Children action coordination development ability assessment method and device

Abstract

The invention provides a children action coordination development ability assessment method and device, and relates to the technical field of data processing. The method comprises the following steps: acquiring behavior images and monitoring data of a to-be-evaluated child when completing different preset evaluation tasks, wherein the monitoring data comprises task duration and motion data of a target detection object; determining a human body posture parameter corresponding to the to-be-evaluated child according to the behavior image; determining a corresponding evaluation task combination under each evaluation dimension, and determining dimension scores corresponding to different evaluation dimensions according to human body posture parameters and task duration corresponding to each evaluation task in the evaluation task combination and motion data of the target detection object; and determining the action coordination development ability level of the to-be-evaluated child based on the dimension scores under all the evaluation dimensions. According to the technical scheme provided by the invention, the accuracy and applicability of the children action coordination development ability evaluation method can be improved.

Description

Background Art

[0002] As a common neurodevelopmental disorder, children's motor coordination disorder has a significant impact on children's daily life and learning activities. At present, the assessment of children's motor coordination development ability mainly relies on a series of manual assessment tools, such as BOT-2 (Bruininks-Oseretsky Test of Motor Proficiency Second Edition) and MABC-2 (Movement Assessment Battery for Children Second Edition). The children under test complete the predetermined movement tasks according to the assessment requirements, and the testers observe, evaluate and record the completion of these tasks, so as to evaluate the motor coordination development ability of the children under test.

[0003] However, the above evaluation methods require high professional skills from testers, which limits their applicability and popularity. And because the evaluation process relies on the observation and judgment of testers, there may be subjective differences between different testers, resulting in poor consistency of evaluation standards, thus affecting the accuracy of the evaluation results.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the embodiments of the present disclosure is to provide a method for evaluating children's motor coordination development ability, a device for evaluating children's motor coordination development ability, an electronic device and a computer-readable storage medium, thereby improving the accuracy and applicability of the method for evaluating children's motor coordination development ability at least to a certain extent.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to a first aspect of an embodiment of the present disclosure, a method for evaluating a child's motor coordination development ability is provided, comprising: obtaining behavioral images and monitoring data of a child to be evaluated when the child completes different preset evaluation tasks, the monitoring data including task duration and motion data of a target detection object; determining human posture parameters corresponding to the child to be evaluated based on the behavioral images; determining a combination of evaluation tasks corresponding to each evaluation dimension, and determining dimension scores corresponding to different evaluation dimensions based on the human posture parameters, task duration and motion data of the target detection object corresponding to each evaluation task in the combination of evaluation tasks; and determining the motor coordination development ability level of the child to be evaluated based on the dimension scores under all evaluation dimensions.

[0008] In some example embodiments of the present disclosure, based on the aforementioned scheme, the evaluation dimensions include a planning dimension, a control dimension, a rhythm dimension, and a coordination dimension, and based on the task score, the child's motor coordination development ability is evaluated through multiple evaluation dimensions, including: according to the weight coefficients corresponding to the planning dimension, the control dimension, the rhythm dimension, and the coordination dimension, weighted summing the dimension scores to obtain a weighted score; determining the motor coordination development ability level of the child to be evaluated according to the weighted score.

[0009] In some example embodiments of the present disclosure, based on the aforementioned scheme, the planning dimension, control dimension, rhythm dimension and coordination dimension respectively include one or more of the tasks of transporting objects, throwing targets, placing objects, billiards, balancing with arms, catching balls, rotating balls on trays, walking through mazes, drawing tracks, pushing balls, walking diagonally with legs together, and jumping grids.

[0010] In some example embodiments of the present disclosure, based on the aforementioned scheme, in the object transporting task, the child to be evaluated is scored based on the holding state of the target detection object, the deviation of the walking route from the predetermined route, and the touching of the target detection object by body parts; in the target throwing task, the child to be evaluated is scored based on the throwing performance and catching ability of the target detection object; in the object placement task, the child to be evaluated is scored based on the placement of the target detection object by the dominant hand and the non-dominant hand; in the billiards task, the child to be evaluated is scored based on the contact of the target detection object with the ball; in the arm extension balance task, the child to be evaluated is scored based on the holding state and holding time of the target detection object. Scoring; in the ball catching task, the child to be evaluated is scored based on the rebound of the target detection object and the number of times the ball is caught; in the tray ball turning task, the child to be evaluated is scored based on the lifting of the target detection object and the moving trajectory; in the maze walking task, the child to be evaluated is scored based on the accuracy of the maze path completed by the child to be evaluated; in the trajectory drawing task, the child to be evaluated is scored based on the movement trajectory drawn by the child to be evaluated; in the ball pushing task, the child to be evaluated is scored based on the performance of pushing the target detection object; in the diagonal leg-joining task, the child to be evaluated is scored based on the diagonal leg-joining movement; in the grid jumping task, the child to be evaluated is scored based on the grid adjustment performance.

[0011] In some example embodiments of the present disclosure, based on the aforementioned scheme, the monitoring data also includes physiological data and emotional data, then the determination of the motor coordination development ability level of the child to be evaluated based on the dimension scores under all evaluation dimensions includes: determining a first correction coefficient based on the physiological data; determining a second correction coefficient based on the emotional data; correcting the task scores in all evaluation dimensions according to the first correction coefficient and the second correction coefficient to obtain a corrected score; and determining the motor coordination development ability level of the child to be evaluated based on the corrected score.

[0012] In some example embodiments of the present disclosure, based on the aforementioned scheme, a first correction coefficient is determined according to the physiological data, including: comparing the physiological data corresponding to different assessment tasks with a preset physiological assessment standard to obtain a plurality of comparison results; and adjusting the first benchmark coefficient according to the plurality of comparison results to obtain the first correction coefficient.

[0013] In some example embodiments of the present disclosure, based on the aforementioned scheme, the adjusting of the first baseline coefficient according to the multiple comparison results includes: in response to the physiological data not satisfying the preset physiological evaluation standard, reducing the first baseline coefficient; or, in response to the physiological data satisfying the preset physiological evaluation standard, increasing the first baseline coefficient.

[0014] In some example embodiments of the present disclosure, based on the aforementioned scheme, the process of acquiring the motion data of the target detection object includes: using a target detection algorithm to perform target detection on the behavior image to obtain a detection object image; performing feature point extraction on the detection object image to obtain feature point coordinates; and determining the motion data of the target detection object based on the feature point coordinates.

