Mouse running wheel and running wheel movement quantitative analysis method and system

Abstract

The invention discloses a mouse running wheel and a running wheel motion quantitative analysis method and system. The mouse running wheel comprises a running wheel body and a support, wherein the running wheel body is used for accommodating a mouse to run; the support is used for supporting the running wheel body; the axes of the two ends of the running wheel body are connected with the support through short shafts respectively, so that the running wheel body can rotate on the support along the axis of the running wheel body. And the sensor mounting seat is arranged on the short shaft, and is used for mounting an angular velocity sensor to sense the rotation of the short shaft. According to the mouse running wheel with the structure, the short shaft and the support are connected with the running wheel body, a traditional long shaft design is replaced, sufficient space is reserved in the running wheel, movement of a mouse is prevented from being hindered, the mouse can move freely, and the movement state is displayed more truly.

Description

Technical Field

[0001] The present invention belongs to the technical field of behavioral research, and particularly relates to a mouse running wheel, a method and a system for quantitatively analyzing running wheel movement. Background Art

[0002] In the fields of life science and medical research, the study of mouse movement behavior is of great significance. For example, in the study of mouse physiological functions, drug responses, and exercise-related disease models, mouse movement data can provide key information for researchers.

[0003] In the study of mouse movement, the mouse cage is the basic environment for mice to live and move, and its structural design has an important impact on the movement performance of mice and data collection. The structure of traditional mouse cages is usually relatively simple. As the main exercise facility for mice, the installation method and structure of the running wheel have certain limitations. For example, traditional running wheels mostly adopt the central axis installation method, which occupies a relatively large space inside the mouse cage, limits the activity range of mice, makes mice less free during movement, and may affect their normal movement behavior performance. At the same time, the friction problem between the traditional running wheel and the bracket is also relatively prominent. Due to the lack of an effective limiting device, the running wheel is prone to friction with the bracket during movement, which not only increases the wear of the running wheel but also may affect the smoothness of mouse movement, thereby interfering with the accuracy of the collected movement data.

[0004] For example, the prior art Chinese patent application discloses a system and method for obtaining mouse running wheel movement data, including a running cage, a bracket, an angular velocity sensor, a single-chip microcomputer system, a display, and an input device. The running cage is used for mice to run, and a central axis is provided in the running cage; the bracket is used to support the running cage; the angular velocity sensor is used to collect angle data during the mouse running wheel process. Among them, the angular velocity sensor is fixed on the bracket, and the rotation axis of the angular velocity sensor is connected to the central axis. During the mouse running process, the rotation axis of the angular velocity sensor rotates together with the running cage and the central axis; the display is connected to the output end of the single-chip microcomputer system, the input device is connected to the input end of the single-chip microcomputer system, and the angular velocity sensor is connected to the input end of the single-chip microcomputer system. The single-chip microcomputer system is used to calculate movement data based on the angle data. The single-chip microcomputer system collects the output electrical signal value of the angular velocity sensor every set time, calculates the angle difference within the set time according to the electrical signals collected twice adjacent to each other, and then calculates the movement data. The prior art adopts the central axis design method.

[0005] In addition, in the aspect of mouse motion analysis, there are also some deficiencies in existing analysis methods and systems. Currently, for the acquisition and processing of mouse running wheel motion data, there is often a lack of unified and efficient processes and methods. During the data acquisition process, problems such as inconsistent data formats and large differences in data volume may exist in the data transmitted back by different sensors, which bring great difficulties to subsequent data processing and analysis. For example, during the data reading stage, a large amount of manual data sorting and conversion work may be required, with low efficiency and high error rates. During the data analysis process, the methods for handling abnormal data are not perfect, which may lead to inaccurate and unreliable data. In addition, when determining key motion indicators such as the total number of running circles of a mouse, existing methods often lack comprehensive consideration of sensor selection and data reliability, which may lead to large errors in the final results.

[0006] For example, the Chinese patent application CN202111243789.X in the prior art discloses an animal signal acquisition system, including a running cage, a data processor, a resistance measurement device, a counting device, a timing device, and a terminal. This application uses the resistance measurement device, the counting device, and the timing device to respectively obtain the rotational resistance of the running cage, the number of rotations of the running cage, and the rotation time of the running cage. The data processor is used to collect the rotation number data and rotation time data of the running cage from the counting device and the timing device respectively. The terminal generates the motion ability data of the animal based on the rotation number data, the rotation time data, and the rotational resistance of the running cage. This prior art has the above problems. Summary of the Invention

[0007] The object of the present invention is to provide a mouse running wheel, a method and a system for quantitative analysis of running wheel motion, which can partially solve or alleviate at least one of the above problems. The running wheel has a more reasonable structure, more accurate data acquisition, and meets the requirements for precise data acquisition and analysis in mouse motion research, providing more reliable technical support for related research.

[0008] In order to solve the above-mentioned technical problems, the present invention specifically adopts the following technical solutions:

[0009] In the first aspect of the present invention, it is to provide a mouse running wheel, including a running wheel body for accommodating a mouse to perform running motion and a bracket for supporting the running wheel body; the axles at both ends of the running wheel body are respectively connected to the bracket by short axles, so that the running wheel body can rotate along its own axle on the bracket; it further includes a sensor mounting seat arranged on the short axle, and the sensor mounting seat is used to mount an angular velocity sensor to sense the rotation of the short axle.

[0010] As an improvement, connection holes are opened on the axles at both ends of the running wheel body. One end of the short axle is fixed to the running wheel body by the connection hole, and the other end is embedded in the U-shaped groove on the bracket and can rotate in the U-shaped groove to drive the running wheel body to rotate.

