Method, apparatus, and electronic device for prompting of sports injury

Abstract

The embodiment of the present application provides a kind of movement injury prompt method, device and electronic equipment, in the method, in response to identifying movement data detection equipment, the identification of movement data detection equipment is displayed on the interface of terminal, and movement data detection equipment is used to collect the motion parameter of user;In response to the motion instruction of user, wake-up instruction is sent to movement data detection equipment;The motion parameter of user is received from movement data detection equipment;If there is movement injury risk in the motion process of user according to motion parameter, output first prompt information, and first prompt information is used to prompt that there is movement injury risk in the user.The embodiment of the present application can detect that there is movement injury risk in the motion process of user according to the motion parameter of user in the process of user motion, and effectively prompt user in time, which can avoid movement injury.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, device, and electronic device for alerting sports injuries. Background Technology

[0002] More and more users are starting to exercise and stay fit. During exercise, users can use their devices to record information such as exercise duration. At the end of the exercise, the device can also display the calories burned, heart rate changes, and other data, all of which provide users with a good experience.

[0003] However, many users exercise with incorrect postures, and prolonged use of these incorrect postures can cause injury to their bodies. Currently, users only undergo physical examinations after a sports injury has occurred, meaning the injury has already taken place. Therefore, there is an urgent need for a method to prevent sports injuries. Summary of the Invention

[0004] This application provides a method, device, and electronic device for alerting users to sports injuries, which can help prevent users from sustaining sports injuries.

[0005] Firstly, this application provides a method for alerting users to sports injuries. The execution entity of this method can be a terminal or a chip within the terminal; the following description uses a terminal as an example. In this method, in response to recognizing a sports data detection device, the terminal displays the identifier of the sports data detection device on its interface. The sports data detection device is used to collect the user's sports parameters. In one embodiment, before the user starts exercising, the terminal can be triggered to recognize the sports data detection device. The recognition method may include, but is not limited to, radio frequency identification (RFID) tag recognition, near field communication (NFC) recognition, etc.

[0006] After the terminal identifies the motion data detection device, the user can trigger the terminal to cause the motion data detection device to start collecting motion parameters. Specifically, in response to the user's movement command, the terminal sends a wake-up command to the motion data detection device, causing it to begin collecting motion parameters. In this embodiment, when the user is using the motion data detection device, the terminal can trigger the device to collect motion parameters, avoiding the problem of the device collecting motion parameters even when the user is not exercising, and reducing the power consumption of the motion data detection device.

[0007] In this embodiment, after collecting motion parameters, the motion data detection device can send the user's motion parameters to the terminal. Correspondingly, the terminal can receive the user's motion parameters from the motion data detection device. In this application embodiment, the terminal can detect whether there is a risk of sports injury during the user's exercise based on the real-time acquired motion parameters. If a risk of sports injury is detected based on the motion parameters, the terminal outputs a first prompt message to alert the user of the risk of sports injury.

[0008] In this embodiment, during the user's exercise, the terminal can detect the risk of sports injury based on the user's real-time exercise parameters and promptly and effectively alert the user to avoid sports injury.

[0009] In one possible implementation, the motion data detection device is at least one. For example, the motion data detection device includes: a first motion data detection device and a second motion data detection device, the first motion data detection device being disposed on the user's foot, and the second motion data detection device being disposed on the user's waist. The motion parameters include a first set of motion parameters and a second set of motion parameters, the first set of motion parameters being foot motion parameters during the user's movement, and the second set of motion parameters being waist motion parameters during the user's movement.

[0010] For example, the first set of motion parameters includes at least one of the following: stride length, stride frequency, stride speed, ground contact time, air time, swing angle, rollover angle, landing mode, ground contact-to-air ratio, peak ground contact, and ground impact force; the second set of motion parameters includes at least one of the following: waist vertical amplitude and ground contact balance.

[0011] The first motion data detection device includes a first inertial sensor, and the second motion data detection device includes a second inertial sensor. In response to a wake-up command from the terminal, the first motion data detection device controls the first inertial sensor to collect first sensor data, and then processes the first sensor data to obtain the first set of motion parameters. Correspondingly, in response to the wake-up command from the terminal, the second motion data detection device controls the second inertial sensor to collect second sensor data, and then processes the second sensor data to obtain the second set of motion parameters.

[0012] In this approach, the terminal can detect whether there is a risk of sports injury during the user's exercise based on the first set of motion parameters and the second set of motion parameters. For example, the terminal can input the first set of motion parameters and the second set of motion parameters into a first injury risk model to obtain a result indicating whether there is a risk of sports injury during the user's exercise, whereby the result is either a risk of sports injury exists or no risk of sports injury exists. In this approach, the first injury risk model is used to characterize the mapping relationship between the "first set of motion parameters and the second set of motion parameters" and the result indicating whether there is a risk of sports injury during the user's exercise.

[0013] In one embodiment, the terminal can also combine some parameters from the first set of motion parameters and some parameters from the second set of motion parameters to obtain a third set of motion parameters. For example, if the first set of motion parameters includes the stride length, the second set of motion parameters includes the vertical amplitude of the waist, and the third set of motion parameters includes the vertical stride ratio, the terminal can use the ratio of the vertical amplitude of the waist to the stride length as the vertical stride ratio.

[0014] In this embodiment, the terminal can detect whether there is a risk of sports injury during the user's exercise based on the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters. For example, the terminal can input the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters into a first injury risk model to obtain a result indicating whether there is a risk of sports injury during the user's exercise, where the result is either a risk of sports injury exists or no risk of sports injury exists.

[0015] In this embodiment, the first injury risk model is used to characterize the mapping relationship between "the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters" and the result of whether there is a risk of motion injury during the user's movement.

[0016] When the result indicates a risk of sports injury, the first injury risk model is further used to output the target parameter that causes the risk of sports injury, the parameter value of the target parameter, and the type of sports injury caused by the target parameter. The first prompt information includes: the target parameter, the parameter value of the target parameter, and the type of sports injury.

[0017] In this embodiment, the terminal can obtain the exercise suggestions corresponding to the target parameters based on the target parameters and the correspondence between the parameters and the exercise suggestions. The first prompt information also includes the exercise suggestions corresponding to the target parameters. In this embodiment, when outputting the first prompt information, the terminal can also output exercise suggestions, which can guide the user to perform correct exercises and effectively avoid sports injuries.

[0018] In one possible implementation, if the material of the ground on which the user is moving is inappropriate, it may also cause injury to the user's movement. Therefore, the terminal can obtain the material of the ground on which the user is moving, and then detect whether there is a risk of sports injury during the user's movement based on the material of the ground, the first set of movement parameters, and the second set of movement parameters (and may also include a third set of movement parameters, if any).

[0019] In one embodiment, a user can use an image acquisition device, such as smart glasses, during movement to capture images of the ground where the user is moving. In this embodiment, in response to the movement command, the terminal can send an image acquisition command to the image acquisition device, instructing the device to acquire an image. Correspondingly, the terminal can receive images from the image acquisition device and then determine the material of the ground based on the images.

[0020] In one embodiment, in response to the movement command, the terminal may output a second prompt message, which instructs the user to use the terminal to capture an image of the ground on which the user is moving. In this embodiment, the user can use the terminal to capture an image of the ground; correspondingly, the terminal, in response to the capture command, captures the image and then obtains the material of the ground based on the image.

[0021] In one embodiment, in response to the movement command, a third prompt message can be output, which instructs the user to select the material of the surface to be moved on from the list of surface materials provided by the terminal. For example, the terminal can display the surface materials to be selected on the interface for the user to choose from, thus determining the surface material based on the user's selection.

[0022] After obtaining the ground material, the terminal can input the ground material, the first set of motion parameters, and the second set of motion parameters into the second injury risk model to obtain the result of whether there is a risk of sports injury during the user's movement. The result is either that there is a risk of sports injury or that there is no risk of sports injury.

[0023] When the result indicates a risk of sports injury, the second injury risk model is further used to output: the target parameter that causes the risk of sports injury due to movement on the ground material, the parameter value of the target parameter, and the type of sports injury caused by the target parameter. The first prompt information includes: the ground material, the target parameter, the parameter value of the target parameter, and the type of sports injury.

[0024] It should be understood that the second injury risk model is used to characterize the mapping relationship between "the material of the ground, the first set of motion parameters, and the second set of motion parameters" and the result of whether there is a risk of sports injury during the user's movement.

[0025] In this embodiment, the terminal combines the ground material with the user's real-time motion parameters to improve the accuracy of detecting the risk of sports injuries.

[0026] In one possible implementation, the terminal can also combine historical motion parameters from the user's past movement history with various data from the current user movement to detect whether there is a risk of sports injury during the user's movement. For example, the terminal can detect whether there is a risk of sports injury during the user's movement based on the historical motion parameters from the user's past movement history, the material of the ground, the first set of motion parameters, and the second set of motion parameters (and may also include a third set of motion parameters, if any).

[0027] For example, the terminal can input the historical motion parameters of the user's historical motion process, the material of the ground, the first set of motion parameters, and the second set of motion parameters into the third injury risk model to obtain the result of whether there is a risk of motion injury during the user's motion process. The result is either that there is a risk of motion injury or that there is no risk of motion injury.

[0028] It should be understood that the third injury risk model is used to characterize the mapping relationship between "the user's historical motion parameters during the historical motion process, the material of the ground, the first set of motion parameters, and the second set of motion parameters" and the result of whether there is a risk of sports injury during the user's motion process.

