A method and system for sports injury assessment

Abstract

The present invention provides a method and system for evaluating sports injuries, belonging to the technical field of data evaluation. Specifically, it includes: using an associated monitoring data group to perform monitoring processing on a target person to obtain the 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 result of the monitoring data, and when it is determined that the severity of the target person's injury meets the requirements by using the severity and occurrence probability of the sports injury, determining 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 determining the evaluation result of the sports injury of the target person through the secondary acquisition target and the monitoring data of the target person, thereby improving the accuracy of the evaluation result of the sports injury.

Description

Technical Field

[0001] The present invention belongs to the technical field of data evaluation, and in particular relates to a sports injury evaluation method and system. Background Art

[0002] To assess sports injuries, the invention patent application CN202411276386.9, "A Method and System for Intelligent Assessment of Sports Injury Status," inputs reconstructed ultrasound images, medical history, and tissue injury severity into an assessment network model to obtain an assessment result of the sports injury status, thereby improving the accuracy of the assessment result of the sports injury status. However, the following technical problems exist:

[0003] When evaluating the status of sports injuries, the types of sports injuries that cause them vary for different people. At the same time, when evaluating different types of sports injuries, the degree of correlation between different types of monitoring data and the types of sports injuries also varies. Therefore, if the monitoring data cannot be obtained according to the type of sports injury of the person, it is impossible to improve the accuracy of the sports injury assessment results while reducing the amount of data collected.

[0004] In response to the above technical problems, this application specifically provides a sports injury assessment method and system. Summary of the Invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0006] According to one aspect of the present invention, a method for assessing sports injuries is provided.

[0007] A sports injury assessment method, specifically comprising:

[0008] S1: using historical monitoring data of people with different types of sports injuries, determining correlation coefficients between the monitoring data and the different types of sports injuries, and associated monitoring data in the monitoring data;

[0009] S2 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;

[0010] S3: monitoring the target person using the associated monitoring data group 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 proceeding to the next step when determining that the severity of the injury of the target person meets the requirements using the severity and occurrence probability of the sports injuries;

[0011] S4 determines the secondary acquisition target of the target person's monitoring data based on the severity and probability of occurrence 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 monitoring data of the target person.

[0012] The beneficial effects of the present invention are:

[0013] Based on the analysis results of the monitoring data, the severity and probability of occurrence of different types of sports injuries of the target personnel are determined, 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 the secondary acquisition target of the targeted monitoring data, reducing the difficulty of the assessment and treatment of sports injuries, and at the same time, while ensuring the accuracy of the assessment results of sports injuries, improving the efficiency of the assessment and treatment of sports injuries.

[0014] The severity and occurrence probability 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 realizes the screening of sports injuries with higher abnormalities based on the severity and occurrence probability 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 obtaining and processing monitoring data, and ensures the reliability of sports injury assessment and processing.

[0015] A further technical solution is that the types of sports injuries include abrasions, strains, contusions, sprains, dislocations, and fractures.

[0016] A further technical solution is that the monitoring data includes motion posture data, ultrasonic image, injury site image, respiratory data, heartbeat data, and ultrasonic echo.

[0017] A further technical solution is that the method for determining the associated monitoring data is:

[0018] Personnel with a history of a specific type of sports injury are used as matching target persons, and the average value of the monitoring data of different matching target persons is determined by using the analysis results of the monitoring data of different matching target persons, and the average value is used as a reference value;

[0019] Determining persons with similar monitoring data among the matching target persons based on deviations between the monitoring data of different matching target persons and the reference value;

[0020] Determine the injury correlation coefficient between the monitoring data and a specific type of sports injury based on the proportion of the number of personnel with similar monitoring data in the number of the matching target personnel, determine the correlation coefficient based on the average value of the injury correlation coefficients for different types of sports injuries, and use the correlation coefficient to determine whether the monitoring data is associated monitoring data.

[0021] A further technical solution is that the personnel with similar monitoring data are the matching target personnel whose deviation amount between the monitoring data and the reference value is not greater than a preset deviation threshold.

[0022] A further technical solution is that the method for determining the evaluation result of the sports injury of the target personnel is as follows:

[0023] Take the secondary acquisition target and the monitoring data of the target personnel 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 personnel.

[0024] A further technical solution is that the evaluation result includes the type and development stage of the sports injury of the target personnel.

[0025] A further technical solution is 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.

[0026] 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, and when the processor runs the computer program, it executes the above-mentioned sports injury evaluation method.

[0027] Other features and advantages will be described in the subsequent specification, and 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.

