Lower limb joint rehabilitation training process monitoring system and method based on feedback analysis

Abstract

The present invention discloses a lower limb joint rehabilitation training process monitoring system and method based on feedback analysis, and belongs to the field of electronic digital data processing. The present invention imports the gait data obtained in the lower limb training process into a gait rehabilitation analysis model to perform gait rehabilitation analysis, obtains the physique change information in the training process and imports it into a matching analysis model to perform matching analysis in the training process, obtains the gait rehabilitation analysis results and the training matching analysis results and imports them into a training rehabilitation analysis strategy to perform training rehabilitation analysis, performs early warning of the training process according to the obtained training rehabilitation analysis results, comprehensively analyzes abnormal situations occurring in the training process based on the physique change information and gait rehabilitation information in the lower limb training process, thereby improving the speed of discovering the mismatch between training equipment and training personnel, and improving the accuracy and safety of the training process.

Description

Technical Field

[0001] The invention belongs to the field of electronic digital data processing, and in particular relates to a lower limb joint rehabilitation training process monitoring system and method based on feedback analysis. Background Art

[0002] The lower limb joint rehabilitation device is based on the theory of continuous passive motion. It simulates the natural movement of the human body, stimulates the natural resilience of the human body, exerts the compensatory effect of tissues, and performs lower limb joint function recovery training. The working principle of the lower limb joint rehabilitation device is based on the theory of continuous passive motion (CPM). It simulates the natural movement of the human body, drives the affected limb to do continuous passive flexion and extension movements, makes the pressure in the joints and muscles change periodically and sinusoidally, promotes the return of blood and lymph liquefied gas, thereby minimizing or avoiding the contracture of muscle soft tissues and the degenerative changes of fibrous adhesions and cartilage in the joints, and improving the range of motion of the joints. The following points should be noted when using the lower limb joint rehabilitation device: First, it needs to be performed under the guidance of a professional doctor. First, ensure the safety and effectiveness of the training; secondly, formulate a personalized training plan according to the patient's specific situation and rehabilitation goals to avoid injuries caused by overtraining; finally, pay attention to the maintenance and maintenance of the equipment to ensure the normal operation of the equipment and extend its service life. Scientific and effective rehabilitation training can help patients restore the function of their lower limb joints and improve their quality of life. However, when users use lower limb joint rehabilitation devices, the existing technology cannot comprehensively analyze the abnormal conditions that occur during the training process based on the physical changes and gait rehabilitation information during the lower limb training process, which makes it easy for the training equipment to not match the trainer, thereby causing secondary injuries. Most of the existing technologies have the above problems.

[0003] The above patents all have the problems raised by this background technology. In order to solve the problems raised by this background technology, this application designs a lower limb joint rehabilitation training process monitoring system and method based on feedback analysis. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention proposes a lower limb joint rehabilitation training process monitoring system and method based on feedback analysis.

[0005] To achieve the above object, the present invention provides the following technical solutions: In a first aspect, the present invention provides a method for monitoring the lower limb joint rehabilitation training process based on feedback analysis, which comprises the following specific steps:

[0006] Step 1: Acquire gait data during lower limb training, and simultaneously acquire physical fitness change data during lower limb training;

[0007] Step 2: Importing the acquired gait data during the lower limb training process into a gait rehabilitation analysis model for gait rehabilitation analysis;

[0008] Step 3: Obtain the physical fitness change information during the training process and import it into the matching analysis model to perform matching analysis during the training process;

[0009] Step 4: Obtain gait rehabilitation analysis results and training matching analysis results, import them into training rehabilitation analysis strategy to conduct training rehabilitation analysis, and issue early warning for the training process based on the obtained training rehabilitation analysis results.

[0010] Furthermore, the specific steps of acquiring the gait data during the lower limb training process in step 1 and acquiring the physical fitness change data during the lower limb training process are:

[0011] S11, installing a lower limb training device at a designated position of the patient's lower limbs, and obtaining lower limb movement gait data during the lower limb training process through a sensor, wherein the lower limb movement gait data includes position angle data of each joint during the movement process and swing data of each joint during the movement process, wherein the swing data includes swing displacement and swing frequency data, and is stored in a storage module;

[0012] S12, collecting physical data during exercise through a physical change collection terminal, wherein the physical data includes heart rate, blood pressure and other data types that can reflect the patient's physical condition;

[0013] Physical changes during exercise can reflect the degree of adaptation to the exercise state.

