Subjective experience multi-dimensional quantification and adaptability evaluation method, system and device for sports shoes

Abstract

The application provides a kind of subjective experience multidimensional quantification and adaptability evaluation method, system and device of sports shoes, it is related to sports shoes performance test technical field.Method includes: user wears test sports shoes and carries out sports test;On the symmetrical bipolar scale of each evaluation dimension, position mark is carried out, and mark point is obtained;The offset distance of mark point relative to the center of scale is measured, and deviation direction is retained;The deviation percentage of offset distance is calculated;The deviation percentage of each evaluation dimension is weighted and summed to obtain the comprehensive experience result;Based on the adaptation classification, the adaptation level of the comprehensive experience result is determined;Fusion individual characteristics of user, construct adaptability prediction model, calculate individual adaptability deviation score;Combined with the objective performance test score of sports shoes, the final evaluation model is constructed.The scheme unifies different dimension performance indexes to the dimension that can be weighted and fused, and provides a reliable statistical basis for the comprehensive judgment of sports shoes adaptability, which is significantly better than the traditional scoring system.

Description

Technical Field

[0001] This invention relates to the field of athletic shoe performance testing technology, and in particular to a method, system, and apparatus for multi-dimensional quantification of subjective experience and suitability evaluation of athletic shoes. Background Technology

[0002] Currently, with the rapid development of athletic shoe materials, structures, and processes, the performance differences in cushioning, stability, and propulsion efficiency among athletic shoes have increased significantly. To guide users in shoe selection and assist manufacturers in product development, the industry commonly uses the following types of athletic shoe evaluation methods: (1) Subjective scoring method: Researchers or users can give ratings such as "poor-average-excellent" or Likert scores based on their experience.

[0003] Defects: The ratings are discrete, the semantics of the intervals are inconsistent, and there are large differences in user understanding, making it difficult to quantify and compare.

[0004] (2) Single-dimensional experience evaluation syntax: Record specific performance sensations through descriptive methods, such as "too soft" or "too hard".

[0005] Limitations: lack of bias, lack of additivity, and inability to aggregate multiple dimensions.

[0006] (3) Purely objective testing method: For example, instrument measurement results such as base hardness, bending stiffness, and deformation.

[0007] Limitations: It cannot reflect the differences in subjective comfort among different users and does not support personalized shoe recommendations.

[0008] (4) Static adaptation method: Some researchers have proposed methods such as "foot type matching" and "landing method matching".

[0009] Drawback: It only matches static biometrics, which is disconnected from the dynamic running experience.

[0010] In summary, the existing technology has the following shortcomings: 1. Lack of a unified quantitative method: subjective expressions are scattered, data are incomparable and lack statistical value.

[0011] 2. Cannot indicate the direction of deviation: It only reflects the degree of good or bad, and cannot indicate the direction of performance differences such as being too hard / too soft, too stable / too poor (shaky).

[0012] 3. Inability to integrate multi-dimensional performance information: Inconsistent indicator dimensions prevent the formation of comprehensive evaluation results.

[0013] 4. Does not support personalized user adaptation: It cannot combine features such as weight, foot type, and running posture, so the recommendation results are unreliable.

[0014] 5. Inability to connect objective and subjective data: The separation between instrument testing and subjective experience makes it difficult to build an intelligent evaluation system. Summary of the Invention

[0015] The purpose of this invention is to provide a method, system, and apparatus for multi-dimensional quantification of subjective experience and suitability evaluation of sports shoes, so as to solve at least one of the above-mentioned technical problems existing in the prior art.

[0016] Firstly, to address the aforementioned technical problems, this invention provides a method for multi-dimensional quantification of subjective experience and suitability evaluation of athletic shoes, comprising the following steps: Step 1: The user wears the test shoes to conduct the exercise test.

[0017] In one feasible implementation, the exercise test is running.

[0018] Step 2: Based on their own experience with the performance of the athletic shoes, users mark their positions on a symmetrical bipolar scale for each evaluation dimension to obtain the marked points.

