Method for synchronously recognizing motion gaits and motion parameters of laboratory mouse

Abstract

The invention discloses a method for synchronously identifying motion gaits and motion parameters of laboratory mice, which comprises the following steps of: respectively putting at least one laboratory mouse on a runway of a corresponding treadmill, performing image shooting on the laboratory mouse on the runway of the treadmill, and constructing a two-dimensional coordinate system by taking a diagonal intersection point of a quadrangle where four feet of the laboratory mouse are located as an original point; four feet of the laboratory mouse are respectively located in four quadrants of the two-dimensional coordinate system; forming a gait information set by the mouse claw two-dimensional coordinate value corresponding to each foot, analyzing the gait information set to obtain the gait information change of each foot of the laboratory mouse, and determining the specific foot position with the gait change based on the change rule corresponding to the mouse claw two-dimensional coordinate value with the gait information change; calculating motion parameters of the laboratory mouse based on the working parameters of the treadmill and an image shot by an image monitoring device above the treadmill; according to the method, the mouse claw position with the gait change can be specifically determined.

Description

Technical Field

[0001] The present invention relates to the technical field of motion gait recognition, and particularly relates to a method for synchronously recognizing the motion gait and motion parameters of experimental mice. Background Art

[0002] Gait analysis is an important examination method for studying the functions and damages of the nervous system and motor system of animals, and is also an important tool for detecting biomechanical irregularities and improving sports performance. In this experiment, mice are placed on a treadmill runway to analyze their motion data and gait characteristics.

[0003] Currently, there are already various gait analysis methods on the market, but there is no method that can accurately analyze the gait of the animal's four limbs throughout the process while obtaining kinematic data during the animal's running. Moreover, most current gait analysis methods can only identify that the gait has changed, but cannot determine the position of the mouse's paw where the gait specifically occurs. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for synchronously recognizing the motion gait and motion parameters of experimental mice, so as to solve the technical problems in the prior art that it is impossible to accurately analyze the gait of the animal's four limbs throughout the process while obtaining kinematic data during the animal's running, and most current gait analysis methods can only identify that the gait has changed, but cannot determine the position of the mouse's paw where the gait specifically occurs.

[0005] To solve the above technical problems, the present invention specifically provides the following technical solutions:

[0006] A method for synchronously recognizing the motion gait and motion parameters of experimental mice, comprising the following steps:

[0007] Step 100: Place at least one experimental mouse on the runway of the corresponding treadmill respectively, and drive the runway to rotate so that the experimental mouse can move on the runway;

[0008] Step 200: Use image monitoring devices arranged above and below the runway of each treadmill to take images of the experimental mouse on the runway of the treadmill, perform image processing on the taken images through a processing system, construct a gait change recognition model of the experimental mouse, and construct a two-dimensional coordinate system with the intersection point of the diagonals of the quadrilateral where the four feet of the experimental mouse are located as the origin, so that the four feet of the experimental mouse are respectively in the four quadrants of the two-dimensional coordinate system;

[0009] Step 300: Form a gait information set with the two-dimensional coordinate values of the mouse paws corresponding to each foot, analyze the gait information set to obtain the gait information changes of each foot of the experimental mouse, and determine the specific foot position where the gait change occurs based on the change rule corresponding to the two-dimensional coordinate value of the mouse paw where the gait information change occurs.

[0010] Step 400: Calculate the motion parameters of the experimental mice based on the working parameters of the treadmill and the images captured by the image monitoring device above the treadmill, so as to independently track and identify the gait images and motion parameters of each mouse respectively.

[0011] As a preferred embodiment of the present invention, in the step 100, the running track of the treadmill is of a transparent structure, and the image monitoring device arranged below the running track of the treadmill can photograph the abdomen of the experimental mice on the running track to obtain the positions where the four feet of the experimental mice are located.

[0012] As a preferred embodiment of the present invention, in the step 200, the image monitoring device below the treadmill is used to photograph the abdomen of the experimental mice on the running track of the treadmill, and the processing system is used to receive the abdominal images of the experimental mice photographed by the image monitoring device below the treadmill, and construct a gait change recognition model based on the abdominal images of the experimental mice. The specific implementation method is as follows:

[0013] The processing system processes the abdominal images of the experimental mice to extract the images of the four paws of the experimental mice in each abdominal image;

[0014] Obtain the central positions of the four paws of the experimental mice, connect the central positions of the four paws in sequence to form a quadrilateral, and connect the central positions of the opposite two paws to form a diagonal line. Construct a two-dimensional coordinate system with the intersection point of the diagonal line as the origin, so that the four paws of the experimental mice are respectively in the four quadrants of the two-dimensional coordinate system;

[0015] Integrate the intersection point of the diagonal lines of the four paws extracted from the abdominal images in real time onto the origin of the two-dimensional coordinate system, and record the two-dimensional coordinate values of the paws corresponding to the central positions of the paws extracted each time to form a gait change recognition model. The two-dimensional coordinate values of the central positions of each paw form a gait information set, which are set A, set B, set C, and set D respectively. Among them, set A and set C correspond to the gait information sets of the two paws on the diagonal line, and set B and set D correspond to the gait information sets of the other two paws on the diagonal line;

[0016] Compare the two-dimensional coordinate values of the paws corresponding to each photograph in each gait information set in real time, and determine the change rule of the two-dimensional coordinate values of the paws in each gait information set through the gait change recognition model to identify the paws of the experimental mice with gait changes.

