Racket intelligent detection and interaction method, intelligent racket and computer storage medium

Abstract

The invention provides an intelligent racket detection and interaction method, an intelligent racket and a computer storage medium. The racket intelligent detection and interaction method comprises the following steps: acquiring handle data and racket surface data when a current user uses a racket; acquiring first preset data from a first preset data set according to the handle data; whether the racket surface data are matched with the first preset data or not is judged, and if the racket surface data are not matched with the first preset data, first interaction information is sent out. The intelligent racket comprises a first sensor unit, a second sensor unit and a control unit. A computer program is stored in a computer storage medium, and the method is implemented when the computer program is executed by a processor.

Description

Technical Field

[0001] This application relates to the field of sports equipment, specifically to a method for intelligent detection and interaction of a racket, an intelligent racket, and a computer storage medium. Background Technology

[0002] Physical exercise is an essential way for Chinese people to improve their physical fitness. Utilizing electronic technology to enhance the scientific nature of sports training is one of the main directions of technological advancement in sports equipment. The intelligent upgrading and application of sports and fitness equipment continues to emerge, with intelligent detection and interactive systems being particularly important in fitness equipment.

[0003] Existing smart products include "swing speed sensing devices," which primarily measure swing speed but cannot test the force of the hit, resulting in insufficient data. Furthermore, users of smart rackets exhibit significant individual differences, and current technologies cannot differentiate between these differences, thus failing to provide personalized training recommendations. Summary of the Invention

[0004] To address the technical problems, this application aims to provide a racket intelligent detection and interaction method, an intelligent racket, and a computer storage medium. This method enriches user data, distinguishes between different user types, and provides richer and more personalized data for training to improve its scientific rigor. The specific solution adopted is as follows:

[0005] A racket intelligent detection and interaction method is provided for a racket. The racket intelligent detection and interaction method includes: acquiring handle data and racket face data when the user is currently using the racket; acquiring first preset data from a first preset dataset based on the handle data; determining whether the racket face data matches the first preset data, wherein if the racket face data does not match the first preset data, a first interaction message is sent.

[0006] Furthermore, in the aforementioned racket intelligent detection and interaction method, the handle data includes one or more of the following: grip pressure data, grip area data, grip duration data, pulse data, blood pressure data, and user input data.

[0007] Furthermore, in the aforementioned racket intelligent detection and interaction method, the racket face data includes one or more of the following: racket face pressure data generated by the ball, ball hitting frequency data, number of hits data, and racket face hitting point distribution data.

[0008] Furthermore, in the aforementioned racket intelligent detection and interaction method, the source of the preset dataset includes one or more of the following: historical usage data of the racket; third-party big data platforms; and user-preset data.

[0009] Furthermore, in the above-mentioned racket intelligent detection and interaction method, the first interactive information is one or more of the following: increasing or decreasing the swing force; increasing or decreasing the hitting force; increasing or decreasing the hitting frequency; increasing or decreasing the duration of the movement; increasing or decreasing the number of hits; and the distribution data of the hitting point on the racket face.

[0010] Furthermore, in the above-mentioned racket intelligent detection and interaction method, the first preset dataset is a user type set, and the first preset data is a user type.

[0011] Furthermore, in the above-mentioned racket intelligent detection and interaction method, the step of obtaining the handle data when the current user is using the racket includes: obtaining one or more of the following at predetermined time intervals within a first preset duration: grip pressure data, grip area data, grip duration data, pulse data, blood pressure data, and user input data; calculating the average value of each type of data; and using the calculated average value as the handle data.

[0012] Furthermore, the above-mentioned racket intelligent detection and interaction method further includes: acquiring inertial data when the user is using the racket; acquiring second preset data from the second preset dataset based on the first preset data; determining whether the inertial data matches the second preset data, wherein if the inertial data does not match the second preset data, a second interaction message is issued.

[0013] Furthermore, in the aforementioned racket intelligent detection and interaction method, the second preset dataset is a standard swing action set or a regular swing action set.

[0014] Furthermore, in the above-mentioned racket intelligent detection and interaction method, the inertial data includes one or more of the following: racket acceleration data; racket angular velocity data; racket azimuth data; and racket posture data.

[0015] Furthermore, in the above-mentioned intelligent racket detection and interaction method, the racket includes a string adjustment device, and the intelligent racket detection and interaction method further includes: automatically adjusting the string tension of the racket by the string adjustment device according to the handle data and the racket face data.

