CN118244894A - Man-machine interaction method, system, equipment and medium of mobile rehabilitation robot - Google Patents
Man-machine interaction method, system, equipment and medium of mobile rehabilitation robot Download PDFInfo
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- A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
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- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
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Abstract
The application provides a man-machine interaction method, a system, equipment and a medium of a mobile rehabilitation robot, wherein the method comprises the steps of dividing a plane movement space into a plurality of predefined independent areas by utilizing the display prompt interface; randomly selecting a predefined area as a target area through the display prompt interface, and definitely indicating the target area through a visual prompt on the display prompt interface so as to guide the mobile rehabilitation robot to perform appointed movement; when the mobile rehabilitation robot detects that the mobile rehabilitation robot moves to the target area, automatically updating and lighting a new target area, and simultaneously recording the sequence of each lighted target area to form a display sequence; based on the display sequence, specific prompt information is generated and sent out and is used for guiding the mobile rehabilitation robot to conduct a series of preset motion paths according to a specific sequence so as to complete rehabilitation training tasks.
Description
Technical Field
The application relates to the technical field of rehabilitation robots, in particular to a man-machine interaction method, a system, equipment and a medium of a mobile rehabilitation robot.
Background
In the field of rehabilitation medicine, in particular for rehabilitation of upper limb dyskinesia and cognitive decline caused by cerebral stroke or other neurological diseases, traditional rehabilitation training methods rely mostly on direct intervention of a physical therapist and a series of standardized physical movements. While these approaches are somewhat effective, they often lack sufficient individuality and dynamic adaptability to meet the specific needs of all patients. In addition, the traditional methods have limited effectiveness in promoting memory and cognitive recovery, and the rehabilitation training requirements in these fields are far from being fully met.
In recent years, mobile rehabilitation robots and rehabilitation training methods based on gambling have attracted a lot of attention, and they aim to improve the participation degree and training effect of patients by providing training modes with strong interactivity and high interest. Despite the technological innovations in these advances, existing rehabilitation robot systems often focus on the assistance of physical movements, while there is still a great room for development in integrating memory and cognitive function training. In particular, how to effectively combine upper limb motor training with memory and cognitive ability recovery training and how to provide personalized and adaptive support through an intelligent power-assisted mode is a problem which is not fully solved by the prior art. In addition, human-computer interaction in existing systems often lacks targeted memory training tasks and dynamic adjustment mechanisms based on user performance. This limits the effectiveness of rehabilitation training, especially in training where it is desirable to promote the recovery of memory and cognitive function.
Disclosure of Invention
The application aims to provide a man-machine interaction method, a system, equipment and a medium of a mobile rehabilitation robot, which are at least used for combining the rehabilitation training actions of the upper limbs with the memory cognition training and improving the rehabilitation training effect.
To achieve the above object, some embodiments of the present application provide a man-machine interaction method of a mobile rehabilitation robot, the method including dividing a planar movement space into a plurality of predefined independent areas using the display prompt interface, each area being identifiable and used for displaying a moving object; randomly selecting a predefined area as a target area through the display prompt interface, and definitely indicating the target area through a visual prompt on the display prompt interface so as to guide the mobile rehabilitation robot to perform appointed movement; when the mobile rehabilitation robot detects that the mobile rehabilitation robot moves to the target area, automatically updating and lighting a new target area, and simultaneously recording the sequence of each lighted target area to form a display sequence; based on the display sequence, specific prompt information is generated and sent out and is used for guiding the mobile rehabilitation robot to conduct a series of preset motion paths according to a specific sequence so as to complete rehabilitation training tasks.
Further, the method further comprises: the mobile rehabilitation robot monitors and analyzes the motion trail and speed of the mobile rehabilitation robot and the position relation of the mobile rehabilitation robot relative to the target area in real time through the motion sensor to obtain motion data; and the mobile rehabilitation robot judges that the mobile rehabilitation robot cannot reach a target area according to a preset track or within a specified time according to the motion data, starts a power assisting mode and provides power assisting assistance for the direction of the target area.