[0017] As a preferred embodiment of the present invention, in the step 300, the method for identifying the change rule of the two-dimensional coordinate value of the mouse paw in each gait information set through the gait change recognition model to identify the specific mouse paw with gait change is as follows:

[0018] Construct a monitoring timeline, integrate each two-dimensional coordinate value of the mouse paw in each gait information set onto the monitoring timeline, compare the two-dimensional coordinate value of the mouse paw corresponding to a certain time point with the two-dimensional coordinate value of the mouse paw corresponding to the previous time point to determine whether the gait of the mouse paw has changed, and determine the number of gait information sets in which the two-dimensional coordinate value of the mouse paw has changed;

[0019] When only the two-dimensional coordinate value of the mouse paw in one gait information set changes, the mouse paw corresponding to the gait information set with the change has a gait change;

[0020] When the two-dimensional coordinate values of the mouse paws in all gait information sets change, obtain the changed two-dimensional coordinate values of the mouse paws in each gait information set and form a variant set;

[0021] Determine the relationship between the straight line formed by the changed two-dimensional coordinate values of the mouse paws in the variant set and the two diagonals. Take the mouse paw corresponding to the changed two-dimensional coordinate values in the same straight line in the variant set as the mouse paw without gait change, and take the mouse paw corresponding to the variant set in which the changed two-dimensional coordinate values of the mouse paws cannot be in the same straight line as the mouse paw with gait change.

[0022] As a preferred embodiment of the present invention, when determining the relationship between the straight line formed by the changed two-dimensional coordinate values of the mouse paws in the variant set and the two diagonals, determine the diagonal equations corresponding to the gait information sets of the two mouse paws on the diagonal in real time, and then determine whether the straight line where the two-dimensional coordinate values of the mouse paws in the variant set extracted from each gait information set are located is parallel to the diagonal to determine the mouse paw with gait change. Among them, the method for constructing the diagonal equations corresponding to the gait information sets of the two mouse paws on the diagonal is as follows:

[0023] Determine the straight line equation formed by the two-dimensional coordinate values of the mouse paws in the gait information sets corresponding to the two mouse paws on the diagonal:

[0024] Y(A, C) = k1 * x;

[0025]

[0026] Wherein, xa(i) is the X coordinate value of the rat paw in set A, xc(i) is the X coordinate value of the rat paw in set C, ya(i) is the Y coordinate value of the rat paw in set A, yc(i) is the Y coordinate value of the rat paw in set C, and i is the coordinate value corresponding to the same i-th time point in set A and set C;

[0027] Y(B, D) = k2 * x;

[0028]

[0029] Wherein, xb(i) is the X coordinate value of the rat paw in set B, xd(i) is the X coordinate value of the rat paw in set D, yb(i) is the Y coordinate value of the rat paw in set B, yd(i) is the Y coordinate value of the rat paw in set D, and i is the coordinate value corresponding to the same i-th time point in set B and set D.

[0030] As a preferred embodiment of the present invention, the method for determining the straight line where the two-dimensional coordinate value of the rat paw in the abnormal change set extracted from each gait information set is as follows:

[0031] Compare each group of two-dimensional coordinate values of the rat paw in each abnormal change set with the two-dimensional coordinate values of the rat paw corresponding to the previous time point to determine the inclination angle kj of the straight line formed by the two groups of two-dimensional coordinate values of the rat paw:

[0032]

[0033] Wherein, xa(j) is the X coordinate value of the rat paw corresponding to a certain time point in the abnormal change set extracted from set A, xa(j - 1) is the X coordinate value of the rat paw corresponding to the previous time point of the above-mentioned certain time point, ya(j) is the Y coordinate value of the rat paw corresponding to a certain time point in the abnormal change set extracted from set A, and ya(j - 1) is the Y coordinate value of the rat paw corresponding to the previous time point of the above-mentioned certain time point;

[0034]

[0035] Wherein, xb(j) is the X coordinate value of the rat paw corresponding to a certain time point in the abnormal change set extracted from set B, xb(j - 1) is the X coordinate value of the rat paw corresponding to the previous time point of the above-mentioned certain time point, yb(j) is the Y coordinate value of the rat paw corresponding to a certain time point in the abnormal change set extracted from set B, and yb(j - 1) is the Y coordinate value of the rat paw corresponding to the previous time point of the above-mentioned certain time point;

[0036]

[0037] Among them, xc(j) is the mouse claw X coordinate value corresponding to a certain time point in the abnormal change set extracted from the C set, xc(j - 1) is the mouse claw X coordinate value corresponding to the previous time point of the above-mentioned certain time point, yc(j) is the mouse claw Y coordinate value corresponding to a certain time point in the abnormal change set extracted from the C set, and yc(j - 1) is the mouse claw Y coordinate value corresponding to the previous time point of the above-mentioned certain time point;

[0038]

[0039] Among them, xd(j) is the mouse claw X coordinate value corresponding to a certain time point in the abnormal change set extracted from the D set, xd(j - 1) is the mouse claw X coordinate value corresponding to the previous time point of the above-mentioned certain time point, yd(j) is the mouse claw Y coordinate value corresponding to a certain time point in the abnormal change set extracted from the D set, and yd(j - 1) is the mouse claw Y coordinate value corresponding to the previous time point of the above-mentioned certain time point.

