Physical fitness level evaluation method and system based on student physical fitness standards

Abstract

The application discloses a physical fitness grade evaluation method and system based on a student physical fitness standard, and belongs to the technical field of student physical fitness evaluation. The method acquires basic attribute parameters and original measurement results of students to be evaluated, and synchronously collects process sampling sequences of various physical fitness test items; credibility of the original measurement results is evaluated based on the process sampling sequences, and a score interval is generated; a cross-item coupling relationship is calculated in combination with a pre-constructed cross-item coupling relationship, a cross-item constraint residual is calculated, and constraint propagation calculation is performed, and a constraint measurement interval vector is generated; interval projection operation is performed on the constraint measurement interval vector and a grade ideal interval vector, and a student physical fitness grade is determined. The application can reduce the influence of test process fluctuation and single-item abnormality on grade determination, and improve the stability and credibility of physical fitness grade evaluation results.

Description

Technical Field

[0001] This invention relates to the field of student physical fitness assessment technology, and in particular to a method and system for assessing physical fitness levels based on student physical fitness standards. Background Technology

[0002] Student physical fitness testing is a crucial foundation for schools to monitor students' physical condition, evaluate physical education teaching, and manage health records. Current student physical fitness level assessments are typically based on student physical fitness standards, taking into account factors such as gender, grade, and test scores in areas like vital capacity, 50-meter sprint, sit-and-reach, standing long jump, endurance running, and strength training, and assigning individual scores and an overall grade according to corresponding scoring rules.

[0003] In actual testing, schools typically need to complete centralized testing of a large number of students within a short period. Due to the large number of test takers, the variety of test items, and differences in testing environments and equipment conditions, scores for the same test item may fluctuate among different students, in different batches, or under different equipment conditions. For example, running events are easily affected by starting reaction, timing triggering, finish line recognition, and running status; long jump events are easily affected by take-off posture, landing point recognition, and the standardization of movement; and lung capacity events are easily affected by exhalation continuity, sampling stability, and equipment condition. These factors may lead to discrepancies between the final recorded scores and the students' actual physical condition.

[0004] Currently, common methods for assessing physical fitness levels typically use the final recorded test scores as the direct evaluation basis, and score or classify students according to the student physical fitness standards. This method is easy to implement and statistically analyze, but situations such as improper form during testing, fluctuations in equipment sampling, or significant differences in repeated tests often require manual review or retesting. Especially when scores are close to the grade boundaries, even small measurement fluctuations can lead to changes in the grade results, thus affecting the stability of physical fitness records and the accuracy of subsequent teaching analysis.

[0005] In addition, there is a certain correlation between the physical fitness test items for students. Some items jointly reflect the ability status of cardiorespiratory endurance, speed explosiveness, flexibility, or strength. However, the existing evaluation methods usually focus more on the independent scores of each item and their total scores. There is a lack of further judgment mechanisms to determine whether the performance of different items is consistent, or whether an abnormal score in a certain item is related to the test process or the performance of related items.

[0006] Therefore, it is necessary to provide a method and system for assessing physical fitness levels based on student physical health standards to solve the above-mentioned technical problems. Summary of the Invention

[0007] To address the aforementioned technical problems, this invention provides a method and system for assessing physical fitness levels based on student physical health standards. This method comprehensively considers fluctuations in the testing process, the correlation between items, and the degree of matching with the level standards, thereby improving the stability, rationality, and reliability of student physical fitness level assessment results.

