A bipedal balance testing system and method, computer storage medium

By correcting and filtering the pressure difference between the animal's two feet, and combining visual detection and a pain level rating scale, an accurate pain value dataset is generated, which solves the problem of inaccurate pain value measurement in existing technologies and achieves higher testing accuracy and stability.

CN121890980BActive Publication Date: 2026-06-16SICHUAN GREENTECH BIOTECHNOLOGY CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SICHUAN GREENTECH BIOTECHNOLOGY CO LTD
Filing Date
2026-03-25
Publication Date
2026-06-16

AI Technical Summary

Technical Problem

In existing technologies, the method of measuring pain values ​​based on the pressure difference between the animal's two feet after applying a standard pain stimulus has poor accuracy and is greatly affected by the randomness of the animal.

Method used

By acquiring the pressure difference between the animal's two feet, applying pain stimuli, correcting and filtering the data, using visual detection equipment to correct the data, and combining it with a pain level rating scale, an accurate pain value data set is generated, and a computer program is used to implement the bipedal balance test.

🎯Benefits of technology

This improved the accuracy and stability of pain value measurement, reduced measurement errors caused by animal randomness, and ensured the reliability of test results.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application provides a biped balance test system and method, and a computer storage medium, and relates to the technical field of balance test. The biped balance test method comprises the following steps: placing an animal in a test environment, obtaining a plurality of biped pressure difference values in a first preset time period after the animal adapts to the test environment, and obtaining a difference value range; applying a painful stimulus to the animal's biped; obtaining a first data group comprising a plurality of biped pressure difference values in a second preset time period; correcting the plurality of biped pressure difference values to obtain a corrected data group; obtaining a corresponding first pain value data group based on the corrected data group, and then obtaining an actual pain value based on the first pain value data group. The biped balance test method provided in the application embodiment can make the obtained biped pressure difference values more suitable for the case of being subjected to a painful stimulus after correction, can reduce the randomness of the animal, and can make the finally obtained actual pain value more accurate.
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Description

Technical Field

[0001] This application relates to the field of balance testing technology, specifically to a bipedal balance testing system and method, and a computer storage medium. Background Technology

[0002] The bipedal balance tester can be used to screen analgesics and anti-inflammatory drugs by obtaining the weight-bearing pressure difference between the two feet when an animal experiences pain in a single limb. It can also be used to diagnose diseases of the limbs in animals, such as joint inflammation and ligament damage, which are not visible to the naked eye.

[0003] Currently, the main method is to apply a standard pain stimulus and then look up the pressure difference between the animal's two feet in a reference table to obtain the actual pain value. However, due to the randomness of the animals, the accuracy of this method is poor. Summary of the Invention

[0004] The present application provides a bipedal balance testing system and method, as well as a computer storage medium, which can effectively improve the accuracy of measurement results.

[0005] The specific technical solution of this embodiment is as follows:

[0006] On one hand, embodiments of this application provide a bipedal balance test method, including the following steps:

[0007] S10. After the animal is in place, obtain multiple pressure differences between the two feet within the first preset time period to obtain the difference range (a1, a2).

[0008] S20. Apply pain stimulation to both feet of the animal;

[0009] S30. Obtain a first data set B={b1,b2,...,bn} including multiple bipedal pressure differences within a second preset time period;

[0010] S40. Correct multiple bipedal pressure difference values ​​to obtain a corrected data set;

[0011] S401. Obtain the bipedal pressure difference values ​​greater than or equal to a2 in the first data set to obtain the second data set C={c1,c2,...,cm};

[0012] S402. Based on the second data set, obtain the third data set D=C-a1={c1-a1,c2-a1,...,cm-a1}, and add the data in the third data set to the correction data set;

[0013] S50. Based on the corrected data set, obtain the corresponding first pain value data set, and then based on the first pain value data set, obtain the actual pain value.

[0014] In some embodiments, after obtaining the second data set and before obtaining the corresponding first pain value data set based on the corrected data set, the following steps are also included:

[0015] S403. Determine whether the amount of data in the second data group exceeds the first preset quantity;

[0016] S404. If it is determined that the amount of data in the second data group exceeds the first preset quantity, then proceed to step S50.

[0017] S405. When it is determined that the amount of data in the second data does not exceed the first preset quantity, obtain the bipedal pressure difference value in the first data group that is greater than a1 and less than a2, and obtain the fourth data group E={e1,e2,...ei}.