[0040] As a preferred embodiment of the present invention, when determining whether the straight line where the mouse claw two-dimensional coordinate value in the abnormal change set extracted from each gait information set is parallel to the diagonal line, Ka(j) is compared with Kc(j). When Ka(j) is the same as Kc(j), it is considered that there is no gait change in the mouse claw position corresponding to the A set and the mouse claw position corresponding to the C set;

[0041] When Ka(j) is different from Kc(j), Ka(j) is respectively compared with k2 and Kc(j) is compared with k2. The mouse claw position corresponding to Ka(j) or Kc(j) that is the same as k2 is determined as the mouse claw without gait change, and the mouse claw position corresponding to Ka(j) or Kc(j) that is different from k2 is determined as the mouse claw with gait change;

[0042] Similarly, Kb(j) is compared with Kd(j). When Kb(j) is the same as Kd(j), it is considered that there is no gait change in the mouse claw position corresponding to the B set and the mouse claw position corresponding to the D set;

[0043] When Kb(j) is different from Kd(j), Kb(j) is respectively compared with k1 and Kd(j) is compared with k1. The mouse claw position corresponding to Kb(j) or Kd(j) that is the same as k1 is determined as the mouse claw without gait change, and the mouse claw position corresponding to Kb(j) or Kd(j) that is different from k1 is determined as the mouse claw with gait change.

[0044] As a preferred embodiment of the present invention, in step 400, the image monitoring device above the treadmill is used to take a video of the experimental mice on the treadmill runway, forming a back recording video stream of the experimental mice, and recording the time point t1 corresponding to the presence of the experimental mice and the startup of the treadmill in the captured video;

[0045] The processing system synchronizes the video transmitted by the image monitoring device above the treadmill to identify the experimental mice in the captured video, and records the corresponding time point t2 when no experimental mice are identified in the captured video;

[0046] The movement parameters of the experimental mice are calculated by combining the time point t1 and the time t2.

[0047] As a preferred embodiment of the present invention, the movement parameter S of the experimental mice is S = V * (t2 - t1), where V is the movement speed of the treadmill.

[0048] As a preferred embodiment of the present invention, when experimental mice are identified in the captured video, but the position of the experimental mice is at the bottom of the treadmill runway and remains at the bottom of the treadmill runway for more than a set threshold, the time point t2 corresponding to the stop of the experimental mice running is recorded.

[0049] The present invention has the following beneficial effects compared with the prior art:

[0050] The present invention can simultaneously and independently identify, track, and record the gait images and important movement parameters (running distance, movement time) of several experimental mice respectively. Compared with the traditional method, the experimental efficiency is greatly improved. The experimental animals are in the same experimental environment for gait change confirmation experiments and mouse movement ability experiments, and can simultaneously identify and analyze the movement gait and movement parameters of the experimental mice. Moreover, the present invention can not only identify the movement time when the experimental mice show gait changes, but also specifically determine the position of the mouse claws where the gait changes occur, which is convenient to provide data support for gait changes and mouse health. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only exemplary, and for those of ordinary skill in the art, other implementation drawings can be obtained according to the provided drawings without creative efforts.

[0052] Figure 1 It is a schematic flow chart for analyzing the movement gait of large and small mice in an embodiment of the present invention; DETAILED DESCRIPTION OF THE INVENTION

[0053] 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 only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0054] As Figure 1 shown, the present invention provides a method for synchronously identifying the movement gait and movement parameters of experimental mice, including the following steps:

[0055] Step 100: Place at least one experimental mouse on the runway of the corresponding treadmill respectively, and drive the runway to rotate so that the experimental mouse can move on the runway.

[0056] In this step, the runway of the treadmill is a transparent structure, and an image monitoring device arranged below the runway of the treadmill can take pictures of the abdomen of the experimental mouse on the runway to obtain the positions of the four feet of the experimental mouse.

[0057] Step 200: Use the image monitoring devices arranged above and below the runway of each treadmill to take pictures of the experimental mouse on the runway of the treadmill, perform image processing on the taken pictures through a processing system, construct a gait change recognition model of the experimental mouse, and construct a two-dimensional coordinate system with the intersection point of the diagonals of the quadrilateral where the four feet of the experimental mouse are located as the origin, so that the four feet of the experimental mouse are respectively in the four quadrants of the two-dimensional coordinate system.

[0058] Step 300: Form a gait information set with the two-dimensional coordinate values of the mouse claws corresponding to each foot, analyze the gait information set to obtain the gait information changes of each foot of the experimental mouse, and determine the specific foot positions where gait changes occur based on the change rules corresponding to the two-dimensional coordinate values of the mouse claws with gait information changes.

[0059] Step 400: Calculate the movement parameters of the experimental mouse based on the working parameters of the treadmill and the images taken by the image monitoring device above the treadmill to independently track and identify the gait images and movement parameters of each mouse respectively.