[0014] Furthermore, the gait rehabilitation analysis model in step 2 includes the following specific steps:

[0015] S21, acquiring position angle data of each joint during the movement and swing data of each joint during the movement;

[0016] S22, importing the position angle data of each joint in the motion process and the position angle data of each joint in the standard motion into the motion joint abnormal value calculation formula to calculate the motion joint abnormal value, wherein the motion joint abnormal value calculation formula is: , where Mk is the abnormal value of the motion joint, N is the number of movements during the movement, nj is the number of motion joints in the jth movement, ki is the distance from the i-th joint to the middle of the spine when standing upright, and the role of 1 / ki here is to weight the importance of different joints of the lower limbs. The importance of the lower limb joints from top to bottom is definitely getting smaller and smaller, exp() is the power of the natural constant e, and a is the angle ratio coefficient. is the standard value of the angle of the i-th joint in the j-th action, is the angle of the i-th joint in the j-th action, so The difference between the i-th joint of the j-th action and the standard action is analyzed by the difference between the standard value of the angle of the i-th joint of the j-th action and the angle of the i-th joint of the j-th action. sijm is the coordinate of the standard position of the i-th joint of the j-th action in the coordinate system, sij is the position of the i-th joint of the j-th action, and hij is the safe distance of the i-th joint of the j-th action.

[0017] S23, obtaining the swing data of each joint during the movement and importing it into the swing abnormal value calculation formula to calculate the swing abnormal value, wherein the swing abnormal value calculation formula is: , where cij is the number of swings of the i-th joint in the j-th action, dij is the average swing amplitude of the i-th joint in the j-th action, cijm is the safe number of swings of the i-th joint in the j-th action, dijm is the safe swing amplitude of the i-th joint in the j-th action, and S is the swing abnormality value;

[0018] S24, importing the obtained motion joint abnormal value and swing abnormal value into the gait rehabilitation analysis value calculation formula to calculate the gait rehabilitation analysis value, wherein the gait rehabilitation analysis value calculation formula is: , where z is the abnormal proportion of motion joints and kf is the gait rehabilitation analysis value.

[0019] Through this step, the gait data during the lower limb training process is comprehensively analyzed to obtain the comprehensive analysis results of the gait data during the training process.

[0020] Furthermore, the step 3 of obtaining the physical fitness change information during the training process and importing it into the matching analysis model to perform matching analysis during the training process includes the following specific steps:

[0021] S31, obtaining the physical fitness change information during the training process and the physical fitness change information at the beginning without training;

[0022] S32, importing the physical fitness change information during the training process and the physical fitness change information at the beginning of the training into the motion matching value calculation formula to calculate the motion matching value, wherein the motion matching value calculation formula is: , where T is the start time of training, t1 is the training duration, G is the number of physical data types, pg is the proportion coefficient of the g-th physical data type, xgt is the specific value of the g-th physical data type at time t, xgtm is the median of the safety range of the g-th physical data type, so |xgt-xgtm| is the difference between the specific value of the g-th physical data type at time t and the median of the safety range, dt is the time integral, and P is the motion matching value.

[0023] Furthermore, the step 4 of obtaining the gait rehabilitation analysis results and the training matching analysis results and importing them into the training rehabilitation analysis strategy for training rehabilitation analysis includes the following specific contents:

[0024] Obtain the calculated gait rehabilitation analysis value and motion matching value and substitute them into the training rehabilitation analysis value calculation formula to calculate the training rehabilitation analysis value, wherein the training rehabilitation analysis value calculation formula is: ,in, is the gait rehabilitation ratio, is the motion matching coefficient, and Zw is the training rehabilitation analysis value.