[0019] In one feasible implementation, the evaluation dimensions include at least four dimensions selected from forefoot feel, heel feel, forefoot cushioning, heel cushioning, acceleration feel, and stability.

[0020] In one feasible implementation, the center of the scale for both the forefoot and heel sensations is the point of maximum comfort, one pole (end) of the scale indicates that the sole is too hard, and the other pole (end) indicates that the sole is too soft. The center of the scale for both the forefoot and heel cushioning is where the most comfortable feeling is felt, one end of the scale indicates that the sole is overly shock-absorbing, and the other end indicates that the sole is underly shock-absorbing. The center of the speed-up scale is where the feeling is most comfortable, one end of the scale is where the speed-up feels sluggish, and the other end of the scale is where the speed-up feels excessive. The center of the stability scale is where the feeling is most comfortable, one end of the scale is where the sole feels too stable, and the other end of the scale is where the sole feels too wobbly (poor).

[0021] Step 3: Measure the offset distance (in cm) of the marker point relative to the center of the scale on each evaluation dimension, and retain the direction of the deviation.

[0022] Step 4: Calculate the percentage deviation of the offset distance for each evaluation dimension.

[0023] In one feasible implementation, the specific formula for the deviation percentage is: ; in, Indicates the first Offset distance in each dimension; This indicates the length of half a ruler, for example, 5cm; Indicates the first The percentage deviation in each dimension.

[0024] Step 5: Weight the percentage deviations of each evaluation dimension and sum them to obtain the overall experience result.

[0025] In one feasible implementation, the specific formula for the weighted summation is: ; in, This indicates the overall experience result; Indicates the total number of evaluation dimensions; Indicates the first Weights for each dimension.

[0026] Step 6: Based on the adaptation level, determine the adaptation level of the overall experience results.

[0027] In one feasible implementation, the adaptation hierarchy includes: When the summation result is in the range of (0%, 20%), the fit level is excellent, which means that the sports shoes have high fit. When the summation result is in the range of (20%, 40%), the fit level is good, which means that the sports shoes have high fit and can be selected. When the summation result is in the range of (40%, 60%), the fit level is medium, which means that the athletic shoes have obvious performance deviations. When the summation result is greater than 60%, the fit level is poor, which means that the athletic shoes have low fit and are not recommended.

[0028] Step 7: Combine the overall experience results and the deviation direction labels of each evaluation dimension with the user's individual characteristics to build an adaptability prediction model, calculate the individual adaptability deviation score and generate a directional interpretation (which can be based on preset directional interpretation rules).

[0029] In one feasible implementation, the specific formula of the adaptability prediction model includes: ; in, Indicates the individual fit bias score; Indicates the weight of the overall experience result; Represents the weight of individual features; Indicates the first Individual characteristics, such as weight, speed, landing style, and foot type; This represents the total number of individual characteristics.

[0030] Step 8: Based on the individual fit deviation score and combined with the objective performance test score of the sports shoe, construct the final evaluation model and calculate the final score.

[0031] In one feasible implementation, the specific formula for the final evaluation model shown includes: ; in, This indicates the final score; This indicates the fusion weight, which can be dynamically adjusted according to the test scenario; Normalized values ​​representing objective performance test scores (e.g., midsole hardness, longitudinal flexural stiffness, etc. of athletic shoes).

[0032] In one feasible implementation, the method for multidimensional quantification and suitability evaluation of subjective experience of sports shoes further includes step 9, which, based on the final score, suitability level and directional interpretation, obtains recommended application scenarios and final evaluation conclusions according to preset recommendation rules.

