Rehabilitation training control method, system and equipment and storage medium

Abstract

The invention provides a rehabilitation training control method, system and device and a storage medium. The method comprises the following steps: determining a movable area of a target patient during rehabilitation training according to a pose state of the target patient during rehabilitation training, trajectory information of the target patient and a preset rehabilitation training trajectory; determining a plurality of dynamic boundaries for adjusting the moving trajectory of the target patient in rehabilitation training; according to a preset rehabilitation training track and the track information, determining a confidence interval boundary of the preset rehabilitation training track during angle adjustment; according to all the dynamic boundaries and the confidence interval boundaries, determining a tolerance interval with a credible moving trajectory when the target patient performs rehabilitation training, and according to the tolerance interval with the credible moving trajectory, controlling the target patient to perform rehabilitation training. By means of the scheme, secondary injury to the rehabilitation part of the target patient in the rehabilitation training process can be avoided.

Description

Technical Field

[0001] The present application relates to the technical field of rehabilitation training, and more specifically, to a rehabilitation training control method, system, device and storage medium. Background Art

[0002] Rehabilitation training is a comprehensive medical and health process aimed at helping individuals who suffer physical, psychological or social functional limitations due to illness, injury or disability to recover or improve their functional abilities. Rehabilitation training can significantly improve an individual's physical function and quality of life. By reducing hospital stays and avoiding re-admissions, rehabilitation training helps reduce medical costs.

[0003] Rehabilitation training control refers to a series of strategies and techniques for managing and adjusting rehabilitation equipment or training programs in order to achieve the expected rehabilitation effect during the rehabilitation training process, thereby improving the efficiency and effectiveness of rehabilitation training while ensuring the safety and personalization of training; in the existing rehabilitation training process, the rehabilitation exerciser in the rehabilitation training equipment is bundled with the rehabilitation part, so that the rehabilitation part moves according to the preset trajectory and drives the rehabilitation exerciser to move, but in the process of the rehabilitation part exercising, if there is a deviation between the preset movement pattern and the actual movement trajectory of the rehabilitation part of the target patient, and the target patient cannot achieve the expected movement trajectory during the actual exercise, the rehabilitation part of the target patient will have excessive rehabilitation activity, which will cause secondary injury and instability of the rehabilitation part. Therefore, how to avoid secondary injury to the rehabilitation part of the target patient during rehabilitation training has become a problem faced by the industry. Summary of the invention

[0004] The present application provides a rehabilitation training control method, system, device and storage medium, which can avoid secondary damage to the rehabilitation parts of target patients during rehabilitation training.

[0005] In a first aspect, the present application provides a rehabilitation training control method for a rehabilitation training device to perform rehabilitation training on a target patient, comprising the following steps: Receive rehabilitation training instructions from target patients and generate preset rehabilitation training trajectories; Determining a movable area of ​​the target patient during rehabilitation training according to the position state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; collecting pressure distribution generated by the exercise part of the target patient during rehabilitation training, and then determining multiple dynamic boundaries for adjusting the running trajectory of the target patient during rehabilitation training according to the pressure distribution and the movable area; Determining the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted based on the angle feature of the running trajectory in the actual trajectory information; The preset rehabilitation training trajectory is adjusted through all dynamic boundaries and the confidence interval limits to obtain a credible tolerance interval of the running trajectory when the target patient is undergoing rehabilitation training, and the target patient is controlled to undergo rehabilitation training according to the credible tolerance interval of the running trajectory.

[0006] In some embodiments, determining the movable area of ​​the target patient during rehabilitation training according to the posture state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory specifically includes: Determining a trajectory deviation of the target patient during rehabilitation training based on the trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; Determine the position and posture of the target patient during rehabilitation training; Inputting the posture state of the target patient during rehabilitation training into the posture analyzer; Determining a plurality of reachable trajectories of the rehabilitation part of the target patient during the movement process according to the posture state and the trajectory deviation; The movable area of ​​the target patient during rehabilitation training is determined based on all reachable trajectories.

[0007] In some embodiments, determining the trajectory deviation of the target patient during rehabilitation training based on the trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory specifically includes: Determine the trajectory information of the target patient during rehabilitation training; Determine the actual running trajectory of the rehabilitation part of the target patient during rehabilitation training according to the trajectory information; The trajectory deviation of the target patient during rehabilitation training is determined through the actual running trajectory of the rehabilitation part and the preset rehabilitation training trajectory.

[0008] In some embodiments, determining multiple dynamic boundaries for adjusting the target patient's running trajectory in rehabilitation training according to the pressure distribution and the movable area specifically includes: Performing a contraction analysis on a preset rehabilitation training track on the rehabilitation display according to the pressure distribution to obtain a contraction track; A plurality of dynamic boundaries for adjusting the running trajectory of a target patient in rehabilitation training are determined by the movable area and the contraction trajectory.

