Control method for active and passive gait rehabilitation training rope-driven robot

Abstract

The invention belongs to the technical field of gait rehabilitation training, and particularly relates to an active and passive gait rehabilitation training rope-driven robot control method. According to the invention, by acquiring the initial length of each rope and the tension applied by the patient, the rehabilitation training stage can be accurately judged, and corresponding control and posture data correction are carried out, so that the robot is ensured to have high precision in posture adjustment of the patient, and the displacement and posture of the patient can be accurately tracked and corrected; a control strategy can be flexibly adjusted according to the rehabilitation stage of a patient and actually fed back force information, especially when an active training mode and a passive training mode are switched, accurate regulation and control under different modes can be achieved, the training effectiveness is improved, the patient can be helped to gradually recover the gait function by regulating and controlling the tension and length of each rope, and the rehabilitation effect of the patient is improved. Especially in the complex gait training process, the efficiency and accuracy of rehabilitation training can be effectively improved.

Description

Technical Field

[0001] The invention belongs to the technical field of gait rehabilitation training, and in particular relates to a control method of a rope-driven robot for active and passive gait rehabilitation training. Background Art

[0002] In the field of rehabilitation medicine, gait rehabilitation training is an important part of helping patients regain their walking ability. Traditional gait rehabilitation training often relies on the direct guidance and assistance of physical therapists, but this method is not only time-consuming and labor-intensive, but also difficult to achieve accurate and personalized training effects. With the continuous integration of robotics technology and rehabilitation medicine, rope-driven rehabilitation robots, as a new type of rehabilitation training equipment, have gradually become an important tool for gait rehabilitation training due to their high flexibility, good safety, and wide range of applications.

[0003] Existing rope-driven rehabilitation robot control methods are mainly divided into two types: passive training and active training. The passive training control strategy mainly guides the patient's lower limbs to move through preset trajectories and parameters. It is suitable for the early stage of rehabilitation when the patient cannot complete the movement independently. The advantage of this strategy is that it can provide a stable movement trajectory and force support, but it lacks consideration of the patient's active participation, which may lead to limited training effects.

[0004] The active training control strategy focuses more on the active participation of the patient, and drives the robot to move through the patient's muscle strength and willingness. This strategy is suitable for the middle and late stages of rehabilitation, when the patient already has a certain degree of motor ability and autonomy. However, the active training control strategy has high requirements on the robot's response speed and anti-interference ability, and also requires a more precise control system to ensure the safety and effectiveness of training.

[0005] At present, although some researchers have tried to combine active and passive training control strategies to provide personalized rehabilitation training, there are still many problems in practical applications. It is impossible to accurately judge the patient's rehabilitation stage, smoothly switch between active and passive training modes, and ensure the stability and safety of the robot in different training modes. In addition, due to the elasticity, friction and nonlinear factors of the rope during the transmission process, traditional PID controllers often find it difficult to achieve ideal control effects. Summary of the invention

[0006] The purpose of the present invention is to provide a control method for a rope-driven robot for active and passive gait rehabilitation training, which can significantly improve the effect and efficiency of rehabilitation training while ensuring safety and comfort during the rehabilitation process.

[0007] The technical solution adopted by the present invention is as follows:

[0008] A control method for a rope-driven robot for active and passive gait rehabilitation training, comprising:

[0009] Obtain the initial length of each rope of the rope-driven robot terminal platform, obtain the initial posture of the patient according to the initial length of each rope, and obtain the tension applied by the patient to each rope;

[0010] Obtaining the patient's rehabilitation training stage according to the initial length of each rope and the tension applied by each rope, wherein the rehabilitation training stage includes an active stage and a passive stage;

[0011] Acquire the corresponding expected posture according to the rehabilitation training stage, and acquire the corresponding corrected posture data according to the patient's initial posture and the corresponding expected posture;

[0012] Obtaining a corresponding control strategy according to the initial length of each rope, the tension applied to each rope, and the corresponding corrected posture data;

[0013] Gait rehabilitation training is performed on patients according to the corresponding regulation strategies.

[0014] In a preferred embodiment, the steps of obtaining the initial length of each rope of the rope-driven robot terminal platform, obtaining the initial posture of the patient according to the initial length of each rope, and obtaining the tension applied by the patient to each rope include:

[0015] Acquire patient image data on the end platform of the rope-driven robot;

[0016] Acquire the corresponding initial length of each rope according to the patient image data;

[0017] Get the standard length of each rope;

[0018] Obtain the initial position of the patient according to the initial length of each rope and the standard length of each rope;

[0019] Obtain the tension applied by each rope corresponding to the patient's initial posture.

