Methods, devices, equipment and media for electromyography (EMG) rehabilitation training

Abstract

This invention relates to the field of limb joint rehabilitation technology, and discloses a method, device, equipment, and medium for electromyographic stimulation rehabilitation training. The method includes: stimulating the muscles of the target training area according to current stimulation parameter values, and collecting the training extension and contraction degree parameter values ​​of the muscles in real time; the stimulation parameter is the stimulation output power; determining whether muscle fatigue conditions are met based on the current stimulation parameter values ​​and the training extension and contraction degree parameter values; if so, adjusting the current stimulation parameter values, and then repeating the aforementioned steps according to the adjusted stimulation parameter values ​​for rehabilitation training until the end-of-training conditions are met. This invention can judge muscle fatigue during stimulation training and can adaptively adjust the stimulation parameter values ​​according to the muscle fatigue level, thereby avoiding secondary damage caused by overstimulation.

Description

Technical Field

[0001] This invention relates to the field of limb joint rehabilitation technology, and in particular to a method, device, equipment and medium for electromyography rehabilitation training. Background Technology

[0002] According to relevant literature, there are currently as many as 70 million stroke patients in my country, with more than 2 million new cases each year. More than 50% of stroke patients experience varying degrees of limb dysfunction, such as hand motor impairment.

[0003] Clinical rehabilitation of hand function disorders can be achieved through hand function rehabilitation training devices. These devices output electrical stimulation pulses to simulate nerve discharges, causing passive contraction and relaxation of the affected muscles. Through continuous muscle contraction and relaxation, hand function rehabilitation is ultimately achieved, or the goal of improving motor function disorders is reached.

[0004] Currently, most training devices on the market that use electrical stimulation to rehabilitate hand function disorders lack monitoring of muscle fatigue during training. During long-term rehabilitation training, limb muscles will experience muscle fatigue. If muscle fatigue is not detected in time, excessive rehabilitation training can lead to unnecessary secondary damage to the limbs. Summary of the Invention

[0005] The purpose of this invention is to provide a method, device, equipment, and medium for electromyography (EMG) rehabilitation training, which can judge muscle fatigue during stimulation training and adaptively adjust stimulation parameter values ​​according to muscle fatigue, thereby avoiding secondary damage caused by overstimulation.

[0006] To address the aforementioned technical problems, in a first aspect, embodiments of the present invention provide an electromyography (EMG) rehabilitation training method, applied to limb joint muscle rehabilitation training, comprising:

[0007] The muscles of the target training area are stimulated according to the current stimulation parameter values, and the training contraction degree parameter values ​​of the muscles are collected in real time; the stimulation parameter is the stimulation output power.

[0008] Determine whether the muscle fatigue condition is met based on the current stimulation parameter value and the training stretching degree parameter value.

[0009] If so, adjust the current stimulus parameter value, and then repeat the aforementioned steps to perform rehabilitation training according to the adjusted stimulus parameter value until the end of training conditions are met.

[0010] In addition, determining whether the muscle fatigue condition is met based on the current stimulus parameter value and the training stretching parameter value includes:

[0011] Based on the training stretching parameter value, determine whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value;

[0012] If the fatigue warning condition is met, the target training part is controlled to perform N maximum voluntary flexion and extension movements, and the voluntary extension and contraction degree parameter value of each maximum voluntary flexion and extension movement is collected in real time; N is greater than or equal to 1.

[0013] Based on the autonomous stretching degree parameter value and the reference stretching degree parameter value, it is determined whether the fatigue judgment condition is met. If the fatigue judgment condition is met, then the muscle fatigue condition is determined to be met.

[0014] In addition, the degree of extension parameter is the flexion and extension angle of the target training part;

[0015] Accordingly, the collected extension and contraction parameter values ​​include: the maximum flexion angle parameter value and the maximum extension angle parameter value of the target training part;

[0016] The step of determining whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value based on the training stretching degree parameter value includes:

[0017] The current flexion-extension angle range is obtained based on the maximum flexion angle parameter value and the maximum extension angle parameter value;

[0018] Determine whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range;

[0019] Optionally, the reference flexion-extension angle range is the previously determined flexion-extension angle range. Correspondingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range includes:

[0020] If the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a first ratio, then the fatigue warning condition is determined to be met.

[0021] Optionally, the reference flexion-extension angle range is an initially determined flexion-extension angle range. Correspondingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range includes:

[0022] If the ratio of the current flexion-extension angle range to the initially determined maximum flexion-extension angle range is less than any warning threshold in the preset warning ratio set, then the fatigue warning condition is determined to be met; wherein, the preset warning ratio set range includes multiple warning thresholds.

[0023] In addition, determining whether the fatigue judgment condition is met based on the autonomous stretching degree parameter value and the reference stretching degree parameter value includes:

[0024] When the reference flexion-extension angle range is the previously determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than the second ratio, then the fatigue determination condition is satisfied.

[0025] When the reference flexion-extension angle range is the initially determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the initially determined flexion-extension angle range is less than any fatigue judgment threshold in the preset fatigue judgment threshold set, then the fatigue judgment condition is determined to be met.

[0026] In addition, the degree of stretching parameter is the electromyographic signal characteristic of the target training area; correspondingly, the collected degree of stretching parameter value is the electromyographic signal characteristic value.

[0027] The step of determining whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value based on the training stretching degree parameter value includes:

[0028] If the current electromyographic signal characteristic value of the target training area is less than the reference electromyographic signal characteristic value, then the fatigue warning condition is determined to be met.

[0029] The step of determining whether the fatigue judgment condition is met based on the autonomous stretching degree parameter value and the reference stretching degree parameter value includes:

[0030] The current effective value of the electromyography signal is calculated based on the characteristic value of the electromyography signal. If the current effective value of the electromyography signal is less than the effective value of the reference electromyography signal, then the fatigue determination condition is met.

[0031] In addition, the method also includes:

[0032] The initial stimulus parameter values ​​are obtained as follows:

[0033] The stimulation parameter value is gradually increased from the initial setting value while the contraction and relaxation parameter value of the muscle in the target training area is collected simultaneously.

[0034] If the stretching degree parameter value meets the preset condition, then the stimulation parameter value corresponding to the stretching degree parameter value that meets the preset condition is used as the initial stimulation parameter value.

[0035] The preset condition is that the value of the stretchability parameter is greater than a preset parameter value or the value of the stretchability parameter remains unchanged within a preset time.

[0036] In addition, adjusting the current stimulus parameter value includes:

[0037] The adjusted stimulus parameter value is equal to the product of the initial stimulus parameter value and the proportional adjustment factor; wherein, the proportional adjustment factor is the ratio of the current stretching parameter value to the initial stretching parameter value;

[0038] Wherein, when the degree of extension parameter is the flexion-extension angle of the target training part, the degree of extension parameter is the maximum flexion-extension angle range; when the degree of extension parameter is the electromyographic signal characteristic value of the target training part, the degree of extension parameter is the difference between the effective value of the electromyographic signal and the background noise of the electromyographic signal.