[0029] In this embodiment, the historical motion parameters of the end user during the historical motion process, combined with the ground material and the user's real-time motion parameters, can further improve the accuracy of detecting the existence of sports injury risks.

[0030] Secondly, embodiments of this application provide a sports injury alert device, which can be a terminal or a chip within a terminal as described in the first aspect above. The device may include:

[0031] The display module is used to display the identifier of the motion data detection device on the terminal interface in response to the detection of the motion data detection device, which is used to collect the user's motion parameters.

[0032] The transceiver module is used to respond to the user's motion commands by sending a wake-up command to the motion data detection device and receiving the user's motion parameters from the motion data detection device.

[0033] The output module is used to output a first prompt message if, based on the motion parameters, a risk of sports injury is detected during the user's exercise. The first prompt message is used to alert the user of the risk of sports injury.

[0034] In one possible implementation, the motion data detection device includes: a first motion data detection device and a second motion data detection device, wherein the first motion data detection device is disposed on the user's foot and the second motion data detection device is disposed on the user's waist, and the motion parameters include a first set of motion parameters and a second set of motion parameters, wherein the first set of motion parameters is the foot motion parameters during the user's exercise and the second set of motion parameters is the waist motion parameters during the user's exercise.

[0035] In one possible implementation, the processing module is configured to detect whether there is a risk of sports injury during the user's movement based on the first set of motion parameters and the second set of motion parameters.

[0036] In one possible implementation, the processing module is specifically used to obtain a third set of motion parameters based on some parameters in the first set of motion parameters and some parameters in the second set of motion parameters; and to detect whether there is a risk of sports injury during the user's exercise based on the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters.

[0037] In one possible implementation, the processing module is specifically used to input the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters into the first injury risk model to obtain a result indicating whether there is a risk of motion injury during the user's movement, wherein the result is either that there is a risk of motion injury or that there is no risk of motion injury.

[0038] In one possible implementation, the first set of motion parameters includes at least one of the following: stride length, stride frequency, stride speed, ground contact time, air time, swing angle, rollover angle, landing mode, ground contact-to-air ratio, peak ground contact, and ground impact force; the second set of motion parameters includes at least one of the following: waist vertical amplitude and ground contact balance.

[0039] In one possible implementation, the first set of motion parameters includes the stride length, the second set of motion parameters includes the waist vertical amplitude, and the third set of motion parameters includes the vertical stride ratio; the processing module is specifically used to use the ratio of the waist vertical amplitude to the stride length as the vertical stride ratio.

[0040] In one possible implementation, when the result indicates a risk of sports injury, the first injury risk model is further configured to output the target parameter that causes the risk of sports injury, the parameter value of the target parameter, and the type of sports injury caused by the target parameter. The first prompt information includes the target parameter, the parameter value of the target parameter, and the type of sports injury.

[0041] In one possible implementation, the processing module is further configured to obtain the motion suggestion corresponding to the target parameter based on the target parameter and the correspondence between the parameter and the motion suggestion, wherein the first prompt information further includes the motion suggestion corresponding to the target parameter.

[0042] In one possible implementation, the processing module is further configured to acquire the material of the ground on which the user is moving, and to detect whether there is a risk of sports injury during the user's movement based on the material of the ground, the first set of movement parameters, and the second set of movement parameters.

[0043] In one possible implementation, the transceiver module is further configured to, in response to the motion command, send an image acquisition command to the image acquisition device, the image acquisition command instructing the image acquisition device to acquire an image, and to receive an image from the image acquisition device. The processing module is specifically configured to obtain the material of the ground based on the image.

[0044] In one possible implementation, the output module is further configured to output a second prompt message in response to the motion command, the second prompt message being used to instruct the user to use the terminal to capture an image of the ground in which the user is moving.

[0045] The shooting module is used to capture images in response to shooting commands.

[0046] The processing module is specifically used to obtain the material of the ground based on the image.

[0047] In one possible implementation, the output module is further configured to output a third prompt message in response to the motion command, the third prompt message being used to instruct the user to select the material of the ground to be moved on from the materials of the ground to be selected provided by the terminal.

[0048] The processing module is specifically used to determine the material of the ground based on the user's selection operation.

[0049] In one possible implementation, the processing module is specifically used to input the ground material, the first set of motion parameters, and the second set of motion parameters into the second injury risk model to obtain a result indicating whether there is a risk of motion injury during the user's movement, wherein the result is either that there is a risk of motion injury or that there is no risk of motion injury.

[0050] In one possible implementation, when the result indicates a risk of sports injury, the second injury risk model is further configured to output: a target parameter that causes a risk of sports injury due to movement on the material of the ground, the parameter value of the target parameter, and the type of sports injury caused by the target parameter. The first prompt information includes: the material of the ground, the target parameter, the parameter value of the target parameter, and the type of sports injury.

[0051] In one possible implementation, the processing module is specifically used to detect whether there is a risk of sports injury during the user's movement based on the user's historical movement parameters, the material of the ground, the first set of movement parameters, and the second set of movement parameters.

[0052] In one possible implementation, the processing module is specifically used to input the historical motion parameters of the user's historical motion process, the material of the ground, the first set of motion parameters, and the second set of motion parameters into the third injury risk model to obtain a result indicating whether there is a risk of motion injury during the user's motion process, wherein the result is either that there is a risk of motion injury or that there is no risk of motion injury.

[0053] Thirdly, embodiments of this application provide an electronic device that may include a processor and a memory. The memory stores computer-executable program code, which includes instructions. When the processor executes the instructions, the instructions cause the electronic device to perform the steps executed by the terminal in the first aspect, thereby implementing the method in the first aspect.

[0054] Fourthly, embodiments of this application provide a computer program product containing instructions that, when run on a computer, causes the computer to perform the steps executed by the terminal in the first aspect, thereby implementing the method in the first aspect.

[0055] Fifthly, embodiments of this application provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the steps executed by the terminal in the first aspect, thereby implementing the method in the first aspect.

[0056] In a sixth aspect, embodiments of this application provide a sports injury alert system, which includes: a sports data detection device and a terminal, the system being used to implement the method described in the first aspect above.

[0057] In one embodiment, the motion data detection device includes a first motion data detection device and a second motion data detection device. The first motion data detection device is disposed on the user's foot, and the second motion data detection device is disposed on the user's waist. The motion parameters include a first set of motion parameters and a second set of motion parameters, wherein the first set of motion parameters is the foot motion parameters during the user's exercise, and the second set of motion parameters is the waist motion parameters during the user's exercise.

[0058] In one embodiment, the system may further include an image acquisition device, such as smart glasses.

[0059] The beneficial effects of the various possible implementations of the second to sixth aspects mentioned above can be found in the beneficial effects of the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0060] Figure 1 A schematic diagram illustrating the applicable scenarios for the sports injury alert method provided in this application embodiment;

[0061] Figure 2 A schematic diagram of the structure of the first motion data detection device provided in the embodiments of this application;

[0062] Figure 3 A schematic diagram of the interface of a terminal provided in an embodiment of this application;

[0063] Figure 4 A flowchart illustrating one embodiment of the sports injury alerting method provided in this application;

[0064] Figure 5 Another schematic diagram of the terminal interface provided in this application embodiment;

[0065] Figure 6 Another schematic diagram of the terminal interface provided in this application embodiment;

[0066] Figure 7 A flowchart illustrating one embodiment of the sports injury alerting method provided in this application;

[0067] Figure 8 A schematic diagram of the process for training the first damage risk model provided in an embodiment of this application;

[0068] Figure 9 Another schematic diagram of the terminal interface provided in this application embodiment;

[0069] Figure 10 A schematic diagram illustrating another scenario to which the sports injury alert method provided in the embodiments of this application is applicable;

[0070] Figure 11 A schematic flowchart of another embodiment of the sports injury alerting method provided in this application;

[0071] Figure 12 Another schematic diagram of the terminal interface provided in this application embodiment;

[0072] Figure 13 A schematic flowchart of another embodiment of the sports injury alerting method provided in this application;

[0073] Figure 14 A schematic flowchart of another embodiment of the sports injury alerting method provided in this application;

[0074] Figure 15 A schematic flowchart of another embodiment of the sports injury alerting method provided in this application;

[0075] Figure 16 A schematic flowchart of another embodiment of the sports injury alerting method provided in this application;

[0076] Figure 17 A schematic diagram of a sports injury alert device provided in an embodiment of this application;

[0077] Figure 18 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0078] Figure 1 This is a schematic diagram illustrating a scenario to which the sports injury alert method provided in this application is applicable. (Refer to...) Figure 1 This scenario may include: a first motion data detection device 11, a second motion data detection device 12, and a terminal 13. In one embodiment, such as when a user is running, the first motion data detection device 11 can be placed on the user's feet, and the second motion data detection device 12 can be placed on the user's waist. In one embodiment, such as when a user is doing yoga, the first motion data detection device 11 can be placed on the user's arm, and the second motion data detection device 12 can be placed on the user's calf. It should be understood that... Figure 1 Taking running as an example, and using a mobile phone as the terminal 13, this will be explained.

[0079] It should be understood that the placement of the first motion data detection device 11 and the second motion data detection device 12 may differ depending on the type of exercise the user is performing. In one embodiment, Figure 1The scenario shown may include, but is not limited to, two motion data detection devices, or more motion data detection devices. Figure 1 The following embodiments use two motion data detection devices as an example. Taking a user running as an example, the structure and function of the first motion data detection device 11 and the second motion data detection device 12 are introduced, as well as the method for alerting sports injuries provided in the embodiments of this application.