[0008] This invention provides a method for assessing physical fitness levels based on student physical health standards. The assessment method includes the following steps: Obtain the basic attribute parameters and raw measurement results of the students to be evaluated, and simultaneously collect the process sampling sequence of each physical fitness test item; Based on the process sampling sequence, the reliability of the original measurement results of each physical fitness test item is evaluated, and a score interval is generated, wherein the score interval is used to characterize the intervalized score expression under the uncertainty condition of the test process. Based on the interval-based performance expression of each physical fitness test item, and combined with the pre-constructed physiological correlation between each physical fitness test item, a cross-item coupling relationship is constructed, and the cross-item constraint residual is calculated. Based on the cross-term constraint residuals and combined with the cross-term coupling relationship, constraint propagation calculations are performed on the physical fitness level boundary to generate a constraint measurement interval vector; The student's physical health level is determined by performing an interval projection operation between the constraint measurement interval vector and the ideal level interval vector.

[0009] Preferably, the step of generating the score range specifically includes: Extract the action execution subsequence and the equipment monitoring subsequence from the process sampling sequence; The action specification offset is determined based on the action execution subsequence, and the measurement fluctuation half-width is determined based on the device monitoring subsequence. The original measurement results are corrected for centering based on the offset of the action specifications, and the interval boundaries are determined based on the half-width of the measurement fluctuation to generate the score intervals for the corresponding physical fitness test items.

[0010] Preferably, the cross-item coupling relationship is a pre-constructed project coupling matrix, and the matrix elements in the project coupling matrix include project mapping direction and project coupling strength; In calculating the cross-item constraint residual, the item mapping direction is used to determine the source physical fitness test item and the target physical fitness test item, and the item coupling strength is used to determine the mapping ratio of the score range of the source physical fitness test item to the target physical fitness test item. When performing constraint propagation calculations, the project mapping direction is used to determine the propagation direction of the constraint adjustment amount, and the project coupling strength is used to determine the propagation ratio of the constraint adjustment amount.

[0011] Preferably, the calculation steps for the cross-term constraint residuals include: Determine the source physical fitness test items and the target physical fitness test items according to the project mapping direction described above; Based on the coupling strength of the project, the score range of the source physical fitness test project is mapped to the predicted score range of the target physical fitness test project; Based on the overlap and deviation between the predicted score interval and the score interval of the target physical fitness test item, the cross-item constraint residual between the source physical fitness test item and the target physical fitness test item is generated.

[0012] Preferably, when the same physical fitness test item corresponds to multiple related physical fitness test items, the cross-item constraint residuals between the physical fitness test item and each related physical fitness test item are calculated respectively, and the multiple cross-item constraint residuals are weighted and synthesized according to the coupling strength of the items to obtain the comprehensive constraint residuals corresponding to the physical fitness test item.

[0013] Preferably, the constraint propagation calculation includes: The constraint adjustment amount for the corresponding physical fitness test item is determined based on the comprehensive constraint residual. The adjustment direction of the constraint adjustment amount acting on the physical fitness level boundary is determined based on the project mapping direction; The adjustment range of the constraint adjustment amount acting on the physical fitness level boundary is determined based on the coupling strength of the project. Based on the adjustment direction and adjustment range, the boundary of the score range for the corresponding physical fitness test item is corrected.

[0014] Preferably, the constraint propagation calculation further includes: The residual trigger threshold is determined based on the coupling strength of the project. When the comprehensive constraint residual does not exceed the residual trigger threshold, the score range of the corresponding physical fitness test item remains unchanged; When the comprehensive constraint residual exceeds the residual trigger threshold, the score range of the corresponding physical fitness test item is corrected according to the constraint adjustment amount.

[0015] Preferably, the step of generating the constraint measurement interval vector includes: The score ranges of each physical fitness test item after boundary correction are used as vector components; The vector components are arranged in the order of the corresponding physical fitness test items in the student physical fitness and health standards, and the constrained measurement interval vector is composed of the arranged multiple vector components.

[0016] Preferably, the interval projection operation includes: The projection weights of each vector component in the constraint measurement interval vector are determined based on the cross-term coupling relationship; Determine the corresponding projection constraint amount based on the cross-term constraint residual; The basic projection value is obtained by weighted interval projection of the constraint measurement interval vector and the grade ideal interval vector; The basic projection value is then corrected using the projection constraint value to obtain the constraint projection value, and the level with the largest constraint projection value is determined as the student's physical health level.