[0033] Secondly, based on the same inventive concept, this application also provides a multi-dimensional quantitative and adaptability evaluation system for subjective experience of sports shoes, including a data acquisition module, a data processing module and a result generation module; The data acquisition module is used to collect the user's marker points on the symmetrical bipolar scale of each evaluation dimension, the user's individual characteristics, and the objective performance test scores of the sports shoes; The data processing module includes a deviation percentage unit, a comprehensive experience result unit, a level determination unit, an adaptability prediction unit, and a final scoring unit. The deviation percentage unit is used to measure the offset distance of the marker point relative to the center of the scale in each evaluation dimension, and calculate the deviation percentage of the offset distance after retaining the deviation direction. The comprehensive experience result unit is used to perform a weighted summation of the deviation percentages of each evaluation dimension to obtain the comprehensive experience result. The level determination unit is used to determine the adaptation level of the overall experience result based on the adaptation level. The adaptability prediction unit integrates the comprehensive experience results and the deviation direction labels of each evaluation dimension, merges the user's individual characteristics, constructs an adaptability prediction model, calculates the individual adaptability deviation score, and generates a directional interpretation. The final scoring unit is used to construct a final evaluation model and calculate the final score based on the individual fit deviation score and the objective performance test score of the sports shoe. The result generation module is used to send out the processing results of the final scoring unit.

[0034] In one feasible implementation, the final scoring unit further includes obtaining recommended application scenarios and final evaluation conclusions based on the final score, adaptation level, and directional interpretation, according to preset recommendation rules.

[0035] Thirdly, based on the same inventive concept, this application also provides a device for multi-dimensional quantification and fit evaluation of subjective experience of sports shoes, including a processor, a memory and a bus. The memory stores instructions and data that can be read by the processor. The processor is used to call the instructions and data in the memory to execute the multi-dimensional quantification and fit evaluation method of subjective experience of sports shoes as described above. The bus connects the functional components for transmitting information.

[0036] In one feasible implementation, the evaluation device further includes individual feature acquisition equipment, including a weighing scale, a speedometer, a motion capture and motion analysis system, etc. The scale is used to measure the user's weight; The speedometer is used to measure the user's speed; The motion capture and motion analysis system is used to collect and classify the user's motion postures.

[0037] In one feasible implementation, the evaluation device further includes sports shoe performance testing equipment, including a hardness tester, a stiffness tester, etc.

[0038] In one feasible implementation, the evaluation device further includes a visual recognition device for identifying the marked points on the symmetrical bipolar scale and automatically calculating the percentage of deviation.

[0039] By adopting the above technical solution, the present invention has the following beneficial effects: This invention provides a method, system, and device for multi-dimensional quantification and suitability evaluation of subjective experience in athletic shoes. It proposes a deviation percentage model, giving subjective feelings a dual attribute of "degree + direction," overcoming the lack of directionality in existing subjective evaluations and providing a concrete basis for structural parameter adjustment. It unifies performance indicators from different dimensions into a weighted and fusionable dimension, providing a reliable statistical basis for comprehensive judgment of athletic shoe suitability, significantly outperforming traditional scoring systems. It incorporates user characteristics such as weight, foot type, and running posture into the evaluation system, enabling the same pair of athletic shoes to output different suitability results for different people, achieving precise recommendations. It links the physical performance test indicators of athletic shoes with user experience data, balancing scientific rigor and user experience, enhancing the credibility of conclusions. Furthermore, it can directly provide suitability levels and application scenario suggestions, improving the practical usability of the scientific evaluation system on both the user and R&D ends. Attached Figure Description

[0040] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0041] Figure 1 This is a flowchart of a method for multi-dimensional quantification and fit evaluation of subjective experience of sports shoes provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a symmetrical bipolar scale provided in an embodiment of the present invention; Figure 3 A schematic diagram of the forefoot cushioning markers provided in an embodiment of the present invention; Figure 4 This is a diagram illustrating a multi-dimensional quantitative and adaptability evaluation system for subjective experience of athletic shoes, provided as an embodiment of the present invention. Detailed Implementation

[0042] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0044] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0045] The present invention will be further explained below with reference to specific embodiments.

[0046] It should also be noted that the specific embodiments or implementation methods described below are a series of optimized settings listed by the present invention to further explain the specific content of the invention, and these settings can be combined or used in conjunction with each other.

[0047] Example 1: like Figure 1 As shown in the figure, this embodiment provides a method for multi-dimensional quantification of subjective experience and suitability evaluation of sports shoes, which includes the following steps: Step 1: The user wears the test shoes to conduct the exercise test.

