WTR pelvic floor rehabilitation training system based on myoelectricity pressure conduction electrode

Abstract

The invention discloses a WTR pelvic floor rehabilitation training system based on an electromyographic pressure conduction electrode, and relates to the technical field of big data analysis. Interaction between a user and the system is achieved through a man-machine interaction interface, and the system retrieves historical information of the user through a unique identifier; when historical information of the user exists in the database, the historical information is decrypted, the training completion degree and compliance are evaluated, if the historical information does not exist, a Probuf scheme file is analyzed, training parameters are extracted, the system guides the user to place an electrode, an electrical stimulation maximum tolerance value is obtained and adjusted to target pressure, warm-up parameters are calculated through an alternating genetic algorithm in combination with the historical data, and the training completion degree and compliance are evaluated. Performing warm-up training according to the parameters, wherein the scheme training can choose to skip a warm-up stage, if active training is included, the steps are executed step by step, after training is completed, the system adjusts warm-up parameters, judges whether a user is tired or not according to the matching degree of an electromyographic signal slope and a pressure template and reduces a pressure value, and the system encrypts training data and uploads the training data to a database. And the user manually ends the training.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and specifically to a WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes. Background Art

[0002] In the field of rehabilitation medicine, the existing technologies mainly have the following deficiencies: First, traditional electromyogram signal acquisition only relies on electrode patch detection, lacking synchronous collection of pelvic floor muscle pressure data, resulting in the inability to dynamically adjust according to the muscle pressure tolerance state during the warm-up stage; Traditional training modes mostly focus on electrostimulation therapy, lacking parameter regulation. During the warm-up stage, failure to dynamically adjust the stretching duration in combination with pressure data easily leads to insufficient muscle activation. In the relaxation stage, there is a lack of fatigue assessment of electromyogram signals and pressure templates, and the relaxation parameters cannot be adjusted according to the muscle recovery state, increasing the risk of muscle fatigue; Third, the degree of personalization is insufficient. The overall plan is not fully considered the individual differences of patients, resulting in different recovery effects for different users. To address the above problems, the present invention proposes a WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes, which realizes synchronous acquisition of electromyogram signals and pressure data by integrating electromyogram acquisition electrodes and micro pressure sensors, designs a three-stage closed-loop training mode of "warm-up - training - relaxation", and dynamically adjusts the parameters of each stage in combination with individual differences, so as to improve the accuracy, systematicness and personalization of rehabilitation training, and provide a more scientific and efficient rehabilitation plan for patients with pelvic floor dysfunction. Summary of the Invention

[0003] The purpose of the present invention is to provide a WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes to solve the problems raised in the existing technologies.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes, the intelligent management system includes the following modules: The human-computer interaction module is used for the user to independently select whether to start the system through the human-computer interaction interface. After the user selects to start, the system retrieves the user's personal historical information based on the user's unique identifier; The human-computer interaction module includes a visualization unit and a retrieval unit; The visualization unit is used for the user to select whether to start the system through the human-computer interaction interface; The retrieval unit is used for the system to retrieve the user's historical information in the database according to the user's unique identifier ID and obtain the user's historical information.

[0005] The decryption module is used to check whether user historical information exists in the system verification database. If the user historical information exists in the database, the user historical information is decrypted, and the training plan in the user historical information is extracted. The system calculates the matching degree of the training plan in the user historical information for the user through statistical analysis. If not, professionals evaluate and customize the user information to provide a training plan; The decryption module includes a data decryption unit and a plan analysis unit; The decryption unit is used to complete the data decryption operation through base64 decoding, AES decryption, and MD5 signature verification if user historical information exists in the database; The plan analysis unit is used to directly jump to the current plan acquisition if user historical information does not exist in the database. By parsing the historical training records, the matching degree between the training plan and the user information is calculated. The calculation formula is: ; In the formula, r xy represents the matching degree between the training plan and the user information, S xy represents the sample covariance, represents the sample standard deviation of x, represents the sample standard deviation of y; ; In the formula, S xy represents the sample covariance, x i and y i represent the i-th observation value in the sample data, μ x and μ y represent the means of x and y respectively, and n represents the number of sample data; ; In the formula, represents the sample standard deviation, μ is the average value calculated from the sequence array, x1, x2,..., x n is each number in the selected sequence array, and n is the number of data in the sequence array.

