Spasticity suppression rehabilitation management system and method

Abstract

The application discloses a spasm inhibition rehabilitation management system and method, and relates to the field of rehabilitation treatment, and comprises the following: a distinguishing module, which is used for distinguishing the spasm position area of the patient's body, and controls a collecting module to collect myoelectric signals in each distinguished area based on the distinguishing result; the collecting module, which is used for collecting the myoelectric signals of the spasm position of the patient's body in real time; and an analog module, which is used for acquiring the myoelectric signal with the highest activity in the collecting module, and analogically outputting the corresponding electric field signal based on the acquired myoelectric signal with the highest activity. The application can accurately determine the position of the spasm of the patient's body, continuously collect the myoelectric signals generated by the spasm, analogically output the targeted electric field signal by analyzing the signals, generate the opposite electric field signal by using the mirror image technology, and then effectively inhibit the spasm of the patient and relieve the spasm symptoms.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rehabilitation treatment, in particular to a spasm suppression rehabilitation management system and method. BACKGROUND

[0002] Spasm suppression is crucial in the field of ankle spasm rehabilitation after stroke. It reduces muscle overexcitation, relieves ankle muscle spasm, improves joint mobility, improves patient motor function and quality of life, and prevents complications through physical therapy, rehabilitation training, and medication.

[0003] The application number 202411032852.9 discloses a method for predicting post-stroke limb spasm, which comprises: collecting static electroencephalogram data and static magnetic resonance imaging data of the subject in a resting state, and obtaining a resting state feature vector based on the static electroencephalogram data and the static magnetic resonance imaging data; collecting dynamic electroencephalogram data and dynamic electromyogram of the subject in a motion task state, and obtaining a task state feature vector according to the dynamic electroencephalogram data and the dynamic electromyogram; integrating and splicing the resting state feature vector and the task state feature vector, and obtaining a state score through a multilayer perceptron, and obtaining a prediction result of the subject through the state score. This application effectively solves the problem that the existing PSS evaluation and prediction method lacks objectivity and real-time, and cannot effectively reflect the actual spasm state and treatment needs of the patient. The limitations of these technologies not only affect the accurate guidance of patient recovery, but also may lead to unreasonable allocation of treatment resources.

[0004] However, the current spasm suppression technology is mainly based on drugs, and there are few physical suppression technologies that can be actually applied.

[0005] Therefore, a spasm suppression rehabilitation management system and method are proposed. SUMMARY

[0006] In view of the above shortcomings of the prior art, the present application provides a spasm suppression rehabilitation management system and method, which can effectively solve the problems of the prior art.

[0007] To achieve the above purpose, the present application is realized by the following technical scheme.

[0008] The present application discloses a spasm suppression rehabilitation management system, which comprises:

[0009] The distinguishing module is used for distinguishing the spasm position area of the patient's body, and the acquisition module is controlled to perform the acquisition of the electromyographic signal in each distinguished area based on the distinguishing result; the acquisition module is used for acquiring the electromyographic signal of the spasm position of the patient's body in real time; the simulation module is used for acquiring the electromyographic signal with the highest activity in the acquisition module, and simulating and outputting the corresponding electric field signal based on the acquired electromyographic signal with the highest activity; the mirror module is used for receiving the electric field signal output by the simulation module, mirroring the electric field signal to output the opposite electric field signal; the suppression module is used for receiving the opposite electric field signal output by the mirror module, generating the suppression logic based on the opposite electric field signal, and dynamically suppressing when the patient has the spasm based on the suppression logic; the evaluation module is used for acquiring the running information of the suppression module, and evaluating the rehabilitation situation of the patient's spasm based on the running information of the suppression module; and the message module is used for recording the historical running evaluation result of the evaluation module, and generating the evaluation result message based on the recorded evaluation result to feed back to the system user.

[0010] Further, the acquisition module is integrated by a sensor capable of sensing the electromyographic signal generated by the spasm, and a plurality of acquisition modules are arranged, and the plurality of acquisition modules are uniformly arranged on the surface of the spasm position of the patient's body when acquiring the electromyographic signal of the spasm position of the patient's body, and the acquisition module is arranged with a storage unit and an identification unit.