[0015] In some example embodiments of the present disclosure, based on the aforementioned scheme, determining the human posture parameters corresponding to the child according to the behavioral image includes: performing target detection on the behavioral image to obtain a child image; performing human posture estimation based on the child image to identify human body key points; and determining the human posture parameters corresponding to the child according to the human body key points.

[0016] According to a second aspect of an embodiment of the present disclosure, a device for evaluating children's motor coordination development ability is provided, comprising: a data acquisition module, used to acquire behavioral images and monitoring data of a child to be evaluated when the child completes different preset evaluation tasks, the monitoring data including task duration and motion data of a target detection object; a posture image module, used to determine the human posture parameters corresponding to the child to be evaluated based on the behavioral image; a task scoring module, used to determine the evaluation task combination corresponding to each evaluation dimension, and determine the dimension scores corresponding to different evaluation dimensions based on the human posture parameters, task duration and motion data of the target detection object corresponding to each evaluation task in the evaluation task combination; and an ability evaluation module, used to determine the motor coordination development ability level of the child to be evaluated based on the dimension scores under all evaluation dimensions.

[0017] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, comprising: a processor; and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the above-mentioned method for assessing the development ability of children's motor coordination is implemented.

[0018] According to a fourth aspect of an embodiment of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method for evaluating the motor coordination development ability of children as described above is implemented.

[0019] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects: The method for evaluating the development ability of children's action coordination in the exemplary embodiment of the present disclosure, on the one hand, can automatically evaluate the actual performance of children by acquiring and analyzing the behavioral images and monitoring data when children complete tasks, and reduce the deviation caused by subjective judgment. On the other hand, combined with the human posture parameters, task duration and the motion data of the target detection object, the children's action coordination development ability is evaluated from multiple angles to ensure that the evaluation results are more comprehensive and reliable. On the other hand, through the quantitative scoring of task combination and each dimension, the relationship between task duration, posture parameters and motion data can be comprehensively considered to form a more comprehensive evaluation dimension. The determination of the scores of each dimension can specifically quantify the performance of children in different action coordination tasks, thereby ensuring that the evaluation results are more targeted and meticulous, and help to provide standardized and objective evaluation basis for the performance of different children in action coordination. Further, the automated image processing and data analysis process reduces the time required for evaluation and the professional requirements for testers. Thus, the accuracy and applicability of the method for evaluating the development ability of children's action coordination are improved to a certain extent.

[0020] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0022] Figure 1 The following is a schematic diagram of a flow chart of a method for evaluating a child's motor coordination development ability according to some embodiments of the present disclosure.

[0023] Figure 2 A schematic diagram of a task of transporting items according to some embodiments of the present disclosure is schematically shown.

[0024] Figure 3 A schematic diagram of a target throwing task according to some embodiments of the present disclosure is schematically shown.

[0025] Figure 4 A schematic diagram of an item placement task according to some embodiments of the present disclosure is schematically shown.

[0026] Figure 5 A schematic diagram of a billiards task according to some embodiments of the present disclosure is schematically shown.

[0027] Figure 6A schematic diagram of a boom balancing task according to some embodiments of the present disclosure is schematically shown.

[0028] Figure 7 A schematic diagram of a ball catching task according to some embodiments of the present disclosure is schematically shown.

[0029] Figure 8 A schematic diagram of a tray ball turning task according to some embodiments of the present disclosure is schematically shown.

[0030] Fig. 9 A schematic diagram of a maze walking task according to some embodiments of the present disclosure is schematically shown.

[0031] Fig.10 A schematic diagram of a trajectory drawing task according to some embodiments of the present disclosure is schematically shown.

[0032] Fig.11 A schematic diagram of a ball pushing task according to some embodiments of the present disclosure is schematically shown.

[0033] Fig.12 A schematic diagram of a diagonal leg-joining task according to some embodiments of the present disclosure is schematically shown.

[0034] Fig.13 A schematic diagram of a skipping task according to some embodiments of the present disclosure is schematically shown.

[0035] Fig.14 A block diagram of a device for evaluating children's motor coordination development ability according to some embodiments of the present disclosure is schematically shown.

[0036] Fig.15 A schematic diagram of the structure of a computer system of an electronic device according to some embodiments of the present disclosure is schematically shown.

[0037] Fig.16 A schematic diagram of a computer-readable storage medium according to some embodiments of the present disclosure is schematically shown.

[0038] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0039] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this specification. Instead, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

[0040] The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit this specification. The singular forms "a", "the" and "the" used in this specification and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0041] It should be understood that although the terms first, second, third, etc. may be used in this specification to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this specification, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0042] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more comprehensive and complete and will fully convey the concept of the example embodiments to those skilled in the art.

[0043] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0044] Furthermore, the drawings are only schematic illustrations and are not necessarily drawn to scale. The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0045] Childhood motor coordination disorder is a common form of neurodevelopmental disorder, which has a significant impact on children's daily life and learning activities. In related technologies, the assessment of children's motor coordination development ability mainly uses a series of manual assessment tools, such as BOT-2 and MABC-2. In these assessments, the children under test need to complete specific motor tasks according to the assessment requirements, and the testers observe, evaluate and record the completion of these tasks to evaluate the motor coordination development ability of the children under test.

[0046] However, the above-mentioned related technologies require high professional skills of testers, which limits the applicability and popularity of the evaluation methods. In addition, the evaluation relies heavily on the observation and judgment of testers. There may be subjective differences between different testers, resulting in poor consistency of evaluation standards, and subjective differences often affect the accuracy of evaluation results.

[0047] In order to solve all or part of the technical problems in the above-mentioned related technologies, in an exemplary embodiment of the present disclosure, a method for evaluating children's motor coordination development ability is firstly provided.

[0048] Figure 1 The following is a schematic diagram of a process flow of a method for evaluating a child's motor coordination development ability according to some embodiments of the present disclosure. Figure 1 As shown, the method for evaluating children's motor coordination development ability may include the following steps: Step S110, obtaining behavioral images and monitoring data of the child to be evaluated when completing different preset evaluation tasks, the monitoring data including task duration and movement data of the target detection object; Step S120, determining the human body posture parameters corresponding to the child to be evaluated according to the behavior image; Step S130, determining the evaluation task combination corresponding to each evaluation dimension, and determining the dimension scores corresponding to different evaluation dimensions according to the human posture parameters, task duration and motion data of the target detection object corresponding to each evaluation task in the evaluation task combination; Step S140, determining the motor coordination development ability level of the child to be evaluated based on the dimension scores under all evaluation dimensions.

