Gait simulation and verification method, system and device based on lower limb exoskeleton rehabilitation robot and medium

Abstract

The invention discloses a gait simulation and verification method, system and device based on a lower limb exoskeleton rehabilitation robot and a medium, and the method comprises the steps: obtaining self-defined gait parameters, and generating a first gait track according to the gait parameters; performing simulation verification on the first gait track to obtain a second gait track passing the simulation verification; generating a control instruction according to the second gait track, and sending the control instruction to the lower limb exoskeleton rehabilitation robot; the lower limb exoskeleton rehabilitation robot is controlled to execute a corresponding motion program according to the control instruction, and gait data of the user in the motion process are collected. According to the embodiment of the invention, the self-defined gait parameters can be converted into the gait track, the rationality of the gait track is checked through simulation verification and actual verification, and a personalized and scientific gait rehabilitation training scheme can be conveniently provided for a user. The device can be widely applied to the field of medical rehabilitation equipment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical rehabilitation equipment, and particularly relates to a gait simulation and verification method, system and device based on a lower limb exoskeleton rehabilitation robot and a medium. BACKGROUND

[0002] Lower limb gait research is of great significance for understanding the mechanism of human motion, evaluating rehabilitation effect and optimizing rehabilitation treatment scheme. However, traditional gait research methods are often limited by experimental conditions, data acquisition difficulty and safety problems. With the development of lower limb exoskeleton rehabilitation robots, a new way for gait research is provided. However, most of the existing systems lack intuitive and easy-to-use gait trajectory editing tools and simulation verification platforms, which are difficult to meet the diversified needs of researchers and rehabilitation therapists for gait research. SUMMARY

[0003] The main purpose of the embodiments of the present application is to provide a gait simulation and verification method, system, device and medium based on a lower limb exoskeleton rehabilitation robot, which aims to convert the self-defined gait parameters into gait trajectories, and test their rationality through simulation verification and actual verification, so as to provide personalized and scientific gait rehabilitation training programs for users.

[0004] To achieve the above purpose, one aspect of the embodiments of the present application provides a gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot, which comprises: obtaining self-defined gait parameters and generating a first gait trajectory according to the gait parameters; performing simulation verification on the first gait trajectory to obtain a second gait trajectory that passes the simulation verification; generating a control instruction according to the second gait trajectory and sending the control instruction to a lower limb exoskeleton rehabilitation robot; controlling the lower limb exoskeleton rehabilitation robot to execute a corresponding motion program according to the control instruction, and collecting gait data of a user during the motion process.

[0005] In some embodiments, the obtaining of the self-defined gait parameters and the generation of the first gait trajectory according to the gait parameters comprises: determining initial gait parameters through a preset gait template library or default gait parameters; displaying gait parameter editing interactive elements through a first visual interface of a gait trajectory editor; adjusting the initial gait parameters in response to an operation instruction for the gait parameter editing interactive elements, and displaying a corresponding gait trajectory preview result through the first visual interface; displaying a gait parameter submission button through the first visual interface; In response to a triggering operation for submitting a button for the gait parameter, the current initial gait parameter is taken as the gait parameter, and a first gait trajectory is generated according to the gait parameter.

[0006] In some embodiments, the simulation verification of the first gait trajectory obtains a second gait trajectory that passes the simulation verification, including: inputting the first gait trajectory into a gait simulation engine; obtaining, through a second visualization interface of the gait simulation engine, a physiological parameter input by a user, a rehabilitation target, and an adjustment instruction for a preset simulation model; adjusting the preset simulation model according to the adjustment instruction; performing simulation calculation on the first gait trajectory through the preset simulation model, simulating stress conditions, muscle activity patterns, and overall movement trajectories of the first gait trajectory in a movement process, and demonstrating simulation results through three-dimensional animation; judging whether the first gait trajectory meets a preset target according to the physiological parameter, the rehabilitation target, and the simulation results; when the first gait trajectory meets the preset target, taking the first gait trajectory as the second gait trajectory.