[0011] The storage unit is used for receiving the electromyographic signal acquired by the acquisition module, and storing the electromyographic signal, and the identification unit is used for traversing each electromyographic signal stored in the storage unit, and identifying the electromyographic signal with the highest activity in each electromyographic signal.

[0012] Further, the storage unit stores the electromyographic signal in the form of an electromyographic signal spectrum graph when storing the electromyographic signal, and the identification logic of the activity of the electromyographic signal in the identification unit is represented as:

[0013] ;

[0014] In the formula, A is the activity of the electromyographic signal; is the total amount of the sequence number of the amplitude in the electromyographic signal; is the amplitude corresponding to the i-th sequence number in the electromyographic signal; is the interval time between the amplitude corresponding to the i-th sequence number and the amplitude corresponding to the i+1-th sequence number in the electromyographic signal; is the deployment area defined based on the deployment result of the acquisition module; is the normalization factor;

[0015] wherein, the greater the value is, the higher the activity of the electromyographic signal is, and vice versa, represents the average of .​

[0016] Further, the acquisition module is used for continuously collecting the muscle spasm position electromyography signals of the patient when the time domain is customized by the system end user, and the initial default time domain is 24 hours;

[0017] The decision of whether the distinguishing module participates in the system operation is subject to the following condition: if the spasm area of the patient's body is greater than or equal to X, the distinguishing module participates in the system operation; if the spasm area of the patient's body is less than X, the distinguishing module does not participate in the system operation, wherein X is a decision threshold value preset by the system end user, the spasm position area of the patient's body is manually divided by the system end user, and each division area contains at least two acquisition modules; after the operation of the distinguishing module ends, the acquisition module takes each division area as a collection target to collect the electromyography signals; and when the distinguishing module participates in the system operation, the identification unit calculates the area of each division area at each time. The area of the corresponding division area is replaced.

[0018] Further, the initialization unit is arranged below the inhibition module, and is used for obtaining the opposite electric field signals received by the inhibition module, converting the opposite electric field signals into electromyography signals, and obtaining the maximum amplitude and the minimum amplitude in the converted electromyography signals to determine the amplitude interval of the electromyography signals.

[0019] Further, the inhibition logic in the inhibition module is as follows:

[0020] The electromyography signals generated by the deployment position of the acquisition module due to the spasm are obtained in real time, and the opposite number of the amplitude corresponding to the electromyography signals is obtained.

[0021] Whether the opposite number is in the amplitude interval is identified.

[0022] If the identification result is yes, the inhibition module generates vibration; and if the identification result is no, the system jumps to the running stage of the acquisition module and refreshes the running after the current spasm of the patient ends.

[0023] The inhibition module and the acquisition module are integrated, and are deployed synchronously at the surface deployment position of the user's body spasm position; the inhibition module is made of a material having a piezoelectric effect, and the material generates vibration based on the electric field signals corresponding to the opposite number of the amplitude corresponding to the electromyography signals.

[0024] Further, the running information of the inhibition module obtained by the evaluation module includes the running frequency of the inhibition module, the electric field signal intensity applied in the running stage of the inhibition module, and the number of times of jumping to the acquisition module based on the identification result of whether the opposite number is in the amplitude interval.

[0025] The evaluation logic of the rehabilitation situation of the patient's spasm problem is as follows:

[0026] ​ ;

[0027] wherein: is a patient spasticity problem rehabilitation state value; is a suppression module running frequency; is the number of times the system jumps to the acquisition module based on the identification result of whether the reciprocal is within the amplitude interval; is the latest electric field signal strength applied by the suppression module in the last run; is the maximum electric field signal strength applied by the suppression module in the historical run; is a constraint function;

[0028] wherein, the greater the value, the better the patient spasticity problem rehabilitation effect, and in the constraint function, when the value of is equal to , when the value of is greater than zero, .

[0029] Further, the evaluation module is continuously run to continuously output a patient spasticity problem rehabilitation state value, denoted as ;

[0030] The evaluation result message content generated by the message module is ;

[0031] wherein, the system end user evaluates the spasticity problem rehabilitation effect by observing the changes in the values of adjacent items in .