[0048] Furthermore, the user has a normal foot arch and weighs 70 kg; the user's running level is a daily training pace of 5 min / km.

[0049] Furthermore, the exercise test is a running exercise; the running speed is 10km / h and the duration is 3 minutes, in order to form a stable subjective experience.

[0050] Step 2: Based on their own experience with the performance of the athletic shoes, users mark their positions on a symmetrical bipolar scale for each evaluation dimension to obtain the marked points.

[0051] Furthermore, such as Figure 2 As shown, the evaluation dimensions include forefoot cushioning, heel cushioning, acceleration feel, and stability.

[0052] Furthermore, the center of the scale for both the forefoot cushioning and the heel cushioning is the point of maximum comfort, one end of the scale indicates excessive shock absorption by the sole, and the other end indicates insufficient shock absorption by the sole. The center of the speed-up scale is where the feeling is most comfortable, one end of the scale is where the speed-up feels sluggish, and the other end of the scale is where the speed-up feels excessive. The center of the stability scale is where the feeling is most comfortable, one end of the scale is where the sole feels too stable, and the other end of the scale is where the sole feels too wobbly (poor).

[0053] Step 3: Measure the offset distance (in cm) of the marker point relative to the center of the scale on each evaluation dimension, and retain the direction of the deviation; For example, such as Figure 3 As shown, the forefoot cushioning is biased 2cm towards the shock absorption direction of the sole; This approach not only facilitates subsequent diagnosis of specific performance deviations, distinguishing between different issues such as "too stiff / too soft," "too shock-prone / too cushioned," "sluggish / too aggressive," and "too stable / too shaky," thus improving the interpretability of the results; it also provides directional label input for subsequent adaptability prediction models, enabling individualized adaptation (users with different weights, running postures, and landing methods have different tolerances for the same directional deviation); it further facilitates the setting of recommendation rules to reasonably recommend the application scenarios of athletic shoes. For example, athletic shoes that are biased towards "too stable, moderate cushioning" can be recommended for daily training, while athletic shoes that are biased towards "too aggressive acceleration, insufficient cushioning" can be recommended for racing or short-distance training; it also provides directional guidance for the design and adjustment of parameters such as midsole hardness, cushioning materials, flexural stiffness, and stability structure.

[0054] Step 4: Calculate the percentage deviation of the offset distance for each evaluation dimension.

[0055] Furthermore, the specific formula for the percentage deviation is as follows: ; in, Indicates the first Offset distance in each dimension; This indicates the length of half a ruler, for example, 5cm; Indicates the first Percentage deviation in each dimension; For example, calculations can yield The deviation direction label is: biased towards excessive shock absorption of the shoe sole.

[0056] Step 5: Weight the percentage deviations of each evaluation dimension and sum them to obtain the overall experience result.

[0057] Furthermore, the specific formula for weighted summation is as follows: ; in, This indicates the overall experience result; Indicates the total number of evaluation dimensions; Indicates the first Weights of each dimension; For example, when the percentage of deviation and weight of each evaluation dimension are as shown in Table 1, The calculated result is 23%.

[0058] Table 1

[0059] Step 6: Based on the adaptation level, determine the adaptation level of the overall experience results.

[0060] Furthermore, the adaptation hierarchy includes: When the summation result is in the range of (0%, 20%), the fit level is excellent, which means that the sports shoes have high fit. When the summation result is in the range of (20%, 40%), the fit level is good, which means that the sports shoes have high fit and can be selected. When the summation result is in the range of (40%, 60%), the fit level is medium, which means that the athletic shoes have obvious performance deviations. When the summation result is greater than 60%, the fit level is poor, which means that the athletic shoes have low fit and are not recommended. For example, when When the value is 23%, the adaptation level is good.

[0061] Step 7: Combine the overall experience results and the deviation direction labels of each evaluation dimension with the user's individual characteristics to build an adaptability prediction model, calculate the individual adaptability deviation score and generate a directional interpretation (which can be based on preset directional interpretation rules).

