Sports injury assessment method and system

Abstract

The invention provides an exercise injury assessment method and system, and belongs to the technical field of data assessment, and the method specifically comprises the steps: carrying out the monitoring processing of a target person through an associated monitoring data group, and obtaining the monitoring data of the target person, determining the severity and the occurrence probability of the target person in different types of sports injuries based on the analysis result of the monitoring data, and when the severity and the occurrence probability of the sports injuries are utilized to determine that the injury severity of the target person meets the requirement, determining that the target person is injured. The method comprises the following steps: determining a secondary acquisition target of monitoring data of a target person according to the severity and occurrence probability of the target person in different types of sports injuries, and determining an assessment result of the sports injuries of the target person according to the secondary acquisition target and the monitoring data of the target person. And the accuracy of the assessment result of the sport injury is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data evaluation, and particularly relates to a method and system for evaluating sports injuries. Background Art

[0002] In order to realize the evaluation of sports injuries, in the invention patent application CN202411276386.9, "An Intelligent Evaluation Method and System for Sports Injury Status", by inputting the reconstructed ultrasound image, medical history, and the degree of tissue injury into the evaluation network model, the evaluation result of the sports injury status is obtained, thereby improving the accuracy of the evaluation result of the sports injury status. However, there are the following technical problems: When evaluating the sports injury status, for different individuals, due to the differences in the types of sports injuries, and when evaluating different types of sports injuries, there are also differences in the degree of association between different types of monitoring data and the types of sports injuries. Therefore, if the monitoring data cannot be obtained according to the types of sports injuries of the individual, it is impossible to improve the accuracy of the evaluation result of sports injuries on the basis of reducing the amount of data collection.

[0003] In view of the above technical problems, specifically, the present application provides a method and system for evaluating sports injuries. Summary of the Invention

[0004] To achieve the object of the present invention, the present invention adopts the following technical solutions: According to one aspect of the present invention, a method for evaluating sports injuries is provided.

[0005] A method for evaluating sports injuries specifically includes: S1: Using the monitoring data of historical individuals under different types of sports injuries to determine the correlation coefficient between the monitoring data and different types of sports injuries, and the associated monitoring data in the monitoring data; S2: Based on the associated monitoring data, constructing multiple monitoring data groups, and determining the associated monitoring data groups in the monitoring data groups according to the number of monitoring data in different monitoring data groups and the correlation coefficient with different types of sports injuries; S3: Using the associated monitoring data group to perform monitoring processing on the target individual to obtain the monitoring data of the target individual, determining the severity and occurrence probability of the target individual in different types of sports injuries based on the analysis result of the monitoring data, and when the severity of the sports injury determined by the severity and occurrence probability of the sports injury meets the requirements, proceeding to the next step; S4 determines the secondary acquisition target of the target person's monitoring data based on the severity and occurrence probability of different types of sports injuries of the target person, and determines the evaluation result of the target person's sports injury based on the secondary acquisition target and the target person's monitoring data.

[0006] The beneficial effects of the present invention are: The severity and probability of occurrence of different types of sports injuries of the target personnel are determined based on the analysis results of the monitoring data, thereby realizing the screening of types of sports injuries with higher severity and probability of occurrence from the perspective of less monitoring data, and also laying the foundation for the determination of targeted secondary acquisition targets of monitoring data, reducing the difficulty of sports injury assessment and processing, while also improving the efficiency of sports injury assessment and processing on the basis of ensuring the accuracy of sports injury assessment results.

[0007] The severity and probability of occurrence of different types of sports injuries of the target personnel are used to determine the secondary acquisition target of the target personnel's monitoring data, which enables the screening of sports injuries with higher abnormalities based on the severity and probability of occurrence of different types of sports injuries of the target personnel. It also lays the foundation for the determination of sports injuries with higher abnormalities, reduces the difficulty of acquiring and processing monitoring data, and ensures the reliability of sports injury assessment and processing.

[0008] A further technical solution is that the types of sports injuries include abrasions, strains, contusions, sprains, dislocations, and fractures.

[0009] A further technical solution is that the monitoring data includes motion posture data, ultrasonic images, images of damaged parts, breathing data, heartbeat data, and ultrasonic echoes.