[0009] In some embodiments, determining the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted based on the angle feature of the running trajectory in the actual trajectory information specifically includes: Extracting preset trajectory features from the preset rehabilitation training trajectory; Determining an angle feature of a running trajectory in the actual trajectory information; Fusing the preset trajectory feature and the angle feature to obtain a trajectory fusion feature; The confidence interval limit of the preset rehabilitation training trajectory during angle adjustment is determined by the trajectory fusion feature.

[0010] In some embodiments, the preset rehabilitation training trajectory is adjusted through all dynamic boundaries and the confidence interval limits to obtain a credible tolerance interval of the running trajectory when the target patient performs rehabilitation training, specifically including: Determining a boundary adjustment trajectory of the preset rehabilitation training trajectory according to all dynamic boundaries; The credible tolerance interval of the running trajectory of the target patient during rehabilitation training is determined by the boundary adjustment trajectory and the confidence interval limit.

[0011] In some embodiments, controlling the target patient to perform rehabilitation training according to the credible tolerance interval of the running trajectory specifically includes: Determining a confident rehabilitation trajectory for the target patient to perform rehabilitation training according to the credible tolerance interval of the running trajectory and the preset rehabilitation training trajectory; The confident rehabilitation trajectory is transmitted to the control module of the rehabilitation device, and the control module controls the rehabilitation device to drive the rehabilitation part of the target patient to perform rehabilitation exercises.

[0012] In a second aspect, the present application provides a rehabilitation training control system, comprising: A receiving module, used to receive rehabilitation training instructions from a target patient and generate a preset rehabilitation training trajectory; A processing module, used to determine a movable area of ​​the target patient during rehabilitation training according to the position state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; The processing module is further used to collect the pressure distribution generated by the exercise part of the target patient during the rehabilitation training, and then determine multiple dynamic boundaries used to adjust the running trajectory of the target patient during the rehabilitation training according to the pressure distribution and the movable area; The processing module is further used to determine the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted based on the angle feature of the running trajectory in the actual trajectory information; The execution module is used to adjust the preset rehabilitation training trajectory through all dynamic boundaries and the confidence interval limits, obtain a credible tolerance interval of the running trajectory when the target patient performs rehabilitation training, and control the target patient to perform rehabilitation training according to the credible tolerance interval of the running trajectory.

[0013] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned rehabilitation training control method.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned rehabilitation training control method is implemented.

[0015] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects: In the rehabilitation training control method, system, device and storage medium provided by the present application, firstly, the rehabilitation training instruction of the target patient is received to generate a preset rehabilitation training trajectory; the movable area of ​​the target patient during rehabilitation training is determined according to the posture state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; the pressure distribution generated by the exercise part of the target patient during rehabilitation training is collected, and then multiple dynamic boundaries for adjusting the target patient's running trajectory during rehabilitation training are determined according to the pressure distribution and the movable area; the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted is determined based on the angle feature of the running trajectory in the actual trajectory information; the preset rehabilitation training trajectory is adjusted by all the dynamic boundaries and the confidence interval limits to obtain a credible tolerance interval of the running trajectory of the target patient during rehabilitation training, and the target patient is controlled to perform rehabilitation training according to the credible tolerance interval of the running trajectory.

[0016] It can be seen that in the rehabilitation training control process of the present application, first, by analyzing the trajectory information in combination with the preset rehabilitation training trajectory, the trajectory deviation of the target patient during rehabilitation training is determined, and the trajectory deviation indicates the degree of difference between the actual running trajectory of the rehabilitation part of the target patient during rehabilitation training and the preset rehabilitation training trajectory, which can be used to adjust the training trajectory of the target patient during rehabilitation training; thereby, the movable area of ​​the target patient during rehabilitation training is analyzed according to the trajectory deviation in combination with the posture state of the target patient during rehabilitation training, and the movable area indicates the area to which the target patient can move after adjusting the running trajectory of the rehabilitation part during rehabilitation training, which can be used to determine the running trajectory of the rehabilitation part of the target patient during the next rehabilitation training, which can reduce the secondary injury of the rehabilitation part of the target patient caused by the expected running trajectory being too large; secondly, multiple dynamic boundaries used to adjust the running trajectory of the target patient during rehabilitation training are determined by the pressure distribution and movable area generated by the exercise part, and the dynamic boundary indicates the boundary when the target patient dynamically contracts the preset rehabilitation training trajectory during rehabilitation training, that is, dynamic contraction indicates that the target patient contracts the preset rehabilitation training trajectory during rehabilitation training. The preset rehabilitation training trajectory can be used to adjust the preset rehabilitation training trajectory, thereby reducing the impact of excessive load on the rehabilitation part of the target patient during rehabilitation training; then, the preset rehabilitation training trajectory and trajectory information are fused to obtain the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted. The confidence interval limit indicates the limit of the adjustment range when the target patient performs a credible angle adjustment on the preset rehabilitation training trajectory when actually performing rehabilitation training, and can be used to adjust the running trajectory of the target patient when actually performing rehabilitation training, thereby improving the progress of the target patient during rehabilitation training and promoting the efficiency of the target patient in rehabilitation part training; thus, the preset rehabilitation training trajectory is adjusted through all dynamic boundaries and the confidence interval limit, and a credible tolerance interval of the running trajectory when the target patient performs rehabilitation training is obtained. The credible tolerance interval of the running trajectory indicates the allowable interval of the credible adjustment area when the running trajectory of the target patient is adjusted during rehabilitation training, and can be used to adjust the preset rehabilitation training trajectory to avoid secondary damage to the rehabilitation part during rehabilitation training; finally, the target patient is controlled to perform rehabilitation training according to the credible tolerance interval of the running trajectory. The above scheme can avoid secondary injury to the rehabilitation parts of the target patients during the rehabilitation training process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is an exemplary flow chart of a rehabilitation training control method according to some embodiments of the present application; Figure 2 is an exemplary flow chart of determining trajectory deviation according to some embodiments of the present application; Figure 3 It is a schematic diagram of a credible tolerance interval of a running trajectory according to some embodiments of the present application; Figure 4 is a structural schematic diagram of a rehabilitation training control system according to some embodiments of the present application; Figure 5 It is a structural schematic diagram of a computer device for implementing a rehabilitation training control method according to some embodiments of the present application. DETAILED DESCRIPTION