[0032] Further, the acquisition module is connected to a storage unit and an identification unit through a wireless network, the acquisition module and the identification module are connected to the acquisition module through a wireless network, the acquisition module is connected to a mirror module and a suppression module through a wireless network, the suppression module is connected to an initialization unit through a wireless network, and the suppression module is connected to an evaluation module and a message module through a wireless network.

[0033] In a second aspect, a spasticity suppression rehabilitation management method includes the following steps:

[0034] Identify the size of the spasm position area of the patient, decide whether to distinguish the spasm position area based on the size of the spasm position area, deploy the muscle electric signal generated by the spasm in the spasm position area, perceive the muscle electric signal in the spasm position area or each distinguished area of the spasm position area, obtain the perceived muscle electric signal, simulate the muscle electric signal as an electric field signal, mirror the simulated electric field signal as an opposite electric field signal, generate an inhibition logic according to the opposite electric field signal obtained by the simulation and the mirroring operation, inhibit the spasm dynamically when the patient generates the spasm based on the inhibition logic, obtain the information of the spasm dynamic inhibition process in real time, evaluate the rehabilitation situation of the spasm problem of the patient based on the obtained information, and generate a message based on the historical evaluation results.

[0035] Compared with the known prior art, the technical scheme provided by the present application has the following beneficial effects:

[0036] In the present application, the system can accurately determine the position of the spasm of the patient's body, continuously collect the muscle electric signal generated by the spasm, simulate and output the targeted electric field signal by analyzing these signals, generate the opposite electric field signal by using the mirroring technology, and then effectively inhibit the spasm when the patient generates the spasm, thereby relieving the spasm symptoms. At the same time, the system can also collect and analyze various key information in the inhibition process, such as the frequency of inhibition, the intensity of the electric field signal used, etc. According to the evaluation of the rehabilitation situation of the spasm problem of the patient, the patient and the medical staff can clearly understand the rehabilitation progress. Moreover, the system records the evaluation results and generates a message to feed back to the user. The user can intuitively evaluate the rehabilitation effect by observing the changes of the evaluation results, which provides a strong basis for the adjustment of the subsequent rehabilitation treatment plan, and greatly improves the scientificity and effectiveness of the spasm rehabilitation treatment. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical scheme in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creating any creative labor.

[0038] Figure 1 It is a structural schematic diagram of a spasm inhibition rehabilitation management system.

[0039] Figure 2 It is a flowchart of a spasm inhibition rehabilitation management method.

[0040] Figure 3 It is a form example schematic diagram of the connection between the prototype put into use based on the system designed in the present application and the patient. DETAILED DESCRIPTION

[0041] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0042] The present application will be further described below with reference to the embodiments. Embodiments

[0043] A spasm inhibition rehabilitation management system of the present embodiment, as shown in Figure 1 includes:

[0044] A distinguishing module for distinguishing spasm position areas of a patient's body, and controlling the acquisition module to perform acquisition of electromyographic signals in each distinguished area based on the distinguishing result;

[0045] An acquisition module for acquiring electromyographic signals at spasm positions of the patient's body in real time;

[0046] The acquisition module is integrated by sensors capable of sensing electromyographic signals generated by spasm. The acquisition module is provided with a plurality of acquisition modules, which are uniformly arranged on the surface of the spasm position of the patient's body when acquiring electromyographic signals at the spasm position of the patient's body. The acquisition module is provided with a storage unit and an identification unit at a lower level;

[0047] The storage unit is used to receive electromyographic signals acquired by the acquisition module and store the electromyographic signals. The identification unit is used to traverse each electromyographic signal stored in the storage unit and identify the electromyographic signal with the highest activity among the electromyographic signals;

[0048] When the storage unit stores the electromyographic signals, the electromyographic signals are stored in the form of electromyographic signal spectrograms. The identification logic of the activity of the electromyographic signals in the identification unit is represented as:

[0049] ;