[0028] To make the above-mentioned objectives, features, and advantages of the present invention more obvious and understandable, the following specifically gives preferred embodiments and, in conjunction with the accompanying drawings, makes a detailed description as follows. Description of the Drawings

[0029] 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;

[0030] Figure 1 is a flowchart of a sports injury evaluation method;

[0031] Figure 2 is a flowchart of a method for determining associated monitoring data;

[0032] Figure 3 It is a flowchart of a method for determining an associated monitoring data group in a monitoring data group;

[0033] Figure 4 It is a flowchart of a method for determining a secondary acquisition target of monitoring data of a target person;

[0034] Figure 5 It is a framework diagram of a computer system. Specific implementation manners

[0035] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below 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 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 protection scope of this specification.

[0036] In this application, first, the recognition process of the type of sports injury of a target person is determined by using 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 process of the sports injury of the target person is performed by using the secondary recognition target.

[0037] Taking historical persons with a specific type of sports injury 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 injury. When the correlation coefficient is greater than 0.6, the monitoring data is determined as associated monitoring data.

[0038] Determining the sum of the correlation coefficients between the monitoring data and different types of sports injury based on the correlation coefficients between the monitoring data and different types of sports injury, and determining the group correlation coefficient by using the average value of the sum of the correlation coefficients of different types of sports injury. 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.

[0039] Embodiment 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 sports injury assessment method, specifically including:

[0040] S1 determines the correlation coefficient between the monitoring data and different types of sports injuries, as well as the associated monitoring data in the monitoring data, based on the monitoring data of historical personnel under different types of sports injuries.

[0041] Furthermore, the types of sports injuries include abrasions, strains, contusions, sprains, dislocations, and fractures.

[0042] Specifically, the monitoring data includes motion posture data, ultrasonic images, injury site images, respiratory data, heartbeat data, and ultrasonic echoes.

[0043] Specifically, as Figure 2 shown, the method for determining the associated monitoring data is as follows:

[0044] Taking historical personnel with a specific type of sports injury 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;

[0045] Determining similar personnel in the monitoring data of the matching target personnel based on the deviation amount between the monitoring data of different matching target personnel and the reference value;

[0046] Based on the proportion of the number of similar personnel in the monitoring data to the number of the matching target personnel, determining the injury correlation coefficient between the monitoring data and the specific type of sports injury, determining the correlation coefficient based on the average value of the injury correlation coefficients with different types of sports injuries, and using the correlation coefficient to determine whether the monitoring data is associated monitoring data.

[0047] Optionally, the similar personnel in the 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.

[0048] In another embodiment, the method for determining the associated monitoring data is as follows:

[0049] Taking historical personnel with a specific type of sports injury 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;

[0050] Taking historical personnel other than the matching target personnel as other historical personnel, and determining similar historical personnel among the other historical personnel using the deviation amount from the reference value;

[0051] Determine the data correlation coefficient between the monitoring data and a specific type of sports injury based on the proportion of the number of the similar historical personnel among other historical personnel, determine the correlation coefficient based on the average value of the data correlation coefficients for different types of sports injuries, and use the correlation coefficient to determine whether the monitoring data is associated monitoring data.

[0052] Furthermore, when the number of the similar historical personnel is greater than the preset similar personnel number threshold, it is determined that the monitoring data does not belong to the associated monitoring data.

[0053] Optionally, the method for determining the associated monitoring data is as follows:

[0054] S11 Use the historical personnel with a specific type of sports injury as the matching target personnel, determine 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 take it as the reference value, and determine the similar monitoring data personnel among the matching target personnel according to the deviation amount between the monitoring data of different matching target personnel and the reference value;

[0055] Optionally, the above step S11 includes the following content:

[0056] S111 Use the historical personnel with a specific type of sports injury as the matching target personnel, determine 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 take it as the reference value, and determine the similar monitoring data personnel among the matching target personnel according to the deviation amount between the monitoring data of different matching target personnel and the reference value;

[0057] S112 When the number of the similar monitoring data personnel is less than the preset personnel number, it is determined that the monitoring data does not belong to the associated monitoring data. When the number of the similar monitoring data personnel is not less than the preset personnel number, proceed to step S113;

[0058] S113 Determine the injury matching coefficient between the monitoring data and a specific type of sports injury based on the number of the similar monitoring data personnel and the proportion of the number of the similar monitoring data personnel 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, proceed to step S12.

[0059] S12 Use the historical personnel other than the matching target personnel as other historical personnel, and determine the similar historical personnel among the other historical personnel by using the deviation amount from the reference value;

[0060] Optionally, the above step S12 includes the following content:

[0061] S121 takes the historical personnel other than the matched 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, it proceeds 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, it proceeds to step S122;

[0062] S122 When the number of the 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 the similar historical personnel is not greater than the preset number of similar personnel, it proceeds to step S123;

[0063] S123 determines the matching anomaly coefficient of the monitoring data with 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, it proceeds to step S13.