[0062] Furthermore, the specific formula of the adaptability prediction model includes: ; in, Indicates the individual fit bias score; Indicates the weight of the overall experience result; Represents the weight of individual features; Indicates the first Individual characteristics can be defined as the percentage deviation of individual parameter values ​​such as weight, speed, landing style, and foot type from reference values ​​or database averages (including the direction of deviation, i.e., positive when greater than the reference value and negative when less than the reference value), which can be used as specific characteristic values. Represents the total number of individual characteristics; For example, when The value is 0.7 (meaning a greater emphasis on user experience). When the value is 23%, The value is 1 (taking user weight as an example only). The value is 0.3 (meaning that body weight has a significant impact on cushioning deviation). When the value is 10% (meaning the deviation between a user's weight of 77kg and the reference weight of 70kg is +10%, implying that a heavier user requires firmer cushioning), then... Meanwhile, based on the directional interpretation rule of increasing forefoot cushioning when the user's weight is greater than the reference weight, we obtain the directional interpretation of the increased demand for forefoot cushioning.

[0063] Step 8: Based on the individual fit deviation score and combined with the objective performance test score of the sports shoe, construct the final evaluation model and calculate the final score.

[0064] Furthermore, the specific formulas for the final evaluation model shown include: ; in, This indicates the final score; This indicates the fusion weight, which can be dynamically adjusted according to the test scenario; Normalized values ​​representing objective performance test scores (e.g., midsole stiffness, longitudinal flexural stiffness, etc. of athletic shoes). For example, when The value is 30%. If the value is 0.6, then: .

[0065] Furthermore, it also includes step 9, which, based on the final score, fit level, and directional interpretation, obtains recommended application scenarios and final evaluation conclusions (e.g., as daily training shoes) according to preset recommendation rules.

[0066] For example, the final evaluation conclusions are shown in Table 2.

[0067] Table 2

[0068] Furthermore, to verify the actual effectiveness of this evaluation method, 12 users with different running postures and running levels were selected to conduct a blind test on three types of sports shoes.

[0069] The test results are shown in Table 3 after users evaluated the results using both the traditional Likert subjective rating method and this evaluation method.

[0070] Table 3

[0071] Among them, the self-repeated difference of the same user refers to the average absolute deviation or standard deviation of the evaluation result relative to the mean of the evaluation results after the same user has repeatedly evaluated the same type of sports shoe under the same test conditions. For example, if the same user, the same type of sports shoe, and the same evaluation dimension are evaluated three times, the average absolute deviation of the deviation percentage of each evaluation relative to the mean can be calculated. The same calculation can also be performed on the final comprehensive experience result.

[0072] The significance of inter-group comparison refers to the differentiation between different types of athletic shoes or different user groups. If multiple athletic shoes are tested within the same user group, paired t-tests, repeated measures ANOVA, or Friedman's test can be used. If different user groups are being compared, independent samples t-tests, one-way ANOVA, or corresponding nonparametric tests can be used, and the significance level can be set to p < 0.05.

[0073] Data aggregation applicability refers to whether the various evaluation dimensions can be reasonably weighted and integrated. This evaluation method uniformly converts different evaluation dimensions into percentage deviations, and the sum of the weights of each dimension is 1, thus allowing for weighted aggregation. Furthermore, the stability of the aggregation results can be verified through repeated testing of the coefficient of variation, intragroup correlation coefficient, or internal consistency coefficient.

[0074] Correlation with objective performance test indicators refers to the process of normalizing objective performance test indicators such as midsole hardness, compressive deformation, rebound rate, longitudinal flexural stiffness, torsional stiffness, peak plantar pressure, or impact loading rate to form an objective performance test score. This score is then correlated with the overall experience results, individual fit deviation scores, or the final score through correlation analysis or linear regression to obtain the correlation coefficient r and the coefficient of determination. .