[0039] Optionally, the target training area includes: the hand, elbow, wrist joint, or knee joint;

[0040] Optionally, the method further includes: if it is determined that the muscle fatigue condition is met, then simultaneously outputting muscle relaxation stimulation while outputting electromyographic flexion-extension stimulation.

[0041] Secondly, embodiments of the present invention provide an electromyography (EMG) rehabilitation training device for use in limb joint and muscle rehabilitation training, comprising:

[0042] The stimulation and acquisition module is used to stimulate the muscles of the target training area according to the current stimulation parameter values, and to acquire the training contraction degree parameter values ​​of the muscles in real time; the stimulation parameter is the stimulation output power.

[0043] The fatigue judgment module is used to determine whether the muscle fatigue condition is met based on the current stimulus parameter value and the training stretching degree parameter value.

[0044] The stimulation adjustment module is used to adjust the current stimulation parameter value if the muscle fatigue condition is met.

[0045] The loop control module is used to control the aforementioned modules to perform rehabilitation training according to the adjusted stimulus parameter values ​​until the end of training conditions are met.

[0046] Thirdly, embodiments of the present invention also provide an electromyography (EMG) stimulation rehabilitation training device, comprising: a memory and a processor, wherein the memory stores a computer program, and the processor runs the computer program to implement the EMG stimulation rehabilitation training method as described above.

[0047] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the electromyographic stimulation rehabilitation training method as described in any embodiment of the present invention.

[0048] Compared with the prior art, the technical solution provided by the embodiments of the present invention has at least the following positive effects:

[0049] In this embodiment of the invention, the training extension and contraction degree parameter values ​​of the muscles are collected in real time during muscle extension and contraction stimulation training. Based on the current stimulation parameter values ​​and the training extension and contraction degree parameter values, it is determined whether the muscle fatigue condition is met. If the muscle fatigue condition is met, the current stimulation parameter values ​​are adjusted. Then, the aforementioned steps are repeated according to the adjusted stimulation parameter values ​​to carry out rehabilitation training until the end of training conditions are met. Therefore, this embodiment of the invention can analyze the muscle fatigue status in real time and can adaptively adjust the stimulation parameter values ​​according to the muscle fatigue status, which not only has a good training effect but also avoids secondary muscle damage caused by overtraining. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. It is understood that the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0051] Figure 1 This is a schematic diagram of the structure of an electromyography (EMG) rehabilitation training device;

[0052] Figure 2 This is a flowchart illustrating the electromyography rehabilitation training method provided in an embodiment of the present invention.

[0053] Figure 3 This is a schematic diagram of the structure of the electromyography rehabilitation training device provided in an embodiment of the present invention;

[0054] Figure 4 This is a schematic diagram of the structure of electromyography rehabilitation training provided in an embodiment of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this invention. Obviously, the described embodiments are only some embodiments of this invention, not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0056] The inventors discovered that current electromyography (EMG) therapy programs for hand function rehabilitation often rely on subjective experience to adjust stimulation parameters to avoid training in a state of muscle fatigue, thus failing to accurately determine muscle fatigue. Therefore, the inventors proposed a method that collects the degree of muscle extension parameters during training, determines the presence of muscle fatigue based on these parameters, and adjusts the stimulation parameters in real time when muscle fatigue occurs. This provides an EMG rehabilitation training method that adaptively adjusts stimulation based on muscle fatigue levels, effectively avoiding overtraining in a fatigued state, improving training safety, ensuring training efficiency, and ultimately enhancing rehabilitation outcomes.

[0057] The electromyography (EMG) stimulation rehabilitation training method provided in this invention is applicable to limb joint muscle rehabilitation training, including but not limited to muscle rehabilitation training for limb joints such as the hand, wrist, elbow, or knee joints that have movement disorders due to muscle injury. This method is applicable to EMG rehabilitation training devices, with a hand function EMG rehabilitation training device as an example. Please refer to... Figure 1 As shown, the device mainly includes: a control unit, an electrical stimulation circuit, an electromyography acquisition circuit, and a flexion-extension angle acquisition module.

[0058] The electromyography (EMG) acquisition circuit is used to acquire muscle electrical signals during rehabilitation training. The EMG acquisition circuit may include an amplification circuit, a filtering circuit, a level-up circuit, and an AD conversion circuit. The EMG stimulation rehabilitation training device can connect to therapeutic electrode pads via electrode wires to input the EMG signals into the EMG acquisition circuit. The electrical stimulation circuit outputs stimulation pulses to induce flexion and extension movements of the hand. The flexion and extension angle acquisition module is used to identify the flexion and extension movements of the hand and the angle of these movements during limb rehabilitation training. The flexion and extension angle acquisition module may include a sensing glove and a sensor signal processing circuit. The sensing glove detects the angle information of the hand's flexion and extension movements, and the sensor signal processing circuit processes the signals provided by the sensing glove. The sensor signal processing circuit may include a sensor drive signal generation circuit, a detection circuit, an amplification and filtering circuit, and an AD conversion circuit. The control unit controls the electrical stimulation circuit to adaptively output electrical stimulation based on the data acquired by the EMG acquisition circuit and the flexion and extension angle acquisition module. The sensing glove can generate an inductive or resistive signal that changes with the flexion and extension movements of the glove. This embodiment does not impose specific limitations on the structure of the EMG stimulation rehabilitation training device.

[0059] Figure 2 This is a flowchart of an electromyography (EMG) rehabilitation training method provided in Embodiment 1 of the present invention. This method can be executed by an EMG rehabilitation training device provided in this embodiment of the invention. This device can be implemented in software and / or hardware and configured within an EMG rehabilitation training equipment. Figure 2As shown, the electromyography rehabilitation training method of this embodiment includes steps 201 to 205.

[0060] Step 201: Stimulate the muscles of the target training area according to the current stimulation parameter values, and collect the training contraction parameter values ​​of the muscles in real time.

[0061] The target training area can be the joint of the limb to be trained, including but not limited to areas with motor dysfunction such as the hand, wrist, elbow, and knee joints. The stimulation parameter is the stimulation output power. Excessive stimulation output power may damage muscles, while insufficient stimulation output power will affect training effectiveness. Therefore, an appropriate stimulation output power, such as the optimal stimulation output power, needs to be used. Theoretically, the optimal stimulation output power can maximize muscle contraction and extension without damaging the muscles. When muscles in the limb joint area are stimulated and contract, they cause the limb joint to flex or extend.

[0062] The initial stimulation parameter values ​​are the stimulation output power values ​​used when stimulation training begins. These initial stimulation parameter values ​​can be obtained before training starts. During electromyography (EMG) training, the initial stimulation parameter values ​​are used to stimulate muscle contraction and extension, and then the stimulation parameter values ​​are adjusted in real time according to the muscle fatigue level.