[0049] Specifically, first, in a preset assessment environment, observe and record the behavioral performance of the children to be assessed as they complete a series of assessment tasks, use a video camera or other image capture device to capture images of the children's behavior, and ensure that the image quality can be used for subsequent analysis. At the same time, use sensors or other monitoring tools to collect monitoring data related to the children's behavior, including but not limited to the time required to complete the task and the motion data of the target detection objects moved by the children during the task.

[0050] Next, the child’s human posture information is extracted from the captured behavioral images, and image processing and computer vision techniques, such as posture estimation algorithms, are applied to determine the child’s specific posture at each moment and generate a series of human posture parameters of the child during the task.

[0051] Then, a score is determined for each assessment task based on human posture parameters, task duration, and motion data of the target detection object, which reflects the child's performance in the task.

[0052] Finally, the task scores obtained from different assessment tasks are used to comprehensively evaluate children's motor coordination development ability from multiple assessment dimensions (such as planning dimension, control dimension, rhythm dimension, and coordination dimension, etc.). The scoring data are analyzed to identify the strengths and weaknesses of children in motor coordination development. Based on the assessment results, personalized feedback and suggestions are provided to children to promote the improvement of their motor coordination ability.

[0053] The method for evaluating the development ability of children's movements in the above-mentioned example embodiments, on the one hand, can automatically evaluate the actual performance of children by acquiring and analyzing the behavioral images and monitoring data when children complete tasks, and reduce the deviation caused by subjective judgment. On the other hand, combined with the human posture parameters, task duration and the motion data of the target detection object, the children's movement coordination development ability is evaluated from multiple angles to ensure that the evaluation results are more comprehensive and reliable. On the other hand, through the quantitative scoring of task combination and each dimension, the relationship between task duration, posture parameters and motion data can be comprehensively considered to form a more comprehensive evaluation dimension. The determination of the scoring of each dimension can specifically quantify the performance of children in different movement coordination tasks, thereby ensuring that the evaluation results are more targeted and meticulous, and help to provide standardized and objective evaluation basis for the performance of different children in movement coordination. Further, the automated image processing and data analysis process reduces the time required for evaluation and the professional requirements for testers. Thus, the accuracy and applicability of the method for evaluating the development ability of children's movements is improved to a certain extent.

[0054] Next, the method for evaluating children's motor coordination development ability in the above exemplary embodiment will be further described.

[0055] In step S110, behavioral images and monitoring data of the child to be evaluated when completing different preset evaluation tasks are obtained, and the monitoring data includes task duration and movement data of the target detection object.

[0056] Among them, the assessment task can represent a series of preset tasks used to test children's motor coordination development ability in specific situations. These tasks may include transporting objects, throwing targets, placing objects, billiards, balancing with arms, catching balls, rotating trays, walking through mazes, drawing tracks, pushing balls, diagonal legs, jumping grids and other assessment tasks. Behavioral images can represent images or video frames recorded by cameras or other image capture devices during the performance of assessment tasks by children to be assessed. Monitoring data includes but is not limited to quantitative information such as the total time required for children to complete the task and the movement trajectory of the target objects involved in the task. The target detection object can represent the target object that children need to operate or interact with in the assessment task, such as a ball, a pen or a springboard, and the motion data of the target detection object can reflect the child's motor control ability and coordination level.

[0057] In some embodiments, the motion data of the target object can be obtained by the following steps: attaching a marker to the target object, which can be a reflective ball, LED light or other object that is easily captured by a camera. Then use multiple high-frame rate cameras to continuously shoot the target object from different angles to obtain an image sequence containing the target object. Perform image analysis on each frame of the image sequence, identify and track the position of the marker point in each frame, and determine its three-dimensional coordinates. Connect the three-dimensional coordinates corresponding to the marker point in each frame of the image in chronological order to obtain the motion data of the target object.

[0058] In some embodiments, the process of acquiring the motion data of the target detection object includes: using a target detection algorithm to perform target detection on the behavior image to obtain a detection object image; extracting feature points from the detection object image to obtain feature point coordinates; and determining the motion data of the target detection object based on the feature point coordinates.

[0059] Specifically, target detection algorithms, such as the YOLO (You Only Look Once) algorithm, the R-CNN algorithm, and the Mask R-CNN algorithm, are used to perform target detection on the behavioral images of the children to be evaluated when completing the evaluation task, and the detection object image is extracted from the behavioral image. Feature point extraction is performed on the detection object image to obtain feature point coordinates, wherein the feature point can be a corner point, an edge point, or other significant image point, and the same type of feature point extraction is performed on each detection object image. Then, the feature point coordinates corresponding to each behavior image are connected in chronological order to obtain the motion data of the target detection object.

[0060] In some embodiments, the motion data of the target detection object can also be obtained by the following steps: a sensor device is set on the target detection object, wherein the sensor device can be an accelerometer, a gyroscope, a GPS module or other sensors suitable for tracking motion. In the process of completing the assessment task, the child to be assessed obtains the original motion state data from the sensor device, and the original motion state data represents the dynamic changes of the target detection object in three-dimensional space in the form of a digital signal. By applying data fusion algorithms, such as Kalman filtering, complementary filtering or multi-sensor data fusion technology, data from different sensors are integrated and processed. Using the processed data, the motion data of the target detection object is calculated by integration or state estimation methods.

[0061] In step S120, human body posture parameters corresponding to the child to be evaluated are determined according to the behavior image.

[0062] Among them, human posture parameters can represent the parameters of the spatial posture and body structure of a child at a specific moment, which can include the position, direction and possible morphological change information of various parts of the body (such as head, shoulders, waist, arms, legs, etc.).

[0063] In some embodiments, determining human body posture parameters corresponding to the child based on the behavior image specifically includes the following steps: performing target detection on the behavior image to obtain a child image; performing human body posture estimation based on the child image to identify human body key points; and determining human body posture parameters corresponding to the child based on the human body key points.

[0064] Specifically, the target detection algorithm is used to perform target detection on the behavior image to identify and locate the image area where the child is located. The image area where the child is located is separated from the background by image segmentation technology to obtain a child image. The human posture estimation model is used to perform human posture estimation on the segmented child image to identify the key points of the human body and determine the position coordinates of each key point of the human body, wherein the human posture points include but are not limited to the head, neck, shoulders, elbows, waist, knee joints, ankles, etc. The position coordinates of the detected key points of the human body are associated to obtain the human posture parameters. Among them, the human posture estimation model can be constructed by other suitable human posture estimation networks such as HRNet (High-Resolution Network) network and PoseNet network.