[0018] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0019] refer to Figure 1 , which is an exemplary flow chart of a rehabilitation training control method according to some embodiments of the present application. The rehabilitation training control method 100 mainly includes the following steps: In step 101, a rehabilitation training instruction of a target patient is received and a preset rehabilitation training trajectory is generated.

[0020] In a specific implementation, the target patient clicks a training button on the rehabilitation display, and a rehabilitation training instruction for the target patient is generated in the background program of the rehabilitation display, wherein the rehabilitation training instruction represents an instruction for performing rehabilitation training on a rehabilitation part of the target patient, and the rehabilitation training instruction is transmitted to the body management system of the target patient, and the body management system generates a preset rehabilitation training trajectory for the target patient, which is transmitted to the rehabilitation display and displayed on the rehabilitation display. The target patient observes the display and trains the rehabilitation part according to the preset rehabilitation training trajectory. In other embodiments, other control methods may also be used, which are not limited here.

[0021] It should be noted that the preset rehabilitation training trajectory in the present application represents the trajectory of the target patient's rehabilitation part that needs to move during rehabilitation training, and can be used to guide the direction of the target patient's running trajectory during rehabilitation training.

[0022] In step 102, the movable area of ​​the target patient during rehabilitation training is determined according to the posture state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory.

[0023] In some embodiments, determining the movable area of ​​the target patient during rehabilitation training according to the posture state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory can be achieved by the following steps: Determining a trajectory deviation of the target patient during rehabilitation training based on the trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; Determine the position and posture of the target patient during rehabilitation training; Inputting the posture state of the target patient during rehabilitation training into the posture analyzer; Determining a plurality of reachable trajectories of the rehabilitation part of the target patient during the movement process according to the posture state and the trajectory deviation; The movable area of ​​the target patient during rehabilitation training is determined based on all reachable trajectories.

[0024] Wherein, in some embodiments, reference Figure 2 As shown in FIG. 1 , this figure is an exemplary flow chart of determining trajectory deviation in some embodiments of the present application. In this embodiment, the trajectory deviation of the target patient during rehabilitation training is determined based on the trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory, which can be implemented by the following steps: First, in step 1021, the trajectory information of the target patient during rehabilitation training is determined; Secondly, in step 1022, the actual running trajectory of the rehabilitation part of the target patient during rehabilitation training is determined according to the trajectory information; Finally, in step 1023, the trajectory deviation of the target patient during rehabilitation training is determined through the actual running trajectory of the rehabilitation part and the preset rehabilitation training trajectory.