[0020] In a preferred embodiment, the rehabilitation training stage of the patient is obtained according to the initial length of each rope and the tension applied by each rope, wherein the rehabilitation training stage includes the steps of active stage and passive stage, including:

[0021] Obtaining the deflection of each rope according to the initial length of each rope and the corresponding rope applied tension;

[0022] Obtaining the offset threshold value of each rope;

[0023] Determining whether the deviation of each rope exceeds the corresponding rope deviation threshold;

[0024] If the rope offset exceeds the corresponding rope offset threshold, the ropes exceeding the corresponding rope offset threshold are summarized to obtain the number of excess ropes;

[0025] Get the threshold root number;

[0026] Determine whether the number of ropes exceeds a threshold number;

[0027] If the number of ropes exceeds the threshold number, the patient's rehabilitation training stage is determined to be the passive stage;

[0028] If the number of ropes exceeds the threshold number, the patient's rehabilitation training stage is determined to be the active stage.

[0029] In a preferred embodiment, the steps of obtaining the corresponding desired posture according to the rehabilitation training stage and obtaining the corresponding corrected posture data according to the patient's initial posture and the corresponding desired posture include:

[0030] Obtaining the corresponding expected posture for the passive phase according to the patient's rehabilitation training stage, and marking it as the expected passive posture;

[0031] Acquire a corresponding initial posture image according to the initial posture of the patient;

[0032] Acquire a passive posture comparison image according to the expected passive posture;

[0033] The corresponding correction information of each rope is obtained according to the initial posture image and the passive posture comparison image, and summarized as the corrected posture data.

[0034] In a preferred embodiment, the step of obtaining a corresponding control strategy according to the initial length of each rope, the tension applied by each rope and the corresponding corrected posture data includes:

[0035] Obtaining corresponding correction information of each rope according to the corrected posture data, and obtaining corresponding correction length of the rope from the correction information of each rope;

[0036] Constructing a first error period, and obtaining a plurality of historical error lengths of each rope within the first error period;

[0037] Obtain the rope tension corresponding to multiple historical error lengths of each rope, and mark it as rope error tension;

[0038] Obtaining the current error length of each rope according to a plurality of historical error lengths of each rope, a plurality of rope error tensions, and rope applied tensions;

[0039] The rope adjustment length is obtained according to the error length, the rope correction length and the rope initial length;

[0040] The control lengths of multiple ropes are aggregated to obtain a passive control strategy.

[0041] In a preferred embodiment, the step of performing gait rehabilitation training on the patient according to the corresponding control strategy includes:

[0042] Adjust the initial posture of the patient according to the passive control strategy to obtain an adjusted posture;

[0043] Obtain passive rehabilitation training trajectories;

[0044] Perform passive rehabilitation training trajectory according to the adjusted posture.

[0045] In a preferred embodiment, the steps of obtaining the corresponding desired posture according to the rehabilitation training stage and obtaining the corresponding corrected posture data according to the patient's initial posture and the corresponding desired posture include:

[0046] Obtaining the corresponding expected posture for the active phase according to the patient's rehabilitation training phase, and marking it as the expected active posture;

[0047] Acquire a corresponding initial posture image according to the initial posture of the patient;

[0048] Acquire an active posture comparison image according to the expected active posture;

[0049] The corresponding correction information of each rope is obtained according to the initial posture image and the active posture comparison image, and summarized as the corrected posture data.

[0050] In a preferred embodiment, the step of obtaining a corresponding control strategy according to the initial length of each rope, the tension applied to each rope and the corresponding corrected posture data includes:

[0051] Obtaining corresponding correction information of each rope according to the corrected posture data, and obtaining corresponding correction length of the rope from the correction information of each rope;

[0052] Get the error length of each rope;

[0053] Obtaining the corresponding rope adjustment length according to the correction length of each rope, the error length of each rope and the initial length of each rope;

[0054] The active control strategy is obtained by summarizing the control lengths of multiple ropes.

[0055] In a preferred embodiment, the step of performing gait rehabilitation training on the patient according to the corresponding control strategy includes:

[0056] constructing a second error period, and obtaining a plurality of reaction forces between the patient and each rope within the second error period;

[0057] Obtaining the amount of interaction tendency of the patient to each rope according to a plurality of reaction forces between the patient and each rope;

[0058] Acquire an interaction table, wherein the interaction table includes a plurality of interaction trend interval quantities and an interaction posture corresponding to each interaction trend interval quantity;

[0059] Obtain the target interactive trend interval quantity according to the interactive trend quantity;

[0060] Obtain the corresponding interaction posture from the interaction table according to the target interaction trend interval;

[0061] Perform rehabilitation training based on interactive postures.