[0065] Furthermore, according to the characteristics of different tasks, the recognized human posture parameters are targeted. For example, in the task of transporting objects, the overall posture of the body and the movements of the limbs can be recognized, and the position information of key points such as shoulders, elbows, knees, ankles, etc. can be obtained to determine the coordination of children's movements and the stability of their gait. In the task of throwing targets, the posture parameters of the upper limbs (shoulders, elbows, wrists) and the core area of ​​the body (waist) can be identified to determine the direction and stability of the throw. In the task of placing objects, the posture parameters of the hands and wrists can be identified, and the operation accuracy and completion efficiency can be judged by combining the hand movement trajectory with the task requirements. In the billiards task, the recognized posture parameters mainly include the wrist, elbow and shoulder. The movement trajectory of the wooden block is associated with the movement trajectory of the ball to judge the reaction speed and the accuracy of the movement. In the arm balance task, the recognized posture parameters include the shoulder, elbow, wrist and waist. By analyzing the persistence time before the sandbag falls and the stability of the body posture change, the balance ability and posture control level are judged. In the ball catching task, the identified posture parameters include the wrist, elbow and shoulder, and the reaction time and completion times of the ball catching action are analyzed to judge the reaction ability and coordination. In the tray ball turning task, the identified posture parameters include the hand, wrist, shoulder and overall body posture. The coordination and control ability of the action are judged by the stability of the tray moving trajectory and the ball holding state. In the maze walking task, the identified posture parameters include the hand and wrist. The children's fine motor control ability and task planning ability are analyzed by the accuracy of the path drawn, the deviation of the trajectory and the time consumption. In the trajectory drawing task, the identified posture parameters include the hand and wrist. The accuracy and coordination ability of the action are judged by analyzing the completion degree of the drawing and the deviation of the trajectory. In the ball pushing task, the identified posture parameters include the hand, wrist, elbow and shoulder. The action control ability and task completion degree are judged by analyzing the direction and success rate of the ball pushing trajectory. In the diagonal leg-to-leg task, the identified posture parameters cover the shoulder, elbow, knee and ankle. The coordination ability and reaction speed are analyzed by the completion quality of the action and the symmetry of the body. In the grid-hopping task, the posture parameters identified include the knees, ankles and overall body posture. The coordination of the action and the accuracy of the route are judged by analyzing the degree of deviation of the jumping trajectory from the predetermined route and the time it takes to complete the action.

[0066] In step S130, the evaluation task combination corresponding to each evaluation dimension is determined, and the dimension scores corresponding to different evaluation dimensions are determined based on the human posture parameters, task duration and motion data of the target detection object corresponding to each evaluation task in the evaluation task combination.

[0067] Specifically, according to the preset evaluation dimensions, the evaluation task combination contained in each evaluation dimension is determined, and the evaluation task combination includes different tasks. Each evaluation task is associated with human body posture parameters, task duration and motion data of the target detection object; according to the relevant human body posture parameters, task duration and motion data of the target detection object of each evaluation task, the score of the task is calculated, and the score is evaluated based on the preset standards and the specific requirements of the evaluation task, reflecting the child's movement coordination, efficiency and other performance when completing the task; the task score of each evaluation task is combined with its weight coefficient in the evaluation dimension, and the dimension score of each evaluation dimension is weighted and summed to obtain the dimension score of the evaluation dimension.

[0068] Furthermore, according to the human posture parameters, task duration and motion data of the target detection object corresponding to each evaluation task in the evaluation task combination, the dimension scores corresponding to different evaluation dimensions are determined, which can be completed by multiple pairs of scoring models based on neural networks. Specifically, firstly, the human posture parameters, task duration and motion data of the target detection object are extracted, and the gender and age of the child to be evaluated are taken as part of the input vector, and the data difference is eliminated through normalization processing; then the neural network model is designed, the input layer receives the posture parameters, motion data, task duration, gender and age, the hidden layer uses CNN to extract spatial features, LSTM processes time series features, and generates a comprehensive evaluation vector through full connection layer fusion. The scoring strategy of the model is dynamically adjusted according to the age group. For example, the task scoring standards and feature weights corresponding to different age groups are determined by parameter learning in the network. Age as an input feature affects the model's weight allocation to different features, thereby ensuring that the scoring strategy adapts to the performance characteristics of different age groups. For example, for children in younger age groups, the model can increase the weight of basic action completion and task stability, while reducing the weight of accuracy and complex task completion efficiency; while for children in older age groups, the model can allocate higher weights to accuracy, coordination and task completion efficiency. During the model training process, mean square error is used as the loss function, and the parameters are adjusted through the Adam optimizer to ensure that the error between the predicted score and the actual score is minimized; in the scoring stage, the collected task data and child information are input into the model to generate the task scoring result, and the scores of each dimension are weighted and summed in combination with the task weight to obtain the final dimension score. Through the dynamically adjusted scoring strategy, the model can specifically evaluate the multi-dimensional performance of children of different age groups, providing a basis for further analysis and optimization.

[0069] Furthermore, specific evaluation tasks can be Figures 2 to 13 As shown, the evaluation rules for different evaluation tasks are introduced in detail below.

[0070] In the object delivery task, the child is scored based on the state of holding the target object, the deviation of the walking route from the planned route, and the contact of the target object with the body parts. Figure 2 As shown, the child to be evaluated 201 is in a standing position, holding a tow stick 203 vertically with one hand, and a ball 202 is placed on the tow stick 203. The child to be evaluated needs to walk 10 steps along the predetermined route without dropping the ball, and cannot hold the ball with his hands or touch the ball with other parts of the body, and his feet cannot leave the predetermined route. The behavior image, task duration, and ball movement trajectory of the child to be evaluated when completing the task are obtained and scored.

[0071] In the target throwing task, the children were scored based on their throwing performance and catching ability of the target object. Figure 3 As shown, the child to be evaluated 201 holds a ball 202 in one hand and stands facing a target wall, on which a round board 204 is provided. The child to be evaluated needs to throw the ball to the round board with one hand and catch it after it bounces back, and the ball cannot fall to the ground. A total of 5 successful catches are required. The behavior images, task duration, and ball movement trajectory of the child to be evaluated when completing the task are obtained and scored.