[0017] This invention also provides a physical fitness level assessment system based on student physical fitness standards, applied to a physical fitness level assessment method based on student physical fitness standards, the assessment system comprising: The data acquisition module is used to obtain the basic attribute parameters and raw measurement results of the students to be evaluated, and to simultaneously collect the process sampling sequence of each physical fitness test item; The score interval generation module is used to evaluate the credibility of the original measurement results of each physical fitness test item based on the process sampling sequence and generate a score interval, wherein the score interval is used to characterize the intervalized score expression under the uncertainty conditions of the test process. The residual calculation module is used to construct cross-item coupling relationships based on the interval-based performance expression of each physical fitness test item, and in combination with the pre-built physiological correlation between each physical fitness test item, and to calculate the cross-item constraint residuals. The vector generation module is used to perform constraint propagation calculation on the physical fitness level boundary based on the cross-term constraint residual and in combination with the cross-term coupling relationship, and generate a constraint measurement interval vector. The grade determination module is used to perform interval projection calculations on the constraint measurement interval vector and the grade ideal interval vector to determine the student's physical health grade.

[0018] Compared with related technologies, the physical fitness level assessment method and system based on student physical health standards provided by this invention have the following beneficial effects: This invention collects process sampling sequences for each physical fitness test item simultaneously with the original measurement results, and generates score intervals based on the process sampling sequences. This allows the standardization of test actions, equipment sampling fluctuations, and uncertainties in the measurement process to be reflected in the evaluation input stage, avoiding the use of a single measurement value as the sole evaluation criterion, thereby improving the stability of physical fitness test score processing.

[0019] This invention calculates cross-item constraint residuals by pre-constructing cross-item coupling relationships, and performs constraint propagation calculations on the score interval based on the cross-item constraint residuals. This allows the score of a physical fitness test item to be evaluated not only based on its own measurement results, but also to be constrained by the performance of related items. This helps to identify abnormal scores caused by abnormal movements, equipment fluctuations, or uncoordinated performance of items, and reduces the impact of single-item random deviations on the overall physical fitness level assessment results.

[0020] This invention constructs a constraint measurement interval vector from the score intervals calculated by constraint propagation, and performs interval projection operation with the ideal grade interval vector. This allows the determination of the final physical fitness grade to simultaneously consider the closeness of the test scores to the grade standard, the reliability of the testing process, and the coupling constraint state between different physical fitness test items. When the scores are close to the grade boundary, it can reduce the instability of grade determination caused by small measurement fluctuations, and improve the rationality and reliability of the student's physical fitness grade assessment results. Attached Figure Description

[0021] Figure 1 The flowchart shows the physical fitness level assessment method based on student physical health standards of the present invention. Figure 2 This is a schematic diagram of the module structure of the physical fitness level assessment system based on student physical health standards of the present invention. Detailed Implementation

[0022] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the drawings, not all structures. Moreover, unless otherwise specified, the embodiments and features described herein can be combined with each other. Example

[0023] This embodiment provides a method for assessing physical fitness levels based on student physical health standards. This method is applicable to scenarios such as school physical health testing, student physical health record management, automatic physical fitness level assessment, and identification of abnormal test results. Unlike methods that directly score based on a single physical fitness test, this embodiment simultaneously collects process sampling sequences for each physical fitness test item while obtaining the student's original measurement results. Based on these process sampling sequences, a score interval is generated. Then, cross-item coupling relationships and cross-item constraint residuals are used to perform constraint propagation calculations on the score intervals, ultimately obtaining a constraint measurement interval vector used for physical fitness level determination.

[0024] refer to Figure 1 As shown, the evaluation method in this embodiment includes the following steps: S1. Obtain the basic attribute parameters and original measurement results of the students to be evaluated, and simultaneously collect the process sampling sequence of each physical fitness test item.