[0006] The calculation module is used to parse the training plan in Protobuf format and guide the user to execute the training plan based on the training parameters. The Protobuf format plan file is provided by professionals evaluating and customizing the user information to provide a training plan; The calculation module includes a training parameter parsing unit and a Protobuf file parsing unit; The training parameter parsing unit is used to calculate the training completion degree by statistically analyzing the compliance of the actual training duration and times with the pre-designed plan if historical information exists; The Protobuf file parsing unit is used to parse the training record file in Protobuf format to obtain the magnitude of the electrical stimulation current and the Kegel template parameters; The parsed parameters are passed to the training module, which collaborates with the pressure regulation and electrical stimulation unit to execute the training mode of the current stage. Through the regulation of multi-dimensional parameters, the system can accurately control the training of users; The training plan customized according to the user's own situation realizes the personalized training of the system.

[0007] The training module is used for the system to obtain the maximum tolerance value and target pressure value of the user for electrical stimulation, and then adjusts the warm-up training parameters to perform warm-up training. After that, it starts the training task of the current stage of the original plan and judges whether the training is completed; The training module includes a warm-up training parameter acquisition unit, a warm-up training parameter adjustment unit, a warm-up training unit, a training judgment unit, and a plan training unit; The warm-up training parameter acquisition unit is used for the system to guide the user to correctly place the electromyogram pressure conduction electrodes and adjust the body position, and at the same time prompts the user to operate through the visualization unit; Set the basic unit of inflation pressure as x, and increase the pressure in units of x through electrode inflation to obtain the maximum tolerable pressure P without pain for the user MAX , the maximum tolerable pressure P without pain for the user MAX is dynamically determined based on the user's subjective feedback; Release the pressure to the target pressure value P X , P X Press P MAX is set according to a reasonable ratio P_RATE of P.

[0008] The warm-up training parameter adjustment unit sets the pressure change amplitude [P X , P MAX according to the user's maximum tolerable pressure and target pressure value, and sets the pressure change amplitude as P; Set the pressure change rate as v, with the range from the historical average rate to the maximum safety threshold of the electromyogram pressure conduction electrode. When there is no historical data, the average rate is taken as 10% of the safety threshold; Set the stretching training duration as t. When there is historical data, the range is between the historical average duration and the longest historical duration. If the proportion of fatigue data in the historical data exceeds the threshold, which is set by professionals, the stretching duration is increased by 1 minute. When there is no historical data, the fixed time is 5 minutes; Generate three individual parameters according to the parameter range, specifically: Individual 1 = [P min , v min , t min ; Individual 2 = [P max , v max , t max ; Individual 3 = [P avg , v avg , t avg ; Wherein, P represents the amplitude of pressure change, v represents the rate of pressure change, and t represents the duration of stretching training; P min , v min , t min are respectively the minimum values of the amplitude of pressure change, the rate of pressure change, and the duration of stretching training, P max , v max , t max are respectively the maximum values of the amplitude of pressure change, the rate of pressure change, and the duration of stretching training, P avg , v avg , t avg are respectively the average values of the amplitude of pressure change, the rate of pressure change, and the duration of stretching training; The current parameters are calculated using the alternating genetic method, specifically: ; ; ; Wherein, weight represents the weight ratio, ranging from [0.3, 0.7], p1 is the adjusted amplitude of pressure change, v1 is the adjusted rate of pressure change, and t1 is the adjusted duration of stretching training; The warm-up training unit is started according to the parameters adjusted by the warm-up training parameter adjustment unit, performs periodic pressure stretching massage on the pelvic floor muscles, detects the muscle activation state, and through multi-dimensional parameter analysis, realizes the personalized relaxation of the system for different users' relaxation training, enabling users to obtain better recovery and preventing muscle damage to users.

[0009] The training judgment unit judges whether the training is completed according to the training end condition judgment scheme. If it is completed, it enters the relaxation module. If it is not completed, it judges whether the next stage of training in the scheme training includes active training. If it does not include active training, it continues to jump to the current stage to continue training. If it includes active training, it continues to execute the training module; The scheme training unit is used to perform training according to the training scheme obtained by analyzing the Protobuf file after the user completes the warm-up training. The scheme training includes active training and passive training, and the active training and passive training are trained in stages in chronological order.

