnormal value of the elderly sunken area obtained for the foot shape model of the elderly patient are marked as ZFG and ZAG, respectively, and are expressed by the formula , the abnormal value of the elderly foot shape ZYG is calculated, where a1 and a2 are weight ratio coefficients, a1+a2=1, the value of a1 is 0.47, and the value of a2 is 0.53;

[0115] The total outliers of the chronic disease floating area and the chronic disease sunken area obtained by the foot shape model of chronic disease patients are marked as ZFM and ZAM respectively. , the abnormal value ZYM of chronic disease foot shape is calculated, where a1 and a2 are weight proportion coefficients, a1+a2=1, the value of a1 is 0.47, and the value of a2 is 0.53;

[0116] The technical solution of the embodiment of the present invention is as follows: the feet of the elderly and patients with chronic diseases are scanned respectively to obtain foot shape models of the elderly and patients with chronic diseases, and then the abnormal foot shape data is determined based on the foot shape models; based on the abnormal foot shape data, the abnormal value of the elderly foot shape and the abnormal value of the chronic disease foot shape are output; the present invention analyzes the feet of the elderly and patients with chronic diseases respectively with the standard foot shape model, and completes the concrete representation of the degree of abnormal relationship through abnormal area extraction and calculation, so as to accurately analyze the relationship between the foot shape information of the elderly and patients with chronic diseases and the standard foot shape information; and improves the accuracy of the model for comparing the foot shapes of the elderly and patients with chronic diseases.

[0117] Example 2

[0118] See also Figure 2 As shown, the relationship analysis system between the foot shape information of the elderly and chronic disease patients and the standard foot shape information according to the embodiment of the present invention also includes the following modules:

[0119] Relationship model building module: Based on the abnormal values ​​of foot shape in the elderly and the abnormal values ​​of foot shape in chronic diseases, the maximum abnormal values ​​of foot shape in the elderly and the maximum abnormal values ​​of foot shape in chronic diseases are extracted respectively, and a relationship model is built to evaluate the degree of association between elderly and chronic diseases;

[0120] In some embodiments, all the foot shape models of the elderly patients are divided into age ranges to obtain foot shape models of elderly patients of different age groups, wherein the age range may be 1 year;

[0121] Obtain the abnormal values ​​of the foot shape of elderly patients in different age groups, extract the maximum value and the minimum value of the abnormal foot shape, mark them as ZYGmax and ZYGmin respectively, and construct the abnormal foot shape interval [ZYGmin, ZYGmax];

[0122] And, the foot shape models of all chronic disease patients are divided according to the severity of the disease, so as to obtain the foot shape models of elderly patients in different disease stages, wherein the disease severity can be the duration of the disease, and the duration of the disease can be 1 year;

[0123] Obtain chronic disease foot shape abnormality values ​​of the foot shape models of chronic disease patients in different disease stages, extract the maximum value and minimum value of chronic disease foot shape abnormality, mark them as ZYMmax and ZYMmin respectively, and construct the chronic disease foot shape abnormality interval [ZYMmin, ZYMmax];

[0124] Conduct relationship model analysis on the intervals of abnormal foot shape in the elderly [ZYGmin, ZYGmax] and the intervals of abnormal foot shape in chronic diseases [ZYMmin, ZYMmax].

[0125] By formula , calculate the minimum value ZJmin; through the formula , the calculated maximum value is close to the value ZJmax;

[0126] Compare the minimum proximity value ZJmin and the maximum proximity value ZJmax with the corresponding proximity thresholds respectively;

[0127] If the minimum approach value ZJmin and the maximum approach value ZJmax are both smaller than the corresponding approach thresholds, it means that the degree of foot shape abnormality of the elderly patients in this age group is similar to that of the chronic disease patients in this condition group, and a signal of similar correlation between the degree of elderly and chronic disease is generated;

[0128] Otherwise, it means that the degree of abnormal foot shape of the elderly patients in this age group is not similar to that of the chronic disease patients in this condition group, and a signal of different degrees of correlation between the influence of advanced age and chronic disease is generated;

[0129] It should be noted that: otherwise, the situation is: either or both of the minimum proximity value ZJmin and the maximum proximity value ZJmax are greater than or equal to the corresponding proximity threshold;

[0130] The working principle of the present invention is as follows: based on the abnormal values ​​of foot shape in the elderly and the abnormal values ​​of foot shape in chronic diseases, the maximum abnormal values ​​of foot shape in the elderly and the abnormal values ​​of foot shape in chronic diseases are extracted respectively, a relationship model is constructed, and the correlation between elderly and chronic diseases is evaluated; the present invention further analyzes the concrete representation of the abnormal relationship between the elderly and chronic disease patients, and more accurately judges the correlation degree of the influence of foot shape on elderly and chronic disease patients.

