A Wearable Tactile Feedback Device for Badminton Training

Abstract

The present invention relates to the technical field of tactile feedback, and specifically provides a wearable tactile feedback device for badminton training, which includes a motion parameter extraction module, an action analysis module, a timing comparison module, a tactile signal generation module, and a feedback execution module. In the present invention, the gait and swing actions captured by the wrist and ankle sensors significantly improve the ability to capture the details of athletes' actions. Different from conventional tactile feedback technologies, the solution enables athletes to accurately master the core parameters of actions such as step length, speed, and angle through real-time data capture, improving the ability to control the details of the movement. Through in-depth analysis of the data, athletes can immediately obtain direct feedback on action optimization and quickly adjust to achieve ideal sports performance, effectively enhancing the personalization and adaptability of sports training and ensuring that the training plan for each athlete can accurately match their actual performance and improvement needs.

Description

Technical Field

[0001] The present invention relates to the technical field of tactile feedback training, and particularly to a wearable tactile feedback device for badminton training. Background Art

[0002] The technical field of tactile feedback training includes tactile feedback technologies applied to various educational and training environments. This technology enhances the interactive experience in virtual environments by simulating real tactile sensations. The core content involves tactile sensors, tactile feedback devices, and corresponding control systems, which act together on users to transmit information through the sensory channels of the skin. In the fields of sports training, medical rehabilitation, and virtual reality, tactile feedback technology is gradually being widely studied and applied to improve user experience and interaction efficiency.

[0003] Among them, a wearable tactile feedback device for badminton training refers to a device specifically designed for badminton sports training. Through tactile feedback elements integrated in clothing or accessories, it directly acts on specific parts of the user's body, detects the user's movement postures and ball-patting actions, and provides real-time tactile feedback, thereby helping users adjust and optimize their sports skills. The device supports personalized training needs and helps beginners quickly master correct badminton sports skills.

[0004] The application of traditional technologies in sports training, especially badminton training, is still insufficient. This is mainly manifested in the lack of real-time monitoring of the details of movement actions and personalized feedback. Traditional technologies mainly focus on basic tactile feedback and do not delve into the precise adjustment and optimization of movement actions. In addition, their ability to synchronize movement actions is weak, and they fail to achieve effective temporal alignment between footwork and swinging, which limits the real-time nature and accuracy of training, affects the pertinence of training, and the rapid improvement of sports skills. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, such as the lack of real-time monitoring of the details of movement actions and personalized feedback, traditional technologies mainly focusing on basic tactile feedback and not delving into the precise adjustment and optimization of movement actions, and in addition, their weak ability to synchronize movement actions and failure to achieve effective temporal alignment between footwork and swinging, which limits the real-time nature and accuracy of training, affects the pertinence of training, and the rapid improvement of sports skills, the embodiments of the present invention provide a wearable tactile feedback device for badminton training. The technical solution is as follows:

[0006] On the one hand, a wearable tactile feedback device for badminton training is provided, and the device includes:

[0007] The motion parameter extraction module collects the user's gait and racket swing actions through wrist and ankle sensors, extracts motion step length, moving direction, and speed signals, calculates step length increment, displacement change, and the acceleration and rotation angle of the racket swing, and synchronizes the motion trajectory to generate original action data;

[0008] Based on the original action data, the action analysis module analyzes the footwork movement trajectory, calculates the displacement coordinate change and step length change rate, extracts the acceleration and angular velocity during hitting, identifies key action nodes, and obtains key action indicators;

[0009] Based on the key action indicators, the timing comparison module compares with the standard action template, calculates the time delay between footwork and racket swing, matches the footwork and racket swing actions, determines the type of action deviation and time deviation, and generates a deviation analysis result;

[0010] Based on the deviation analysis result, the tactile signal generation module calculates the time deviation amount of abnormal footwork and racket swing, adjusts the vibration mode during abnormal actions, and generates a vibration control signal;

[0011] Based on the vibration control signal, the feedback execution module adjusts the vibration frequency and amplitude, monitors the gait and racket swing actions after feedback, compares with the original action offset, records the action deviation before and after adjustment, and generates a training feedback result.

[0012] On the other hand, the original action data includes step length records, speed waveforms, acceleration curves, and rotation angle data. The key action indicators include footwork change frequency, hitting speed, acceleration peak value, and angular velocity analysis result. The deviation analysis result includes footwork start delay, racket swing synchronization score, and action deviation type. The vibration control signal includes adjusted vibration frequency, vibration mode, and vibration duration setting. The training feedback result includes vibration effect monitoring data, action response analysis result, and deviation trend comparison result.

[0013] On the other hand, the motion parameter extraction module includes:

[0014] The sensor data analysis sub-module analyzes the user's gait and racket swing actions collected by wrist and ankle sensors, analyzes motion step length, moving direction, and speed signals, identifies motion patterns and time rhythms, and obtains motion rhythm characteristics;

[0015] Based on the motion rhythm characteristics, the motion feature calculation sub-module calculates the step length increment and displacement vector change within adjacent time periods, analyzes the acceleration and rotation angle during the racket swing, quantifies the action intensity and motion accuracy, and generates motion intensity indicators;

[0016] The data synchronization sub-module calculates the relative time offset between the gait and the swing based on the exercise intensity index, aligns the timestamps of the motion trajectory data, adjusts the synchronization matching degree of the data points on the time axis, and obtains the original action data.