[0010] The training compensation module is used to judge the next stage of training task and compensate the training task when it is judged that the training task is not completed; The training compensation module includes an active training judgment unit; The active training judgment unit is used to ask the user whether to skip the warm-up through the man-machine interface if the next stage includes active training; If the user chooses to skip, directly enter the scenario training unit in the training module. If the user chooses not to skip, an additional warm-up stretching training will be added, and after activating the muscles, return to the training module.

[0011] The relaxation module is used to, after the user completes the training, the system adjusts the warm-up training parameters according to the user's training results, and then generates a relaxation training plan according to the adjusted warm-up training parameters. After the relaxation training is completed, the system uploads the data during this training process to the database, and then the user ends the training through the man-machine interface.

[0012] The relaxation module includes a warm-up parameter adjustment unit and a data upload unit; The warm-up parameter adjustment unit is used to adjust the warm-up parameters. Specifically, referring to the warm-up parameter adjustment logic, the stretching duration is additionally increased by 1 minute to adapt to the muscle recovery needs after training; Start the warm-up training unit to perform periodic stretching massage, and monitor the recovery status through the fatigue recognition algorithm; Extract the electromyogram signals collected during the warm-up training process and calculate their average value V avg , analyze the rising slope Tup during the contraction phase. Tup is obtained by fitting the slope every 0.1 second within 0.5 seconds through a fitting equation, and the calculation process is as follows; Define the X array as [0, 1, 2, 3, 4,], where the array corresponds to the indexes of five samplings, and the Y array is the electromyogram signal intensity data of 5 samplings. Calculate the average value of the X array x , calculate the average value of the Y array y , calculate the mean cross product sum crossSum, and the calculation formula is: ; In the formula, X i is the i-th number of the X array, Y i is the i-th number of the Y array, μ X is the average value of the X array, μ y is the average value of the Y array; Loop N times and calculate the sum of squares of deviations from the mean squareSum of the X array. The formula is: ; In the formula, X i is the i-th number of the X array, μ X is the average value of the X array, and the slope is crossSum divided by squareSum; During the pressure stretching process, the amplitude of the output pressure change and the stretching time can form a graph, denoted as the template value template for the relaxation stage; Set the threshold angle_max for the rising slope of the electromyogram signal and the threshold r_max for the matching degree between the pressure signal and the template; When Tup < angle_max and the matching degree r xy < r_max, it is determined as fatigue, and the maximum tolerance value obtained by the warm-up training parameter acquisition unit is used to reduce the pressure by a ratio of 10% - 20%.

[0013] The data uploading unit is used to integrate training parameters, electromyogram signals, and user feedback data, and upload them to the database according to the user's unique identifier through the SSL / TLS encryption protocol; The user manually clicks to trigger the end operation through the visualization unit to complete the current training process.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. By adopting the electromyogram pressure conduction electrode, the present invention integrates the electromyogram acquisition electrode sheet and the micro pressure sensor to realize the synchronous and accurate acquisition of pelvic floor electromyogram signals and pressure data, providing comprehensive and reliable data support for the formulation of personalized rehabilitation training programs.

[0015] 2. The present invention proposes a three-stage training mode of WTR (Warm-up - Training - Relaxation). In the warm-up stage, the pressure stretching mode is adopted to activate the muscles and reduce the risk of training injuries; in the training stage, a personalized program is formulated based on accurate data, and the training enthusiasm is enhanced by combining gamification interaction; in the relaxation stage, the pressure stretching mode is used again in combination with vibration massage to accelerate muscle recovery. A complete training closed-loop is formed to ensure the scientific and efficient training process and improve the overall effect of rehabilitation training.