[0131] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A system for analyzing the relationship between the foot shape information of the elderly and chronic disease patients and the standard foot shape information, characterized in that: include: Foot shape abnormality determination module: scan the feet of the elderly and chronic disease patients respectively to obtain the foot shape models of the elderly and chronic disease patients, and then determine the foot shape abnormality data based on the foot shape models; Among them, the abnormal foot shape data include: abnormal values ​​of elderly foot shape and abnormal values ​​of chronic disease foot shape; abnormal values ​​of elderly foot shape include: total abnormal values ​​of elderly floating area and total abnormal values ​​of elderly sunken area; abnormal values ​​of chronic disease foot shape include: total abnormal values ​​of chronic disease floating area and total abnormal values ​​of chronic disease sunken area; Abnormal data analysis module: Based on the abnormal foot shape data, the output is the abnormal values ​​of elderly foot shape and chronic disease foot shape; Relationship model building module: Based on the abnormal values ​​of foot shape in the elderly and the abnormal values ​​of foot shape in chronic diseases, the maximum abnormal values ​​of foot shape in the elderly and the maximum abnormal values ​​of foot shape in chronic diseases are extracted respectively, and a relationship model is built to evaluate the correlation between the elderly and chronic diseases; The process of obtaining the total outlier value of the elderly floating area is as follows: Analyze each old floating area, output the old floating area volume old abnormal factor and abnormal convex peak value, multiply the old floating area volume abnormal factor and the old abnormal convex peak value to obtain the old floating area abnormal value; Sum up all the outliers in the elderly floating area to get the total outlier in the elderly floating area; Among them, the output process of the volume anomaly factor of the old floating area is: The volume of each elderly floating area is obtained, and the ratio of the volume of the elderly floating area to the volume of the standard foot shape model is calculated to obtain the elderly volume abnormality factor; The output process of the abnormal convex peak value of old age is: Obtain the farthest point of each elderly floating area from the standard foot shape model in vertical distance, mark it as the elderly floating peak point, measure the vertical distance between the elderly floating peak point and the standard foot shape model, mark it as the elderly abnormal convex peak value; The process of obtaining the total outlier value of the high-age depression area is as follows: Analyze each elderly depression area, output the elderly depression volume abnormality factor and the elderly abnormal depression peak value, perform product operation on the elderly depression volume abnormality factor and the elderly abnormal depression peak value, and obtain the elderly depression area abnormal value; The total outlier value of the elderly depression area is calculated by summing up all outliers in the elderly depression area; Among them, the output process of the abnormal volume factor of the elderly depression is: The volume of each elderly depression area is obtained, and the ratio of the volume of the elderly depression area to the volume of the standard foot shape model is calculated to obtain the abnormal factor of the elderly depression volume; The output process of the abnormal concave peak of old age is: Obtain the farthest point of each elderly depression area from the standard foot shape model in vertical distance, mark it as the elderly depression peak point, measure the vertical distance between the elderly depression peak point and the standard foot shape model, mark it as the elderly abnormal depression peak point; The process of obtaining the total outlier value of the chronic disease floating area is as follows: Analyze each chronic disease floating area, output the chronic disease floating area volume chronic disease abnormal factor and abnormal convex peak value, multiply the chronic disease floating area volume abnormal factor and chronic disease abnormal convex peak value to obtain the chronic disease floating area abnormal value; Sum up all the outliers in the chronic disease emerging areas to get the total outliers in the chronic disease emerging areas; Among them, the output process of the abnormal volume factor of the chronic disease floating area is: The volume of each chronic disease floating area is obtained, and the ratio of the volume of the chronic disease floating area to the volume of the standard foot shape model is calculated to obtain the chronic disease volume abnormality factor; The output process of abnormal convex peak value of chronic diseases is: Obtain the farthest point of each chronic disease floating area from the standard foot shape model in vertical distance, mark it as the chronic disease floating peak point, measure the vertical distance between the chronic disease floating peak point and the standard foot shape model, mark it as the chronic disease abnormal convex peak value; The process of obtaining the total outlier value of the chronic disease depression area is as follows: Analyze each chronic disease depression area, output the chronic disease depression volume abnormality factor and the chronic disease abnormal depression peak value, multiply the chronic disease depression volume abnormality factor and the chronic disease abnormal depression peak value to obtain the chronic disease depression area outlier; The total outlier value of the chronic disease depression area is calculated by summing up all outliers in the chronic disease depression area; Among them, the output process of the chronic disease depression volume abnormality factor is: The volume of each chronic disease depression area is obtained, and the ratio of the volume of the chronic disease depression area to the volume of the standard foot shape model is calculated to obtain the chronic disease depression volume abnormality factor; The output process of abnormal concave peak of chronic disease is as follows: Obtain the farthest point of each chronic disease depression area from the standard foot shape model in vertical distance, mark it as the chronic disease depression peak point, measure the vertical distance between the chronic disease depression peak point and the standard foot shape model, mark it as the chronic disease abnormal depression peak point.