[0017] On the other hand, to quantify the exercise intensity and motion accuracy, the formula is used: ;

[0018] Generate the exercise intensity index;

[0019] Where, represents the exercise intensity index, represents the swing acceleration of the th frame, represents the swing rotation angle of the th frame, represents the number of time frames within the calculation interval, represents the displacement speed of the th frame, represents the average displacement speed within the time window.

[0020] On the other hand, the action analysis module includes;

[0021] The displacement direction analysis sub-module analyzes the displacement direction of the footwork based on the original action data, calculates the displacement coordinate change value of each motion sequence, determines the stability and change trend of the motion direction, and generates the direction stability analysis result;

[0022] The step length change rate calculation sub-module extracts the step length change values in adjacent time periods based on the direction stability analysis result, analyzes the step length increment in each cycle, calculates the step length change rate, and determines whether there is an abnormal fluctuation in the footwork rhythm to obtain the rhythm fluctuation index;

[0023] The swing power calculation sub-module extracts the speed and angle change data in the swing action based on the rhythm fluctuation index, measures the acceleration peak value and instantaneous angular velocity, compares the synchronization of the footwork data and the swing action on the time axis, identifies the key action nodes, and generates the action key index.

[0024] On the other hand, to calculate the step length change rate, the formula is used:

[0025] ;

[0026] Determine whether there is an abnormal fluctuation in the footwork rhythm to obtain the rhythm fluctuation index;

[0027] Where, represents the step length change rate, represents the step length in the th time period, Represents the step size of the previous time period, Represents the total number of step size change periods, Represents the th time point, Represents the previous time point.

[0028] On the other hand, the timing comparison module includes:

[0029] The feature parameter comparison sub-module compares the key action metrics with the standard action template based on the key action metrics, calculates the weighted deviation mean of the step size, speed, and angle parameters, evaluates the standard deviation and relative dispersion of the action, identifies the key performance deviation points, and obtains the key deviation parameters;

[0030] The time delay analysis sub-module uses the key deviation parameters to calculate the difference in the time series between the start of the footwork and the swing action, extracts the time interval between the two actions, sets the time delay reference value, compares and judges the offset direction of the real-time time interval, and generates the time offset;

[0031] The time deviation classification sub-module classifies the time difference between the start of the footwork and the swing action based on the time offset, divides the type of time deviation, analyzes the distribution frequency of the deviation in the action sequence, and obtains the deviation analysis result.

[0032] On the other hand, when calculating the weighted deviation mean of the step size, speed, and angle parameters, the formula is used:

[0033] ;

[0034] Evaluate the standard deviation and relative dispersion of the action, identify the key performance deviation points, and obtain the key deviation parameters;

[0035] Among them, Represents the weighted deviation mean, Represents the th sample weight, Represents the th sample observation value, Represents the th parameter value in the standard action template, Represents the total number of measured action parameters.

[0036] On the other hand, the tactile signal generation module includes;

[0037] The vibration amplitude adjustment sub-module extracts the data of footwork anomalies and swing errors based on the deviation analysis result, calculates the corresponding vibration amplitude adjustment amount, determines the error level, adjusts the vibration power according to the error level, and generates the vibration power adjustment value;

[0038] The vibration mode setting sub-module calls the vibration power adjustment value, matches the vibration mode for the training action, optimizes the vibration trigger time according to the motion feedback, and calculates the vibration duration in different modes to obtain the vibration mode configuration.

[0039] The sensor signal distribution sub-module extracts the vibration feedback direction of abnormal footwork based on the vibration mode configuration, optimizes the signal intensity of the wrist part for the racket swing error, adjusts the signal distribution of the wrist and ankle sensors, and obtains the vibration control signal.

[0040] On the other hand, the feedback execution module includes;

[0041] The sensor adjustment sub-module extracts the vibration frequency and amplitude adjustment parameters in the feedback signal based on the vibration control signal, performs numerical analysis, calculates the vibration adjustment ratio corresponding to the difference deviation range, and corrects the vibration parameters of the ankle and wrist sensors according to the adjustment ratio to obtain the vibration correction value.

[0042] The motion response monitoring sub-module monitors the gait and racket swing motion after the feedback trigger based on the vibration correction value, calculates the time difference from the feedback signal trigger to the motion response, obtains the motion offset before and after adjustment, calculates the motion offset amplitude and the direction change angle, and generates the motion offset index.

[0043] The deviation trend analysis sub-module compares the motion data before and after adjustment based on the motion offset index, determines the motion change amplitude after feedback, analyzes the motion feedback deviation trend curve, calculates the trend ratio of the motion change, and generates the training feedback result.