[0050] In the formula: is the activity of the electromyographic signal; is the total amount of the sequence number of the amplitude in the electromyographic signal; is the amplitude corresponding to the i-th sequence number in the electromyographic signal; is the interval time between the amplitude corresponding to the i-th sequence number and the amplitude corresponding to the i+1-th sequence number in the electromyographic signal; is the deployment area defined based on the deployment result of the acquisition module; is a normalization factor;

[0051] wherein, The greater the value, the higher the activity of the electromyographic signal, and vice versa, the lower the activity of the electromyographic signal, representing the average of ;

[0052] The activity of the electromyographic signal is determined by the above logical formula, thereby providing data support for the simulation module of the system in this embodiment, and adapting the system to the patient;

[0053] The acquisition module continuously acquires the spastic position electromyographic signal of the patient by the system end user customizing the time domain. The initial default acquisition time domain is 24 hours;

[0054] The decision of whether the distinguishing module participates in the system operation is subject to the patient's body spastic area being greater than or equal to X, and the distinguishing module participates in the system operation when the patient's body spastic area is less than X. X is the decision threshold preset by the system end user. When the distinguishing module distinguishes the patient's body spastic position area, it is manually divided by the system end user, and each division area contains at least two acquisition modules. After the distinguishing module runs, the acquisition module takes each division area as the acquisition target to execute the electromyographic signal acquisition. When the distinguishing module participates in the system operation, the recognition unit calculates at each run by replacing the area of the corresponding division area;

[0055] The simulation module is used to obtain the electromyographic signal with the highest activity in the acquisition module, and simulate the output of the corresponding electric field signal based on the obtained electromyographic signal with the highest activity;

[0056] The mirror module is used to receive the electric field signal output by the simulation module, mirror the electric field signal, and output the opposite electric field signal;

[0057] The inhibition module is used to receive the opposite electric field signal output by the mirror module, generate an inhibition logic based on the opposite electric field signal, and dynamically inhibit the patient when the patient has a spasm based on the inhibition logic;

[0058] The initialization unit is arranged below the inhibition module. The initialization unit is used to obtain the opposite electric field signal received by the inhibition module, convert the opposite electric field signal into an electromyographic signal, and obtain the maximum amplitude and the minimum amplitude in the converted electromyographic signal to determine the amplitude interval of the electromyographic signal;

[0059] The inhibition logic in the inhibition module is:

[0060] The electromyographic signal generated by the spasm at the deployment position of the acquisition module is obtained in real time, and the opposite number of the amplitude corresponding to the electromyographic signal is obtained;

[0061] Whether the opposite number is within the amplitude interval is identified;

[0062] The identification result is yes, the inhibition module generates vibration, the identification result is no, after the current spasm of the patient ends, the system jumps to the running phase of the acquisition module and is refreshed;

[0063] The inhibition module is integrated with the acquisition module, and is disposed synchronously with the acquisition module at the surface of the spasm position of the user's body. The inhibition module is made of a material with a piezoelectric effect, and the material generates vibration based on the corresponding electric field signal of the opposite number of the corresponding amplitude of the electromyographic signal.

[0064] The evaluation module is configured to obtain inhibition module running information and evaluate the rehabilitation situation of the patient's spasm problem based on the inhibition module running information.

[0065] The inhibition module running information obtained by the evaluation module includes: the inhibition module running frequency, the electric field signal strength applied in the inhibition module running phase, and the number of times the system jumps to the acquisition module based on the identification result of whether the opposite number is within the amplitude interval.

[0066] The evaluation logic of the rehabilitation situation of the patient's spasm problem is as follows:

[0067] ;

[0068] In the formula: is the rehabilitation situation value of the patient's spasm problem; is the inhibition module running frequency; is the number of times the system jumps to the acquisition module based on the identification result of whether the opposite number is within the amplitude interval; is the electric field signal strength applied in the latest inhibition module running; is the maximum electric field signal strength applied in the historical inhibition module running; is a constraint function;

[0069] In the formula, The larger the value is, the better the rehabilitation effect of the patient's spasm problem is. In the constraint function, When the value of is less than or equal to zero, The value of is equal to , When the value of is greater than zero, The value of is ;

[0070] Through the above logical formula, the rehabilitation situation of the patient's spasm problem is evaluated to achieve further rehabilitation health management of the patient's spasm.