[0016] 3. By dynamically adjusting the parameters of each stage of the WTR training mode according to the individual differences of users, whether it is the pressure stretching intensity in the warm-up stage, the intensity and rhythm in the training stage, or the duration in the relaxation stage, etc., it can accurately adapt to the user's needs, realize personalized rehabilitation training in the true sense, maximize the rehabilitation effect, and meet the rehabilitation needs of different users. Brief Description of the Drawings

[0017] Figure 1 It is a schematic flow diagram of the WTR pelvic floor rehabilitation training system based on the electromyogram pressure conduction electrode of the present invention; Figure 2 It is a schematic structural diagram of the WTR pelvic floor rehabilitation training system based on the electromyogram pressure conduction electrode of the present invention. Detailed Embodiments

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0019] Embodiment: As Figure 1 - Figure 2 shown, the present invention provides a technical solution.

[0020] A WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes, the system includes the following steps: The human-computer interaction module is used for the user to independently select whether to start the system through the human-computer interaction interface. When the user selects to start, the system retrieves the user's personal historical information based on the user's unique identifier; The human-computer interaction module includes a visualization unit and a retrieval unit; The visualization unit is used for the user to select whether to start the system through the human-computer interaction interface; The retrieval unit is used for the system to retrieve the user's historical information in the database according to the user's unique identifier ID and obtain the user's historical information.

[0021] The decryption module is used for the system to verify whether there is user historical information in the database. If there is user historical information in the database, the user historical information is decrypted, and the training plan in the user historical information is extracted. The system calculates the matching degree of the training plan in the user historical information for the user through statistical analysis. If not, professionals evaluate and customize the user information to provide a training plan; The decryption module includes a data decryption unit and a plan analysis unit; The decryption unit is used for if there is user historical information in the database, to complete the data decryption operation through base64 decoding, AES decryption and MD5 signature verification; The plan analysis unit is used for if there is no user historical information in the database, to directly jump to the current plan acquisition, to calculate the matching degree between the training plan and the user information by parsing the historical training records. The calculation formula is:

[0022] In the formula, r xy represents the matching degree between the training plan and the user information, S xy represents the sample covariance, represents the sample standard deviation of x, represents the sample standard deviation of y;

[0023] In the formula, S xy represents the sample covariance, x i and y i represent the i-th observation value in the sample data, μ x and μ y represent the means of x and y respectively, and n represents the number of sample data;

[0024] In the formula, represents the sample standard deviation, μ is the average value calculated for the sequence array, x1, x2,..., x n are each number of the selected sequence array, and n is the number of data in the sequence array.

[0025] The calculation module is used to parse the training plan in Protobuf format, and based on the training parameters, guide the user to execute the training plan. The Protobuf format plan file is provided by professionals who evaluate the user information to customize the training plan; The calculation module includes a training parameter parsing unit and a Protobuf file parsing unit; The training parameter parsing unit is used to calculate the training completion degree by statistically analyzing the compliance of the actual training duration and times with the pre-designed plan if historical information exists; The Protobuf file parsing unit is used to parse the training record file in Protobuf format to obtain the magnitude of the electrical stimulation current and the Kegel template parameters; Transmit the parsed parameters to the training module, and cooperate with the pressure regulation and electrical stimulation unit to execute the current stage training mode. Through the regulation of multi-dimensional parameters, the system realizes precise control of the user's training; The training plan customized according to the user's own situation realizes the personalized training of the system.

[0026] The training module is used for the system to obtain the maximum tolerance value of the user to electrical stimulation and the target pressure value, then adjust the warm-up training parameters to conduct warm-up training, and then start the training task of the current stage of the original plan to determine whether the training is completed; The training module includes a warm-up training parameter acquisition unit, a warm-up training parameter adjustment unit, a warm-up training unit, a training judgment unit, and a plan training unit; The warm-up training parameter acquisition unit is used for the system to guide the user to correctly place the electromyogram pressure conduction electrode and adjust the body position, and at the same time prompt the user to operate through the visualization unit; Set the basic unit x of the inflation pressure, increase the pressure in units of x through electrode inflation, and obtain the maximum tolerable pressure P without pain for the user MAX at which the user has no pain, the maximum tolerable pressure P without pain for the userMAX Dynamically determined based on subjective user feedback; Release the pressure to the target pressure value P X , P X Set according to the reasonable ratio P_RATE of P MAX .