[0016] Meanwhile, this application also provides a smart racket, including: a first sensor unit for acquiring handle data; a second sensor unit for acquiring racket face data; and a control unit configured to: acquire first preset data from a first preset dataset based on the handle data; determine whether the racket face data matches the first preset data, wherein if the racket face data does not match the first preset data, a first interactive message is issued.

[0017] This application also provides a computer storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0018] Compared with the prior art, this application has the following advantages:

[0019] This application adds the acquisition of controller data and enables personalized user interaction based on controller data, thereby improving the scientific nature of training.

[0020] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application, it can be implemented according to the contents of the specification. In order to make the above and other objects, features and advantages of this application more obvious and understandable, specific embodiments of this application are given below. Attached Figure Description

[0021] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the various drawings denote the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings depict only some embodiments according to this application and should not be construed as limiting the scope of this application.

[0022] Figure 1 This is a flowchart of a racket intelligent detection and interaction method according to an embodiment of this application;

[0023] Figure 2 This is a flowchart illustrating the second interactive information emitted in a racket intelligent detection and interaction method according to another embodiment of this application; and

[0024] Figure 3 This is a structural block diagram of a smart racket according to an embodiment of this application. Detailed Implementation

[0025] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the concept or scope of this application. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0026] To facilitate understanding of the technical solutions of the embodiments of this application, the relevant technologies of the embodiments of this application are described below. The following relevant technologies are optional solutions and can be combined with the technical solutions of the embodiments of this application in any way, and all of them fall within the protection scope of the embodiments of this application.

[0027] The following detailed description, with reference to the accompanying drawings, describes the racket intelligent detection and interaction method, the intelligent racket, and the computer storage medium of this application.

[0028] This application provides a smart racket detection and interaction method, applicable to rackets. The racket can be, for example, a badminton racket, tennis racket, table tennis racket, squash racket, etc. Furthermore, the smart racket detection and interaction method of this application can also be applied to clubs such as golf clubs and hockey clubs. The racket includes a handle (i.e., the grip area) and a racket face (i.e., the hitting area). The handle is used for gripping and can be a straight handle, a crank handle, or other shapes. Other accessories (e.g., rubber sleeves, felt sleeves, bushings, etc.) can be provided on the handle to increase comfort and improve the user's grip experience. The racket face can be a mesh hitting surface of different sizes (e.g., the racket face of a tennis racket, the racket face of a badminton racket), a blade hitting surface (e.g., the racket face of a table tennis racket), or other hitting parts (e.g., a billiard cue, a golf club, etc.) depending on the hitting target. In the following description, unless otherwise specified, a badminton racket will be used as an example of the racket mentioned in the application.

[0029] The racket intelligent detection and interaction method includes: acquiring handle data and racket face data when the current user is using the racket; acquiring first preset data from a first preset dataset based on the handle data; determining whether the racket face data matches the first preset data, wherein if the racket face data does not match the first preset data, a first interaction message is sent.

[0030] The following reference Figure 1 The racket intelligent detection and interaction method 100 provided in this application is described in detail. Figure 1 A flowchart of a racket intelligent detection and interaction method 100 according to an embodiment of this application is shown. Figure 1 As shown, the racket intelligent detection and interaction method 100 includes steps 101, 102, 103, and 104. Steps 101 to 104 are described in detail below.

[0031] In step 101, the handle data and racket face data of the current user using the racket are obtained.

[0032] When using a racket for exercise, the handle is the part the user directly contacts. Data from or obtained through the handle (hereinafter referred to as "handle data") can most directly reflect the user's relevant information. The first function of handle data is data collection, which enriches data types by collecting various data. For example, different types of users can use the same racket, so information such as gender, age, blood pressure, and pulse can be collected through the handle. The second function of handle data is data processing and feedback. For example, handle data can be used to determine the current user's swing motion and habits, providing feedback to the user; furthermore, data such as grip strength, pulse, and blood pressure can be used to determine the user's gender, thus providing gender-specific training suggestions.