[0080] Figure 2 This is a schematic diagram of a first motion data detection device provided in an embodiment of this application. (Refer to...) Figure 2 The first motion data detection device 11 includes a fixing component 111 and a data acquisition component 112. The data acquisition component 112 is detachably mounted on the fixing component 111, which can be positioned on a user's body part. For example, before exercise, the fixing component 111 can be positioned on the user's waist (or foot), and the data acquisition component 112 can be mounted on the fixing component 111. For example, the fixing component 111 can be strapped to the user's waist or attached to the user's shoes. This application embodiment does not limit the way the fixing component is positioned on the user's body part.

[0081] The data acquisition component 112 is used to acquire six-axis data. The six-axis data includes three-axis acceleration data and three-axis gyroscope data. For example, the data acquisition component 112 may include a three-axis accelerometer and a three-axis gyroscope to acquire three-axis acceleration data and three-axis gyroscope data respectively, or the data acquisition component 112 may be an inertial sensor that integrates the functions of a three-axis accelerometer and a three-axis gyroscope.

[0082] In one embodiment, the first motion data detection device 11 may further include a processor 113. The processor 113 may be disposed in the fixed component 111 or the data acquisition component 112, and the processor 113 may be a chip or other component with processing capabilities. The processor 113 is used to process the six-axis data acquired by the data acquisition component 112 based on a preset algorithm in the processor 113 to obtain the user's motion parameters during the motion process.

[0083] For example, when the first motion data detection device is a device installed on the foot, the processor 113 can process six-axis data to obtain foot motion parameters such as stride length, cadence, gait speed, ground contact time, airtime, ground contact-to-air ratio, peak ground contact, impact force (ground impact force), supination angle, swing angle, and landing pattern. Similarly, when the first motion data detection device is a device installed on the waist, the processor 113 can process six axes to obtain waist motion parameters such as waist amplitude and ground contact balance.

[0084] In one embodiment, the processor 113 is disposed in the fixed component 111. The components included in the second motion data detection device 12 are the same as those in the first motion data detection device 11. The difference is that the processor in the second motion data detection device 12 and the processor 113 in the first motion data detection device 11 store different preset algorithms to perform different processing on the six-axis data to obtain different motion parameters.

[0085] In this embodiment, because the processor is housed within a fixed component, and the fixed component can be positioned on different parts of the user's body in various ways, and the data acquisition components are all used to acquire six-axis data, the data acquisition components in the second motion data detection device 12 and the first motion data detection device 11 can be used interchangeably. For example, the first motion data detection device 11 is a device mounted on the foot, and the second motion data detection device 12 is a device mounted on the waist. The processor 113 is housed within the fixed component 111, and the processor 113 may be pre-configured with a first preset algorithm for processing six-axis data to obtain foot motion parameters. The processor in the second motion data detection device 12 may be pre-configured with a second preset algorithm for processing six-axis data to obtain waist motion parameters.

[0086] In one embodiment, the fixing component 111 is provided with an identifier for identifying the fixing component 111. For example, the fixing component 111 may be provided with a radio frequency identification (RFID) tag 114. The terminal may be provided with a reader / writer device for the RFID tag 114. The reader / writer device interacts with the RFID tag 114 in the fixing component 111, and can identify the RFID tag 114 in the fixing component 111 (to identify the first motion data detection device 11), and transmit data (such as a first set of motion parameters and a second set of motion parameters, or foot motion parameters and waist motion parameters, as described in the following embodiments).

[0087] In this embodiment, before exercising, the user can place the first motion data detection device 11 on the foot and the second motion data detection device 12 on the waist. The user can trigger the terminal to scan the devices on a device (such as a sports-related application). Accordingly, the terminal can identify the first motion data detection device 11 (detecting foot motion parameters) and the second motion data detection device 12 (detecting waist motion parameters) based on the RFID tags in the first and second motion data detection devices 11 and 12. The terminal can then display the identifiers of the scanned motion data detection devices on the interface, such as... Figure 3 As shown.

[0088] like Figure 3 As shown, the interface can display the devices scanned by the terminal (or the devices the user is using), namely the identifier (e.g., name) and setting location "foot" for the first motion data detection device 11, and the identifier (e.g., name) and setting location "waist" for the second motion data detection device 12. Additionally, the interface can provide prompts for the user to modify the motion data detection device used, such as "Click the device name above to confirm the device you are using." The user can click the "OK" control 31 on the interface to trigger the first motion data detection device 11 and the second motion data detection device 12 to start working. In one embodiment, the user clicking the "OK" control 31 on the interface can be understood as inputting a motion command to the terminal, instructing the user to start exercising.

[0089] It should be understood that when the user clicks the "OK" control 31, the first motion data detection device 11 and the second motion data detection device 12 start working. As an example, after the user clicks the "OK" control 31, other parameters can also be set to trigger the first motion data detection device 11 and the second motion data detection device 12 to start working.

[0090] It should be understood that, taking the first motion data detection device 11 as an example, in response to clicking the "OK" control 31, the terminal can send a wake-up command to the first motion data detection device 11, instructing the data acquisition component 112 in the first motion data detection device 11 to start acquiring six-axis data, and the processor 113 to start processing the six-axis data to obtain foot motion parameters. After obtaining the foot motion parameters, the processor 113 can send the foot motion parameters to the terminal. Similarly, taking the second motion data detection device 12 as an example, in response to clicking the "OK" control 31, the terminal can send a wake-up command to the second motion data detection device 12, instructing the data acquisition component in the second motion data detection device 12 to start acquiring six-axis data, and the processor in the second motion data detection device 12 to start processing the six-axis data to obtain waist motion parameters. After obtaining the waist motion parameters, the processor in the second motion data detection device 12 can send the waist motion parameters to the terminal.

[0091] Accordingly, the terminal can determine whether there is a risk of sports injury during the user's exercise based on foot and waist movement parameters, and promptly alert the user. It should be understood that the terminal can detect the risk of sports injury during the user's exercise in real time based on the foot movement parameters sent in real time by the first motion data detection device 11 and the waist movement parameters sent in real time by the second motion data detection device 12.

[0092] In one embodiment, the processor 113 may be disposed in the fixing component 111 or the data acquisition component 112. In this embodiment, the first motion data detection device 11 and the second motion data detection device 12 may be used interchangeably, such as the first motion data detection device 11 being disposed at the foot and the second motion data detection device 12 being disposed at the waist, or the first motion data detection device 11 being disposed at the waist and the second motion data detection device 12 being disposed at the foot.

[0093] In this embodiment, both the processors of the first motion data detection device 11 and the second motion data detection device 12 may be equipped with a first preset algorithm and a second preset algorithm. The first motion data detection device 11 and the second motion data detection device 12 can determine which preset algorithm to use to process the six-axis data based on settings installed on the user. For example, refer to... Figure 3 As shown, before exercising, the user can select the first motion data detection device 11 and the second motion data detection device 12 on the terminal (such as the interface of a sports-type application). For example, the user can set the device installed on the user's waist as the second motion data detection device 12 and the device installed on the user's feet as the first motion data detection device 11.

[0094] In this embodiment, after the terminal determines the device installed on the user's body part, it can instruct the corresponding device to activate the corresponding algorithm. For example, the terminal can send an algorithm activation command to the first motion data detection device 11 to instruct it to activate a first preset algorithm. Correspondingly, the terminal can send an algorithm activation command to the second motion data detection device 12 to instruct it to activate a second preset algorithm. Thus, during the user's movement, the first motion data detection device 11 can acquire foot movement parameters, and the second motion data detection device 12 can acquire waist movement parameters.

[0095] In one embodiment, Figure 1 The terminal shown may include, but is not limited to, mobile phones, wearable devices, virtual reality (VR) terminal devices, augmented reality (AR) terminal devices, etc. During exercise, users may or may not carry the terminal (e.g., placing the terminal beside them). The form of the terminal is not specifically limited in this embodiment. Taking running as an example, the terminal can be mounted on the arm or held in the hand.

[0096] The method for alerting to sports injuries provided in this application will be described below with reference to specific embodiments. These embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0097] Figure 4 This is a schematic flowchart of one embodiment of the sports injury alerting method provided in this application. (Refer to...) Figure 4 The sports injury alert method provided in this application embodiment may include:

[0098] S401, during the user's movement, the first motion data detection device collects the first six-axis data and processes the first six-axis data to obtain the first set of motion parameters.

[0099] In one embodiment, in response to a user's motion command (such as a start running command), the terminal can send a wake-up command to a first motion data detection device and a second motion data detection device. The wake-up command is used to wake up the first and second motion data detection devices so that they can begin collecting six-axis data. For example, the user's input of a start running command to the terminal may include, but is not limited to, commands such as: Figure 3 As shown, clicking the "OK" control 31 on the interface or saying the command "Start running" are examples of how this application embodiment does not limit the way the user inputs the command to start running on the terminal.

[0100] During user movement, the first motion data detection device can collect first six-axis data. In one embodiment, because the first six-axis data is data collected by the sensor in the first motion data detection device, the first six-axis data can be referred to as data collected by the first sensor in the first motion data detection device (e.g., first sensor data). The first sensor can be referred to as a first inertial sensor.

