CN109605385A - A kind of rehabilitation auxiliary robot of mixing brain-computer interface driving - Google Patents
A kind of rehabilitation auxiliary robot of mixing brain-computer interface driving Download PDFInfo
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- CN109605385A CN109605385A CN201811434591.8A CN201811434591A CN109605385A CN 109605385 A CN109605385 A CN 109605385A CN 201811434591 A CN201811434591 A CN 201811434591A CN 109605385 A CN109605385 A CN 109605385A
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
- B25J11/008—Manipulators for service tasks
- B25J11/009—Nursing, e.g. carrying sick persons, pushing wheelchairs, distributing drugs
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J13/00—Controls for manipulators
- B25J13/08—Controls for manipulators by means of sensing devices, e.g. viewing or touching devices
- B25J13/085—Force or torque sensors
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/02—Sensing devices
- B25J19/04—Viewing devices
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/08—Programme-controlled manipulators characterised by modular constructions
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
- B25J9/1697—Vision controlled systems
Abstract
The invention discloses a kind of rehabilitation auxiliary robots of mixing brain-computer interface driving, comprising: data acquisition module, for acquiring sight motion information and Mental imagery EEG signals, and the deep image information of acquisition user face and target object；PC processing module, for obtaining the target object that user wants crawl according to the Mental imagery EEG signals of user, image information extracts location information based on the received；Mechanical arm control module, for target object to be transported to the motion path of user face according to the location information of user face and target object planning mechanical arm, and the sight motion information of synthetic user and the motion path of planning generate mechanical arm and control signal, control the movement of mechanical arm；Mechanical arm, for the control campaign according to mechanical arm control module；Feedback module is installed on mechanical arm, for feeding back the clamping whether successful signal of target object.The characteristics of comprehensive brain-computer interface technology of the present invention and healing robot both techniques, it is more advantageous to patients ' recovery training.
Description
Technical field
The present invention relates to robot field more particularly to a kind of rehabilitation auxiliary robots of mixing brain-computer interface driving.
Background technique
Traditional rehabilitation auxiliary robot is the movement for driving limbs to do repeatability by machine, to control limb motion
Nervous system is stimulated and is promoted its reconstruction, and healing robot includes two kinds of healing robots of upper limb and lower limb, most of to need
Want other people auxiliary that patient is helped to use, patient cannot be actively engaged in wherein, lack the mechanism accurately fed back, be unfavorable for patient
The accurate feedback played an active part in rehabilitation efficacy.Traditional healing robot is devoted to the limbs nervous system of user
Restore, can not be provided to user and assist help, such as patient for many severe paralysis, they can only be by by others
It helps to complete activity necessary to some daily lifes, such as eats food, drinks water.
Brain-computer interface (Brain Computer Interface, BCI) is to be related to Neuscience, cognitive science, computer
Science, control and multidisciplinary, the multi-field man-machine interface mode such as information science and technology, medicine, are in brain and external rings
The nerve information exchange established between border and control channel.The present invention is using non-intrusion type brain-computer interface technology, by adopting
Collection and the EEG signals feature for extracting brain generation accordingly generate control signal to complete brain and external equipment and carry out information biography
The task with control is passed, realizes the direct interaction between central nervous system and internal or external device, patient is helped to realize
Some control instruction auxiliary Rehabilitations or life are realized in the interaction of brain and computer.
It is currently, there are part existing research and combines brain-computer interface technology with intelligent robot technology, such as Publication No.
The patent " a kind of system of brain wave control mechanical arm " of CN105425963A using brain wave signal acquisition attention and put
Looseness parameter, to complete preset mechanical arm control action.Publication No. CN102198660A, it is entitled " to be based on brain-machine
The mechanical arm control system and action command control program of interface ", the brain-computer interface of motor pattern, switching are imagined using three kinds
With the motor pattern of selection mechanical arm, realizes mechanical arm and grab and put, eight deliberate action instructions of up, down, left, right, before and after.
Above-mentioned patent of invention, only by brain-computer interface it is technically simple and robot technology combine, by acquiring and analyzing brain telecommunications
Number feature, generate to the control instruction of robot, robot according to some movements predetermined of predefined instruction completion,
Such technology lacks corresponding feedback mechanism, does not give full play of the advantage that brain-computer interface is combined with robot technology.Cause
This, it would be highly desirable to it solves the above problems.