[0025] Furthermore, the step 4 of providing early warning of the training process according to the obtained training and rehabilitation analysis results includes the following specific contents:

[0026] The obtained training rehabilitation analysis value is compared with the set training rehabilitation analysis threshold. If the training rehabilitation analysis value is less than or equal to the set training rehabilitation analysis threshold, an unsafe training process warning is issued to remind maintenance personnel to repair the training equipment. If the training rehabilitation analysis value is greater than the set training rehabilitation analysis threshold, it indicates that the training process is safe.

[0027] In a second aspect, the present invention provides a lower limb joint rehabilitation training process monitoring system based on feedback analysis, which is implemented based on the above-mentioned lower limb joint rehabilitation training process monitoring method based on feedback analysis, and specifically includes a data acquisition module, a gait rehabilitation analysis module, a physical fitness matching analysis module, a training process early warning module and a control module;

[0028] The data acquisition module is used to acquire gait data during lower limb training and simultaneously acquire physical fitness change data during lower limb training;

[0029] The gait rehabilitation analysis module is used to import the acquired gait data during the lower limb training process into the gait rehabilitation analysis model to perform gait rehabilitation analysis;

[0030] The physical fitness matching analysis module is used to obtain physical fitness change information during training and import it into the matching analysis model to perform matching analysis during training;

[0031] The training process warning module is used to obtain gait rehabilitation analysis results and training matching analysis results, import them into the training rehabilitation analysis strategy to perform training rehabilitation analysis, and issue a training process warning based on the obtained training rehabilitation analysis results;

[0032] The control module is used for controlling the operation of the data acquisition module, the gait rehabilitation analysis module, the physique matching analysis module and the training process early warning module.

[0033] In a third aspect, the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0034] The processor executes the above-mentioned method for monitoring the lower limb joint rehabilitation training process based on feedback analysis by calling the computer program stored in the memory.

[0035] In a fourth aspect, the present invention provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute the method for monitoring the lower limb joint rehabilitation training process based on feedback analysis as described above.

[0036] Compared with the prior art, the beneficial effects of this application are:

[0037] The present application imports the gait data obtained during the lower limb training process into a gait rehabilitation analysis model to perform gait rehabilitation analysis, obtains the physical change information during the training process and imports it into a matching analysis model to perform matching analysis during the training process, obtains the gait rehabilitation analysis results and the training matching analysis results and imports them into a training rehabilitation analysis strategy to perform training rehabilitation analysis, performs early warning of the training process based on the obtained training rehabilitation analysis results, and comprehensively analyzes abnormal situations occurring during the training process by integrating the physical change information during the lower limb training process and the gait rehabilitation information, thereby improving the speed of discovering the mismatch between the training equipment and the trainees, and improving the accuracy and safety of the training process. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the overall flow of the method for monitoring the lower limb joint rehabilitation training process based on feedback analysis of the present invention;

[0039] Figure 2 This is a schematic diagram of step 2 in the method for monitoring the lower limb joint rehabilitation training process based on feedback analysis of the present invention;

[0040] Figure 3 It is a schematic diagram of the overall framework of the lower limb joint rehabilitation training process monitoring system based on feedback analysis of the present invention;

[0041] Figure 4 This is a schematic diagram of joint position analysis for abnormal motion joints according to the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present application and its application or use.

[0043] Example 1

[0044] In order to solve the technical problems raised in the background technology, the present invention provides a preferred embodiment: Figure 1 - Figure 2 As shown, the lower limb joint rehabilitation training process monitoring method based on feedback analysis includes the following specific steps:

[0045] Step 1: Acquire gait data during lower limb training, and simultaneously acquire physical fitness change data during lower limb training;

[0046] In this embodiment, the specific steps of acquiring the gait data during the lower limb training process in step 1 and acquiring the physical fitness change data during the lower limb training process are:

[0047] S11, installing a lower limb training device at a designated position of the patient's lower limbs, and obtaining lower limb movement gait data during the lower limb training process through a sensor, wherein the lower limb movement gait data includes position angle data of each joint during the movement process and swing data of each joint during the movement process, wherein the swing data includes swing displacement and swing frequency data, and is stored in a storage module;

[0048] The position angle data of each joint during exercise and the swing data of each joint during exercise are crucial for the safety analysis of the exercise process. First, the joint position angle data can reflect the bending degree and range of motion of the patient's joints during exercise. These data can help assess whether the joints are within a safe and reasonable range of motion, thereby avoiding injuries such as overextension, sprains or overuse. Second, the joint swing data can provide information about the dynamic changes of the patient's joints during exercise.

