CN105962935B - The brain electric nerve feedback training system and its method improved for motor learning function - Google Patents
The brain electric nerve feedback training system and its method improved for motor learning function Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
- A61B5/375—Electroencephalography [EEG] using biofeedback
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/25—Bioelectric electrodes therefor
- A61B5/279—Bioelectric electrodes therefor specially adapted for particular uses
- A61B5/291—Bioelectric electrodes therefor specially adapted for particular uses for electroencephalography [EEG]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/7475—User input or interface means, e.g. keyboard, pointing device, joystick
Abstract
The invention patent relates to a kind of brain electric nerve feedback training system improved for motor learning function and its methods, including brain wave acquisition module, brain electricity analytical module, neural feedback module, ancillary equipment module and feedback output module, it is connected in each intermodule using wirelessly or non-wirelessly mode, brain wave acquisition module is connected with brain electricity analytical module, brain wave acquisition module acquisition EEG signals are simultaneously transferred to brain electricity analytical module, brain electricity analytical module carries out feature extraction to EEG signals and classifies and be transferred to neural feedback module, neural feedback module and brain electricity analytical module and feedback output module, ancillary equipment module, which is connected, realizes the optimization and adjustment function of brain electric nerve feedback training.The present invention can targetedly be trained for the development of motor learning neural feedback scene, reduce the time in neural feedback training process and professional requirement, the application scenarios for expanding neural feedback training improve neural feedback training to the improvement of motor educability.
Description
Technical field
The invention belongs to the field of medical instrument technology, especially a kind of brain electric nerve improved for motor learning function is anti-
Present training system and its method.
Background technique
Neural feedback is a kind of technology caused by neuroscience field and biomedical engineering field mixing together, former
Reason feeds back to subject with being the physiological activity by acquiring subject and real-time online with some form, to enable subject
It is capable of the state of the adjusting physical function of active.The neural feedback of narrow sense is based primarily upon EEG signals, and the neural feedback of broad sense can
Utilize a variety of different physiological signals including EEG signals, such as electrocardio, myoelectricity, respiratory rhythm.
Neural feedback technical application based on EEG signals is extensive, mainly passes through the EEG signals of acquisition subject, warp
After computer disposal analysis, using the brain electrical feature of subject as neural feedback information.Currently, being existed based on neural feedback technology
Following technical problem: (1) EEG signals are faint and complicated and changeable, how to select suitable feature, enable effectively to reflect
Brain state relevant to motor learning, and effective guidance can be provided for subject；(2) suitable feedback form how is selected
Existing form, enables to subject should be readily appreciated that and accurately holds brain electricity condition；(3) how to formulate and expeditiously feedback training
System operating mode or process enable to subject to complete neural feedback training within the relatively short time, avoid the occurrence of tired
Labor situation.
Summary of the invention
In place of making up the deficiencies in the prior art, it is reasonable, high-efficient and quick to provide a kind of design
The accurately brain electric nerve feedback training system and its method for the improvement of motor learning function.
The present invention solves existing technical problem and adopts the following technical solutions to achieve:
A kind of brain electric nerve feedback training system improved for motor learning function, including brain wave acquisition module, brain electricity
Analysis module, neural feedback module, ancillary equipment module and feedback output module, the brain wave acquisition module and brain electricity analytical mould
Block is connected, and brain wave acquisition module acquisition EEG signals are simultaneously transferred to brain electricity analytical module, and the brain electricity analytical module is to brain
Electric signal carries out feature extraction and classifies simultaneously to be transferred to neural feedback module, the neural feedback module and brain electricity analytical module and
Feedback output module, ancillary equipment module, which are connected, realizes the optimization and adjustment function of brain electric nerve feedback training.
The brain wave acquisition module includes electrode for encephalograms, acquisition component, Power Supply Assembly, CPU, processing component and transmission group
Part；The CPU is connected with processing component, acquisition component and transmission assembly to be realized to the control functions of modules；The confession
Electrical component is connected with CPU, acquisition component, processing component and transmission assembly to be realized to the function of supplying power of modules；It is described to adopt
Collection component connect acquisition EEG signals with human body by electrode for encephalograms；The transmission assembly is connected with brain electricity analytical module；Institute
Stating transmission assembly is wireless transmission unit or wire transmission unit.