Summary of the invention
Goal of the invention: in view of the problems of the existing technology the present invention, provides a kind of auxiliary of mixing brain-computer interface driving
Healing robot.
Technical solution: it is of the present invention mixing brain-computer interface driving rehabilitation auxiliary robot include:
Data acquisition module, for acquiring the sight motion information of user and the movement of generation is thought when carrying out Mental imagery
As EEG signals, and according to the deep image information of PC processing module instruction acquisition user face and target object；
PC processing module, for obtaining the target object that user wants crawl according to the Mental imagery EEG signals of user,
The deep image information of instruction acquisition user face and target object is sent to data acquisition module, and image is believed based on the received
Breath extracts location information；
Mechanical arm control module, for planning mechanical arm by object according to the location information of user face and target object
Body is transported to the motion path of user face and the sight motion information of synthetic user and the motion path of planning generates machinery
Arm controls signal, controls the movement of mechanical arm；
Mechanical arm, for the control campaign according to mechanical arm control module；
Feedback module is installed on mechanical arm, for feeding back the clamping whether successful signal of target object.
Further, the data acquisition module specifically includes:
Eeg signal acquisition unit, for acquiring the Mental imagery EEG signals of user's generation when carrying out Mental imagery,
And PC processing module is transmitted to after carrying out signal filtering, amplification, analog-to-digital conversion；
Image acquisition units, acquisition are located at the target object three dimensional depth image information of target position, and acquisition user
The deep image information of face receives the instruction that PC processing module is sent, and therefrom parses target position and user face position
Confidence breath；
Eye-controlling focus unit for acquiring the sight motion information of user, and is transmitted to mechanical arm control module.
Further, the PC processing module specifically includes:
Eeg data processing unit is pre-processed for the Mental imagery EEG signals to user, and it is special to extract brain electricity
Reference number, and according to the classifier of pre-training obtain the brain electrical feature signal corresponding to object space, want to grab as user
The position of the target object taken generates the acquisition instructions comprising target object location to data acquisition module；
Positioning unit is identified, for believing according to the user face of data collecting module collected and the depth image of target object
Breath extracts the location information of user face and target object；
Mental imagery guidance unit, for playing the audio and video of the guidance user movement imagination.
Further, the mechanical arm control module specifically includes:
Robotic arm path planning unit, for the location information according to user face and target object, plan mechanical arm with
The position of target object is clamped as starting point, motion path of the face location of user as terminal；
Manipulator motion control unit, user's sight motion information for sending data acquisition module is as mechanical arm
Start stop signal is moved, mechanical arm is generated according to the motion path of planning and controls signal, control the movement of mechanical arm.
Further, the feedback module specifically includes:
Touch detection device, is installed at robot arm end effector, the pressure for detection mechanical arm end effector
Variation；
Vibrational feedback unit, for issuing when touch detection device detects robot arm end effector pressure increase
Pass signal is clamped, ownership goal object is prompted to clamp successfully.
Further, the eeg signal acquisition unit includes that sequentially connected standard 10-20 leads brain electrode cap, multichannel
Eeg amplifier, analog-digital converter and signal transmission unit.
Further, described image acquisition unit includes two Kinect cameras, for obtaining target object and use respectively
The deep image information of family face.
Further, the Eye-controlling focus unit is specially eye tracker, is being installed on PC processing module display just
Lower section, for being realized by the position for the blinkpunkt for measuring eyes to oculomotor tracking.
The utility model has the advantages that compared with prior art, the present invention its remarkable advantage is:
1, the rehabilitation auxiliary robot of the present invention-mixing brain-computer interface driving, based on Mental imagery brain-computer interface technology with
Rehabilitation auxiliary robot technology combines, and user is only needed to provide Mental imagery EEG signals and eye movement signal, rehabilitation auxiliary machinery
The planning path work that the mechanical arm of people is generated according to system is user service, and the use of the robot is intervened without other people, used
One people of family can be operated, convenient for application.
2, the present invention uses the Mental imagery brain-computer interface technology of non-intrusion type, and Mental imagery movement is left hand, the right hand, double
Hand and loosen four kinds of states, user is adaptable using simple, recognition accuracy is high.
3, the present invention using power touch detection and shakes the feedback device as system, it is ensured that rehabilitation auxiliary robot
Safety has better man-machine interaction.