[0049] S12, collecting physical data during exercise through a physical change collection terminal, wherein the physical data includes heart rate, blood pressure and other data types that can reflect the patient's physical condition;

[0050] Step 2: Importing the acquired gait data during the lower limb training process into a gait rehabilitation analysis model for gait rehabilitation analysis;

[0051] In this embodiment, the gait rehabilitation analysis model in step 2 includes the following specific steps:

[0052] S21, acquiring position angle data of each joint during the movement and swing data of each joint during the movement;

[0053] S22, importing the position angle data of each joint in the motion process and the position angle data of each joint in the standard motion into the motion joint abnormal value calculation formula to calculate the motion joint abnormal value, wherein the motion joint abnormal value calculation formula is: , where Mk is the abnormal value of the motion joint, N is the number of movements during the movement, nj is the number of motion joints in the jth movement, ki is the distance from the i-th joint to the middle of the spine when standing upright, and the role of 1 / ki here is to weight the importance of different joints of the lower limbs. The importance of the lower limb joints from top to bottom is definitely getting smaller and smaller, exp() is the power of the natural constant e, and a is the angle ratio coefficient. is the standard value of the angle of the i-th joint in the j-th action, is the angle of the i-th joint in the j-th action, so The difference between the i-th joint of the j-th action and the standard action is analyzed by the difference between the standard value of the angle of the i-th joint of the j-th action and the angle of the i-th joint of the j-th action. sijm is the coordinate of the standard position of the i-th joint of the j-th action in the coordinate system, sij is the position of the i-th joint of the j-th action, and hij is the safe distance of the i-th joint of the j-th action. is the distance between the two coordinates, and then divided by hij to calculate the difference between the joint position and the standard position;

[0054] It should be noted that in this embodiment, the coordinate system in this step is as follows: Figure 4 As shown, the patient lies flat on the training device, the coordinate origin is equivalent to the middle of the spine, joint A corresponds to the hip joint of the human body, joints B and joint B1 correspond to the knee joint of the human body, and joints C and joint C1 correspond to the ankle joint of the human body. In this specific embodiment, joints A, joints B and joints C constitute a standard action, joints A, joints B1 and joints C1 constitute the movement action of the operator, and the standard values ​​of the angles of the joints are also shown as the angles of joints A, joints B and joints C. The coordinates of the standard positions of the joints in the coordinate system are shown as the coordinates of joints A, joints B and joints C, and the distance between the two coordinates is shown as the distance B between joint B and joint B1;

[0055] S23, obtaining the swing data of each joint during the movement and importing it into the swing abnormal value calculation formula to calculate the swing abnormal value, wherein the swing abnormal value calculation formula is: , where cij is the number of swings of the i-th joint in the j-th action, dij is the average swing amplitude of the i-th joint in the j-th action, cijm is the safe number of swings of the i-th joint in the j-th action, dijm is the safe swing amplitude of the i-th joint in the j-th action, and S is the swing abnormality value;

[0056] S24, importing the obtained motion joint abnormal value and swing abnormal value into the gait rehabilitation analysis value calculation formula to calculate the gait rehabilitation analysis value, wherein the gait rehabilitation analysis value calculation formula is: , where z is the abnormal proportion of motion joints, and kf is the gait rehabilitation analysis value;

[0057] Step 3: Obtain the physical fitness change information during the training process and import it into the matching analysis model to perform matching analysis during the training process;

[0058] In this embodiment, the step 3 of obtaining the physical fitness change information during the training process and importing it into the matching analysis model for matching analysis during the training process includes the following specific steps:

[0059] S31, obtaining the physical fitness change information during the training process and the physical fitness change information at the beginning without training;

[0060] S32, importing the physical fitness change information during the training process and the physical fitness change information at the beginning of the training into the motion matching value calculation formula to calculate the motion matching value, wherein the motion matching value calculation formula is: , where P is the motion matching value, T is the start time of training, t1 is the training duration, G is the number of physical data types, pg is the proportion coefficient of the g-th physical data type, xgt is the specific value of the g-th physical data type at time t, xgtm is the median of the safety range of the g-th physical data type, so |xgt-xgtm| is the difference between the specific value of the g-th physical data type at time t and the median of the safety range, dt is the time integral, and the exp() here is to prevent the calculation of the negative number in the brackets from causing the formula to take a negative number as a whole. At the same time, the physical abnormality values ​​during the training process and the physical abnormality before the training are calculated by this formula for comparative analysis to evaluate the damage to the physical fitness during the training process, and then evaluate the matching of the training process with the patient's physical fitness;

[0061] Step 4: Obtain gait rehabilitation analysis results and training matching analysis results, import them into the training rehabilitation analysis strategy to perform training rehabilitation analysis, and issue a warning for the training process based on the obtained training rehabilitation analysis results;

[0062] In this embodiment, the step 4 of obtaining the gait rehabilitation analysis results and importing the training matching analysis results into the training rehabilitation analysis strategy for training rehabilitation analysis includes the following specific contents:

[0063] Obtain the calculated gait rehabilitation analysis value and motion matching value and substitute them into the training rehabilitation analysis value calculation formula to calculate the training rehabilitation analysis value, wherein the training rehabilitation analysis value calculation formula is: ,in, is the gait rehabilitation ratio, is the sports matching ratio coefficient, Zw is the training rehabilitation analysis value;

[0064] At the same time, the training process warning in step 4 based on the obtained training and rehabilitation analysis results includes the following specific contents:

[0065] The obtained training rehabilitation analysis value is compared with the set training rehabilitation analysis threshold. If the training rehabilitation analysis value is less than or equal to the set training rehabilitation analysis threshold, an unsafe training process warning is issued to remind maintenance personnel to repair the training equipment. If the training rehabilitation analysis value is greater than the set training rehabilitation analysis threshold, it indicates that the training process is safe.

[0066] It should be noted here that the method for determining the proportion of motion joint abnormalities, angle proportion coefficient, proportion coefficient of the g-th physical data type, gait rehabilitation proportion coefficient, motion matching proportion coefficient and training rehabilitation analysis threshold is as follows: 5000 sets of gait data during lower limb training and physical fitness change data during lower limb training are obtained as the control group, and substituted into the training rehabilitation analysis value calculation formula to calculate the training rehabilitation analysis value, and obtain the judgment result of whether the equipment has caused secondary injury to the human body during the next stage of use, and import the calculated training rehabilitation analysis value and the judgment result of secondary injury into the fitting software, and output the proportion of motion joint abnormalities, angle proportion coefficient, proportion coefficient of the g-th physical data type, gait rehabilitation proportion coefficient, motion matching proportion coefficient and training rehabilitation analysis threshold that meet the maximum secondary injury judgment accuracy.

[0067] The advantages of this embodiment over the prior art are as follows: by importing the gait data obtained during the lower limb training process into the gait rehabilitation analysis model for gait rehabilitation analysis, obtaining the physical change information during the training process and importing it into the matching analysis model for matching analysis during the training process, obtaining the gait rehabilitation analysis results and the training matching analysis results and importing them into the training rehabilitation analysis strategy for training rehabilitation analysis, performing early warning of the training process based on the obtained training rehabilitation analysis results, and comprehensively analyzing abnormal situations occurring during the training process based on the physical change information during the lower limb training process and the gait rehabilitation information, the speed of discovering the mismatch between the training equipment and the trainees is improved, and the accuracy and safety of the training process are improved.