[0007] In some embodiments, the control instruction is generated according to the second gait trajectory, and the control instruction is sent to a lower extremity exoskeleton rehabilitation robot; including: converting the second gait trajectory into an initial control instruction through a real-time control interface; obtaining an adjustment parameter input by a user, adjusting the initial control instruction according to the adjustment parameter to obtain the control instruction; sending the control instruction to the lower extremity exoskeleton rehabilitation robot according to a preset communication protocol through the real-time control interface.

[0008] In some embodiments, the lower extremity exoskeleton rehabilitation robot includes a plurality of joint modules, a power and control unit, and a perception and feedback unit, and the lower extremity exoskeleton rehabilitation robot is controlled to execute a corresponding movement program according to the control instruction, and gait data of a user in a movement process is collected, including: driving each joint module to move according to the control instruction through the power and control unit; collecting the gait data of the user in the movement process through the perception and feedback unit.

[0009] In some embodiments, the gait simulation verification method further includes: detecting, through the perception and feedback unit, whether an abnormal situation exists in the movement process; When the abnormal situation exists, the power and control unit controls the lower extremity exoskeleton rehabilitation robot to brake in emergency and executes a protection measure.

[0010] In some embodiments, the gait simulation verification method further comprises: Adjusting a motion state of the lower extremity exoskeleton rehabilitation robot according to the gait data.

[0011] To achieve the above object, another aspect of the embodiments of the present application proposes a gait simulation and verification system based on a lower extremity exoskeleton rehabilitation robot, which comprises: A gait trajectory editing module, configured to acquire customized gait parameters and generate a first gait trajectory according to the gait parameters; A gait trajectory simulation and verification module, configured to simulate and verify the first gait trajectory to obtain a second gait trajectory that passes the simulation and verification; A control instruction generation module, configured to generate a control instruction according to the second gait trajectory and send the control instruction to the lower extremity exoskeleton rehabilitation robot; A gait trajectory actual verification module, configured to control the lower extremity exoskeleton rehabilitation robot to execute a corresponding motion program according to the control instruction and collect gait data of a user in a motion process.

[0012] To achieve the above object, another aspect of the embodiments of the present application proposes a computer device, which comprises: At least one processor; At least one memory configured to store at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method described / mentioned above.

[0013] To achieve the above object, another aspect of the embodiments of the present application proposes a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method described / mentioned above.

[0014] The embodiments of the present application at least have the following beneficial effects: The present application provides a gait simulation and verification method, system, device and medium based on a lower limb exoskeleton rehabilitation robot. The scheme generates a gait trajectory according to user-defined gait parameters, which facilitates flexible design of the gait trajectory by the user. The first gait trajectory is simulated and verified, and the second gait trajectory meeting the preset target is screened out, which can screen and verify the gait before executing the control, thereby improving the adaptability of the gait trajectory and the user gait rehabilitation training scheme, and reducing the possibility of accidents in the actual verification stage. The gait trajectory that has completed the simulation verification is converted into a control instruction and sent to the lower limb exoskeleton rehabilitation robot, which facilitates accurate execution of the motion program by the robot. The gait data of the user is collected during the motion process, which provides a data basis for subsequent evaluation of the gait rehabilitation training effect, adjustment of the gait trajectory design scheme, and optimization of the motion control of the lower limb exoskeleton rehabilitation robot, and helps to provide personalized and scientific gait rehabilitation training schemes for the user. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a step flow chart of a gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot provided by the embodiments of the present application; Figure 2 is a schematic diagram of a first visual interface of a gait trajectory editor provided by the embodiments of the present application; Figure 3 is a schematic diagram of a second visual interface of a gait simulation engine provided by the embodiments of the present application; Figure 4 is a structural schematic diagram of a lower limb exoskeleton rehabilitation robot provided by the embodiments of the present application; Figure 5 is a signal connection diagram of a lower limb exoskeleton rehabilitation robot provided by the embodiments of the present application; Figure 6 is a structural schematic diagram of a gait simulation and verification system based on a lower limb exoskeleton rehabilitation robot provided by the embodiments of the present application; Figure 7 is a hardware structural schematic diagram of a computer device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0016] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application and not to limit the present application. When the following description refers to the accompanying drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with embodiments of the present application. They are merely examples of apparatuses and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0017] It can be understood that the terms "first", "second", and the like used in the present application can be used herein to describe various concepts, but unless specifically stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "when" or "when" or "in response to determining".