Further, the assist mode includes: defining the inertia, damping and rigidity of the mobile rehabilitation robot as M 1,B1 and K 1 respectively; obtaining the external force F, the power F d, the displacement x 0 and the speed of the mobile rehabilitation robotAnd accelerationThe impedance model of the mobile rehabilitation robot has the following relation:
further, the assisting force F d is provided with a plurality of assisting force grades; and dynamically adjusting the power output by the mobile rehabilitation robot according to the motion data.
Further, the method further comprises: and when the mobile rehabilitation robot detects that the mobile rehabilitation robot reaches the target area or the motion trend of the mobile rehabilitation robot meets the target motion track, automatically releasing the power-assisting mode.
Further, the generating and sending specific prompt information includes: a hint is generated that requires that the target area in a particular order arrive at the action before repeating.
Further, the method further comprises: according to the corresponding and executing conditions of the mobile rehabilitation robot on the prompt information, the memory and executing training conditions of the training individuals are automatically evaluated, and the power-assisted mode implementation is adjusted according to the training conditions.
Some embodiments of the present application also provide a human-computer interaction system of a mobile rehabilitation robot, the system comprising: the motion sensor module is used for monitoring the position and the motion state of the mobile rehabilitation robot in real time and detecting whether the mobile rehabilitation robot has moved to a preset target area or not; the method comprises the steps of displaying a prompt interface, wherein the prompt interface is used for performing visual prompt and comprises the steps of dividing a plane movement space into a plurality of predefined independent areas, displaying a target area and indicating a mobile rehabilitation robot to perform appointed movement; the display sequence module is used for randomly selecting target areas, updating and lighting new target areas after the robot reaches each target area, and recording the sequence of each lighted target area to form a display sequence; and the power assisting module is used for controlling the mobile rehabilitation robot to provide corresponding power assisting.
Some embodiments of the present application also provide a human-computer interaction device of a mobile rehabilitation robot, the device comprising: one or more processors; and a memory storing computer program instructions that, when executed, cause the processor to perform the method as described above.
Some embodiments of the present application also provide a computer readable medium having stored thereon computer program instructions executable by a processor to implement the method of man-machine interaction of a mobile rehabilitation robot.
Compared with the prior art, in the scheme provided by the embodiment of the application, the man-machine interaction method of the mobile rehabilitation robot effectively combines the physical rehabilitation training of the upper limb with the memory and cognitive function training through intelligent man-machine interaction. The power-assisted output can be adjusted in real time according to the athletic performance of the individuals involved in training, and accurate physical assistance and dynamic training difficulty adjustment are provided for the individuals. This significantly improves the individuality and adaptability of the training compared to conventional, static or entirely manual-dependent rehabilitation training methods.
Drawings
FIG. 1 is a flowchart of a man-machine interaction method of a mobile rehabilitation robot according to an embodiment of the present application;
fig. 2 is an effect schematic diagram of a man-machine interaction method of a mobile rehabilitation robot according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a man-machine interaction system of a mobile rehabilitation robot according to an embodiment of the present application;
Fig. 4 is a schematic structural diagram of a man-machine interaction device of a mobile rehabilitation robot according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Some products in the market at present, such as upper limb rehabilitation products of Fourier and tall, usually have no active movement in a period of time when a patient is detected, and then the current mode is switched to a passive mode, so that a robot drives the patient to move to a designated position. Once the booster mechanism is triggered, the robot becomes a passive mode and does not interact with the patient. Restricting the autonomous movement of the patient and thus also impairing the healing effect.