[0011] As an improvement, the short shaft is made of engineering plastic, and a limiting ring is arranged on the short shaft. The limiting rings on the two short shafts clamp and fix the running wheel body.

[0012] As an improvement, the sensor mounting seat is arranged at the end of the short shaft, and there are two sensor mounting seats respectively arranged on the two short shafts.

[0013] The present invention also provides a method for quantitative analysis of the movement of a running wheel, which is applied to the above-mentioned mouse running wheel, and includes:

[0014] Target sensor screening step:

[0015] Install the sensor to be screened on the sensor mounting seat of the mouse running wheel, rotate the mouse running wheel according to a preset number of turns, and collect the data transmitted back by the sensor to be screened.

[0016] Take the data of the sensor to be screened with the shortest data length as the reference data, and crop the data of other sensors to be screened.

[0017] Screen all the data of the sensors to be screened, and correct the abnormal data screened out.

[0018] Calculate the number of turns of the mouse running wheel recorded by each sensor to be screened according to the data of each sensor to be screened.

[0019] Compare the number of turns of the mouse running wheel recorded by each sensor to be screened with the preset number of turns, and select one or two angular velocity sensors corresponding to the data of the sensor to be screened with the smallest difference from the preset number of turns as the target sensors.

[0020] Measurement step:

[0021] Install the target sensor on the mouse running wheel, use the target sensor to detect the rotation of the mouse running wheel driven by the running movement of the mouse, and collect the data transmitted back by the target sensor.

[0022] When there is one target sensor, calculate the number of turns of the mouse running wheel based on the data transmitted back by the target sensor.

[0023] When there are two target sensors, compare the data transmitted back by the two target sensors. If the difference is less than the threshold, calculate the number of turns of the mouse running wheel using the data transmitted back by the two target sensors; otherwise, determine that the data transmitted back by the two target sensors is invalid.

[0024] As an improvement, the step of cropping the data of the sensor to be screened includes:

[0025] Calculate the quantity difference between the data of the sensor to be screened and the reference data.

[0026] Average the sensor data to be screened into corresponding segments according to the quantity difference;

[0027] Randomly delete one data in each segment of data.

[0028] As an improvement, the method for calculating the number of rotations of the mouse running wheel according to the sensor data is to use the formula:

[0029]

[0030] Calculate the number of rotations of the mouse running wheel; where, R n is the number of rotations of the mouse running wheel recorded by the sensor numbered n, ωi is the i-th angular velocity value, and N is the quantity of sensor data.

[0031] As an improvement, in the case where there are two target sensors, use the formula

[0032] R = a * R12 + b * R22

[0033] to calculate the number of rotations of the mouse running wheel; where, R is the number of rotations, R12 is the number of rotations of the mouse running wheel recorded by the first target sensor in the measurement step, R22 is the number of rotations of the mouse running recorded by the second target sensor in the measurement step, a is the weight of the first target sensor, b is the weight of the second target sensor, and a + b = 1;

[0034] Use the formula:

[0035]

[0036] Calculate the weight of the first target sensor; where, a is the weight of the first target sensor, R11 is the number of rotations of the mouse running wheel recorded by the first target sensor in the target sensor screening step, R21 is the number of rotations of the mouse running wheel recorded by the second target sensor in the target sensor screening step, and r is the preset number of rotations;

[0037] Use the formula:

[0038]

[0039] Calculate the weight of the second target sensor; where, b is the weight of the second target sensor, R11 is the number of rotations of the mouse running wheel recorded by the first target sensor, R21 is the number of rotations of the mouse running wheel recorded by the second target sensor, and r is the preset number of rotations.

[0040] As an improvement, the steps for screening the sensor data to be screened and correcting the screened abnormal data include:

[0041] For a certain screening sensor, when the value of the sensor data at a certain time point is greater than the angular velocity threshold and the standard deviation of the angular velocity is greater than the standard deviation threshold, the sensor data at this time point is determined as abnormal data; the calculation method of the standard deviation of the angular velocity is to use the formula:

[0042]

[0043] Calculate the standard deviation of the angular velocity; where, σ ω is the standard deviation of the angular velocity, ωi is the i-th angular velocity value, is the average angular velocity of all sensor data, and N is the number of sensor data;

[0044] Delete the abnormal data, and fill the vacant position of the deleted abnormal data with the average value of the two normal data before and after the abnormal data.

[0045] The present invention also provides a quantitative analysis system for running wheel movement, including:

[0046] A target sensor screening module, which is used to rotate the mouse running wheel according to a preset number of turns after the sensor to be screened is installed on the sensor mounting seat of the mouse running wheel, and collect the data transmitted back by the sensor to be screened;

[0047] Taking the sensor data to be screened with the shortest data length as the reference data, and trimming the other sensor data to be screened;

[0048] Screen all the sensor data to be screened, and correct the screened abnormal data;

[0049] Calculate the number of turns of the mouse running wheel recorded by each sensor to be screened according to each sensor data to be screened;

[0050] Compare the number of turns of the mouse running wheel recorded by each sensor to be screened with the preset number of turns, and select one or two angular velocity sensors corresponding to the sensor data to be screened with the smallest difference from the preset number of turns as the target sensors;

[0051] A measurement module, which is used to detect the rotation of the mouse running wheel driven by the mouse running movement by using the target sensor after the target sensor is installed on the mouse running wheel, and collect the data transmitted back by the target sensor;

[0052] When there is one target sensor, calculate the number of turns of the mouse running wheel based on the data transmitted back by the target sensor;

[0053] When there are two target sensors, compare the data transmitted back by the two target sensors. If the difference is less than the threshold, calculate the number of turns of the mouse running wheel by using the data transmitted back by the two target sensors; otherwise, determine that the data transmitted back by the two target sensors is invalid.