[0018] The terms "at least one", "multiple", "each", "any" and the like used in the present application include one, two or more than two, multiple includes two or more than two, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by those skilled in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0020] Before the embodiments of the present application are described in detail, the background art related to the embodiments of the present application is further described.

[0021] The lower extremity exoskeleton rehabilitation robot gait research and simulation platform system is a product based on the cross-fusion of multiple disciplines such as robotics, biomechanics, motion control theory and simulation technology. This system aims to study and evaluate the gait function of patients with lower extremity movement disorders in a scientific and accurate manner, and to provide scientific basis for formulating personalized rehabilitation training plans.

[0022] In the prior art, lower extremity exoskeleton rehabilitation robots have achieved certain achievements. These robots usually have the following characteristics: Wearable: able to closely fit the structure of the lower extremities of the human body, ensuring the comfort and stability of the patient during the wearing process.

[0023] Drive system: adopts motor, cylinder or hydraulic drive mode, provides necessary power support for robot.

[0024] Sensor network: by installing various sensors (such as accelerometer, gyroscope, force sensor, etc.), real-time monitoring of gait data and physiological parameters of patients.

[0025] Intelligent control system: based on advanced control algorithm and strategy, realize accurate control to robot motion trajectory, speed and force.

[0026] There are still some deficiencies in the prior art: Insufficient individualization: although certain gait patterns can be simulated, it is difficult to completely match the specific physiological characteristics and rehabilitation needs of each patient.

[0027] Evaluation accuracy needs to be improved: in the process of gait data collection and analysis, it may be affected by various factors (such as sensor accuracy, patient cooperation degree, etc.), resulting in certain errors in the evaluation results.

[0028] Poor human-computer interaction: some robots have deficiencies in human-computer interaction, and it is difficult to dynamically adjust the training plan according to the real-time feedback of patients.

[0029] Therefore, in view of the deficiencies of the existing lower limb gait research method in gait trajectory editing, simulation verification and real-time control, etc., the present application provides a gait simulation and verification method, system, device and medium based on lower limb exoskeleton rehabilitation robot, provides an intuitive and easy-to-use gait trajectory editing tool, reduces the threshold and complexity of gait research, ensures the rationality and stability of gait trajectory through simulation verification, improves the accuracy and reliability of research, realizes real-time control of gait trajectory, provides strong support for the application of lower limb exoskeleton rehabilitation robot, promotes the in-depth development of lower limb gait research, and provides scientific basis for the optimization of rehabilitation treatment scheme.

[0030] Figure 1 is an optional flowchart of a gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot provided by the present application, Figure 1 The method in the method can include but is not limited to steps S101-S104.

[0031] S101, obtain the customized gait parameters, and generate a first gait trajectory according to the gait parameters; In some embodiments, obtaining the customized gait parameters and generating a first gait trajectory according to the gait parameters comprises: S1011, determine initial gait parameters through a preset gait template library or default gait parameters; S1012, display gait parameter editing interactive elements through a first visual interface of a gait trajectory editor; S1013, in response to an operation instruction for editing the gait parameter interaction element, adjusting the initial gait parameter, and displaying a corresponding gait trajectory preview result through the first visualization interface; S1014, displaying a gait parameter submission button through the first visualization interface; S1015, in response to a triggering operation of the gait parameter submission button, taking the current initial gait parameter as the gait parameter, and generating a first gait trajectory according to the gait parameter.

[0032] Specifically, in this embodiment, the customized gait parameters include but are not limited to step length, step frequency, angle change curves of the hip joint, knee joint and ankle joint in each step, etc. Referring to Figure 2 , this embodiment provides a highly flexible and intuitive operating environment for users through the gait trajectory editor, which uses an advanced graphical interface design (i.e., the first visualization interface), so that even non-professional users can easily get started, users can freely define and adjust various parameters of the gait, and these parameter adjustments can be completed not only by directly inputting numerical values, but also by dragging elements in the graphical interface, greatly improving the efficiency and intuitiveness of editing. The editor also has a rich preset gait template library, users can select existing templates as initial gait parameters for modification, or completely design new gait trajectories from scratch. In addition, the editor also provides real-time preview function, users can see the simulation effect of gait trajectory immediately during the editing process, in order to make further adjustment and optimization.