[0018] S406. Based on the fourth data set, obtain the fifth data set F=E-a1={e1-a1,e2-a1,...,ei-a1}, and add the data in the fifth data set to the correction data set.

[0019] In some embodiments, obtaining a corresponding first pain value data set based on the corrected data set, and then obtaining the actual pain value based on the first pain value data set, includes the following steps:

[0020] S501. Based on the third data group, obtain the corresponding first pain value data group, and then obtain the specific first pain value;

[0021] S502. Based on the fifth data group, obtain the corresponding first pain value data group, and then obtain the specific second pain value;

[0022] S503. Obtain the actual pain value = first pain value * z1 + second pain value * z2, where z1 is the first preset weight, z2 is the second preset weight, z1 + z2 = 1, z1 > z2.

[0023] In some embodiments, obtaining the actual pain value based on the first pain value data set includes the following steps:

[0024] The median of all data in the first pain value data group is used as the actual pain value.

[0025] In some embodiments, before obtaining the actual pain value based on the first pain value data set, the following steps are included:

[0026] T10. Obtain the degree of whitening of animal feet based on visual inspection equipment;

[0027] T20. Based on the degree of whitening of the animal's feet, the sixth data group was obtained; the data in the sixth data group corresponded one-to-one with the data in the first pain value data group, and the two corresponding data were obtained at the same time.

[0028] T30. Calculate the difference between the data in the sixth data group and the corresponding data in the first pain value data group;

[0029] T40. If the difference calculated in step T30 is greater than the first preset value, then the corresponding data in the first pain value data group will be deleted.

[0030] In some embodiments, the second preset time period is ≥ 2 * the first preset time period.

[0031] In some embodiments, obtaining the corresponding first pain value data set based on the modified data set includes the following steps:

[0032] K10: Compare each data value in the corrected data set with a preset pain level rating scale, which includes multiple pain intensity ranges and corresponding pressure differences.

[0033] K20: Map each data value to the pressure difference corresponding to its respective pain intensity range to generate the first pain value data group.

[0034] On the other hand, embodiments of this application provide a bipedal balance testing system, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement any of the bipedal balance testing methods described in the above embodiments.

[0035] This application also provides a computer storage medium storing a computer program, which is executed to implement the bipedal balance test method of any of the above embodiments.

[0036] Compared with the prior art, the embodiments of this application have the following beneficial effects:

[0037] The bipedal balance test method provided in this application embodiment can make the obtained bipedal pressure difference value more closely reflect the situation of pain stimulation after correction, which can reduce the poor accuracy of the measurement results due to the randomness of the animal, and thus make the final actual pain value more accurate. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1This is a flowchart illustrating a bipedal balance test method provided in some embodiments of this application;

[0040] Figure 2 This is a partial flowchart illustrating a bipedal balance test method provided in other embodiments of this application. Detailed Implementation

[0041] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0042] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are used only for the convenience of describing this application and 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, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0043] The use of "applies to" or "configured to" in this application implies open and inclusive language, which does not exclude the applicability to or configuration to devices performing additional tasks or steps. Additionally, the use of "based on" implies openness and inclusivity, because processes, steps, calculations, or other actions "based on" one or more of the stated conditions or values ​​may in practice be based on additional conditions or values ​​beyond those stated.

[0044] In this application, the term "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use this application. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be made without using these specific details. In other instances, well-known structures and processes are not described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0045] On the one hand, embodiments of this application provide a bipedal balance test method; please refer to [link to relevant documentation]. Figure 1 , Figure 1 This is a flowchart illustrating a bipedal balance test method provided in some embodiments of this application, including the following steps:

[0046] S10. After the animal is in place, obtain multiple pressure differences between the two feet within the first preset time period to obtain the difference range (a1, a2).

[0047] In S10, "animal placement" refers to placing the animal in the test environment and allowing it to adapt. Once the animal has adapted, it is considered "placed." Depending on the specific test content, the bipedal pressure difference can be either the pressure difference between the hind and front legs. The bipedal pressure difference is primarily determined by acquiring the pressure of both legs in the area where pressure sensors are installed, and then calculating the pressure difference. Within the first preset time period, multiple bipedal pressure differences will be obtained; the minimum value a1 and the maximum value a2 are primarily selected. "Multiple bipedal pressure differences" refers to at least two.

[0048] S20. Apply pain stimulation to the animal's feet.

[0049] In S20, the painful stimulus can be a von Frey wire measuring the mechanical pain threshold or a hot / cold plate measuring the temperature pain threshold.