[0054] Beneficial effects: The mouse running wheel with the above structure uses a short shaft to connect the running wheel body, replacing the traditional long shaft design, reserving sufficient space inside the running wheel, avoiding hindering the movement of mice, enabling them to move freely, and more truly showing their movement state. And it can avoid the error caused by the mouse hanging on the long shaft during the movement process and the rotation of the mouse cage under the action of inertia or the mouse.

[0055] Connecting holes are opened on the axles at both ends of the running wheel body, which are precisely matched with the short shafts, ensuring uniform force during rotation and stable operation. The other end of the short shaft is embedded in the U-shaped groove of the bracket. The U-shaped groove not only provides support and rotation space for the short shaft but also restricts its radial movement, making the running wheel rotate flexibly and stably, and also facilitating the disassembly, maintenance, and replacement of components.

[0056] The short shaft is made of engineering plastic, which has the characteristics of high strength, rigidity, wear resistance, and self-lubrication. It can withstand various forces during the operation of the running wheel, extend the service life, reduce the friction coefficient, reduce the weight of the running wheel, facilitate the movement of mice, and reduce noise interference.

[0057] Limit rings are provided on the short shaft, and the limit rings of the two short shafts clamp and fix the running wheel body, precisely defining the axial position, preventing axial movement, ensuring the operation accuracy, enhancing the structural safety, and avoiding the running wheel falling off and hurting the mice and damaging the equipment.

[0058] The sensor mounting seats are placed at the ends of the short shafts, with a total of two and are respectively arranged on the two short shafts, facilitating the selection and installation of one or two angular velocity sensors according to experimental requirements, reducing the interference error of data transmission, and accurately obtaining the real-time movement data of the running wheel.

[0059] For the running wheel motion quantitative analysis method with the above steps, first install the sensors to be screened to collect data, cut other data based on the shortest data to unify the data volume, then screen and correct abnormal data, calculate the number of rotations of the running wheel recorded by each sensor based on the processed data, and finally compare and select one or two sensors with the smallest difference from the preset number of rotations as the target sensors. This process ensures the accuracy and reliability of the selected sensors through multiple steps.

[0060] After installing the target sensors, different calculation strategies are adopted according to the number of them. When there is a single target sensor, the number of rotations is directly calculated based on its data, which is simple to operate; when there are two target sensors, compare their data. If the difference is less than the threshold, the weighted average method is used to calculate the number of rotations, combining the advantages of both. If the difference is large, the data is determined to be invalid to avoid interference from incorrect data and ensure that the measurement results accurately reflect the actual rotation of the running wheel to the greatest extent. Description of the Drawings

[0061] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. In all the drawings, similar elements or parts are generally denoted by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale. Obviously, the following-described drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0062] Figure 1 Structural schematic diagram of Embodiment 1 of the present invention;

[0063] Figure 2 Exploded view of Embodiment 1 of the present invention;

[0064] Figure 3 Enlarged view of the short shaft in Embodiment 1 of the present invention;

[0065] Figure 4 Enlarged view of the connection between the short shaft and the running wheel body in Embodiment 1 of the present invention;

[0066] Figure 5 Flowchart of Embodiment 2 of the present invention.

[0067] Summary of reference numeral identifications:

[0068] 1 Running wheel body, 2 Bracket, 3 Short shaft, 4 Sensor mounting seat, 5 Limit ring, 6 U-shaped groove. Detailed implementation manners

[0069] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0070] In this article, suffixes such as "module", "component", or "unit" used to represent elements are only for the convenience of the description of the present invention, and they have no specific meaning in themselves. Therefore, "module", "component", or "unit" can be used interchangeably.

[0071] In this text, the orientation or positional relationships indicated by terms such as "upper", "lower", "inner", "outer", "front", "rear", "one end", "the other end", etc. are based on the orientation or positional relationships shown in the drawings. These are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention. In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0072] In this text, unless otherwise clearly specified and defined, terms such as "installed", "provided with", "connected", etc. shall be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, a direct connection, or an indirect connection through an intermediate medium, and can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0073] In this text, "and / or" includes any and all combinations of one or more of the listed related items.

[0074] In this text, "a plurality of" means two or more, that is, it includes two, three, four, five, etc.

[0075] Embodiment 1: As Figure 1 , Figure 2 shown, this embodiment provides a mouse running wheel, which includes a running wheel body 1 for accommodating a mouse to perform running exercise and a bracket 2 for supporting the running wheel body 1; the axles at both ends of the running wheel body 1 are respectively connected to the bracket 2 by short axles 3, so that the running wheel body 1 can rotate along its own axle on the bracket 2; it further includes a sensor mounting seat 4 arranged on the short axle 3, and the sensor mounting seat 4 is used for mounting an angular velocity sensor to sense the rotation of the short axle 3.

[0076] In the traditional long axle design, the long axle will occupy a certain space inside the running wheel, which may hinder the movement of the mouse. On the other hand, during the movement of the mouse, it will also hang on the long axle, thus causing interference to the acquisition of movement data. In this embodiment, the axles at both ends of the running wheel are respectively connected to the bracket 2 by short axles 3. This connection method enables the running wheel body 1 to rotate along its own axle on the bracket 2. The design of the short axle 3 support avoids this problem, ensures that the mouse is not hindered during movement, can move more freely, and thus can more truly reflect the movement state of the mouse, which is beneficial to obtaining more accurate experimental data. And basically, the situation where the mouse hangs on the long axle is avoided.