[0068] Example 2

[0069] like Figure 3 As shown, this embodiment provides a lower limb joint rehabilitation training process monitoring system based on feedback analysis, which is implemented based on the above-mentioned lower limb joint rehabilitation training process monitoring method based on feedback analysis, and specifically includes a data acquisition module, a gait rehabilitation analysis module, a physical fitness matching analysis module, a training process early warning module and a control module;

[0070] The data acquisition module is used to acquire gait data during lower limb training and physical fitness change data during lower limb training;

[0071] The gait rehabilitation analysis module is used to import the gait data obtained during the lower limb training process into the gait rehabilitation analysis model to perform gait rehabilitation analysis;

[0072] The physical fitness matching analysis module is used to obtain physical fitness change information during training and import it into the matching analysis model to perform matching analysis during training;

[0073] The training process warning module is used to obtain the gait rehabilitation analysis results and the training matching analysis results and import them into the training rehabilitation analysis strategy to perform training rehabilitation analysis, and to issue a training process warning based on the obtained training rehabilitation analysis results;

[0074] The control module is used for controlling the operation of the data acquisition module, the gait rehabilitation analysis module, the physique matching analysis module and the training process early warning module.

[0075] Example 3

[0076] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0077] The processor executes the above-mentioned lower limb joint rehabilitation training process monitoring method based on feedback analysis by calling the computer program stored in the memory.

[0078] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors and one or more memories, wherein the memories store at least one computer program, and the computer program is loaded and executed by the processor to implement the lower limb joint rehabilitation training process monitoring method based on feedback analysis provided by the above method embodiment. The electronic device may also include other components for realizing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0079] Example 4

[0080] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0081] When the computer program runs on a computer device, the computer device executes the above-mentioned method for monitoring the lower limb joint rehabilitation training process based on feedback analysis.

[0082] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0083] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

Claims

1. A method for monitoring the rehabilitation training process of lower limb joints based on feedback analysis, characterized in that: It includes the following specific steps: Acquire gait data during lower limb training, and simultaneously acquire physical fitness change data during lower limb training; Importing the acquired gait data during the lower limb training process into the gait rehabilitation analysis model for gait rehabilitation analysis; Obtain the physical fitness change information during the training process and import it into the matching analysis model to perform matching analysis during the training process; Obtain gait rehabilitation analysis results and training matching analysis results and import them into the training rehabilitation analysis strategy to perform training rehabilitation analysis, and issue early warnings during the training process based on the obtained training rehabilitation analysis results; The gait rehabilitation analysis model includes the following specific steps: Acquire the position angle data of each joint during the movement and the swing data of each joint during the movement; The position angle data of each joint in the motion process and the position angle data of each joint in the standard motion are introduced into the motion joint abnormal value calculation formula to calculate the motion joint abnormal value, wherein the motion joint abnormal value calculation formula is: , where Mk is the abnormal value of the motion joint, N is the number of movements during the movement, nj is the number of motion joints in the jth movement, ki is the distance from the i-th joint to the middle of the spine when standing upright, exp() is the power of the natural constant e, and a is the angle ratio coefficient. is the standard value of the angle of the i-th joint in the j-th action, is the angle of the i-th joint of the j-th action, sijm is the coordinate of the standard position of the i-th joint of the j-th action in the coordinate system, sij is the coordinate of the position of the i-th joint of the j-th action in the coordinate system, and hij is the safety distance of the i-th joint of the j-th action.

2. The method for monitoring the lower limb joint rehabilitation training process based on feedback analysis according to claim 1, characterized in that: The gait rehabilitation analysis model also includes the following specific steps: The swing data of each joint during the movement is obtained and imported into the swing abnormal value calculation formula to calculate the swing abnormal value, wherein the swing abnormal value calculation formula is: , where cij is the number of swings of the i-th joint in the j-th action, dij is the average swing amplitude of the i-th joint in the j-th action, cijm is the safe number of swings of the i-th joint in the j-th action, dijm is the safe swing amplitude of the i-th joint in the j-th action, and S is the swing abnormality value; The obtained motion joint abnormal value and swing abnormal value are introduced into the gait rehabilitation analysis value calculation formula to calculate the gait rehabilitation analysis value, wherein the gait rehabilitation analysis value calculation formula is: , where z is the abnormal proportion of motion joints and kf is the gait rehabilitation analysis value.