[0072] In the object placement task, the children were scored based on whether they used their dominant hand or non-dominant hand to place the target object. Figure 4 As shown, it can be divided into a coin-tossing task and a nail-inserting task. For a child 201 to be evaluated who is less than 7 years old, complete the coin-tossing task, first use the dominant hand to put 6 coins 206 into the box 205, and then use the non-dominant hand to put 6 coins 206 into the box 205, and obtain the behavior image and task duration of the child to be evaluated when completing the task. For a child 201 to be evaluated who is not less than 7 years old, complete the nail-inserting task, first use the dominant hand to insert 6 nails 208 into the nail board 207, and then use the non-dominant hand to insert 6 nails 208 into the nail board 207, and obtain the behavior image and task duration of the child to be evaluated when completing the task and score it.

[0073] In the billiards task, the child is scored based on how well the ball touches the target object. Figure 5 As shown, the tester 209 and the child to be evaluated 201 stand on both sides of the table. The tester pushes the ball 202 on the table in different directions toward the child to be evaluated. The child to be evaluated needs to move the wooden block 210. When the wooden block successfully contacts the ball, it is considered a success. A total of 5 successes are required. The behavior image, task duration, and movement trajectory of the wooden block of the child to be evaluated when completing the task are obtained and scored.

[0074] In the arm balance task, the children were scored based on how well they maintained the target object and how long they maintained it. Figure 6As shown, the child 201 to be evaluated stands, raises his right arm, bends his elbow to the right side of the body, and places the sandbag 211 at the elbow; then raises his left arm, bends his elbow to the left side of the body, and places the sandbag 211 at the elbow. The time the child persists before the sandbag falls during the two tests is recorded, and the sum of the two times is used as the task duration for scoring.

[0075] In the ball catching task, the children were scored based on the bounce of the target object and the number of times they caught the ball. Figure 7 As shown, the tester 209 and the child to be evaluated 201 stand at a preset distance, and the child holds a ball basket 212 in one hand. The tester throws the ball 202 to the ground, and the child needs to catch the ball with the ball basket after the ball bounces up, and needs to catch the ball 5 times in total. The behavior image and task duration of the child to be evaluated when completing the task are obtained and scored.

[0076] In the tray ball task, the children are scored based on their lifting and moving trajectory of the target object. Figure 8 As shown, the child 201 to be evaluated holds a tray 213 with one hand, and a ball 202 is placed on the tray. The child needs to start from the starting point and walk with the ball on the tray, passing through the first area, the second area, the third area, and the fourth area in sequence. The behavior image, task duration, and ball movement trajectory of the child to be evaluated when completing the task are obtained and scored.

[0077] In the maze task, the child is scored based on the accuracy of the maze path completed by the child. Fig. 9 As shown, the child to be evaluated 201 holds a paintbrush 214 in one hand and uses the paintbrush to draw a route from the bear in the upper right corner to the bear in the lower left corner on the maze diagram 215, and the route needs to pass through the apple. The behavior image, task duration, and route trajectory of the child to be evaluated when completing the task are obtained and scored.

[0078] In the trajectory drawing task, the children were scored based on the movement trajectories they drew. Fig.10 As shown, for a child 201 to be evaluated who is younger than 7 years old, a brush 214 is used to draw along the track on a simple drawing chart 216; for a child 201 to be evaluated who is not younger than 7 years old, a brush 214 is used to draw along the track on a complex drawing chart 217. The behavior images, task duration, and drawing tracks of the child to be evaluated when completing the task are obtained and scored.

[0079] In the ball pushing task, the children were scored based on their performance in pushing the target object. Fig.11As shown, the child 201 to be evaluated stands on one side of the table and uses a wooden block 210 to push a ball 202 into a ball box 218, and needs to push the ball into the ball box 5 times in total. The behavior images and task duration of the child to be evaluated when completing the task are obtained and scored.

[0080] In the diagonal leg-joining task, the child's diagonal leg-joining action is scored. Fig.12 As shown, the child 201 to be evaluated bends his knees and raises his left leg, touches his left knee with his right palm, and keeps his left hand hanging naturally, completing this action 5 times. Then, he bends his knees and raises his right leg, touches his right knee with his left palm, and keeps his right hand hanging naturally, completing the above action 5 times. The behavior images and task duration of the child to be evaluated when completing the task are obtained and scored.

[0081] In the skipping task, the children are scored based on their performance. Fig.13 As shown, the child 201 to be evaluated stands at the starting end of the springboard 219, and then jumps from the first square to the next square until the last square is reached. The behavior image and task duration of the child to be evaluated when completing the task are obtained and scored.

[0082] Of course, in other embodiments of the present disclosure, the task scores corresponding to different evaluation tasks can also be determined based on the comparison results of human posture parameters and standard posture parameters, the comparison results of the moving trajectory of the target detection object and the standard trajectory, and the task duration. Among them, the standard posture parameters can represent the standard child posture set for each evaluation task, and the standard posture parameters include the key points of the human body corresponding to the human posture parameters. The standard trajectory can represent the moving path of the target detection object when each evaluation task is successfully completed.

[0083] Exemplarily, the deviation between the human body posture parameters and the corresponding key points in the standard posture parameters can be calculated, and the human body posture parameters can be compared with the standard posture parameters to obtain the posture deviation value. Specifically, the human body posture parameters can be pre-processed by scaling, rotating and translating to make the human body posture parameters consistent with the perspective and proportion of the standard posture parameters. Then, for each human body key point, its position deviation in the human body posture parameters and the standard posture parameters is calculated, and the position deviation can be obtained by calculating the Euclidean distance between the two points. The mean of the position deviations corresponding to all human body key points is calculated, and the mean is used as the posture deviation value to evaluate the similarity between the human body posture parameters and the standard posture parameters.

[0084] Exemplarily, the deviation between the moving trajectory of the target detection object and the standard trajectory can be calculated, and the moving trajectory can be compared with the standard trajectory to obtain a trajectory deviation value. Specifically, the time axis of the moving trajectory and the standard trajectory is aligned by adjusting the timestamp or using a dynamic time warping method. Then, for each time point, the Euclidean distance between the moving trajectory and the corresponding point in the standard trajectory is calculated. The mean of the Euclidean distances corresponding to all time points is calculated, and the mean is used as the trajectory deviation value to evaluate the similarity between the moving trajectory and the standard trajectory.

