Motion intention-based rehabilitation robot-assisted motion system and method

Abstract

Disclosed in the present invention are a rehabilitation robot-assisted motion method and system based on a user's active motion intention. The described method comprises: acquiring eye movement information of a user; processing the eye movement information to generate a user attention degree coefficient; and in response to that the user attention degree coefficient meets a preset condition, generating an execution control signal based on the eye movement information for controlling an execution mechanism to assist the user in movement. The active motion intention of the user can be acquired, and the execution mechanism can be controlled to move based on the active motion intention of the user, so that the effect of rehabilitation training of the user can be improved.

Description

Rehabilitation robot assisted motion system and method based on motion intention Technical Field

[0001] The present invention relates to the field of rehabilitation robots, and further to a rehabilitation robot auxiliary motion system and method based on motion intention. Background Art

[0002] Rehabilitation robots are considered "wearable devices" for specialized environments, offering functions such as assisting mobility, providing rehabilitation therapy, and reducing labor intensity. Rehabilitation robots are a high-end rehabilitation medical technology that has developed in recent years. They are the product of a fusion of robotics and medical technologies, helping disabled patients regain motor function and offering hope for a return to society.

[0003] Rehabilitation robots are currently mainly suitable for upper or lower limb motor dysfunction caused by stroke, brain injury, spinal injury, neurological injury, muscle injury and orthopedic diseases. They help patients reshape the brain's motor nerves and restore the brain's control over upper limb movements, thereby improving patients' daily living ability.

[0004] Rehabilitation robots can be divided into rehabilitation treatment / training robots, auxiliary terminal robots and health care combined intelligent robots according to their functions; according to the parts of the body they target, they can be divided into upper limb and lower limb robots; according to the way of human-machine integration, they can be divided into exoskeleton type and chimeric type.

[0005] It should be pointed out that in the process of using current rehabilitation robots for rehabilitation training, rehabilitation training is passive. Patients can only perform rehabilitation training according to the original functions of the rehabilitation equipment, which cannot be consistent with the user's movement intentions, and the effect of rehabilitation training is limited.

[0006] Summary of the Invention

[0007] In response to the above technical problems, the purpose of the present invention is to provide a rehabilitation robot-assisted motion system and method based on the patient's movement intention, which can obtain the user's active movement intention, and can control the movement of the actuator based on the user's active movement intention, thereby improving the effect of the user's rehabilitation training.

[0008] In order to achieve the above object, the present invention aims to provide a rehabilitation robot-assisted movement method based on the user's active movement intention, comprising:

[0009] Obtain user's eye movement information;

[0010] Processing the eye movement information to generate a user attention degree coefficient;

[0011] In response to the user attention degree coefficient meeting a preset condition, an execution control signal is generated based on the eye movement information to control an execution mechanism to assist the user in movement.

[0012] In some embodiments, a rehabilitation robot-assisted motion system based on the user's active motion intention is further provided, comprising:

[0013] Signal acquisition module, used to obtain user's eye movement information;

[0014] A signal processing module, configured to process the eye movement information to generate a user attention degree coefficient;

[0015] The exercise intention evaluation module is used to generate an execution control signal based on the user degree information in response to the user attention degree coefficient meeting a preset condition, so as to control the execution mechanism to assist the user in exercise. Beneficial effects:

[0016] 1) This application can obtain the user's active movement intention and control the movement of the actuator based on the user's active movement intention, thereby improving the effect of the user's rehabilitation training;

[0017] 2) This application targets users who lack the ability to actively exercise. It uses eye movement information to determine the user's exercise intention and assists the user in exercising based on the exercise intention, which is conducive to improving the effectiveness of their rehabilitation training.

[0018] 3) This application can adaptively adjust working parameters to adaptively adjust exercise intensity, which will effectively increase users' enthusiasm and participation in training;

[0019] 4) This application has a variety of sports mode options to meet the user's various usage needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The preferred embodiments will be described below in a clear and understandable manner with reference to the accompanying drawings to further illustrate the above-mentioned characteristics, technical features, advantages and implementation methods of the present invention.