[0033] In one embodiment, the handle data can be acquired using sensors. For example, various sensors, such as inertial measurement units (IMUs), pressure sensors, and biosensors, can be integrated on the handle surface and / or inside the handle. These sensors can monitor the user's grip, swing speed, swing angle, and physiological parameters (such as pulse and blood pressure) in real time. Taking an inertial measurement unit as an example, it can measure changes in the racket's posture and acceleration during movement, thereby helping to obtain the user's swing speed, direction, and angle. It can also further help identify different swing actions (such as forehand, backhand, high clear, smash, etc.) so that subsequent data analysis can provide suggestions for improving the user's movements. It is understood that the types and applications of sensors described above are merely exemplary. Those skilled in the art can select the types and applications of sensors based on the technical principles of this application, as long as the technical principles of this application are implemented.

[0034] The handle data may include one or more of the following: grip pressure data, grip area data, grip duration data, pulse data, blood pressure data, and user input data.

[0035] Grip pressure data and grip area data can be used to determine the user type set to which the current user belongs; for example, low grip pressure data indicates that the current user lacks strength, and low grip area data indicates that the current user has a small palm area, thus determining that the current user belongs to the juvenile category.

[0036] The duration of grip can be used to determine the duration of a user's single continuous movement.

[0037] Pulse and blood pressure data can be used to determine a user's health status and user type (e.g., professional athlete, ordinary person).

[0038] The combination of grip duration data, pulse data, and blood pressure data can also reflect changes in bodily functions during exercise.

[0039] The controller data obtained by the aforementioned sensors can also be transmitted to a companion mobile application or cloud server via Bluetooth or Wi-Fi. This method not only enables real-time data feedback but also allows users to easily view and analyze their athletic performance. The controller data can also be stored in a storage unit designed into the controller itself.

[0040] The racket face, as the striking part, provides data that directly reflects the position, force, angle, and speed of the strike.

[0041] Various types of sensors can be installed on and / or inside the racket face to acquire racket face data.

[0042] For example, one or more pressure sensors can be installed on the racket face to monitor the pressure applied when the racket contacts the ball in real time. By analyzing the pressure distribution at different locations, the location, force, and changes of the hit can be determined. This data can be used to identify the user's hitting habits and the ball's flight trajectory.

[0043] For example, inertial measurement units (such as accelerometers and gyroscopes) can be set up to capture the dynamic changes of the racket face during impact, thereby measuring the acceleration, racket face angle, and rotation information of the racket face at the moment of impact. This data can help analyze the swing speed and angle during the hit and their impact on the ball.

[0044] For example, optical sensors (such as infrared or laser sensors) can be set up to track the moment the racket hits the ball. By analyzing the optical data at the moment of impact, the hitting position and the initial velocity of the ball can be obtained.

[0045] For example, acoustic sensors can be used to capture the sound waves generated when the ball is hit. Different hitting methods and forces produce different sound wave characteristics. By analyzing the sound wave signals, the force and angle of the hit can be determined.

[0046] It is understood that the types and applications of sensors described above for obtaining shooting face data are merely exemplary. Those skilled in the art can select the types and applications of sensors based on the technical principles of this application, as long as the technical principles of this application can be implemented.

[0047] The racket face data may include one or more of the following: racket face pressure data generated by the ball, ball hitting frequency data, number of hits data, and racket face hitting point distribution data.

[0048] The racket face pressure data generated by hitting the ball can be obtained by the pressure change on the racket face sensor at the moment of impact, or by the tension change of the net strings at the moment of impact.

[0049] Hitting frequency data and hit count data can be obtained through sensors and counters.

[0050] The data on the distribution of the hitting point on the racket face can be obtained through the sensors mentioned above, which can reflect the user's hitting accuracy and hitting stability during movement.

[0051] For example, data on racket face pressure and hitting frequency can determine the user's hitting power and frequency, and further, their playing style. High racket face pressure and a high hitting frequency indicate a smash style. Conversely, a high number of swings but low number of hits suggests a low hit rate. Furthermore, a loose distribution of racket face contact points during training indicates insufficient swing stability.

[0052] Next, proceed to step 102, where the first preset data is obtained from the first preset dataset based on the handle data.

[0053] In one embodiment, the source of the first preset dataset includes one or more of the following: historical usage data of the racket; a third-party big data platform; and data preset by the user.

[0054] In one embodiment, the first preset dataset may include historical data. For example, the first preset dataset may be the result of summarizing and classifying data from various users that have been gradually accumulated and recorded over a period of time (e.g., a week, a month, a year, etc.) during the racket's use. For instance, if 10-20 different users use the racket each day, and each time the racket is used, the racket records each user's pulse, blood pressure, grip pressure, etc., through sensors, after accumulating a preset amount of data, these users can be classified to form a user type dataset. The handle data and racket data corresponding to each data point can be used as handle matching data and racket matching data, respectively.