[0101] After acquiring the first six-axis data, the first motion data detection device can preprocess the first six-axis data. For example, the first motion data detection device can perform a 50Hz low-pass filter on the first six-axis data to remove interference data in the first six-axis data, thereby obtaining filtered first six-axis data.

[0102] The first motion data detection device can process the filtered first six-axis data to obtain a first set of motion parameters. In one embodiment, taking the first motion data detection device installed on the user's foot as an example, the first motion data detection device can perform gait segmentation during the user's running process based on the first six-axis data. Specifically, the first motion data detection device can determine the user's heel strike time, forefoot strike time, heel lift-off time, and forefoot lift-off time based on the first six-axis data. The gait segmentation point refers to the time point corresponding to heel strike, forefoot strike, heel lift-off, and forefoot lift-off within one step.

[0103] The first motion data detection device can use the processed and filtered first six-axis data and gait segmentation points as parameters, and employ a coordinate system detection algorithm to obtain the components of gravity and forward direction in the inertial sensor. Further, the first motion data detection device can use the components of gravity and forward direction in the inertial sensor as parameters, and employ an initial quaternion algorithm to obtain an initial quaternion (the first initial quaternion). Further still, the first motion data detection device can use the processed and filtered first six-axis data and the initial quaternion as parameters, and employ an inertial navigation algorithm to extract the first kinematic features. These first kinematic features include, but are not limited to: stride length, stride frequency, stride speed, ground contact time, airtime, swing angle, eversion angle, landing pattern, and ground contact-to-air ratio. The first motion data detection device can use stride length, stride speed, ground contact time, and the user's body mass index (BMI) to extract the first dynamic features using a linear regression algorithm. These first dynamic features include, but are not limited to: peak ground contact and impact force.

[0104] In one embodiment, the set of coordinate system detection algorithm, initialization quaternion algorithm, inertial navigation algorithm, and linear regression algorithm is referred to as the first preset algorithm. In one embodiment, the first set of motion parameters (foot motion parameters) may include a first kinematic feature and a first dynamic feature.

[0105] S402, the first motion data detection device sends the first set of motion parameters to the terminal.

[0106] After acquiring the first set of motion parameters, the first motion data detection device can send the first set of motion parameters to the terminal.

[0107] S403, the second motion data detection device collects the second six-axis data and processes the second six-axis data to obtain the second set of motion parameters.

[0108] During the user's movement, the second motion data detection device can collect second six-axis data. In one embodiment, because the second six-axis data is data collected by the sensors in the second motion data detection device, the second six-axis data can be referred to as data collected by the second sensors in the second motion data detection device (e.g., second sensor data).

[0109] After the second motion data detection device collects the second six-axis data, it can preprocess the second six-axis data, referring to the preprocessing process of the first six-axis data.

[0110] The second motion data detection device can process the filtered second six-axis data to obtain a second set of motion parameters. In one embodiment, taking the second motion data detection device as an example, which is positioned at the user's waist, the second motion data detection device can obtain the component of gravity in the inertial sensor based on the three-axis acceleration data in the second six-axis data. Further, the second motion data detection device can use the component of gravity in the inertial sensor as a parameter and employ an initial quaternion algorithm to obtain an initial quaternion (the second initial quaternion). Further still, the second motion data detection device can use the processed second six-axis data and the initial quaternion as parameters to calculate the vertical acceleration, and use the vertical acceleration as a parameter for gait segmentation to obtain the user's ground contact time and zero-velocity point. The zero-velocity point can be understood as the moment when the user's velocity is 0 during movement, such as the highest point in the air when the user jumps.

[0111] The time from when the user's heel touches the ground to the next heel touches the ground is defined as one step, and the ratio of the time taken for two adjacent steps is the ground contact balance. The second motion data detection device uses vertical acceleration and the zero velocity point as parameters, employing an inertial navigation algorithm to obtain the vertical amplitude of the waist.

[0112] In one embodiment, the set of initialization quaternion algorithms and inertial navigation algorithms is referred to as the second preset algorithm. In one embodiment, the second set of motion parameters (waist motion parameters) may include waist vertical amplitude and ground contact balance.

[0113] S404, the second motion data detection device sends the second set of motion parameters to the terminal.

[0114] After acquiring the second set of motion parameters, the second motion data detection device can send the second set of motion parameters to the terminal.

[0115] In one embodiment, there is no restriction on the order of "S401-S402" and "S403-S404", and they can be executed simultaneously.

[0116] S405, the terminal determines whether there is a risk of sports injury based on the first set of motion parameters and the second set of motion parameters. If yes, proceed to S406; otherwise, continue to proceed to S405 based on the new first set of motion parameters from the first motion data detection device and the new second set of motion parameters from the second motion data detection device (not shown in the figure).

[0117] In one embodiment, after the terminal identifies the first motion data detection device and the first motion data detection device, deletable parameters can be displayed on the interface so that the user can delete parameters they are not interested in. This process can be as follows: Figure 5 As shown in a and b in the figure. (Refer to...) Figure 5In the b part, the interface may include the names of foot movement parameters and waist movement parameters, as well as a delete control 51. Users can operate the delete control to delete parameters they are not interested in. In this embodiment, after deleting parameters they are not interested in, the user can trigger the terminal to send a wake-up command to the first motion data detection device and the first motion data detection device. In one embodiment, in Figure 5 The interface shown in b can display all parameters. Users can select the motion parameters they are interested in so that the first motion data detection device and the first motion data detection device can calculate the motion parameters they are interested in.

[0118] Accordingly, the terminal can send a deletion instruction to the first motion data detection device and the second motion data detection device based on the user's deletion operation, so that the first motion data detection device and the second motion data detection device will not calculate the parameters deleted by the user when calculating and acquiring motion parameters.

[0119] In one embodiment, after receiving the first set of motion parameters and the second set of motion parameters, the terminal can also combine the first set of motion parameters and the second set of motion parameters (or some parameters in the first set of motion parameters and some parameters in the second set of motion parameters) to obtain a third set of motion parameters. For example, the terminal can use the ratio of the waist vertical amplitude to the stride as the vertical stride ratio (included in the third set of motion parameters) to detect whether there is a risk of sports injury.

[0120] In one embodiment, the terminal can determine whether there is a risk of sports injury in the following manner:

[0121] The terminal stores a first threshold value for each parameter in a first set of motion parameters, a second threshold value for each parameter in a second set of motion parameters, and a third threshold value for each parameter in a third set of motion parameters. In this embodiment, taking the first set of motion parameters as an example, the terminal can compare each parameter in the first set of motion parameters from the first motion data detection device with its corresponding first threshold value. If the parameter values ​​of all parameters exceed their corresponding first threshold values, the terminal can determine that there is a risk of sports injury. The same logic applies to the second set of motion parameters. In one embodiment, if the parameter values ​​of no parameters exceed their corresponding first threshold values, the terminal can determine that there is no risk of sports injury. The terminal can then continue to determine whether there is a risk of sports injury based on the motion parameters from the first motion data detection device and the first set of motion data detection device.

[0122] For example, regarding touchdown balance, the second threshold corresponding to touchdown balance is 50%. If the touchdown balance in the second set of motion parameters is 58%, the terminal can determine that there is a risk of sports injury. Similarly, regarding impact force, the first threshold corresponding to impact force is 2 BW. If the impact force in the first set of motion parameters is 3.5 BW, the terminal can determine that there is a risk of sports injury.

[0123] In one embodiment, the terminal can determine whether there is a risk of sports injury in the following manner:

[0124] The terminal is pre-set with a first injury risk model, which is used to determine whether there is a risk of sports injury based on a first set of motion parameters and a second set of motion parameters. The training process of the first injury risk model can be referred to... Figure 8 The relevant description is as follows. Specifically, the terminal can input a first set of motion parameters, a second set of motion parameters (and a third set of motion parameters, if any), into a first injury risk model to obtain the output of the first injury risk model. This output indicates whether there is a risk of motion injury or not, and if so, outputs the parameters and their values ​​indicating the presence of a risk of motion injury. It should be understood that the following embodiments use the first and second motion parameters as examples for illustration.

[0125] In one embodiment, the terminal can display a motion parameter interface in real time during user exercise. (See reference...) Figure 6 In the exercise parameter interface, the real-time changing values ​​of various parameters and the distance the user has run are displayed. Users can click on the area containing any parameter (such as stride length) to trigger the terminal to display the real-time change curve of that parameter (e.g., stride length). In one embodiment, clicking on the area containing any parameter triggers the terminal to display the parameter value in the area displaying "distance run," allowing users to intuitively see the changes in the parameters they are interested in. Figure 6 As shown in b in the diagram. It should be understood that... Figure 6 Actual parameter values ​​are not shown.

[0126] S406, The terminal outputs a prompt message to alert the user of the risk of sports injury.

[0127] The prompt message is used to alert users to the risk of sports injury. In one embodiment, the prompt message may further include parameters that enable the risk of sports injury, parameter values, and the type of injury (such as muscle injury, knee injury, etc.), so that users can intuitively see which parameter of their exercise is not in compliance. In one embodiment, to prompt users to adopt the correct running posture in time when there is a risk of sports injury, the prompt message also includes: exercise suggestions. The exercise suggestions may include suggestions on running posture. In one embodiment, this prompt message may be referred to as the first prompt message.