[0050] S30. Obtain a first data set B={b1,b2,...,bn} that includes multiple bipedal pressure differences within a second preset time period.

[0051] In S30, depending on the specific circumstances, the first data set can be acquired either simultaneously with the application of the pain stimulus or immediately after the stimulus ends. The second preset time period can be the same length as the first preset time period, or they can be different lengths. When the second preset time period and the first preset time period are different lengths, the second preset time period can be longer or shorter than the first preset time period. The more bipedal pressure difference values ​​there are, i.e., the more data in the first data set, the more accurate the subsequent test results will be.

[0052] S40. Correct multiple bipedal pressure difference values ​​to obtain a corrected data set, which mainly includes the following steps:

[0053] S401. Obtain the bipedal pressure difference values ​​of the first data set that are greater than or equal to a2, and obtain the second data set C={c1,c2,...,cm}.

[0054] In S401, the second data group includes at least one data point. If the second data group is empty, the test process fails and no further steps are performed. Where m ≤ n.

[0055] S402. Based on the second data set, obtain the third data set D=C-a1={c1-a1,c2-a1,...,cm-a1}, and add the data in the third data set to the correction data set.

[0056] In S402, the third data group consists of each data point in the second data group minus the value of a1. The amount of data in the third data group is the same as that in the second data group. Before the data from the third data group is added to the correction data group, the correction data group can be empty or it can include data obtained through other means.

[0057] S50. Based on the corrected data set, obtain the corresponding first pain value data set, and then based on the first pain data set, obtain the actual pain value.

[0058] In S50, obtaining the corresponding first pain value data group based on the corrected data group means obtaining a first pain value data for each data point in the corrected data group. This process can be implemented using existing technologies. The amount of data in the first pain value data group is the same as the amount of data in the corrected data group. Obtaining the actual pain value based on the first pain data group means obtaining a relatively accurate pain value based on multiple pain data points. This process can be achieved by taking the median of multiple pain data points or by calculating the value by assigning weights to multiple different pain data points.

[0059] In the above embodiment, the state of the animal before the application of pain stimulus is first obtained to obtain the range of pressure difference between the two feet under normal conditions. Then, based on the range of pressure difference between the two feet under normal conditions, multiple data after the application of pain stimulus are filtered. Then, the filtered data is further corrected so that the data in the final corrected data set is more consistent with the data values ​​generated by the animal after the application of pain stimulus. Then, the actual pain value is obtained based on the corrected data set.

[0060] By setting up the above embodiments, the obtained pressure difference value of the two feet can be more closely related to the situation of being subjected to pain stimulation after correction, which can reduce the poor accuracy of the measurement results caused by the randomness of the animal, and thus make the final actual pain value more accurate.

[0061] In some embodiments, after obtaining the second data set in step S40 and before obtaining the corresponding first pain value data set based on the corrected data set in step S50, the following steps are also included:

[0062] S403. Determine whether the amount of data in the second data group exceeds the first preset quantity.

[0063] In S403, in order to obtain a certain number of first pain value data in the future, it is necessary to ensure that the corrected data set also meets a certain requirement.

[0064] S404. If it is determined that the amount of data in the second data group exceeds the first preset quantity, then proceed to step S50.

[0065] In S404, the subsequent S50 proceeds normally, that is, the data in the third data group is added to the correction data group, and then the corresponding first pain value data group is obtained based on the correction data group.

[0066] S405. When it is determined that the amount of data in the second data group does not exceed the first preset quantity, the pressure difference between the two feet that is greater than a1 and less than a2 in the first data is obtained, and the fourth data group E={e1,e2,...ei} is obtained.

[0067] In step S405, the fourth data set and the second data set are not necessarily related, where i≤n.

[0068] S406. Based on the fourth data set, obtain the fifth data set F=E-a1={e1-a1,e2-a1,...,ei-a1}, and add the data in the fifth data set to the correction data set.

[0069] In S406, the fifth data group is the data after subtracting the a1 value from each data in the fourth data group, and the amount of data in the fifth data group is the same as the amount of data in the fourth data group.

[0070] In the above embodiments, there is no necessary connection between steps S403-S406 and step S402. Step S402 may be performed before steps S403-S406, after steps S403-S406, or simultaneously.

[0071] With the settings of the above embodiments, if the amount of data in the second data group is small after obtaining the second data group, the amount of data in the first pain data group obtained subsequently will also be small. This may lead to a large deviation in the actual pain value obtained subsequently. In the above embodiments, by obtaining a fourth data group to increase the amount of data in the first pain data group, the deviation of the actual pain value obtained subsequently can be smaller, and the test results can be more accurate.