[0025] In specific implementation, determining the trajectory information of the target patient during rehabilitation training can be achieved in the following manner, namely: tying the rehabilitation device to the rehabilitation area of ​​the target patient, the target patient exercises according to the preset rehabilitation training trajectory on the rehabilitation display, monitoring the rehabilitation area for training, collecting all running trajectories of the target patient's rehabilitation area during training through a global positioning system (GPS) sensor, and taking the collection of all running trajectories as the trajectory information of the target patient during rehabilitation training, wherein the trajectory information represents the actual running trajectory of the rehabilitation area of ​​the target patient during rehabilitation training; determining the actual running trajectory of the rehabilitation area of ​​the target patient during rehabilitation training based on the trajectory information can be achieved in the following manner, namely: first, using the moving average method in the prior art to convert the trajectory Each running trajectory in the information is smoothed, and then the central trajectory of all the running trajectories after the smoothing is used as the actual running trajectory of the rehabilitation part of the target patient during rehabilitation training, wherein the actual running trajectory of the rehabilitation part represents the running trajectory of the rehabilitation part of the target patient when the target patient actually undergoes rehabilitation training; determining the trajectory deviation of the target patient during rehabilitation training through the actual running trajectory of the rehabilitation part and the preset rehabilitation training trajectory can be achieved in the following manner, namely: calculating the interval between the actual running trajectory of the rehabilitation part and the preset rehabilitation training trajectory through the relative trajectory error method in the prior art, and using the interval as the trajectory deviation of the target patient during rehabilitation training; in other embodiments, other methods can also be used for determination, which are not limited here.

[0026] It should be noted that the trajectory deviation in the present application indicates the degree of difference between the actual running trajectory of the rehabilitation part of the target patient during rehabilitation training and the preset rehabilitation training trajectory, which can be used to adjust the training trajectory of the target patient during rehabilitation training, and can improve the rehabilitation efficiency of the target patient in rehabilitation part training.

[0027] In specific implementation, determining the posture state of the target patient during rehabilitation training can be achieved in the following manner, namely: capturing the posture and activity direction of the target patient during rehabilitation training through a video acquisition device, and using the collection of postures and activity directions as the posture state of the target patient during rehabilitation training, wherein the posture state represents the activity state of the posture of the target patient during rehabilitation training, and inputting the posture state of the target patient during rehabilitation training into a posture analyzer; in other embodiments, other methods may also be used for determination, which are not limited here.

[0028] In specific implementation, the following method can be used to determine the multiple reachable trajectories of the target patient's rehabilitation part during the movement process according to the posture state and the trajectory deviation, namely: the target patient moves the rehabilitation part according to the direction of the trajectory deviation, reduces the trajectory deviation, and thus approaches the expected preset rehabilitation training trajectory. The target patient moves closer to the expected preset rehabilitation training trajectory, but must consider the limit of what he can achieve to avoid secondary injury to the rehabilitation part. In the process of moving the rehabilitation part, the movement method of the activity direction in the posture state is monitored by a video monitoring device, and all the running trajectories of the rehabilitation part after adjusting the moving direction of the target patient's rehabilitation part are monitored by a GPS sensor, and the monitored running trajectories of each rehabilitation part are displayed. The trajectories are all used as reachable trajectories of the rehabilitation part during movement, wherein the reachable trajectory represents the trajectory that the target patient can reach when adjusting the rehabilitation part; determining the movable area of ​​the rehabilitation part according to all reachable trajectories can be achieved in the following manner, namely: extracting the starting point and the ending point of each reachable trajectory, wherein the starting point represents the point when the rehabilitation part of the target patient starts to move according to the trajectory during rehabilitation training, and the ending point represents the point when the rehabilitation part of the target patient ends moving according to the trajectory during rehabilitation training, and the interval composed of all starting points and the collection of the interval composed of all ending points are used as the movable area of ​​the rehabilitation part; in other embodiments, other methods can also be used for determination, which are not limited here.

[0029] It should be noted that the movable area in the present application refers to the area to which the target patient can move after adjusting the running trajectory of the rehabilitation part during rehabilitation training, which can be used to determine the running trajectory of the rehabilitation part of the target patient during the next rehabilitation training, and can reduce the secondary injury to the rehabilitation part of the target patient caused by the expected running trajectory being too large.

[0030] In step 103, the pressure distribution generated by the exercise part of the target patient during rehabilitation training is collected, and then multiple dynamic boundaries for adjusting the running trajectory of the target patient during rehabilitation training are determined according to the pressure distribution and the movable area.

[0031] In specific implementation, the pressure distribution generated by the exercise parts of the target patient during rehabilitation training can be collected in the following manner, namely: a pressure sensor is arranged on the rehabilitation device, and the pressure of each rehabilitation part on the rehabilitation device when the target patient undergoes rehabilitation training is collected through the pressure sensor, and the collected pressures are distributed in the order of their positions on the rehabilitation device, and the distribution result is used as the pressure distribution of the rehabilitation part of the target patient on the rehabilitation device, wherein the pressure distribution represents the distribution of the pressure of the target patient on the rehabilitation device during the rehabilitation part training process; in other embodiments, other methods can also be used for collection, which are not limited here.

[0032] In some embodiments, determining multiple dynamic boundaries for adjusting the target patient's running trajectory in rehabilitation training according to the pressure distribution and the movable area can be implemented by the following steps: Performing a contraction analysis on a preset rehabilitation training track on the rehabilitation display according to the pressure distribution to obtain a contraction track; A plurality of dynamic boundaries for adjusting the running trajectory of a target patient in rehabilitation training are determined by the movable area and the contraction trajectory.