[0085] Furthermore, after obtaining the posture deviation value, trajectory deviation value and task duration, the task scores corresponding to different evaluation tasks can be determined based on the preset scoring criteria. Specifically, the maximum allowable posture deviation value can be pre-set. , Maximum allowed trajectory deviation value and the longest task time , then based on , and Calculating pose scores A , trajectory score B and time rating C For example, the maximum score of the posture score, trajectory score and time score is set to 100. P , trajectory deviation value D And the duration of the task T After that, when P is less than hour, , if P is not less than , then the posture score A is 0; when D Less than hour, ,like D Not less than , then the trajectory score B is 0; when T Less than When the time score is determined according to the preset time score standard C , each time period corresponds to a time score, if T Not less than , then the time score C Of course, for tasks where longer task times indicate stronger coordination abilities of children, such as the arm-stretching balance task, the minimum task time can be preset. ,like T Less than , then the time score C is 0. Then according to the posture score A , trajectory score B and time rating CThe corresponding weight coefficients are weighted and summed to obtain the task scores corresponding to different tasks.

[0086] In step S140 , the motor coordination development ability level of the child to be evaluated is determined based on the dimension scores under all evaluation dimensions.

[0087] The assessment dimensions may represent different aspects of assessing children's motor coordination development ability. Motor coordination development ability may represent the ability of various parts of the body to work together to achieve the desired goal when performing various actions.

[0088] In some embodiments, the evaluation dimensions include planning dimension, control dimension, rhythm dimension and coordination dimension, and the motor coordination development ability level of the child to be evaluated is determined based on the dimension scores under all evaluation dimensions, specifically including the following steps: according to the weight coefficients corresponding to the planning dimension, control dimension, rhythm dimension and coordination dimension, the dimension scores are weighted summed to obtain a weighted score; according to the weighted score, the motor coordination development ability level of the child to be evaluated is determined.

[0089] Specifically, after obtaining the task scores corresponding to different assessment tasks, the dimension scores can be determined according to the assessment tasks included in different assessment dimensions. Exemplarily, the planning dimension includes five tasks: transporting items, throwing targets, rotating tray balls, walking mazes, and drawing tracks. The planning dimension score corresponding to the planning dimension is the sum of the task scores of the children to be assessed when completing the above five assessment tasks. After obtaining the planning dimension score, the control dimension score, the rhythm dimension score, and the coordination dimension score, the dimension score can be weighted and summed according to the weight coefficients corresponding to each dimension to obtain a weighted score. The weighted score is the assessment score of the motor coordination development ability corresponding to the child to be assessed. Then, according to the preset division criteria, the motor coordination development ability of the child to be assessed is divided into different levels according to the weighted value, including: excellent, good, qualified, and poor, etc. In addition, different assessment tasks can be combined according to the actual assessment situation so that the assessment tasks included in different assessment dimensions are more in line with the assessment requirements.

[0090] In some embodiments, the planning dimension, control dimension, rhythm dimension, and coordination dimension respectively include one or more of the tasks of transporting objects, throwing targets, placing objects, billiards, balancing with arms, catching balls, rotating trays, walking through mazes, drawing tracks, pushing balls, diagonal legs, and skipping grids. In addition, different evaluation dimensions may include the same evaluation task. Exemplarily, the planning dimension includes transporting objects, placing objects, billiards, diagonal legs, skipping grids, and drawing tracks; the control dimension includes throwing targets, walking through mazes, throwing targets, balancing with arms, and rotating trays; the rhythm dimension includes billiards, catching balls, throwing targets, and balancing with arms; the coordination dimension includes walking through mazes, transporting objects, diagonal legs, rotating trays, pushing balls, and billiards.

[0091] In some embodiments, the monitoring data also includes physiological data and emotional data. The motor coordination development ability level of the child to be evaluated is determined based on the task score and the dimension scores under all evaluation dimensions, which specifically includes the following steps: determining a first correction coefficient based on the physiological data; determining a second correction coefficient based on the emotional data; correcting the task scores in all evaluation dimensions according to the first correction coefficient and the second correction coefficient to obtain a corrected score; and determining the motor coordination development ability level of the child to be evaluated based on the corrected score.

[0092] Among them, physiological data can represent data related to the physical functions of the child to be evaluated, which may include but are not limited to data such as heart rate, respiratory rate, body temperature, etc., which can reflect the physical health status and physiological reactions of the child to be evaluated. Emotional data can represent information related to the emotional state of the child to be evaluated, which may include facial expressions, voice emotions, etc. Emotional data helps to understand the emotional experience and changes of the child to be evaluated during the evaluation process. The first correction coefficient can represent a numerical value determined based on physiological data for adjusting the task score to reflect the impact of physiological state on the evaluation of children's motor coordination development ability. The second correction coefficient can represent a numerical value determined based on emotional data for adjusting the task score to take into account the impact of emotional state on the evaluation of children's motor coordination development ability.

[0093] For example, when the child to be evaluated completes the evaluation task, if the physiological data shows that the child has a high heart rate or a fast breathing rate, etc., it indicates that the child is in a highly nervous state when completing the task, and it can be considered that the child's motor ability is poor, so the task score can be reduced by the first correction coefficient. When the child to be evaluated completes the evaluation task, the emotional data shows that the child is in a crying or depressed state when completing the task, which often affects the child's task performance, so the task score can be increased by the second correction coefficient, so that the task score can more objectively reflect the child's actual performance.

[0094] The task score is corrected according to the first correction coefficient and the second correction coefficient to obtain a corrected score, which can be obtained by multiplying the task score by the first correction coefficient and the second correction coefficient. Then, according to the corrected score, the child's motor coordination development ability is evaluated through the planning dimension, the control dimension, the rhythm dimension and the coordination dimension.

[0095] In some embodiments, the physiological data of the child to be evaluated can be obtained through a wearable device. When the child to be evaluated completes the evaluation task, the physiological data such as heart rate, respiratory rate, body temperature, etc. can be obtained through the wearable device on the wrist.

[0096] In some embodiments, determining the first correction coefficient based on physiological data specifically includes the following steps: comparing the physiological data corresponding to different assessment tasks with preset physiological assessment standards to obtain multiple comparison results; adjusting the first benchmark coefficient based on the multiple comparison results to obtain the first correction coefficient.