3. The method for monitoring the lower limb joint rehabilitation training process based on feedback analysis as claimed in claim 2, characterized in that: The step of obtaining the physical fitness change information during the training process and importing it into the matching analysis model to perform matching analysis during the training process includes the following specific steps: Obtain information about changes in physical fitness during training and at the beginning of training; The physical fitness change information during the training process and the physical fitness change information at the beginning of the training are introduced into the motion matching value calculation formula to calculate the motion matching value, wherein the motion matching value calculation formula is: , where T is the start time of training, t1 is the training duration, G is the number of physical data types, pg is the proportion coefficient of the g-th physical data type, xgt is the specific value of the g-th physical data type at time t, xgtm is the median value of the safety range of the g-th physical data type, and P is the motion matching value.

4. The method for monitoring the lower limb joint rehabilitation training process based on feedback analysis as claimed in claim 3, characterized in that: The acquisition of gait rehabilitation analysis results and the importation of training matching analysis results into the training rehabilitation analysis strategy for training rehabilitation analysis includes the following specific contents: Obtain the calculated gait rehabilitation analysis value and motion matching value and substitute them into the training rehabilitation analysis value calculation formula to calculate the training rehabilitation analysis value, wherein the training rehabilitation analysis value calculation formula is: ,in, is the gait rehabilitation ratio, is the motion matching coefficient, and Zw is the training rehabilitation analysis value.

5. The method for monitoring the lower limb joint rehabilitation training process based on feedback analysis as claimed in claim 4, characterized in that: The training process early warning according to the obtained training rehabilitation analysis results includes the following specific contents: The obtained training rehabilitation analysis value is compared with the set training rehabilitation analysis threshold. If the training rehabilitation analysis value is less than or equal to the set training rehabilitation analysis threshold, an unsafe training process warning is issued to remind maintenance personnel to repair the training equipment. If the training rehabilitation analysis value is greater than the set training rehabilitation analysis threshold, it indicates that the training process is safe.

6. The method for monitoring the lower limb joint rehabilitation training process based on feedback analysis as claimed in claim 5, characterized in that: The specific steps of acquiring the gait data during the lower limb training process and acquiring the physical fitness change data during the lower limb training process are: The lower limb training device is installed at a designated position of the patient's lower limbs, and the lower limb movement gait data during the lower limb training process is obtained through the sensor, wherein the lower limb movement gait data includes the position angle data of each joint during the movement process and the swing data of each joint during the movement process, wherein the swing data includes the swing displacement and the swing frequency data, which are stored in the storage module; The physical fitness data during exercise is collected through the physical fitness change collection terminal.

7. A lower limb joint rehabilitation training process monitoring system based on feedback analysis, which is implemented based on the lower limb joint rehabilitation training process monitoring method based on feedback analysis as claimed in any one of claims 1 to 6, characterized in that: It specifically includes a data acquisition module, a gait rehabilitation analysis module, a physical fitness matching analysis module, a training process warning module and a control module; The data acquisition module is used to acquire gait data during lower limb training and simultaneously acquire physical fitness change data during lower limb training; The gait rehabilitation analysis module is used to import the acquired gait data during the lower limb training process into the gait rehabilitation analysis model to perform gait rehabilitation analysis; The physical fitness matching analysis module is used to obtain physical fitness change information during training and import it into the matching analysis model to perform matching analysis during training; The training process warning module is used to obtain gait rehabilitation analysis results and training matching analysis results, import them into the training rehabilitation analysis strategy to perform training rehabilitation analysis, and issue a training process warning based on the obtained training rehabilitation analysis results; The control module is used for controlling the operation of the data acquisition module, the gait rehabilitation analysis module, the physique matching analysis module and the training process early warning module.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the lower limb joint rehabilitation training process monitoring method based on feedback analysis as described in any one of claims 1-6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute the method for monitoring the lower limb joint rehabilitation training process based on feedback analysis as described in any one of claims 1-6.

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