[0033] In specific implementation, a contraction analysis is performed on the preset rehabilitation training trajectory on the rehabilitation display according to the pressure distribution, and the contraction trajectory can be obtained in the following manner, namely: a group of adjacent pressures in the pressure distribution is selected as the selected adjacent pressures, the first pressure in the selected adjacent pressures is subtracted from the second pressure, and the value obtained by subtraction is used as the pressure difference value of the selected adjacent pressures, and the pressure difference values ​​of the remaining groups of adjacent pressures are continued to be determined, wherein the pressure difference value represents the parameter value of the degree of difference between adjacent pressures collected by the target patient during rehabilitation training, the average value of all pressure difference values ​​is calculated, the absolute value of the average value is subjected to a natural exponential operation, the inverse of the value obtained by the natural exponential operation is multiplied by the preset rehabilitation training trajectory, and the trajectory obtained by the multiplication is used as the contraction trajectory, wherein the contraction trajectory represents the trajectory after the preset rehabilitation training trajectory is contracted in combination with the pressure changes of the target patient during the rehabilitation training process, and can be used to predict the trajectory of the target patient during rehabilitation training; in other embodiments, other methods can also be used for determination, which are not limited here.

[0034] In specific implementation, the multiple dynamic boundaries used to adjust the target patient's running trajectory in rehabilitation training determined by the movable area and the contraction trajectory can be implemented in the following manner, namely: initialize a dynamic boundary model, use the movable area as the constraint parameter of the dynamic boundary model, use the contraction trajectory as the initialization parameter of the dynamic boundary model, and output the multiple dynamic boundaries when the preset rehabilitation training trajectory contracts to the actual running trajectory through the dynamic boundary model. The dynamic boundary model is a dynamic boundary model that uses a machine learning algorithm (such as a regression algorithm, a neural network, etc.) to establish a dynamic boundary. The dynamic boundary model is, for example: multiple dynamic boundaries = movable area * A + contraction trajectory * B, wherein A and B are weight coefficients, A and B can be determined based on the collected dynamic boundary experimental data, and can also be determined in other ways in other embodiments, which are not limited here.

[0035] It should be noted that the dynamic boundary in the present application represents the boundary when the target patient dynamically contracts the preset rehabilitation training trajectory during the rehabilitation training process, that is: dynamic contraction means that the target patient contracts the preset rehabilitation training trajectory during the rehabilitation training process, which can be used to adjust the preset rehabilitation training trajectory, thereby reducing the impact of excessive load on the rehabilitation part of the target patient during rehabilitation training.

[0036] In step 104, the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted is determined based on the angle feature of the running trajectory in the actual trajectory information.

[0037] In some embodiments, determining the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted based on the angle feature of the running trajectory in the actual trajectory information can be achieved by the following steps: Extracting preset trajectory features from the preset rehabilitation training trajectory; Determining an angle feature of a running trajectory in the actual trajectory information; Fusing the preset trajectory feature and the angle feature to obtain a trajectory fusion feature; The confidence interval limit of the preset rehabilitation training trajectory during angle adjustment is determined by the trajectory fusion feature.

[0038] In specific implementation, the following method can be used to extract the preset trajectory features from the preset rehabilitation training trajectory, namely: first, the angle, length, and all inflection points of the trajectory in the preset rehabilitation training trajectory are extracted through the deep learning model in the prior art, and then the set of the extracted angles, lengths, and all inflection points are used as the preset trajectory features, wherein the preset trajectory features represent the angles, lengths, inflection points and other features of the preset rehabilitation training trajectory; the following method can be used to determine the angle features of the running trajectory in the actual trajectory information, namely: the angle, length, and all inflection points of each running trajectory in the trajectory information are extracted through the deep learning model in the prior art, and the set of all the extracted angles, lengths, and all inflection points are used as the angle features of the running trajectory in the actual trajectory information, wherein the angle features represent the angles, lengths, inflection points and other features of the actual running trajectory of the target patient in rehabilitation training; in other embodiments, other methods can also be used for determination, which are not limited here.