[0033] Exemplarily, referring to Figure 1 , in the actual operation process, after the user starts the gait simulation verification system, the user will first enter the first visualization interface of the gait trajectory editor. This interface is designed to be intuitive and user-friendly, aiming to enable even first-time users to quickly get started. Users can freely define various parameters of the gait by dragging elements on the graphical interface, such as step length adjustment slider, step frequency setting button, and joint angle change curve graph, etc. The editor provides rich preset templates and parameter adjustment options, users can flexibly adjust every detail of the gait trajectory according to research needs or personal preferences.

[0034] During the editing process, users can preview the simulation effect of the gait trajectory at any time. The real-time preview function built into the editor will immediately update the display according to the user's input parameters, allowing users to intuitively see the changes in the gait trajectory and make further adjustments and optimizations accordingly. When the user is satisfied with the gait trajectory, the user can send the edited gait trajectory data to the gait simulation engine through the submit button on the editor interface to continue the subsequent steps.

[0035] It can be recognized that the embodiment enables the user to customize and edit the gait trajectory according to the specific situation and needs through the gait trajectory editor. This personalized customization capability makes the rehabilitation training more in line with the actual situation of the user, improving the accuracy and effectiveness of the rehabilitation training. Compared with traditional rehabilitation methods, the embodiment can provide a training scheme that is more in line with the individual differences of the user, which helps to accelerate the rehabilitation process of the user.

[0036] S102, simulating and verifying the first gait trajectory to obtain a second gait trajectory that passes the simulation verification; In some embodiments, simulating and verifying the first gait trajectory to obtain a second gait trajectory that passes the simulation verification comprises: S1021, inputting the first gait trajectory to a gait simulation engine; S1022, obtaining the physiological parameters, rehabilitation goals and adjustment instructions for the preset simulation model input by the user through a second visualization interface of the gait simulation engine; S1023, adjusting the preset simulation model according to the adjustment instructions; S1024, simulating and calculating the first gait trajectory through the preset simulation model to simulate the stress condition, muscle activity mode and overall motion trajectory of the first gait trajectory in the motion process, and demonstrating the simulation results through a three-dimensional animation; S1025, judging whether the first gait trajectory meets the preset goal according to the physiological parameters, rehabilitation goals and simulation results; S1026, when the first gait trajectory meets the preset goal, taking the first gait trajectory as the second gait trajectory.

[0037] Specifically, in the embodiment, the gait simulation engine is responsible for receiving the gait trajectory data generated by the gait trajectory editor, and performing simulation calculation using advanced dynamics model, kinematics model and human biomechanics principles. By simulating the stress condition of each joint, muscle activity mode and overall motion trajectory of the human body during walking, the simulation engine can highly realistically restore the performance of the gait in actual motion. During the simulation process, the engine will comprehensively consider various factors such as ground friction, air resistance, human inertia, etc. to ensure the accuracy and reliability of the simulation results. At the same time, the engine also has a powerful error detection and correction mechanism, which can automatically identify and correct unreasonable gait parameters to ensure the smooth progress of the simulation process. After the simulation is completed, the engine will generate a detailed simulation report, including animation demonstration of the gait trajectory, stress analysis of each joint, muscle activity mode diagram, etc. to provide comprehensive gait evaluation basis for the user.

[0038] Exemplarily, with reference to Figure 3The gait simulation engine in this embodiment provides an intuitive graphical user interface (i.e., a second visualization interface) that allows users to input the patient's physiological parameters (such as height, weight, lower limb length, etc.) and rehabilitation goals. The interface supports multiple languages, making it convenient for patients from different countries and regions to use.