[0075] Example 2: like Figure 4 As shown, this embodiment provides a multi-dimensional quantitative and adaptability evaluation system for subjective experience of sports shoes, including a data acquisition module, a data processing module, and a result generation module; The data acquisition module is used to collect the user's marker points on the symmetrical bipolar scale of each evaluation dimension, the user's individual characteristics, and the objective performance test scores of the sports shoes; The data processing module includes a deviation percentage unit, a comprehensive experience result unit, a level determination unit, an adaptability prediction unit, and a final scoring unit. The deviation percentage unit is used to measure the offset distance of the marker point relative to the center of the scale in each evaluation dimension, and calculate the deviation percentage of the offset distance after retaining the deviation direction. The comprehensive experience result unit is used to perform a weighted summation of the deviation percentages of each evaluation dimension to obtain the comprehensive experience result. The level determination unit is used to determine the adaptation level of the overall experience result based on the adaptation level. The adaptability prediction unit integrates the comprehensive experience results and the deviation direction labels of each evaluation dimension, merges the user's individual characteristics, constructs an adaptability prediction model, calculates the individual adaptability deviation score, and generates a directional interpretation. The final scoring unit is used to construct a final evaluation model and calculate the final score based on the individual fit deviation score and the objective performance test score of the sports shoe. The result generation module is used to send out the processing results of the final scoring unit.

[0076] Furthermore, the final scoring unit also includes obtaining recommended application scenarios and final evaluation conclusions based on the final score, adaptation level, and directional interpretation, in accordance with preset recommendation rules.

[0077] Example 3: This embodiment provides a device for multi-dimensional quantification and suitability evaluation of subjective experience of sports shoes, including a processor, a memory, and a bus. The memory stores instructions and data that can be read by the processor. The processor is used to call the instructions and data in the memory to execute the multi-dimensional quantification and suitability evaluation method of subjective experience of sports shoes as described above. The bus connects the various functional components for transmitting information.

[0078] Furthermore, the evaluation device also includes individual feature acquisition equipment, including a weighing scale, a speedometer, a motion capture and motion analysis system, etc. The scale is used to measure the user's weight; The speedometer is used to measure the user's speed; The motion capture and motion analysis system is used to collect and classify the user's motion postures.

[0079] Furthermore, the evaluation device also includes sports shoe performance testing equipment, including a hardness tester, a stiffness tester, etc.

[0080] In another embodiment, this solution can also be implemented using an integrated device, which may include corresponding modules that perform one or more steps in the various embodiments described above. A module may be one or more hardware modules specifically configured to perform the corresponding step, or implemented by a processor configured to perform the corresponding step, or stored in a computer-readable medium for implementation by a processor, or implemented through some combination thereof.

[0081] The processor executes the various methods and processes described above. For example, the method implementations in this scheme can be implemented as software programs tangibly contained in a machine-readable medium, such as memory. In some implementations, part or all of the software program can be loaded and / or installed via memory and / or a communication interface. When the software program is loaded into memory and executed by the processor, one or more steps of the methods described above can be performed. Alternatively, in other implementations, the processor can be configured to execute one of the methods described above by any other suitable means (e.g., by means of firmware).

[0082] This device can be implemented using a bus architecture. A bus architecture can include any number of interconnect buses and bridges, depending on the specific application of the hardware and overall design constraints. The bus connects various circuits, including one or more processors, memory, and / or hardware modules. The bus can also connect various other circuits such as peripherals, voltage regulators, power management circuitry, external antennas, etc.

[0083] Buses can be Industry Standard Architecture (ISA) buses, Peripheral Component Interconnect (PCI) buses, or Extended Industry Standard Component (EISA) buses, etc. Buses can be divided into address buses, data buses, control buses, etc.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for multi-dimensional quantification of subjective experience and suitability evaluation of athletic shoes, characterized in that, include: Step 1: The user wears the test shoes to conduct the exercise test; Step 2: Based on their own experience with the performance of the athletic shoes, users mark the positions on the symmetrical bipolar scale of each evaluation dimension to obtain the marked points; Step 3: Measure the offset distance of the marker point relative to the center of the scale in each evaluation dimension, and retain the direction of the deviation; Step 4: Calculate the percentage deviation of the offset distance for each evaluation dimension; Step 5: Calculate the weighted sum of the deviation percentages for each evaluation dimension to obtain the overall experience result; Step 6: Based on the adaptation level, determine the adaptation level of the overall experience results; Step 7: Combine the overall experience results and the deviation direction labels of each evaluation dimension with the user's individual characteristics to build an adaptability prediction model, calculate the individual adaptability deviation score and generate directional interpretations; Step 8: Based on the individual fit deviation score and combined with the objective performance test score of the sports shoe, construct the final evaluation model and calculate the final score.