[0021] 1 is a flow chart of a rehabilitation robot-assisted exercise method based on a user's active exercise intention according to a preferred embodiment of the present invention;

[0022] 2 is a first sub-flowchart of a rehabilitation robot-assisted exercise method based on a user's active exercise intention according to a preferred embodiment of the present invention;

[0023] 3 is a second sub-flowchart of the rehabilitation robot-assisted exercise method based on the user's active exercise intention according to a preferred embodiment of the present invention;

[0024] 4 is a third sub-flowchart of the rehabilitation robot-assisted exercise method based on the user's active exercise intention according to a preferred embodiment of the present invention;

[0025] 5 is a structural block diagram of a rehabilitation robot-assisted motion system based on a user's active motion intention according to a preferred embodiment of the present invention;

[0026] FIG6 is a structural block diagram of a modified implementation of a rehabilitation robot-assisted motion system based on user active motion intention according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the specific embodiments of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings and other embodiments can be obtained based on these drawings without inventive work.

[0028] To simplify the drawings, only portions relevant to the invention are schematically depicted in each figure; they do not represent the actual structure of the product. Furthermore, to simplify the drawings and facilitate understanding, in some figures, only one component with the same structure or function is schematically depicted or labeled. In this document, "one" not only means "only one" but also "more than one."

[0029] It should be further understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0030] It should be noted that, unless otherwise specified or limited, the terms "mounted," "connected," and "connected" should be understood broadly. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediary; and internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in the present invention based on the specific circumstances.

[0031] In addition, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0032] Research in recent years has shown that the human nervous system is plastic throughout the life course, that is, the nervous system will adapt to changes in the external environment through "relearning", or its own structure and function will be continuously modified and reorganized when damaged. Neuroplasticity is an important foundation of modern rehabilitation medicine and a top priority in rehabilitation training. Neural reorganization and compensation are important features of the neural remodeling process. Studies have shown that important factors affecting neural reorganization in rehabilitation training include appropriate training prescriptions and active patient participation. Even if the user does not have the ability to actively move, the intention to actively move is necessary to ensure the effectiveness of training. Effectively identifying the user's active movement intention is one of the keys for rehabilitation robots to ensure the effectiveness of patient rehabilitation training.

[0033] A person's eye movement information is related to the content of the brain's thinking. The amount of information that the brain can process at the same time is limited. In order to decide which information needs to be processed in a timely manner, humans and many other animals have evolved an information selection mechanism, which is usually called attention. Attention is the direction or concentration of mental activities on a certain object. Attention enables people to selectively process certain stimuli and ignore other stimuli to avoid information overload in the brain. A large number of studies have confirmed that the position of the eyes is usually related to the things that are paid attention to and thought about, especially when observing an object with a goal. This is called the eye-brain consistency hypothesis. Based on the eye-brain consistency hypothesis, this application integrates eye movement information into rehabilitation training, effectively improving the effect of rehabilitation training.

[0034] Example 1

[0035] FIG1 shows a flow chart of a rehabilitation robot-assisted exercise method based on a user's active exercise intention according to an embodiment of the present application. Referring to FIG1 , the rehabilitation robot-assisted exercise method based on a user's active exercise intention includes:

[0036] 101. Obtain user's eye movement information;

[0037] 102. Process the eye movement information to generate a user attention degree coefficient;

[0038] 103. In response to the user attention coefficient meeting a preset condition, generating an execution control signal based on the eye movement information, for controlling an execution mechanism to assist the user in movement.

[0039] In the rehabilitation robot-assisted movement method based on the user's active movement intention provided in the present application, the user's active movement intention can be evaluated based on the user's eye movement information, and the eye movement information can be integrated into the rehabilitation training, which can improve the effect of the rehabilitation training.