[0025] Specifically, the basic attribute parameters include parameters related to matching the student's physical fitness standards, such as gender, grade, age, height, and weight. Raw measurement results include at least two test results from lung capacity, 50-meter sprint, sit-and-reach, standing long jump, endurance running, and strength-related items. Strength-related items can include pull-ups, sit-ups, or other physical fitness tests that reflect a student's strength.

[0026] While collecting the raw measurement results, the process sampling sequence for each physical fitness test item is also collected simultaneously. The process sampling sequence reflects the execution status of the actions and the sampling status of the equipment during the test, and it can include action execution sub-sequences and equipment monitoring sub-sequences. The action execution sub-sequence reflects the student's completion of the actions during the test, such as the start and end status of the actions, the amplitude of the actions, the duration of the actions, and the changes in rhythm; the equipment monitoring sub-sequence reflects the monitoring status of the testing equipment during the data collection process, such as sensor sampling values, equipment trigger status, and measurement fluctuations.

[0027] S2. Based on the process sampling sequence, the reliability of the original measurement results of each physical fitness test item is evaluated, and the score range is generated.

[0028] Specifically, action execution subsequences and equipment monitoring subsequences are extracted from the process sampling sequence.

[0029] The motion specification offset is determined based on the motion execution subsequence. In this embodiment, the motion execution subsequence is compared with a pre-stored standard motion template sequence using dynamic time warping (DTW). The resulting distance value is the motion specification offset, which characterizes the degree of deviation between the student's actual test motion and the standard test motion. For example, in the standing long jump, the greater the DTW distance between the knee flexion angle time series data acquired by the IMU and the standard template, the worse the motion specification.

[0030] The measurement fluctuation half-width is determined based on the equipment monitoring subsequence. In this embodiment, steady-state sampling data of the equipment monitoring subsequence within the effective measurement period are extracted, and its standard deviation is calculated. and will The half-width at half-width is used to characterize the range of measurement fluctuations of the testing equipment in the corresponding physical fitness test items.

[0031] After determining the movement standard deviation and the half-width of the measurement fluctuation, the original measurement result is corrected for centering based on the movement standard deviation to obtain the corrected measurement result. The centering correction amount is obtained by looking up a table based on the movement standard deviation, and the lookup relationship is pre-calibrated by the regression relationship between movement standard deviation and performance deviation in historical data of the same event. For example, for the 50-meter sprint, when the DTW deviation is greater than a preset threshold, the centering correction amount is positive (i.e., time addition), and the correction amount monotonically does not decrease with the deviation; for the vital capacity event, if there is an interruption in the exhalation process causing waveform abnormalities, the original volume value is negatively corrected according to the degree of interruption.

[0032] Subsequently, the interval boundaries were determined based on the measured fluctuation half-width, generating the corresponding score intervals for the physical fitness test items. ,in For the corrected measurement results, This is a comprehensive half-width coefficient that integrates the measured fluctuation half-width and the motion offset correction. This performance interval is used to characterize the intervalized performance results under the uncertainty conditions of the testing process.

[0033] S3. Based on the score range of each physical fitness test item and combined with the pre-built physiological correlation between each physical fitness test item, construct cross-item coupling relationship and calculate cross-item constraint residual.

[0034] Specifically, the cross-item coupling relationship is a pre-constructed project coupling matrix. Matrix elements in the project coupling matrix This includes the item mapping direction and the item coupling strength. The item mapping direction is used to represent the relationship between one physical fitness test item i and another physical fitness test item. The direction of correlation between them (e.g., vital capacity i positively affects endurance running j), and the strength of coupling between items. Used to indicate the degree of correlation between two physical fitness test items.

[0035] In this embodiment, the project coupling matrix The system is built based on historical physical fitness test big data of students of the same age group. The initial coupling strength is determined by calculating the Pearson correlation coefficient between each pair of items, and the mapping direction is calibrated according to the physiological causal direction (e.g., cardiopulmonary function index as cause and endurance running performance as effect), forming an asymmetric matrix.