4, the present invention using eye movement tracer technique control mechanical arm movement, avoid directly adopt EEG signals control by
There is the problem of mechanical arm control fault in the classification of mistake caused by classifier, it is ensured that the safety of rehabilitation auxiliary robot.
5, the present invention combines brain-computer interface technology, Robot Control Technology, 3D vision location technology, realizes user
Mechanical arm is controlled using idea, required target object can be independently selected, target object is successfully grabbed and the mouth for being sent to user is attached
Closely.When target object is food, the autonomous feed of paralytic is may be implemented in the present invention, can improve the life matter of user
Amount, promotes its autonomous viability.
Detailed description of the invention
Fig. 1 is the system structure diagram of the embodiment of the present invention；
Fig. 2 is that target object location and Mental imagery act corresponding relationship in the embodiment of the present invention；
Fig. 3 is the work flow diagram of the embodiment of the present invention.
Specific embodiment
Technical solution of the present invention is described further with reference to the accompanying drawing, but embodiments of the present invention are not limited to
This.
As shown in Figure 1, the present invention is a kind of rehabilitation auxiliary robot of mixing brain-computer interface driving, comprising: data acquisition
Module, mechanical arm control module, mechanical arm, feedback module and PC processing module.Data acquisition module is used to acquire the view of user
Line motion information and when carrying out Mental imagery generation Mental imagery EEG signals, and according to PC processing module instruction acquisition
The deep image information of user face and target object (such as food)；PC processing module is used for the Mental imagery brain according to user
Electric signal parses user's brain electricity and is intended to obtain the target object that user wants crawl, sends instruction acquisition to data acquisition module and uses
The deep image information of family face and target object, and image information extracts location information based on the received；Mechanical arm control
Module is used to plan that target object is transported to user face (tool by mechanical arm according to the location information of user face and target object
Body is mouth) motion path and synthetic user sight motion information and planning motion path generate mechanical arm control
Signal controls the movement of mechanical arm；Mechanical arm is used for the control campaign according to mechanical arm control module；Feedback module installation
In on mechanical arm, clamp whether target object succeeds for feeding back.
Data acquisition module specifically includes eeg signal acquisition unit, image acquisition units and Eye-controlling focus unit.Brain electricity
Signal acquisition unit be used for acquire user carry out Mental imagery when generation Mental imagery EEG signals, and carry out signal filtering,
Amplification is transmitted to PC processing module after analog-to-digital conversion, the mode of signal transmission be not limited to using USB, serial communication, bluetooth,
The communication modes such as WIFI can be led brain electrode cap, multichannel brain electric amplifier, modulus by standard 10-20 and turned in the specific implementation
Parallel operation and signal transmission unit composition, 10-20 conduction polar cap can acquire C3, FC3, CP3, C5, C4, FC4, CP4, C6 etc. eight
The EEG signals of electrode channel.The target object three dimensional depth image that image acquisition units are used to acquire positioned at target position is believed
Breath, and the deep image information of acquisition user face, receive the instruction that PC processing module is sent, and therefrom parse target position
Set with user's face location information, in the specific implementation, image acquisition units can be made of two Kinect cameras, be obtained respectively
Deep image information is taken, is extracted for later positions.Eye-controlling focus unit is used to acquire the sight motion information of user (specially
Eyeball motion information), and it is transmitted to mechanical arm control module, in the specific implementation, eye tracker can be used, PC is installed on
The underface of processing module display is realized by measuring the position of blinkpunkt of eyes to oculomotor tracking.
PC processing module specifically includes eeg data processing unit, identification positioning unit and Mental imagery guidance unit.Fortune
Dynamic imagination guidance unit, for playing the audio and video of the guidance user movement imagination, specifically display.The eeg data
Processing unit extracts brain electrical feature signal, and according to pre- instruction for pre-processing to the Mental imagery EEG signals of user
Experienced classifier classifies to brain electrical feature signal, and parsing user's brain electricity is intended to obtain object corresponding to the brain electrical feature signal
Body position wants the position of the target object of crawl as user, generates the acquisition instructions comprising target object location to data
Acquisition module.Identify that positioning unit is used to believe according to the user face of data collecting module collected and the depth image of target object
Breath extracts the location information of user face and target object.Wherein, the training process of classifier are as follows:
A, object is placed as shown in Fig. 2, present in two-dimensional space, is left and right, lower four kinds of position distributions, it is above-mentioned it is upper,
Placed at left and right three positions different objects (food, fruit, other etc.), object and the position are not placed as machinery in lower section
The initial position of arm end manipulator.
