Wearable tactile feedback device for badminton training

Abstract

The invention relates to the technical field of tactile feedback, in particular to a wearable tactile feedback device for badminton training, which comprises a motion parameter extraction module, an action analysis module, a time sequence comparison module, a tactile signal generation module and a feedback execution module. According to the invention, through gaits and racket swinging actions captured by wrist and ankle sensors, the ability of capturing action details of athletes is significantly improved, and different from a conventional tactile feedback technology, the scheme enables the athletes to accurately grasp core parameters of actions such as step length, speed and angle through real-time data capture; the control ability of exercise details is improved, through deep analysis of data, an athlete can obtain direct feedback about action optimization in real time, rapid adjustment is carried out to achieve ideal exercise performance, the individuation and adaptability of exercise training are effectively enhanced, and the exercise training efficiency is improved. And it is ensured that the training scheme of each athlete can accurately meet the actual performance and improvement requirements of the athlete.

Description

Technical Field

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

[0002] The field of tactile feedback training technology includes tactile feedback technology used in various educational and training environments. This technology simulates real tactile sensations to enhance the interactive experience in virtual environments. The core content involves tactile sensors, tactile feedback devices, and corresponding control systems, which work together on users and 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, the wearable tactile feedback device for badminton training refers to a device designed specifically for badminton training. It directly acts on specific parts of the user's body through tactile feedback elements integrated in clothing or accessories, and provides real-time tactile feedback by detecting the user's movement posture and ball-bouncing action, thereby helping the user adjust and optimize sports skills. The device supports personalized training needs and helps beginners quickly master correct badminton sports skills.

[0004] The application of traditional technology in sports training, especially badminton training, is still insufficient, mainly manifested in the lack of real-time monitoring and personalized feedback on the details of sports movements. Traditional technology focuses more on basic tactile feedback and fails to go deep into the precise adjustment and optimization of sports movements. In addition, the ability of synchronized sports movements is weak and the effective time alignment between footwork and swing cannot be achieved. This limits the real-time and accuracy of training, affecting the targeted training and the rapid improvement of sports skills. Summary of the invention

[0005] In order to solve the problem that the existing technology lacks real-time monitoring and personalized feedback of sports action details, traditional technology focuses on basic tactile feedback, fails to go deep into the precise adjustment and optimization of sports actions, and is weak in the ability to synchronize sports actions, and fails to achieve effective time alignment between footwork and swing, which limits the real-time and accuracy of training, affects the targetedness of training and the rapid improvement of sports skills. The embodiment of the present invention provides a wearable tactile feedback device for badminton training. The technical solution is as follows: On the one hand, a wearable tactile feedback device for badminton training is provided, comprising: 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 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.

[0006] On the other hand, 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.

[0007] On the other hand, the motion parameter extraction module includes: 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.

[0008] On the other hand, the quantified action intensity and movement accuracy adopts the formula: ; Generate exercise intensity index; in, Represents the exercise intensity index. 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.

[0009] On the other hand, 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 key action nodes, and generates key action indicators.

[0010] On the other hand, the step length change rate is calculated using the formula: ; Determine whether there is abnormal fluctuation in the step rhythm and obtain the rhythm fluctuation index; 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 previous point in time.

[0011] On the other hand, 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.

[0012] On the other hand, the weighted deviation mean of the step length, speed and angle parameters is calculated using the formula: ; Evaluate the standard deviation and relative dispersion of the action, identify the key performance deviation points, and obtain the key deviation parameters; 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.

[0013] On the other hand, the tactile signal generating module includes: 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.

[0014] On the other hand, the feedback execution module includes: 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.

[0015] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least: The innovative solution captures the gait and swing of athletes through wrist and ankle sensors, significantly improving the ability to capture the details of athletes' movements. Different from conventional tactile feedback technology, the solution enables athletes to accurately grasp the core parameters of movements such as stride length, speed and angle through real-time data capture, improving the ability to control movement details. Through in-depth analysis of data, athletes can instantly obtain direct feedback on movement optimization and quickly adjust to achieve ideal athletic performance, effectively enhancing the personalization and adaptability of sports training, ensuring that each athlete's training plan can accurately match their actual performance and improvement needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a schematic diagram of the system of the present invention; Figure 2 It is a schematic diagram of the system framework of the present invention; Figure 3 It is a flow chart of the motion parameter extraction module of the present invention; Figure 4 It is a flow chart of the action analysis module of the present invention; Figure 5 It is a flow chart of the timing comparison module of the present invention; Figure 6 This is a flow chart of a tactile signal generating module of the present invention; Figure 7 It is a flow chart of the feedback execution module of the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0019] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0020] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0021] In the embodiments of the present invention, sometimes the subscripts such as W 1 It may be written in non-subscript form such as W1. When the difference is not emphasized, the meaning is the same.