[0063] Optionally, the initial stimulation parameter value can be obtained in the following way: gradually increase the stimulation parameter value from the initial set value while simultaneously collecting the muscle contraction parameter value of the target training area. If the contraction parameter value meets a preset condition, then the stimulation parameter value corresponding to the contraction parameter value that meets the preset condition is used as the initial stimulation parameter value. The preset condition is that the contraction parameter value is greater than a preset parameter value or the contraction parameter value remains unchanged within a preset time. It can be understood that the contraction parameter value can be a parameter value that characterizes the amount of muscle elongation or muscle contraction, and is converted into a form where the larger the parameter value, the greater the corresponding elongation or contraction. Therefore, the contraction ability can be directly judged based on the magnitude of the parameter value. Muscle contraction ability determines the degree of flexion and extension of the limb joint; therefore, muscle contraction ability can be represented by the flexion and extension angle. This embodiment does not impose specific restrictions on the comparison and judgment method of muscle contraction, as long as the muscle contraction or joint flexion and extension can be accurately obtained.

[0064] The degree of extension parameter value is used to represent the extension and contraction of the muscles in the target training area, and can also reflect the flexion and extension of the target training area when performing flexion and extension movements. Taking the hand as an example, when the flexor muscles contract, the hand can make a fist. The greater the contraction strength of the flexor muscles, the greater the degree of flexion. When the extensor muscles contract, the hand can extend. The greater the muscle contraction, the better the hand extension. The training degree of extension parameter value is the degree of extension parameter value collected during stimulation training. For example, the degree of extension parameter can be the flexion and extension angle of the target training area or the electromyographic signal characteristics of the muscles in the target training area. The flexion and extension angle reflects the extension and contraction of the muscles in that area through the angle of the fist and extension of the hand. The electromyographic signal characteristics can directly reflect the extension and contraction of the muscles when the hand is clenched and extended. It is understood that this embodiment does not impose specific limitations on the degree of extension parameter, as long as it can quantify and reflect the degree of muscle extension and contraction.

[0065] The preset parameter value can be the maximum degree of extension / retraction when the trainee performs maximum voluntary flexion / extension. When the degree of extension / retraction parameter is the flexion / extension angle, the preset parameter value can be the initially determined flexion angle parameter value for the maximum flexion movement in the specific example below. Or the extension angle parameter value of the maximum extension movement. Alternatively, it can be an initial range of flexion and extension angles determined by both, which can be represented by the absolute value of the difference between the two. When the degree of extension parameter is a characteristic of electromyography (EMG) signals, the preset parameter value can be the initially determined effective EMG value in the specific example below. In determining the initial stimulus parameter values, the stimulus output power gradually increases, and the muscle contraction and extension gradually increase. When the muscle contraction and extension reaches the contraction and extension corresponding to the optimal degree of flexion and extension during the maximum voluntary flexion and extension movement, the minimum stimulus output power that can achieve the best training effect can be obtained.

[0066] Regarding the criterion that the muscle contraction parameter remains constant within a preset time, when the muscle is stimulated with a small stimulus output power, the amount of muscle contraction will change. As the amount of muscle contraction gradually increases, a larger stimulus output power is required to stimulate muscle contraction. However, when the amount of muscle contraction has reached a critical value, a larger stimulus output power cannot drive muscle contraction. If the stimulus output power continues to increase, it may damage the muscle. Therefore, the stimulus output power that remains constant for a preset time is used as the initial stimulus parameter value, so that training using the initial stimulus parameter value is more efficient and will not damage the muscle.

[0067] Step 202: Determine whether the muscle fatigue condition is met based on the current stimulus parameter value and the training stretching degree parameter value. If the muscle fatigue condition is met, proceed to step 203. If the muscle fatigue condition is not met, return to step 201.

[0068] Optionally, step 202, determining whether the muscle fatigue condition is met based on the current stimulation parameter value and the training extension degree parameter value, may include: determining whether the muscle of the target training area meets the fatigue warning condition under the action of the current stimulation parameter value based on the training extension degree parameter value; if the fatigue warning condition is met, controlling the target training area to perform N maximum voluntary flexion and extension movements, and collecting the voluntary extension degree parameter value of each maximum voluntary flexion and extension movement in real time; determining whether the fatigue judgment condition is met based on the voluntary extension degree parameter value and the reference extension degree parameter value; if the fatigue judgment condition is met, then it is determined that the muscle fatigue condition is met. Here, N is greater than or equal to 1. In other words, during stimulation, whether the muscle is fatigued is monitored in real time; when the muscle is fatigued, the amount of muscle extension produced by stimulation with the same stimulation output power will decrease. When a decrease in the muscle's contractile ability in the target training area is detected to a certain extent, muscle fatigue is considered to be likely, thus meeting the fatigue warning condition. Then, the target training area is controlled to perform N repetitions of voluntary flexion and extension movements. The fatigue judgment condition is determined by comparing the voluntary contraction degree parameter value of the voluntary contraction and extension movements with a reference contraction degree parameter value. This allows for an accurate assessment of muscle fatigue through the training contraction degree parameter value. It is understood that this embodiment does not impose specific limitations on the method for determining whether the muscle fatigue condition is met. For example, in some cases, the step of obtaining the voluntary contraction degree parameter value through voluntary flexion and extension movements to determine whether the fatigue judgment condition is met can be omitted, and muscle fatigue can be judged directly based on the fatigue warning condition or a variation thereof. During training, voluntary maximal flexion and extension movements can more accurately obtain the trainee's current muscle contractile ability. It is understood that the contraction degree parameter can be any parameter that can characterize muscle contractile ability, such as electromyographic characteristic values, effective electromyographic values, maximum flexion angle parameter values, maximum extension angle parameter values, flexion and extension angle range, etc., as long as the parameter value can accurately quantify muscle contractile ability; no specific limitations are imposed here. Taking the voltage value collected from the glove as an example, the voltage increases continuously as the hand moves from fully open to fully clenched; conversely, the voltage gradually decreases as the hand moves from fully clenched to fully open. The range of flexion and extension angles, or the degree of extension parameter, can be expressed as the absolute value of the difference between the voltage values ​​corresponding to a fully open hand and a fully clenched hand.

[0069] The longer the training time, the more easily muscles fatigue. For example, if muscles are stimulated with a high output power for a period of time, they gradually become fatigued, and their contraction and relaxation range is much smaller than before the training period—for example, less than 90% of the pre-training range. In this case, the muscle is considered fatigued at that output power. At this point, the stimulation parameters can be appropriately reduced to continue stimulation. Similarly, after a period of training, muscles may become fatigued again, and the output power can be reduced to continue stimulation.

[0070] Step 203: Adjust the current stimulus parameter value.