[0128] Exceeding the corresponding threshold for any parameter can lead to sports injuries for the user. In one embodiment, the terminal can pre-store exercise suggestions corresponding to parameters that enable the risk of sports injuries. Therefore, the terminal can add such exercise suggestions to the prompt message based on the parameters that enable the risk of sports injuries and the corresponding exercise suggestions. For example, if the ground balance exceeds the corresponding second threshold, the corresponding exercise suggestion is "Please adjust your running pace".

[0129] In one embodiment, the terminal may display a prompt message on its interface, such as: "Ground contact balance 58%. Your ground contact is very unbalanced, with a high risk of muscle injury (injury type). Please pay attention to your running pace (exercise advice)." Figure 6 As shown in c in the figure. In one embodiment, when the terminal displays the prompt information on the interface, it may be accompanied by vibration or sound to prompt the user to view it. In one embodiment, the terminal may also output the prompt information using voice prompts or other methods.

[0130] In one embodiment, after a user finishes running, the terminal can summarize the run and provide feedback. For example, such as... Figure 6 As shown in d, the terminal can output information such as "running summary and suggestions" so that users can learn from their experience and avoid sports injuries in their next run.

[0131] In one embodiment, steps S401-S406 can be simplified as follows: Figure 7 As shown.

[0132] In this embodiment, during user exercise, motion parameters collected and processed by sensors (motion data detection devices) installed on different parts of the user's body can be used to determine whether there is a risk of sports injury. If a risk of sports injury is detected, a warning message is output so that the user can adjust their posture in time to avoid injury. Furthermore, the motion parameters collected and processed by the motion data detection device in this embodiment are obtained from multiple dimensions, making it suitable for scenarios involving professional athletes to prevent sports injuries.

[0133] The following describes the first injury risk model and its training process:

[0134] The first damage risk model can be a training device, such as a server or computer, trained based on training data and pre-installed on a terminal. The training device can input training data into an initial network model for training to obtain the first damage risk model. In one embodiment, the initial network model can be, but is not limited to, convolutional neural networks (CNN), recurrent neural networks (RNN), long short-term memory networks (LSTM), and GoogLeNet, etc.

[0135] The following description uses GoogLeNet as an example of an initial network model. In one embodiment, GoogLeNet consists of one input layer, two convolutional layers, five pooling layers, nine inception layers, two auxiliary classifiers, one fully connected layer, and one output layer. All convolutional layers are activated using the rectified linear unit (ReLU) function, the pooling layers use average pooling or max pooling, and the output layer is calculated using the softmax function. During network training, the learning rate is 0.0003, and the batch size can be 16. It should be understood that the structure of GoogLeNet, as well as the learning rate and batch size, are illustrative examples, and this embodiment does not limit the scope of the application.

[0136] The training process of the first injury risk model is described below:

[0137] 1. Training Phase: During user exercise (e.g., running), parameters that pose a risk of injury to the user's body (e.g., foot movement parameters, waist movement parameters) are selected as positive samples, while parameters that do not pose a risk of injury to the user's body (e.g., foot movement parameters, waist movement parameters) are selected as negative samples. In this embodiment, the training device can use the positive and negative samples as training data and input them into GoogLeNet for training to obtain a first injury risk model. In one embodiment, the training data used to train the first injury risk model can be referred to as the first training data.

[0138] Reference Figure 8 The training process for the first injury risk model may include:

[0139] S801 divides the training data into N batches.

[0140] Training data includes parameters that pose a risk of injury to the user's body (such as foot movement parameters and waist movement parameters), and parameters that do not pose a risk of injury to the user's body (such as foot movement parameters and waist movement parameters). The training device can divide the training data into N batches to iteratively train GoogLeNet using these N batches of training data. For example, the training device can divide the training data into N batches, where N is an integer greater than 1, such as N=16.

[0141] S802, input the training data of the i-th batch into GoogLeNet to obtain the cross-entropy loss of the i-th batch.

[0142] For example, at the start of training, when i is 1, the training device inputs the first batch of training data into GoogLeNet. GoogLeNet can output the cross-entropy loss of the first batch of training data. It should be understood that the cross-entropy loss characterizes the similarity between the risk of harm to the user predicted by the parameters used by GoogLeNet and the actual risk of harm to the user based on those parameters. The smaller the cross-entropy loss, the higher the similarity, and the closer the risk of harm to the user predicted by the parameters used by GoogLeNet is to the actual risk (e.g., the parameters do indeed pose a risk of harm to the user).

[0143] The smaller the cross-entropy loss, the more accurate the representation of the weight values ​​in GoogLeNet. Here, i is an integer greater than or equal to 1 and less than or equal to N.

[0144] S803, update the weight values ​​of GoogLeNet based on the cross-entropy loss of the i-th batch.

[0145] For example, the training device can update the weights of GoogLeNet based on the cross-entropy loss of the first batch, such as updating the channel weights of convolutional layers and the weights of fully connected layers in GoogLeNet. That is, the training device can determine the error between the "similarity between the result of the parameter causing harm to the user and the actual result of the parameter causing harm to the user" and 100% based on the cross-entropy loss of the first batch, and then update the weights of GoogLeNet based on this error. For example, the training device can use gradient descent or stochastic gradient descent to update the weights of GoogLeNet; this embodiment of the application does not limit this.

[0146] S804, determine if i is less than N. If yes, increment i by 1 and execute S802. If no, execute S805.

[0147] The training device can determine whether i is less than N in order to determine whether the training data of N batches has been trained.

[0148] If i is less than N, the training device can increment i by 1 and continue executing S802. For example, when i is 1, the training device determines that i is less than N (16), and then the training device can input the training data of the second batch into the GoogLeNet to update the weight values, obtaining the cross-entropy loss of the second batch. Similarly, the training device can update the weight values ​​of GoogLeNet using gradient descent or stochastic gradient descent based on the cross-entropy loss of the second batch. This process is iterated until i equals N, at which point the training device inputs the training data of the Nth batch into GoogLeNet, and updates the weight values ​​of GoogLeNet based on the cross-entropy loss of the Nth batch. When i equals N, the training device can execute the following S805.

[0149] S805: Based on the target cross-entropy loss and the cross-entropy loss of the Nth batch, determine whether the training has converged. If the training has converged, proceed to S806; otherwise, return to S801.

[0150] Users can pre-set the target cross-entropy loss as the convergence criterion for training. When the training device obtains the cross-entropy loss of the Nth batch, it can determine whether the training has converged based on the cross-entropy loss of the Nth batch and the target cross-entropy loss.

[0151] If the cross-entropy loss of the Nth batch is less than or equal to the target cross-entropy loss, it indicates that the result of the risk of harm to the user based on the parameters predicted by GoogLeNet is closer to the actual risk of harm to the user, and the prediction accuracy is high. In this case, the training device can determine that the training has converged, i.e., training ends. If the cross-entropy loss of the Nth batch output by GoogLeNet is greater than the target cross-entropy loss, it is determined that the training has not converged. When the training has not converged, the training device returns to execution S801, that is, it continues to divide the training data into N batches and uses the N batches of training data to continue training GoogLeNet until the training converges.

[0152] S806, End.

[0153] If the training equipment determines that the training has converged, then the training will end, and the first damage risk model will be obtained.

[0154] 2. Testing Phase: Again, select parameters that pose a risk of injury to the user (e.g., foot movement parameters, waist movement parameters) and parameters that do not pose a risk of injury to the user (e.g., foot movement parameters, waist movement parameters). Parameters that pose a risk of injury to the user (e.g., foot movement parameters, waist movement parameters) can be used as positive samples, and parameters that do not pose a risk of injury to the user (e.g., foot movement parameters, waist movement parameters) can be used as negative samples. In this embodiment, the positive and negative samples from this batch can be used as test data and input into the first injury risk model to test the accuracy of the first injury risk model.

[0155] If, based on the test data, the parameters output by the first damage risk model correctly predict the risk of damage to the user, then the accuracy of the first damage risk model is considered high. If the accuracy rate of the parameters output by the first damage risk model in predicting the risk of damage to the user is less than the preset accuracy rate, then the amount of training data can be increased, and the above steps S801-S806 can be executed to train the model and obtain the first damage risk model.

[0156] During exercise, besides incorrect posture leading to injury, the environment (such as the surface material) also poses a risk of injury. For example, in running, the surface material significantly impacts knee load; a well-cushioned track reduces the risk of knee injury. Common track materials, ranked by cushioning ability, can be "treadmill = synthetic track > asphalt road > concrete road." Therefore, based on the above embodiments, this application can add "surface material" as a parameter to determine the risk of injury during exercise, thereby improving the accuracy of the assessment.

[0157] In one embodiment, to obtain the ground material, the terminal can prompt the user to take an image of the ground before the user moves, and then the terminal determines the ground material based on the image. For example, in... Figure 3 The interface shown can also include additional prompts (which can be called secondary prompts), such as "Please take a picture of the ground before you start running," to encourage the user to take a picture of the ground using their device. Figure 9 As shown. For example, or in response to the user's command to start running, before sending a wake-up command to the first and second motion data detection devices, a prompt box appears on the interface to display a message prompting the user to capture an image of the ground. For example, as... Figure 9 As shown, when a user clicks on the prompt box 91 containing the prompt information, the terminal can be triggered to open the camera and start taking pictures.