[0022] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0023] The embodiment of the present invention provides a wearable tactile feedback device for badminton training, such as Figure 1 As shown, including: 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 and displacement vector changes in adjacent time periods, analyzes the acceleration and rotation angle of the swinging process, and synchronizes the gait and swinging motion trajectory data 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 value to determine the step length change rate in each time period, and extracts the acceleration peak and calculates the instantaneous angular velocity according to the speed and angle changes at the moment of hitting the ball in the swing action. It synchronizes the time axis of the footwork and the swing data, identifies the key action nodes, and obtains the key action indicators; The timing comparison module compares the key indicators of the action with the standard action template, calculates the time delay between the start of the step and the swing action, analyzes the matching degree between the step and the swing action, determines the action deviation type and time deviation data, and generates deviation analysis results; The tactile signal generation module calculates the time deviation between the step advance and the swing lag based on the deviation analysis results, sets the trigger frequency and amplitude of the vibration signal, adjusts the vibration frequency of the ankle sensor according to the abnormal step, and adjusts the vibration duration of the wrist sensor according to the swing deviation to generate a vibration control signal. The feedback execution module adjusts the vibration frequency and amplitude after sensor feedback based on the vibration control signal, and monitors the gait and swing movements after the feedback is triggered, compares the original movement offset and records the movement deviation before and after adjustment, analyzes the movement deviation trend, and generates training feedback results.

[0024] 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 the 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.

[0025] like Figure 2 and Figure 3 As shown, the motion parameter extraction module includes: 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; Wrist and ankle sensors collect the user's gait and swinging movements. Gait data includes information such as step length, step frequency, movement direction, and ground contact method. Swinging movement 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 movement step length, the difference in the coordinates of the sole contact points between two adjacent steps is calculated. For example, in a gait detection, the coordinates of the left foot contact point are (1.2, 3.4), and the coordinates of the right foot contact point are (2.5, 3.8). The step length is calculated as follows: , substituting the data, the step length is 1.39 meters. The moving direction is determined by calculating the vector angle. Assuming that the two consecutive displacement vectors in a certain movement cycle are (1.2, 0.8) and (1.4, 0.9), the direction angle is The calculated direction change angle is 4.2 degrees. The speed signal is calculated by dividing the displacement change in the time period by the time interval. For example, if the displacement changes by 1.2 meters in 0.5 seconds, the speed is 2.4 meters / second. The gait mode is determined based on all step lengths, moving directions, and speed signal data. If the step length is between 1.21.5 meters, the step frequency is between 1.52.0 steps / second, and the moving direction is stable, it is determined to be a normal gait. If the step length is less than 0.8 meters or the step frequency exceeds 2.5 steps / second, it is a running mode. Based on the swing action data, the acceleration and angular velocity change rate are calculated. By determining the acceleration characteristics of different swing modes, the swing mode is identified. For example, the acceleration peak of a fast swing reaches 15m / s2, while that of a slow swing is only 5m / s2. By comparing the swing rhythm parameters of different modes, the motion rhythm characteristics are generated.

[0026] The motion feature calculation submodule calculates the step increment and displacement vector changes in 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 a motion intensity index; To quantify the intensity and accuracy of movement, the formula is used: ; Generate exercise intensity index; in, Represents the exercise intensity index. 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; For badminton, the maximum acceleration can generally reach 50-60m / s². m / s², m / s², m / s², select a common hitting angle range, set °, °, °, the general athlete's footwork speed is between 1.5-3m / s, set m / s, m / s, m / s, using the arithmetic mean formula: ; Bring in known data: ; Represents the number of time frames in the calculation interval, set n=3 (sampling interval 100ms, 3 frames in total); Substitute the parameters into the formula for calculation; The first part calculates: the mean of the product of acceleration and rotation angle; ; Bring in parameters: ; The second part calculates: speed standard deviation; ; Bring in data: ; ; ; ; ; Finally, the exercise intensity index is calculated; ; Calculation results analysis The results show that the sports intensity index is 399.84, which reflects the changes in the mechanical strength of the athlete's footwork and swinging process within the set time frame. Combined with the acceleration, rotation angle and speed fluctuations, it explains the movement stability and strength matching of the movement mode. A higher value indicates that the movement is stronger and changes violently, while a lower value indicates that the movement is relatively stable or lacks strength.