[0071] Optionally, the adjusted stimulus parameter value is equal to the product of the initial stimulus parameter value and the proportional adjustment factor. The proportional adjustment factor can be the ratio of the current extension / contraction parameter value to the initial extension / contraction parameter value. It should be noted that the extension / contraction parameter value can also be called the muscle extension / contraction capacity parameter value, as long as it can accurately quantify the amount of muscle extension / contraction when stimulated. The ratio of the current extension / contraction parameter value to the initial extension / contraction parameter value is used to compare the muscle's current extension / contraction capacity with its initial extension / contraction capacity before training. The initial extension / contraction parameter value characterizes the muscle's flexion / extension capacity in its initial state. The current extension / contraction parameter value characterizes the muscle's current flexion / extension capacity. Generally speaking, the larger the extension / contraction parameter value, the stronger the muscle's extension / contraction capacity and the greater the amount of muscle extension / contraction; the stronger the muscle's flexion / extension capacity, the greater the stimulus output power required. Adjusting the stimulus output power according to the ratio of the current extension / contraction parameter value to the initial extension / contraction parameter value can obtain a stimulus output power adapted to the current muscle extension / contraction capacity. However, this is not the only method; other methods can also be used to adjust the stimulus output parameters. For example, the adjusted stimulus output parameters can be obtained similarly to the initial stimulus parameters.

[0072] Step 204: Determine whether the end-of-training conditions are met. If the end-of-training conditions are met, proceed to step 205; otherwise, return to step 201.

[0073] Specifically, when the cumulative training time reaches the set training time, such as 60 minutes of training, the training termination condition is determined to be met. This embodiment does not impose specific restrictions on the method for determining whether the training termination condition is met.

[0074] Therefore, by repeatedly executing steps 201 to 204, it is possible to determine in real time whether muscle fatigue occurs based on the stretching parameter value generated during training, and adaptively adjust the stimulus output parameters according to the muscle fatigue condition when muscle fatigue occurs. This not only ensures good training results but also avoids muscle damage caused by fatigue training.

[0075] It is worth mentioning that the method may also include: if it is determined that the muscle fatigue condition is met, then outputting muscle relaxation stimulation at the same time as outputting muscle flexion and extension stimulation, thereby improving muscle training conditions.

[0076] Step 205: End training.

[0077] The following is a detailed explanation of the electromyographic stimulation rehabilitation training method in this embodiment, using the flexion-extension angle of the target training area as an example:

[0078] Accordingly, the training extension parameter values ​​collected in step 201 may include: the maximum flexion angle parameter value and the maximum extension angle parameter value of the target training part.

[0079] Accordingly, determining whether the muscles of the target training area meet the fatigue warning conditions under the current stimulus parameter value based on the training extension degree parameter value may include: obtaining the current flexion-extension angle range based on the maximum flexion angle parameter value and the maximum extension angle parameter value, and determining whether the fatigue warning conditions are met based on the current flexion-extension angle range and the reference flexion-extension angle range.

[0080] Optionally, the reference flexion-extension angle range can be the previously determined flexion-extension angle range (i.e., the maximum flexion-extension angle range determined during the previous maximum voluntary flexion-extension training). Accordingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range may include: if the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a first ratio, then the fatigue warning condition is determined to be met.

[0081] As an alternative, the reference flexion-extension angle range can also be an initially determined flexion-extension angle range, which can be the maximum flexion-extension angle range detected before training. Accordingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range can include: if the ratio of the current flexion-extension angle range to the initially determined maximum flexion-extension angle range is less than any warning threshold in a preset warning ratio set, then the fatigue warning condition is determined to be met. The preset warning ratio set contains multiple warning thresholds. For example, the preset warning ratio set may contain multiple warning thresholds such as 90%, 80%, 70%, 60%, etc.

[0082] Optionally, determining whether the fatigue judgment condition is met based on the autonomous stretching degree parameter value and the reference stretching degree parameter value may include: when the reference flexion-extension angle range is the previously determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a second ratio, then the fatigue judgment condition is determined to be met. The second ratio is, for example, 90%. As an alternative, when the reference flexion-extension angle range is the initially determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the initially determined flexion-extension angle range is less than any fatigue judgment threshold in the preset fatigue judgment threshold set, then the fatigue judgment condition is determined to be met. Similarly, the preset fatigue judgment threshold set includes multiple fatigue judgment thresholds such as 90%, 80%, 70%, 60%, etc.

[0083] Accordingly, in the step of adjusting the current stimulus parameter value, the degree of extension parameter can be the maximum flexion-extension angle range. However, it is not limited to this; the degree of extension parameter can also be the maximum flexion angle or the maximum extension angle.

[0084] The following example illustrates the electromyographic stimulation rehabilitation training method based on flexion and extension angles:

[0085] 1) This step is a training preparation step, used to determine the initial extension and contraction parameters: After the trainee puts on the sensor gloves used to collect the extension and contraction parameters, they perform a maximum voluntary contraction movement. The flexion and extension signals of the hand are collected through the gloves. The maximum flexion angle parameter value of each maximum flexion movement and the maximum extension angle parameter value of each maximum extension movement are recorded. The maximum flexion angle parameter and the maximum extension angle parameter are denoted as follows: and Repeat the maximum voluntary flexion and extension movements. Next, obtain all record values. , ,…, ,and , ,…, And find the root mean square value of the two aforementioned extreme values. and These are used as the initially determined maximum buckling angle parameter value and maximum extension angle parameter value, respectively.

[0086] 2) This step is a training preparation step, used to determine the initial stimulus parameter values, i.e., the initial optimal stimulus output power value: The control device increases the output electrical stimulation power sequentially, and each power output value lasts for a certain time T. T can be set to 1s or 2s based on experience. The flexion-extension angle parameter values ​​of the glove are collected under different stimulus powers. When the stimulus output power value increases to the point where the glove's output flexion-extension angle parameter value is greater than or equal to the maximum flexion angle parameter value determined in step 1), or when the stimulus output power continues to increase until the maximum flexion angle parameter value output by the sensor no longer increases within a preset time, such as 2s, then this stimulus output power value is taken as the initial stimulus output power value, or the initial optimal stimulus output power value. The flexion-extension angle parameter value output by the glove can be a voltage value used to characterize the flexion-extension angle, and there is no restriction on the specific type of the flexion-extension angle parameter value.

[0087] 3) Stimulus output power is adaptively adjusted based on flexion-extension angle:

[0088] a. Stimulation Training and Acquisition of Flexion-Extension Angle Parameters: At the start of training, the device continuously stimulates the muscles using the initial optimal stimulation output power determined in step 2), promoting hand flexion and extension. Simultaneously, it acquires training flexion-extension angle parameter values, which can serve as the flexion-extension angle signal provided by the glove. , Its corresponding root mean square value is ;、 ;

[0089] This step corresponds to step 201 above.