[0039] The gait simulation engine incorporates various gait simulation models, including normal gait and pathological gait. After selecting a suitable gait simulation model, users can adjust its parameters (such as stride length, cadence, and joint angles) through the interface to simulate different rehabilitation stages and training effects. The model automatically generates personalized gait simulation results based on the input physiological parameters and rehabilitation goals. The simulation results are displayed in 3D animation, intuitively reflecting the patient's gait characteristics. Users can observe the simulation results and adjust parameters as needed to optimize the training plan. The adjusted simulation results are fed back to the control system in real time, guiding the robot in corresponding training.

[0040] It is understood that in this embodiment, gait trajectory data is simulated and verified using a gait simulation engine before being applied to actual rehabilitation. This step ensures the rationality and safety of the gait trajectory, avoiding the risk of potential harm to the patient due to an inappropriate gait trajectory. The simulation verification process is based on advanced dynamic and kinematic models, ensuring the accuracy and reliability of the simulation results.

[0041] S103. Generate control commands based on the second gait trajectory and send the control commands to the lower limb exoskeleton rehabilitation robot; In some embodiments, control commands are generated based on the second gait trajectory and sent to the lower limb exoskeleton rehabilitation robot; including: S1031. Convert the second gait trajectory into initial control commands through the real-time control interface; S1032. Obtain the adjustment parameters input by the user, adjust the initial control command according to the adjustment parameters, and obtain the control command; S1033. Control commands are sent to the lower limb exoskeleton rehabilitation robot through the real-time control interface according to the preset communication protocol.

[0042] Specifically, in this embodiment, the real-time control interface serves as a bridge connecting the gait simulation engine and the lower limb exoskeleton rehabilitation robot. It is responsible for converting the simulated and validated gait trajectory data into control commands and sending them to the robot via a specific communication protocol. These control commands contain detailed information such as the angles and speeds that each joint of the robot should achieve at each time point, ensuring that the robot can move according to the predetermined gait trajectory.

[0043] The real-time control interface also has high-speed data transmission capability and powerful real-time processing capability, which can ensure the timeliness and accuracy of the control instructions. At the same time, the interface also has an error detection and feedback mechanism, which can discover any abnormal situation during communication and immediately report it to the system administrator, so as to take timely measures to handle it.

[0044] Illustratively, after the simulation verification is passed, the user can convert the verified gait trajectory data into control instructions through the real-time control interface of the system and send them to the lower limb exoskeleton rehabilitation robot. The real-time control interface uses an efficient communication protocol to ensure that the control instructions can be quickly and accurately transmitted to the robot end.

[0045] Before sending the control instructions, the user can also set some additional parameters according to needs, such as training time, repetition number, etc., in order to control the rehabilitation process more finely.

[0046] It can be recognized that the embodiment sends the verified gait trajectory data to the lower limb exoskeleton rehabilitation robot through the real-time control interface, and the robot can quickly respond and execute the instructions. This real-time control capability makes the rehabilitation training process more smooth and efficient, which helps the user to obtain better rehabilitation effect in a short time. At the same time, the precise transmission mechanism and servo motor inside the robot ensure the accuracy and stability of the movement.

[0047] S104、According to the control instructions, control the lower limb exoskeleton rehabilitation robot to execute the corresponding motion program, and collect the gait data of the user in the motion process.

[0048] In some embodiments, the lower limb exoskeleton rehabilitation robot includes a plurality of joint modules, a power and control unit, and a perception and feedback unit, according to the control instructions, control the lower limb exoskeleton rehabilitation robot to execute the corresponding motion program, and collect the gait data of the user in the motion process, including: S1041, drive each joint module to move according to the control instructions through the power and control unit; S1042, collect the gait data of the user in the motion process through the perception and feedback unit.

[0049] Specifically, in the embodiment, the lower limb exoskeleton rehabilitation robot is an actual verification execution mechanism, referring to Figure 4 and Figure 5The joint modules of the lower extremity exoskeleton rehabilitation robot can include hip joint modules, knee joint modules, and ankle joint modules, which are constructed with lightweight high-strength materials and can simulate the natural movement of the human lower extremities. Each joint module has a precise transmission mechanism and a limiting device integrated inside, ensuring the accuracy and safety of the movement. The drive system uses high-performance servo motors as the power source, which transmits power to each joint through a reducer and transmission mechanism to achieve precise angle and force control. At the same time, it is equipped with an emergency braking device to respond to unexpected situations.