[0044] The beneficial effects brought by the technical solution provided by the embodiments of the present invention at least include:

[0045] The innovative solution captures the gait and racket swing motion through the wrist and ankle sensors, significantly improving the ability to capture the details of athletes' movements. Different from conventional tactile feedback technologies, the solution enables athletes to precisely master the core parameters of movements such as step length, speed, and angle through real-time data capture, enhancing the ability to control the details of the movement. Through in-depth analysis of the data, athletes can immediately obtain direct feedback on movement optimization and quickly adjust to achieve ideal sports performance, effectively enhancing the personalization and adaptability of sports training and ensuring that the training plan for each athlete can accurately meet their actual performance and improvement needs. Description of the Drawings

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0047] Figure 1 It is a system schematic diagram of the present invention;

[0048] Figure 2 It is a schematic diagram of the system framework of the present invention;

[0049] Figure 3 It is a flowchart of the motion parameter extraction module of the present invention;

[0050] Figure 4 It is a flowchart of the action analysis module of the present invention;

[0051] Figure 5 It is a flowchart of the timing comparison module of the present invention;

[0052] Figure 6 It is a flowchart of the tactile signal generation module of the present invention;

[0053] Figure 7 It is a flowchart of the feedback execution module of the present invention. Detailed implementation manners

[0054] The following will describe the technical solutions in the present invention in conjunction with the accompanying drawings.

[0055] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either of the two can be selected.

[0056] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when their differences are not emphasized, the meanings they express are the same. "(of)", "corresponding" and "corresponding" can sometimes be used interchangeably. It should be noted that when their differences are not emphasized, the meanings they express are the same.

[0057] In the embodiments of the present invention, sometimes subscripts such as W1 may be written in a non-subscript form such as W1. When their differences are not emphasized, the meanings they express are the same.

[0058] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0059] An embodiment of the present invention provides a wearable tactile feedback device for badminton training, as Figure 1 shown, the device includes:

[0060] The motion parameter extraction module collects the user's gait and racket swing actions through wrist and ankle sensors, extracts motion step length, moving direction and speed signals, calculates the step length increment and displacement vector change within adjacent time periods, analyzes the acceleration and rotation angle during the racket swing process, and synchronizes the gait and racket swing motion trajectory data to generate original action data;

[0061] The action analysis module analyzes the moving trajectory of the footwork based on the original action data, calculates the change value of the displacement coordinate to determine the step length change rate within each time period, and extracts the acceleration peak value and calculates the instantaneous angular velocity according to the speed and angle changes at the moment of hitting the ball during the racket swing action. It synchronizes the footwork and racket swing data on the time axis, identifies key action nodes, and obtains key action indicators;

[0062] The timing comparison module compares with the standard action template based on the key action indicators, calculates the time delay amount between the start of the footwork and the racket swing action, analyzes the matching degree between the footwork and the racket swing action, determines the type of action deviation and time deviation data, and generates a deviation analysis result;

[0063] The tactile signal generation module calculates the time deviation amount of the footwork ahead and the racket swing lag based on the deviation analysis result, sets the trigger frequency and amplitude of the vibration signal, adjusts the vibration frequency of the ankle sensor for abnormal footwork, and at the same time adjusts the vibration duration of the wrist sensor according to the racket swing deviation to generate a vibration control signal;

[0064] The feedback execution module adjusts the vibration frequency and amplitude after the sensor feedback based on the vibration control signal, monitors the gait and racket swing actions after the feedback trigger, compares the original action offset amount and records the action deviation before and after adjustment, analyzes the action deviation trend, and generates a training feedback result.

[0065] The original action data includes step length records, speed waveforms, acceleration curves and rotation angle data. The key action indicators include the footwork change frequency, hitting speed, acceleration peak value and angular velocity analysis result. The deviation analysis result includes footwork start delay, racket swing synchronization score and action deviation type. The vibration control signal includes the adjusted vibration frequency, vibration mode and vibration duration setting. The training feedback result includes vibration effect monitoring data, action response analysis result and deviation trend comparison result.

[0066] As Figure 2 andFigure 3 As shown in the figure, the motion parameter extraction module includes:

[0067] The sensor data analysis sub-module collects the user's gait and swing actions based on the wrist and ankle sensors, analyzes the motion step length, moving direction, and speed signal, identifies the motion pattern and time rhythm, and obtains the motion rhythm characteristics;

[0068] The wrist and ankle sensors collect the user's gait and swing actions. The gait data includes information such as step length, step frequency, moving direction, and grounding method. The swing action data includes parameters such as acceleration, angular velocity, and swing trajectory. The acquired data is sorted by timestamp to ensure that all data points are arranged in time series. When identifying the motion step length, the coordinate difference of the sole contact points between two adjacent steps is calculated. For example, in a gait detection, the coordinate of the left foot touchdown point is (1.2, 3.4), and the coordinate of the right foot touchdown point is (2.5, 3.8). The step length calculation method is , substituting the data, the step length can be obtained as 1.39 meters. The moving direction is determined by calculating the vector angle. Assuming that two consecutive displacement vectors within a certain motion cycle are (1.2, 0.8) and (1.4, 0.9), then the direction angle , and the calculated direction change angle is 4.2 degrees. The speed signal is calculated by dividing the displacement change amount within a time period by the time interval. For example, if the displacement changes by 1.2 meters within 0.5 seconds, the speed is 2.4 m / s. Based on all the step length, moving direction, and speed signal data, the gait pattern is judged. If the step length is between 1.2 and 1.5 meters, the step frequency is between 1.5 and 2.0 steps per second, and the moving direction is stable, it is judged as a normal gait. If the step length is less than 0.8 meters or the step frequency exceeds 2.5 steps per second, it is a running mode. Based on the swing action data, the acceleration and angular velocity change rates are calculated, and the swing mode is identified by judging the acceleration characteristics of different swing modes. For example, the acceleration peak of a fast swing reaches 15 m / s², while that of a slow swing is only 5 m / s². By comparing the swing rhythm parameters of different modes, the motion rhythm characteristics are generated.