[0010] A further technical solution is that the method for determining the associated monitoring data is: Personnel with a history of a specific type of sports injury are used as matching target persons, and the average values ​​of the monitoring data of different matching target persons are determined by using the analysis results of the monitoring data of different matching target persons, and the average values ​​are used as reference values; Determine persons with similar monitoring data among the matching target persons according to the deviations between the monitoring data of different matching target persons and the reference value; The injury correlation coefficient between the monitoring data and a specific type of sports injury is determined based on the proportion of the number of persons similar to the monitoring data in the matching target persons, the correlation coefficient is determined based on the average value of the injury correlation coefficients with different types of sports injuries, and the correlation coefficient is used to determine whether the monitoring data is associated monitoring data.

[0011] A further technical solution lies in that the personnel with similar monitoring data are matching target personnel whose deviation amount between the monitoring data and the reference value is not greater than a preset deviation threshold.

[0012] A further technical solution lies in that the method for determining the evaluation result of the sports injury of the target personnel is as follows: Taking the secondary acquisition target and the monitoring data of the target personnel as the input quantities of the evaluation model, and taking the output quantity of the evaluation model as the evaluation result of the sports injury of the target personnel.

[0013] A further technical solution lies in that the evaluation result includes the type and development stage of the sports injury of the target personnel.

[0014] A further technical solution lies in that the evaluation model is constructed by using one or more of a BP neural network, an LSTM neural network, and a CNN convolutional neural network.

[0015] In a second aspect, the present invention provides a computer system, including: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, wherein when the processor runs the computer program, it executes the above-mentioned sports injury evaluation method.

[0016] Other features and advantages will be described in the subsequent specification. The objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the specification and the drawings.

[0017] To make the above objectives, features, and advantages of the present invention more obvious and understandable, the following specific preferred embodiments are given, and in conjunction with the accompanying drawings, the detailed description is as follows. Description of the Drawings

[0018] By referring to the accompanying drawings and describing its exemplary embodiments in detail, the above and other features and advantages of the present invention will become more obvious; Figure 1 It is a flowchart of a sports injury evaluation method; Figure 2 It is a flowchart of a method for determining associated monitoring data; Figure 3 It is a flowchart of a method for determining an associated monitoring data group in a monitoring data group; Figure 4 It is a flowchart of a method for determining a secondary acquisition target of the monitoring data of a target personnel; Figure 5 It is a framework diagram of a computer system. Detailed Embodiments

[0019] To enable those skilled in the art to better understand the technical solutions in this specification, the following will clearly and completely describe the technical solutions in the embodiments of this specification in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this specification.

[0020] In this application, first, the recognition processing of the type of sports injury of the target person is determined by using the associated monitoring data with a relatively high recognition accuracy for the type of sports injury, and the secondary recognition target of the monitoring data of the target person is determined by using the recognized type of sports injury of the target person, and the recognition processing of the sports injury of the target person is carried out by using the secondary recognition target.

[0021] Taking historical personnel with specific types of sports injuries as matching target persons, taking the average value of the monitoring data of different matching target persons as a reference value, determining the persons with similar monitoring data among the matching target persons through the deviation amount from the reference value, determining the injury correlation coefficient between the monitoring data and the specific type of sports injury by the proportion of the number of persons with similar monitoring data in the number of matching target persons, and determining the correlation coefficient based on the average value of the injury correlation coefficients for different types of sports injuries. When the correlation coefficient is greater than 0.6, the monitoring data is determined as associated monitoring data.

[0022] Determining the sum of the correlation coefficients between the monitoring data and different types of sports injuries based on the correlation coefficients between the monitoring data and different types of sports injuries, and determining the group correlation coefficient by using the average value of the sum of the correlation coefficients of different types of sports injuries. Determining the data correlation coefficient of the monitoring data group according to the ratio of the group correlation coefficient to the number of associated monitoring data in the monitoring data group, and taking the monitoring data group with the largest data correlation coefficient as the associated monitoring data group.

[0023] Example 1 To solve the above problems, according to one aspect of the present invention, as Figure 1 shown, a first aspect is provided. The present invention proposes a method for evaluating sports injuries, specifically including: S1 Determining the correlation coefficient between the monitoring data and different types of sports injuries and the associated monitoring data in the monitoring data by using the monitoring data of historical personnel under different types of sports injuries; Further, the types of sports injuries include abrasions, strains, contusions, sprains, dislocations, and fractures.

[0024] Specifically, the monitoring data includes motion posture data, ultrasonic images, injury site images, respiratory data, heartbeat data, and ultrasonic echoes.