Aiming at the technical problems, the embodiment of the application provides a man-machine interaction method of a mobile rehabilitation robot, which has the following core: s101, dividing a plane movement space into a plurality of predefined independent areas by utilizing the display prompt interface, wherein each area can be identified and used for displaying a moving object; s102, randomly selecting a predefined area as a target area through the display prompt interface, and clearly indicating the target area through a visual prompt on the display prompt interface so as to guide the mobile rehabilitation robot to perform appointed movement; s103, after the mobile rehabilitation robot detects that the mobile rehabilitation robot moves to the target area, automatically updating and illuminating a new target area, and simultaneously recording the sequence of each illuminated target area to form a display sequence; and S104, generating and sending specific prompt information based on the display sequence, wherein the prompt information is used for guiding the mobile rehabilitation robot to perform a series of preset motion paths according to a specific sequence so as to complete a rehabilitation training task.
The mobile rehabilitation robot is provided with a high-precision motion sensor, a graphical display prompt interface and a built-in processor and software algorithm, and is used for controlling the training process and implementing man-machine interaction. The display prompt interface can clearly show training tasks and instructions, and meanwhile key data in the training process are recorded. The robot display prompt interface divides the planar motion space into a plurality of predefined independent areas, the areas are distributed on the display interface, and each area represents a potential moving object. One area is randomly selected as an initial target area and indicated on a display interface by a visual cue (e.g., highlighting) to guide the mobile rehabilitation robot (and the patient participating in the training) to a designated movement. The patient participating in the training moves the mobile rehabilitation robot to the designated target area through the upper limb operation. The motion sensor of the robot monitors and analyzes the motion trail in real time, automatically updates the target area once the robot is detected to successfully reach the target area, lights up a new target area and indicates through a display prompt interface. The process loops and the system records the order of each illuminated target area to form a display sequence.
At some stage of the exercise training, specific memory training prompts are sent to the patient through the display prompt interface based on the previously recorded display sequence, for example, requiring the patient to repeat a particular sequence of exercise paths. This step aims at combining memory and cognitive function training, further stimulating and training the memory and cognitive ability of the patient by requiring the patient to memorize and perform a specific sequence of motor paths. According to the response of the patient to the prompt information and the training performance, the training effect is evaluated, and the subsequent training plan can be adjusted according to the evaluation result. The training difficulty can be automatically adjusted according to the progress of the patient, so that the training is challenging and the training can not exceed the capacity range of the patient.
The embodiment provides a comprehensive and effective rehabilitation training method by combining physical movement of the upper limbs with memory cognitive function training. The method can obviously improve the rehabilitation efficiency and the participation degree of training of the patient through intelligent man-machine interaction and personalized training adjustment, and particularly provides an innovative rehabilitation training scheme for the patient needing to improve physical exercise capacity and cognitive function simultaneously.
In some embodiments of the application, the method further comprises: the mobile rehabilitation robot monitors and analyzes the motion trail and speed of the mobile rehabilitation robot and the position relation of the mobile rehabilitation robot relative to the target area in real time through the motion sensor to obtain motion data; and the mobile rehabilitation robot judges that the mobile rehabilitation robot cannot reach a target area according to a preset track or within a specified time according to the motion data, starts a power assisting mode and provides power assisting assistance for the direction of the target area.
The mobile rehabilitation robot is equipped with high-precision motion sensors capable of capturing the motion state of the robot in real time, including speed, trajectory, and relative position between the robot and a predefined target area. These data are transmitted in real time to the central processing unit of the robot, where built-in algorithms analyze the data to evaluate the performance of the training. When the analysis results show that the robot (and the robot operated by the patient) fails to move in a predetermined trajectory or fails to reach the target area within a specified time, it is automatically determined that additional assistance is required. On the basis, the robot automatically starts a power assisting mode, and a proper amount of power assistance is provided to the direction of the target area through a driving system of the robot. Such assistance is intended to assist the patient in overcoming movement disorders and to assist the robot in reaching the target area more accurately and efficiently. The magnitude and the direction of the assistance are calculated dynamically by a processor of the robot according to the motion data, so that the provided assistance can not only effectively help a patient to complete a training task, but also can not completely replace the active motion of the patient, and the effectiveness of the training and the participation degree of the patient are maintained.