[0069] The motion feature calculation sub-module calculates the step length increment and displacement vector change within adjacent time periods based on the motion rhythm characteristics, analyzes the acceleration and rotation angle during the swing process, quantifies the action intensity and motion accuracy, and generates the motion intensity index;

[0070] The quantification of the action intensity and motion accuracy adopts the formula: ;

[0071] Generate the motion intensity index;

[0072] Among them, represents the motion intensity index, represents the swing acceleration of the th frame, represents the swing rotation angle of the th frame, represents the number of time frames within the calculation interval, represents the displacement speed of the th frame, represents the average displacement speed within the time window.

[0073] For badminton, the general maximum acceleration can reach 50 - 60 m / s². Select m / s², m / s², m / s², select the common hitting angle range, set °, °, °. Generally, the footwork speed of athletes is between 1.5 - 3 m / s. Set m / s, m / s, m / s, and use the arithmetic mean formula:

[0074] ;

[0075] Substitute the known data:

[0076] ;

[0077] represents the number of time frames within the calculation interval. Set n = 3 (sampling interval 100 ms, a total of 3 frames);

[0078] Substitute the parameters into the formula for calculation;

[0079] First - part calculation: The mean of the product of acceleration and rotation angle;

[0080] ;

[0081] Substitute the parameters:

[0082] ;

[0083] Second - part calculation: The standard deviation of speed;

[0084] ;

[0085] Substitute the data:

[0086] ;

[0087] ;

[0088] ;

[0089] ;

[0090] ;

[0091] Finally, calculate the exercise intensity index;

[0092] ;

[0093] Analysis of calculation results

[0094] The result shows that the exercise intensity index is 399.84. Its value reflects the change in mechanical strength during the athlete's footwork and racket swing within the set time frame. Combining the acceleration, rotation angle, and speed fluctuation, it illustrates the action stability and force matching of this exercise pattern. A higher value indicates a more powerful and intense action with significant changes, while a lower value indicates a smoother or less forceful movement.

[0095] Based on the exercise intensity index, the data synchronization sub-module calculates the relative time offset between gait and racket swing, aligns the timestamps of the motion trajectory data, adjusts the synchronization matching degree of the data points on the time axis, and obtains the original action data.

[0096] Based on the exercise intensity index, calculate the relative time offset between gait and racket swing. The calculation method of the time offset is the racket swing start time minus the gait start time. For example, if the gait start time is 1.2 seconds and the racket swing start time is 1.8 seconds, then the time offset is 0.6 seconds. Align the timestamps of the motion trajectory data, adjust the timestamps of all data points to match the time axis. Assuming the time axis interval is 0.1 seconds, if the gait data points are recorded at 1.2 seconds, 1.3 seconds, 1.4 seconds, and the racket swing data points are recorded at 1.22 seconds, 1.32 seconds, 1.42 seconds, then adjust the racket swing data point timestamps to 1.2 seconds, 1.3 seconds, 1.4 seconds to ensure time matching. By calculating the time matching error, if the matching error is less than 0.05 seconds, it is determined that the data alignment is successful; otherwise, continue to adjust. Optimize the time synchronization matching through a loop matching algorithm to obtain the original action data.

[0097] As Figure 2 and Figure 4 shown, the action analysis module includes;

[0098] Based on the original action data, the displacement direction analysis sub-module analyzes the displacement direction of the footwork, calculates the displacement coordinate change value of each motion sequence, determines the stability and change trend of the motion direction, and generates the direction stability analysis result;

[0099] Obtain the displacement coordinate points in the motion trajectory. Each motion sequence contains multiple coordinate points. By calculating the change value of the displacement coordinates at adjacent time points, determine the stability of the motion direction. The calculation method is to subtract the coordinate of the previous time point from the current position coordinate. For example, the displacement coordinate point sequence of a certain user is (3.0, 4.2), (3.8, 4.5), (4.6, 5.0). Calculate the change value of adjacent coordinates, , substituting the data gives (0.8, 0.3) and (0.8, 0.5). Calculate the motion direction change rate. If the current direction change angle is , calculate that the direction angle of the first step is 20.6°, the direction angle of the second step is 32.0°, and the direction change trend is (32.0° - 20.6°) = 11.4°. If the direction change angle between adjacent steps is less than 10°, it is determined that the motion direction is stable. If it is greater than 20°, it is determined that the direction changes violently, and generate the direction stability analysis result.