[0077] As Figure 3As shown, more specifically, connection holes are opened on the axles at both ends of the running wheel body 1. One end of the short axle 3 is fixed to the running wheel body 1 by using the connection holes, and the other end is embedded in the U-shaped groove 6 on the bracket 2 and can rotate in the U-shaped groove 6 to drive the running wheel body 1 to rotate.

[0078] Connection holes are opened at the axles of both ends of the running wheel body 1, providing a specific interface for the connection between the short axle 3 and the running wheel body 1. Fixing the short axle 3 through the connection holes ensures that the axis of the short axle 3 coincides with that of the running wheel body 1, making the running wheel receive uniform force during rotation and ensuring the stability of the running wheel when the mouse exercises.

[0079] The connection between the short axle 3 and the connection holes of the running wheel body 1 can adopt interference fit, that is, the outer diameter of the short axle 3 is slightly larger than the inner diameter of the connection holes. During installation, a certain pressure needs to be applied to press the short axle 3 into the connection holes, and the friction between the two is used to prevent the short axle 3 from loosening; key connection can also be adopted, by machining key grooves on the short axle 3 and the connection holes and installing keys to transmit torque, so that the short axle 3 drives the running wheel body 1 to rotate synchronously, effectively avoiding relative sliding.

[0080] The other end of the short axle 3 is embedded in the U-shaped groove 6 on the bracket 2, and the U-shaped groove 6 provides a support and rotation space for the short axle 3. The short axle 3 can rotate freely in the U-shaped groove 6, and the shape and size of the U-shaped groove 6 can limit the radial movement of the short axle 3, ensuring that the short axle 3 always rotates within the specified range. When the mouse exercises on the running wheel body 1, the generated force causes the running wheel body 1 to rotate, driving the fixed short axle 3 to rotate in the U-shaped groove 6. The design of the U-shaped groove 6 not only ensures the flexible rotation of the running wheel but also maintains its stability.

[0081] The above assembly method is convenient for disassembling and replacing the running wheel body 1 or the short axle 3. If the components are damaged, they can be quickly repaired and replaced; and it can ensure the smooth rotation of the running wheel when the mouse exercises, reduce friction and energy loss, provide a smooth exercise experience for the mouse, and is also beneficial for the sensor to accurately collect exercise data, meeting the needs of experimental research.

[0082] As Figure 4 shown, in some embodiments, the short axle 3 is made of engineering plastic, and a limiting ring 5 is provided on the short axle 3. The limiting rings 5 on the two short axles 3 clamp and fix the running wheel body 1.

[0083] Engineering plastics have high strength and rigidity, and can withstand various forces generated during the operation of the running wheel, including the acting force of the mouse on the running wheel during movement and the centrifugal force generated by the rotation of the running wheel itself, etc., ensuring that the short shaft 3 will not easily deform or be damaged during long-term use, and maintaining the stability of the running wheel structure. Secondly, engineering plastics have good wear resistance. Friction will occur at the contact parts of the short shaft 3 with the running wheel body 1 and the bracket 2. The wear-resistant characteristics can extend the service life of the short shaft 3 and reduce the accuracy decline and component replacement frequency caused by wear. Moreover, engineering plastics also have good self-lubricity, which can reduce the friction coefficient when the short shaft 3 rotates, make the running wheel rotate more smoothly, reduce energy loss, which is not only beneficial for the mouse to move more easily, but also can reduce the noise generated by friction and avoid interfering with the experimental environment. In addition, engineering plastics are lighter in weight than materials such as metals, which helps to reduce the weight of the entire running wheel, facilitate movement and installation, and at the same time can also reduce the inertia that the mouse needs to overcome during movement, making the mouse movement more natural.

[0084] A limit ring 5 is arranged on the short shaft 3, and the limit rings 5 on the two short shafts 3 clamp and fix the running wheel body 1. The limit ring 5 can accurately limit the axial position of the running wheel body 1 on the short shaft 3 and prevent axial movement of the running wheel during rotation. If the running wheel has axial movement, it will cause uneven friction between the running wheel and the bracket 2, accelerate component wear, and may also affect the mouse's movement experience and even lead to inaccurate experimental data. Through the clamping and fixing of the limit ring 5, it can be ensured that the running wheel always rotates at a stable position, improving the running accuracy of the running wheel. From a safety perspective, the limit ring 5 can enhance the safety of the running wheel structure, prevent the running wheel from falling off the short shaft 3 during high-speed rotation or under external impact, and avoid causing harm to the mouse or damaging the experimental equipment.

[0085] In addition, the sensor mounting seat 4 is arranged at the end of the short shaft 3, and there are two sensor mounting seats 4 respectively provided on the two short shafts 3, which is convenient for researchers to selectively install one or two angular velocity sensors for experiments.

[0086] Since the short shaft 3 rotates synchronously with the running wheel body 1, the sensor installed at the end of the short shaft 3 can accurately obtain the real-time motion data of the running wheel, such as angular velocity, etc. Compared with being installed in other positions, this position can minimize interference and errors during data transmission, ensure that the data collected by the sensor truly reflects the motion state of the running wheel, and provide an accurate basis for subsequent experimental analysis.