[0055] In another embodiment, the first preset dataset may include third-party data. For example, the first preset dataset may be a user type dataset obtained from a third-party big data platform. Data obtained from a third-party big data platform is more universally applicable.

[0056] In another embodiment, the first preset dataset may include pre-set data. For example, the first preset dataset may be a collection of various users who may use the racket, pre-set by the racket owner. User-preset data is more conducive to targeted training by users.

[0057] In another embodiment, the first preset dataset may include the aforementioned historical data, third-party data, and pre-set data. In other words, the first preset dataset may be a collection of the aforementioned historical data, third-party data, and pre-set data.

[0058] The first preset dataset includes various preset data. These preset data include controller matching data corresponding to the various controller data types described above. If controller data matches a particular controller matching data set, then the preset data corresponding to that controller matching data is used as the first preset data.

[0059] For example, the first preset dataset is a set of user types. In a certain exercise, if the pressure data in the handle data matches a specific handle matching data set, then the user type corresponding to that handle matching data is taken as the first preset data. See Table 1 below for a specific example. Assume the first preset dataset includes a set of user types, distinguishing between children, adults, and adult athletes. The corresponding grip pressure ranges for these three user types are 5-20 lbs, 20-40 lbs, and 30-50 lbs, respectively. Assume the current user is using a badminton racket and the measured grip pressure data is 8 lbs. This grip pressure data matches "5-20 lbs" (i.e., handle matching data), and the preset data corresponding to this handle matching data is "children." Therefore, "children" is taken as the first preset data.

[0060]

[0061] Table 1

[0062] For example, grip area data can be used as part of the handle data. Assume the first preset dataset includes a set of user types, distinguishing between child users and adult users, with grip area ranges of 10-20cm for each type. 2 20-30cm 2 Assuming the user is currently using a badminton racket to hit the shuttlecock, the measured grip area is 25cm. 2 This grip area data is consistent with "20-30cm". 2 The controller matching data matches the controller matching data. The preset data corresponding to this controller matching data is "adult user". Therefore, "adult user" is used as the first preset data. In this example, the relationship between controller data, first preset dataset, first preset data, and controller matching data is shown in Table 2.

[0063]

[0064] Table 2

[0065] It is understood that the above exemplary description of the controller data, the first preset dataset, the first preset data, and the controller matching data is not an exhaustive list of the above types of data. Those skilled in the art can selectively set the controller data, the first preset dataset, the first preset data, and the controller matching data based on their understanding of the technical principles of this application, as long as the technical principles of this application can be achieved.

[0066] Next, proceed to step 103 to determine whether the shot face data matches the first preset data.

[0067] It is understood that the first preset data includes not only the corresponding handle matching data but also the corresponding racket face matching data, and the types of racket face matching data corresponding to the first preset data include all data types corresponding to the racket face data. For example, if the racket face data includes two types of data: racket face pressure data generated by hitting the ball and hitting frequency, then the first preset data includes at least two types of data: racket face pressure (or pressure range) generated by hitting the ball and hitting frequency (or hitting frequency range). The essence of "determining whether the racket face data matches the first preset data" is the comparison between the racket face data and the racket face matching data corresponding to the first preset data.

[0068] For example, suppose an 8-year-old user is using a badminton racket employing the racket intelligent detection and interaction method described in this application for badminton training. Actual measurements show a grip pressure of 8 pounds, a racket face pressure of 8 Newtons, and a hitting frequency of 2 hits per minute. This measured grip pressure data matches "5-20 pounds" (i.e., handle matching data), and the preset data corresponding to this handle matching data is "child user." Therefore, "child user" is used as the first preset data. Next, it will be determined whether the "racket face pressure data" and "hitting frequency data" match the "racket face pressure data" and "hitting frequency" corresponding to the child user. See Table 3 below for details of the above example.

[0069]

[0070] Table 3

[0071] Taking Table 3 above as an example, the actual measurement showed that the racket face pressure generated by hitting the ball was 8 Newtons; the hitting frequency was 2 times / minute. However, the racket face pressure range corresponding to the first preset data for "children's users" is 10-30 Newtons, and the corresponding hitting frequency range is 3-6 times / minute. Therefore, it can be determined that the racket face data does not match the first preset data.