[0100] Based on the direction stability analysis result, the step length change rate calculation sub-module extracts the step length change values in adjacent time periods, analyzes the step length increment in each cycle, calculates the step length change rate, and determines whether there is an abnormal fluctuation in the gait rhythm to obtain the rhythm fluctuation index;

[0101] Calculate the step length change rate using the formula:

[0102] ;

[0103] Determine whether there is an abnormal fluctuation in the gait rhythm to obtain the rhythm fluctuation index;

[0104] Among them, represents the step length change rate, represents the step length in the th time cycle, represents the step length in the previous time cycle, represents the total number of step length change cycles, represents the th time point, represents the previous time point;

[0105] The step length Measure the length of each step through a pressure sensor. Assume that in a test, the device records the step length data of 10 steps, with the unit of meter, and obtains the following data:

[0106] 、 、 、 、 、 、 、 、 , ;

[0107] Time point corresponds to the timestamp at each step measurement, in seconds. Assume the corresponding timestamps are:

[0108] , , , , , , , , , ;

[0109] Step difference : Calculate the absolute difference between adjacent steps. For example:

[0110] meters;

[0111] meters;

[0112] And so on, calculate all adjacent step differences;

[0113] Time interval : Calculate the time difference between adjacent time points. For example:

[0114] seconds;

[0115] seconds;

[0116] And so on, calculate all adjacent time differences;

[0117] Substitute the above data into the formula for calculation:

[0118] Calculate the sum of step differences:

[0119] ;

[0120] ;

[0121] ;

[0122] Calculate the square root of the sum of the squares of time intervals:

[0123] ;

[0124] ;

[0125] ;

[0126] Calculate the step length change rate :

[0127] ;

[0128] The result shows that the step length change rate is 0.00913 m / s, indicating that during the test, the average rate of step length change is low and the pace rhythm is relatively stable.

[0129] The swing power calculation sub-module extracts the speed and angle change data in the swing action based on the rhythm fluctuation index, measures the peak acceleration and instantaneous angular velocity, compares the synchronization of the footwork data and the swing action on the time axis, identifies the key action nodes, and generates the key action indicators.

[0130] The speed calculation method is the total length of the swing path divided by the swing time. For example, if the total swing length is 2.4 meters and the swing time is 0.8 seconds, the swing speed is 3.0 m / s. The peak acceleration calculation method is the speed increment divided by the time increment. For example, if the initial swing speed is 2.0 m / s, the maximum speed is 4.5 m / s, and the time change is 0.6 seconds, the peak acceleration is , substituting the data gives a peak acceleration of 4.17 m / s2. The instantaneous angular velocity calculation method is the angle change divided by the time increment. For example, if the starting angle of the swing is 15°, the ending angle is 75°, and the time increment is 0.5 seconds, the angular velocity is 120° / s. Compare the synchronization of the footwork data and the swing action on the time axis, calculate the time matching error between the two. For example, the time required for footwork adjustment is 0.7 seconds, the swing adjustment time is 0.9 seconds, and the time synchronization error is 0.2 seconds. If the error is less than 0.3 seconds, it is judged that the swing and footwork are synchronized, otherwise it is judged that the footwork and swing rhythms are out of balance, and the key action indicators are generated.

[0131] As Figure 2 and Figure 5 shown, the timing comparison module includes:

[0132] The characteristic parameter comparison sub-module compares the key action indicators with the standard action template based on the key action indicators, calculates the weighted deviation values of the step length, speed, and angle parameters, evaluates the standard deviation and relative dispersion of the action, identifies the key performance deviation points, and obtains the key deviation parameters;

[0133] Calculate the weighted deviation mean of the step length, speed, and angle parameters, using the formula:

[0134] ;

[0135] Evaluate the standard deviation and relative dispersion of the action, identify the key performance deviation points, and obtain the key deviation parameters;

[0136] Among them, represents the weighted mean deviation, denotes the weight of the th sample, denotes the observed value of the th sample, represents the th parameter value in the standard action template, represents the total number of measured action parameters;

[0137] Record step length, speed, and angle action parameters through a motion sensor , the step length data is obtained from an inertial measurement unit, the speed is calculated by the ratio of displacement change to time, and the angle parameter is measured by a gyroscope. For example, a certain test sample contains the following measurement data:

[0138] (step length, unit: meter);

[0139] (speed, unit: m / s);

[0140] (angle, unit: degree);

[0141] Standard action template parameters Obtaining method;

[0142] Establish a standard template from the original training data, calculated from the average values of professional athletes. For example:

[0143] (step length, unit: meter);

[0144] (speed, unit: m / s);

[0145] (angle, unit: degree);

[0146] Calculate the absolute deviation value ;

[0147] Calculate the deviation value of each parameter:

[0148] m (step length deviation);

[0149] m / s (speed deviation);

[0150] degree (angle deviation);

[0151] The weight coefficient is determined based on the importance of the parameters. The importance of the step size, speed, and angle is different. For example, the step size has a greater impact on the overall movement rhythm, so a higher weight is set, while the weights of speed and angle are relatively lower:

[0152] (step size weight);

[0153] (speed weight);

[0154] (angle weight);

[0155] Calculate the numerator part ;

[0156] ;

[0157] Calculate the denominator part ; ;

[0158] Calculate the weighted deviation mean ; ;

[0159] This result shows that the weighted deviation mean is 0.585, indicating that there is a certain degree of deviation between the current action characteristics and the standard template. The larger the deviation value, the more obvious the gap from the standard template. The result can be used to further optimize the action parameters to make them closer to the standard action and improve the overall action stability.