[0062] And, a control method terminal of a rope-driven robot for active and passive gait rehabilitation training, comprising:

[0063] one or more processors;

[0064] a storage device having one or more programs stored thereon;

[0065] When one or more programs are executed by one or more processors, the one or more processors implement the active and passive gait rehabilitation training rope-driven robot control method.

[0066] The technical effects achieved by the present invention are:

[0067] The present invention can accurately determine the stage of rehabilitation training and perform corresponding control by obtaining the initial length of each rope and the tension applied by the patient, and correct the posture data to ensure that the robot adjusts the patient's posture with high precision, and can accurately track and correct the patient's displacement and posture. According to the patient's rehabilitation stage and actual feedback force information, the control strategy can be flexibly adjusted, especially when switching between active and passive training modes, and precise regulation in different modes can be achieved, thereby improving the effectiveness of training. By regulating the tension and length of each rope, the patient can be helped to gradually recover gait function, especially in complex gait training processes, and the efficiency and accuracy of rehabilitation training can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a flow chart of the method provided by the present invention. DETAILED DESCRIPTION

[0069] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0070] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0071] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" that appears in different places in this specification does not refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0072] Secondly, the present invention is described in detail in conjunction with schematic diagrams. When describing the embodiments of the present invention in detail, for the convenience of explanation, the schematic diagrams are only examples and should not limit the scope of protection of the present invention.

[0073] Please refer to the attached Figure 1 As shown, a control method for a rope-driven robot for active and passive gait rehabilitation training is provided, comprising:

[0074] S1, obtaining the initial length of each rope of the rope-driven robot terminal platform, obtaining the initial posture of the patient according to the initial length of each rope, and obtaining the tension applied by the patient to each rope;

[0075] S2. Obtaining the patient's rehabilitation training stage according to the initial length of each rope and the tension applied by each rope, wherein the rehabilitation training stage includes an active stage and a passive stage;

[0076] S3, obtaining the corresponding expected posture according to the rehabilitation training stage, and obtaining the corresponding corrected posture data according to the patient's initial posture and the corresponding expected posture;

[0077] S4, obtaining a corresponding control strategy according to the initial length of each rope, the tension applied to each rope and the corresponding corrected posture data;

[0078] S5. Conduct gait rehabilitation training for patients according to corresponding regulation strategies.

[0079] As in the above steps S1 to S5, first, the initial length of each rope on the end platform of the rope-driven robot is obtained, which reflects the current position and posture (posture) of the patient. Then, the tension applied by the patient to each rope can be measured by a force sensor or other sensing device. According to the initial length of each rope and the tension applied by the patient, the current stage of rehabilitation training is judged. This stage usually includes an active training stage and a passive training stage. In the active training stage, the patient has a certain motor ability and can apply external force. The rope-driven robot adjusts the posture according to the external force of the patient. In the passive training stage, the patient lacks autonomous motor ability. The robot actively drives the patient to perform rehabilitation training through trajectory planning. The target posture that the patient needs to achieve is determined by the preset rehabilitation goal (expected posture). After obtaining the initial posture of the patient, the corrected posture data is calculated according to the difference. These corrected posture data are used to guide the robot on how to adjust the patient's posture during rehabilitation training. By combining the initial length of each rope, the tension applied by the patient and the corrected posture data, a specific control strategy is generated. The control strategy includes the rope Tension control, posture adjustment, etc., ensure that each rope can achieve the desired motion path during the control process, thereby helping patients complete rehabilitation training. Finally, according to the formulated control strategy, the robot performs gait rehabilitation training for the patient. Regardless of whether it is an active training mode or a passive training mode, the robot will dynamically adjust the length and tension of each rope to ensure that the patient's motion trajectory and posture during the rehabilitation training can meet the set goals. By obtaining the initial length of each rope and the tension applied by the patient, the stage of rehabilitation training can be accurately judged and corresponding control can be performed. Correcting the posture data ensures that the robot has high precision in adjusting the patient's posture, and can accurately track and correct the patient's displacement and posture. According to the patient's rehabilitation stage and the actual feedback force information, the control strategy can be flexibly adjusted, especially when switching between active and passive training modes, precise control in different modes can be achieved, which improves the effectiveness of training. By adjusting the tension and length of each rope, patients can gradually recover their gait function, especially in complex gait training processes, which can effectively improve the efficiency and accuracy of rehabilitation training.

[0080] In a specific embodiment, the steps of obtaining the initial length of each rope of the rope-driven robot terminal platform, obtaining the initial posture of the patient according to the initial length of each rope, and obtaining the tension applied by the patient to each rope include:

[0081] S101, acquiring patient image data on the end platform of the rope-driven robot;

[0082] S102, acquiring the corresponding initial length of each rope according to the patient image data;

[0083] S103, obtaining the standard length of each rope;

[0084] S104, obtaining the initial posture of the patient according to the initial length of each rope and the standard length of each rope;

[0085] S105, obtaining the tension applied by each rope corresponding to the initial posture state of the patient.