[0027] The data synchronization submodule calculates the relative time offset between gait and 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.

[0028] Based on the motion intensity index, the relative time offset between gait and swing is calculated. The time offset is calculated by subtracting the gait start time from the swing start time. For example, if the gait start time is 1.2 seconds and the swing start time is 1.8 seconds, the time offset is 0.6 seconds. Align the timestamps of the motion trajectory data and adjust the timestamps of all data points to match the time axis. Assuming that the time axis interval is 0.1 seconds, if the gait data points are recorded at 1.2 seconds, 1.3 seconds, and 1.4 seconds, and the swing data points are recorded at 1.22 seconds, 1.32 seconds, and 1.42 seconds, then adjust the timestamps of the swing data points to 1.2 seconds, 1.3 seconds, and 1.4 seconds to ensure time matching. By calculating the time matching error, if the matching error is less than 0.05 seconds, the data alignment is judged to be successful, otherwise continue to adjust. The time synchronization matching is optimized through the cyclic matching algorithm to obtain the original motion data.

[0029] like Figure 2 and Figure 4 As shown, 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 the directional stability analysis results; Get the displacement coordinate points in the motion trajectory. Each motion sequence contains multiple coordinate points. Determine the stability of the motion direction by calculating the displacement coordinate change values ​​of adjacent time points. The calculation method is to subtract the coordinates of the previous time point from the current position coordinates. For example, a user's displacement coordinate point sequence is (3.0, 4.2), (3.8, 4.5), (4.6, 5.0). Calculate the adjacent coordinate change values. , we can get (0.8, 0.3) and (0.8, 0.5) by substituting the data, and calculate the rate of change of the direction of motion. If the current direction changes by an angle for , the calculated 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°, the movement direction is judged to be stable. If it is greater than 20°, the direction change is judged to be drastic, and the directional stability analysis result is generated.

[0030] 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; Calculate the step size change rate using the formula: ; Determine whether there is abnormal fluctuation in the step rhythm and obtain the rhythm fluctuation index; 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; Step Length The length of each step is measured by the pressure sensor. Assume that in a test, the device records the stride length data of 10 steps in meters, and the following data is obtained: , , , , , , , , , ; Time The timestamp corresponding to each step measurement is in seconds. Assume that the corresponding timestamp is: , , , , , , , , , ; Step Difference : Calculate the absolute difference between adjacent steps, for example: rice; rice; And so on, calculate all adjacent step length differences; Time interval : Calculate the time difference between adjacent time points, for example: Second; Second; And so on, calculate all adjacent time differences; Substitute the above data into the formula for calculation: Compute the sum of the step size differences: ; ; ; Compute the square root of the sum of the squares of the time intervals: ; ; ; Calculate the step change rate : ; This result shows that the step size change rate It is 0.00913 m / s, which means that during the test, the average rate of change of stride length is low and the gait rhythm is relatively stable.

[0031] The swing power calculation submodule 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 footwork data and the swing action on the timeline, identifies key action nodes, and generates key action indicators.

[0032] The speed is calculated by dividing the total length of the swing path by the swing time. For example, if the total length of the swing is 2.4 meters and the swing time is 0.8 seconds, the swing speed is 3.0 meters per second. The peak acceleration is calculated by dividing the speed increment by the time increment. For example, if the initial speed of the swing is 2.0 meters per second, the maximum speed is 4.5 meters per second, and the time change is 0.6 seconds, the peak acceleration is , substituting the data into the acceleration peak value of 4.17m / s2, the instantaneous angular velocity is calculated by dividing the angle change by the time increment. For example, the starting angle of the swing is 15°, the ending angle is 75°, and the time increment is 0.5 seconds, then the angular velocity is 120° / s. Compare the synchronization of the footwork data and the swing action on the time axis, and 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 the swing rhythm are unbalanced, and the key indicators of the action are generated.