[0064] S13 determines the injury correlation coefficient of the monitoring data with 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 similar personnel in the monitoring data among the matched target personnel, 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.

[0065] Optionally, the following content is included in the above step S13:

[0066] S131 determines the injury correlation coefficient of the monitoring data with 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 similar personnel in the monitoring data among the matched 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, it proceeds to step S132;

[0067] 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, it proceeds to step S133. When there is no type of sports injury for which the injury correlation coefficient is within the preset correlation coefficient interval, it proceeds to step S134;

[0068] If the number of types of sports injuries with injury correlation coefficients within the preset correlation coefficient range 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 with injury correlation coefficients within the preset correlation coefficient range meets the requirements, proceed to step S134;

[0069] S134 Determine the correlation coefficient based on the average value of the injury correlation coefficients of different types of sports injuries, and use the correlation coefficient to determine whether the monitoring data is associated monitoring data.

[0070] S2 Construct multiple monitoring data groups based on the associated monitoring data, and determine 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 coefficients with different types of sports injuries;

[0071] Further, constructing multiple monitoring data groups based on the associated monitoring data specifically includes:

[0072] Freely combine the associated monitoring data to generate multiple monitoring data groups.

[0073] Specifically, as Figure 3 shown, the method for determining the associated monitoring data group in the monitoring data group is:

[0074] Determine the sum of the correlation coefficients between the monitoring data in the monitoring data group and different types of sports injuries based on 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;

[0075] Determine the group correlation coefficient based on the average value of the sum of the correlation coefficients with different types of sports injuries;

[0076] 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.

[0077] Further, the associated monitoring data group is the monitoring data group with the largest data correlation coefficient.

[0078] In another embodiment, the method for determining the associated monitoring data group in the monitoring data group is:

[0079] 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;

[0080] When the number of associated monitoring data in the monitoring data group is not greater than the preset associated quantity threshold:

[0081] Determine the sum of the correlation coefficients between the monitoring data in the monitoring data group and different types of sports injuries based on the correlation coefficients between the monitoring data 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 for which the sum of the correlation coefficients does not meet the requirements, it is determined that the associated monitoring data group does not belong to the monitoring data group;

[0082] When there are no types of sports injuries for which the sum of the correlation coefficients does not meet the requirements:

[0083] 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;

[0084] When the number of types of sports injuries within the preset correlation coefficient interval meets the requirements:

[0085] Determine the group correlation coefficient based on the average value of the sum of the correlation coefficients with 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;

[0086] 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.

[0087] 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;

[0088] Furthermore, the severity and occurrence probability of the target person's different types of sports injuries are determined based on 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 injuries, 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.

[0089] Specifically, the value range of the severity of the sports injury is between 0 and 1, where the higher the severity of the sports injury, the more severe the sports injury.

[0090] It should be noted that determining that the severity of the injury of the target person meets the requirements specifically includes:

[0091] Based on the occurrence probabilities of different types of sports injuries, determine the high-probability sports injuries;

[0092] 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 problematic sports injuries;

[0093] Determine whether the severity of the injury of the target person meets the requirements based on the number of the problematic sports injuries.

[0094] Furthermore, the high-probability sports injuries are sports injuries with an occurrence probability greater than the preset probability threshold.

[0095] 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 loss of the target person does not meet the requirements.

[0096] 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 are obtained, and the evaluation result of the sports injury of the target person is determined using all the monitoring data.

[0097] In another embodiment, determining that the severity of the injury of the target person meets the requirements specifically includes:

[0098] Based on the occurrence probabilities of different types of sports injuries and in combination with the severity of different types of sports injuries, determine the severity abnormality coefficients of different types of sports injuries;

[0099] Determine the injury abnormality coefficient based on the average value of the severity abnormality coefficients of different types of sports injuries;

[0100] Determine whether the severity of the injury of the target person meets the requirements through the injury abnormality coefficient.

[0101] 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.

[0102] 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.

[0103] Optionally, determining that the loss severity of the target person meets the requirements specifically includes:

[0104] 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, then it is determined that the loss severity of the target person meets the requirements;

[0105] When there is a type of sports injury with an occurrence probability greater than the preset probability threshold:

[0106] 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, then it is determined that the loss severity of the target person meets the requirements;

[0107] When there is a type of sports injury with a severity greater than the preset severity threshold:

[0108] Based on the occurrence probabilities of different types of sports injuries and in combination with the severities of different types of sports injuries, determine 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, then it is determined that the loss severity of the target person meets the requirements;

[0109] When there is a type of sports injury with a severity abnormality coefficient not less than the preset coefficient threshold:

[0110] 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, then it is determined that the loss severity of the target person does not meet the requirements;

[0111] When there is no type of sports injury with a severity abnormality coefficient greater than the abnormality coefficient setting value:

[0112] Take the types of sports injuries with severity abnormality coefficients not less than the preset coefficient threshold as the screened injury types. When the number of the screened injury types is greater than the preset type number, then it is determined that the loss severity of the target person does not meet the requirements;

[0113] When the number of the screened injury types is not greater than the preset type number:

[0114] Determine the injury abnormality coefficient based on the average value of the severity abnormality coefficients of different types of sports injuries, and determine whether the injury severity of the target person meets the requirements through the injury abnormality coefficient.