[0036] When calculating cross-item constraint residuals, the item mapping direction is used to determine the source physical fitness test item and the target physical fitness test item, and the item coupling strength is used to determine the mapping ratio from the score interval of the source physical fitness test item to the target physical fitness test item. Specifically, the score interval of the source physical fitness test item i is first... According to the mapping direction Mapped to target physical fitness test items Predicted score range .

[0037] Specifically, let the score range of physical fitness test item i be . Target physical fitness test items The predicted score range is When the project mapping direction This indicates the relationship between source physical fitness test item i and target physical fitness test item i. When a positive impact is generated, the predicted score range is generated as follows: ; When the project mapping direction This indicates the relationship between source physical fitness test item i and target physical fitness test item i. When a reverse effect occurs, the predicted score range is generated as follows: ; in, To determine the coupling strength of the project Determined interval mapping coefficients, This refers to the baseline offset between items pre-calibrated based on historical physical fitness test samples of students of the same age group. If the order of the interval endpoints changes after mapping, the smaller endpoint is taken as the lower limit of the interval, and the larger endpoint is taken as the upper limit of the interval.

[0038] Then based on the predicted score range The range of actual test scores for the target physical fitness test items The overlap and deviation between intervals are used to generate residual components.

[0039] Among them, the interval overlap Calculated using the intersection-over-union ratio (IoU): ; Interval deviation The calculation is performed using the normalized distance between the midpoints of the two intervals, specifically as follows: ; in, To predict the range of scores The midpoint, Target physical fitness test items score range The midpoint, Target physical fitness test items The effective scoring range in the student physical fitness standards, or the range of values ​​for this item in historical physical fitness test samples of students of the same age group. Through... The midpoint distance is normalized so that physical fitness test items with different dimensions can be compared under the same residual scale.

[0040] Cross-term constrained residual components Through formula Synthesis, in which and The preset weighting coefficients are used. By generating cross-item constraint residuals through interval overlap and interval deviation, it is possible to avoid judging project anomalies solely based on single-point score differences, thereby improving the stability of cross-item constraint judgment.

[0041] When the same physical fitness test item Corresponding to multiple related physical fitness test items At that time, calculate the cross-item constraint residual components between the physical fitness test item and each related physical fitness test item. And according to the project coupling strength The weighted summation of multiple residual components yields the comprehensive constraint residual corresponding to this physical fitness test item. .

[0042] S4. Based on the cross-term constraint residuals and combined with the cross-term coupling relationship, perform constraint propagation calculation on the physical fitness level boundary to generate the constraint measurement interval vector.

[0043] Specifically, in constraint propagation calculations, the project mapping direction is used to determine the propagation direction of constraint adjustment amounts, and the project coupling strength is used to determine the propagation ratio of constraint adjustment amounts. First, based on the comprehensive constraint residuals... Determine the corresponding physical fitness test items Constraint adjustment amount .

[0044] In this embodiment, when the comprehensive constraint residual The residual trigger threshold has not been exceeded. At that time, the constraint adjustment amount Set to 0; when the comprehensive constraint residual Exceeding the residual trigger threshold When doing so, the constraint adjustment amount shall be determined as follows: ; in, For physical fitness test items The relevant adjustment coefficient, According to the project coupling matrix Physical fitness test items The coupling strength of related projects is determined. A higher coupling strength indicates a stronger influence of cross-project constraints on the project. The larger.

[0045] In this embodiment, the residual trigger threshold Based on historical samples and physical fitness test items The distribution of relevant cross-term constraint residuals is determined. For example, suppose... Physical fitness test items in historical samples The corresponding set of comprehensive constraint residuals, then the residual trigger threshold. Determine as follows:

[0046] in, This represents the median absolute deviation of the comprehensive constraint residual set. By determining the residual trigger threshold based on the historical residual distribution, it is possible to avoid directly judging abnormal deviations of different physical fitness test items using fixed empirical thresholds.