[0072] Next, proceed to step 104. If the shot face data does not match the first preset data, then issue the first interactive information.

[0073] In one embodiment, the handle data (i.e., handle matching data) and / or racket face data (i.e. racket face matching data) in the first preset data can be a numerical range, such as "5-20 lbs" or "10-30 Nm" as recorded in Tables 1, 2 and 3 above. If the racket face data is not within the corresponding numerical range, it can be determined that the racket face data does not match the first preset data.

[0074] The first interactive information can be a reminder or a suggestion. For example, if the racket face data includes a racket face pressure of 15 pounds generated by hitting the ball, while the racket face matching data corresponding to the first preset data has a racket face pressure range of 20-25 pounds, then it can be determined that the racket face data does not match the first preset data.

[0075] In another embodiment, the handle data and / or racket face data in the first preset data can be a threshold. If the racket face data is less than the threshold, it can be determined that the racket face data does not match the first preset data.

[0076] Taking Table 3 above as an example, after determining that the racket face data does not match the first preset data, the racket can issue a first interactive message. For example, it could be a voice prompt to increase the hitting power or a voice prompt to increase the hitting frequency. The first interactive message can also be vibration information, image display information, etc. The above description of the first interactive message is merely exemplary and is not intended to limit the connotation of the first interactive message. Those skilled in the art can select the first interactive message according to the technical principles of this application, as long as the technical principles of this application can be implemented.

[0077] In one embodiment, the first interactive information is one or more of the following: increasing or decreasing swing force; increasing or decreasing hitting force; increasing or decreasing hitting frequency; increasing or decreasing motion duration; increasing or decreasing the number of hits; and racket face hitting point distribution data.

[0078] Continuing with the example in Table 3 above, after determining that the racket face data does not match the first preset data, the racket can issue one or more of the following voice messages as the first interactive information: "Please increase the hitting power", "Please increase the hitting frequency", "Please hit faster", "Please hit harder", "The racket face pressure you are currently generating is 8 Newtons, please increase the hitting power to reach at least 10 Newtons", "The current hitting frequency is 2 times / minute, please increase the hitting frequency to at least 3 times / minute".

[0079] It should be understood that the above description of voice information is merely an example to illustrate the first interactive information and is not intended to limit the connotation of voice information or the first interactive information.

[0080] In this embodiment, the first preset dataset is a user type set, and the first preset data is a user type. For example, a user type can be a man, a woman, a child, an amateur athlete, a master athlete, a professional athlete, etc., and the user type set is a collection of data for the aforementioned user types.

[0081] The process of obtaining handle data when the user is using the racket includes: obtaining one or more of the following at predetermined time intervals within a first preset duration: grip pressure data, grip area data, grip duration data, pulse data, blood pressure data, and user input data; calculating the average value of each type of data; and using the calculated average value as the handle data.

[0082] Understandably, averaging the various data points within the controller's data over a period of time helps eliminate measurement errors within relatively short timeframes and more accurately reflects the user's actual physical condition. This averaging method can also be modified to use weighted measurements based on the time of data acquisition. For example, during the warm-up phase at the start of exercise, the accuracy of controller data is easily affected by other factors and can therefore be assigned a low weight; after a period of exercise, when the user's condition stabilizes, it can be assigned a high weight.

[0083] The predetermined time interval can be a common time interval for the various sensors mentioned above, or different time intervals can be set for different sensors. For example, since users hold the handle for a relatively long time when playing, the measurement time interval of the pressure sensor on the handle can be relatively long in order to save the power consumption of the sensor; the measurement time interval of the inertial measurement unit of the racket face can be relatively short in order to obtain information such as the angular velocity and attitude of the racket in a timely and accurate manner during the user's high-speed swing.

[0084] In one embodiment, the racket intelligent detection and interaction method further includes: acquiring inertial data when the user is using the racket; acquiring second preset data from the second preset dataset based on the first preset data; determining whether the inertial data matches the second preset data, wherein if the inertial data does not match the second preset data, a second interaction message is sent.

[0085] Using data on racket face and handle for pressure and grip strength may not accurately determine user behavior. Furthermore, racket face and handle data are significantly influenced by individual factors and are greatly affected by external resistance and interference. Therefore, tracking a user's swing habits solely based on racket face and handle data may not be ideal. Figure 2 As shown, the racket intelligent detection and interaction method 100 also includes steps 105, 106, 107 and 108.