[0027] The warm-up training parameter adjustment unit sets the pressure change amplitude [P X , P MAX based on the user's maximum tolerable pressure and the target pressure value, and sets the pressure change amplitude to P; Set the pressure change rate to v, with the range from the historical average rate to the maximum safety threshold of the electromyogram pressure conduction electrode. When there is no historical data, the average rate is taken as 10% of the safety threshold; Set the stretching training duration to t. When there is historical data, the range is between the historical average duration and the longest historical duration. If the proportion of fatigue data in the historical data exceeds the threshold (set by professionals), the stretching duration is increased by 1 minute. When there is no historical data, the fixed time is 5 minutes; Generate three individual parameters according to the parameter range, specifically: Individual 1 = [P min , v min , t min ; Individual 2 = [P max , v max , t max ; Individual 3 = [P avg , v avg , t avg ; In the formula, P represents the pressure change amplitude, v represents the pressure change rate, and t represents the stretching training duration; P min , v min , t min are respectively the minimum values of the pressure change amplitude, pressure change rate, and stretching training duration, P max , v max , t max are respectively the maximum values of the pressure change amplitude, pressure change rate, and stretching training duration, P avg , v avg , t avg are respectively the average values of the pressure change amplitude, pressure change rate, and stretching training duration; Calculate the current parameters using the alternating genetic method, specifically: ; ; ; In the formula, weight represents the weight ratio, with a range of [0.3, 0.7], p1 is the adjusted pressure change amplitude, v1 is the adjusted pressure change rate, and t1 is the adjusted stretching training duration; The warm-up training unit is started according to the parameters adjusted by the warm-up training parameter adjustment unit, performs periodic pressure stretching massage on the pelvic floor muscles, detects the muscle activation state, and through multi-dimensional parameter analysis, realizes the personalized relaxation of the relaxation training for different users by the system, enabling users to obtain better recovery and preventing muscle damage to users.

[0028] The training judgment unit judges whether the training is completed according to the training end condition judgment scheme. If it is completed, it enters the relaxation module. If it is not completed, it judges whether the next stage of training in the scheme training includes active training. If it does not include active training, it continues to jump to the current stage to continue training. If it includes active training, it continues to execute the training module; The scheme training unit is used to perform training according to the training scheme obtained by analyzing the Protobuf file after the user completes the warm-up training. The scheme training includes active training and passive training, and the active training and passive training are carried out in stages according to the time sequence.

[0029] The training compensation module is used to judge the next stage of training task when it is judged that the training task is not completed and compensate the training task; The training compensation module includes an active training judgment unit; The active training judgment unit is used to ask the user whether to skip the warm-up through the man-machine interaction interface if the next stage includes active training; If the user chooses to skip, it directly enters the scheme training unit in the training module. If the user chooses not to skip, an additional warm-up stretching training is added, and after activating the muscles, it returns to the training module.

[0030] The relaxation module is used to adjust the warm-up training parameters according to the user's training results after the user completes the training. Then, a relaxation training scheme is generated according to the adjusted warm-up training parameters. After the relaxation training is completed, the system uploads the data in the current training process to the database, and then the user ends the training through the man-machine interaction interface.

[0031] The relaxation module includes a warm-up parameter adjustment unit and a data upload unit; The warm-up parameter adjustment unit is used to adjust the warm-up parameters. Specifically, referring to the warm-up parameter adjustment logic, the stretching duration is additionally increased by 1 minute to adapt to the muscle recovery needs after training; Start the warm-up training unit to perform periodic stretching massage, and monitor the recovery state through the fatigue recognition algorithm; Extract the electromyogram signals collected during the warm-up training process and calculate their average value Vavg Analyze the rising slope Tup during the contraction phase. Tup is obtained by fitting through the slope every 0.1 second within 0.5 seconds, and the calculation process is as follows: Define the X array as [0, 1, 2, 3, 4,], where the array corresponds to the indices of five samplings. The Y array is the myoelectric signal intensity data of five samplings, and calculate the average value of the X array. x Calculate the average value of the Y array. y Calculate the mean cross product sum crossSum, and the calculation formula is:

[0032] In the formula, X i is the i-th number of the X array, Y i is the i-th number of the Y array, μ X is the average value of the X array, μ y is the average value of the Y array; Loop N times to calculate the sum of squared deviations from the mean squareSum of the X array. The formula is:

[0033] In the formula, X i is the i-th number of the X array, μ X is the average value of the X array, and the slope is crossSum divided by squareSum; During the pressure stretching process, the output pressure change amplitude and stretching time can form a chart, denoted as the template value template of the relaxation phase; Set the myoelectric signal rising slope threshold angle_max and the pressure signal and template matching degree threshold r_max; When Tup < angle_max and the matching degree r xy < r_max, it is determined as fatigue, and the maximum tolerance value obtained by the warm-up training parameter acquisition unit is used to reduce the pressure by a ratio of 10% - 20%.