[0047] When the comprehensive constraint residual The residual trigger threshold has not been exceeded. At that time, the test results for this item are deemed reliable, and the score range for the corresponding physical fitness test item is maintained. Unchanged; when the comprehensive constraint residual Exceeding the residual trigger threshold When an abnormal deviation is determined in the project, the constraint adjustment amount is applied. The score ranges for the corresponding physical fitness test items were adjusted.

[0048] The correction includes interval shift, interval contraction, or a combination of both. Let the physical fitness test item to be corrected be an example. The score range is The midpoint of the interval is The half-width of the interval is .

[0049] When the cross-item constraint residuals are mainly caused by deviations from the center of the score interval, the score intervals are shifted as a whole according to the direction of the deviation. The corrected score range is obtained as follows: ; in, Indicates the direction of offset. This indicates a shift towards increasing numerical values. This indicates a shift in the direction of decreasing value.

[0050] When the cross-item constraint residuals are mainly caused by excessively wide score intervals, the constraint adjustment amount should be used. By narrowing the score range, we obtain the corrected score range: ; Among them, when When the width is less than the preset minimum half-width, the preset minimum half-width is taken as the corrected interval half-width.

[0051] When the cross-item constraint residual contains both center deviation and interval width anomaly, the score interval is first shifted as a whole according to the offset direction, and then the offset score interval is shrunk according to the constraint adjustment amount to obtain the corrected score interval.

[0052] After boundary correction, the score intervals of each physical fitness test item after boundary correction are used as vector components. These vector components are then arranged according to the order of the corresponding physical fitness test items in the Student Physical Fitness and Health Standard. The multiple arranged vector components form the constraint measurement interval vector. The constraint measurement interval vector is no longer an evaluation input directly formed from the original measurement results, but an intervalized evaluation input obtained by combining process sampling sequence, performance interval, cross-item coupling relationship, and cross-item constraint residual.

[0053] S5. Perform interval projection operation between the constraint measurement interval vector and the ideal grade interval vector to determine the student's physical health grade.

[0054] Specifically, the ideal interval vector for each grade is constructed based on the standard intervals corresponding to different physical fitness levels (e.g., excellent, good, pass) in the student physical fitness standards. Let the ideal interval vector for the k-th grade be... .

[0055] Interval projection operations include: First, determining the projection weights of each vector component in the constraint measurement interval vector based on the cross-term coupling relationship. (For example, take the average of the coupling strength between this project and other projects); determine the corresponding projective constraint amount based on the cross-item constraint residuals. Specifically, the projection constraint quantity The comprehensive constraint residual of the corresponding physical fitness test item i Normalization yields: ; in, The residual trigger threshold corresponding to physical fitness test item i. Preset constraint coefficients. Comprehensive constraint residuals. The larger the value, the greater the projection constraint. The larger the value, the stronger the credible constraint of the physical fitness test item in the final grade projection.

[0056] Subsequently, the constrained measurement interval vector is calculated. with the ideal interval vector of the grade The weighted interval projection values ​​between them. For each component interval and ideal interval Calculate interval membership :like Completely included The membership degree is 1; if there is an intersection, the membership degree is the sum of the intersection length and the membership degree of the intersection. The ratio of lengths; if there is no intersection, the membership degree is 0. Basic projection value. Through formula Calculated.

[0057] Finally, the basic projection values ​​are corrected using projection constraints. Specifically, for the first... Each level utilizes the corresponding projection constraints of the project. Correct its base projection value Obtain the constrained projection value The corrected formula is as follows: ; constrained projection values The highest level is defined as the student's physical health level. Example

[0058] This embodiment also provides a physical fitness level assessment system based on student physical health standards, used to perform the above assessment method, with reference to... Figure 2 As shown, the evaluation system includes a data acquisition module 100, a score interval generation module 200, a residual calculation module 300, a vector generation module 400, and a grade determination module 500.