According to the embodiment, the individuation level and the adaptability of rehabilitation training are remarkably improved through intelligent motion monitoring and analysis and combination of the self-adaptive power-assisted mode. The method can provide immediate support when the patient encounters difficulty, and optimize the training process, thereby improving the rehabilitation efficiency and accelerating the recovery process of the patient. In addition, due to the introduction of the power-assisted mode, the flexibility and the interactivity of training are improved, and the rehabilitation training is more humanized and patient-friendly.
In some embodiments of the application, the assist mode includes: defining the inertia, damping and rigidity of the mobile rehabilitation robot as M 1,B1 and K 1 respectively; obtaining the external force F, the power F d, the displacement x 0 and the speed of the mobile rehabilitation robotAnd accelerationThe impedance model of the mobile rehabilitation robot has the following relation:
Through implementing impedance control model, the mobile rehabilitation robot of this embodiment can provide fine-tuning's helping hand, has strengthened the interactivity and the adaptability of training greatly. The intelligent assistance assisting device can be dynamically adjusted according to real-time athletic performance and requirements of users, so that training effectiveness is guaranteed, and comfort and satisfaction of the users are improved. In addition, the method is also beneficial to improving the accuracy and individualization level of rehabilitation training, and provides a more customized rehabilitation solution for users.
In some embodiments of the present application, the assist force F d sets a plurality of assist force levels; and dynamically adjusting the power output by the mobile rehabilitation robot according to the motion data.
The control system of the mobile rehabilitation robot presets a plurality of power-assisted grades, and each grade corresponds to different power-assisted sizes. These assist levels may be set according to the specific needs of the rehabilitation training and the individual differences of the user, for example from light assist (low level) to significant assist (high level). The setting of the boost level allows rehabilitation training to provide proper physical support at different stages or for different training tasks, making the training process more flexible and adaptable.
The mobile rehabilitation robot monitors the motion data such as displacement, speed, acceleration and the like of the mobile rehabilitation robot in real time through a motion sensor of the mobile rehabilitation robot, and simultaneously obtains external force applied to the robot by a user. These data are transmitted in real time to the central processing unit of the robot for analysis. Based on the motion data obtained by the analysis, the control system of the robot will evaluate the performance of the current training task and the motion ability of the user. If it is detected that the user encounters difficulty in performing a task, such as a slow motion or inability to reach the target area along a predetermined trajectory, the level of assistance will be automatically increased to provide greater assistance. The adjustment of the assistance is not only based on the current performance and needs of the user, but also takes into account the rehabilitation progress and long-term training goals of the user. The system can continuously adjust the power-assisted level in the whole training process, and ensures that the user always carries out rehabilitation training under the most proper support.
Through setting up a plurality of helping hand grades and carrying out dynamic adjustment to helping hand according to motion data, the removal rehabilitation robot in this embodiment can provide more individualized and the rehabilitation training assistance of refinement for the user. The method not only increases the flexibility and adaptability of training, but also helps to improve the training efficiency and satisfaction of users. In addition, the ability of dynamic adjustment helping hand output makes rehabilitation training can optimize to user's specific demand and recovered stage to accelerate rehabilitation process, improve recovered effect.
In some embodiments of the application, the method further comprises: and when the mobile rehabilitation robot detects that the mobile rehabilitation robot reaches the target area or the motion trend of the mobile rehabilitation robot meets the target motion track, automatically releasing the power-assisting mode.
The mobile rehabilitation robot monitors the position and the motion state of the mobile rehabilitation robot in real time through a precise sensor system. When the robot detects that the robot successfully reaches a preset target area or the movement trend of the robot fully coincides with the movement track of the target, the robot automatically judges that the current training task or the movement target is completed. The determination of reaching the target area may be based on a displacement sensor and positioning technique of the robot; the judgment of the movement trend involves the analysis of the movement parameters such as the speed, the acceleration and the like of the robot and the comparison with the preset track. When one of the above conditions is met, the control system of the mobile rehabilitation robot will automatically deactivate the booster mode. This means that the robot will stop providing additional assistance, revert to a normal state of motion, wait for the next operation of the user or go to the next training task. The function of automatically releasing the power assisting mode not only reduces the excessive dependence on the user and promotes the active participation and the self-control capability of the user, but also improves the safety and the efficiency of training.