[0158] In this system, after acquiring an image of the ground, the terminal can identify the ground material to determine its composition. In one embodiment, the terminal can extract features from the ground in the image to identify the ground material based on these features. In another embodiment, the terminal can input the ground image into a pre-trained ground material recognition model to obtain the ground material output by the model. It should be understood that the ground material recognition model is obtained through deep learning. In one embodiment, the terminal can also store preset images of each ground material, and the terminal can determine the ground material based on the similarity between the captured image and the preset images of each material. For example, the terminal can use the ground material in the preset image with the highest similarity as the ground material when the user is moving.

[0159] In one embodiment, in order to obtain the ground material, the terminal can display a third prompt on the interface before the user moves, so that the user can select the ground material to move on from the ground materials provided by the terminal. The user can choose the ground material independently, so the terminal can also determine the ground material to move on based on the user's selection.

[0160] The surface material can change during exercise, such as when a user runs from a rubber track to a concrete surface. Therefore, the accuracy of determining the surface material using the above method is not high. Thus, in one embodiment, referring to... Figure 10 In the embodiments of this application, it is possible to use the above... Figure 1 In the scenario shown, an image acquisition device 14 is added. The image acquisition device 14 is used to acquire ground images during the user's movement. For example, the image acquisition device 14 can be smart glasses or a wearable device that can capture images of the ground.

[0161] In this embodiment, in response to the user's movement command, the terminal can send an image acquisition command to the image acquisition device 14, which instructs the image acquisition device 14 to acquire an image. After acquiring the image, the image acquisition device 14 can send it to the terminal so that the terminal can obtain the ground material based on the image from the image acquisition device 14, as detailed in the above description.

[0162] Based on the scenario where the terminal can obtain the ground material, the following describes the process by which the terminal combines the ground material to provide sports injury warnings, including parameters. Figure 11 The sports injury alert method provided in this application embodiment may include:

[0163] S1101, The terminal obtains the material of the ground where the user is moving.

[0164] In one embodiment, based on the scenario where the terminal can obtain the ground material as described above, the terminal can obtain the ground material before the user moves, or the terminal can obtain the ground material during the user's movement.

[0165] S1102, during the user's movement, the first motion data detection device collects the first six-axis data to process and obtain the first set of motion parameters.

[0166] S1103, the first motion data detection device sends the first set of motion parameters to the terminal.

[0167] S1104, the second motion data detection device collects the second six-axis data to process and obtain the second set of motion parameters.

[0168] S1105, the second motion data detection device sends the second set of motion parameters to the terminal.

[0169] S1102-S1105 can be referred to the relevant descriptions in S401-S404 above.

[0170] S1106, the terminal determines whether there is a risk of sports injury based on the ground material, the first set of motion parameters, and the second set of motion parameters. If yes, proceed to S1107; otherwise, continue to proceed to S1106 based on the new first set of motion parameters from the first motion data detection device and the new second set of motion parameters from the second motion data detection device (not shown in the figure).

[0171] In one embodiment, the terminal can determine whether there is a risk of sports injury in the following manner:

[0172] The terminal stores first threshold values ​​for each parameter in the first set of motion parameters under different ground materials, and second threshold values ​​for each parameter in the second set of motion parameters under different ground materials. In this embodiment, after acquiring the ground material, the terminal can compare each parameter in the first set of motion parameters from the first motion data detection device with the corresponding first threshold value for that ground material. If the parameter values ​​all exceed the corresponding first threshold value, the terminal can determine that there is a risk of sports injury, as described in S405. The determination of the first set of motion parameters is similar.

[0173] For example, if the surface the user is exercising on is concrete, and the impact force of 3.5 BW exceeds the impact force threshold for concrete, the terminal can determine that there is a risk of sports injury. Similarly, if the surface the user is exercising on is a synthetic running track, and the impact force of 3.0 BW exceeds the impact force threshold for synthetic running tracks, the terminal can determine that there is a risk of sports injury.

[0174] In one embodiment, the terminal can determine whether there is a risk of sports injury in the following manner:

[0175] The terminal is pre-set with a second injury risk model, which is used to determine whether there is a risk of sports injury based on the ground material, the first set of motion parameters, and the second set of motion parameters. The training process for the second injury risk model can be referred to... Figure 8 The training process of the first injury risk model is described below. The training data for the second injury risk model (i.e., the second training data) may include: parameters that pose a risk of injury to the user's body (such as foot movement parameters and waist movement parameters) as positive samples under different ground materials, and parameters that do not pose a risk of injury to the user's body (such as foot movement parameters and waist movement parameters) as negative samples. The terminal can input the ground material (such as an image or sign), the first set of movement parameters, and the second set of movement parameters into the second injury risk model to obtain the output result of the second injury risk model, which indicates whether there is a risk of sports injury or not.

[0176] S1107, The terminal outputs a prompt message to alert the user of the risk of sports injury.

[0177] The notification message is used to alert users to the risk of sports injury. In one embodiment, the notification message includes parameters that enable the risk of sports injury, parameter values, and the type of injury (such as muscle injury, knee injury, etc.), as well as the material of the running surface. In another embodiment, to prompt users to adopt the correct running posture when there is a risk of sports injury, the notification message also includes exercise suggestions. These suggestions may include recommendations on running posture, running surface material, etc.

[0178] In one embodiment, the terminal can pre-store exercise suggestions corresponding to parameters that enable the risk of sports injuries under different ground materials. Therefore, the terminal can add exercise suggestions to the prompt information based on the parameters that enable the risk of sports injuries and the corresponding exercise suggestions. For example, as shown... Figure 12As shown, if the ground material where the user is exercising is concrete, and the impact force of 3.5 BW exceeds the impact force threshold for concrete, the terminal can output a prompt message, such as "Concrete has poor cushioning, the current knee load is high, consider changing the running track to reduce the risk of knee injury." For example, if the ground material where the user is exercising is synthetic running track, and the impact force of 3.0 BW exceeds the impact force threshold for synthetic running track, the terminal can output a prompt message, such as "The current knee load is high, consider changing to running shoes with better cushioning." The method by which the terminal outputs the prompt message can be referred to the relevant description in S406.

[0179] In one embodiment, steps S1101-S1107 can be simplified to: Figure 13 As shown.

[0180] In this embodiment, the material of the ground on which the user is moving, as well as the motion parameters collected and processed by sensors on different parts of the body, can be combined to determine whether there is a risk of sports injury during the user's movement. Because various parameters that can cause the risk of sports injury can be combined, the accuracy of determining whether there is a risk of sports injury can be improved.

[0181] In one embodiment, as in the above embodiments, the risk of sports injury is assessed by combining the user's current exercise parameters and the material of the ground. If a user runs on the same ground material for a long time, it means that the user is constantly using the same muscles, which will increase muscle fatigue and cause sports injury. Therefore, in order to improve the accuracy of the assessment, this embodiment of the application can combine the user's historical exercise data to assess the risk of sports injury. (See also...) Figure 14 The sports injury alert method provided in this application embodiment may include:

[0182] S1401, The terminal obtains the material of the ground where the user is moving.

[0183] S1402, During the user's movement, the first motion data detection device collects the first six-axis data to process and obtain the first set of motion parameters.

[0184] S1403, the first motion data detection device sends the first set of motion parameters to the terminal.

[0185] S1404, the second motion data detection device collects the second six-axis data to process and obtain the second set of motion parameters.

[0186] S1405, the second motion data detection device sends the second set of motion parameters to the terminal.

[0187] S1402-S1405 can be referred to the relevant descriptions in S401-S404 above.

[0188] S1406, the terminal determines whether there is a risk of sports injury based on the ground material, the user's historical motion data, the first set of motion parameters, and the second set of motion parameters. If yes, proceed to S1407; otherwise, continue to proceed to S1406 based on the new first set of motion parameters from the first motion data detection device and the new second set of motion parameters from the second motion data detection device (not shown in the figure).

[0189] The user's historical motion data may include: the ground material during each historical movement (or each movement within a previous period), the first set of motion parameters collected by the first motion data detection device, and the second set of motion parameters collected by the second motion data detection device.

[0190] In one embodiment, the terminal may store conditions for determining the existence of sports injury risk. The terminal can determine the existence of sports injury risk based on these preset conditions, the ground material, the user's historical exercise data, a first set of exercise parameters, and a second set of exercises. For example, if a user has accumulated more than 30 kilometers of running on asphalt roads in the past three months, resulting in a monotonous running environment and a risk of muscle fatigue injury, it is recommended to change running tracks. Similarly, if a user has frequently run uphill sections in the past three months, resulting in a monotonous running route and a risk of muscle fatigue, it is recommended to change running routes.

[0191] In one embodiment, the terminal is pre-configured with a third injury risk model. This third injury risk model is used to determine whether there is a risk of sports injury based on the ground material, the user's historical motion data, a first set of motion parameters, and a second set of motion parameters. The training process of the third injury risk model can be referred to... Figure 8 A description of the training process of the first injury risk model.

[0192] The training data for the third injury risk model (i.e., the third training data) can include: parameters that pose a risk of injury to the user's body (such as foot movement parameters and waist movement parameters) as positive samples under different ground materials, and parameters that pose a risk of injury to the user's body from historical movement data; and parameters that do not pose a risk of injury to the user's body (such as foot movement parameters and waist movement parameters) as negative samples, and parameters that do not pose a risk of injury to the user's body from historical movement data. The terminal can input the ground material (such as an image or sign), the user's historical movement data, the first set of movement parameters, and the second set of movement parameters into the third injury risk model to obtain the output result of the third injury risk model, which indicates whether there is a risk of sports injury or not.

[0193] S1407, The terminal outputs a prompt message to alert the user of the risk of sports injury.