[0097] Among them, the physiological assessment standard can represent a pre-set physiological parameter threshold or range, which is used to measure whether the physiological state of the person to be assessed is within a normal or expected range when completing the assessment task. Specifically, when the acquired physiological data include heart rate, respiratory rate and body temperature, the physiological assessment standard can include a standard heart rate range, a standard respiratory rate range and a standard body temperature range. The heart rate, respiratory rate and body temperature corresponding to different assessment tasks are compared with the standard heart rate range, the standard respiratory rate range and the standard body temperature range. The first correction coefficient is then adjusted according to the comparison result.

[0098] In some embodiments, the first baseline coefficient is adjusted according to multiple comparison results, specifically including the following steps: in response to the physiological data not meeting the preset physiological evaluation standard, the first baseline coefficient is reduced; or, in response to the physiological data meeting the preset physiological evaluation standard, the first baseline coefficient is increased.

[0099] Specifically, the first reference coefficient can be set to 1. When any of the heart rate, respiratory rate, and body temperature does not meet the physiological evaluation standard, the first reference coefficient is reduced by a preset base of 0.02. When any of the heart rate, respiratory rate, and body temperature meets the physiological evaluation standard, the first reference coefficient is increased by a preset base of 0.02. Exemplarily, when the heart rate meets the standard heart rate range, the respiratory rate does not meet the standard respiratory rate range, and the body temperature does not meet the standard body temperature range, the first correction coefficient is 0.98.

[0100] In some embodiments, determining the second correction coefficient based on the emotional data may be to adjust the second reference coefficient based on the emotional classification corresponding to the emotional data to obtain the second correction coefficient. Exemplarily, the second reference coefficient may be 1, and when the emotional classification corresponding to the emotional data is a positive emotion such as happiness or neutrality, the second correction coefficient is equal to the second reference coefficient. When the emotional classification corresponding to the emotional data is a negative emotion such as crying or anger, the second reference coefficient may be increased to avoid the influence of the emotional state on the evaluation result.

[0101] In some embodiments, the emotion data may be represented by facial expression information. Specifically, facial expression images of the child to be evaluated may be obtained, and then the facial expression images may be classified using a pre-trained emotion classification model to classify the facial expression images into predefined emotion categories, which may include happiness, crying, anger, or neutrality. When the emotion data is represented by facial expression information, the emotion classification model may be constructed using other suitable networks such as a VGGNet network, a Residual Network network, and an Inception Net network.

[0102] In some embodiments, the emotion data can be represented by speech data. Specifically, the speech data of the child to be evaluated when completing the evaluation task is obtained, and the features of the speech data are extracted to obtain acoustic features and spectral features. The pre-trained emotion classification model classifies the data based on the above-mentioned acoustic features and spectral features to obtain the emotion category corresponding to the speech data. When the emotion data is represented by speech data, the emotion classification model can be constructed by other suitable networks such as convolutional neural networks, recurrent neural networks and deep residual networks.

[0103] The method for evaluating the children's motor coordination development ability in the above-mentioned example embodiments, on the one hand, can automatically evaluate the children's actual performance by acquiring and analyzing the behavioral images and monitoring data when the children complete the tasks, thereby reducing the deviation caused by subjective judgment. On the other hand, by combining the human body posture parameters, task duration and the motion data of the target detection object, the children's motor coordination development ability is evaluated from multiple angles to ensure that the evaluation results are more comprehensive and reliable. Furthermore, the automated image processing and data analysis process reduces the time required for the evaluation and the professional requirements for the testers. Thus, the accuracy and applicability of the method for evaluating the children's motor coordination development ability are improved to a certain extent.

[0104] Furthermore, by mapping the task scores to specific evaluation dimensions (planning, control, rhythm, coordination), the children's abilities in different aspects can be analyzed in more detail, and the weighted sum of the dimension scores using weight coefficients can highlight the importance of different dimensions, making the evaluation results more targeted and practical. By determining the correction coefficient through physiological data and emotional data, the evaluation results can be adjusted according to the individual differences of children, and when evaluating children's motor coordination development ability, the influence of physiological and emotional factors can be considered, making the evaluation results more comprehensive and accurate. In addition, the automatic acquisition of children's images and human posture estimation reduces the errors and deviations of manual participation.

[0105] It should be noted that, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0106] Next, in the embodiment of the present disclosure, a device for evaluating the development ability of children's motor coordination is also provided. Fig.14 As shown in , a device 1400 for evaluating the ability of children's motor coordination development can be composed of a data acquisition module 1401, a posture image module 1402, a task scoring module 1403 and an ability evaluation module 1404, wherein: the data acquisition module can be used to obtain the behavior images and monitoring data of the child to be evaluated when completing different preset evaluation tasks, and the monitoring data includes the task duration and the motion data of the target detection object; the posture image module can be used to determine the human body posture parameters corresponding to the child to be evaluated based on the behavior image; the task scoring module can be used to determine the evaluation task combination corresponding to each evaluation dimension, and determine the dimension scores corresponding to different evaluation dimensions based on the human body posture parameters, task duration and motion data of the target detection object corresponding to each evaluation task in the evaluation task combination; the ability evaluation module can be used to determine the motor coordination development ability level of the child to be evaluated based on the dimension scores under all evaluation dimensions.

[0107] It should be noted that the specific details of each part of the above-mentioned children's motor coordination development ability assessment device have been described in detail in the implementation method of the children's motor coordination development ability assessment method part. The undisclosed details can be found in the implementation method content of the method part, and will not be repeated here.

[0108] In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above-mentioned method for evaluating children's motor coordination development ability is also provided.

[0109] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware embodiments, complete software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0110] Refer to the following Fig.15 15 to describe the electronic device 1500 according to such an embodiment of the present disclosure. Fig.15 The electronic device 1500 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0111] like Fig.15 As shown, the electronic device 1500 is in the form of a general computing device. The components of the electronic device 1500 may include but are not limited to: the at least one processing unit 1510, the at least one storage unit 1520, a bus 1530 connecting different system components (including the storage unit 1520 and the processing unit 1510), and a display unit 1540.

[0112] The storage unit stores program codes, which can be executed by the processing unit 1510, so that the processing unit 1510 executes the steps according to various exemplary embodiments of the present disclosure described in the above “Exemplary Method” section of this specification.

[0113] The storage unit 1520 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 1521 and / or a cache memory unit 1522 , and may further include a read-only memory unit (ROM) 1523 .