[0039] In specific implementation, the preset trajectory feature and the angle feature are feature-fused to obtain the trajectory fusion feature, which can be implemented in the following manner, namely: calculate the average value of all angles and the average value of all lengths in the angle feature, subtract the average value of all angles from the angle in the preset trajectory feature, and use the value obtained by subtraction as the angle difference value, subtract the average value of all lengths from the length in the preset trajectory feature, and use the value obtained by subtraction as the length difference value, connect each inflection point in the preset trajectory feature and each inflection point in the angle feature according to adjacent inflection points, fit the connected curve through a polynomial curve fitting trajectory prediction algorithm, and use the slope of the fitted straight line as the inflection point change rate, wherein the inflection point change rate represents the actual running trajectory of the target patient and the preset rehabilitation training The changes of all inflection points on the rehabilitation training trajectory are taken, and the set of angle difference value, length difference value and inflection point change rate is taken as the trajectory fusion feature, wherein the trajectory fusion feature represents the characteristics between the angle, length and inflection point on the actual running trajectory of the target patient and the preset rehabilitation training trajectory, which can be used to adjust the actual running trajectory of the target patient; the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted is determined by the trajectory fusion feature, which can be achieved in the following way, namely: multiplying the length difference value and the inflection point change rate in the trajectory fusion feature, adding the multiplied value to the angle difference value, performing a natural exponential operation on the added value, and taking the reciprocal of the value obtained by the natural exponential operation as the first value, wherein the reciprocal refers to a number multiplied by its reciprocal, which is 1. For example, for a non-zero number a, its reciprocal is 1 / a. The first value plus 1 is multiplied by the angle in the preset trajectory feature, and the value obtained by the multiplication is used as the upper limit value. 1 minus the first value is multiplied by the angle in the preset trajectory feature, and the value obtained by the multiplication is used as the lower limit value. The interval composed of the upper limit value and the lower limit value is used as the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted; in other embodiments, other methods can also be used for determination, which is not limited here.

[0040] It should be noted that the confidence interval limits in the present application represent the limits of the adjustment degree range when the target patient makes a credible angle adjustment to the preset rehabilitation training trajectory during rehabilitation training. Since the target patient's rehabilitation part trajectory does not reach the preset rehabilitation training trajectory during the rehabilitation training process, the preset rehabilitation training trajectory is adjusted to meet the rehabilitation training needs of the target patient. It can be used to adjust the running trajectory of the target patient during actual rehabilitation training, thereby improving the progress of the target patient during rehabilitation training and promoting the efficiency of the target patient in rehabilitation part training.

[0041] In step 105, the preset rehabilitation training trajectory is adjusted through all dynamic boundaries and the confidence interval limits to obtain a credible tolerance interval of the running trajectory when the target patient is undergoing rehabilitation training, and the target patient is controlled to undergo rehabilitation training according to the credible tolerance interval of the running trajectory.

[0042] In some embodiments, the preset rehabilitation training trajectory is adjusted through all dynamic boundaries and the confidence interval limits to obtain a credible tolerance interval of the running trajectory when the target patient is undergoing rehabilitation training, which can be achieved by the following steps: Determining a boundary adjustment trajectory of the preset rehabilitation training trajectory according to all dynamic boundaries; The credible tolerance interval of the running trajectory of the target patient during rehabilitation training is determined by the boundary adjustment trajectory and the confidence interval limit.

[0043] In a specific test, determining the boundary adjustment trajectory of the preset rehabilitation training trajectory according to all dynamic boundaries can be implemented in the following manner, namely: extracting the center point of each dynamic boundary, connecting the adjacent center points of all the center points, and using the connected line as the boundary adjustment trajectory of the target patient in the rehabilitation part training, wherein the boundary adjustment trajectory represents the boundary adjustment trajectory of the target patient when adjusting the preset rehabilitation training trajectory, namely: the trajectory of the boundary range within which the preset rehabilitation training trajectory can be adjusted; determining the credible tolerance interval of the running trajectory of the target patient during rehabilitation training through the boundary adjustment trajectory and the confidence interval limit can be implemented in the following manner, namely: drawing a circle with the difference between the upper limit value and the lower limit value of the confidence interval limit as the radius, sliding the center of the circle along the boundary adjustment trajectory as the path, and using the area passed by the circle as the credible tolerance interval of the running trajectory of the target patient during rehabilitation training, for example: Figure 3 As described, this figure is a schematic diagram of the tolerance range of the credible running trajectory in some embodiments of the present application, such as Figure 3 As described above, both circle 1 and circle 2 have a radius whose confidence interval limit is the confidence interval. The center of circle 1 is slid to circle 2 along the boundary adjustment trajectory. The area included by the dotted line is the tolerance interval of the trajectory credibility. In other embodiments, other methods can also be used to determine, which is not limited here.

[0044] It should be noted that the credible tolerance interval of the running trajectory in the present application represents the allowable interval of the credible adjustment area when the target patient adjusts the running trajectory during rehabilitation training, which can be used to adjust the preset rehabilitation training trajectory to avoid secondary damage to the rehabilitation part during rehabilitation training.

[0045] In some embodiments, controlling the target patient to perform rehabilitation training according to the credible tolerance interval of the running trajectory can be achieved by using the following steps: Determining a confident rehabilitation trajectory for the target patient to perform rehabilitation training according to the credible tolerance interval of the running trajectory and the preset rehabilitation training trajectory; The confident rehabilitation trajectory is transmitted to the control module of the rehabilitation device, and the control module controls the rehabilitation device to drive the rehabilitation part of the target patient to perform rehabilitation exercises.