[0025] Specifically, as Figure 2 shown, the method for determining the associated monitoring data is as follows: Taking historical personnel with specific types of sports injuries as matching target personnel, using the analysis results of the monitoring data of different matching target personnel, determining the average value of the monitoring data of different matching target personnel, and taking it as a reference value; Determining the personnel with similar monitoring data among the matching target personnel according to the deviation amount between the monitoring data of different matching target personnel and the reference value; Based on the proportion of the number of personnel with similar monitoring data in the number of matching target personnel, determining the injury correlation coefficient between the monitoring data and specific types of sports injuries, determining the correlation coefficient based on the average value of the injury correlation coefficients for different types of sports injuries, and using the correlation coefficient to determine whether the monitoring data is associated monitoring data.

[0026] Optionally, the personnel with similar monitoring data are matching target personnel whose deviation amount between the monitoring data and the reference value does not exceed a preset deviation threshold.

[0027] In another embodiment, the method for determining the associated monitoring data is as follows: Taking historical personnel with specific types of sports injuries as matching target personnel, using the analysis results of the monitoring data of different matching target personnel, determining the average value of the monitoring data of different matching target personnel, and taking it as a reference value; Taking the historical personnel other than the matching target personnel as other historical personnel, and determining the similar historical personnel among the other historical personnel using the deviation amount from the reference value; Based on the proportion of the number of similar historical personnel in the number of other historical personnel, determining the data correlation coefficient between the monitoring data and specific types of sports injuries, determining the correlation coefficient based on the average value of the data correlation coefficients for different types of sports injuries, and using the correlation coefficient to determine whether the monitoring data is associated monitoring data.

[0028] Furthermore, when the number of similar historical personnel is greater than a preset threshold for the number of similar personnel, it is determined that the monitoring data does not belong to the associated monitoring data.

[0029] Optionally, the method for determining the associated monitoring data is as follows: S11 uses the historical personnel with a specific type of sports injury as the matching target personnel, determines the average value of the monitoring data of different matching target personnel by using the analysis results of the monitoring data of different matching target personnel, and takes it as the reference value, and determines the personnel with similar monitoring data among the matching target personnel according to the deviation amount between the monitoring data of different matching target personnel and the reference value; Optionally, the above step S11 includes the following content: S111 uses the historical personnel with a specific type of sports injury as the matching target personnel, determines the average value of the monitoring data of different matching target personnel by using the analysis results of the monitoring data of different matching target personnel, and takes it as the reference value, and determines the personnel with similar monitoring data among the matching target personnel according to the deviation amount between the monitoring data of different matching target personnel and the reference value; S112 When the number of personnel with similar monitoring data is less than the preset number of personnel, it is determined that the monitoring data does not belong to the associated monitoring data. When the number of personnel with similar monitoring data is not less than the preset number of personnel, go to step S113; S113 determines the injury matching coefficient between the monitoring data and the specific type of sports injury based on the number of personnel with similar monitoring data and the proportion of the number of personnel with similar monitoring data among the matching target personnel. When the injury matching coefficient is less than the preset matching coefficient threshold, it is determined that the monitoring data does not belong to the associated monitoring data. When the injury matching coefficient is not less than the preset matching coefficient threshold, go to step S12.

[0030] S12 uses the historical personnel other than the matching target personnel as other historical personnel, and determines the similar historical personnel among the other historical personnel by using the deviation amount from the reference value; Optionally, the above step S12 includes the following content: S121 uses the historical personnel other than the matching target personnel as other historical personnel. When it is determined that there are no similar historical personnel among the other historical personnel by using the deviation amount from the reference value, go to step S13. When it is determined that there are similar historical personnel among the other historical personnel by using the deviation amount from the reference value, go to step S122; S122 When the number of similar historical personnel is greater than the preset number of similar personnel, it is determined that the monitoring data does not belong to the associated monitoring data. When the number of similar historical personnel is not greater than the preset number of similar personnel, go to step S123; S123 determines the matching anomaly coefficient of the monitoring data and a specific type of sports injury based on the number of the similar historical personnel and the proportion of the number of the similar historical personnel among the other historical personnel. When the matching anomaly coefficient is greater than the preset anomaly coefficient threshold, it is determined that the monitoring data does not belong to the associated monitoring data. When the injury matching coefficient is not greater than the preset anomaly coefficient threshold, proceed to step S13.

[0031] S13 determines the injury correlation coefficient of the monitoring data and a specific type of sports injury based on the proportion of the number of the similar historical personnel among the other historical personnel and the proportion of the number of the personnel similar to the monitoring data among the matching target personnel. Determine the correlation coefficient based on the average value of the injury correlation coefficients with different types of sports injuries, and use the correlation coefficient to determine whether the monitoring data is associated monitoring data.