2. The relationship analysis system between the foot shape information of the elderly and chronic disease patients and the standard foot shape information according to claim 1, characterized in that: The foot shape model of the elderly patient is overlapped with the standard foot shape model to obtain the elderly non-overlapping area; Extract the volume of each non-overlapping area of ​​the elderly and mark it as the non-overlapping area volume of the elderly; If the volume of the elderly non-heavy area is greater than the elderly non-heavy area volume threshold, the elderly non-overlapping area is marked as an elderly analysis area; All the elderly analysis areas are divided according to the concave-convex features to obtain elderly floating areas and elderly sunken areas.

3. The relationship analysis system between the foot shape information of the elderly and chronic disease patients and the standard foot shape information according to claim 2, characterized in that: Perform overlap analysis on the foot shape model of chronic disease patients and the standard foot shape model to obtain the non-overlapping area of ​​chronic disease; Extract the volume of each non-overlapping area of ​​chronic diseases and mark it as the volume of non-overlapping area of ​​chronic diseases; If the volume of the non-serious chronic disease area is greater than the volume threshold of the non-serious chronic disease area, the non-overlapping chronic disease area is marked as a chronic disease analysis area; All chronic disease analysis areas are divided according to concave and convex features to obtain chronic disease floating areas and chronic disease sunken areas.

4. The relationship analysis system between the foot shape information of the elderly and chronic disease patients and the standard foot shape information according to claim 1, characterized in that: In the abnormal data analysis module, the total abnormal values ​​of the elderly floating area and the total abnormal values ​​of the elderly sunken area obtained for the foot shape model of elderly patients are marked as ZFG and ZAG respectively, and the formula , calculate the abnormal value ZYG of the elderly foot shape; The total outliers of the chronic disease floating area and the chronic disease sunken area obtained by the foot shape model of chronic disease patients are marked as ZFM and ZAM respectively. , calculate the abnormal value ZYM of chronic disease foot shape; Among them, a1 and a2 are weight ratio coefficients, a1+a2=1.

5. The relationship analysis system between the foot shape information of the elderly and chronic disease patients and the standard foot shape information according to claim 1, characterized in that: In the relational model building module, all the foot shape models of the elderly patients are divided according to age ranges to obtain the foot shape models of the elderly patients in different age groups; Obtain the abnormal values ​​of the foot shape of elderly patients in different age groups, extract the maximum value and the minimum value of the abnormal foot shape, mark them as ZYGmax and ZYGmin respectively, and construct the abnormal foot shape interval [ZYGmin, ZYGmax]; The foot shape models of all chronic disease patients are divided according to the severity of their disease, and the foot shape models of elderly patients in different disease stages are obtained; Obtain chronic disease foot shape abnormality values ​​of the foot shape models of chronic disease patients in different disease stages, extract the maximum value and minimum value of chronic disease foot shape abnormality, mark them as ZYMmax and ZYMmin respectively, and construct the chronic disease foot shape abnormality interval [ZYMmin, ZYMmax]; A relationship model analysis was conducted on the abnormal foot shape intervals in the elderly [ZYGmin, ZYGmax] and the abnormal foot shape intervals in chronic diseases [ZYMmin, ZYMmax], and the degree of correlation between advanced age and chronic diseases was evaluated.

6. The relationship analysis system between the foot shape information of the elderly and chronic disease patients and the standard foot shape information according to claim 5, characterized in that: The relationship model analysis process is: By formula , calculate the minimum value ZJmin; through the formula , the calculated maximum value is close to the value ZJmax; Compare the minimum proximity value ZJmin and the maximum proximity value ZJmax with the corresponding proximity thresholds respectively; If the minimum approach value ZJmin and the maximum approach value ZJmax are both less than the approach threshold, a signal with a similar degree of correlation between advanced age and chronic disease impact is generated; Otherwise, signals of different degrees of association between advanced age and the impact of chronic diseases are generated.

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