[0090] b. Muscle fatigue warning judgment: With continuous contraction and relaxation, the stimulated muscles will become fatigued, mainly manifested as the maximum flexion-extension angle range being much smaller than the initial flexion-extension angle range determined in step 1) above, or smaller than the previous flexion-extension angle range, under the same stimulus output power; specifically, for example, it may be less than 10% of the previous flexion-extension angle range;

[0091] This step corresponds to the steps described above for determining whether the fatigue warning conditions are met.

[0092] c. Muscle Fatigue Assessment: When the phenomenon described in step b. occurs, i.e., the fatigue warning conditions are met, electromyographic stimulation can be paused. The trainee is prompted by voice to perform a maximum voluntary flexion-extension movement, and the flexion-extension angle parameter values ​​of multiple voluntary flexion-extension movements are calculated and recorded as follows. , ;like Value less than or equal to 90% and / or If the condition is met, then muscle fatigue can be diagnosed.

[0093] This step corresponds to the step above that checks whether the fatigue determination criteria are met.

[0094] d. Stimulus output power adjustment: To promote hand muscle contraction and relieve fatigue, the stimulation output power is adjusted. To decrease, the adjustment formula is as follows:

[0095]

[0096] It is worth mentioning that the stimulation program can also be adjusted at the same time: the stimulation program can be changed from one that mainly promotes muscle contraction to one that promotes muscle contraction while also promoting muscle relaxation; the electrical stimulation methods for stimulating muscle relaxation are well known to those skilled in the art and will not be described in detail here.

[0097] This step corresponds to step 204 above. ) is an example of the current scaling parameter value, ( () is an example of the initial scaling parameter value. It is understandable that the scaling factor can also be a fixed value, or the ratio of the current scaling parameter value to the previous scaling parameter value; no specific restrictions are imposed here.

[0098] e. Utilizing the adjusted Replace the previous stimulation output power value and repeat each sub-step in step 3) until a complete electrical stimulation therapy training process is completed.

[0099] Then, taking the electromyographic signal characteristics of the target training area as an example, the electromyographic stimulation rehabilitation training method of this embodiment will be described in detail as follows:

[0100] Accordingly, the collected extension / contraction parameter values ​​are the electromyographic (EMG) signal characteristic values. These EMG signal characteristic values ​​are related to muscle extension / contraction ability; the larger the EMG signal characteristic value, the stronger the muscle extension / contraction ability, and vice versa. Determining whether the muscles in the target training area meet the fatigue warning conditions under the current stimulus parameter value based on the training extension / contraction parameter value may include: if the current EMG signal characteristic value of the target training area is less than the reference EMG signal characteristic value, then the fatigue warning conditions are met. Determining whether the fatigue judgment conditions are met based on the voluntary extension / contraction parameter value and the reference extension / contraction parameter value may include: calculating the current effective value of the EMG signal based on the EMG signal characteristic value; if the current effective value of the EMG signal is less than the reference effective value, then the fatigue judgment conditions are met.

[0101] Accordingly, in the step of adjusting the current stimulation parameter value, the degree of contraction parameter is the difference between the effective value of the electromyographic signal and the background noise of the electromyographic signal. Therefore, the proportional adjustment factor is the ratio of the difference between the current effective value of the electromyographic signal and the background noise of the electromyographic signal to the difference between the initial effective value of the electromyographic signal and the background noise of the electromyographic signal.

[0102] The following example illustrates the electromyographic stimulation rehabilitation training method based on electromyographic signal characteristics:

[0103] 1) Determining the effective electromyographic value of maximal voluntary flexion and extension: After attaching therapeutic electrodes to the muscles controlling hand flexion and extension, the trainee performs maximal voluntary flexion and extension movements. The electromyographic signal characteristic value of each maximal voluntary flexion movement is recorded, and the electromyographic characteristic value of any maximal flexion and extension movement is recorded as follows: Repeat the maximum flexion and extension movements. Next, all recorded values ​​are , ,…, And seek Valid values ,Will ;

[0104] 2) Determine the initial stimulation output power: The electrical stimulation power output by the control device is increased sequentially, with each power value lasting for a certain time T. The electromyographic signal characteristic values ​​corresponding to different power values ​​are calculated. When the stimulation output power increases to a level where the corresponding electromyographic signal characteristic value is greater than or equal to the value determined in step 1), the initial power is determined. The initial stimulation output power value, also known as the optimal output power value, is determined by continuously increasing the electrical stimulation output power until the effective value of the electromyographic signal remains constant within a preset time. ;

[0105] 3) Electrical stimulation output power is adaptively adjusted based on electromyographic signal characteristic values:

[0106] a. Stimulus training: Based on the initial stimulus parameter values ​​determined above. Continuous stimulation of the muscles induces flexion and extension of the hand, while electromyographic signals are simultaneously acquired and their characteristic values ​​are calculated. ;

[0107] b. Muscle fatigue trend: With continuous contraction and relaxation, the stimulated muscles will become fatigued, mainly manifested in the decrease of characteristic values ​​of electromyographic signals acquired under the same power stimulation scheme.

[0108] c. Assessment of muscle fatigue: When the phenomenon described in b. occurs, electrical stimulation can be paused, and the patient should be verbally instructed to perform maximum voluntary flexion and extension. The effective electromyographic values ​​of multiple voluntary flexion and extensions should be calculated and recorded as follows. ,like Value less than or equal to If the value is 90%, then muscle fatigue is considered.

[0109] d. Adjusting the electrical stimulation output power and stimulation protocol: To promote hand muscle contraction and relieve fatigue, adjust the electrical stimulation output power... To decrease, the adjustment formula is as follows:

[0110] ,in This represents the background noise of the electromyographic signal.

[0111] Stimulation program adjustment: The stimulation program was changed from one that mainly promoted muscle contraction to one that promoted muscle flexion and extension while also promoting muscle relaxation.

[0112] e. Using the adjusted result Replace the previous stimulation output power and repeat step 3) until a complete electrical stimulation therapy training process is completed.

[0113] Compared with the prior art, the embodiments of the present invention can analyze and judge muscle fatigue in real time, and can adaptively adjust the stimulation parameter values ​​according to the muscle fatigue status. This not only has a good training effect, but also avoids secondary muscle damage caused by overtraining.

[0114] This invention provides an electromyography (EMG) stimulation rehabilitation device, configured within an EMG rehabilitation training equipment. For example... Figure 3 As shown, the device includes: a stimulation and acquisition module 301, a fatigue judgment module 302, a stimulation adjustment module 303, and a cycle control module 304.

[0115] The stimulation and acquisition module 301 is used to stimulate the muscles of the target training area according to the current stimulation parameter value, and to acquire the training contraction degree parameter value of the muscle in real time; the stimulation parameter is the stimulation output power.