B, guidance user's setting in motion imagination, the different motion obtained under different imagination movements imagine EEG signals.The imagination
Guidance unit guides user's beginning and end Mental imagery according to certain regular playing animation, generates Mental imagery brain telecommunications
Number, the movement of Mental imagery is left hand, the right hand, both hands and loosens four kinds of motion states, the movement of Mental imagery and target object
Position be one-to-one relationship.Such as the corresponding imagination bimanual movements of object above, i.e., to control auxiliary robot crawl
The object of top then imagines bimanual movements, as shown in Figure 2.
C, different types of Mental imagery EEG signals are passed through into the denoising of 8-12Hz and 19-26Hz bandpass filter,
The feature vector of signal is extracted using feature extraction algorithm again, it is preferred to use CSP cospace model algorithm extracts EEG signals
Feature vector.
D, it using different EEG signals feature vectors and corresponding object space as sample, completes to divide using pattern classifier
The training of class device, it is preferred to use linear classifier (LDA) is classified.After training classifier, an EEG signals spy is inputted
Sign vector can be obtained by the location information of an object.
Mechanical arm is specially multiple degrees of freedom (6DOF) mechanical arm, and end is manipulator mechanism.
Mechanical arm control module specifically includes robotic arm path planning unit and manipulator motion control unit, mechanical arm road
Diameter planning unit is used for the location information according to user face and target object, plans mechanical arm to clamp the position of target object
As starting point, motion path of face (specially mouth) position of user as terminal；Manipulator motion control unit is used for
User's sight motion information that data acquisition module is sent is as manipulator motion start stop signal, according to the motion path of planning
It generates mechanical arm and controls signal, control the movement of mechanical arm.When it is implemented, using user's sight motion information control start and stop tool
Body may is that from the brain electricity of user intention in parsing target object location then control manipulator be moved to target object just on
Side waits crawl control signal, and user actively moves eyeball sight at this time, and Eye-controlling focus unit detects watching attentively for user eyeball
Point changes, and generates active auxiliary control signal all the way and sends mechanical arm motion control unit, start mechanical arm, completes target crawl
It is carried with mechanical arm, after the completion of target crawl, feedback module can export feedback signal and remind user that target crawl is completed, mechanical
Arm started to carry target object after delay a period of time；When target object is carried to user's mouth according to motion profile by mechanical arm
Afterwards, eye tracker is watched in user's active attentively, and Eye-controlling focus unit is made to detect that the eye movement variation Eye-controlling focus unit of user produces
Raw mechanical arm return control signal to mechanical arm control module, mechanical arm control module controls mechanical arm and returns to initial position.
Feedback module specifically includes touch detection device and vibrational feedback unit, and touch detection device is installed on mechanical arm end
Hold joint, the pressure change for detection mechanical arm；When it is implemented, can be examined using two pressure sensors as tactile
Survey device, two independent pressure sensors are installed on mechanical arm tail end claw two sides, can acquire end claw whether stress, from
And judge whether mechanical arm has successfully grabbed target object (food).Vibrational feedback unit is used to detect in touch detection device
When to mechanical arm pressure increase, clamping pass signal is issued, clamping pass signal is not limited to the feedback signals such as sound, light, vibration
To prompt user to clamp object success.
As shown in figure 3, the course of work of robot are as follows:
1) user is sitting in the front of Mental imagery guidance unit, is adjusted to comfortable position, wears brain wave acquisition
Electrode cap, opens data acquisition module, and confirmation signal acquisition state is good.
2) Eye-controlling focus unit is installed on the underface of imagination guidance unit, and after user adjusts good position, test sight is chased after
Track cell operation is in good condition.
3) Mental imagery prompts, and places object.The placement of object as shown in Fig. 2, present in two-dimensional space, be left and right, lower four
Kind of position distribution, placed at above-mentioned upper, left and right three positions different target objects (food, fruit, other etc.), under
Side does not place object and the position is the initial position of mechanical arm tail end manipulator.
4) start image acquisition units, confirm the face of user and the required object grabbed of mechanical arm in image acquisition units
Field range.