[0034] The data upload unit is used to integrate training parameters, myoelectric signals, and user feedback data, and upload them to the database according to the user's unique identifier through the SSL / TLS encryption protocol; The user manually clicks to trigger the end operation through the visualization unit to complete the current training process.

[0035] WTR Pelvic Floor Rehabilitation Training System Based on Myoelectric Pressure Conduction Electrodes The user starts the system through the man-machine interface, queries the database according to the user ID, and confirms that there is no historical information.

[0036] Since there is no historical information, the solution analysis unit parses the Protobuf format solution file provided by professionals according to the user's own situation, extracts training parameters, and calculates the matching degree; Suppose the user information data X = [80, 85, 90], representing the basic pelvic floor muscle strength, and the solution parameter Y = [75, 80, 85], representing the preset training intensity. The average value of the basic pelvic floor muscle strength is obtained as 85, and the preset training intensity is 80. The sample covariance is calculated as 25, the sample standard deviation of the basic pelvic floor muscle strength is 5, and the sample standard deviation of the preset training intensity is 25. The matching degree is obtained as 1, and it is determined to be highly compliant; Obtain the maximum tolerance P according to the inflation method max = 60, the target pressure P x = 48, the pressure change amplitude = [48, 60], the minimum value = 48, the maximum value = 60, the average value = 54, and there is no historical data for the pressure change rate v. Take 10% of the safety threshold, then v min = 1, v max = 10, v avg = 5.5, set the stretching duration t = 5 min, then t min = t max = t avg = 5. Using the alternating genetic algorithm, P1 = 54, v1 = 5.5, and t1 = 5 min are obtained. The system is started for massage according to the parameters [54, 5.5, 5], and the muscle activation state is detected.

[0037] After the warm-up is completed, the solution training unit executes the electrical stimulation and Kegel training tasks in the Protobuf file. After the training is completed, if the system determines that the current stage is not completed and the next stage includes active training, the user is asked through the human-computer interaction interface whether to skip the warm-up. If the user chooses not to skip, the system adds an additional warm-up training and then continues to execute the solution; Set the stretching duration to increase by 1 min, t = 6 min, start the periodic stretching massage, monitor the electromyogram signal, collect the electromyogram signal intensity Y = [10, 20, 30, 40, 50] five times, corresponding to X = [0, 1, 2, 3, 4], and calculate the rising slope Tup. x = 2, y = 30, the mean cross product sum = 100, the sum of squares of deviations from the mean = 10, the slope Tup = 10, set angle max = 15, r max = 0.8. At this time, Tup = 10 < 15, it is determined that the muscle is not fatigued, there is no need to lower the pressure, the training data is integrated and uploaded, and the user clicks the system to complete the training.

[0038] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-described exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, in any regard, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Thus, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. The WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes is characterized in that: The WTR pelvic floor rehabilitation training system includes a human-computer interaction module, a decryption module, a calculation module, a training module, a training compensation module, and a relaxation module; The human-computer interaction module is used for the user to independently select whether to start the system through the human-computer interaction interface. After the user selects to start, the system retrieves the user's personal historical information based on the user's unique identifier; The decryption module is used to check whether the user's historical information exists in the system database. If the user's historical information exists in the database, the decryption module decrypts the user's historical information, extracts the training plan in the user's historical information, and the system calculates the matching degree of the training plan in the user's historical information for the user through statistical analysis. If it does not exist, a professional will evaluate and customize the user information to provide a training plan; The calculation module is used to parse the training plan in Protobuf format and guide the user to execute the training plan based on the training parameters. The Protobuf format plan file is provided by a professional who evaluates and customizes the user information to provide a training plan; The training module is used for the system to obtain the user's maximum tolerance value for electrical stimulation and the target pressure value, then adjust the warm-up training parameters to perform warm-up training, and then start the training task of the current stage of the original plan to determine whether the training is completed; The training compensation module is used to judge the next stage of the training task and compensate the training task when it is judged that the training task is not completed; The relaxation module is used after the user completes the training. The system adjusts the warm-up training parameters according to the user's training results, and then generates a relaxation training plan according to the adjusted warm-up training parameters. After the relaxation training is completed, the system uploads the data during this training process to the database, and then the user ends the training through the human-computer interaction interface.