[0086] As in the above steps S101 to S105, the image data of the patient on the rope-driven platform is obtained by installing a camera or image acquisition device around the terminal platform of the rope-driven robot, and the connection point position between each rope and the robot terminal platform is analyzed through the image data, and the actual initial length of each rope is calculated. The rope-driven robot stores the standard length of each rope, that is, the ideal length of the rope in an unstressed state. The standard length is used as a reference for comparison with the initial length, so as to reflect the deformation or elongation of the rope after being stressed. By comparing the initial length of each rope with the standard length, the tension change of the rope and the corresponding length change can be calculated. Combined with these length changes, the initial position of the patient can be inferred. The patient's posture is determined by the three-dimensional spatial position of each key point on the rope-driven platform, and the patient's initial posture model is generated. The force sensor installed at the end of the rope or other relevant positions can be used to measure the tension applied by the patient to each rope in the initial posture state. By combining the patient's image data and the initial length of the rope, the patient's initial posture can be accurately calculated. Compared with simple mechanical or sensor data, image data provides more intuitive and accurate position information, especially in complex three-dimensional space. The patient's initial state data can be quickly obtained at the beginning of rehabilitation training, saving time for subsequent training sessions. At the same time, this method avoids errors in manual measurement and input, and improves the degree of intelligence and automation.

[0087] In a specific embodiment, the rehabilitation training stage of the patient is obtained according to the initial length of each rope and the tension applied by each rope, wherein the rehabilitation training stage includes the steps of active stage and passive stage, including:

[0088] S201, obtaining the offset of each rope according to the initial length of each rope and the corresponding rope applied tension;

[0089] S202, obtaining a deviation threshold value of each rope;

[0090] S203, determining whether the deviation of each rope exceeds the corresponding rope deviation threshold;

[0091] If the rope offset exceeds the corresponding rope offset threshold, the ropes exceeding the corresponding rope offset threshold are summarized to obtain the number of excess ropes;

[0092] S204, obtaining the threshold root number;

[0093] S205, determining whether the number of ropes exceeds a threshold number;

[0094] If the number of ropes exceeds the threshold number, the patient's rehabilitation training stage is determined to be the passive stage;

[0095] If the number of ropes exceeds the threshold number, the patient's rehabilitation training stage is determined to be the active stage.

[0096] As in the above steps S201 to S205, the offset of each rope is obtained by measuring the difference between the initial length of the rope and the actual length under the force state. The offset of the rope reflects the displacement change caused by the patient's autonomous movement or external force. The offset threshold of each rope is preset as an important criterion for judging whether the offset is abnormal. The threshold is usually set according to multiple factors such as the patient's rehabilitation stage, strength and rehabilitation goals. The existence of the threshold helps to distinguish whether the patient is actively participating in rehabilitation training. The actual offset of each rope is compared with the preset offset threshold. If the offset is greater than the threshold, it means that the rope has undergone significant displacement, which may be caused by the patient's active movement. On the contrary, if the offset is small, it means that the patient has not actively generated enough strength and relies more on external force guidance. The number of ropes exceeding the threshold is summarized to obtain the "number of ropes exceeded". The threshold number is another preset criterion for judging the current active or passive stage. The threshold number refers to the maximum number of ropes that allow the rope offset to exceed the threshold. The summarized "number of ropes exceeding" is compared with the preset "threshold number". If the number of ropes exceeding is less than the threshold number, it means that the patient cannot control enough ropes independently, and the rehabilitation rope-driven robot needs to provide more external force support. Therefore, the rehabilitation training is in the passive stage at this time. If the number of ropes exceeding is greater than the threshold number, it means that the patient can control a sufficient number of ropes through autonomous movement, and the training is in the active stage, that is, the patient's own strength is the main driving force. It can intelligently distinguish whether the patient is in the active or passive training stage, reducing the need for manual intervention. Automatic judgment through real-time data feedback ensures the continuity and real-time nature of the training. By analyzing the offset and tension of each rope, the patient's motor ability can be accurately identified, and quantitative data on the patient's rehabilitation progress can be provided. This provides doctors and rehabilitation therapists with a more comprehensive basis for rehabilitation evaluation and helps them better adjust their training plans.

[0097] Embodiment 1 is a method of passive rehabilitation training strategy for a rope-driven robot.