[0087] In some experimental scenarios, researchers only need to obtain the basic motion data of the running wheel. In this case, they can choose to install an angular velocity sensor on one of the mounting seats 4. In experiments with higher requirements for the accuracy and reliability of experimental data, researchers can choose to install an angular velocity sensor on each of the two mounting seats 4. The dual-sensor configuration can mutually verify the collected data and effectively avoid data deviation caused by environmental interference or single-sensor failure. For example, when there are some accidental electromagnetic interferences in the environment that affect one of the sensors, the data of the other sensor can be used as a reference to ensure the credibility of the experimental data.

[0088] Embodiment 2: As Figure 5 shown, this embodiment provides a method for quantitative analysis of running wheel motion, which is applied to the mouse running wheel described in Embodiment 1. The specific steps include:

[0089] S1 Target sensor screening step:

[0090] S11 Install the sensor to be screened on the sensor mounting seat of the mouse running wheel, rotate the mouse running wheel according to a preset number of turns, and collect the data transmitted back by the sensor to be screened.

[0091] This step simulates the motion state of the running wheel in the actual use scenario. By collecting the data transmitted back by the sensor to be screened, it provides a raw data basis for subsequent screening. The setting of the preset number of turns is to ensure that each sensor is tested under the same motion conditions, making the collected data comparable.

[0092] S12 Use the data of the sensor to be screened with the shortest data length as the reference data, and crop the data of other sensors to be screened.

[0093] In the actual data collection process, due to the influence of various factors, the data lengths collected by different sensors may be inconsistent. If these data with different lengths are directly used for analysis, it will lead to deviation in the results. By cropping, the data lengths of all sensors are made the same, unifying the data specifications, which is convenient for subsequent fair comparison and analysis.

[0094] Preferably, if the difference in data length (i.e., the amount of data) between each sensor is less than 0.002%, based on the data of the sensor to be screened with the shortest data length as the reference data, the data points that are later in time among the corresponding data points of other sensors are cropped to align with the amount of data of the sensor to be screened with the shortest data length. For example, assume that in a mouse running wheel experiment, there are three sensors to be screened, A, B, and C, and the number of data collected is 30005, 30006, and 30004 respectively. Here, the data of sensor C with the least amount of data is used as the reference data, and the last 1 piece of data collected in the data of sensor A is cropped. Similarly, the last 2 pieces of data collected in the data of sensor B are cropped.

[0095] Further, if the difference in data length (i.e., the amount of data) between each sensor is greater than 0.002%, based on the data of the sensor to be screened with the shortest data length as the reference data, a random cropping mechanism is used to crop the data of other sensors.

[0096] More specifically, the steps for cropping the data of the sensor to be screened include:

[0097] S121 Calculate the difference in the number of data between the sensor data to be screened and the reference data.

[0098] Assume that in a mouse running wheel experiment, there are three sensors to be screened, A, B, and C, and the number of data collected is 30005, 30008, and 29900 respectively. Here, the data of sensor C with the least amount of data is used as the reference data.

[0099] The difference in the number of data between sensor A and the reference data is: 30005 - 29990 = 15.

[0100] The difference in the number of data between sensor B and the reference data is: 30008 - 29990 = 18.

[0101] S122 Divide the data of the sensor to be screened into corresponding segments according to the difference in the number of data.

[0102] For sensor A, its 30005 pieces of data are evenly divided into 15 segments, and each segment has approximately 30005÷15≈2000.33 pieces of data (in actual operation, it can be flexibly processed according to the characteristics of the data. Here, for the convenience of understanding, it is rounded to about 2000 pieces of data per segment, and the remaining data can be randomly distributed to each segment, the same below).

[0103] For sensor B, its 30008 pieces of data are evenly divided into 18 segments, and each segment has approximately 30008÷18≈1667.11 pieces of data (also rounded to 1667 pieces of data per segment).

[0104] S123 randomly deletes one data from each segment of data.

[0105] Among every 200 pieces of data of sensor A, randomly select one piece of data to delete. For example, randomly delete the 50th piece of data in the first segment, the 120th piece of data in the second segment... and so on, until 15 pieces of data are deleted, making the data volume of sensor A become 2990 pieces.

[0106] Among every 167 pieces of data of sensor B, also randomly delete one piece of data. For example, randomly delete the 80th piece of data in the first segment, the 35th piece of data in the second segment... A total of 18 pieces of data are deleted, making the data volume of sensor B also become 2990 pieces.

[0107] Through such trimming operations, the data volumes of sensors A, B, and C are all unified to 29900 pieces, providing a unified data basis for subsequent data analysis and ensuring the accuracy and consistency of experimental data processing.

[0108] S13 screens all the sensor data to be screened and corrects the abnormal data screened out.

[0109] Abnormal data may be caused by environmental interference (such as electromagnetic interference, vibration, etc.), sensor failures, or abnormal situations of mouse movement. If not processed, these abnormal data will seriously affect the accuracy and reliability of the data. Identifying abnormal data through specific algorithms or rules and using appropriate methods (such as replacing abnormal values with the mean of normal data before and after) for correction can improve data quality and make the subsequent calculation and analysis results more credible.

[0110] More specifically, the steps of screening the sensor data to be screened and correcting the abnormal data screened out include:

[0111] S131 For a certain sensor to be screened, when the value of the sensor data at a certain time point is greater than the angular velocity threshold and the standard deviation of the angular velocity is greater than the standard deviation threshold, the sensor data at this time point is determined to be abnormal data; the calculation method of the standard deviation of the angular velocity is to use the formula:

[0112]

[0113] Calculate the standard deviation of the angular velocity; where σ ω is the standard deviation of the angular velocity, ωi is the i-th angular velocity value, is the mean angular velocity of all sensor data, and N is the number of sensor data. The standard deviation of the angular velocity is an index to measure the dispersion degree of angular velocity data over a period of time, which reflects the fluctuation of the angular velocity. By calculating the standard deviation of the angular velocity, the stability of sensor data can be understood.