2. The WTR pelvic floor rehabilitation training system based on the electromyogram pressure conduction electrode according to claim 1, wherein: The human-computer interaction module includes a visualization unit and a retrieval unit; The visualization unit is used for the user to select whether to start the system through the human-computer interaction interface; The retrieval unit is used for the system to retrieve the user's historical information in the database according to the user's unique identifier ID and obtain the user's historical information.

3. The WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes according to claim 1, characterized in that: The decryption module includes a data decryption unit and a plan analysis unit; The data decryption unit is used to complete the data decryption operation through base64 decoding, AES decryption, and MD5 signature verification if the user's historical information exists in the database; The plan analysis unit is used to directly jump to the current plan acquisition if the user's historical information does not exist in the database. By parsing the historical training records, the matching degree between the training plan and the user information is calculated. The calculation formula is: ； where r xy represents the matching degree between the training scheme and the user information, S xy represents the sample covariance, represents the sample standard deviation of x, represents the sample standard deviation of y; ； Where S xy represents the sample covariance, x i and y i represent the i-th observation in the sample data, μ x and μ y represent the means of x and y respectively, and n represents the number of sample data; ； In the formula, represents the sample standard deviation, μ is the average value calculated from the sequence array, and x1, x2, …, x n are each number of the selected sequence array, and n is the number of data in the sequence array.

4. The WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes according to claim 1, wherein: The calculation module includes a training parameter parsing unit and a Protobuf file parsing unit; The training parameter parsing unit is used to calculate the training completion degree by statistically analyzing the compliance of the actual training duration and times with the pre-designed plan if historical information exists; The Protobuf file parsing unit is used to parse the Protobuf format training record file to obtain the electrical stimulation current magnitude and Kegel template parameters; Transfer the parsed parameters to the training module, and cooperate with the pressure regulation and electrical stimulation unit to execute the current stage training mode.

5. The WTR pelvic floor rehabilitation training system based on electromyographic pressure conduction electrodes according to claim 1, wherein: The training module includes a warm-up training parameter acquisition unit, a warm-up training parameter adjustment unit, a warm-up training unit, a training judgment unit, and a program training unit; The warm-up training parameter acquisition unit is used to guide the user to correctly place the electromyogram pressure conduction electrode and adjust the body position, and at the same time prompt the user to operate through the visualization unit; Set the basic unit x of the inflation pressure, inflate through the electrode to increase the pressure in units of x, and obtain the maximum tolerable pressure P without pain for the user MAX , the maximum tolerable pressure P without pain for the user MAX is dynamically determined based on the user's subjective feedback; Release the pressure to the target pressure value P X , P X Set according to the reasonable ratio P_RATE of P MAX .