[0098] In a specific embodiment, the step of obtaining the corresponding desired posture according to the rehabilitation training stage, and obtaining the corresponding corrected posture data according to the patient's initial posture and the corresponding desired posture includes:

[0099] S301, obtaining a corresponding expected posture according to the patient's rehabilitation training stage being a passive stage, and marking it as an expected passive posture;

[0100] S302, acquiring a corresponding initial posture image according to the initial posture of the patient;

[0101] S303, acquiring a passive posture comparison image according to the desired passive posture;

[0102] S304: Obtain corresponding correction information for each rope according to the initial posture image and the passive posture comparison image, and summarize them into correction posture data.

[0103] As in the above steps S301 to S304, when it is detected that the rehabilitation training is in the passive stage, the preset expected passive posture is called. The expected passive posture is set according to the rehabilitation training goals and stages, and is the posture that the patient should be in under ideal circumstances. This can be a standard posture set according to the patient's body structure, gait data, and standard rehabilitation process, marked as the expected passive posture, and the patient's actual posture is converted into image data (initial posture image) that can be used for analysis by shooting or collecting real-time image data from sensors, reflecting the patient's actual body position and posture in the current state, and extracting the image corresponding to the expected passive posture (passive posture comparison image), which is used as the ideal posture. The purpose is to compare it with the patient's initial posture image to determine the deviation of the patient's posture. By analyzing the difference between the initial posture image and the passive posture comparison image, the adjustment amount required for each rope, that is, the correction information, is calculated one by one. The correction information includes the length adjustment of each rope, the tension adjustment direction, etc. The correction information of all ropes is summarized to form a complete correction posture data set to guide the rope-driven robot to adjust the patient's posture. By comparing the initial posture and the expected passive posture, the patient's posture deviation can be accurately identified and each rope can be accurately adjusted. The correction posture data provides a detailed adjustment plan, making the rehabilitation training process more targeted and effective.

[0104] In a specific embodiment, the step of obtaining a corresponding control strategy according to the initial length of each rope, the tension applied by each rope, and the corresponding corrected posture data includes:

[0105] S401, obtaining corresponding correction information of each rope according to the corrected posture data, and obtaining corresponding correction length of the rope from the correction information of each rope;

[0106] S402, constructing a first error period, and obtaining a plurality of historical error lengths of each rope in the first error period;

[0107] S403, obtaining the rope applied tension corresponding to multiple historical error lengths of each rope, and marking it as rope error tension;

[0108] S404, obtaining a current error length of each rope according to a plurality of historical error lengths of each rope, a plurality of rope error tensions, and rope applied tensions;

[0109] S405, obtaining the rope adjustment length according to the error length, the rope correction length and the rope initial length;

[0110] S406: Summarize the control lengths of multiple ropes to obtain a passive control strategy.

[0111] As in the above steps S401 to S406, firstly, the length of each rope that needs to be adjusted (rope correction length) is calculated based on the correction posture data. The correction length reflects the difference between the current state and the target posture of each rope, which is the basis of the control strategy. A time period is set, and the past training process is divided into several time periods. The error data of each rope is tracked in each time period. The error length refers to the difference between the rope and the target length during the past training process. By summarizing the historical error lengths of multiple time points in the first error period, the change trend of each rope in the period can be obtained, and the rope applied tension corresponding to the historical error length is obtained, which is marked as the rope error tension. According to the historical error length, the rope error tension and the currently applied tension, the current error length is calculated in real time. The calculation formula of the error length is: Where W represents the current error length, i represents the numbers of multiple historical error lengths and the corresponding numbers of multiple rope error tensions, i = 1, 2, 3...n, C i Expressed as the length of the i-th historical error, L i It is expressed as the error tension of the i-th rope. The control length that needs to be adjusted is calculated according to the current error length, the correction length and the initial length of each rope. The control length can be obtained by adding multiple lengths. The control lengths of multiple ropes are summarized to form a complete passive control strategy. This strategy will be executed to control the rope-driven robot to adjust the rope length, thereby adjusting the patient's posture. It not only relies on the current correction data, but also combines historical error data to formulate a control strategy. It can predict possible deviations in patients during the rehabilitation process and make corresponding adjustments in advance, thereby improving the accuracy of control.

[0112] In a specific embodiment, the step of performing gait rehabilitation training on the patient according to the corresponding control strategy includes:

[0113] S501, adjusting the initial posture of the patient according to the passive control strategy to obtain an adjusted posture;

[0114] S502, obtaining a passive rehabilitation training trajectory;

[0115] S503: Execute the passive rehabilitation training trajectory according to the adjusted posture.