[0194] The prompt message is used to alert the user to the risk of sports injury, and the prompt message can be referred to as shown in S1107. In one embodiment, the way the terminal outputs the prompt message can be referred to the relevant description in S406.

[0195] In one embodiment, steps S1401-S1407 can be simplified to: Figure 15 As shown.

[0196] In this embodiment, the material of the ground on which the user is moving, the user's historical movement parameters, and the movement parameters collected and processed by sensors on different parts of the body can be combined to determine whether there is a risk of sports injury during the user's movement, which can further improve the accuracy of determining whether there is a risk of sports injury.

[0197] In one embodiment, during user movement, motion detection can be performed using one of the first motion data detection devices and the second motion data detection device described above. The detection device used by the user during movement can be referred to as a motion data detection device, and there can be one or more such devices. (Referring to...) Figure 16 For the terminal, the sports injury alert method provided in this application embodiment may include:

[0198] S1601, in response to the recognition of the motion data detection device, displays the identifier of the motion data detection device on the terminal interface. The motion data detection device is used to collect the user's motion parameters.

[0199] The method by which the terminal identifies the motion data detection device can be referred to the relevant description of the RFID tag in the above embodiments. The terminal can identify the motion data detection device based on the RFID tag. When the terminal identifies the motion data detection device, it can display the icon of the motion data detection device on the interface, such as... Figure 3 As shown in the image. The motion data detection device is used to collect the user's motion parameters.

[0200] In one embodiment, the motion data detection device includes: a first motion data detection device and a second motion data detection device. The first motion data detection device is disposed at the user's feet, and the second motion data detection device is disposed at the user's waist. The motion parameters include a first set of motion parameters and a second set of motion parameters. The first set of motion parameters consists of foot motion parameters during the user's exercise, and the second set of motion parameters consists of waist motion parameters during the user's exercise. Figure 3As shown, in response to the identification of the first motion data detection device and the second motion data detection device, the identifiers of the first motion data detection device and the second motion data detection device are displayed on the terminal interface.

[0201] The process of the first motion data detection device acquiring the first set of motion parameters and the second motion data detection device acquiring the second set of motion parameters can be referred to the relevant description in the above embodiments, and will not be repeated here.

[0202] S1602, in response to the user's motion command, sends a wake-up command to the motion data detection device.

[0203] The exercise command is used to instruct the user to start exercising. The method by which the user inputs the exercise command into the terminal, as well as the wake-up command, can be referred to the relevant descriptions in the above embodiments.

[0204] S1603 receives motion parameters from the user of the motion data detection device.

[0205] In one implementation, the motion data detection device includes an inertial sensor for acquiring six-axis data. The motion data detection device can process the six-axis data to obtain the user's motion parameters.

[0206] In one embodiment, the motion data detection device includes a first motion data detection device and a second motion data detection device. The first motion data detection device includes a first inertial sensor, and the second motion data detection device includes a second inertial sensor. The first motion data detection device, in response to a wake-up command from a terminal, controls the first inertial sensor to collect first sensor data, and processes the first sensor data to obtain a first set of motion parameters (refer to the specific processing procedure in the above embodiment). Correspondingly, the second motion data detection device, in response to a wake-up command from the terminal, can control the second inertial sensor to collect second sensor data, and then processes the second sensor data to obtain a second set of motion parameters (refer to the specific processing procedure in the above embodiment).

[0207] After acquiring the first set of motion parameters, the first motion data detection device can send the first set of motion parameters to the terminal. Similarly, after acquiring the second set of motion parameters, the second motion data detection device can send the second set of motion parameters to the terminal. In this way, the terminal can receive the first set of motion parameters from the first motion data detection device and the second set of motion parameters from the second motion data detection device.

[0208] S1604, if the risk of sports injury is detected during the user's exercise based on the motion parameters, the first prompt information is output, which is used to prompt the user that there is a risk of sports injury.

[0209] The terminal can detect whether there is a risk of sports injury during the user's exercise based on the user's motion parameters. In this embodiment, if the terminal detects a risk of sports injury during the user's exercise based on the motion parameters, it outputs a first prompt message, which is used to alert the user of the risk of sports injury. The detection of whether there is a risk of sports injury during the user's exercise based on the motion parameters can be referred to the relevant description in the above embodiments.

[0210] In this embodiment, during a user's exercise, the system can determine whether there is a risk of sports injury based on the motion parameters collected and processed by the motion data detection device installed on the user's body, and output a prompt message when there is a risk of sports injury so that the user can adjust their exercise posture in time to avoid injury to the user's body, thus effectively preventing sports injuries.

[0211] Figure 17 This is a schematic diagram of the structure of a sports injury alerting device provided in an embodiment of this application. The sports injury alerting device involved in this embodiment can be the aforementioned terminal, or it can be a chip applied to a terminal. This sports injury alerting device can be used to perform the actions of the terminal in the above method embodiments. For example... Figure 17 As shown, the sports injury warning device 1700 may include: a display module 1701, a transceiver module 1702, an output module 1703, a processing module 1704, and a shooting module 1705.

[0212] Display module 1701 is used to display the identifier of the motion data detection device on the terminal interface in response to the detection of the motion data detection device. The motion data detection device is used to collect the user's motion parameters.

[0213] The transceiver module 1702 is used to respond to the user's motion commands by sending a wake-up command to the motion data detection device and receiving motion parameters from the user from the motion data detection device.

[0214] The output module 1703 is used to output a first prompt message if the user is detected to have a risk of sports injury during exercise based on the motion parameters. The first prompt message is used to prompt the user that there is a risk of sports injury.

[0215] In one possible implementation, the motion data detection device includes: a first motion data detection device and a second motion data detection device. The first motion data detection device is installed on the user's feet, and the second motion data detection device is installed on the user's waist. The motion parameters include a first set of motion parameters and a second set of motion parameters. The first set of motion parameters consists of foot motion parameters during the user's exercise, and the second set of motion parameters consists of waist motion parameters during the user's exercise.

[0216] In one possible implementation, the processing module 1704 is used to detect whether there is a risk of sports injury during the user's exercise based on the first set of motion parameters and the second set of motion parameters.

[0217] In one possible implementation, the processing module 1704 is specifically used to obtain a third set of motion parameters based on some parameters in the first set of motion parameters and some parameters in the second set of motion parameters; and to detect whether there is a risk of sports injury during the user's exercise based on the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters.

[0218] In one possible implementation, the processing module 1704 is specifically used to input the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters into the first injury risk model to obtain the result of whether there is a risk of motion injury during the user's movement, and the result is whether there is a risk of motion injury or no risk of motion injury.

[0219] In one possible implementation, the first set of motion parameters includes at least one of the following: stride length, stride frequency, stride speed, ground contact time, air time, swing angle, rollover angle, landing mode, ground contact-to-air ratio, peak ground contact, and ground impact force; the second set of motion parameters includes at least one of the following: waist vertical amplitude and ground contact balance.

[0220] In one possible implementation, the first set of motion parameters includes stride length, the second set of motion parameters includes waist vertical amplitude, and the third set of motion parameters includes vertical stride ratio; the processing module 1704 is specifically used to use the ratio of waist vertical amplitude to stride length as the vertical stride ratio.

[0221] In one possible implementation, when the result indicates a risk of sports injury, the first injury risk model is also used to output the target parameter that causes the risk of sports injury, the parameter value of the target parameter, and the type of sports injury caused by the target parameter. The first prompt information includes: the target parameter, the parameter value of the target parameter, and the type of sports injury.

[0222] In one possible implementation, the processing module 1704 is further configured to obtain the motion suggestion corresponding to the target parameter based on the target parameter and the correspondence between the parameter and the motion suggestion. The first prompt information also includes the motion suggestion corresponding to the target parameter.

[0223] In one possible implementation, the processing module 1704 is further configured to acquire the material of the ground on which the user is moving, and to detect whether there is a risk of sports injury during the user's movement based on the ground material, the first set of motion parameters, and the second set of motion parameters.

[0224] In one possible implementation, the transceiver module 1702 is further configured to, in response to a motion command, send an image acquisition command to the image acquisition device, the image acquisition command instructing the image acquisition device to acquire an image, and receive an image from the image acquisition device. The processing module 1704 is specifically configured to obtain the material of the ground based on the image.

[0225] In one possible implementation, the output module 1703 is further configured to output a second prompt message in response to a motion command, the second prompt message being used to instruct the user to take an image of the ground where the user is moving.

[0226] The shooting module 1705 is used to capture images in response to shooting commands.

[0227] Processing module 1704 is specifically used to obtain the material of the ground based on the image.

[0228] In one possible implementation, the output module 1703 is further configured to output a third prompt message in response to a motion command, the third prompt message being used to instruct the user to select the material of the ground to be moved from among the materials of the ground to be selected provided by the terminal.

[0229] The processing module 1704 is specifically used to determine the material of the ground based on the user's selected operation.

[0230] In one possible implementation, the processing module 1704 is specifically used to input the ground material, the first set of motion parameters, and the second set of motion parameters into the second injury risk model to obtain the result of whether there is a risk of sports injury during the user's movement, and the result is whether there is a risk of sports injury or no risk of sports injury.

[0231] In one possible implementation, when the result indicates a risk of sports injury, the second injury risk model is also used to output: the target parameter that causes the risk of sports injury due to movement on the ground material, the parameter value of the target parameter, and the type of sports injury caused by the target parameter. The first prompt information includes: the ground material, the target parameter, the parameter value of the target parameter, and the type of sports injury.