[0072] In some embodiments, in step S50, obtaining a corresponding first pain value data set based on the corrected data set, and then obtaining the actual pain value based on the first pain value data set, includes the following steps:

[0073] S501. Based on the third data group, obtain the corresponding first pain value data group, and then obtain the specific first pain value.

[0074] S502. Based on the fifth data group, obtain the corresponding first pain value data group, and then obtain the specific second pain value.

[0075] S503. Obtain the actual pain value = first pain value * z1 + second pain value * z2, where z1 is the first preset weight, z2 is the second preset weight, z1 + z2 = 1, z1 > z2.

[0076] In the above embodiments, because the amount of data in the third data group is relatively small, if the average value of the corrected data group, including the third and fifth data groups, is simply obtained when a fifth data group is introduced, although the deviation of the final actual pain value is reduced, a certain degree of bias will still occur. Therefore, by assigning a heavier weight to the more authoritative first pain value, the final actual pain value can be made more accurate.

[0077] In some other embodiments, in step S50, obtaining the actual pain value based on the first pain value data set includes the following steps:

[0078] The median of all data in the first pain value data group is used as the actual pain value.

[0079] By implementing the above-described embodiments, the calculation of actual pain values ​​can be made more robust and reliable by avoiding significant impact from individual abnormal data. This method of using the median as the actual pain value reduces errors caused by data fluctuations to a certain extent, improving the accuracy and stability of the measurement results.

[0080] Please see Figure 2 , Figure 2 This is a flowchart illustrating a bipedal balance testing method provided in some other embodiments of this application. In some of these embodiments, before obtaining the actual pain value based on the first pain value data set in step S50, the following steps are also included:

[0081] T10. Obtain the degree of whitening of animal feet based on visual inspection equipment.

[0082] T20. Based on the whitening of the animal's feet, the sixth data group was obtained; the data in the sixth data group corresponded one-to-one with the data in the first pain value data, and the two corresponding data were obtained at the same time.

[0083] In steps T10 and T20, while measuring the pressure difference between the animal's two feet using a pressure testing device, a second pain value is simultaneously acquired through a visual detection device for each pressure difference value. The acquisition times are the same. After filtering the pressure difference values, the data that is filtered out is deleted, so that the amount of data in the sixth data group, which includes multiple second pain value data, is the same as the amount of data in the first pain value data group, and they correspond one-to-one.

[0084] The sixth data set obtained through visual inspection equipment is an existing technology. The general process involves using the equipment to acquire images of an animal's feet, analyzing the color features of the feet in the images using image recognition technology, and converting the degree of paleness of the feet into corresponding pain value data based on a pre-defined correspondence between color and pain value. For example, a color database can be pre-established, where different color ranges correspond to different pain value intervals. After the visual inspection equipment acquires images of the animal's feet, it analyzes the range of colors within the images to determine the corresponding pain value data.

[0085] T30. Calculate the difference between the data in the sixth data group and the corresponding data in the first pain value data group.

[0086] In T30, the amount of data in the first pain value data group is the same as the amount of data in the sixth data group, so the amount of data for the difference between the two is also the same as the amount of data in the two data groups mentioned above.

[0087] T40. If the difference calculated in step T30 is greater than the first preset value, then the corresponding data in the first pain value data group will be deleted.

[0088] By using the above-described embodiments, a sixth data set is obtained from a conventional visual inspection device with relatively blurry test results. This sixth data set is then compared with the first pain value data set. Data with large deviations are further filtered, and then the actual pain value is obtained from the filtered first pain value data set. This approach makes the final actual pain value more accurate and improves the test results.

[0089] In some embodiments, the second preset time period is ≥ 2 * the first preset time period.

[0090] In the above embodiments, the length of the second preset time period is greater than or equal to twice the length of the first preset time period. On the one hand, this can make the length of the first preset time period shorter, thereby improving the efficiency of the entire test. On the other hand, it can make the amount of data in the first data set obtained after applying pain stimulation to the animal's feet more, which can better serve the subsequent screening and correction processes. In this way, the final actual pain value can be obtained through more data, resulting in higher test accuracy.

[0091] In some embodiments, step S50, obtaining the corresponding first pain value data set based on the corrected data set, includes the following steps:

[0092] K10: Compare each data value in the corrected data set with a preset pain level rating scale, which includes multiple pain intensity ranges and corresponding pressure differences.