[0032] Optionally, the above step S13 includes the following content: S131 determines the injury correlation coefficient of the monitoring data and a specific type of sports injury based on the proportion of the number of the similar historical personnel among the other historical personnel and the proportion of the number of the personnel similar to the monitoring data among the matching target personnel. When there is a type of sports injury for which the loss correlation coefficient does not meet the requirements, it is determined that the monitoring data does not belong to the associated monitoring data. When there is no type of sports injury for which the loss correlation coefficient does not meet the requirements, proceed to step S132; S132 When it is determined that there is a type of sports injury for which the injury correlation coefficient is within the preset correlation coefficient interval based on the injury correlation coefficients with different types of sports injuries, proceed to step S133. When there is no type of sports injury for which the injury correlation coefficient is within the preset correlation coefficient interval, proceed to step S134; S133 When the number of types of sports injuries for which the injury correlation coefficient is within the preset correlation coefficient interval does not meet the requirements, it is determined that the monitoring data does not belong to the associated monitoring data. When the number of types of sports injuries for which the injury correlation coefficient is within the preset correlation coefficient interval meets the requirements, proceed to step S134; S134 determines the correlation coefficient based on the average value of the injury correlation coefficients with different types of sports injuries, and uses the correlation coefficient to determine whether the monitoring data is associated monitoring data.

[0033] S2 constructs multiple monitoring data groups based on the associated monitoring data, and determines the associated monitoring data groups in the monitoring data groups based on the number of monitoring data in different monitoring data groups and the correlation coefficients with different types of sports injuries; Further, constructing multiple monitoring data groups based on the associated monitoring data specifically includes: Freely combine the associated monitoring data to generate multiple monitoring data groups.

[0034] Specifically, as Figure 3 shown, the method for determining the associated monitoring data group in the monitoring data group is as follows: Determine the sum of the correlation coefficients between the monitoring data in the monitoring data group and different types of sports injuries, and use the sum of the correlation coefficients to determine the sum of the correlation coefficients with different types of sports injuries; Determine the group correlation coefficient based on the average value of the sum of the correlation coefficients with different types of sports injuries; Determine the data correlation coefficient of the monitoring data group according to the ratio of the group correlation coefficient to the number of associated monitoring data in the monitoring data group, and determine whether the monitoring data group is an associated monitoring data group based on the data correlation coefficient.

[0035] Furthermore, the associated monitoring data group is the monitoring data group with the largest data correlation coefficient.

[0036] In another embodiment, the method for determining the associated monitoring data group in the monitoring data group is as follows: Obtain the number of associated monitoring data in the monitoring data group. When the number of associated monitoring data in the monitoring data group is greater than the preset associated quantity threshold, it is determined that the associated monitoring data group does not belong to the monitoring data group; When the number of associated monitoring data in the monitoring data group is not greater than the preset associated quantity threshold: Determine the sum of the correlation coefficients between the monitoring data in the monitoring data group and different types of sports injuries, and use the sum of the correlation coefficients to determine the sum of the correlation coefficients with different types of sports injuries. When there are types of sports injuries whose sum of correlation coefficients does not meet the requirements, it is determined that the associated monitoring data group does not belong to the monitoring data group; When there are no types of sports injuries whose sum of correlation coefficients does not meet the requirements: Use the sum of the correlation coefficients to count the number of types of sports injuries within different correlation coefficient intervals. When the number of types of sports injuries within the preset correlation coefficient interval does not meet the requirements, it is determined that the associated monitoring data group does not belong to the monitoring data group; When the number of types of sports injuries within the preset correlation coefficient interval meets the requirements: Determine the group correlation coefficient based on the average value of the correlation coefficients related to different types of sports injuries. When the group correlation coefficient is not greater than the preset group coefficient threshold, it is determined that the associated monitoring data group does not belong to the monitoring data group; When the group correlation coefficient is greater than the preset group coefficient threshold: Determine the data correlation coefficient of the monitoring data group according to the ratio of the group correlation coefficient to the number of associated monitoring data in the monitoring data group, and determine whether the monitoring data group is an associated monitoring data group based on the data correlation coefficient.

[0037] S3 Use the associated monitoring data group to perform monitoring processing on the target person to obtain the monitoring data of the target person. Based on the analysis result of the monitoring data, determine the severity and occurrence probability of the target person's different types of sports injuries. When it is determined that the severity of the target person's injuries meets the requirements, proceed to the next step; Furthermore, the severity and occurrence probability of the target person's different types of sports injuries are determined according to the associated monitoring data in the associated monitoring data group. Among them, the associated monitoring data in the associated monitoring data group is used as the input quantity of the evaluation models for different types of sports losses, and the output quantities of the evaluation models for different types of sports injuries are used as the severity and occurrence probability of the target person's different types of sports injuries.