[0160] The time delay analysis sub-module uses the key deviation parameters to calculate the difference in the time series between the start of the footwork and the swing action, extracts the time interval between the two actions, sets the time delay reference value, compares and judges the offset direction of the real-time time interval, and generates the time offset;

[0161] Obtain the start time of the footwork and the start time of the swing. For example, if the start time of the footwork is 2.1 seconds and the start time of the swing is 2.8 seconds, the calculation method of the time interval between the two actions is , substituting the data gives a time interval of 0.7 seconds. Set the time delay reference value. For example, the reference value is 0.5 seconds. Compare the deviation between the time interval and the reference value, judge the offset direction of the time interval. If the time interval is greater than the reference value, the start of the footwork lags behind, otherwise the start of the footwork is ahead. Calculate the time offset , if the calculated time offset is 0.2 seconds, the start of the footwork lags behind by 0.2 seconds. If the offset is -0.3 seconds, the start of the footwork is ahead by 0.3 seconds, and generate the time offset.

[0162] The time deviation classification sub-module classifies based on the time offset and the time difference between the start of the footwork and the swing action, divides the types of time deviation, analyzes the distribution frequency of the deviation in the action sequence, and obtains the deviation analysis result.

[0163] Divide the types of time deviation. The classification method is to set a time difference threshold. For example, the normal deviation range is set to ±0.2 seconds. If the time offset is between -0.2 seconds and 0.2 seconds, it is judged as normal synchronization. If it is greater than 0.2 seconds, it is judged that the start of the footwork lags. If it is less than -0.2 seconds, it is judged that the start of the footwork is advanced. Analyze the distribution frequency of the time deviation in the action sequence, and count the occurrence times of various types of time deviation. For example, in 100 motion records, the number of times the footwork lags is 30, the number of times it is advanced is 15, and the number of times of normal synchronization is 55. Then the lag frequency is 30%, the advance frequency is 15%, and the normal frequency is 55%. Obtain the deviation analysis result.

[0164] As Figure 2 and Figure 6 shown, the tactile signal generation module includes;

[0165] Based on the deviation analysis result, the vibration amplitude adjustment sub-module extracts the data of footwork anomalies and swing errors, calculates the corresponding vibration amplitude adjustment amount, determines the error level, and adjusts the vibration power according to the error level to generate a vibration power adjustment value;

[0166] Screen the footwork anomaly data points, including records with excessive step length changes, footwork direction deviations, and abnormal start times. At the same time, extract the swing error data points, including records with swing angle offsets, swing speed fluctuations, and mismatched hitting times. Calculate the vibration amplitude adjustment amount. The calculation method is the error deviation value multiplied by the vibration adjustment coefficient. For example, the footwork deviation value is 0.3 seconds, the swing error value is 5°, and the vibration adjustment coefficient is set to 2.5. Then the vibration amplitude adjustment amount calculation formula is , substituting the data, the vibration amplitude adjustment amount can be obtained as 0.75. Determine the error level, set multiple error ranges. For example, 0 - 0.2 seconds is low error, 0.2 - 0.5 seconds is medium error, and greater than 0.5 seconds is high error. Corresponding to different levels of vibration power, low error corresponds to a power of 0.5W, medium error corresponds to a power of 1.0W, and high error corresponds to a power of 1.5W. Match the corresponding vibration power according to the error level to generate a vibration power adjustment value.

[0167] The vibration mode setting sub-module calls the vibration power adjustment value, matches the vibration mode for the training action, optimizes the vibration trigger time according to the motion feedback, and calculates the vibration duration in different modes to obtain the vibration mode configuration;

[0168] Set the vibration trigger timing. For example, the step adjustment delay threshold is set to 0.3 seconds. If the step error exceeds this threshold, the vibration trigger timing is set to 0.1 seconds after the error occurs. If the error is less than 0.3 seconds, the vibration is triggered 0.05 seconds after the error occurs. Calculate the vibration duration in the differential mode. The vibration duration calculation method is the error magnitude multiplied by the vibration duration coefficient. For example, if the error is 0.4 seconds and the vibration duration coefficient is set to 1.2, then , substituting the data for calculation, the vibration duration is 0.48 seconds. If the duration is less than 0.2 seconds, set the minimum vibration time to 0.2 seconds. If it exceeds 1 second, set the maximum vibration time to 1 second to obtain the vibration mode configuration.

[0169] Based on the vibration mode configuration, the sensor signal distribution sub-module extracts the vibration feedback direction of the abnormal steps, optimizes the signal intensity of the wrist part for the swing error, adjusts the signal distribution between the wrist and ankle sensors, and obtains the vibration control signal.

[0170] Judge the main direction of the step deviation. For example, if the step deviates 0.3 meters to the left, the vibration feedback direction is set to the right. If the step deviates forward beyond the set range, the vibration feedback direction is set to the rear. Optimize the signal intensity of the wrist part for the swing error, calculate the signal intensity of the wrist vibration feedback, and the calculation method is the error deviation angle multiplied by the signal adjustment coefficient. For example, if the error angle is 8° and the signal adjustment coefficient is set to 0.4, then the signal intensity is calculated as , substituting the data for calculation, the signal intensity is 3.2. Adjust the signal distribution between the wrist and ankle sensors, set the feedback signal distribution ratio. For example, the ankle signal accounts for 60% and the wrist signal accounts for 40%. If the step error is large, the ankle signal ratio is increased to 70% to obtain the vibration control signal.