[0033] like Figure 2 and Figure 5 As shown, the timing comparison module includes: The feature parameter comparison submodule compares the key indicators of the action with the standard action template based on the key indicators of the action, 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; Calculate the weighted deviation mean of the step size, speed, and angle parameters using the formula: ; Evaluate the standard deviation and relative dispersion of the action, identify the key performance deviation points, and obtain the key deviation parameters; 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; Record step length, speed, angle motion parameters through motion sensors , step length data is obtained from the inertial measurement unit, speed is calculated by the ratio of displacement change to time, and angle parameters are measured by the gyroscope. For example, a test sample contains the following measurement data: (step length, unit: meter); (speed, unit: m / s); (angle, unit: degree); Standard action template parameters How to obtain it; A standard template is established from raw training data, calculated from the average values ​​of professional athletes, for example: (step length, unit: meter); (speed, unit: m / s); (angle, unit: degree); Calculate the absolute deviation ; Calculate the deviation value of each parameter: m (step size deviation); m / s (speed deviation); Degree (angle deviation); The weight coefficient is determined based on the importance of the parameter. The importance of step length, speed, and angle varies. For example, step length has a greater impact on the overall movement rhythm, so a higher weight is set. The weights of speed and angle are relatively low: (step weight); (speed weight); (angle weight); Calculate the molecular part ; ; Calculate the denominator ; ; Calculate the weighted mean deviation ; ; The result shows that the weighted deviation mean is 0.585, indicating that there is a certain degree of deviation between the current action features and the standard template. The larger the deviation value, the more obvious the gap with the standard template. The result can be used to further optimize the action parameters to make it closer to the standard action and improve the overall action stability.

[0034] The time delay analysis submodule uses 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; Get the footwork start time and the swing start time. For example, if the footwork start time is 2.1 seconds and the swing start time is 2.8 seconds, the time interval between the two actions is calculated as follows: , substitute the data to get a time interval of 0.7 seconds, set a time delay reference value, for example, the reference value is 0.5 seconds, compare the deviation between the time interval and the reference value, and determine the offset direction of the time interval. If the time interval is greater than the reference value, the step start is delayed, otherwise the step start is advanced, and the time offset is calculated. If the calculated time offset is 0.2 seconds, the step start will be delayed by 0.2 seconds. If the offset is -0.3 seconds, the step start will be advanced by 0.3 seconds to generate the time offset.

[0035] 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 results.

[0036] The time deviation type is divided into the following classification methods: setting the time difference threshold, for example, setting the normal deviation range 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 as a gait start delay. If it is less than -0.2 seconds, it is judged as a gait start advance. The distribution frequency of time deviation in the action sequence is analyzed, and the number of occurrences of each category of time deviation is counted. For example, in 100 movement records, the number of gait lags is 30 times, the number of advances is 15 times, and the number of normal synchronizations is 55 times. The lag frequency is 30%, the advance frequency is 15%, and the normal frequency is 55%. The deviation analysis result is obtained.

[0037] like Figure 2 and Figure 6 As shown, the tactile signal generating module includes: The vibration amplitude adjustment submodule extracts the data of abnormal footwork and swing error based on the deviation analysis results, 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; Filter out abnormal footwork data points, including records of excessive step length changes, footwork direction deviations, and abnormal start-up times. At the same time, extract swing error data points, including swing angle deviations, swing speed fluctuations, and mismatched hitting timings. Calculate the vibration amplitude adjustment amount by multiplying the error deviation value by the vibration adjustment coefficient. For example, if 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 adjustment amount calculation formula is: , substituting the data into the value, the vibration amplitude adjustment amount is 0.75, the error level is determined, and multiple error ranges are set, for example, 0-0.2 seconds is a low error, 0.2-0.5 seconds is a medium error, and greater than 0.5 seconds is a 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. The corresponding vibration power is matched according to the error level to generate a vibration power adjustment value.

[0038] 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; Set the vibration triggering time. For example, the step adjustment delay threshold is 0.3 seconds. If the step error exceeds this threshold, the vibration triggering time 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 difference mode. The vibration duration is calculated by multiplying the error size 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 , the vibration duration is calculated to be 0.48 seconds. If the duration is less than 0.2 seconds, the minimum vibration time is set to 0.2 seconds. If it exceeds 1 second, the maximum vibration time is set to 1 second to obtain the vibration mode configuration.