[0040] In some embodiments, in step 101 above, the user's eye movement information comes from the eye movement sensor 100. The eye movement sensor 100 can locate the pupil position through image processing technology, obtain coordinates, and calculate the point of eye gaze or gaze through a certain algorithm. In some embodiments, the eye movement sensor 100 is a "non-invasive" technology based on video oculographic (VOG). Its basic principle is: a beam of light (near-infrared light) and a camera are aimed at the subject's eyes, and the direction of the subject's gaze is inferred through the light and back-end analysis. The camera records the interaction process. In addition to monitoring gaze, it can also display other useful measurement indicators, including pupil size and blink rate.

[0041] In some implementations, in step 102 above, the user attention coefficient is calculated using the following formula:

[0042] Among them, C focus is the user attention coefficient; t start is the time when the moving target appears; t curr is the current time; f eye is the sampling frequency of eye movement information;

[0043] f focus t start to t curr Satisfy within time |P eye -P targ |<|r targ |The number of eye movements under the condition, where P targ The coordinates of the preset moving target, P eye The gaze target obtained by mapping the user's eye movement information, r targ is the preset distance.

[0044] In some implementations, the above step 103 includes:

[0045] 103a. In response to the user attention coefficient satisfying a first preset condition, generate a first execution control signal based on the user attention coefficient, for controlling the execution mechanism to move according to preset working parameters.

[0046] In some embodiments, the preset operating parameters include a preset target speed parameter V targ and preset target force parameter F targ In the above step 1031, when C focus >C cons When , it is considered that the user attention coefficient meets the first preset condition, where C cons is the preset attention threshold in the constant assistance mode, and the rehabilitation robot is at the preset target speed parameter Vtarg and preset target force parameter F targ Assisting the user to move to the target. The above step 103a can be called a constant assistance mode.

[0047] In some implementations, the above step S103 includes:

[0048] 103A. In response to the user attention coefficient satisfying a second preset condition, generating a second execution control signal based on the user attention coefficient, for controlling the actuator to move according to a first operating parameter, wherein the first operating parameter is less than a preset operating parameter;

[0049] 103B. Within a preset time period, in response to an increase in the user attention coefficient meeting a preset condition, determine an adaptive coefficient based on the increase in the user attention coefficient, and adjust the first operating parameter based on the adaptive coefficient and a preset operating parameter.

[0050] In step 103A, the first operating parameter is a certain percentage of the preset operating parameter. In step 103B, as the user's attention level increases, the proportion of the first operating parameter to the preset operating parameter is adaptively increased based on the adaptive coefficient until the preset operating parameter is reached. Adaptively adjusting the operating parameters and exercise intensity in steps 103A and 103B will effectively increase the user's enthusiasm for and participation in training. These steps 103A and 103B can be referred to as an adaptive assistance mode.

[0051] In the above step 103B, the adaptive coefficient μ adpa The calculation formula is as follows:

[0052] Among them, C adpa To preset the attention threshold; is the attention scaling factor.

[0053] For example, according to the preset target speed parameter V targ Calculate the adaptive target speed parameter V adap =μ adap V targ , according to the preset target force parameter F targ Calculate the adaptive force parameter F adap =μ adap F targ , the rehabilitation robot will use the speed parameter V adap and force parameter F adap Provides exercise assistance to users.

[0054] In some embodiments, the rehabilitation robot-assisted movement method based on the user's active movement intention further includes, before obtaining the user's eye movement information:

[0055] 104. Control the movement of the actuator according to the initial working parameters;

[0056] In the above step 103, further comprising:

[0057] 1031. Fusing the control parameter corresponding to the control signal with the initial operating parameter to generate a fused operating parameter;

[0058] 1032. Compare the fused working parameter with the user's current working parameter, and in response to the user's current working parameter not reaching the fused working parameter, control the actuator movement with the auxiliary parameter to assist the user's movement;

[0059] 1033. In response to the user's current working parameter reaching or exceeding the fused working parameter, the parameter is used to control the movement of the actuator to increase the resistance to the user's movement.

[0060] In some implementations, the above steps 1031 , 1032 , and 1033 can be referred to as an adaptive assistance mode.

[0061] In some embodiments, the initial operating parameters include an initial motion speed V init and target force parameter F targ , auxiliary parameters include adaptive speed parameter V adap , determine V by the following formula adap : V adpa =μ adpa (V targ -V init )+V init

[0062] Among them, C adpa To preset the attention threshold; is the attention zoom factor; V targ Preset target speed.