In some embodiments of the present application, the generating and sending specific prompt information includes: a hint is generated that requires that the target area in a particular order arrive at the action before repeating.
In the rehabilitation training process, the mobile rehabilitation robot divides the plane movement space into a plurality of predefined areas through a display prompt interface, and guides a user to move the robot to the areas through the upper limb movement. After each time the target area is successfully reached, the robot automatically records the sequence number of the area to form a training sequence. Based on the completed training sequence, the control system of the robot will generate specific prompt information, requiring the user to repeat the previous target area arrival actions in a specific order. For example, if the previous training sequence was 1-3-2-4, the system may generate a hint message that asks for "please repeat the position of the second motion", i.e. point to region 3. The generated prompt information is sent out through a display prompt interface or an audio output module of the mobile rehabilitation robot to guide a user to carry out memory training. This training involves not only the physical mobility of the user, but more importantly the training of memory and cognitive functions. The user tries to repeat the appointed motion path according to the prompt information, the robot monitors the motion execution condition of the user through the sensor, and evaluates according to the response of the user to the prompt information so as to judge the effect of memory training.
By generating the prompt information of the target area reaching action in a specific order before the repetition, the rehabilitation method combining physical movement and memory training is realized. The application of the method not only can promote the upper limb movement ability of the user, but also can promote the recovery of the cognitive function through the memory training task, and is particularly helpful for improving the memory. Through the training mode with strong interactivity, the training participation degree and training effect of the user are obviously improved.
In some embodiments of the application, the method further comprises: according to the corresponding and executing conditions of the mobile rehabilitation robot on the prompt information, the memory and executing training conditions of the training individuals are automatically evaluated, and the power-assisted mode implementation is adjusted according to the training conditions.
After the mobile rehabilitation robot is guided to complete a specific memory training task (for example, target area reaching actions in a specific sequence before repeating), response and execution conditions of a training individual to prompt information are monitored and analyzed in real time through a sensor system and a built-in algorithm of the mobile rehabilitation robot. The robotic assessment includes, but is not limited to, whether the training individual is able to accurately recall and execute a specified sequence of movements, the speed and accuracy of execution, and the degree of coincidence of the trajectory of movements during execution with a predetermined trajectory. Based on the evaluation result, the performance of the training individual on the memory and execution tasks is automatically determined, and if the training individual is found to be difficult to perform the memory training tasks, the system may decide to increase the assistance strength of the assistance mode to help the individual to complete the training tasks better. Conversely, if the training individual is able to perform the task with ease and accuracy, the system may reduce the provision of assistance to encourage more voluntary exercise, thereby facilitating further improvement in the exercise capacity and memory of the training individual. The power-assisted mode is adjusted based on a dynamic feedback loop, namely the size and the time provided by the power assistance are continuously adjusted according to the real-time performance and progress of the training individuals, so that the optimal training effect is realized.
The following describes implementation details of the man-machine interaction method of the mobile rehabilitation robot according to the embodiment of the present application with reference to a specific application example, and the following description is only provided for understanding the implementation details, and is not necessary for implementing the present embodiment.