[0039] The sensor signal distribution submodule extracts the vibration feedback direction of abnormal footwork based on the vibration pattern configuration, optimizes the signal strength at the wrist according to the swing error, adjusts the signal distribution of the wrist and ankle sensors, and obtains the vibration control signal.

[0040] Determine the main direction of the footwork deviation. For example, if the footwork deviates to the left by 0.3 meters, the vibration feedback direction is set to the right. If the footwork deviates forward beyond the set range, the vibration feedback direction is set to the back. Optimize the signal strength of the wrist for swing error and calculate the wrist vibration feedback signal strength. The calculation method is to multiply the error deviation angle by the signal adjustment coefficient. For example, if the error angle is 8° and the signal adjustment coefficient is set to 0.4, the signal strength is calculated as , substitute the data to calculate the signal strength of 3.2, adjust the signal distribution of the wrist and ankle sensors, and set the distribution ratio of the feedback signal. For example, the ankle signal accounts for 60% and the wrist signal accounts for 40%. If the step error is large, the ankle signal accounts for 70% to obtain the vibration control signal.

[0041] like Figure 2 and Figure 7 As shown, the feedback execution module includes: 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; Get vibration amplitude from vibration feedback data and vibration frequency , analyze the feedback signal strength under different action states, and calculate the vibration adjustment ratio corresponding to the difference deviation range. 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, the adjustment ratio calculation formula is: , substituting the data into the adjustment ratio of 1.5, the vibration parameters of the ankle and wrist sensors are corrected according to the adjustment ratio, and the correction formula is: , assuming that the current vibration amplitude is 2.0mm and the frequency is 50Hz, substitute the adjustment ratio to calculate the new vibration amplitude of 3.0mm and the frequency of 75Hz. Ensure that the corrected vibration parameters are within the allowable range. For example, set the amplitude range to 1.0mm to 4.0mm and the frequency range to 30Hz to 100Hz. If it exceeds the range, take the maximum or minimum value to get the vibration correction value.

[0042] 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; Collect the movement displacement of the wrist and ankle after vibration triggering, and calculate the time difference from the feedback signal triggering to the action response. The time difference is calculated by subtracting the vibration triggering time from the action response time. For example, if the vibration triggering time is 3.2 seconds and the action response time is 3.6 seconds, the time difference calculation formula is: , substituting the data into the time difference of 0.4 seconds, the action offset before and after adjustment is obtained, which is calculated by subtracting the displacement value before adjustment from the displacement value after adjustment. For example, if the displacement before adjustment is 0.8 meters and the displacement after adjustment is 1.1 meters, the displacement increment is 0.3 meters. The action offset amplitude is calculated using the formula: ,in are the displacement changes respectively, assuming rice, meters, the calculated deviation is 0.29 meters, and the direction change angle is calculated as follows: , substituting the data into the calculated angle change, it is 31.2°, generating the motion offset index.

[0043] The deviation trend analysis submodule compares the motion data before and after adjustment based on the motion offset 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.

[0044] The system extracts the offset change data within each time window to calculate the amplitude of the action change after feedback. Assume that the step offset data of the first five time windows are adjusted as follows: cm, adjusted cm, Then calculate the average change: ; in =5, substitute the data and calculate: ; ; At the same time, the system analyzes the action feedback deviation trend curve, calculates the trend ratio, and uses the trend change calculation formula: ; in, =5.0cm; ; The system records trend ratios and generates training feedback results.

[0045] It should be understood that the term "and / or" in this article is only 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 at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0046] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0047] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned 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 on the implementation process of the embodiments of the present invention.

[0048] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0049] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0050] In the 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0051] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0052] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0053] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0054] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A wearable tactile feedback device for badminton training, characterized in that: include: 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 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: ； Generate exercise intensity index; 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 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 key action nodes, and generates key action indicators.

6. The wearable tactile feedback device for badminton training according to claim 5, characterized in that: The step length change rate is calculated using the formula: ； Determine whether there is abnormal fluctuation in the step rhythm and obtain the rhythm fluctuation index; 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 previous point in time.

7. 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.

8. The wearable tactile feedback device for badminton training according to claim 7, characterized in that: The weighted deviation mean of the step length, speed and angle parameters is calculated using the formula: ； Evaluate the standard deviation and relative dispersion of the action, identify the key performance deviation points, and obtain the key deviation parameters; 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.

9. 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.

10. 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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