[0063] In some embodiments, when the user's current working parameter reaches or exceeds the fusion working parameter, the target force parameter F targ Controls actuator movement to increase resistance to user movement.

[0064] Example 2

[0065] The present application further provides a rehabilitation robot-assisted motion system based on the user's active movement intention, including: a signal acquisition module 10, a signal processing module 20 and a motion intention evaluation module 30, the signal acquisition module 10 is used to obtain the user's eye movement information; the signal processing module 20 is used to process the eye movement information to generate a user attention degree coefficient; the motion intention evaluation module 30 is used to generate an execution control signal based on the user degree information in response to the user attention degree coefficient meeting a preset condition, so as to control the movement of the actuator 40.

[0066] In some embodiments, the actuator 40 is a driver, such as a motor, which can assist the user in performing rehabilitation exercises.

[0067] In some embodiments, the signal processing module 20 includes: a timing unit 21, a frequency acquisition unit 22, a coordinate acquisition unit 23, a counting unit 24, and a calculation unit 25. The timing unit 21 is used to record the time t when the moving target appears. start and the current time t curr The frequency acquisition unit 22 is used to obtain the acquisition frequency of the user's eye movement information; the coordinate acquisition unit 23 is used to obtain the coordinates of the preset moving target P targ , the gaze target P obtained by mapping the user's eye movement information eye ; The counting unit 24 is used to count t start to t curr Satisfy within time |P eye -P targ |<|r targ |The number of eye movements under the condition, where r targ The calculation unit 25 is used to determine the user attention coefficient C based on the following formula focus :

[0068] In some embodiments, the movement intention assessment module 30 includes a judgment unit 31 and a control signal generation unit 32. The judgment unit 31 is configured to determine whether the user attention coefficient satisfies a first preset condition; when the user attention coefficient satisfies the first preset condition, the control signal generation unit 32 is configured to generate a first execution control signal based on the user attention coefficient, for controlling the actuator to move according to preset working parameters.

[0069] In the above embodiment, when the user's attention coefficient meets the first preset condition, it can be judged that the user has reached a certain level of attention to the movement target, and the rehabilitation robot assists the user in achieving the movement target according to the preset working parameters; on the contrary, if the user's attention coefficient does not meet the first preset condition, it means that the user's attention level to the movement target has not been reached, and the rehabilitation robot will not assist the user in movement.

[0070] In some embodiments, the determination unit 31 can also be used to determine whether the user attention coefficient satisfies a second preset condition. When the user attention coefficient satisfies the second preset condition, the control signal generation unit 32 can also be used to generate a second execution control signal based on the user attention coefficient, for controlling the actuator to move according to the first operating parameter. Preferably, the intensity of the first operating parameter is less than the preset operating parameter. In other words, the first operating parameter is only a certain proportion of the preset operating parameter.

[0071] The exercise intention assessment module 30 further includes an adaptive coefficient calculation unit 33. Within a preset time period, in response to a gradual increase in the user attention coefficient, the adaptive coefficient calculation unit 33 is configured to determine an adaptive coefficient based on the increase in the user attention coefficient. The control signal generation unit 32 is configured to adjust the first operating parameter based on the adaptive coefficient and the preset operating parameter. Preferably, as the user attention coefficient gradually increases, the proportion of the first operating parameter to the preset operating parameter is increased based on the adaptive coefficient until the first operating parameter equals the preset operating parameter.

[0072] Referring to Figure 5 , the rehabilitation robot-assisted motion system based on user-intentioned movement further includes a state assessment module 80. State assessment module 80 is in communication with planning module 60, movement intention assessment module 30, and actuator 40. State assessment module 80 is capable of obtaining initial motion parameters from planning module 60 and user intention parameters from movement intention assessment module 30. State assessment module 80 can then fuse the initial motion parameters with the user intention parameters to generate fused operating parameters.