[0050] In the lower extremity exoskeleton rehabilitation robot, the power and control unit can use high-performance embedded processors to realize data analysis and processing, responsible for receiving sensor data, executing control algorithms, and sending control instructions to the drive system, providing preprocessing and denoising of sensor data and simulation results to improve data accuracy and reliability. The processor has a real-time operating system built-in to ensure system stability and response speed.

[0051] The perception and feedback unit inside the robot integrates multiple sensors (such as accelerometers, gyroscopes, and force sensors) at key positions of the robot (such as joints and soles), which are used to monitor the gait data of the patient (such as joint angles and ground reaction forces) in real time and feedback to the power and control unit. Sensor data is transmitted to the power and control unit through wireless or wired means. These data can not only be used to evaluate the patient's gait function and rehabilitation progress, but also provide important basis for subsequent gait optimization and personalized rehabilitation training.

[0052] After receiving control instructions from the real-time control interface, the lower extremity exoskeleton rehabilitation robot controls the precise transmission mechanism and servo motor through the power and control unit to drive each joint to move according to the specified gait trajectory. The robot fully considers the physiological structure and movement characteristics of the human body in design, ensuring comfort and safety during movement.

[0053] It can be recognized that in addition to the rehabilitation field, the present embodiment also has wide application potential in military, fire fighting, rescue, and sports training fields. For example, in extreme walking environments, this technology can provide additional strength and stability support for personnel; in sports training, it can help athletes improve performance and protect the body. Compared with traditional rehabilitation training methods.

[0054] In some embodiments, the gait simulation verification method further comprises: S105, detecting whether there is an abnormal situation in the movement process through the perception and feedback unit; S106, when the abnormal situation exists, controlling the lower extremity exoskeleton rehabilitation robot to brake urgently through the power and control unit, and executing protection measures.

[0055] Specifically, in the embodiment, the lower extremity exoskeleton rehabilitation robot also has safety functions such as emergency braking and overload protection to ensure the safety of the patient during the training process. Once any abnormal situation or dangerous signal is detected, the robot will immediately stop moving and take corresponding protective measures.

[0056] It can be recognized that these safety mechanisms can immediately stop moving and take corresponding protective measures when detecting abnormal situations or dangerous signals, ensuring the safety of the patient during the training process.

[0057] In some embodiments, the gait simulation verification method further comprises: S107, adjusting the motion state of the lower extremity exoskeleton rehabilitation robot according to the gait data.

[0058] Specifically, in the embodiment, the power and control unit can also realize precise control of the robot's motion trajectory, speed and force based on gait data, biomechanical models and machine learning algorithms, and can automatically adjust the training parameters according to the patient's gait data and rehabilitation needs, realizing personalized rehabilitation training.

[0059] It can be recognized that compared with traditional rehabilitation training methods, the embodiment can provide a more scientific, efficient and accurate rehabilitation training scheme. By training the lower extremities externally, the nervous system can be stimulated to remodel, and the ability of the lower extremities to walk autonomously can be improved, thereby accelerating the rehabilitation process. In addition, the embodiment can objectively and accurately quantify the improvement of the patient's motor function, providing strong support for the evaluation of rehabilitation effect.

[0060] In summary, the present application has significant advantages in personalized customization, simulation verification, real-time control, actual verification, safety, multi-field application, and improvement of rehabilitation training efficiency and effect.

[0061] Please refer to Figure 6 The embodiment of the present application also provides a gait simulation and verification system based on a lower extremity exoskeleton rehabilitation robot, which can realize the above-mentioned method, and the system comprises: A gait trajectory editing module is configured to obtain self-defined gait parameters and generate a first gait trajectory according to the gait parameters; A gait trajectory simulation and verification module is configured to simulate and verify the first gait trajectory to obtain a second gait trajectory that passes the simulation verification; A control instruction generation module is configured to generate a control instruction according to the second gait trajectory and send the control instruction to the lower extremity exoskeleton rehabilitation robot; A gait trajectory actual verification module is configured to control the lower extremity exoskeleton rehabilitation robot to execute a corresponding motion program according to the control instruction and collect gait data of the user during the motion process.