[0114] In this step, by setting the angular velocity threshold and the standard deviation threshold of the angular velocity, the data of a certain sensor to be screened at each time point is judged. Only when the value of the sensor data is greater than the angular velocity threshold and the standard deviation of the angular velocity is greater than the standard deviation threshold, the sensor data at this time point is determined to be abnormal data. This dual judgment criterion is more rigorous and scientific than a single criterion and can more accurately identify the real abnormal data.

[0115] S132 deletes the abnormal data and fills the vacant position of the deleted abnormal data with the average value of the two normal data before and after the abnormal data.

[0116] Once it is determined that the data at a certain time point is abnormal data, it is first deleted. Abnormal data will seriously interfere with subsequent data analysis and results. If these abnormal values are retained, it may lead to wrong conclusions. For example, when calculating indicators such as the average angular velocity and the total number of rotations of the mouse running wheel, the abnormal data will cause deviations in these indicators and cannot truly reflect the movement of the mouse.

[0117] After deleting the abnormal data, a vacant position will be left in the data sequence. To ensure the continuity and integrity of the data, the vacant position is filled with the average value of the two normal data before and after the abnormal data. This filling method is based on the assumption of data continuity, that is, it is considered that in a short period of time, the change of data is relatively stable. For example, if the data at time point is determined to be abnormal and deleted, then the average value of the normal data at time point and is used to fill the vacant position at time point. This can restore the continuity of the data to a certain extent and at the same time will not introduce too much error, enabling subsequent data analysis to be based on relatively reasonable data.

[0118] S14 calculates the number of rotations of the mouse running wheel recorded by each sensor to be screened according to the data of each sensor to be screened.

[0119] In this embodiment, the formula:

[0120]

[0121] is used to calculate the number of rotations of the mouse running wheel; where R n is the number of rotations of the mouse running wheel recorded by the sensor numbered n, ωi is the i-th angular velocity value, and N is the number of sensor data.

[0122] In the mouse running wheel experiment, the movement speed and direction of the mouse inside the running wheel change randomly. If the angular velocity data is simply accumulated, the positive angular velocity generated by the mouse's forward movement and the negative angular velocity generated by the reverse movement will cancel each other out. For example, if the mouse first rotates the running wheel clockwise to generate a positive angular velocity and then rotates counterclockwise to generate a negative angular velocity, and these two angular velocities are directly accumulated, their values will weaken each other, resulting in the calculated number of rotations being less than the actual number of rotations of the running wheel, and unable to truly reflect the mouse's movement situation.

[0123] Using the absolute value of the angular velocity at a single time point for accumulation can effectively avoid the cancellation problem of positive and negative direction movements. Whether the mouse rotates the running wheel forward or backward, the absolute value of the generated angular velocity is included in the calculation scope, and the calculated number of rotations is more in line with the actual running wheel rotation situation. In this way, the total amount of the mouse's movement on the running wheel can be accurately counted, providing reliable data support for subsequent experimental analysis. For example, in experiments studying the mouse's exercise endurance, exercise habits, etc., the accurate number of rotations of the running wheel is an important indicator for evaluating the mouse's movement situation, and using the calculation method of absolute value accumulation can ensure the accuracy and scientific nature of these research results.

[0124] S15 Compare the number of rotations of the mouse running wheel recorded by each sensor to be screened with the preset number of rotations, and select one or two angular velocity sensors corresponding to the data of the sensor to be screened with the smallest difference from the preset number of rotations as the target sensors.

[0125] Compare the number of rotations of the running wheel recorded by each sensor to be screened with the preset number of rotations, and select one or two angular velocity sensors with the smallest difference from the preset number of rotations as the target sensors. The purpose of this is to select the sensors with the measurement results closest to the actual situation in this screening test, and these sensors can provide more reliable data in the subsequent measurement steps. Selecting one or two sensors is to meet different experimental requirements and scenarios. For example, a single sensor is suitable for situations where the requirement for data accuracy is relatively low or the experimental conditions are simple, while two sensors can verify each other's data and improve the reliability of the data, and are suitable for experiments with high requirements for data accuracy.

[0126] S2 Measurement step:

[0127] S21 Install the target sensors on the mouse running wheel, use the target sensors to detect the rotation of the mouse running wheel driven by the mouse's running movement, and collect the data transmitted back by the target sensors.

[0128] Since at most two angular velocity sensors can be installed on the mouse running wheel, the number of angular velocity sensors can be selected according to needs.

[0129] When there is one target sensor, calculate the number of rotations of the mouse running wheel based on the data transmitted back by the target sensor.

[0130] When there is only one target sensor, based on the data transmitted back by this sensor, use the method in step S14 for calculating the number of rotations to calculate the number of rotations of the mouse running wheel. This situation is applicable to some experiments with requirements for cost and operational simplicity, obtaining data through a single reliable sensor and conducting analysis.

[0131] S23 When there are two target sensors, compare the data transmitted back by the two target sensors. If the difference is less than the threshold, use the data transmitted back by the two target sensors to calculate the number of rotations of the mouse running wheel; otherwise, determine that the data transmitted back by the two target sensors is invalid.