[0046] In specific implementation, the confident rehabilitation trajectory for rehabilitation training of the target patient can be determined according to the credible tolerance interval of the running trajectory and the preset rehabilitation training trajectory in the following manner, namely: initializing a confident rehabilitation trajectory model, taking the credible tolerance interval of the running trajectory as a constraint parameter of the confident rehabilitation trajectory model, taking the preset rehabilitation training trajectory as an initialization parameter of the confident rehabilitation trajectory model, and outputting the confident rehabilitation trajectory for rehabilitation training of the target patient through the confident rehabilitation trajectory model. The confident rehabilitation trajectory model is a trajectory model of the confident rehabilitation trajectory established by a machine learning algorithm (such as a regression algorithm, a neural network, etc.). For example, the trajectory model is: confident rehabilitation trajectory = credible tolerance interval of the running trajectory * C + preset rehabilitation training trajectory * D, wherein C and D are weight coefficients, C and D can be determined according to the collected rehabilitation training trajectory experimental data, and can also be determined in other ways in other embodiments, which are not limited here.

[0047] It should be noted that the confident rehabilitation trajectory in the present application represents a reliable preset rehabilitation training trajectory for the target patient during rehabilitation training, which can be used to predict the running trajectory of the target patient during rehabilitation training, thereby avoiding secondary damage to the rehabilitation part during rehabilitation training.

[0048] In specific implementation, the confident rehabilitation trajectory is transmitted to the control module of the rehabilitation device, and the control module is used to control the rehabilitation device to drive the rehabilitation part of the target patient to perform rehabilitation training. This can be achieved in the following manner, namely: first, the confident rehabilitation trajectory is transmitted to the control module of the rehabilitation device, and secondly, the control module is used to control the rehabilitation device to operate according to the confident rehabilitation trajectory, thereby driving the rehabilitation part of the target patient to perform rehabilitation training through the rehabilitation device; in other embodiments, other methods can also be used to determine, which are not limited here.

[0049] In addition, in another aspect of the present application, in some embodiments, the present application provides a rehabilitation training control system, referring to Figure 4 , which is a schematic diagram of the structure of a rehabilitation training control system according to some embodiments of the present application. The rehabilitation training control system 400 includes: a receiving module 401, a processing module 402 and an execution module 403, which are described as follows: Receiving module 401, in the present application, the receiving module 401 is mainly used to receive rehabilitation training instructions of a target patient and generate a preset rehabilitation training trajectory; Processing module 402, in the present application, the processing module 402 is used to determine the movable area of ​​the target patient during rehabilitation training according to the posture state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; It should be noted that the processing module 402 in the present application is also used to collect the pressure distribution generated by the exercise part of the target patient during rehabilitation training, and then determine multiple dynamic boundaries for adjusting the running trajectory of the target patient during rehabilitation training according to the pressure distribution and the movable area; In addition, it should be noted that the processing module 402 in the present application is also used to determine the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted based on the angle feature of the running trajectory in the actual trajectory information; Execution module 403. In the present application, execution module 403 is mainly used to adjust the preset rehabilitation training trajectory through all dynamic boundaries and the confidence interval limits, obtain a credible tolerance interval of the running trajectory when the target patient undergoes rehabilitation training, and control the target patient to undergo rehabilitation training according to the credible tolerance interval of the running trajectory.

[0050] In addition, the present application also provides a computer device, which includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute the above-mentioned rehabilitation training control method.

[0051] In some embodiments, reference Figure 5 , which is a schematic diagram of the structure of a computer device for implementing a rehabilitation training control method according to some embodiments of the present application. The rehabilitation training control method in the above embodiment can be Figure 5 The computer device 500 shown in the figure is implemented, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503 and at least one communication interface 504.

[0052] The processor 501 may be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0053] The communication bus 502 may be used to transmit information between the above-mentioned components.

[0054] The memory 503 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including a compressed optical disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 503 may exist independently and be connected to the processor 501 via the communication bus 502. The memory 503 may also be integrated with the processor 501.

[0055] The memory 503 is used to store the program code for executing the solution of the present application, and the execution is controlled by the processor 501. The processor 501 is used to execute the program code stored in the memory 503. The program code may include one or more software modules. The method used in the above embodiment can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0056] The communication interface 504 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0057] In a specific implementation, as an embodiment, a computer device may include multiple processors, each of which may be a single-CPU processor or a multi-CPU processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0058] The above-mentioned computer device may be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device may be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device or an embedded device. The embodiment of the present application does not limit the type of computer device.

[0059] In addition, the present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned rehabilitation training control method is implemented.