5) user's setting in motion is imagined, eeg signal acquisition unit starts according to certain regular playing animation guidance user
With terminate Mental imagery, generate Mental imagery EEG signals, the movement of Mental imagery is left hand, the right hand, both hands and loosens four kinds
Motion state, the movement of Mental imagery and the position of target object are one-to-one relationship.
6) the brain electrical feature of user is obtained according to the Mental imagery EEG signals that step 5) is extracted, and according to point of pre-training
Class device obtains object space corresponding to the brain electrical feature signal, and the position of the target object of crawl is wanted as user, generates
Acquisition instructions comprising target object location to image acquisition units, image acquisition units acquire target object and face (mouth)
Image information, be input to PC processing module.Such as, user imagines bimanual movements, is intended that clamping top object, then image is adopted
Collect the image information that unit obtains top target object.
7) location information is extracted according to the image information that step 6) obtains, in conjunction with the installation site of mechanical arm, rationally established
Coordinate system, solves mechanical arm to clamp the position of target object as starting point, inverse solution of the mouth position of user as terminal,
And plan reasonable motion path.
8) target location coordinate obtained according to step 7), control mechanical arm tail end manipulator are moved to object to be grabbed
The surface of body waits crawl control signal.
9) according to step 8), the end of mechanical arm is moved into the top of object to be grabbed, and user actively moves eyeball
Sight, Eye-controlling focus unit detects that the blinkpunkt of user eyeball changes, generates active auxiliary control signal all the way, which passes
Mechanical arm control module is transported to, mechanical arm control module controls mechanical arm and completes target crawl and mechanical arm carrying, target crawl
After the completion, touch detection device detects that the variation of pressure can export feedback signal and remind user that target crawl is completed, mechanical
Arm started to carry target object after delay a period of time.
10) according to step 9) and step 6), mechanical arm anticipates user by the brain electricity that Mental imagery brain-computer interface is expressed
The target object that figure-wants crawl is carried near the mouth of user.When target object is different food, user is only needed
Movement slightly can be completed and take to eating for target object, realize autonomous life.
11) after user completes the use of target object, Eye-controlling focus unit is watched in user's active attentively, makes Eye-controlling focus list
Member detects the eye movement variation of user, and Eye-controlling focus unit generates mechanical arm return control signal, which is transmitted to mechanical arm
Control module, mechanical arm control module control mechanical arm and return to initial position.
The step 8) and step 11) eye tracker generate control signal and realize especially by step once:
A, human eye faces eye tracker.
B, its eyeball fixes point that moves left and right of human eye active changes.
C, eye tracker detects that eyeball fixes point changes meeting trigger signal output, and the signal is for controlling mechanical arm system
The starting and return of system.
Above disclosed is only a preferred embodiment of the present invention, and the right model of the present invention cannot be limited with this
It encloses, therefore equivalent changes made in accordance with the claims of the present invention, is still within the scope of the present invention.
Claims (8)
1. a kind of rehabilitation auxiliary robot of mixing brain-computer interface driving, characterized by comprising:
Data acquisition module, for acquire the sight motion information of user and when carrying out Mental imagery generation Mental imagery brain
Electric signal, and the deep image information according to PC processing module instruction acquisition user face and target object；
PC processing module, for obtaining the target object that user wants crawl according to the Mental imagery EEG signals of user, to number
The deep image information of instruction acquisition user face and target object is sent according to acquisition module, and image information mentions based on the received
Extracting position information；
Mechanical arm control module, for planning that mechanical arm transports target object according to the location information of user face and target object
It is sent to the motion path of user face and the sight motion information of synthetic user and the motion path of planning generates mechanical arm control
Signal processed controls the movement of mechanical arm；
Mechanical arm, for the control campaign according to mechanical arm control module；
Feedback module is installed on mechanical arm, for feeding back the clamping whether successful signal of target object.
2. the rehabilitation auxiliary robot of mixing brain-computer interface driving according to claim 1, it is characterised in that: the data
Acquisition module specifically includes:
Eeg signal acquisition unit is gone forward side by side for acquiring the Mental imagery EEG signals of user's generation when carrying out Mental imagery
PC processing module is transmitted to after the filtering of row signal, amplification, analog-to-digital conversion；
Image acquisition units, for acquiring the target object three dimensional depth image information for being located at target position, and acquisition user
The deep image information of face receives the instruction that PC processing module is sent, and therefrom parses target position and user face position
Confidence breath；
Eye-controlling focus unit for acquiring the sight motion information of user, and is transmitted to mechanical arm control module.