[0116] As in the above steps S501 to S503, according to the previously generated passive control strategy, the initial posture of the patient is adjusted by the rope-driven robot to make it close to the ideal posture after correction. The adjustment length of each rope in the control strategy will be executed one by one, and finally the patient's adjusted posture is obtained. In the passive training process, an ideal rehabilitation training trajectory needs to be set in advance. This trajectory is set according to the rehabilitation goal and the patient's current rehabilitation progress to ensure that the patient follows a scientific gait trajectory for recovery during the training process. The rehabilitation training trajectory can be customized according to the patient's individual situation and the doctor's advice. The patient is controlled to move along the preset rehabilitation training trajectory by adjusting the rope length. Since it is a passive stage, the rope-driven robot will guide the patient to perform a complete gait movement. The patient passively receives rehabilitation training in this process. This step is a key part of rehabilitation training. By accurately controlling the patient's movement path, the gradual recovery of gait is achieved, ensuring that the patient's movements during training are more standard and reducing unnecessary errors. Through precise adjustment of the starting posture, the training effect is maximized.

[0117] Embodiment 2 is an active rehabilitation training strategy for a rope-driven robot.

[0118] In a specific embodiment, the step of obtaining the corresponding desired posture according to the rehabilitation training stage, and obtaining the corresponding corrected posture data according to the patient's initial posture and the corresponding desired posture includes:

[0119] Step 301, obtaining the corresponding expected posture according to the patient's rehabilitation training stage as the active stage, and marking it as the expected active posture;

[0120] Step 302, obtaining a corresponding initial posture image according to the initial posture of the patient;

[0121] Step 303, obtaining an active posture comparison image according to the expected active posture;

[0122] Step 304, obtaining corresponding correction information of each rope according to the initial posture image and the active posture comparison image, and summarizing them into corrected posture data.

[0123] As in the above steps Step 301 to Step 304, during the active rehabilitation stage, the patient needs to actively participate in rehabilitation training. Therefore, according to the patient's current rehabilitation stage and goals, an expected active posture is generated. The expected active posture is the correct gait posture that the patient should achieve under ideal conditions. As a reference standard in training, a suitable expected active posture is set according to the rehabilitation goals. The patient's current actual initial posture image is obtained through an image sensor or a camera device. The initial posture image can record the patient's posture before the start of active training, which is used for subsequent comparative analysis with the expected active posture. If the expected active posture is different from the patient's initial posture, an active posture will be generated. The comparison image of the initial posture of the patient is used as a reference between the actual movement of the patient and the ideal movement. The comparison image will show the ideal movement pattern of the patient and is used to analyze the aspects in which the patient needs to make adjustments and corrections. By comparing the initial posture image of the patient with the comparison image of the expected active posture, the length of each rope that needs to be corrected in actual operation is calculated. The correction information of each rope reflects the deviation between the actual movement of the patient and the expected movement. The correction information will be summarized as the corrected posture data. The corrected posture data is used to guide the rope-driven robot to adjust the patient's training and help it achieve the expected active posture. It can make precise adjustments during training, thereby improving the effect of rehabilitation training.

[0124] In a specific embodiment, the step of obtaining a corresponding control strategy according to the initial length of each rope, the tension applied by each rope, and the corresponding corrected posture data includes:

[0125] Step 401, obtaining corresponding correction information of each rope according to the correction posture data, and obtaining corresponding correction length of the rope from the correction information of each rope;

[0126] Step 402, obtaining the error length of each rope;

[0127] Step 403, obtaining the corresponding rope adjustment length according to the correction length of each rope, the error length of each rope and the initial length of each rope;

[0128] Step 404, obtain the active control strategy by summarizing the control lengths of multiple ropes.

[0129] As in the above steps Step 401 to Step 404, according to the correction posture data, the correction information of each rope is obtained, including its deviation direction and correction force. By analyzing these correction information, the adjustment length of each rope is calculated, which is called the rope correction length. This length indicates the degree to which the rope should be tightened or relaxed, so as to correct the patient's posture deviation. The rope error length is the actual deviation of each rope in the current state relative to the ideal state. These deviation data are obtained through real-time monitoring and can reflect the difference between the patient's current posture and the expected posture. The correction length, error length and initial length of the rope are combined to calculate the specific adjustment amount required for each rope, which is called the rope adjustment length. It can be calculated by the same calculation formula in passive training, which determines the tension or relaxation force required to be applied to each rope to ensure that the patient's posture is close to the expected posture. By summarizing the adjustment length of each rope, an overall active adjustment strategy is obtained. The strategy includes adjustment plans for all ropes, guides the real-time adjustment of the patient's posture, and ensures that its motion trajectory meets the expected rehabilitation plan.