[0073] The state evaluation module 80 can also compare the fusion working parameters with the user's actual state parameters. If the user's actual state parameters do not reach (are less than) the fusion working parameters, the actuator is appropriately controlled to assist the user's movement with a certain force (the actuator is controlled to work with auxiliary parameters); if the user's actual state exceeds (is greater than) the fusion working parameters, the actuator is appropriately controlled to hinder the user's movement with a certain force.

[0074] 5 , in some embodiments, the rehabilitation robot-assisted motion system based on the user's active motion intention further includes a target module 50. Target module 50 is used to store training targets, including pre-stored schemes or adjustable setting parameters for designing motion targets, including target quantities such as target position / angle or target trajectory.

[0075] In some embodiments, the rehabilitation robot-assisted motion system based on the user's active motion intention further includes a planning module 60. The planning module 60 can process the training target to convert a single or abstract training target into fixed motion and force parameters executable by the rehabilitation robot.

[0076] In some embodiments, the rehabilitation robot-assisted exercise system based on the user's active exercise intention further includes a target communication module 70 for converting training targets into visual signals, auditory signals, or tactile signals to guide the user in training. For example, target communication module 70 is a display that can convert training targets into image signals for display or play them through sound.

[0077] It should be noted that the above embodiments can be freely combined as needed. The above are only preferred embodiments of the present invention. It should be noted that those skilled in the art can make several improvements and modifications without departing from the principles of the present invention, and such improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A rehabilitation robot-assisted motion method based on the user's active motion intention, characterized in that: include: Get the user's eye movement information; Processing the eye movement information to generate a user attention degree coefficient; In response to the user attention degree coefficient satisfying a preset condition, an execution control signal is generated based on the eye movement information to control an execution mechanism to assist the user in movement.

2. The rehabilitation robot-assisted movement method based on the user's active movement intention according to claim 1, characterized in that: The user attention coefficient is calculated by the following formula: Among them, C focus is the user attention coefficient; t start is the time when the moving target appears; t curr is the current time; f eye is the sampling frequency of eye movement information; f focus t start to curr Satisfy within time |P eye -P targ |<|r targ |The number of eye movements under the condition, where P targ Preset the coordinates of the moving target, P eye The gaze target obtained by perceiving the user's eye movement information mapping, r targ is the preset distance.

3. The rehabilitation robot-assisted movement method based on the user's active movement intention according to claim 2, characterized in that: In response to the user attention degree coefficient satisfying a first preset condition, a first execution control signal is generated based on the user attention degree coefficient, for controlling the execution mechanism to move according to preset working parameters.

4. The rehabilitation robot-assisted movement method based on the user's active movement intention according to claim 2, characterized in that: In response to the user attention coefficient satisfying a second preset condition, generating a second execution control signal based on the user attention coefficient, for controlling the execution mechanism to move according to a first working parameter, wherein the first working parameter is less than the preset working parameter; In a preset time period, in response to an increase in the user attention coefficient satisfying a preset condition, an adaptive coefficient is determined based on the increase in the user attention coefficient, and the first operating parameter is adjusted based on the adaptive coefficient and the preset operating parameter.

5. The method for rehabilitation robot-assisted movement based on user's active movement intention according to claim 4, characterized in that: The adaptive coefficient μ adpa The calculation formula is as follows: Among them, C adpa To preset the attention threshold; is the attention scaling factor.

6. The rehabilitation robot-assisted movement method based on the user's active movement intention according to claim 2, characterized in that: Before obtaining the user's eye movement information, the method further includes: controlling the movement of the actuator according to the initial working parameters; In response to the user attention coefficient meeting a preset condition, generating an execution control signal based on the user attention information to control an execution mechanism to assist the user in exercising, further comprising: Fusion the control parameter corresponding to the control signal with the initial working parameter to generate a fusion working parameter; comparing the fused working parameter with the user's current working parameter, and in response to the user's current working parameter not reaching the fused working parameter, controlling the actuator movement with the auxiliary parameter to assist the user's movement; In response to the current working parameter of the user reaching or exceeding the fused working parameter, the movement of the actuator is controlled by the obstruction parameter to increase the resistance to the user's movement.