[0086] In step 105, the inertial data of the current user using the racket is obtained.

[0087] Inertial data can be acquired using an inertial measurement unit (IMU), which can be installed in the racket handle, on the racket face, or in the connecting rod between the racket face and handle. Based on the measurement results of the IMU, the user's motion state data during the swing can be calculated, such as the swing path and swing angle. If the IMU continuously collects the inertial data of the same user's swing over a period of time (e.g., 1 hour) and processes this inertial data, the user's motion habit data, i.e., swing habit data, can be obtained.

[0088] In step 106, second preset data is obtained from the second preset dataset based on the first preset data.

[0089] It is understood that the second preset data is the data in the second preset dataset that corresponds to the first preset data. The second preset dataset may include standard swing motion data for different users. For example, for children, the second preset dataset may include: the child's standard swing speed, standard swing path, standard swing angle, the racket position at the standard moment of impact, and the position of the standard hitting point on the racket face. Similarly, for athletes, the second preset dataset may include: the athlete's standard swing speed, standard swing path, standard swing angle, the racket position at the standard moment of impact, and the position of the standard hitting point on the racket face. Assuming, as described above, "children" are used as the first preset data, then the second preset data is the data in the second preset dataset that corresponds to "children," including the child's standard swing speed, standard swing path, and standard swing angle.

[0090] In step 107, it is determined whether the inertial data matches the second preset data.

[0091] By comparing the inertial data with the second preset data, it is possible to determine the differences between the current user's swing habits and the standard swing motion. See Table 4 below for a specific example:

[0092]

[0093] Table 4

[0094] As shown in Table 4 above, the measured inertia data of the current user (child user) during the swing differs significantly from the standard swing path of a child user. The child user's inertia data does not include the upward backswing motion, and the swing path does not have an arc. Therefore, it can be determined that the inertia data does not match the second preset data. Next, proceed to step 108.

[0095] In step 108, if the inertial data does not match the second preset data, a second interactive message is sent.

[0096] The second interactive information can be either a reminder or a suggestion. It can be displayed in text, voice, and / or graphic form. For example, it could be a text prompt such as "Incorrect swing motion," or a voice prompt such as "High clear requires a backswing" or "Adjust the swing angle for a jump smash." If the racket has a display screen, it can also demonstrate the standard / correct swing motion through images or videos. The racket can also send the second interactive information to the user's smartphone via Wi-Fi or mobile data for viewing and learning.

[0097] Understandably, the second preset dataset is a set of standard or regular swing motions. Of course, the "second preset dataset" can also be set with different standard swing motions according to different user types, such as net swing motions for adult men, net swing motions for teenage women, backcourt jump smash motions for adult men, and backcourt jump smash motions for teenage men, etc.

[0098] Similar to the first preset dataset source mentioned above, the second preset dataset includes one or more of the following: historical usage data of the racket; third-party big data platforms; and user-preset data. Taking historical usage data of the racket as an example, for instance, if 10-20 different users use the racket daily, each time the racket is used, it records the inertial data of each user during movement. After accumulating a preset amount of data, this inertial data can be categorized to form an inertial data dataset. Data obtained from third-party big data platforms (such as large-scale models of motion state data or large-scale models of motion habit data) is more universal. User-preset data is more conducive to targeted, specialized training by the user.

[0099] It is understood that the inertial data includes one or more of the following: racket acceleration data; racket angular velocity data; racket azimuth data; and racket attitude data. The acceleration data, angular velocity data, and azimuth data are acceleration data, angular velocity data, and azimuth data in three axes, respectively, and can be obtained using a three-axis accelerometer and a three-axis angular velocity meter.

[0100] In one embodiment, the racket includes a string adjustment device, and the racket intelligent detection and interaction method further includes: automatically adjusting the string tension of the racket by the string adjustment device based on the handle data and the racket face data. A higher string tension can improve the accuracy and power of the shot, but it increases pressure on the wrist and arm. Therefore, adjusting to a suitable string tension can achieve good training results for users with different strengths and playing styles.