[0062] It can be understood that the contents in the above method embodiments are all applicable to the present system embodiments, the present system embodiments specifically implement the same functions as the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

[0063] The present application also provides an electronic device, which comprises a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above method. The electronic device can be any smart terminal, such as a tablet computer or a vehicle-mounted computer.

[0064] It can be understood that the contents in the above method embodiments are all applicable to the present device embodiments, the present device embodiments specifically implement the same functions as the above method embodiments, and achieve the same beneficial effects as the above method embodiments.

[0065] Please refer to Figure 7 , Figure 7 The present application also provides a computer device, which comprises: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0066] The processor 901 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, and is used to execute related programs to implement the technical solutions provided by the present application; The memory 902 can be implemented in the form of a ROM (Read Only Memory), a static storage device, a dynamic storage device, or a RAM (Random Access Memory). The memory 902 can store an operating system and other application programs. When the technical solutions provided by the present application are implemented by software or firmware, the related program codes are stored in the memory 902 and are called and executed by the processor 901 to implement the above method of the present application; The input / output interface 903 is used to realize information input and output; The communication interface 904 is used to realize the communication interaction between the device and other devices. The communication can be realized by a wired manner (such as a USB, a network cable, etc.) or a wireless manner (such as a mobile network, WIFI, Bluetooth, etc.). a bus 905 for communicating information between the various components (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904) of the device; The processor 901, the memory 902, the input / output interface 903, and the communication interface 904 are communicatively connected with each other within the device through the bus 905.

[0067] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the method.

[0068] It can be understood that the contents in the above method embodiments are all applicable to the present storage medium embodiment. The present storage medium embodiment specifically implements the functions of the above method embodiments and achieves the same beneficial effects as the above method embodiments.

[0069] The embodiment of the present application further provides a computer program product, which comprises a computer program. The computer program is executed by a processor to implement the method.

[0070] It can be understood that the contents in the above method embodiments are all applicable to the present program product embodiment. The present program product embodiment specifically implements the functions of the above method embodiments and achieves the same beneficial effects as the above method embodiments.

[0071] The memory, as a non-transitory computer readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory and can further include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0072] The embodiment of the application provides a gait simulation and verification method, system and device based on a lower limb exoskeleton rehabilitation robot and a medium, which realizes unified collection and management of flash furnace smelting process data, smelting process artificial observation information and smelting product inspection data through establishing a global database, so as to provide a basis for intelligent operation decision of the flash furnace; through the flash furnace fire hole area, the internal of the flue gas pipeline and the slagging hole wall, the flame information of the furnace mouth, the color of the dust returned in the internal of the flue gas pipeline and the temperature abnormality of the slagging hole wall are obtained, so as to provide a basis for subsequent intelligent operation decision and facilitate the realization of safety warning; the intelligent operation decision of the flash furnace through the collected data and the preset rules helps to improve the efficiency and quality of production decision.

[0073] The embodiments described in the embodiments of the application are used to more clearly illustrate the technical solutions of the embodiments of the application, and do not constitute a limitation on the technical solutions provided by the embodiments of the application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the application are also applicable to similar technical problems.

[0074] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the application, and can include more or fewer steps than those shown in the figures, or combine certain steps or different steps.

[0075] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, that is, can be located in one place or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the application.

[0076] Those skilled in the art can understand that all or some of the steps in the above disclosed method, the function modules / units in the system and the device can be implemented as software, firmware, hardware and their appropriate combinations.

[0077] The terms "first", "second", "third", "fourth" and the like (if any) in the specification of the application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0078] It should be understood that, in the present application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the relationship between associated objects, which means that there can be three relationships, for example, "A and / or B" can mean: only A, only B, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects. "At least one of the following" or similar expressions means any combination of these items, including single or multiple items in any combination. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0079] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the above units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0080] The units described above as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the present embodiment.