[0060] This embodiment can monitor the movement parameters and gait change information of one experimental mouse in real time, or can also independently monitor the movement parameters and gait change information of multiple experimental mice in real time. The specific implementation method is as follows:

[0061] The running track of the treadmill is designed to be a transparent structure. An image monitoring device under the track is used to take pictures of the abdomen of the experimental mouse, so as to obtain the real-time abdominal image of the experimental mouse. The foot position information of the experimental mouse is extracted from the real-time abdominal image. The central positions of the four claws of the experimental mouse are connected in sequence to form a quadrilateral. By analyzing the change of the coordinate positions of the claws of the experimental mouse, the specific foot position where the gait change occurs is determined. The specific implementation method is as follows:

[0062] The central positions of the four claws of the experimental mouse extracted from each captured image are connected in sequence to form a quadrilateral, and the intersection point of the diagonals of the quadrilateral is determined. A two-dimensional coordinate system is constructed with the intersection point of the diagonals of the quadrilateral as the origin, so that the four claws are respectively in the four quadrants of the two-dimensional coordinate system. The two-dimensional coordinate values of the center position of each claw corresponding to each capture are integrated into a gait information set, and sets A, B, C, and D are respectively formed.

[0063] The two-dimensional coordinate values of the claws in each gait information set are respectively analyzed and processed to determine whether the two-dimensional coordinate values of the claws change, and then according to the change law of the two-dimensional coordinate values, the claws with gait changes are specifically identified.

[0064] An image monitoring device above the track is used to take pictures of the back of the experimental mouse. The experimental mouse in the moving state is determined from the captured video stream, and the start time t1 and the end time t2 of the experimental mouse's movement are determined. Combining with the running speed of the treadmill track, the movement distance of the experimental mouse is determined.

[0065] Therefore, this embodiment can simultaneously monitor the movement distance of the experimental mouse and the gait information changes of the four claws.

[0066] In addition, multiple treadmills are connected in series. Experimental mice of different volumes are respectively placed on each treadmill. Each experimental mouse also monitors the movement distance of the experimental mouse and the gait information changes of the four claws according to the above independent real-time monitoring method. Therefore, this embodiment can also simultaneously and independently identify, track, and record the gait images and important movement parameters (running distance, movement time) of several mice of different sizes. Compared with the traditional method, the experimental efficiency is greatly improved. At the same time, more experimental animals are in the same experimental environment for experiments, improving the accuracy of the experimental results.

[0067] In the step 200, the image monitoring device under the treadmill is used to take pictures of the abdomen of the experimental mouse on the treadmill track. The processing system is used to receive the abdominal image of the experimental mouse taken by the image monitoring device under the treadmill, and construct a gait change recognition model of the experimental mouse based on the abdominal image of the experimental mouse. The specific implementation method is as follows:

[0068] (1) The processing system processes the abdominal images of the experimental mice to extract the images of the four paws of each experimental mouse in each abdominal image.

[0069] (2) Obtain the central positions of the four paws of the experimental mouse, connect the central positions of the four paws in sequence to form a quadrilateral, and connect the central positions of the opposite two paws to form a diagonal line. Construct a two-dimensional coordinate system with the intersection point of the diagonal line as the origin, so that the four paws of the experimental mouse are respectively in the four quadrants of the two-dimensional coordinate system.

[0070] (3) Integrate the intersection point of the diagonal line of the four paws extracted in real time from the abdominal image onto the origin of the two-dimensional coordinate system, and record the two-dimensional coordinate values of the paws corresponding to the central position of the paws extracted each time to form a gait change recognition model. The two-dimensional coordinate values of the central position of each paw form a gait information set, which are set A, set B, set C, and set D respectively. Among them, set A and set C correspond to the gait information sets of the two paws on the diagonal line, and set B and set D correspond to the gait information sets of the other two paws on the diagonal line.

[0071] (4) Compare in real time the two-dimensional coordinate values of the paws corresponding to each shooting in each gait information set, and determine the change rule of the two-dimensional coordinate values of the paws in each gait information set through the gait change recognition model to identify the experimental mouse paws with gait changes.

[0072] The specific implementation method for determining the change rule of the two-dimensional coordinate values of the paws in each gait information set through the gait change recognition model to identify the experimental mouse paws with gait changes is as follows:

[0073] Construct a monitoring time axis, integrate the two-dimensional coordinate values of each paw in each gait information set onto the monitoring time axis, compare the two-dimensional coordinate value of the paw corresponding to a certain time point with the two-dimensional coordinate value of the paw corresponding to the previous time point to determine whether the gait of the paw has changed, and determine the number of gait information sets in which the two-dimensional coordinate value of the paw changes.

[0074] When only the two-dimensional coordinate values of the paws in one gait information set change, the paw corresponding to the gait information set with the change has a gait change.

[0075] In the actual experiment process, when the mouse runs in this case, only the two-dimensional coordinate value of one paw changes compared with the two-dimensional coordinate value of the steady gait of this paw, which means that this paw moves along the diagonal direction of this paw, so there is a situation where only the two-dimensional coordinate value of one paw changes. At this time, it can be directly confirmed that the paw at this position has a gait change when running.