7. The method for rehabilitation robot-assisted movement based on user's active movement intention according to claim 6, characterized in that: The initial working parameters include the initial motion speed V init and the target force parameter F targ , the auxiliary parameters include an adaptive speed parameter V adap , determine V by the following formula adap : V adpa =μ adpa (V targ -V init )+V init Among them, C adpa To preset the attention threshold; is the attention scaling factor; V targ Preset target speed.

8. The method for rehabilitation robot-assisted movement based on user's active movement intention according to claim 7, characterized in that: In response to the user's current working parameter reaching or exceeding the fusion working parameter, the target force parameter F targ Controls actuator movement to increase resistance to user movement.

9. A rehabilitation robot-assisted motion system based on the user's active motion intention, characterized in that: include: A signal acquisition module is used to obtain the user's eye movement information; A signal processing module, used for processing the eye movement information to generate a user attention degree coefficient; The movement intention evaluation module is used to generate an execution control signal based on the user degree information in response to the user attention degree coefficient meeting a preset condition, so as to control the execution mechanism to assist the user in movement.

10. The rehabilitation robot-assisted motion system based on user's active motion intention according to claim 9, characterized in that: The signal processing module comprises: Timing unit, used to record the time t when the moving target appears start and the current time t curr ; A frequency acquisition unit, used to acquire the collection frequency of the user's eye movement information; A coordinate acquisition unit, used to acquire the coordinates P of a preset moving target targ , the gaze target P obtained by mapping the user's eye movement information eye ; Counting unit, used to count t start to curr The number of eye movements that satisfy the condition |Peye-Ptarg|<|rtarg| within a certain time period, where r targ is the preset distance; A calculation unit is used to determine the user attention coefficient C based on the following formula: focus :

11. The rehabilitation robot-assisted motion system based on user's active motion intention according to claim 10, characterized in that: The movement intention assessment module includes: A judging unit, used to judge whether the user attention degree coefficient meets a first preset condition; A control signal generating unit, when the user attention degree coefficient meets a first preset condition, the control signal generating unit is used to generate a first execution control signal based on the user attention degree coefficient, so as to control the execution mechanism to move according to preset working parameters.

12. The rehabilitation robot-assisted motion system based on user's active motion intention according to claim 11, characterized in that: The judging unit can also be used to judge whether the user attention degree coefficient meets a second preset condition; When the user attention coefficient satisfies a second preset condition, the control signal generating unit can also be used to generate a second execution control signal based on the user attention coefficient, so as to control the execution mechanism to move according to the first working parameter; The movement intention assessment module further includes: an adaptive coefficient calculation unit, in response to the user attention degree coefficient gradually increasing within a preset time period, for determining an adaptive coefficient based on an increase in the user attention degree coefficient; The control signal generating unit is used to adjust the first operating parameter based on the adaptive coefficient and the preset operating parameter.

13. The rehabilitation robot-assisted motion system based on user's active motion intention according to claim 10, characterized in that: It further includes a target communication module for converting the training target into a visual signal, an auditory signal or a tactile signal to guide the user to perform training.

14. The rehabilitation robot-assisted motion system based on user's active motion intention according to claim 12, characterized in that: It further includes a target module and a planning module, wherein the target module is used to store training targets, and the planning module can process the training targets to convert single or abstract training targets into executable parameters for the rehabilitation robot.

15. The rehabilitation robot-assisted motion system based on user's active motion intention according to claim 14, characterized in that: It further includes a state evaluation module, which is communicated with the planning module and the motion intention evaluation module respectively. The state evaluation module can obtain initial motion parameters from the planning module and obtain the user attention coefficient from the motion intention evaluation module. It can fuse the initial motion parameters and the user attention coefficient to generate fusion working parameters, and can compare the fusion working parameters with the user's current working parameters. When the user's current working parameters do not reach the fusion working parameters, the auxiliary parameters are used to control the movement of the actuator to assist the user's movement; when the user's current working parameters reach or exceed the fusion working parameters, the hindering parameters are used to control the movement of the actuator to increase the resistance to the user's movement.

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