[0101] For example, if the handle data and racket face data indicate that the current user is a beginner / teenager / child, and their accuracy and power in hitting the ball are not high, the string adjustment device can automatically adjust the string tension to a range of 20 to 24 pounds for easier racket control and serves. For intermediate and advanced players, the string adjustment device will adjust the string tension to 24 to 30 pounds, or even higher. Furthermore, the string adjustment device can automatically adjust the racket string tension based on inertia data. Inertia data reflects the user's behavioral habits (e.g., different playing styles), and the optimal string tension varies depending on the same user's different behavioral habits. Automatically adjusting the string tension by referring to inertia data is more beneficial for training.

[0102] like Figure 3 As shown, in a second aspect of this application, a smart racket is provided, comprising: a first sensor unit for acquiring handle data; a second sensor unit for acquiring racket face data; and a control unit configured to: acquire first preset data from a first preset dataset based on the handle data; determine whether the racket face data matches the first preset data, wherein if the racket face data does not match the first preset data, a first interactive message is issued.

[0103] It is understood that the intelligent racket described above has the same or similar technical features as the racket intelligent detection and interaction method described above, and will not be repeated here.

[0104] A third aspect of this application provides a computer storage medium storing a computer program that, when executed by a processor, implements the above-described racket intelligent detection and interaction method.

[0105] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0106] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0107] The above description is merely an exemplary embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope described in this application, and these should all be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A racket intelligent detection and interaction method, used for rackets, characterized in that, The racket intelligent detection and interaction method includes: Obtain the handle data and racket face data of the current user when using the racket; The first preset data is obtained from the first preset dataset based on the handle data; Determine whether the shot face data matches the first preset data, wherein, If the shot face data does not match the first preset data, then a first interactive message is sent.

2. The racket intelligent detection and interaction method according to claim 1, characterized in that, The handle data includes one or more of the following: grip pressure data, grip area data, grip duration data, pulse data, blood pressure data, and user input data.

3. The racket intelligent detection and interaction method according to claim 1, characterized in that, The racket face data includes one or more of the following: racket face pressure data generated by the ball, ball hitting frequency data, number of hits data, and racket face hitting point distribution data.

4. The racket intelligent detection and interaction method according to claim 1, characterized in that, The source of the first preset dataset includes one or more of the following: The racket's historical usage data; Third-party big data platforms; and User-preset data.

5. The racket intelligent detection and interaction method according to claim 1, characterized in that, The first interactive information is one or more of the following: Increase or decrease the power of your swing; Increase or decrease the power of the shot; Increase or decrease the frequency of hitting the ball; Increase or decrease the duration of exercise; Increase or decrease the number of shots; and Data on the distribution of the hitting point on the racket face.

6. The racket intelligent detection and interaction method according to claim 1, characterized in that, The first preset dataset is a user type set, and the first preset data is a user type.

7. The racket intelligent detection and interaction method according to claim 2, characterized in that, The process of obtaining handle data when the user is using the racket includes: obtaining one or more of the following at predetermined time intervals within a first preset duration: grip pressure data, grip area data, grip duration data, pulse data, blood pressure data, and user input data; calculating the average value of each type of data; and using the calculated average value as the handle data.

8. The racket intelligent detection and interaction method according to claim 1, characterized in that, Also includes: Obtain the inertial data of the current user when using the racket; The second preset data is obtained from the second preset dataset based on the first preset data; Determine whether the inertial data matches the second preset data, wherein, If the inertial data does not match the second preset data, a second interactive message is sent.

9. The racket intelligent detection and interaction method according to claim 8, characterized in that, The second preset dataset is a standard swing motion set or a regular swing motion set.

10. The racket intelligent detection and interaction method according to claim 8, characterized in that, The inertial data includes one or more of the following: The racket's acceleration data; Angular velocity data of the racket; Racket azimuth data; and Racket posture data.

11. The racket intelligent detection and interaction method according to claim 1, characterized in that, The racket includes a string adjustment device, and the racket intelligent detection and interaction method further includes: Based on the handle data and the racket face data, the string tension of the racket is automatically adjusted by the string adjustment device.

12. A smart racket, characterized in that, include: The first sensor unit is used to acquire handle data; The second sensor unit is used to acquire shooting face data. Control unit, the control unit is configured to: The first preset data is obtained from the first preset dataset based on the handle data; Determine whether the shot face data matches the first preset data, wherein, If the shot face data does not match the first preset data, then a first interactive message is sent.

13. A computer storage medium storing a computer program that, when executed by a processor, implements the method of any one of claims 1-11.

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