[0115] S4 determines the target of secondary acquisition of the monitoring data of the target person based on 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.

[0116] 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:

[0117] Taking the product of the severity and occurrence probability of different types of sports injuries of the target person, determine the injury abnormality coefficient of the target person for different types of sports injuries;

[0118] Determine the problem type in the type of the sports injury according to the injury abnormality coefficient, and use the associated monitoring data of the problem type to determine the target of secondary acquisition of the monitoring data of the target person.

[0119] Further, the problem type is the type of sports injury with an injury abnormality coefficient greater than the preset injury coefficient threshold.

[0120] It can be understood that the method for determining the evaluation result of the sports injury of the target person is:

[0121] Taking the secondary acquisition target and the monitoring data of the target person 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 person.

[0122] Specifically, the evaluation result includes the type and development stage of the sports injury of the target person.

[0123] 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.

[0124] In the second aspect of Embodiment 2, as Figure 5 shown, 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, and the processor executes the above-mentioned sports injury evaluation method when running the computer program.

[0125] 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 devices, apparatuses, and non-volatile computer storage media, 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.

[0126] 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 result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0127] 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 changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A method for evaluating sports injuries, characterized in that, Specifically, it includes: Determine the correlation coefficient between the monitoring data and different types of sports injuries, as well as the associated monitoring data in the monitoring data, based on the monitoring data of historical personnel under different types of sports injuries; Construct multiple monitoring data groups based on the associated monitoring data, and determine 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; Use the associated monitoring data group to perform monitoring processing on the target personnel to obtain the monitoring data of the target personnel. Based on the analysis results of the monitoring data, determine the severity and occurrence probability of the target personnel in different types of sports injuries. When the severity of the sports injury meets the requirements, proceed to the next step; Determine the secondary acquisition target of the monitoring data of the target personnel through the severity and occurrence probability of the target personnel in different types of sports injuries, and determine the evaluation result of the sports injury of the target personnel through the secondary acquisition target and the monitoring data of the target personnel; The method for determining the associated monitoring data is: Take the historical personnel with specific types of sports injuries as the matching target personnel, and use the analysis results of the monitoring data of different matching target personnel to determine the average value of the monitoring data of different matching target personnel, and use it as the reference value; Determine the personnel with similar monitoring data in 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, determine the injury correlation coefficient between the monitoring data and specific types of sports injuries. Based on the average value of the injury correlation coefficients with different types of sports injuries, determine the correlation coefficient, and use the correlation coefficient to determine whether the monitoring data is associated monitoring data.

2. The exercise injury assessment method according to claim 1, wherein, The types of sports injuries include abrasions, strains, contusions, sprains, dislocations, and fractures.

3. The exercise injury assessment method according to claim 1, wherein, The monitoring data includes sports posture data, ultrasonic images, injury site images, respiratory data, heartbeat data, and ultrasonic echoes.

4. The exercise injury assessment method according to claim 1, wherein, The personnel with similar monitoring data are the matching target personnel whose deviation amount between the monitoring data and the reference value does not exceed the preset deviation threshold.

5. The sports injury assessment method according to claim 1, characterized in that 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.

6. The exercise injury assessment method according to claim 1, wherein, The method for determining the secondary acquisition target of the monitoring data of the target personnel is: Determine the injury anomaly coefficient of the target personnel in different types of sports injuries by multiplying the severity and occurrence probability of the target personnel in different types of sports injuries; Determine the problem type in the type of sports injury according to the injury anomaly coefficient, and use the associated monitoring data of the problem type to determine the secondary acquisition target of the monitoring data of the target personnel.

7. The sports injury assessment method according to claim 6, wherein, The problem type is the type of sports injury with an injury anomaly coefficient greater than the preset injury coefficient threshold.

8. The sports injury assessment method according to claim 1, wherein, The method for determining the evaluation result of the sports injury of the target person is as follows: Taking the secondary acquisition target and the monitoring data of the target person as the input quantity of the evaluation model, and taking the output quantity of the evaluation model as the evaluation result of the sports injury of the target person.

9. A computer system, comprising: 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 a sports injury evaluation method according to any one of claims 1-8.

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