As shown in fig. 2, the mobile rehabilitation robot divides the screen into 9 areas and numbers them. Assuming that the current device is located at (x 0, y 0), the current desired target point (x 1, y 1), the system inertia coefficient M 1, the damping coefficient B 1, the stiffness K 1, the device displacement x 0, the speedAccelerationThe external force applied by the system is F. The system impedance model equation is as follows:
In this application scenario, the device is required to follow the force exerted by the patient. When the external force is lost, the apparatus should not return to the initial position any more, so the rigidity K 1 =0 is required. The power to be introduced in the system is F d, the size of the power to be introduced can be set through system parameters, such as different power-assisted grades, the 1-grade power-assisted grade corresponds to the power-assisted size of 2N, and the 3-grade power-assisted grade corresponds to the power-assisted size of 6N. And the direction of F d is determined by the vector of the current location of the device and the desired target location, (x 1-x0,y1-y0). The assistance can better help the user, give out certain prompt information of the user, and can automatically move to the target position after the user has one direction, thereby greatly improving the initiative of the patient, and not limiting the initiative of the autonomous movement of the user in the whole training process
The triggering and implementation of the power assisting comprise a response link of the cognitive rehabilitation, wherein the device is switched to an active mode, the device meets the relation in the formula (1), and at the moment, F d =0; recording the distance between the initial position of the device and the desired target position at this timeAssuming that the current real-time position of the device is (x, y), if the distance S between the current device and the target position (x 1,y1) is less than S 0, let S 0 =s; if S-S 0 is more than 5mm and S is more than S 0 for 3 seconds, introducing a power assisting mechanism; f d was assigned as described above. At the moment, the patient can feel that the device moves along the patient towards one direction, so that the patient can be helped to recall which target area the patient should reach, and at the moment, the patient can form resultant force with the robot to accelerate to move to the target point; if the patient cannot recall, the robot can also drive the patient to reach the target point; when S-S 0 <5mm, the current training task is considered to be completed. The memory and training process of the next round can be started; finally, according to the degree of active participation of the patient, the number of times and time of the activation of the power-assisted mode can be evaluated in the training process of the patient.
Fig. 3 shows a human-computer interaction system of a mobile rehabilitation robot, the system comprising:
the motion sensor module is used for monitoring the position and the motion state of the mobile rehabilitation robot in real time and detecting whether the mobile rehabilitation robot has moved to a preset target area or not;
The method comprises the steps of displaying a prompt interface, wherein the prompt interface is used for performing visual prompt and comprises the steps of dividing a plane movement space into a plurality of predefined independent areas, displaying a target area and indicating a mobile rehabilitation robot to perform appointed movement;
The display sequence module is used for randomly selecting target areas, updating and lighting new target areas after the robot reaches each target area, and recording the sequence of each lighted target area to form a display sequence;
and the power assisting module is used for controlling the mobile rehabilitation robot to provide corresponding power assisting.
It should be noted that, in the embodiment of the present application, a system embodiment corresponding to a method embodiment, details of implementation of the embodiment of the present application have been set forth in the method embodiment, and in order to avoid repetition, details are not repeated herein.
In addition, the embodiment of the application further provides a laser frequency stabilization device in a near ultraviolet band, the structure of the device is shown in fig. 4, the device comprises a memory 90 for storing computer readable instructions and a processor 100 for executing the computer readable instructions, wherein when the computer readable instructions are executed by the processor, the processor is triggered to execute the man-machine interaction method of the mobile rehabilitation robot.
The methods and/or embodiments of the present application may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. The above-described functions defined in the method of the application are performed when the computer program is executed by a processing unit.
The computer readable medium according to the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
In the present application, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowchart or block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of devices, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
As another aspect, the embodiment of the present application also provides a computer-readable medium that may be contained in the apparatus described in the above embodiment; or may be present alone without being fitted into the device. The computer readable medium carries one or more computer readable instructions executable by a processor to perform the steps of the methods and/or aspects of the various embodiments of the application described above.
In one exemplary configuration of the application, the terminal, the devices of the services network each include one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer-readable media include both permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium which can be used to store information that can be accessed by a computing device.