[0071] The evaluation module is continuously run to continuously output the rehabilitation situation value of the patient's spasm problem, denoted as ;

[0072] The evaluation result message content generated by the message module is ;

[0073] wherein the system end user evaluates the spasm problem rehabilitation effect by observing the change of each adjacent item value in the system;

[0074] The message module is used for recording the historical running evaluation results of the evaluation module, generating an evaluation result message based on the recorded evaluation results, and feeding back to the system end user.

[0075] The lower level of the acquisition module is connected with the storage unit and the identification unit through the wireless network interaction, the acquisition module and the distinguishing module are connected with the acquisition module through the wireless network, the acquisition module is connected with the mirror module and the suppression module through the wireless network interaction, the lower level of the suppression module is connected with the initialization unit through the wireless network interaction, and the suppression module is connected with the evaluation module and the message module through the wireless network interaction.

[0076] In this embodiment, the distinguishing module runs to distinguish the spasm position area of the patient's body, controls the acquisition module to perform the acquisition of the electromyographic signal in each distinguished area based on the distinguishing result, the acquisition module acquires the electromyographic signal of the spasm position of the patient's body in real time, the storage unit synchronously receives the electromyographic signal acquired by the acquisition module, stores the electromyographic signal, the identification unit synchronously traverses each electromyographic signal stored in the storage unit, identifies the electromyographic signal with the highest activity in each electromyographic signal, the simulation module is run behind the acquisition module to obtain the electromyographic signal with the highest activity, simulates the output of the corresponding electric field signal based on the obtained electromyographic signal with the highest activity, the mirror module receives the electric field signal output by the simulation module, mirrors the electric field signal to output the opposite electric field signal, the suppression module further receives the opposite electric field signal output by the mirror module, generates the suppression logic based on the opposite electric field signal, dynamically suppresses when the patient has a spasm based on the suppression logic, the initialization unit synchronously obtains the opposite electric field signal received by the suppression module, converts the opposite electric field signal into the electromyographic signal, obtains the maximum amplitude and the minimum amplitude in the converted electromyographic signal to determine the amplitude interval of the electromyographic signal, and obtains the running information of the suppression module through the evaluation module, evaluates the rehabilitation situation of the patient's spasm problem based on the running information of the suppression module, and finally records the historical running evaluation results of the evaluation module through the message module, generates an evaluation result message based on the recorded evaluation results, and feeds back to the system end user.

[0077] Through the inverse piezoelectric effect principle used by the system in the above embodiment, when the patient has a spasm, the piezoelectric material generates a movement opposite to the electromyographic signal caused by the spasm, thereby relieving the patient's spasm through physical intervention, achieving the effect of suppressing the spasm. Based on this method, it effectively adapts to patients with different degrees of spasm and provides patients with spasm suppression that adapts to the whole stage of the rehabilitation process. Embodiment

[0078] In the specific implementation level, on the basis of embodiment 1, this embodiment refers to​Figure 2 Further specific description of a spasm suppression rehabilitation management system in Example 1:

[0079] A spasm suppression rehabilitation management method, comprising the following steps:

[0080] Step 1: Identify the size of the spasm location area of the patient, and decide whether to divide the spasm location area based on the size of the spasm location area;

[0081] Specifically, it can include identifying the size of the spasm location area of the patient, and deciding whether to divide the spasm location area and paste the surface electrode based on the distribution of the target muscle, the arrangement direction of the muscle fiber, etc.

[0082] Step 2: Deploy a sensor to perceive the myoelectric signal generated by the spasm in the spasm location area, and perceive the myoelectric signal in the spasm location area or each divided area of the spasm location area;

[0083] Step 3: Obtain the perceived myoelectric signal, simulate the myoelectric signal as an electric field signal, and mirror the simulated electric field signal as an opposite electric field signal;

[0084] Step 4: Generate suppression logic according to the opposite electric field signal obtained by the simulation and mirroring operation, and dynamically suppress the spasm when the patient has a spasm based on the suppression logic;

[0085] Step 5: Real-time acquisition of spasm dynamic suppression process information, evaluation of the rehabilitation situation of the patient's spasm problem based on the acquired information, and generation of a message based on the historical evaluation results.