[0060] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0061] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A rehabilitation training control method, used for a rehabilitation training device to perform rehabilitation training on a target patient, characterized in that: The method comprises the following steps: Receive rehabilitation training instructions from target patients and generate preset rehabilitation training trajectories; Determining a movable area of ​​the target patient during rehabilitation training according to the position state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; collecting pressure distribution generated by the exercise part of the target patient during rehabilitation training, and then determining multiple dynamic boundaries for adjusting the running trajectory of the target patient during rehabilitation training according to the pressure distribution and the movable area; Determining the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted based on the angle feature of the running trajectory in the actual trajectory information; The preset rehabilitation training trajectory is adjusted through all dynamic boundaries and the confidence interval limits to obtain a credible tolerance interval of the running trajectory when the target patient is undergoing rehabilitation training, and the target patient is controlled to undergo rehabilitation training according to the credible tolerance interval of the running trajectory.

2. The method according to claim 1, characterized in that Determining the movable area of ​​the target patient during rehabilitation training according to the posture state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory specifically includes: Determining a trajectory deviation of the target patient during rehabilitation training based on the trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; Determine the position and posture of the target patient during rehabilitation training; Inputting the posture state of the target patient during rehabilitation training into the posture analyzer; Determining a plurality of reachable trajectories of the rehabilitation part of the target patient during the movement process according to the posture state and the trajectory deviation; The movable area of ​​the target patient during rehabilitation training is determined based on all reachable trajectories.

3. The method according to claim 2, characterized in that Determining the trajectory deviation of the target patient during rehabilitation training based on the trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory specifically includes: Determine the trajectory information of the target patient during rehabilitation training; Determine the actual running trajectory of the rehabilitation part of the target patient during rehabilitation training according to the trajectory information; The trajectory deviation of the target patient during rehabilitation training is determined through the actual running trajectory of the rehabilitation part and the preset rehabilitation training trajectory.

4. The method according to claim 1, characterized in that Determining multiple dynamic boundaries for adjusting the running trajectory of the target patient in rehabilitation training according to the pressure distribution and the movable area specifically includes: Performing a contraction analysis on a preset rehabilitation training track on the rehabilitation display according to the pressure distribution to obtain a contraction track; A plurality of dynamic boundaries for adjusting the running trajectory of a target patient in rehabilitation training are determined by the movable area and the contraction trajectory.

5. The method according to claim 1, characterized in that Determining the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted based on the angle feature of the running trajectory in the actual trajectory information specifically includes: Extracting preset trajectory features from the preset rehabilitation training trajectory; Determining an angle feature of a running trajectory in the actual trajectory information; Performing feature fusion on the preset trajectory feature and the angle feature to obtain a trajectory fusion feature; The confidence interval limit of the preset rehabilitation training trajectory during angle adjustment is determined by the trajectory fusion feature.

6. The method according to claim 1, characterized in that The preset rehabilitation training trajectory is adjusted through all dynamic boundaries and the confidence interval limits to obtain a credible tolerance interval of the running trajectory when the target patient undergoes rehabilitation training, specifically including: Determining a boundary adjustment trajectory of the preset rehabilitation training trajectory according to all dynamic boundaries; The credible tolerance interval of the running trajectory of the target patient during rehabilitation training is determined by the boundary adjustment trajectory and the confidence interval limit.

7. The method according to claim 1, characterized in that Controlling the target patient to perform rehabilitation training according to the credible tolerance interval of the running trajectory specifically includes: Determining a confident rehabilitation trajectory for the target patient to perform rehabilitation training according to the credible tolerance interval of the running trajectory and the preset rehabilitation training trajectory; The confident rehabilitation trajectory is transmitted to the control module of the rehabilitation device, and the control module controls the rehabilitation device to drive the rehabilitation part of the target patient to perform rehabilitation exercises.

8. A rehabilitation training control system, characterized in that: include: A receiving module, used to receive rehabilitation training instructions from a target patient and generate a preset rehabilitation training trajectory; A processing module, used to determine a movable area of ​​the target patient during rehabilitation training according to the position state of the target patient during rehabilitation training and the trajectory deviation between the actual trajectory information of the target patient during rehabilitation training and the preset rehabilitation training trajectory; The processing module is further used to collect the pressure distribution generated by the exercise part of the target patient during the rehabilitation training, and then determine multiple dynamic boundaries used to adjust the running trajectory of the target patient during the rehabilitation training according to the pressure distribution and the movable area; The processing module is further used to determine the confidence interval limit of the preset rehabilitation training trajectory when the angle is adjusted based on the angle feature of the running trajectory in the actual trajectory information; The execution module is used to adjust the preset rehabilitation training trajectory through all dynamic boundaries and the confidence interval limits, obtain a credible tolerance interval of the running trajectory when the target patient performs rehabilitation training, and control the target patient to perform rehabilitation training according to the credible tolerance interval of the running trajectory.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute the rehabilitation training control method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the rehabilitation training control method according to any one of claims 1 to 7 is implemented.

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