2. The evaluation method according to claim 1, characterized in that, The exercise test was a running exercise.

3. The evaluation method according to claim 1, characterized in that, The evaluation dimensions include at least four of the following: forefoot feel, heel feel, forefoot cushioning, heel cushioning, acceleration feel, and stability.

4. The evaluation method according to claim 3, characterized in that, The center of the scale for both forefoot and heel feel is the most comfortable position, one end of the scale indicates the sole is too hard, and the other end indicates the sole is too soft. The center of the scale for both forefoot and heel cushioning is the most comfortable position, one end of the scale is the feeling of excessive shock absorption by the sole, and the other end of the scale is the feeling of insufficient shock absorption by the sole. The center of the speed acceleration scale is where the feeling is most comfortable, one extreme of the scale feels like sluggish acceleration, and the other extreme of the scale feels like excessive acceleration. The center of the stability scale is where the feeling is most comfortable; one extreme of the scale feels like the sole is too stable, while the other extreme feels like the sole is too wobbly.

5. The evaluation method according to claim 1, characterized in that, The specific formula for the percentage deviation is: ； in, Indicates the first Offset distance in each dimension; Indicates half the scale length; Indicates the first The percentage deviation in each dimension.

6. The evaluation method according to claim 5, characterized in that, The specific formula for weighted summation is: ； in, This indicates the overall experience result; Indicates the total number of evaluation dimensions; Indicates the first Weights for each dimension.

7. The evaluation method according to claim 6, characterized in that, The specific formulas of the adaptability prediction model include: ； in, Indicates the individual fit bias score; Indicates the weight of the overall experience result; Represents the weight of individual features; Indicates the first Individual characteristics; This represents the total number of individual characteristics.

8. The evaluation method according to claim 7, characterized in that, The specific formulas for the final evaluation model shown include: ； in, This indicates the final score; Indicates the fusion weights; This represents the normalized value of the objective performance test score.

9. A multi-dimensional quantitative and adaptability evaluation system for subjective experience of athletic shoes, characterized in that, It includes a data acquisition module, a data processing module, and a result generation module; The data acquisition module is used to collect the user's marker points on the symmetrical bipolar scale of each evaluation dimension, the user's individual characteristics, and the objective performance test scores of the sports shoes; The data processing module includes a deviation percentage unit, a comprehensive experience result unit, a level determination unit, an adaptability prediction unit, and a final scoring unit. The deviation percentage unit is used to measure the offset distance of the marker point relative to the center of the scale in each evaluation dimension, and calculate the deviation percentage of the offset distance after retaining the deviation direction. The comprehensive experience result unit is used to perform a weighted summation of the deviation percentages of each evaluation dimension to obtain the comprehensive experience result. The level determination unit is used to determine the adaptation level of the overall experience result based on the adaptation level. The adaptability prediction unit integrates the comprehensive experience results and the deviation direction labels of each evaluation dimension, merges the user's individual characteristics, constructs an adaptability prediction model, calculates the individual adaptability deviation score, and generates a directional interpretation. The final scoring unit is used to construct a final evaluation model and calculate the final score based on the individual fit deviation score and the objective performance test score of the sports shoe. The result generation module is used to send out the processing results of the final scoring unit.

10. A device for multi-dimensional quantification and suitability evaluation of subjective experience in athletic shoes, characterized in that, It includes a processor, a memory, and a bus. The memory stores instructions and data read by the processor. The processor is used to call the instructions and data in the memory to execute the evaluation method as described in any one of claims 1 to 8. The bus connects the functional components for transmitting information.

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