[0086] In summary, the system and method in the above examples can accurately determine the location of the patient's body spasm, continuously collect the myoelectric signal generated by the spasm, simulate and output the specific electric field signal by analyzing these signals, generate the opposite electric field signal by using the mirroring technology, and then effectively suppress the patient's spasm when the patient has a spasm, thereby relieving the spasm symptoms. At the same time, the system can also collect and analyze various key information in the suppression process, such as the frequency of suppression, the intensity of the electric field signal used, etc., to evaluate the rehabilitation situation of the patient's spasm problem, so that the patient and medical staff can clearly understand the rehabilitation progress. Moreover, the system will record the evaluation results and generate a message to feedback to the user, and the user can intuitively evaluate the rehabilitation effect by observing the changes in the evaluation results, which provides a strong basis for adjusting the subsequent rehabilitation treatment plan, greatly improving the scientificity and effectiveness of spasm rehabilitation treatment.

[0087] The above examples are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that the technical solutions recorded in the foregoing examples can be modified, or some technical features can be replaced by equivalent features; and these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A spasticity inhibition rehabilitation management system, characterized in that, include: The differentiation module is used to differentiate the location of the patient's body spasms, and controls the acquisition module to perform electromyography signal acquisition in each differentiated area based on the differentiation results; The acquisition module is used to acquire electromyographic signals at the location of the patient's body spasms in real time; The simulation module is used to acquire the most active electromyographic signal in the acquisition module and simulate the corresponding electric field signal based on the acquired most active electromyographic signal. The mirror module is used to receive the electric field signal output by the analog module, mirror the electric field signal, and output an opposite electric field signal. The inhibition module receives the opposite electric field signal output from the mirror module, generates inhibition logic based on the opposite electric field signal, and performs dynamic inhibition when the patient experiences spasm based on the inhibition logic. The assessment module is used to obtain operational information from the inhibition module and to assess the patient's recovery status regarding spasticity based on this information. The message module is used to record the historical evaluation results of the evaluation module and generate evaluation result messages based on the recorded evaluation results to provide feedback to the system user. The acquisition module is integrated with a sensor that can sense the electromyographic signals generated by the spasm. Several acquisition modules are set up. When the acquisition modules acquire the electromyographic signals of the spasm location of the patient's body, they are evenly distributed on the surface of the spasm location of the patient's body. The acquisition module is equipped with a storage unit and a recognition unit. The storage unit is used to receive and store the electromyographic signals collected by the acquisition module. The recognition unit is used to traverse the electromyographic signals stored in the storage unit and identify the electromyographic signal with the highest activity among them. When the storage unit stores electromyographic (EMG) signals, it stores the EMG signals in the form of an EMG signal spectrum. The recognition logic for the activity level of EMG signals in the recognition unit is as follows: ； In the formula: This refers to the activity level of electromyographic signals. This represents the total number of amplitude sequence numbers in the electromyographic signal; This represents the amplitude corresponding to the i-th sequence number in the electromyographic signal; The interval between the amplitude corresponding to the i-th sequence number and the amplitude corresponding to the (i+1)-th sequence number in the electromyographic signal; The deployment area is defined based on the deployment results of the data acquisition module. Normalization factor; in, A higher value indicates higher electromyographic signal activity, and vice versa. Indicates to Find the average; The suppression module operation information acquired by the evaluation module includes: the suppression module operation frequency, the electric field signal intensity applied during the suppression module operation phase, and the number of times the system jumps to the acquisition module based on the identification result of whether the opposite number is within the amplitude range; The assessment logic for the patient's recovery status regarding spasticity is as follows: ； In the formula: The value represents the patient's recovery status regarding spasticity. To suppress the module's operating frequency; This refers to the number of times the system jumps to the acquisition module based on the recognition result of whether the opposite number is within the amplitude range; To suppress the electric field signal strength applied in the module's most recent operation; To suppress the maximum electric field signal strength of the module's historical operating applications; For constraint functions; in, The larger the value, the better the rehabilitation effect for the patient's spasticity problem. In the constraint function, When the value is less than or equal to zero, The value is equal to , When the value is greater than zero, Values .