[0232] In one possible implementation, the processing module 1704 is specifically used to detect whether there is a risk of sports injury during the user's exercise based on the user's historical motion parameters, the ground material, the first set of motion parameters, and the second set of motion parameters.

[0233] In one possible implementation, the processing module 1704 is specifically used to input the user's historical motion parameters, the ground material, the first set of motion parameters, and the second set of motion parameters into the third injury risk model to obtain the result of whether there is a risk of motion injury during the user's motion, and the result is whether there is a risk of motion injury or no risk of motion injury.

[0234] The sports injury alert device provided in this application embodiment can perform the actions executed by the terminal in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0235] This application also provides an electronic device, which can be the terminal described in the above embodiments. (Refer to...) Figure 18 As shown, the electronic device may include a processor 1801 (e.g., CPU) and a memory 1802. The memory 1802 may include high-speed random-access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device. The memory 1802 may store various instructions for performing various processing functions and implementing the method steps of this application.

[0236] Optionally, the electronic device involved in this application may further include: a power supply 1803, a communication bus 1804, and a communication port 1805. The communication port 1805 is used to enable communication between the electronic device and other peripherals. In this embodiment, the memory 1802 is used to store computer-executable program code, which includes instructions. When the processor 1801 executes the instructions, the instructions cause the processor 1801 of the electronic device to perform the actions described in the above method embodiment. The implementation principle and technical effects are similar and will not be repeated here.

[0237] In one embodiment, the electronic device may further include a display screen 1806 and a camera 1807. The display screen 1806 is used to display a human-computer interaction interface and the prompt information in the above embodiments, and the camera 1807 is used to capture images of the ground. The camera 1807 is, for example, a camera.

[0238] It should be noted that the modules or components described in the above embodiments can be one or more integrated circuits configured to implement the above methods, such as one or more application-specific integrated circuits (ASICs), one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs), etc. Furthermore, when a module is implemented through processing element scheduler code, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processors capable of calling program code, such as a controller. Additionally, these modules can be integrated together to implement a system-on-a-chip (SOC).

[0239] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0240] The term "multiple" in this document refers to two or more. The term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Furthermore, the character " / " in this document generally indicates an "or" relationship between the preceding and following related objects; in formulas, " / " indicates a "division" relationship. Additionally, it should be understood that in the description of this application, words such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0241] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application.

[0242] It is understood that, in the embodiments of this application, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

Claims

1. A method for alerting sports injuries, characterized in that, include: In response to the detection of a motion data detection device, the device's identifier is displayed on the terminal's interface. The motion data detection device is used to collect the user's motion parameters. The motion parameters include a first set of motion parameters and a second set of motion parameters. The first set of motion parameters consists of the user's foot motion parameters during exercise, and the second set of motion parameters consists of the user's waist motion parameters during exercise. In response to the user's motion command, a wake-up command is sent to the motion data detection device; Receive motion parameters from the user from the motion data detection device; If, based on the motion parameters, a risk of sports injury is detected during the user's exercise, a first prompt message is output, which is used to alert the user of the risk of sports injury. Before outputting the first prompt message if a risk of sports injury is detected during the user's exercise based on the motion parameters, the method further includes: Based on some parameters from the first set of motion parameters and some parameters from the second set of motion parameters, a third set of motion parameters is obtained; Based on the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters, detect whether there is a risk of sports injury during the user's exercise; or, Obtain the material of the ground on which the user is moving; Based on the ground material, the first set of motion parameters, and the second set of motion parameters, the risk of sports injury during the user's exercise is detected.

2. The method according to claim 1, characterized in that, The motion data detection device includes a first motion data detection device and a second motion data detection device, wherein the first motion data detection device is disposed at the user's feet and the second motion data detection device is disposed at the user's waist.

3. The method according to claim 1, characterized in that, The step of detecting whether there is a risk of sports injury during the user's exercise based on the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters includes: The first set of motion parameters, the second set of motion parameters, and the third set of motion parameters are input into the first injury risk model to obtain the result of whether there is a risk of motion injury during the user's exercise. The result is either that there is a risk of motion injury or that there is no risk of motion injury.

4. The method according to claim 1 or 3, characterized in that, The first set of motion parameters includes at least one of the following: stride length, stride frequency, stride speed, ground contact time, air time, swing angle, rollover angle, landing mode, ground contact-to-air ratio, peak ground contact, and ground impact force. The second set of motion parameters includes at least one of the following: waist vertical amplitude and ground contact balance.

5. The method according to claim 4, characterized in that, The first set of motion parameters includes the stride length, the second set of motion parameters includes the vertical amplitude of the waist, and the third set of motion parameters includes the vertical stride ratio; The process of obtaining a third set of motion parameters based on a portion of the parameters in the first set of motion parameters and a portion of the parameters in the second set of motion parameters includes: The ratio of the vertical amplitude of the waist to the stride length is taken as the vertical stride ratio.

6. The method according to claim 3, characterized in that, When the result indicates a risk of sports injury, the first injury risk model is further used to output the target parameter that causes the risk of sports injury, the parameter value of the target parameter, and the type of sports injury caused by the target parameter. The first prompt information includes: the target parameter, the parameter value of the target parameter, and the type of sports injury.

7. The method according to claim 6, characterized in that, After obtaining the result indicating whether there is a risk of sports injury during the user's exercise, the method further includes: Based on the target parameters and the correspondence between the parameters and the exercise suggestions, the exercise suggestions corresponding to the target parameters are obtained. The first prompt information also includes the exercise suggestions corresponding to the target parameters.

8. The method according to claim 1, characterized in that, The step of obtaining the material of the ground on which the user is moving includes: In response to the motion command, an image acquisition command is sent to the image acquisition device, the image acquisition command instructing the image acquisition device to acquire an image; Receive images from the image acquisition device; Based on the image, obtain the material of the ground.

9. The method according to claim 1, characterized in that, The step of obtaining the material of the ground on which the user is moving includes: In response to the motion command, a second prompt message is output, which instructs the user to use the terminal to capture an image of the ground where the user is moving; In response to the shooting command, an image is captured; Based on the image, obtain the material of the ground.

10. The method according to claim 1, characterized in that, The step of obtaining the material of the ground on which the user is moving includes: In response to the motion command, a third prompt message is output, which is used to instruct the user to select the material of the ground to be moved on from the materials of the ground to be selected provided by the terminal; The material of the ground is determined based on the user's selected operation.

11. The method according to any one of claims 1, 8-10, characterized in that, The step of detecting whether there is a risk of sports injury during the user's exercise based on the ground material, the first set of motion parameters, and the second set of motion parameters includes: The ground material, the first set of motion parameters, and the second set of motion parameters are input into the second injury risk model to obtain the result of whether there is a risk of sports injury during the user's exercise. The result is either that there is a risk of sports injury or that there is no risk of sports injury.

12. The method according to claim 11, characterized in that, When the result indicates a risk of sports injury, the second injury risk model is further used to output: the target parameter that causes the risk of sports injury due to movement on the material of the ground, the parameter value of the target parameter, and the type of sports injury caused by the target parameter. The first prompt information includes: the material of the ground, the target parameter, the parameter value of the target parameter, and the type of sports injury.

13. The method according to any one of claims 1, 8-10, and 12, characterized in that, The step of detecting whether there is a risk of sports injury during the user's exercise based on the ground material, the first set of motion parameters, and the second set of motion parameters includes: Based on the user's historical movement parameters, the ground material, the first set of movement parameters, and the second set of movement parameters, the system detects whether there is a risk of sports injury during the user's movement.

14. The method according to claim 13, characterized in that, The step of detecting whether there is a risk of sports injury during the user's exercise based on the user's historical movement parameters, the ground material, the first set of movement parameters, and the second set of movement parameters includes: The historical motion parameters of the user's historical motion process, the material of the ground, the first set of motion parameters, and the second set of motion parameters are input into the third injury risk model to obtain the result of whether there is a risk of sports injury during the user's motion process. The result is either that there is a risk of sports injury or that there is no risk of sports injury.

15. A sports injury alert device, characterized in that, include: The display module is used to display the identifier of the motion data detection device on the terminal interface in response to the detection of the motion data detection device. The motion data detection device is used to collect the user's motion parameters. The motion parameters include a first set of motion parameters and a second set of motion parameters. The first set of motion parameters is the foot motion parameters during the user's exercise, and the second set of motion parameters is the waist motion parameters during the user's exercise. The transceiver module is used to respond to the user's motion command by sending a wake-up command to the motion data detection device and receiving the user's motion parameters from the motion data detection device. The output module is configured to output a first prompt message if, based on the motion parameters, a risk of sports injury is detected during the user's exercise, and the first prompt message is used to alert the user of the risk of sports injury. The processing module is used to obtain a third set of motion parameters based on some parameters in the first set of motion parameters and some parameters in the second set of motion parameters; Based on the first set of motion parameters, the second set of motion parameters, and the third set of motion parameters, detect whether there is a risk of sports injury during the user's exercise; or, Obtain the material of the ground on which the user is moving; Based on the ground material, the first set of motion parameters, and the second set of motion parameters, the risk of sports injury during the user's exercise is detected.

16. An electronic device, characterized in that, include: Processor and memory; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-14.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions that, when executed, implement the method as described in any one of claims 1-14.

18. A computer program product comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the method of any one of claims 1-14.

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