The electrode for encephalograms is one or more, and electrode for encephalograms is noninvasive wearable electrode for encephalograms.
The brain electricity analytical module includes that two transmission assemblies, pretreatment unit, parser unit and index output are single
Member；The pretreatment unit is connected by a transmission assembly with brain wave acquisition module, pretreatment unit, parser unit
It is sequentially connected and connects with index output unit, the index output unit is connected by another transmission assembly with neural feedback module
It connects, described two transmission assemblies are wireless transmission unit or wire transmission unit.
The neural feedback module includes two transmission assemblies, feedback model selecting unit, feedback model library, feedback training
Execution unit, feedback effects evaluation unit, feedback model optimization unit, feedback output unit and feedback output pattern base；It is described
Feedback model selecting unit is connected by a transmission assembly with brain electricity analytical module and ancillary equipment module, feedback model choosing
Select unit, feedback model library, feedback model optimization unit are sequentially connected and connect, the feedback training execution unit respectively with feedback mould
Type selecting unit, feedback output unit are connected, feedback training execution unit, feedback effects evaluation unit, feedback model optimization
Unit, which is sequentially connected, to be connect, and the feedback output unit is connected with feedback output pattern base, which also passes through separately
One output precision is connected with feedback output module, and described two transmission assemblies are wireless transmission unit or wire transmission list
Member.
The ancillary equipment module is mouse, handwriting pad or touch screen.
The feedback output module is display screen, virtual reality device, device for force feedback, sound output device, light stimulus
Output device or electro photoluminescence output device.
The brain electricity analytical module and neural feedback module be made of FPGA circuitry or brain electricity analytical module and nerve it is anti-
Feedback module is standalone module and is connected to form by wirelessly or non-wirelessly transmission mode or brain electricity analytical module and neural feedback
Module is the software run on computers and other modules are connected with this system by universal computer architecture
A method of the brain electric nerve feedback training system improved for motor learning function, comprising the following steps:
Step 1: acquiring the EEG signals of user by one or more electrode for encephalograms, and EEG signals are transferred to brain
Electric acquisition module；
Step 2: brain wave acquisition module is to carrying out preliminary amplification, be filtered and be converted to after collected EEG signals
Digital signal is sent to brain electricity analytical module by way of wirelessly or non-wirelessly；
Step 3: brain electricity analytical module carries out further analysis to EEG signals, extract frequency, amplitude, power spectrum,
Entropy, graph theory network parameter, chaos and parting index, carry out feature extraction and classification, and by index analysis result by wireless or
Wired mode is sent to neural feedback module；
Step 4: a series of neural feedback training suitable for motor learning enhancing training are built-in in neural feedback module
Model and training normal form, after selecting a kind of training pattern, on the one hand neural feedback module obtains the EEG signals from user,
On the other hand the motor message that user's operation support device module generates is obtained, is assessed and is compared, and by user's
The motor message that brain electricity index and operation support device module generate passes through feedback output module feedback to user, so that using
Person knows that the state of itself EEG signals variation is generated with rule and self by motor performance ancillary equipment module in real time
Motor message state；
Step 5: neural feedback module is according to the operating conditions of each user, the state of EEG signals and neural feedback mould
The estimated index of type generates the feature database of optimization, carries out accumulation optimization to the effect of neural feedback training pattern.
The advantages and positive effects of the present invention are:
Each intermodule of the invention transmits instruction and data using wirelessly or non-wirelessly mode, the brain electricity with direct body contact
Acquisition module can work independently, and not need to connect using cable with other modules, and use noninvasive wearable brain electricity electricity
Pole reduces the time in neural feedback training process and professional requirement, while also improving neural feedback training
Application scenarios.By the user motion information incoming using the ancillary equipment module that can be operated by limb motion, nerve is anti-
Present module can by the brain electric information of user, motion information in real time by feedback output module feedback to user, and generate
The profile of user is for optimizing neural feedback model, to improve improvement of the neural feedback training to motor educability
Effect.