[0171] As Figure 2 and Figure 7 shown, the feedback execution module includes;

[0172] Based on the vibration control signal, the sensor adjustment sub-module extracts the vibration frequency and amplitude adjustment parameters in the feedback signal, performs numerical analysis, calculates the vibration adjustment ratio corresponding to the differential deviation range, and corrects the vibration parameters of the ankle and wrist sensors according to the adjustment ratio to obtain the vibration correction value;

[0173] Obtain the vibration amplitude from the vibration feedback data and the vibration frequency , analyze the feedback signal intensity in different motion states, calculate the vibration adjustment ratio corresponding to the differential deviation range, and the calculation method is the ratio of the current error value to the set reference error value. For example, if the current vibration adjustment error is 0.6 seconds and the set reference error value is 0.4 seconds, then the adjustment ratio calculation formula is , substituting the data gives an adjustment ratio of 1.5. According to the adjustment ratio, the vibration parameters of the ankle and wrist sensors are corrected. The correction formula is , assuming the current vibration amplitude is 2.0 mm and the frequency is 50 Hz. Substituting the adjustment ratio for calculation gives a new vibration amplitude of 3.0 mm and a frequency of 75 Hz. Ensure that the corrected vibration parameters are within the allowable range. For example, the set amplitude range is 1.0 mm to 4.0 mm, and the frequency range is 30 Hz to 100 Hz. If it exceeds the range, take the maximum or minimum value to obtain the vibration correction value.

[0174] Based on the vibration correction value, the action response monitoring sub-module monitors the gait and racket swing actions after the feedback trigger, calculates the time difference from the feedback signal trigger to the action response, obtains the action offset before and after adjustment, calculates the action offset amplitude and the direction change angle, and generates an action offset index;

[0175] Collect the movement displacements of the wrist and ankle after the vibration trigger, and calculate the time difference from the feedback signal trigger to the action response. The time difference calculation method is the action response time minus the vibration trigger time. For example, if the vibration trigger time is 3.2 seconds and the action response time is 3.6 seconds, then the time difference calculation formula is , substituting the data gives a time difference of 0.4 seconds. Obtain the action offset before and after adjustment. The calculation method is the adjusted displacement value minus the pre-adjustment displacement value. For example, if the pre-adjustment displacement is 0.8 meters and the adjusted displacement is 1.1 meters, then the displacement increment is 0.3 meters. Calculate the action offset amplitude. The formula is , where are the displacement change amounts respectively. Assuming meters, meters, then the calculated offset amplitude is 0.29 meters. Calculate the direction change angle. The calculation method is , substituting the data for calculation gives an angle change of 31.2°, and generates an action offset index.

[0176] Based on the action offset index, the deviation trend analysis sub-module compares the action data before and after adjustment, determines the action change amplitude after feedback, analyzes the action feedback deviation trend curve, calculates the trend ratio of the action change, and generates a training feedback result.

[0177] The system extracts the offset change data within each time window to calculate the action change amplitude after feedback. Assuming the step offset data for the previous 5 time windows are respectively:

[0178] cm, and after adjustment cm,

[0179] Then calculate the average change amplitude:

[0180] ;

[0181] Among them = 5, substitute the data for calculation:

[0182] ;

[0183] ;

[0184] Meanwhile, the system analyzes the action feedback deviation trend curve, calculates the trend ratio, and adopts the trend change calculation formula:

[0185] ;

[0186] Among them, = 5.0 cm;

[0187] ; The system records the trend ratio and generates the training feedback result.

[0188] It should be understood that the term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. These three situations, where A and B can be singular or plural. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship. Specifically, it can be understood by referring to the context before and after.

[0189] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following items (pieces)" or its similar expressions refer to any combination of these items, including any combination of single items (pieces) or plural items (pieces). For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0190] It should be understood that in various embodiments of the present invention, the magnitude of the sequence numbers of the above processes does not mean 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 to the implementation process of the embodiments of the present invention.

[0191] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0192] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0193] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections between each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0194] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0195] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0196] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0197] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claimed rights.

Claims

1. A wearable tactile feedback device for badminton training, characterized in that: The device comprises: The motion parameter extraction module collects the user's gait and swinging movements through wrist and ankle sensors, extracts the motion step length, moving direction and speed signals, calculates the step length increment, displacement change, and the acceleration and rotation angle of the swing, and synchronizes the motion trajectory to generate raw motion data; The action analysis module analyzes the movement trajectory of the footwork based on the original action data, calculates the displacement coordinate change and the step length change rate, extracts the acceleration and angular velocity when hitting the ball, identifies the key action nodes, and obtains the key action indicators; The action parsing module includes: The displacement direction analysis submodule analyzes the displacement direction of the steps based on the original motion data, calculates the displacement coordinate change value of each motion sequence, determines the stability and change trend of the motion direction, and generates a directional stability analysis result; The step length change rate calculation submodule extracts the step length change values ​​of adjacent time periods based on the directional stability analysis results, analyzes the step length increment in each cycle, calculates the step length change rate, and determines whether there is abnormal fluctuation in the step rhythm to obtain the rhythm fluctuation index; The swing power calculation submodule extracts the speed and angle change data in the swing action based on the rhythm fluctuation index, measures the acceleration peak and instantaneous angular velocity, compares the synchronization of the footwork data and the swing action on the time axis, identifies the key action nodes, and generates the key action indicators; The step length change rate is calculated using the formula: ； in, represents the rate of change of step size, Representative The step length in a time period, Represents the step size of the previous time period, Represents the total number of step length change cycles, Representative A point in time, Represents the last point in time; The timing comparison module compares the standard action template based on the key action indicators, calculates the time delay between the footwork and the swing, matches the footwork and the swing, determines the action deviation type and time deviation, and generates a deviation analysis result; The tactile signal generation module calculates the time deviation of abnormal steps and swings based on the deviation analysis results, adjusts the vibration mode during abnormal movements, and generates a vibration control signal; The feedback execution module adjusts the vibration frequency and amplitude based on the vibration control signal, monitors the gait and swing action after feedback, compares the original action offset, records the action deviation before and after adjustment, and generates training feedback results.