2. The spasticity inhibition rehabilitation management system according to claim 1, characterized in that, The acquisition module continuously acquires electromyographic signals of the patient at the location of spasm using a user-defined time domain on the system side. The initial default acquisition time domain is 24 hours. The decision-making process for whether the differentiation module participates in system operation is as follows: if the area of ​​the patient's body spasm is greater than or equal to X, the differentiation module participates in system operation; if the area of ​​the patient's body spasm is less than X, the differentiation module does not participate in system operation. X is a decision threshold preset by the system user. When the differentiation module differentiates the location area of ​​the patient's body spasm, the system user manually divides the area, and each divided area contains at least two acquisition modules. After the differentiation module finishes running, the acquisition module uses each divided area as the acquisition target to perform electromyography signal acquisition. When the differentiation module participates in system operation, the identification unit obtains data each time it runs. hour, Replace with the area of ​​the corresponding distinguishing region.

3. The spasticity inhibition rehabilitation management system according to claim 1, characterized in that, The suppression module is equipped with an initialization unit at its lower level. The initialization unit is used to acquire the opposite electric field signal received by the suppression module, convert the opposite electric field signal into an electromyographic signal, and obtain the maximum and minimum amplitude values ​​from the converted electromyographic signal to determine the amplitude range of the electromyographic signal.

4. The spasticity inhibition rehabilitation management system according to claim 3, characterized in that, The suppression logic in the suppression module is as follows: Real-time acquisition of electromyographic signals generated by spasms at the deployment location of the acquisition module, and taking the inverse of the corresponding amplitude of the electromyographic signal; Identify whether the opposite number is within the amplitude range; If the identification result is yes, the suppression module will vibrate; if the identification result is no, the system will jump to the acquisition module operation phase and refresh the operation after the patient's current spasm ends. The inhibition module and the acquisition module are integrated into one unit and are deployed synchronously on the surface of the acquisition module at the location of the user's body spasm. The inhibition module is made of a material with piezoelectric effect, which vibrates based on the electric field signal corresponding to the opposite of the amplitude of the electromyographic signal.

5. The spasticity inhibition rehabilitation management system according to claim 1, characterized in that, The assessment module runs continuously to continuously output values ​​indicating the patient's recovery status regarding spasticity, denoted as... ; The evaluation result message content generated by the message module is... ; Among them, system-side users observe The changes in the values ​​of adjacent terms are used to evaluate the rehabilitation effect of spasticity problems.

6. The spasticity inhibition rehabilitation management system according to claim 1, characterized in that, The acquisition module is connected to a storage unit and an identification unit via a wireless network. The acquisition module and the differentiation module are connected to the acquisition module via a wireless network. The acquisition module is connected to a mirroring module and a suppression module via a wireless network. The suppression module is connected to an initialization unit via a wireless network. The suppression module is connected to an evaluation module and a message module via a wireless network.

7. A method for spasticity inhibition rehabilitation management, wherein the method is an implementation method of the spasticity inhibition rehabilitation management system as described in any one of claims 1-6, characterized in that, Includes the following steps: Step 1: Identify the size of the area where the patient is experiencing spasms, and decide whether to differentiate the spasm area based on the size of the area. Step 2: Deploy sensors to detect electromyographic signals generated by the spasm in the spasticity area, and detect electromyographic signals in the spasticity area or in different regions of the spasticity area; Step 3: Acquire the sensed electromyographic signals, simulate the electromyographic signals as electric field signals, and mirror the simulated electric field signals to obtain the opposite electric field signals; Step 4: Generate inhibition logic based on the opposite electric field signals obtained from the simulation and mirror operation. Based on the inhibition logic, dynamically inhibit the spasm when the patient experiences it. Step 5: Acquire information on the dynamic inhibition process of spasticity in real time, assess the patient's recovery status of spasticity based on the acquired information, and generate a message based on historical assessment results.

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