[0038] Specifically, the value range of the severity of the sports injury is between 0 and 1. The higher the severity of the sports injury, the more serious the sports injury.

[0039] It should be noted that determining that the severity of the target person's injuries meets the requirements specifically includes: Based on the occurrence probability of different types of sports injuries, determine the high-probability sports injuries; Based on the severity of the high-probability sports injuries, determine the high-probability sports injuries with a severity greater than the preset severity, and use them as the problematic sports injuries; Determine whether the severity of the target person's injuries meets the requirements based on the number of the problematic sports injuries.

[0040] Furthermore, the high-probability sports injuries are sports injuries with an occurrence probability greater than the preset probability threshold.

[0041] It should be noted that when the number of types of the problematic sports injuries is greater than the preset injury type number threshold, it is determined that the severity of the target person's losses does not meet the requirements.

[0042] It can be understood that when the severity of the injury of the target person does not meet the requirements, all the monitoring data of the target person is acquired, and the evaluation result of the sports injury of the target person is determined by using all the monitoring data.

[0043] In another embodiment, determining that the severity of the injury of the target person meets the requirements specifically includes: Based on the occurrence probabilities of different types of sports injuries and in combination with the severities of different types of sports injuries, determining the severity abnormality coefficients of different types of sports injuries; Determining the injury abnormality coefficient based on the average value of the severity abnormality coefficients of different types of sports injuries; Determining whether the severity of the injury of the target person meets the requirements through the injury abnormality coefficient.

[0044] Furthermore, the severity abnormality coefficient of the sports injury is determined according to the product of the severity and the occurrence probability of different types of sports injuries.

[0045] Specifically, when the injury abnormality coefficient is greater than the preset abnormality coefficient threshold, it is determined that the severity of the injury of the target person does not meet the requirements.

[0046] Optionally, determining that the severity of the loss of the target person meets the requirements specifically includes: Based on the occurrence probabilities of different types of sports injuries, when it is determined that there is no type of sports injury with an occurrence probability greater than the preset probability threshold, it is determined that the severity of the loss of the target person meets the requirements; When there is a type of sports injury with an occurrence probability greater than the preset probability threshold: Based on the severities of different types of sports injuries, when it is determined that there is no type of sports injury with a severity greater than the preset severity threshold, it is determined that the severity of the loss of the target person meets the requirements; When there is a type of sports injury with a severity greater than the preset severity threshold: Based on the occurrence probabilities of different types of sports injuries and in combination with the severities of different types of sports injuries, determining the severity abnormality coefficients of different types of sports injuries. When the severity abnormality coefficients of different types of sports injuries are all less than the preset coefficient threshold, it is determined that the severity of the loss of the target person meets the requirements; When there is a type of sports injury with a severity abnormality coefficient not less than the preset coefficient threshold: Based on the severity abnormality coefficients of different types of sports injuries, when it is determined that there is a type of sports injury with a severity abnormality coefficient greater than the abnormality coefficient setting value, it is determined that the severity of the loss of the target person does not meet the requirements; When there is no type of sports injury with a severity anomaly coefficient greater than the anomaly coefficient setting value: Take the type of sports injury with a severity anomaly coefficient not less than the preset coefficient threshold as the screened injury type. When the number of the screened injury types is greater than the preset type number, it is determined that the loss severity of the target person does not meet the requirements; When the number of the screened injury types is not greater than the preset type number: Determine the injury anomaly coefficient based on the average value of the severity anomaly coefficients of different types of sports injuries, and determine whether the injury severity of the target person meets the requirements through the injury anomaly coefficient.

[0047] S4 determines the target of secondary acquisition of the monitoring data of the target person through the severity and occurrence probability of different types of sports injuries of the target person, and determines the evaluation result of the sports injury of the target person through the secondary acquisition target and the monitoring data of the target person.

[0048] It should be noted that as Figure 4 shown, the method for determining the target of secondary acquisition of the monitoring data of the target person is: Determine the injury anomaly coefficient of the target person for different types of sports injuries by multiplying the severity and occurrence probability of different types of sports injuries of the target person; Determine the problem type in the type of the sports injury according to the injury anomaly coefficient, and determine the target of secondary acquisition of the monitoring data of the target person by using the associated monitoring data of the problem type.