[0116] The fatigue judgment module 302 is used to determine whether the muscle fatigue condition is met based on the current stimulus parameter value and the training stretching degree parameter value.

[0117] The stimulation adjustment module 303 is used to adjust the current stimulation parameter value if the muscle fatigue condition is met.

[0118] The loop control module 304 is used to control the aforementioned module to perform rehabilitation training according to the adjusted stimulus parameter values ​​until the end of training conditions are met.

[0119] Optionally, the fatigue judgment module 302 may include a fatigue early warning submodule and a fatigue determination submodule.

[0120] The fatigue warning submodule is used to determine whether the muscles of the target training part meet the fatigue warning conditions under the action of the current stimulation parameter value, based on the training stretching degree parameter value.

[0121] The fatigue determination submodule is used to control the target training part to perform N maximum voluntary flexion and extension movements if the fatigue warning condition is met, and to collect the voluntary extension degree parameter value of each maximum voluntary flexion and extension movement in real time; N is greater than or equal to 1; and to determine whether the fatigue judgment condition is met based on the voluntary extension degree parameter value and the reference extension degree parameter value. If the fatigue judgment condition is met, it is determined that the muscle fatigue condition is met.

[0122] Optionally, the degree of extension parameter is the flexion-extension angle of the target training part.

[0123] Accordingly, the collected extension and contraction parameter values ​​include: the maximum flexion angle parameter value and the maximum extension angle parameter value of the target training part.

[0124] The fatigue warning submodule is specifically used to obtain the current flexion-extension angle range based on the maximum flexion angle parameter value and the maximum extension angle parameter value; and to determine whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range.

[0125] Optionally, the reference flexion-extension angle range is the previously determined flexion-extension angle range. Accordingly, the fatigue warning submodule is specifically used to determine that the fatigue warning condition is met if the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a first ratio.

[0126] Optionally, the reference flexion-extension angle range is an initially determined flexion-extension angle range. Accordingly, the fatigue warning submodule is specifically used to determine that the fatigue warning condition is met if the ratio of the current flexion-extension angle range to the initially determined maximum flexion-extension angle range is less than any warning threshold in the preset warning ratio set; wherein, the preset warning ratio set range includes multiple warning thresholds.

[0127] The fatigue determination submodule is specifically used to determine that the fatigue determination condition is met when the reference flexion-extension angle range is the previously determined flexion-extension angle range, and the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a second ratio value. Alternatively, when the reference flexion-extension angle range is the initially determined flexion-extension angle range, it is determined that the fatigue determination condition is met when the ratio of the current flexion-extension angle range to the initially determined flexion-extension angle range is less than any fatigue determination threshold in the preset fatigue determination threshold set.

[0128] Optionally, the degree of stretching parameter can also be the electromyographic signal characteristics of the target training area. Accordingly, the acquired degree of stretching parameter value is the electromyographic signal characteristic value.

[0129] The fatigue warning submodule is specifically used to determine that the fatigue warning condition is met if the current electromyographic signal feature value of the target training site is less than the reference electromyographic signal feature value.

[0130] The fatigue determination submodule is specifically used to calculate the current effective value of the electromyography signal based on the characteristic value of the electromyography signal. If the current effective value of the electromyography signal is less than the effective value of the reference electromyography signal, then the fatigue determination condition is met.

[0131] The device may further include an initial stimulation parameter value generation module, which is used to obtain the initial stimulation parameter value in the following manner: gradually increasing the stimulation parameter value from an initial set value while simultaneously acquiring the contraction degree parameter value of the muscle in the target training area; if the contraction degree parameter value meets a preset condition, then the stimulation parameter value corresponding to the contraction degree parameter value that meets the preset condition is used as the initial stimulation parameter value; wherein, the preset condition is that the contraction degree parameter value is greater than a preset parameter value or the contraction degree parameter value remains unchanged within a preset time.

[0132] Optionally, the stimulus adjustment module 303 is specifically used to make the adjusted stimulus parameter value equal to the product of the initial stimulus parameter value and the proportional adjustment factor. The proportional adjustment factor is the ratio of the current stretching parameter value to the initial stretching parameter value.

[0133] Wherein, when the degree of extension parameter is the flexion-extension angle of the target training part, the degree of extension parameter is the maximum flexion-extension angle range; when the degree of extension parameter is the electromyographic signal characteristic value of the target training part, the degree of extension parameter is the difference between the effective value of the electromyographic signal and the background noise of the electromyographic signal.

[0134] Optionally, the target training area includes: hand, wrist, elbow joint or knee joint;

[0135] Optionally, the device also includes a stimulation-relaxation control module, which, if it is determined that the muscle fatigue condition is met, outputs muscle relaxation stimulation while outputting electromyographic flexion-extension stimulation.

[0136] Figure 4 This is a schematic diagram of the electromyography (EMG) stimulation rehabilitation training device provided in Embodiment 3 of the present invention. The rehabilitation training device 40 includes a memory 41, a processor 42, and a computer program stored in the memory 41 and executable on the processor 42. When the processor 42 executes the program, it implements the technical solution described in the foregoing method.

[0137] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or grid device, etc.) to execute the methods described in the various embodiments of the present invention.

[0138] It is worth noting that in the embodiments of the above-mentioned rehabilitation training device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0139] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A myoelectric stimulation rehabilitation training device, used for limb joint muscle rehabilitation training, characterized in that, include: The stimulation and acquisition module is used to stimulate the muscles of the target training area according to the current stimulation parameter values, and to acquire the training contraction degree parameter values ​​of the muscles in real time. The stimulation parameter is the stimulation output power; The fatigue judgment module is used to determine whether the muscle fatigue condition is met based on the current stimulus parameter value and the training stretching degree parameter value. The stimulation adjustment module is used to adjust the current stimulation parameter value if the muscle fatigue condition is met. The loop control module is used to control the aforementioned modules to perform rehabilitation training according to the adjusted stimulus parameter values ​​until the end of training conditions are met. The fatigue assessment module includes a fatigue early warning submodule and a fatigue determination submodule; The fatigue warning submodule is used to determine whether the muscles of the target training part meet the fatigue warning conditions under the action of the current stimulation parameter value, based on the training stretching degree parameter value. The fatigue determination submodule is used to control the target training part to perform N maximum voluntary flexion and extension movements if the fatigue warning condition is met, and to collect the voluntary extension degree parameter value of each maximum voluntary flexion and extension movement in real time; N is greater than or equal to 1; and to determine whether the fatigue judgment condition is met based on the voluntary extension degree parameter value and the reference extension degree parameter value. If the fatigue judgment condition is met, it is determined that the muscle fatigue condition is met. The degree of extension parameter is the flexion and extension angle of the target training part; Accordingly, the collected extension and contraction parameter values ​​include: the maximum flexion angle parameter value and the maximum extension angle parameter value of the target training part; The fatigue warning submodule is specifically used to obtain the current flexion-extension angle range based on the maximum flexion angle parameter value and the maximum extension angle parameter value; and to determine whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range.