[0132] When there are two target sensors, compare the data transmitted back by the two sensors. If the difference between the data of the two sensors is less than the preset threshold, it indicates that the measurement results of the two sensors are relatively consistent and the data is reliable. At this time, use the data transmitted back by the two sensors to calculate the number of rotations of the mouse running wheel. Weighted average or other appropriate calculation methods can be adopted to integrate the data of the two sensors and further improve the accuracy of the measurement results. If the difference is greater than the threshold, determine that the data transmitted back by the two target sensors is invalid. This may mean that there are large interference factors or the sensors malfunction, and it is necessary to recheck the experimental equipment or replace the sensors to ensure the reliability of the experimental data.

[0133] More specifically, when there are two target sensors, use the formula

[0134] R = a * R12 + b * R22

[0135] to calculate the number of rotations of the mouse running wheel; where R is the number of rotations, R12 is the number of rotations of the mouse running wheel recorded by the first target sensor in the measurement step, R22 is the number of rotations of the mouse recorded by the second target sensor in the measurement step, a is the weight of the first target sensor, b is the weight of the second target sensor, and a + b = 1.

[0136] The above formula is based on the principle of weighted average. By assigning different weights to the two sensors, the number of rotations of the mouse running wheel recorded by the two sensors is integrated to obtain a more accurate and reliable result. This is because in actual measurement, the two sensors may be interfered to different degrees, and there will be a certain difference in their measurement results. Simply taking the average may not truly reflect the actual number of rotations of the running wheel, while weighted average can reasonably allocate weights to their measurement results according to the performance of the sensors in the screening step, making the final result closer to the true value.

[0137] Furthermore, use the formula:

[0138]

[0139] Calculate the weight of the first target sensor; where a is the weight of the first target sensor, R11 is the number of rotations of the mouse running wheel recorded by the first target sensor in the target sensor screening step, R21 is the number of rotations of the mouse running wheel recorded by the second target sensor in the target sensor screening step, and r is the preset number of rotations.

[0140] Use the formula:

[0141]

[0142] Calculate the weight of the second target sensor; where b is the weight of the second target sensor, R11 is the number of rotations of the mouse running wheel recorded by the first target sensor, R21 is the number of rotations of the mouse running wheel recorded by the second target sensor, and r is the preset number of rotations.

[0143] By comparing the deviation between the number of rotations recorded by the two sensors in the screening step and the preset number of rotations. The smaller the deviation, the closer the measurement result of the sensor is to the real situation during screening, and the higher its weight should be in the comprehensive calculation. Specifically, when calculating, use the absolute value of the deviation between a certain sensor and the preset number of rotations as the numerator, and the sum of the absolute values of the deviations between the two sensors and the preset number of rotations as the denominator. The ratio obtained is the weight of the sensor. For example, if the deviation between the number of rotations recorded by the first target sensor and the preset number of rotations during screening is small, while the deviation of the second target sensor is large, then the value calculated according to the formula will be large, meaning that the number of rotations recorded by the first target sensor contributes more to the final result in the comprehensive calculation.

[0144] Implementation Three: This embodiment provides a quantitative analysis system for running wheel movement, including:

[0145] A target sensor screening module, which is used to rotate the mouse running wheel according to the preset number of rotations after the sensor to be screened is installed on the sensor mounting seat of the mouse running wheel, and collect the data transmitted back by the sensor to be screened.

[0146] Use the data of the sensor to be screened with the shortest data length as the reference data to crop the data of other sensors to be screened.

[0147] Screen all the data of the sensors to be screened, and correct the abnormal data screened out.

[0148] Calculate the number of rotations of the mouse running wheel recorded by each sensor to be screened according to the data of each sensor to be screened.

[0149] Compare the number of rotations of the mouse running wheel recorded by each sensor to be screened with a preset number of rotations, and select one or two angular velocity sensors corresponding to the data of the sensor to be screened with the smallest difference from the preset number of rotations as the target sensors;

[0150] A measurement module, after installing the target sensor on the mouse running wheel, is used to detect the rotation of the mouse running wheel driven by the mouse running movement by the target sensor and collect the data transmitted back by the target sensor;

[0151] When there is one target sensor, calculate the number of rotations of the mouse running wheel based on the data transmitted back by the target sensor;

[0152] When there are two target sensors, compare the data transmitted back by the two target sensors. If the difference is less than the threshold, calculate the number of rotations of the mouse running wheel using the data transmitted back by the two target sensors; otherwise, determine that the data transmitted back by the two target sensors is invalid.

[0153] It should be noted that in this article, the terms "including", "comprising" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including that element.

[0154] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a computer terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0155] The embodiments of the present invention have been described above in conjunction with the accompanying drawings, but the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope protected by the claims of the present invention. These all fall within the protection scope of the present invention.

Claims

1. A mouse running wheel, characterized in that: It includes a running wheel body for accommodating a mouse to perform running exercise and a bracket for supporting the running wheel body; the axles at both ends of the running wheel body are respectively connected to the bracket by short axles, so that the running wheel body can rotate along its own axle on the bracket; it also includes a sensor mounting seat arranged on the short axle, and the sensor mounting seat is used for mounting an angular velocity sensor to sense the rotation of the short axle.

2. The mouse running wheel according to claim 1, wherein: Connection holes are opened on the axles at both ends of the running wheel body, one end of the short axle is fixed to the running wheel body by the connection hole, and the other end is embedded in the U-shaped groove on the bracket and can rotate in the U-shaped groove to drive the running wheel body to rotate.