[0059] The data acquisition module 100 communicates with the IMU sensor and physical fitness testing equipment worn by the student via Bluetooth or serial port to acquire the basic attribute parameters and raw measurement results of the student to be evaluated, and simultaneously collects the process sampling sequences of each physical fitness test item. The IMU sensor is used to collect the movement execution sub-sequences in running, long jump and strength tests, and the physical fitness testing equipment is used to provide raw measurement results and equipment monitoring sub-sequences.

[0060] The grade interval generation module 200, residual calculation module 300, vector generation module 400, and grade determination module 500 are all implemented by the processor executing computer programs stored in memory. The memory stores the algorithmic logic and standard action template data used to implement each of the above steps. The processor calls the program code in memory to execute interval generation, residual calculation, constraint propagation, and projection operations, such as S2 to S5, thereby outputting the final physical fitness grade.

[0061] In this embodiment, a continuous data processing relationship is formed between the modules. The intervalized scores output by the score interval generation module 200 serve as the input to the residual calculation module; the cross-item constraint residuals output by the residual calculation module 300 serve as the input to the vector generation module; and the constraint measurement interval vector output by the vector generation module 400 serves as the input to the grade determination module. Therefore, the determination of physical fitness level does not directly rely on a single original measurement result, but rather on the constraint measurement interval vector formed after the reliability assessment of the testing process and the propagation of cross-item coupling constraints, thereby improving the stability and accuracy of the student's physical fitness level assessment results.

[0062] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

Claims

1. A method for assessing physical fitness levels based on student physical health standards, characterized in that, The evaluation method includes the following steps: Obtain the basic attribute parameters and raw measurement results of the students to be evaluated, and simultaneously collect the process sampling sequence of each physical fitness test item; Based on the process sampling sequence, the reliability of the original measurement results of each physical fitness test item is evaluated, and a score interval is generated, wherein the score interval is used to characterize the intervalized score expression under the uncertainty condition of the test process. Based on the interval-based performance expression of each physical fitness test item, and combined with the pre-constructed physiological correlation between each physical fitness test item, a cross-item coupling relationship is constructed, and the cross-item constraint residual is calculated. Based on the cross-term constraint residuals and combined with the cross-term coupling relationship, constraint propagation calculations are performed on the physical fitness level boundary to generate a constraint measurement interval vector; The student's physical health level is determined by performing an interval projection operation between the constraint measurement interval vector and the ideal level interval vector.

2. The method for assessing physical fitness levels based on student physical health standards according to claim 1, characterized in that, The steps for generating the score range specifically include: Extract the action execution subsequence and the equipment monitoring subsequence from the process sampling sequence; The action specification offset is determined based on the action execution subsequence, and the measurement fluctuation half-width is determined based on the device monitoring subsequence. The original measurement results are corrected for centering based on the offset of the action specifications, and the interval boundaries are determined based on the half-width of the measurement fluctuation to generate the score intervals for the corresponding physical fitness test items.

3. The method for assessing physical fitness levels based on student physical health standards according to claim 1, characterized in that, The cross-item coupling relationship is a pre-constructed project coupling matrix, and the matrix elements in the project coupling matrix include the project mapping direction and the project coupling strength; In calculating the cross-item constraint residual, the item mapping direction is used to determine the source physical fitness test item and the target physical fitness test item, and the item coupling strength is used to determine the mapping ratio of the score range of the source physical fitness test item to the target physical fitness test item. When performing constraint propagation calculations, the project mapping direction is used to determine the propagation direction of the constraint adjustment amount, and the project coupling strength is used to determine the propagation ratio of the constraint adjustment amount.