2. The apparatus according to claim 1, characterized in that, The reference flexion-extension angle range is the previously determined flexion-extension angle range. Accordingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range includes: If the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a first ratio, then the fatigue warning condition is determined to be met.

3. The apparatus according to claim 1, characterized in that, The reference flexion-extension angle range is an initially determined flexion-extension angle range. Accordingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range includes: If the ratio of the current flexion-extension angle range to the initially determined maximum flexion-extension angle range is less than any warning threshold in the preset warning ratio set, then the fatigue warning condition is determined to be met; wherein, the preset warning ratio set range includes multiple warning thresholds.

4. The apparatus according to claim 1, characterized in that, The fatigue determination submodule is specifically used to determine that the fatigue determination condition is met when the reference flexion-extension angle range is the previously determined flexion-extension angle range, and the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a second ratio value; or when the reference flexion-extension angle range is the initially determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the initially determined flexion-extension angle range is less than any fatigue determination threshold in the preset fatigue determination threshold set, then the fatigue determination condition is met.

5. The apparatus according to claim 1, characterized in that, The degree of stretching parameter is the electromyographic signal characteristic of the target training area; correspondingly, the collected degree of stretching parameter value is the electromyographic signal characteristic value; The fatigue warning submodule is specifically used to determine that the fatigue warning condition is met if the current electromyographic signal feature value of the target training site is less than the reference electromyographic signal feature value. The fatigue determination submodule is specifically used to calculate the current effective value of the electromyography signal based on the characteristic value of the electromyography signal. If the current effective value of the electromyography signal is less than the effective value of the reference electromyography signal, then the fatigue determination condition is met.

6. The apparatus according to any one of claims 1 to 5, characterized in that, The device further includes an initial stimulation parameter value generation module, which is used to obtain the initial stimulation parameter value in the following manner: gradually increasing the stimulation parameter value from an initial set value while simultaneously collecting the contraction degree parameter value of the muscle in the target training area; if the contraction degree parameter value meets a preset condition, then the stimulation parameter value corresponding to the contraction degree parameter value that meets the preset condition is used as the initial stimulation parameter value; wherein, the preset condition is that the contraction degree parameter value is greater than a preset parameter value or the contraction degree parameter value remains unchanged within a preset time.

7. The apparatus according to claim 6, characterized in that, The stimulus adjustment module is specifically used to make the adjusted stimulus parameter value equal to the product of the initial stimulus parameter value and the proportional adjustment factor; wherein, the proportional adjustment factor is the ratio of the current stretching parameter value to the initial stretching parameter value; Wherein, when the degree of extension parameter is the flexion-extension angle of the target training part, the degree of extension parameter is the maximum flexion-extension angle range; when the degree of extension parameter is the electromyographic signal characteristic value of the target training part, the degree of extension parameter is the difference between the effective value of the electromyographic signal and the background noise of the electromyographic signal.

8. The apparatus according to claim 7, characterized in that, The target training areas include: hand, wrist, elbow joint, or knee joint.

9. The apparatus according to claim 7, characterized in that, The device also includes a stimulation-relaxation control module, which, if it is determined that the muscle fatigue condition is met, outputs muscle relaxation stimulation at the same time as outputting electromyographic flexion-extension stimulation.

10. A myoelectric stimulation rehabilitation training device, characterized in that, include: A memory and a processor, the memory storing a computer program, the processor running the computer program to implement the following electromyographic stimulation rehabilitation training method, the method comprising: The muscles of the target training area are stimulated according to the current stimulation parameter values, and the training contraction degree parameter values ​​of the muscles are collected in real time; the stimulation parameter is the stimulation output power. Determine whether the muscle fatigue condition is met based on the current stimulation parameter value and the training stretching degree parameter value. If so, adjust the current stimulus parameter value, and then repeat the aforementioned steps to perform rehabilitation training according to the adjusted stimulus parameter value until the end of training conditions are met; The step of determining whether the muscle fatigue condition is met based on the current stimulus parameter value and the training stretching parameter value includes: Based on the training stretching parameter value, determine whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value; If the fatigue warning condition is met, the target training part is controlled to perform N maximum voluntary flexion and extension movements, and the voluntary extension and contraction degree parameter value of each maximum voluntary flexion and extension movement is collected in real time; N is greater than or equal to 1. Based on the autonomous stretching degree parameter value and the reference stretching degree parameter value, it is determined whether the fatigue judgment condition is met. If the fatigue judgment condition is met, then the muscle fatigue condition is determined to be met. The degree of extension parameter is the flexion and extension angle of the target training part; Accordingly, the collected extension and contraction parameter values ​​include: the maximum flexion angle parameter value and the maximum extension angle parameter value of the target training part; The step of determining whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value based on the training stretching degree parameter value includes: The current flexion-extension angle range is obtained based on the maximum flexion angle parameter value and the maximum extension angle parameter value; Determine whether the fatigue warning conditions are met based on the current flexion-extension angle range and the reference flexion-extension angle range.

11. The device according to claim 10, characterized in that, The reference flexion-extension angle range is the previously determined flexion-extension angle range. Accordingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range includes: If the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a first ratio, then the fatigue warning condition is determined to be met.

12. The device according to claim 10, characterized in that, The reference flexion-extension angle range is an initially determined flexion-extension angle range. Accordingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range includes: If the ratio of the current flexion-extension angle range to the initially determined maximum flexion-extension angle range is less than any warning threshold in the preset warning ratio set, then the fatigue warning condition is determined to be met; wherein, the preset warning ratio set range includes multiple warning thresholds.

13. The device according to claim 10, characterized in that, The step of determining whether the fatigue judgment condition is met based on the autonomous stretching degree parameter value and the reference stretching degree parameter value includes: When the reference flexion-extension angle range is the previously determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than the second ratio, then the fatigue determination condition is satisfied. When the reference flexion-extension angle range is the initially determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the initially determined flexion-extension angle range is less than any fatigue judgment threshold in the preset fatigue judgment threshold set, then the fatigue judgment condition is determined to be met.

14. The device according to claim 10, characterized in that, The degree of stretching parameter is the electromyographic signal characteristic of the target training area; correspondingly, the collected degree of stretching parameter value is the electromyographic signal characteristic value; The step of determining whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value based on the training stretching degree parameter value includes: If the current electromyographic signal characteristic value of the target training area is less than the reference electromyographic signal characteristic value, then the fatigue warning condition is determined to be met. The step of determining whether the fatigue judgment condition is met based on the autonomous stretching degree parameter value and the reference stretching degree parameter value includes: The current effective value of the electromyography signal is calculated based on the characteristic value of the electromyography signal. If the current effective value of the electromyography signal is less than the effective value of the reference electromyography signal, then the fatigue determination condition is met.