2. The wearable tactile feedback device for badminton training according to claim 1, characterized in that: The original motion data includes step length records, speed waveforms, acceleration curves and rotation angle data; the key motion indicators include footwork change frequency, hitting speed, acceleration peak and angular velocity analysis results; the deviation analysis results include footwork start delay, swing synchronization score and motion deviation type; the vibration control signal includes adjusted vibration frequency, vibration mode and vibration duration settings; the training feedback results include vibration effect monitoring data, motion response analysis results and deviation trend comparison results.

3. The wearable tactile feedback device for badminton training according to claim 1, characterized in that: The motion parameter extraction module comprises: The sensor data analysis submodule collects the user's gait and swing movements based on wrist and ankle sensors, analyzes the movement step length, movement direction and speed signals, identifies the movement pattern and time rhythm, and obtains the movement rhythm characteristics; The motion feature calculation submodule calculates the step increment and displacement vector change in adjacent time periods based on the motion rhythm features, analyzes the acceleration and rotation angle during the swing process, quantifies the action intensity and motion accuracy, and generates a motion intensity index; The data synchronization submodule calculates the relative time offset between the gait and the swing based on the motion intensity index, aligns the timestamps of the motion trajectory data, adjusts the synchronization matching degree of the data points on the time axis, and obtains the original motion data.

4. The wearable tactile feedback device for badminton training according to claim 3, characterized in that: The quantified movement intensity and movement accuracy adopts the formula: ; in, Represents the intensity index of exercise. Representative The swing acceleration of the frame, Representative The swing rotation angle of the frame, Represents the number of time frames within the calculation interval, Representative The frame displacement speed, Represents the average displacement velocity within the time window.

5. The wearable tactile feedback device for badminton training according to claim 1, characterized in that: The timing comparison module includes: The feature parameter comparison submodule compares the key action indicators with the standard action template based on the key action indicators, calculates the weighted deviation mean of the step length, speed and angle parameters, evaluates the standard deviation and relative dispersion of the action, identifies the key performance deviation points, and obtains the key deviation parameters; The time delay analysis submodule uses the key deviation parameters to perform difference calculation on the time series between the footwork start and the swing action, extracts the time interval between the two actions, sets the time delay reference value, compares and determines the offset direction of the real-time time interval, and generates the time offset; The time deviation classification submodule classifies the time difference between the footwork start and the swing action based on the time offset, divides the type of time deviation, analyzes the distribution frequency of the deviation in the action sequence, and obtains the deviation analysis result.

6. The wearable tactile feedback device for badminton training according to claim 5, characterized in that: The weighted deviation mean of the step length, speed and angle parameters is calculated using the formula: ； in, represents the weighted mean deviation, Indicates The weight of the samples, Indicates The observed value of a sample, Represents the standard action template parameter values, Represents the total number of action parameters measured.

7. The wearable tactile feedback device for badminton training according to claim 1, characterized in that: The tactile signal generating module comprises: The vibration amplitude adjustment submodule extracts data of abnormal footwork and swing error based on the deviation analysis result, calculates the corresponding vibration amplitude adjustment amount, determines the error level, adjusts the vibration power according to the error level, and generates a vibration power adjustment value; The vibration mode setting submodule calls the vibration power adjustment value, matches the vibration mode to the training action, optimizes the vibration trigger time according to the motion feedback, and calculates the vibration duration in the difference mode to obtain the vibration mode configuration; The sensor signal distribution submodule extracts the vibration feedback direction of abnormal footwork based on the vibration mode configuration, optimizes the signal strength of the wrist according to the swing error, adjusts the signal distribution of the wrist and ankle sensors, and obtains the vibration control signal.

8. The wearable tactile feedback device for badminton training according to claim 1, characterized in that: The feedback execution module comprises: The sensor adjustment submodule extracts the vibration frequency and amplitude adjustment parameters in the feedback signal based on the vibration control signal, performs numerical analysis, calculates the vibration adjustment ratio corresponding to the difference deviation range, and corrects the vibration parameters of the ankle and wrist sensors according to the adjustment ratio to obtain the vibration correction value; The action response monitoring submodule monitors the gait and swinging action after the feedback is triggered based on the vibration correction value, calculates the time difference from the triggering of the feedback signal to the action response, obtains the action offset before and after the adjustment, calculates the action offset amplitude and direction change angle, and generates the action offset index; The deviation trend analysis submodule compares the motion data before and after adjustment based on the motion deviation index, determines the magnitude of motion change after feedback, analyzes the motion feedback deviation trend curve, calculates the trend ratio of motion change, and generates training feedback results.

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