[0076] When the two-dimensional coordinate values of the rat claws in all gait information sets change, obtain the changed two-dimensional coordinate values of the rat claws in each of the gait information sets and form a set of variant changes.

[0077] Determine the relationship between the straight line formed by the changed two-dimensional coordinate values of the rat claws in the set of variant changes and the two diagonals. Take the rat claws corresponding to the changed two-dimensional coordinate values of the rat claws in the set of variant changes that are on the same straight line as the rat claws without gait changes, and take the rat claws corresponding to the set of variant changes where the changed two-dimensional coordinate values of the rat claws in the set of variant changes cannot be on the same straight line as the rat claws with gait changes.

[0078] In the actual experimental process, when the rat runs in this situation, when the gait change direction of at least one rat claw is not along its corresponding diagonal direction but randomly changes its position, the change in the position of the diagonal intersection point of the four rat claws is relatively large. When integrating the diagonal intersection point of the four rat claws into the two-dimensional coordinate system for constructing the steady-state gait, it causes the two-dimensional coordinate values of all four rat claws to change. However, only the central position coordinates of the rat claws with random gait changes are unstable, while the central position coordinates of the other rat claws that change passively with the gait changes of these rat claws have a certain pattern, that is, the central position coordinates of their rat claws still lie on their corresponding diagonals or are parallel to one of the diagonals. Based on the change pattern of the central position coordinates of the rat claws, it is still possible to determine the rat claws with gait changes.

[0079] When determining the relationship between the straight line formed by the changed two-dimensional coordinate values of the rat claws in the set of variant changes and the two diagonals, determine the diagonal equations corresponding to the gait information sets of the two rat claws on the diagonal in real time, and then determine whether the straight line where the two-dimensional coordinate values of the rat claws in the set of variant changes extracted from each gait information set are located is parallel to the diagonal to determine the rat claws with gait changes. Among them, the implementation method for constructing the diagonal equations corresponding to the gait information sets of the two rat claws on the diagonal is as follows:

[0080] Determine the straight line equation formed by the two-dimensional coordinate values of the rat claws in the gait information sets corresponding to the two rat claws on the diagonal:

[0081] Y(A, C) = k1 * x;

[0082]

[0083] In the formula, xa(i) is the X coordinate value of the rat claw in set A, xc(i) is the X coordinate value of the rat claw in set C, ya(i) is the Y coordinate value of the rat claw in set A, yc(i) is the Y coordinate value of the rat claw in set C, and i is the coordinate value corresponding to the same i-th time point in set A and set C;

[0084] Y(B, D) = k2 * x;

[0085]

[0086] Wherein, xb(i) is the X coordinate value of the mouse paw in set B, xd(i) is the X coordinate value of the mouse paw in set D, yb(i) is the Y coordinate value of the mouse paw in set B, yd(i) is the Y coordinate value of the mouse paw in set D, and i is the coordinate value corresponding to the same ith time point in set B and set D.

[0087] The implementation method for determining the straight line where the two-dimensional coordinate values of the mouse paw in the abnormal change set extracted from each gait information set are located is as follows:

[0088] Compare each group of two-dimensional coordinate values of the mouse paw in each abnormal change set with the two-dimensional coordinate values of the mouse paw corresponding to the previous time point to determine the straight line inclination angle kj formed by the two groups of two-dimensional coordinate values of the mouse paw:

[0089]

[0090] Wherein, xa(j) is the X coordinate value of the mouse paw corresponding to a certain time point in the abnormal change set extracted from the A set, xa(j - 1) is the X coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned certain time point, ya(j) is the Y coordinate value of the mouse paw corresponding to a certain time point in the abnormal change set extracted from the A set, and ya(j - 1) is the Y coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned certain time point;

[0091]

[0092] Wherein, xb(j) is the X coordinate value of the mouse paw corresponding to a certain time point in the abnormal change set extracted from the B set, xb(j - 1) is the X coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned certain time point, yb(j) is the Y coordinate value of the mouse paw corresponding to a certain time point in the abnormal change set extracted from the B set, and yb(j - 1) is the Y coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned certain time point;

[0093]

[0094] Wherein, xc(j) is the X coordinate value of the mouse paw corresponding to a certain time point in the abnormal change set extracted from the C set, xc(j - 1) is the X coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned certain time point, yc(j) is the Y coordinate value of the mouse paw corresponding to a certain time point in the abnormal change set extracted from the C set, and yc(j - 1) is the Y coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned certain time point;

[0095]

[0096] Among them, xd(j) is the mouse claw X coordinate value corresponding to a certain time point in the abnormal change set extracted from the D set, xd(j - 1) is the mouse claw X coordinate value corresponding to the previous time point of the above-mentioned certain time point, yd(j) is the mouse claw Y coordinate value corresponding to a certain time point in the abnormal change set extracted from the D set, and yd(j - 1) is the mouse claw Y coordinate value corresponding to the previous time point of the above-mentioned certain time point.