15. The device according to any one of claims 10 to 14, characterized in that, The method further includes: The initial stimulus parameter values ​​are obtained as follows: The stimulation parameter value is gradually increased from the initial setting value while the contraction and relaxation parameter value of the muscle in the target training area is collected simultaneously. If the stretching degree parameter value meets the preset condition, then the stimulation parameter value corresponding to the stretching degree parameter value that meets the preset condition is used as the initial stimulation parameter value. The preset condition is that the value of the stretchability parameter is greater than a preset parameter value or the value of the stretchability parameter remains unchanged within a preset time.

16. The device according to claim 15, characterized in that, Adjusting the current stimulus parameter value includes: The adjusted stimulus parameter value is equal to the product of the initial stimulus parameter value and the proportional adjustment factor; wherein, the proportional adjustment factor is the ratio of the current stretching parameter value to the initial stretching parameter value; Wherein, when the degree of extension parameter is the flexion-extension angle of the target training part, the degree of extension parameter is the maximum flexion-extension angle range; when the degree of extension parameter is the electromyographic signal characteristic value of the target training part, the degree of extension parameter is the difference between the effective value of the electromyographic signal and the background noise of the electromyographic signal.

17. The device according to claim 16, characterized in that, The target training areas include: hand, wrist, elbow joint, or knee joint.

18. The device according to claim 16, characterized in that, The method further includes: if it is determined that the muscle fatigue condition is met, then simultaneously outputting muscle relaxation stimulation while outputting electromyographic flexion-extension stimulation.

19. A computer-readable storage medium having a computer program stored thereon, characterized in that... When executed by the processor, the program implements the following electromyographic stimulation rehabilitation training method, the method comprising: The muscles of the target training area are stimulated according to the current stimulation parameter values, and the training contraction degree parameter values ​​of the muscles are collected in real time; the stimulation parameter is the stimulation output power. Determine whether the muscle fatigue condition is met based on the current stimulation parameter value and the training stretching degree parameter value. If so, adjust the current stimulus parameter value, and then repeat the aforementioned steps to perform rehabilitation training according to the adjusted stimulus parameter value until the end of training conditions are met; The step of determining whether the muscle fatigue condition is met based on the current stimulus parameter value and the training stretching parameter value includes: Based on the training stretching parameter value, determine whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value; If the fatigue warning condition is met, the target training part is controlled to perform N maximum voluntary flexion and extension movements, and the voluntary extension and contraction degree parameter value of each maximum voluntary flexion and extension movement is collected in real time; N is greater than or equal to 1. Based on the autonomous stretching degree parameter value and the reference stretching degree parameter value, it is determined whether the fatigue judgment condition is met. If the fatigue judgment condition is met, then the muscle fatigue condition is determined to be met. The degree of extension parameter is the flexion and extension angle of the target training part; Accordingly, the collected extension and contraction parameter values ​​include: the maximum flexion angle parameter value and the maximum extension angle parameter value of the target training part; The step of determining whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value based on the training stretching degree parameter value includes: The current flexion-extension angle range is obtained based on the maximum flexion angle parameter value and the maximum extension angle parameter value; Determine whether the fatigue warning conditions are met based on the current flexion-extension angle range and the reference flexion-extension angle range.

20. The medium according to claim 19, characterized in that, The reference flexion-extension angle range is the previously determined flexion-extension angle range. Accordingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range includes: If the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than a first ratio, then the fatigue warning condition is determined to be met.

21. The medium according to claim 19, characterized in that, The reference flexion-extension angle range is an initially determined flexion-extension angle range. Accordingly, determining whether the fatigue warning condition is met based on the current flexion-extension angle range and the reference flexion-extension angle range includes: If the ratio of the current flexion-extension angle range to the initially determined maximum flexion-extension angle range is less than any warning threshold in the preset warning ratio set, then the fatigue warning condition is determined to be met; wherein, the preset warning ratio set range includes multiple warning thresholds.

22. The medium according to claim 19, characterized in that, The step of determining whether the fatigue judgment condition is met based on the autonomous stretching degree parameter value and the reference stretching degree parameter value includes: When the reference flexion-extension angle range is the previously determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the previously determined flexion-extension angle range is less than the second ratio, then the fatigue determination condition is satisfied. When the reference flexion-extension angle range is the initially determined flexion-extension angle range, if the ratio of the current flexion-extension angle range to the initially determined flexion-extension angle range is less than any fatigue judgment threshold in the preset fatigue judgment threshold set, then the fatigue judgment condition is determined to be met.

23. The medium according to claim 19, characterized in that, The degree of stretching parameter is the electromyographic signal characteristic of the target training area; correspondingly, the collected degree of stretching parameter value is the electromyographic signal characteristic value; The step of determining whether the muscles of the target training area meet the fatigue warning conditions under the action of the current stimulation parameter value based on the training stretching degree parameter value includes: If the current electromyographic signal characteristic value of the target training area is less than the reference electromyographic signal characteristic value, then the fatigue warning condition is determined to be met. The step of determining whether the fatigue judgment condition is met based on the autonomous stretching degree parameter value and the reference stretching degree parameter value includes: The current effective value of the electromyography signal is calculated based on the characteristic value of the electromyography signal. If the current effective value of the electromyography signal is less than the effective value of the reference electromyography signal, then the fatigue determination condition is met.

24. The medium according to any one of claims 19 to 23, characterized in that, The method further includes: The initial stimulus parameter values ​​are obtained as follows: The stimulation parameter value is gradually increased from the initial setting value while the contraction and relaxation parameter value of the muscle in the target training area is collected simultaneously. If the stretching degree parameter value meets the preset condition, then the stimulation parameter value corresponding to the stretching degree parameter value that meets the preset condition is used as the initial stimulation parameter value. The preset condition is that the value of the stretchability parameter is greater than a preset parameter value or the value of the stretchability parameter remains unchanged within a preset time.

25. The medium according to claim 24, characterized in that, Adjusting the current stimulus parameter value includes: The adjusted stimulus parameter value is equal to the product of the initial stimulus parameter value and the proportional adjustment factor; wherein, the proportional adjustment factor is the ratio of the current stretching parameter value to the initial stretching parameter value; Wherein, when the degree of extension parameter is the flexion-extension angle of the target training part, the degree of extension parameter is the maximum flexion-extension angle range; when the degree of extension parameter is the electromyographic signal characteristic value of the target training part, the degree of extension parameter is the difference between the effective value of the electromyographic signal and the background noise of the electromyographic signal.

26. The medium according to claim 25, characterized in that, The target training areas include: hand, wrist, elbow joint, or knee joint.

27. The medium according to claim 25, characterized in that, The method further includes: if it is determined that the muscle fatigue condition is met, then simultaneously outputting muscle relaxation stimulation while outputting electromyographic flexion-extension stimulation.

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