[0114] The storage unit 1520 may also include a program / utility 1524 having a set (at least one) of program modules 1525, such program modules 1525 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0115] Bus 1530 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0116] The electronic device 1500 may also communicate with one or more external devices 1570 (e.g., cameras, keyboards, pointing devices, Bluetooth devices, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 1500, and / or may communicate with any device that enables the electronic device 1500 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed through an input / output (I / O) interface 1550. In addition, the electronic device 1500 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 1560. As shown, the network adapter 1560 communicates with other modules of the electronic device 1500 through a bus 1530. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 1500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0117] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiment of the present disclosure.

[0118] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible embodiments, various aspects of the present disclosure can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present disclosure described in the above "Exemplary Method" section of the present specification.

[0119] refer to Fig.16 As shown, a program product 1600 for implementing the above-mentioned child motor coordination development ability assessment method according to an embodiment of the present disclosure is described, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0120] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0121] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0122] The program code contained on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, electromagnetic waves, etc., or any suitable combination of the foregoing.

[0123] Program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0124] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0125] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present disclosure.

[0126] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0127] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for evaluating children's motor coordination development ability, characterized in that: include: Obtaining behavioral images and monitoring data of the child to be evaluated when completing different preset evaluation tasks, wherein the monitoring data includes task duration and movement data of the target detection object; Determining human body posture parameters corresponding to the child to be evaluated according to the behavior image; Determine the evaluation task combination corresponding to each evaluation dimension, and determine the dimension scores corresponding to different evaluation dimensions according to the human posture parameters, the task duration and the motion data of the target detection object corresponding to each evaluation task in the evaluation task combination; The motor coordination development ability level of the child to be assessed is determined based on the dimension scores under all assessment dimensions.

2. The method for evaluating children's motor coordination development ability according to claim 1, characterized in that: The assessment dimensions include planning dimension, control dimension, rhythm dimension and coordination dimension, and the step of determining the motor coordination development ability level of the child to be assessed based on the dimension scores under all the assessment dimensions includes: According to the weight coefficients corresponding to the planning dimension, the control dimension, the rhythm dimension and the coordination dimension, the dimension scores are weighted and summed to obtain a weighted score; The motor coordination development ability level of the child to be assessed is determined according to the weighted score.

3. The method for evaluating children's motor coordination development ability according to claim 2, characterized in that: The planning dimension, control dimension, rhythm dimension and coordination dimension respectively include one or more of the tasks of transporting objects, throwing targets, placing objects, billiards, balancing with arms, catching balls, rotating balls on trays, walking through mazes, drawing tracks, pushing balls, walking diagonally with legs together, and jumping grids.

4. The method for evaluating children's motor coordination development ability according to claim 3, characterized in that: In the object transporting task, the child to be evaluated is scored based on the state of holding the target detection object, the deviation of the walking route from the predetermined route, and the contact of the target detection object with the body parts; In the target throwing task, the child to be assessed is scored based on his or her throwing performance and catching ability of the target object; In the object placement task, scoring is performed based on the placement of the target object by the child to be assessed using the dominant hand and the non-dominant hand; In the billiard task, scoring is performed based on the contact of the child to be assessed with the target ball; In the arm-stretching balance task, scoring is performed based on the child's holding condition and holding time of the target detection object; In the ball catching task, the child to be evaluated is scored based on the rebound of the target detection object and the number of times the ball is caught; In the tray ball-turning task, the child to be evaluated is scored based on the lifting situation and movement trajectory of the target detection object; In the maze walking task, scoring is performed based on the accuracy of the maze path completed by the child to be assessed; In the trajectory drawing task, scoring is performed according to the movement trajectory drawn by the child to be evaluated; In the ball pushing task, scoring is performed based on the performance of the child to be assessed in pushing the target object into the ball; In the diagonal legs-together task, scoring is performed according to the diagonal legs-together action of the child to be assessed; In the skipping task, a score is given according to the skipping performance of the child to be assessed.

5. The method for evaluating children's motor coordination development ability according to claim 2, characterized in that: The monitoring data also includes physiological data and emotional data, and the step of determining the motor coordination development ability level of the child to be evaluated based on the dimension scores under all evaluation dimensions includes: determining a first correction coefficient according to the physiological data; determining a second correction coefficient according to the emotion data; Correcting the task scores in all evaluation dimensions according to the first correction coefficient and the second correction coefficient to obtain a corrected score; Based on the revised score, the motor coordination development ability level of the child to be assessed is determined.

6. The method for evaluating children's motor coordination development ability according to claim 5, characterized in that: Determining a first correction coefficient according to the physiological data includes: Comparing the physiological data corresponding to different assessment tasks with preset physiological assessment standards to obtain multiple comparison results; The first reference coefficient is adjusted according to the multiple comparison results to obtain the first correction coefficient.

7. The method for evaluating children's motor coordination development ability according to claim 6, characterized in that: The adjusting the first reference coefficient according to the plurality of comparison results comprises: In response to the physiological data not satisfying the preset physiological assessment standard, reducing the first reference coefficient; or In response to the physiological data satisfying the preset physiological evaluation standard, the first reference coefficient is increased.

8. The method for evaluating children's motor coordination development ability according to claim 1, characterized in that: The process of acquiring the motion data of the target detection object includes: Using a target detection algorithm, performing target detection on the behavior image to obtain a detection object image; Extracting feature points from the image of the object to be detected to obtain feature point coordinates; The motion data of the target detection object is determined according to the feature point coordinates.

9. The method for evaluating children's motor coordination development ability according to claim 1, characterized in that: The determining of the human body posture parameters corresponding to the child according to the behavior image includes: Performing target detection on the behavior image to obtain a child image; Performing human body posture estimation based on the child image to identify key points of the human body; The human body posture parameters corresponding to the child are determined according to the human body key points.

10. A device for evaluating children's motor coordination development ability, characterized in that: include: A data acquisition module, used to acquire behavioral images and monitoring data of the child to be evaluated when completing different preset evaluation tasks, wherein the monitoring data includes task duration and motion data of the target detection object; A posture image module, used to determine the human posture parameters corresponding to the child to be evaluated according to the behavior image; The task scoring module is used to determine the evaluation task combination corresponding to each evaluation dimension, and determine the dimension scores corresponding to different evaluation dimensions according to the human posture parameters, the task duration and the motion data of the target detection object corresponding to each evaluation task in the evaluation task combination; The ability assessment module is used to determine the motor coordination development ability level of the child to be assessed based on the dimension scores under all assessment dimensions.

Images