6. The WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes according to claim 5, characterized in that ； The warm-up training parameter adjustment unit sets the pressure change amplitude [P according to the user's maximum tolerable pressure and the target pressure value X , P MAX , and sets the pressure change amplitude to P; Set the pressure change rate as v, and the range is from the historical average rate to the maximum safety threshold of the electromyogram pressure conduction electrode. When there is no historical data, the average rate is taken as 10% of the safety threshold; Set the stretching training duration as t. When there is historical data, the range is between the historical average duration and the longest historical duration. If the proportion of fatigue data in the historical data exceeds the threshold, the threshold is set by professionals, and the stretching duration is increased by 1 minute. When there is no historical data, the fixed time is 5 minutes; Generate three individual parameters according to the parameter range, specifically: Individual 1 = [P min , v min , t min ; Individual 2 = [P max , v max , t max ; Individual 3 = [P avg , v avg , t avg ; Wherein, P represents the amplitude of pressure change, v represents the rate of pressure change, and t represents the duration of stretching training; P min , v min , t min are respectively the minimum values of the amplitude of pressure change, the rate of pressure change, and the duration of stretching training, P max , v max , t max are respectively the maximum values of the amplitude of pressure change, the rate of pressure change, and the duration of stretching training, P avg , v avg , t avg are respectively the average values of the amplitude of pressure change, the rate of pressure change, and the duration of stretching training; Calculate the current parameters using the alternating genetic method, specifically: ； ； ； In the formula, weight represents the weight ratio, and the range is [0.3, 0.7]. p1 is the adjusted pressure change amplitude, v1 is the adjusted pressure change rate, and t1 is the adjusted stretching training duration; The warm-up training unit is started according to the parameters adjusted by the warm-up training parameter adjustment unit, and performs periodic pressure stretching massage on the pelvic floor muscles to detect the muscle activation state.

7. The WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes according to claim 5, wherein ； The training judgment unit judges whether the program training is completed according to the training end condition. If completed, it enters the relaxation module. If not completed, it judges whether the next stage of the program training includes active training. If it does not include active training, it continues to jump to the current stage for training. If it includes active training, it continues to execute the training module; The program training unit is used to perform training according to the training program obtained by analyzing the Protobuf file after the user completes the warm-up training. The program training includes active training and passive training, and the active training and passive training are trained in stages according to the time sequence.

8. The WTR pelvic floor rehabilitation training system based on the electromyogram pressure conduction electrode according to claim 1, wherein: The training compensation module includes an active training judgment unit; The active training judgment unit is used to ask the user whether to skip the warm-up if the next stage includes active training through the man-machine interaction interface; If the user chooses to skip, it directly enters the program training unit in the training module. If the user chooses not to skip, an additional warm-up stretching training is added, and after activating the muscles, it returns to the training module.

9. The WTR pelvic floor rehabilitation training system based on electromyographic pressure conduction electrodes according to claim 1, wherein: The relaxation module includes a warm-up parameter adjustment unit and a data upload unit; The warm-up parameter adjustment unit is used to adjust the warm-up parameters, specifically referring to the warm-up parameter adjustment logic, and additionally increasing the stretching duration by 1 minute to adapt to the muscle recovery requirements after training; Start the warm-up training unit to perform periodic stretching massage, and monitor the recovery status through the fatigue recognition algorithm; Extract the EMG signals collected during the warm-up training and calculate their average value V avg , analyze the rising slope Tup during the contraction phase. Tup is obtained by fitting the slope every 0.1 second within 0.5 seconds through a fitting equation. The calculation process is as follows; Define the X array as [0, 1, 2, 3, 4,], which corresponds to the indices of five samplings, and the Y array as the EMG signal intensity data of five samplings, and calculate the average value of the X array x , calculate the average value of the Y array y , calculate the mean cross product sum crossSum, and the calculation formula is: ； where X i is the i-th number of the X array, Y i is the i-th number of the Y array, μ X is the average value of the X array, μ y is the average value of the Y array; Loop N times, calculate the sum of squares of deviations from the mean squareSum of the X array, and the formula is: ； where X i is the i-th number of the X array, and μ X is the average value of the X array, and the slope is crossSum divided by squareSum; During the pressure stretching process, the output pressure change amplitude and stretching time can form a chart, which is recorded as the template value template in the relaxation stage; Set the threshold angle_max of the rising slope of the electromyogram signal and the threshold r_max of the matching degree between the pressure signal and the template; When Tup < angle_max and the matching degree r xy < r_max, it is determined to be fatigued, and the pressure is decreased by 10% - 20% according to the maximum tolerance value obtained by the warm-up training parameter acquisition unit.

10. The WTR pelvic floor rehabilitation training system based on electromyogram pressure conduction electrodes according to claim 9, wherein: The data upload unit is used to integrate training parameters, EMG signals, and user feedback data, and upload them to the database according to the user's unique identifier through the SSL / TLS encryption protocol; The user manually clicks through the visualization unit to trigger the end operation and complete the current training process.

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