[0130] In a specific embodiment, the step of performing gait rehabilitation training on the patient according to the corresponding control strategy includes:

[0131] Step 501, constructing a second error period, and obtaining a plurality of reaction forces between the patient and each rope in the second error period;

[0132] Step 502, obtaining the interaction tendency amount of the patient to each rope according to multiple reaction forces between the patient and each rope;

[0133] Step 503, obtaining an interaction table, wherein the interaction table includes a plurality of interaction trend interval quantities and an interaction posture corresponding to each interaction trend interval quantity;

[0134] Step 504, obtaining the target interactive trend interval quantity according to the interactive trend quantity;

[0135] Step 505, obtaining the corresponding interaction posture from the interaction table according to the target interaction trend interval;

[0136] Step 506, performing rehabilitation training according to the interactive posture.

[0137] As in the above steps Step 501 to Step 506, a second error period is constructed during the training process. During this period, multiple reaction forces between the patient and each rope are monitored and recorded. By recording these data, the patient's reaction to each extension and retraction of the rope-driven robot during rehabilitation training can be captured, that is, the force feedback generated by the patient on the rope when performing active exercise. These reaction forces directly reflect the patient's rehabilitation participation and current exercise ability. Based on the multiple reaction forces between the patient and each rope, the interaction trend amount is calculated. The calculation formula of the interaction trend amount is: Where Z represents the interactive trend quantity, k represents the number of multiple reaction forces, k = 1, 2, 3...r, F k Expressed as the kth reaction force, F k-1 It is expressed as the k-1th reaction force. The interaction trend quantity is an indicator used to evaluate the patient's continuous force application or force reduction on the rope within a certain period of time. It represents the changing trend of the patient's rope tension. For example, a continuously increasing reaction force indicates that the patient actively participates in rehabilitation, while a weakened reaction force may indicate the patient's fatigue or passive state. The interaction trend quantity is linked to the specific interaction posture through a pre-set interaction table. The interaction table contains multiple interaction trend interval quantities and the interaction posture corresponding to each interval quantity, and provides posture adjustment suggestions for patients under different trends. Through these trend intervals, it can intelligently judge the patient's state in the rehabilitation process and match the most suitable training posture for him. According to the current interaction trend quantity, the corresponding target interaction is matched from the interaction table. The interactive trend interval quantity reflects the patient's interactive characteristics in the current period and is the key basis for judging the patient's posture adjustment. The interactive trend interval can be subdivided into different levels, such as mild active, strong active or passive, etc. According to the target interactive trend interval quantity, the corresponding interactive posture is found and obtained from the interactive table. These interactive postures are adjustment postures designed according to the patient's current interactive trend, which are used to help patients complete rehabilitation training smoothly. Rehabilitation training is performed according to the obtained interactive postures. According to the patient's actual interactive trend, the patient's active or passive participation can be judged in real time, so as to select the appropriate training posture. Compared with fixed rehabilitation paths, this dynamic adjustment method based on interactive trends is more personalized, ensuring the comfort and safety of patients during training.

[0138] And, a control method terminal of a rope-driven robot for active and passive gait rehabilitation training, comprising:

[0139] one or more processors;

[0140] a storage device having one or more programs stored thereon;

[0141] When one or more programs are executed by one or more processors, the one or more processors implement the active and passive gait rehabilitation training rope-driven robot control method.

[0142] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A control method for a rope-driven robot for active and passive gait rehabilitation training, characterized in that: include: Obtain the initial length of each rope of the rope-driven robot terminal platform, obtain the initial posture of the patient according to the initial length of each rope, and obtain the tension applied by the patient to each rope; Obtaining the patient's rehabilitation training stage according to the initial length of each rope and the tension applied by each rope, wherein the rehabilitation training stage includes an active stage and a passive stage; Acquire the corresponding expected posture according to the rehabilitation training stage, and acquire the corresponding corrected posture data according to the patient's initial posture and the corresponding expected posture; Obtaining a corresponding control strategy according to the initial length of each rope, the tension applied to each rope, and the corresponding corrected posture data; Gait rehabilitation training is performed on patients according to the corresponding regulation strategies.

2. The active and passive gait rehabilitation training rope-driven robot control method according to claim 1, characterized in that: The steps of obtaining the initial length of each rope of the rope-driven robot terminal platform, obtaining the initial posture of the patient according to the initial length of each rope, and obtaining the tension applied by the patient to each rope include: Acquire patient image data on the end platform of the rope-driven robot; Acquire the corresponding initial length of each rope according to the patient image data; Get the standard length of each rope; Obtain the initial position of the patient according to the initial length of each rope and the standard length of each rope; Obtain the tension applied by each rope corresponding to the patient's initial posture.