In addition, the embodiment of the application also provides a computer program which is stored in the computer equipment, so that the computer equipment executes the method for executing the control code.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, e.g., using Application Specific Integrated Circuits (ASIC), a general purpose computer or any other similar hardware device. In some embodiments, the software program of the present application may be executed by a processor to implement the above steps or functions. Likewise, the software programs of the present application (including associated data structures) may be stored on a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. In addition, some steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
It will be evident to those skilled in the art that the application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the apparatus claims can also be implemented by means of one unit or means in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Claims (10)
1. A human-computer interaction method of a mobile rehabilitation robot, wherein the mobile rehabilitation robot is configured with a motion sensor and a display prompt interface, the method comprising:
Dividing the planar motion space into a plurality of predefined independent areas by utilizing the display prompt interface, wherein each area can be identified and used for displaying a moving object;
Randomly selecting a predefined area as a target area through the display prompt interface, and definitely indicating the target area through a visual prompt on the display prompt interface so as to guide the mobile rehabilitation robot to perform appointed movement;
when the mobile rehabilitation robot detects that the mobile rehabilitation robot moves to the target area, automatically updating and lighting a new target area, and simultaneously recording the sequence of each lighted target area to form a display sequence;
Based on the display sequence, specific prompt information is generated and sent out and is used for guiding the mobile rehabilitation robot to conduct a series of preset motion paths according to a specific sequence so as to complete rehabilitation training tasks.
2. The human-machine interaction method of claim 1, further comprising:
the mobile rehabilitation robot monitors and analyzes the motion trail and speed of the mobile rehabilitation robot and the position relation of the mobile rehabilitation robot relative to the target area in real time through the motion sensor to obtain motion data;
and the mobile rehabilitation robot judges that the mobile rehabilitation robot cannot reach a target area according to a preset track or within a specified time according to the motion data, starts a power assisting mode and provides power assisting assistance for the direction of the target area.
3. The human-machine interaction method according to claim 2, wherein the assistance mode includes:
defining the inertia, damping and rigidity of the mobile rehabilitation robot as M 1,B1 and K 1 respectively;
obtaining the external force F, the power F d, the displacement x 0 and the speed of the mobile rehabilitation robot And acceleration
The impedance model of the mobile rehabilitation robot has the following relation:
4. A human-machine interaction method according to claim 3, wherein the assistance F d sets a plurality of assistance levels; and dynamically adjusting the power output by the mobile rehabilitation robot according to the motion data.
5. The human-machine interaction method according to any one of claims 2 to 4, further comprising:
and when the mobile rehabilitation robot detects that the mobile rehabilitation robot reaches the target area or the motion trend of the mobile rehabilitation robot meets the target motion track, automatically releasing the power-assisting mode.
6. The human-computer interaction method according to claim 5, wherein the generating and sending specific prompt information comprises: a hint is generated that requires that the target area in a particular order arrive at the action before repeating.
7. The human-machine interaction method according to claim 5, further comprising: according to the corresponding and executing conditions of the mobile rehabilitation robot on the prompt information, the memory and executing training conditions of the training individuals are automatically evaluated, and the power-assisted mode implementation is adjusted according to the training conditions.
8. A human-machine interaction system of a mobile rehabilitation robot, the system comprising:
the motion sensor module is used for monitoring the position and the motion state of the mobile rehabilitation robot in real time and detecting whether the mobile rehabilitation robot has moved to a preset target area or not;
The method comprises the steps of displaying a prompt interface, wherein the prompt interface is used for performing visual prompt and comprises the steps of dividing a plane movement space into a plurality of predefined independent areas, displaying a target area and indicating a mobile rehabilitation robot to perform appointed movement;
The display sequence module is used for randomly selecting target areas, updating and lighting new target areas after the robot reaches each target area, and recording the sequence of each lighted target area to form a display sequence;
and the power assisting module is used for controlling the mobile rehabilitation robot to provide corresponding power assisting.
9. A human-machine interaction device for a mobile rehabilitation robot, the device comprising:
One or more processors; and
A memory storing computer program instructions that, when executed, cause the processor to perform the method of any one of claims 1 to 7.
10. A computer readable medium having stored thereon computer program instructions executable by a processor to implement the method of any of claims 1 to 7.
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