[0097] When determining whether the straight line where the mouse claw two-dimensional coordinate values in the abnormal change set extracted from each gait information set are located is parallel to the diagonal line, compare Ka(j) with Kc(j). When Ka(j) is the same as Kc(j), it is considered that there is no gait change in the mouse claw positions corresponding to the A set and the C set.

[0098] When Ka(j) is different from Kc(j), compare Ka(j) with k2 and Kc(j) with k2 respectively. Determine the mouse claw position corresponding to the Ka(j) or Kc(j) that is the same as k2 as the mouse claw without gait change, and determine the mouse claw position corresponding to the Ka(j) or Kc(j) that is different from k2 as the mouse claw with gait change.

[0099] Similarly, compare Kb(j) with Kd(j). When Kb(j) is the same as Kd(j), it is considered that there is no gait change in the mouse claw positions corresponding to the B set and the D set.

[0100] When Kb(j) is different from Kd(j), compare Kb(j) with k1 and Kd(j) with k1 respectively. Determine the mouse claw position corresponding to the Kb(j) or Kd(j) that is the same as k1 as the mouse claw without gait change, and determine the mouse claw position corresponding to the Kb(j) or Kd(j) that is different from k1 as the mouse claw with gait change.

[0101] Suppose the mouse claw images captured by the image monitoring device under the treadmill are named A mouse claw, B mouse claw, C mouse claw, and D mouse claw in the order of upper right, upper left, lower left, and lower right. Then the two-dimensional coordinate values of the A mouse claw are integrated into the A set, the two-dimensional coordinate values of the B mouse claw are integrated into the B set, the two-dimensional coordinate values of the C mouse claw are integrated into the C set, and the two-dimensional coordinate values of the D mouse claw are integrated into the D set.

[0102] Independently monitor the two-dimensional coordinate values of the mouse claws in the A set, B set, C set, and D set respectively. When the two-dimensional coordinate values of the mouse claws in the A set, B set, C set, and D set change simultaneously, then determine in real time when each coordinate value change is extracted, and calculate the straight line equation formed by the two-dimensional coordinate value corresponding to this time point in the A set and the two-dimensional coordinate value corresponding to the same time point in the C set. k1 represents its inclination angle.

[0103] Calculate the linear equation formed by the two-dimensional coordinate values corresponding to this time point in set B and the two-dimensional coordinate values corresponding to the same time point in set D, where k2 represents its inclination angle.

[0104] Suppose the gait information of the C mouse's paw changes. Then, in the abnormal change set within set C corresponding to this change time, the inclination angle Kc(j) of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within this abnormal change set is constantly changing. And the inclination angle Kc(j) of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within the abnormal change set in set C is the same as k2, the inclination angle Kb(j) of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within the abnormal change set in set B is the same as k2, and the inclination angle Kd(j) of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within the abnormal change set in set D is also the same as k2.

[0105] Similarly, suppose the gait information of the B mouse's paw changes. Then, in the abnormal change set within set B corresponding to this change time, the inclination angle Kb(j) of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within this abnormal change set is constantly changing. And the inclination angle Ka(j) of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within the abnormal change set in set A is the same as k1, the inclination angle Kc(j) of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within the abnormal change set in set C is the same as k1, and the inclination angle Kd(j) of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within the abnormal change set in set D is also the same as k1.

[0106] Therefore, only by determining the parallel relationship between the inclination angle of the straight line formed by every two groups of two-dimensional coordinate values of the mouse's paw within the abnormal change set where the gait information changes and the inclination angle of the diagonal line can the mouse's paw with gait changes be determined.

[0107] In the step 400, the image monitoring device above the treadmill is used to take a video of the experimental mouse on the treadmill runway, forming a back recording video stream of the experimental mouse, and recording the time point t1 corresponding to when there is an experimental mouse in the captured video and the treadmill starts;

[0108] The processing system synchronously processes the video transmitted by the image monitoring device above the treadmill to identify the experimental mouse in the captured video, and records the corresponding time point t2 when no experimental mouse is recognized in the captured video;

[0109] Combine the time point t1 and the time t2 to calculate the motion parameters of the experimental mouse.

[0110] The motion parameter S of the experimental mouse = V * (t2 - t1), where V is the motion speed of the treadmill.

[0111] When it is recognized that there is a laboratory mouse in the captured video, but the position of the laboratory mouse is at the bottom of the running track of the treadmill and remains at the bottom of the running track of the treadmill for more than a set threshold, record the time point t2 corresponding to when the laboratory mouse stops running.

[0112] This embodiment can simultaneously and independently identify, track, and record the gait images and important motion parameters (running distance, motion time) of several laboratory mice respectively. Compared with the traditional method, the experimental efficiency is greatly improved. By conducting gait change confirmation experiments and mouse motor ability experiments on experimental animals in the same experimental environment, it is possible to simultaneously identify and analyze the movement gait and motion parameters of laboratory mice. Moreover, this embodiment can not only identify the motion time when the gait of the laboratory mouse changes, but also specifically determine the position of the mouse paw where the gait change specifically occurs, which is convenient for providing data support for gait changes and the health of mice.

[0113] The above embodiments are only exemplary embodiments of the present application and are not used to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art can make various modifications or equivalent replacements within the essence and protection scope of the present application, and such modifications or equivalent replacements should also be regarded as falling within the protection scope of the present application.