3. The active and passive gait rehabilitation training rope-driven robot control method according to claim 1, characterized in that: The rehabilitation training stage of the patient is obtained according to the initial length of each rope and the tension applied by each rope, wherein the rehabilitation training stage includes steps of an active stage and a passive stage, including: Obtaining the deflection of each rope according to the initial length of each rope and the corresponding rope applied tension; Get the offset threshold value of each rope; Determining whether the deviation of each rope exceeds the corresponding rope deviation threshold; If the rope offset exceeds the corresponding rope offset threshold, the ropes exceeding the corresponding rope offset threshold are summarized to obtain the number of excess ropes; Get the threshold root number; Determine whether the number of ropes exceeds a threshold number; If the number of ropes exceeds the threshold number, the patient's rehabilitation training stage is determined to be the passive stage; If the number of ropes exceeds the threshold number, the patient's rehabilitation training stage is determined to be the active stage.

4. The active and passive gait rehabilitation training rope-driven robot control method according to claim 1, characterized in that: The steps of obtaining the corresponding expected posture according to the rehabilitation training stage and obtaining the corresponding corrected posture data according to the patient's initial posture and the corresponding expected posture include: Obtaining the corresponding expected posture for the passive phase according to the patient's rehabilitation training phase, and marking it as the expected passive posture; Acquire a corresponding initial posture image according to the initial posture of the patient; Acquire a passive posture comparison image according to the expected passive posture; The corresponding correction information of each rope is obtained according to the initial posture image and the passive posture comparison image, and summarized as the corrected posture data.

5. The active and passive gait rehabilitation training rope-driven robot control method according to claim 4, characterized in that: The step of obtaining a corresponding control strategy according to the initial length of each rope, the tension applied to each rope and the corresponding corrected posture data includes: Obtaining corresponding correction information of each rope according to the corrected posture data, and obtaining corresponding correction length of the rope from the correction information of each rope; Constructing a first error period, and obtaining a plurality of historical error lengths of each rope within the first error period; Obtain the rope tension corresponding to multiple historical error lengths of each rope, and mark it as rope error tension; Obtaining the current error length of each rope according to a plurality of historical error lengths of each rope, a plurality of rope error tensions, and rope applied tensions; The rope adjustment length is obtained according to the error length, the rope correction length and the rope initial length; The control lengths of multiple ropes are aggregated to obtain a passive control strategy.

6. The active and passive gait rehabilitation training rope-driven robot control method according to claim 5, characterized in that: The steps of conducting gait rehabilitation training for patients according to the corresponding control strategy include: Adjust the initial posture of the patient according to the passive control strategy to obtain an adjusted posture; Obtain passive rehabilitation training trajectories; Perform passive rehabilitation training trajectory according to the adjusted posture.

7. The active and passive gait rehabilitation training rope-driven robot control method according to claim 1, characterized in that: The steps of obtaining the corresponding expected posture according to the rehabilitation training stage and obtaining the corresponding corrected posture data according to the patient's initial posture and the corresponding expected posture include: Obtaining the corresponding expected posture for the active phase according to the patient's rehabilitation training phase, and marking it as the expected active posture; Acquire a corresponding initial posture image according to the initial posture of the patient; Acquire an active posture comparison image according to the expected active posture; The corresponding correction information of each rope is obtained according to the initial posture image and the active posture comparison image, and summarized as the corrected posture data.

8. The active and passive gait rehabilitation training rope-driven robot control method according to claim 7, characterized in that: The step of obtaining a corresponding control strategy according to the initial length of each rope, the tension applied to each rope and the corresponding corrected posture data includes: Obtaining corresponding correction information of each rope according to the corrected posture data, and obtaining corresponding correction length of the rope from the correction information of each rope; Get the error length of each rope; Obtaining the corresponding rope adjustment length according to the correction length of each rope, the error length of each rope and the initial length of each rope; The active control strategy is obtained by summarizing the control lengths of multiple ropes.

9. The active and passive gait rehabilitation training rope-driven robot control method according to claim 8, characterized in that: The steps of conducting gait rehabilitation training for patients according to the corresponding control strategy include: constructing a second error period, and obtaining a plurality of reaction forces between the patient and each rope within the second error period; Obtaining the amount of interaction tendency of the patient to each rope according to a plurality of reaction forces between the patient and each rope; Acquire an interaction table, wherein the interaction table includes a plurality of interaction trend interval quantities and an interaction posture corresponding to each interaction trend interval quantity; Obtain the target interactive trend interval quantity according to the interactive trend quantity; Obtain the corresponding interaction posture from the interaction table according to the target interaction trend interval; Perform rehabilitation training based on interactive postures.

10. A control method terminal for a rope-driven robot for active and passive gait rehabilitation training, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When one or more programs are executed by one or more processors, the one or more processors implement the active and passive gait rehabilitation training rope-driven robot control method as described in any one of claims 1 to 9.

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