3. A mouse running wheel according to claim 2, characterized in that: The short axle is made of engineering plastic, and a limiting ring is arranged on the short axle, and the limiting rings on the two short axles clamp and fix the running wheel body.

4. A mouse running wheel according to claim 1, characterized in that: The sensor mounting seat is arranged at the end of the short axle, and there are two sensor mounting seats respectively arranged on the two short axles.

5. A method for quantitative analysis of running wheel movement, applied to the mouse running wheel according to any one of claims 1 to 4, characterized in that It includes: Target sensor screening step: Install the sensor to be screened on the sensor mounting seat of the mouse running wheel, rotate the mouse running wheel according to the preset number of turns, and collect the data transmitted back by the sensor to be screened. Taking the data of the sensor to be screened with the shortest data length as the reference data, crop the data of other sensors to be screened. Screen all the data of the sensors to be screened, and correct the abnormal data screened out. Calculate the number of turns of the mouse running wheel recorded by each sensor to be screened according to the data of each sensor to be screened. Compare the number of turns of the mouse running wheel recorded by each sensor to be screened with the preset number of turns, and select one or two angular velocity sensors corresponding to the data of the sensor to be screened with the smallest difference from the preset number of turns as the target sensors. Measurement step: Install the target sensor on the mouse running wheel, use the target sensor to detect the rotation of the mouse running wheel driven by the mouse running exercise, and collect the data transmitted back by the target sensor. When there is one target sensor, calculate the number of turns of the mouse running wheel rotation based on the data transmitted back by the target sensor. When there are two target sensors, compare the data transmitted back by the two target sensors. If the difference is less than the threshold, calculate the number of turns of the mouse running wheel rotation using the data transmitted back by the two target sensors. Otherwise, it is determined that the data transmitted back by the two target sensors is invalid.

6. The quantitative analysis method for running wheel movement according to claim 5, characterized in that The step of cropping the data of the sensor to be screened includes: Calculate the quantity difference between the data of the sensor to be screened and the reference data. Divide the data of the sensor to be screened into corresponding segments according to the quantity difference. Randomly delete one data in each segment of data.

7. A quantitative analysis method for running wheel movement according to claim 5, characterized in that The method of calculating the number of turns of the mouse running wheel rotation according to the sensor data is to use the formula: Calculate the number of rotations of the mouse running wheel; where R n is the number of rotations of the mouse running wheel recorded by the sensor numbered n, ωi is the i-th angular velocity value, and N is the number of sensor data.

8. A quantitative analysis method for running wheel movement according to claim 5, characterized in that: When there are two target sensors, use the formula R = a * R12 + b * R22 to calculate the number of turns of the mouse running wheel rotation; where, R is the number of turns, R12 is the number of turns of the mouse running wheel rotation recorded by the first target sensor in the measurement step, R22 is the number of turns of the mouse running rotation recorded by the second target sensor in the measurement step, a is the weight of the first target sensor, b is the weight of the second target sensor, and a + b = 1; Use the formula: Calculate the weight of the first target sensor; where a is the weight of the first target sensor, R11 is the number of rotations of the mouse running wheel recorded by the first target sensor in the target sensor screening step, R21 is the number of rotations of the mouse running wheel recorded by the second target sensor in the target sensor screening step, and r is the preset number of rotations; Use the formula: Calculate the weight of the second target sensor; where b is the weight of the second target sensor, R11 is the number of rotations of the mouse running wheel recorded by the first target sensor, R21 is the number of rotations of the mouse running wheel recorded by the second target sensor, and r is the preset number of rotations.

9. The quantitative analysis method for running wheel movement according to claim 5, characterized in that The steps of screening the sensor data to be screened and correcting the screened abnormal data include: For a certain sensor to be screened, when the value of the sensor data at a certain time point is greater than the angular velocity threshold and the standard deviation of the angular velocity is greater than the standard deviation threshold, the sensor data at this time point is determined as abnormal data; the calculation method of the standard deviation of the angular velocity is to use the formula: Calculate the standard deviation of the angular velocity; where, σ ω is the standard deviation of the angular velocity, ωi is the i-th angular velocity value, is the mean angular velocity of all sensor data, and N is the number of sensor data; Delete the abnormal data, and fill the vacancy of the deleted abnormal data with the average value of the two normal data before and after the abnormal data.

10. A quantitative analysis system for running wheel movement, characterized in that Include: A target sensor screening module, configured to, after the sensor to be screened is installed on the sensor mount of the mouse running wheel, rotate the mouse running wheel according to a preset number of rotations, and collect the data transmitted back by the sensor to be screened; Take the sensor data to be screened with the shortest data length as the reference data, and crop the other sensor data to be screened; Screen all the sensor data to be screened, and correct the screened abnormal data; Calculate the number of rotations of the mouse running wheel recorded by each sensor to be screened according to each sensor data to be screened; Compare the number of rotations of the mouse running wheel recorded by each sensor to be screened with the preset number of rotations, and select one or two angular velocity sensors corresponding to the sensor data to be screened with the smallest difference from the preset number of rotations as the target sensors; A measurement module, configured to, after the target sensor is installed on the mouse running wheel, use the target sensor to detect the rotation of the mouse running wheel driven by the mouse running movement, and collect the data transmitted back by the target sensor; When there is one target sensor, calculate the number of rotations of the mouse running wheel based on the data transmitted back by the target sensor; When there are two target sensors, compare the data transmitted back by the two target sensors. If the difference is less than the threshold, calculate the number of rotations of the mouse running wheel using the data transmitted back by the two target sensors; Otherwise, determine that the data transmitted back by the two target sensors is invalid.

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