Claims

1. A method for synchronously identifying the gait and motion parameters of experimental mice, characterized in that: The following steps are involved: Step 100: placing at least one experimental mouse on a corresponding treadmill track, and driving the track to rotate so that the experimental mouse can move on the track; Step 200: Use image monitoring devices disposed above and below the runway of each treadmill to capture images of the experimental mouse on the runway of the treadmill, perform image processing on the captured images through a processing system, construct a gait change recognition model of the experimental mouse, and construct a two-dimensional coordinate system with the intersection of the diagonals of the quadrilateral where the four feet of the experimental mouse are located as the origin, so that the four feet of the experimental mouse are respectively in four quadrants of the two-dimensional coordinate system; Step 300, forming a gait information set from the two-dimensional coordinate values ​​of the paws corresponding to each foot, analyzing the gait information set to obtain the gait information changes of each foot of the experimental mouse, and determining the specific foot position where the gait change occurs based on the change rules corresponding to the two-dimensional coordinate values ​​of the paws where the gait information changes occur; Step 400: Calculate the motion parameters of the experimental mice based on the working parameters of the treadmill and the images taken by the image monitoring device above the treadmill, so as to independently track and identify the gait image and motion parameters of each mouse.

2. A method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 1, characterized in that: In step 100, the track of the treadmill is a transparent structure, and an image monitoring device disposed below the track of the treadmill can photograph the abdomen of the experimental mouse on the track to obtain the positions of the four feet of the experimental mouse.

3. A method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 2, characterized in that: In step 200, the image monitoring device under the treadmill is used to photograph the abdomen of the experimental mouse on the treadmill track, and the processing system is used to receive the abdominal image of the experimental mouse photographed by the image monitoring device under the treadmill, and construct a gait change recognition model of the experimental mouse based on the abdominal image of the experimental mouse. The specific implementation method is: The processing system performs image processing on the abdominal images of the experimental mouse to extract images of four paws of the experimental mouse in each abdominal image; Obtain the center positions of the four paws of the experimental mouse, connect the center positions of the four paws in sequence to form a quadrilateral, and connect the center positions of two opposite paws to form a diagonal line, and construct a two-dimensional coordinate system with the intersection of the diagonals as the origin, so that the four paws of the experimental mouse are respectively in four quadrants of the two-dimensional coordinate system; The intersection points of the diagonals of the four paws extracted from the abdominal image in real time are integrated into the origin of the two-dimensional coordinate system, and the two-dimensional coordinate values ​​of the paws corresponding to the center positions of the paws extracted each time are recorded to form a gait change recognition model, and the two-dimensional coordinate values ​​of the paws at the center positions of each paw are formed into gait information sets, namely, set A, set B, set C and set D, wherein set A and set C correspond to the gait information sets of the two paws on the diagonal, and set B and set D correspond to the gait information sets of the other two paws on the diagonal; The two-dimensional coordinate values ​​of the mouse paw corresponding to each shot in each gait information set are compared in real time, and the change pattern of the two-dimensional coordinate values ​​of the mouse paw in each gait information set is determined by the gait change recognition model to identify the experimental mouse paw with gait changes.

4. A method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 3, characterized in that: In step 300, the specific implementation method of determining the change rule of the two-dimensional coordinate value of the mouse paw in each gait information set through the gait change recognition model to identify the experimental mouse paw with gait change is: Constructing a monitoring time axis, integrating each two-dimensional coordinate value of the mouse paw in each gait information set into the monitoring time axis, comparing the two-dimensional coordinate value of the mouse paw corresponding to a certain time point with the two-dimensional coordinate value of the mouse paw corresponding to the previous time point to determine whether the gait of the mouse paw has changed, and determining the number of the gait information sets in which the two-dimensional coordinate value of the mouse paw has changed; When only one of the two-dimensional coordinate values ​​of the mouse paw in the gait information set changes, the mouse paw corresponding to the changed gait information set undergoes a gait change; When the two-dimensional coordinate values ​​of the mouse paw in all gait information sets change, the two-dimensional coordinate values ​​of the mouse paw that have changed in each gait information set are obtained to form a mutation set; Determine the relationship between the straight line formed by the two-dimensional coordinate values ​​of the mouse paws that have changed in the mutation set and the two diagonal lines, and take the mouse paws corresponding to the mutation set where the two-dimensional coordinate values ​​of the mouse paws that have changed in the mutation set are on the same straight line as the mouse paws that have not shown gait changes, and take the mouse paws corresponding to the mutation set where the two-dimensional coordinate values ​​of the mouse paws that have changed in the mutation set cannot be on the same straight line as the mouse paws that have shown gait changes.