3. the rehabilitation auxiliary robot of mixing brain-computer interface driving according to claim 1, it is characterised in that: at the PC
Reason module specifically includes:
Eeg data processing unit is pre-processed for the Mental imagery EEG signals to user, extracts brain electrical feature letter
Number, and user's brain electricity is parsed according to the classifier of pre-training and is intended to obtain object space corresponding to the brain electrical feature signal, make
The position of the target object of crawl is wanted for user, generates the acquisition instructions comprising target object location to data acquisition module；
Positioning unit is identified, for mentioning according to the user face of data collecting module collected and the deep image information of target object
Take out the location information of user face and target object；
Mental imagery guidance unit, for playing the audio and video of the guidance user movement imagination.
4. the rehabilitation auxiliary robot of mixing brain-computer interface driving according to claim 1, it is characterised in that: the machinery
Arm control module specifically includes:
Robotic arm path planning unit plans mechanical arm to clamp for the location information according to user face and target object
The position of target object is as starting point, motion path of the face location of user as terminal；
Manipulator motion control unit, user's sight motion information for sending data acquisition module is as manipulator motion
Start stop signal generates mechanical arm according to the motion path of planning and controls signal, controls the movement of mechanical arm.
5. the rehabilitation auxiliary robot of mixing brain-computer interface driving according to claim 1, it is characterised in that: the feedback
Module specifically includes:
Touch detection device, is installed at robot arm end effector, the pressure change for detection mechanical arm end effector；
Vibrational feedback unit, for issuing clamping when touch detection device detects robot arm end effector pressure increase
Pass signal prompts ownership goal object to clamp successfully.
6. the rehabilitation auxiliary robot of mixing brain-computer interface driving according to claim 2, it is characterised in that: the brain electricity
Signal acquisition unit includes that sequentially connected standard 10-20 leads brain electrode cap, multichannel brain electric amplifier, analog-digital converter and letter
Number transmission unit.
7. the rehabilitation auxiliary robot of mixing brain-computer interface driving according to claim 2, it is characterised in that: described image
Acquisition unit includes two Kinect cameras, for obtaining the deep image information of target object and user face respectively.
8. the rehabilitation auxiliary robot of mixing brain-computer interface driving according to claim 2, it is characterised in that: the sight
Tracing unit is specially eye tracker, is installed on the underface of PC processing module display, for the note by measurement eyes
The position of viewpoint and realize to oculomotor tracking.
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Cited By (11)
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| US20190387995A1 (en) * | 2016-12-20 | 2019-12-26 | South China University Of Technology | Brain-Computer Interface Based Robotic Arm Self-Assisting System and Method |
| CN110827974A (en) * | 2019-11-08 | 2020-02-21 | 上海第二工业大学 | Intelligent auxiliary feeding nursing system and auxiliary feeding method thereof |
| CN111462906A (en) * | 2020-04-26 | 2020-07-28 | 郑州大学 | Visual system and man-machine interaction interface for assisting paralyzed patient to eat food |
| CN112085052A (en) * | 2020-07-28 | 2020-12-15 | 中国科学院深圳先进技术研究院 | Training method of motor imagery classification model, motor imagery method and related equipment |
| CN112757302A (en) * | 2021-01-06 | 2021-05-07 | 北京航空航天大学 | Control method of portable dining-assistant robot |
| CN113500611A (en) * | 2021-07-22 | 2021-10-15 | 常州大学 | Feeding robot system based on electroencephalogram and visual guidance |
| CN113849067A (en) * | 2021-09-26 | 2021-12-28 | 华东理工大学 | Motion imagery artificial data generation method and device based on empirical mode decomposition |
| CN113925742A (en) * | 2021-10-20 | 2022-01-14 | 南通大学 | Control method and control system of target-driven upper limb exoskeleton rehabilitation robot |
| CN115617046A (en) * | 2022-11-01 | 2023-01-17 | 中国第一汽车股份有限公司 | Path planning method and device, electronic equipment and storage medium |
| CN117873330A (en) * | 2024-03-11 | 2024-04-12 | 河海大学 | Electroencephalogram-eye movement hybrid teleoperation robot control method, system and device |
| CN117873330B (en) * | 2024-03-11 | 2024-05-17 | 河海大学 | Electroencephalogram-eye movement hybrid teleoperation robot control method, system and device |
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