4. The method for assessing physical fitness levels based on student physical health standards according to claim 3, characterized in that, The calculation steps for the cross-term constraint residuals include: Determine the source physical fitness test items and the target physical fitness test items according to the project mapping direction described above; Based on the coupling strength of the project, the score range of the source physical fitness test project is mapped to the predicted score range of the target physical fitness test project; Based on the overlap and deviation between the predicted score interval and the score interval of the target physical fitness test item, the cross-item constraint residual between the source physical fitness test item and the target physical fitness test item is generated.

5. The method for assessing physical fitness levels based on student physical health standards according to claim 4, characterized in that, When the same physical fitness test item corresponds to multiple related physical fitness test items, the cross-item constraint residuals between the physical fitness test item and each related physical fitness test item are calculated respectively, and the multiple cross-item constraint residuals are weighted and synthesized according to the coupling strength of the items to obtain the comprehensive constraint residuals corresponding to the physical fitness test item.

6. The method for assessing physical fitness levels based on student physical health standards according to claim 5, characterized in that, The constraint propagation calculation includes: The constraint adjustment amount for the corresponding physical fitness test item is determined based on the comprehensive constraint residual. The adjustment direction of the constraint adjustment amount acting on the physical fitness level boundary is determined based on the project mapping direction; The adjustment range of the constraint adjustment amount acting on the physical fitness level boundary is determined based on the coupling strength of the project. Based on the adjustment direction and adjustment range, the boundary of the score range for the corresponding physical fitness test item is corrected.

7. The method for assessing physical fitness levels based on student physical health standards according to claim 6, characterized in that, The constraint propagation calculation also includes: The residual trigger threshold is determined based on the coupling strength of the project. When the comprehensive constraint residual does not exceed the residual trigger threshold, the score range of the corresponding physical fitness test item remains unchanged; When the comprehensive constraint residual exceeds the residual trigger threshold, the score range of the corresponding physical fitness test item is corrected according to the constraint adjustment amount.

8. The method for assessing physical fitness levels based on student physical health standards according to claim 7, characterized in that, The steps for generating the constraint measurement interval vector include: The score ranges of each physical fitness test item after boundary correction are used as vector components; The vector components are arranged in the order of the corresponding physical fitness test items in the student physical fitness and health standards, and the constrained measurement interval vector is composed of the arranged multiple vector components.

9. The method for assessing physical fitness levels based on student physical health standards according to claim 8, characterized in that, The interval projection operation includes: The projection weights of each vector component in the constraint measurement interval vector are determined based on the cross-term coupling relationship; Determine the corresponding projection constraint amount based on the cross-term constraint residual; The basic projection value is obtained by weighted interval projection of the constraint measurement interval vector and the grade ideal interval vector; The basic projection value is then corrected using the projection constraint value to obtain the constraint projection value, and the level with the largest constraint projection value is determined as the student's physical health level.

10. A physical fitness level assessment system based on student physical fitness standards, applied to the physical fitness level assessment method based on student physical fitness standards as described in any one of claims 1 to 9, characterized in that, The evaluation system includes: The data acquisition module is used to obtain the basic attribute parameters and raw measurement results of the students to be evaluated, and to simultaneously collect the process sampling sequence of each physical fitness test item; The score interval generation module is used to evaluate the credibility of the original measurement results of each physical fitness test item based on the process sampling sequence and generate a score interval, wherein the score interval is used to characterize the intervalized score expression under the uncertainty conditions of the test process. The residual calculation module is used to construct cross-item coupling relationships based on the interval-based performance expression of each physical fitness test item, and in combination with the pre-built physiological correlation between each physical fitness test item, and to calculate the cross-item constraint residuals. The vector generation module is used to perform constraint propagation calculation on the physical fitness level boundary based on the cross-term constraint residual and in combination with the cross-term coupling relationship, and generate a constraint measurement interval vector. The grade determination module is used to perform interval projection calculations on the constraint measurement interval vector and the grade ideal interval vector to determine the student's physical health grade.

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