5. A method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 4, characterized in that: When determining the relationship between the straight line formed by the two-dimensional coordinate values ​​of the paws that have changed in the mutation set and the two diagonals, the diagonal equations corresponding to the gait information set corresponding to the two paws on the diagonal are determined in real time, and then it is determined whether the straight line on which the two-dimensional coordinate values ​​of the paws in the mutation set extracted from each gait information set are located is parallel to the diagonal to determine the paws with gait changes, wherein the implementation method of constructing the diagonal equations corresponding to the gait information set corresponding to the two paws on the diagonal is: Determine the equation of the line formed by the two-dimensional coordinate values ​​of the paws in the gait information set corresponding to the two paws on the diagonal line: Y(A,C)=k1*x; Where xa(i) is the X-coordinate value of the mouse paw in set A, xc(i) is the X-coordinate value of the mouse paw in set C, ya(i) is the Y-coordinate value of the mouse paw in set A, yc(i) is the Y-coordinate value of the mouse paw in set C, and i is the coordinate value corresponding to the same i-th time point in sets A and C; Y(B,D)=k2*x; Where xb(i) is the X-coordinate value of the mouse paw in set B, xd(i) is the X-coordinate value of the mouse paw in set D, yb(i) is the Y-coordinate value of the mouse paw in set B, yd(i) is the Y-coordinate value of the mouse paw in set D, and i is the coordinate value corresponding to the same i-th time point in set B and set D.

6. A method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 5, characterized in that: The method for determining the straight line on which the two-dimensional coordinate values ​​of the mouse paw in the variation set extracted from each gait information set lie is as follows: Compare each set of two-dimensional coordinate values ​​of the mouse paw in each mutation set with the two-dimensional coordinate values ​​of the mouse paw corresponding to the previous time point to determine the inclination angle kj of the straight line formed by the two sets of two-dimensional coordinate values ​​of the mouse paw: Wherein, xa(j) is the X coordinate value of the mouse paw corresponding to a certain time point in the mutation set extracted from the A set, xa(j-1) is the X coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned time point, ya(j) is the Y coordinate value of the mouse paw corresponding to a certain time point in the mutation set extracted from the A set, and ya(j-1) is the Y coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned time point; Wherein, xb(j) is the X coordinate value of the mouse paw corresponding to a certain time point in the mutation set extracted from the B set, xb(j-1) is the X coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned time point, yb(j) is the Y coordinate value of the mouse paw corresponding to a certain time point in the mutation set extracted from the B set, and yb(j-1) is the Y coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned time point; Wherein, xc(j) is the X coordinate value of the mouse paw corresponding to a certain time point in the mutation set extracted from the C set, xc(j-1) is the X coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned time point, yc(j) is the Y coordinate value of the mouse paw corresponding to a certain time point in the mutation set extracted from the C set, and yc(j-1) is the Y coordinate value of the mouse paw corresponding to the previous time point of the above-mentioned time point; Among them, xd(j) is the X coordinate value of the mouse paw corresponding to a certain time point in the mutation set extracted from the D set, xd(j-1) is the X coordinate value of the mouse paw corresponding to the previous time point of the above time point, yd(j) is the Y coordinate value of the mouse paw corresponding to a certain time point in the mutation set extracted from the D set, and yd(j-1) is the Y coordinate value of the mouse paw corresponding to the previous time point of the above time point.

7. A method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 6, characterized in that: When determining whether the straight line where the two-dimensional coordinate values ​​of the mouse paw in the variation set extracted from each gait information set are located is parallel to the diagonal line, Ka(j) is compared with Kc(j). When Ka(j) is the same as Kc(j), it is considered that the mouse paw position corresponding to the A set and the mouse paw position corresponding to the C set have no gait changes; When Ka(j) and Kc(j) are different, Ka(j) is compared with k2 and Kc(j) is compared with k2, and the paw position corresponding to Ka(j) or Kc(j) that is the same as k2 is judged as the paw without gait change, and the paw position corresponding to Ka(j) or Kc(j) that is different from k2 is judged as the paw with gait change; Similarly, Kb(j) is compared with Kd(j). When Kb(j) is the same as Kd(j), it is considered that the paw positions corresponding to the B set and the paw positions corresponding to the D set have no gait changes. When Kb(j) is different from Kd(j), Kb(j) is compared with k1 and Kd(j) is compared with k1 respectively, and the paw position corresponding to Kb(j) or Kd(j) that is the same as k1 is judged as the paw without gait change, while the paw position corresponding to Kb(j) or Kd(j) that is different from k1 is judged as the paw with gait change.

8. The method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 1, characterized in that: In step 400, the image monitoring device above the treadmill is used to shoot a video of the experimental mouse on the treadmill track to form a video stream of the back of the experimental mouse, and record the time point t1 corresponding to the presence of the experimental mouse in the shot video and the start of the treadmill; The processing system synchronously processes the video transmitted by the image monitoring device above the treadmill to identify the experimental mouse in the captured video, and records the corresponding time point t2 when it is identified that there is no experimental mouse in the captured video; The movement parameters of the experimental mouse are calculated by combining time point t1 and time t2.

9. A method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 8, characterized in that: The motion parameter of the experimental mouse is S=V*(t2-t1), where V is the motion speed of the treadmill.

10. The method for synchronously identifying the movement gait and movement parameters of experimental mice according to claim 8, characterized in that: When it is identified that there is an experimental mouse in the captured video, but the position of the experimental mouse is at the bottom of the treadmill runway, and when the maintenance of the bottom of the treadmill runway exceeds the set threshold, the time point t2 corresponding to when the experimental mouse stops running is recorded.

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