[0093] K20: Map each data value to the pressure difference corresponding to its respective pain intensity range to generate the first pain value data group.

[0094] The above-described embodiments allow for the effective correlation between the data in the corrected data set and the pain level rating scale, transforming the data into meaningful pain pressure differences. This approach makes the abstract data in the corrected data set intuitive and understandable, facilitating subsequent calculations of actual pain values.

[0095] On the other hand, embodiments of this application provide a bipedal balance testing system, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the bipedal balance testing method of any of the above embodiments.

[0096] This application also provides a computer storage medium storing a computer program, which is executed to implement the bipedal balance test method of any of the above embodiments.

[0097] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for testing bipedal balance, characterized in that, Includes the following steps: S10. Place the animal in the test environment. After the animal adapts to the test environment, obtain multiple bipedal pressure differences within the first preset time period to obtain the difference range (a1, a2). S20. Apply pain stimulation to both feet of the animal; S30. Obtain a first data set B={b1,b2,...,bn} including multiple bipedal pressure differences within a second preset time period; S40. Correct multiple bipedal pressure difference values ​​to obtain a corrected data set; S401. Obtain the bipedal pressure difference values ​​greater than or equal to a2 in the first data set to obtain the second data set C={c1,c2,...,cm}; S402. Based on the second data set, obtain the third data set D=C-a1={c1-a1,c2-a1,...,cm-a1}, and add the data in the third data set to the correction data set; S50. Based on the corrected data set, obtain the corresponding first pain value data set, and then based on the first pain value data set, obtain the actual pain value.

2. The bipedal balance test method as described in claim 1, characterized in that, After obtaining the second data set, and before obtaining the corresponding first pain value data set based on the corrected data set, the following steps are also included: S403. Determine whether the amount of data in the second data group exceeds the first preset quantity; S404. If it is determined that the amount of data in the second data group exceeds the first preset quantity, then proceed to step S50. S405. When it is determined that the amount of data in the second data does not exceed the first preset quantity, obtain the bipedal pressure difference value in the first data group that is greater than a1 and less than a2, and obtain the fourth data group E={e1,e2,...ei}. S406. Based on the fourth data set, obtain the fifth data set F=E-a1={e1-a1,e2-a1,...,ei-a1}, and add the data in the fifth data set to the correction data set.

3. The bipedal balance test method as described in claim 2, characterized in that, Based on the corrected data set, the corresponding first pain value data set is obtained. Then, based on the first pain value data set, the actual pain value is obtained, including the following steps: S501. Based on the third data group, obtain the corresponding first pain value data group, and then obtain the specific first pain value; S502. Based on the fifth data group, obtain the corresponding first pain value data group, and then obtain the specific second pain value; S503. Obtain the actual pain value = first pain value * z1 + second pain value * z2, where z1 is the first preset weight, z2 is the second preset weight, z1 + z2 = 1, z1 > z2.

4. The bipedal balance test method as described in claim 1, characterized in that, The actual pain value is obtained based on the first pain value data set through the following steps: The median of all data in the first pain value data group is used as the actual pain value.

5. The bipedal balance test method as described in any one of claims 1-4, characterized in that, Before obtaining the actual pain value based on the first pain value data set, the following steps are also included: T10. Obtain the degree of whitening of animal feet based on visual inspection equipment; T20. Based on the degree of whitening of the animal's feet, the sixth data group was obtained; the data in the sixth data group corresponded one-to-one with the data in the first pain value data group, and the two corresponding data were obtained at the same time. T30. Calculate the difference between the data in the sixth data group and the corresponding data in the first pain value data group; T40. If the difference calculated in step T30 is greater than the first preset value, then the corresponding data in the first pain value data group will be deleted.

6. The bipedal balance test method as described in any one of claims 1-4, characterized in that, The second preset time period is greater than or equal to 2 * the first preset time period.

7. The bipedal balance test method according to any one of claims 1-4, characterized in that, Based on the corrected data set, the corresponding first pain value data set is obtained through the following steps: K10: Compare each data value in the corrected data set with a preset pain level rating scale, which includes multiple pain intensity ranges and corresponding pressure differences. K20: Map each data value to the pressure difference corresponding to its respective pain intensity range to generate the first pain value data group.

8. A bipedal balance testing system, characterized in that, The device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the bipedal balance test method according to any one of claims 1-7.

9. A computer storage medium, characterized in that, It contains a computer program that is executed to implement the bipedal balance test method according to any one of claims 1-7.