[0049] Further, the problem type is the type of sports injury with an injury anomaly coefficient greater than the preset injury coefficient threshold.

[0050] It can be understood that the method for determining the evaluation result of the sports injury of the target person is: Take the secondary acquisition target and the monitoring data of the target person as the input quantities of the evaluation model, and take the output quantity of the evaluation model as the evaluation result of the sports injury of the target person.

[0051] Specifically, the evaluation result includes the type and development stage of the sports injury of the target person.

[0052] It should be noted that the evaluation model is constructed by using one or more of BP neural network, LSTM neural network and CNN convolutional neural network.

[0053] In the second aspect of Embodiment 2, as Figure 5As shown, the present invention provides a computer system, comprising: a memory and a processor connected communicatively, and a computer program stored on the memory and capable of running on the processor, wherein when the processor runs the computer program, it executes the above-mentioned method for evaluating sports injuries.

[0054] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0055] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0056] The above is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A sports injury assessment method, characterized in that: Specifically include: Based on the monitoring data of historical personnel with different types of sports injuries, determining the correlation coefficients between the monitoring data and the different types of sports injuries and the associated monitoring data in the monitoring data; constructing a plurality of monitoring data groups based on the associated monitoring data, and determining associated monitoring data groups in the monitoring data groups according to the number of monitoring data in different monitoring data groups and correlation coefficients with different types of sports injuries; Using the associated monitoring data group to perform monitoring processing on the target person to obtain monitoring data of the target person, determining the severity and occurrence probability of different types of sports injuries of the target person based on the analysis results of the monitoring data, and when determining that the severity of the injury of the target person meets the requirements using the severity and occurrence probability of the sports injury, proceeding to the next step; The secondary acquisition target of the target person's monitoring data is determined based on the severity and occurrence probability of different types of sports injuries of the target person, and the assessment result of the target person's sports injury is determined based on the secondary acquisition target and the monitoring data of the target person.

2. The sports injury assessment method according to claim 1, characterized in that: The types of sports injuries include abrasions, strains, bruises, sprains, dislocations, and fractures.

3. The sports injury assessment method according to claim 1, characterized in that: The monitoring data includes motion posture data, ultrasonic images, images of damaged parts, breathing data, heartbeat data, and ultrasonic echoes.

4. The sports injury assessment method according to claim 1, characterized in that: The method for determining the associated monitoring data is: Personnel with a history of a specific type of sports injury are used as matching target persons, and the average values ​​of the monitoring data of different matching target persons are determined by using the analysis results of the monitoring data of different matching target persons, and the average values ​​are used as reference values; Determine persons with similar monitoring data among the matching target persons according to the deviations between the monitoring data of different matching target persons and the reference value; The injury correlation coefficient between the monitoring data and a specific type of sports injury is determined based on the proportion of the number of persons similar to the monitoring data in the matching target persons, the correlation coefficient is determined based on the average value of the injury correlation coefficients with different types of sports injuries, and the correlation coefficient is used to determine whether the monitoring data is associated monitoring data.

5. The sports injury assessment method according to claim 4, characterized in that: The monitoring data similar persons are matching target persons whose monitoring data have a deviation from the reference value that is not greater than a preset deviation threshold.

6. The sports injury assessment method according to claim 1, characterized in that: Therefore, multiple monitoring data groups are constructed based on the associated monitoring data, specifically including: The associated monitoring data are freely combined to generate multiple monitoring data groups.

7. The sports injury assessment method according to claim 1, characterized in that: The method for determining the secondary acquisition target of the monitoring data of the target person is: Determine the injury abnormality coefficient of the target person in different types of sports injuries by multiplying the severity and occurrence probability of the target person in different types of sports injuries; The problem type in the type of sports injury is determined based on the injury abnormality coefficient, and the secondary acquisition target of the monitoring data of the target person is determined using the associated monitoring data of the problem type.

8. The sports injury assessment method according to claim 7, characterized in that: The problem type is a type of sports injury in which the injury abnormality coefficient is greater than a preset injury coefficient threshold.

9. The sports injury assessment method according to claim 1, characterized in that: The method for determining the evaluation result of the sports injury of the target person is: The monitoring data of the secondary acquisition target and the target person are used as inputs of an evaluation model, and the output of the evaluation model is used as an evaluation result of the sports injury of the target person.

10. A computer system comprising: A memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes a sports injury assessment method as described in any one of claims 1-9 when running the computer program.

Images