[0081] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0082] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0083] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot, characterized in that, include: Obtain custom gait parameters and generate a first gait trajectory based on the gait parameters; The first gait trajectory was simulated and verified to obtain the second gait trajectory that passed the simulation verification. Control commands are generated based on the second gait trajectory and sent to the lower limb exoskeleton rehabilitation robot; The lower limb exoskeleton rehabilitation robot is controlled to execute the corresponding movement program according to the control instructions, and the user's gait data is collected during the movement.

2. The gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot according to claim 1, characterized in that, The step of obtaining custom gait parameters and generating a first gait trajectory based on the gait parameters includes: Initial gait parameters are determined by using a preset gait template library or default gait parameters; The gait trajectory editor's first visual interface displays interactive elements for editing gait parameters; In response to an operation command for editing interactive elements of the gait parameters, the initial gait parameters are adjusted, and the corresponding gait trajectory preview results are displayed through the first visualization interface; The gait parameter submission button is displayed through the first visual interface; In response to a trigger operation for submitting the gait parameters using a button, the current initial gait parameters are used as the gait parameters, and a first gait trajectory is generated based on the gait parameters.

3. The gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot according to claim 1, characterized in that, The step of simulating and verifying the first gait trajectory to obtain a second gait trajectory that passes the simulation verification includes: The first gait trajectory is input into the gait simulation engine; The second visualization interface of the gait simulation engine obtains the physiological parameters, rehabilitation goals, and adjustment instructions for the preset simulation model input by the user. The preset simulation model is adjusted according to the adjustment instructions; The first step trajectory is simulated and calculated using the preset simulation model to simulate the force, muscle activity pattern and overall movement trajectory of the first step trajectory during the movement process, and the simulation results are demonstrated through three-dimensional animation. Based on the physiological parameters, the rehabilitation goals, and the simulation results, determine whether the first step trajectory meets the preset goals; When the first step gait trajectory meets the preset target, the first step gait trajectory is used as the second gait trajectory.

4. The gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot according to claim 1, characterized in that, The step of generating control commands based on the second gait trajectory and sending the control commands to the lower limb exoskeleton rehabilitation robot includes: The second gait trajectory is converted into initial control commands through a real-time control interface; Obtain the adjustment parameters input by the user, adjust the initial control command according to the adjustment parameters, and obtain the control command; The control commands are sent to the lower limb exoskeleton rehabilitation robot through the real-time control interface according to the preset communication protocol.

5. The gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot according to claim 1, characterized in that, The lower limb exoskeleton rehabilitation robot includes several joint modules, a power and control unit, and a sensing and feedback unit. The robot is controlled to execute corresponding movement programs according to the control commands, and gait data of the user is collected during the movement, including: The power and control unit drives each joint module to move according to the control command; The user's gait data during movement is collected through the sensing and feedback unit.

6. The gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot according to claim 5, characterized in that, The gait simulation verification method further includes: The sensing and feedback unit detects whether there are any abnormalities during the motion process; When the abnormal situation occurs, the power and control unit controls the lower limb exoskeleton rehabilitation robot to brake urgently and implement protective measures.

7. The gait simulation and verification method based on a lower limb exoskeleton rehabilitation robot according to claim 1, characterized in that, The gait simulation verification method further includes: The movement state of the lower limb exoskeleton rehabilitation robot is adjusted based on the gait data.

8. A gait simulation and verification system based on a lower limb exoskeleton rehabilitation robot, characterized in that, include: The gait trajectory editing module is used to obtain custom gait parameters and generate a first gait trajectory based on the gait parameters; The gait trajectory simulation and verification module is used to simulate and verify the first gait trajectory to obtain a second gait trajectory that passes the simulation verification. The control command generation module is used to generate control commands based on the second gait trajectory and send the control commands to the lower limb exoskeleton rehabilitation robot. The gait trajectory verification module is used to control the lower limb exoskeleton rehabilitation robot to execute the corresponding movement program according to the control instructions, and to collect the user's gait data during the movement.

9. A computer device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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