Detailed description of the invention
Fig. 1 is system connection schematic diagram of the invention；
Fig. 2 is the circuit block diagram of brain wave acquisition module of the invention；
Fig. 3 is the circuit block diagram of brain electricity analytical module of the invention；
Fig. 4 is the circuit block diagram of neural feedback module of the invention.
Specific embodiment
The embodiment of the present invention is further described below in conjunction with attached drawing:
A kind of brain electric nerve feedback training system improved for motor learning function, as shown in Figure 1, including brain wave acquisition
Module, brain electricity analytical module, neural feedback module, ancillary equipment module and feedback output module.The brain wave acquisition module
It is connected with the brain electricity analytical by wirelessly or non-wirelessly transmission mode, brain electricity analytical module is integrated with a variety of suitable for movement
The brain electricity analytical algorithm of study can be converted to the signal from brain wave acquisition module such as: frequency, amplitude, power spectrum, entropy, graph theory
The quantizating index such as network parameter, chaos and parting simultaneously carry out feature extraction and classification.The brain electricity analytical module and neural feedback
Module can be an overall structure, be also possible to two independent modules, when brain electricity analytical module and neural feedback module are
When one overall structure, the software program that also can be implemented as in general computer architecture can be realized by FPGA circuitry, when
When brain electricity analytical module and neural feedback module are two independent modules, brain electricity analytical module and neural feedback module are by having
Line or wireless transmission method link together.The feedback output module passes through wireless or has with the neural feedback module
Line mode is connected, and can will substitute into motor learning neural feedback instruction from the index of brain electricity analytical module by neural feedback module
Practice pattern base, exported such as by feedback output module to user in a specific way: sound, image, force feedback movement, electricity pierce
The signals such as sharp, light stimulus, user can be by paying attention to, staring, imagine or operating the side such as ancillary equipment module relevant to movement
Formula inputs auxiliary signal to neural feedback module, and the input from user can be converted to feedback training and commented by neural feedback module
Valence index is optimized and is adjusted to motor learning neural feedback training mode.Below to the modules in system respectively into
Row explanation:
As shown in Fig. 2, brain wave acquisition module includes electrode for encephalograms, acquisition component, Power Supply Assembly, CPU, processing component and biography
Defeated component, CPU is connected with processing component, acquisition component and transmission assembly to be realized to the control functions of modules.Power supply group
Part is connected with CPU, acquisition component, processing component and transmission assembly to be realized to the function of supplying power of modules.Acquisition component is logical
Cross the EEG signals that non-invasive electrode for encephalograms connect acquisition human body with human body.EEG signals from human body are in brain wave acquisition module
It is middle to be converted to digital signal after the pretreatment such as the amplification of acquisition component and processing component, filtering, and by transmission assembly with
Wired or wireless mode is transferred to brain electricity analytical module.When using wireless transmission method, brain wave acquisition module passes through itself
Battery power supply is, it can be achieved that be convenient for the brain wave acquisition and wireless transmission function of wearing.Those of ordinary skill in the art will be appreciated that
It arrives, all electrodes that can provide EEG signals sampling can be adapted for system and method described in the invention.In example
Provided electrode type and lead mode are not intended to propose any limitation to use scope of the invention or function.
As shown in figure 3, brain electricity analytical module includes transmission assembly, pretreatment unit, parser unit, index output list
Member.Transmission assembly includes the transmission assembly being connected with brain wave acquisition module and the transmission group being connected with neural feedback module
Part, transmission assembly can be transmitted in a wired or wireless fashion.From brain wave acquisition module by pretreated brain telecommunications
Number brain electricity analytical module is entered by transmission assembly in a wired or wireless manner, EEG signals are carried out in pretreatment unit
The operations such as further filtering, removal interference, artefact.Parser unit is integrated with a variety of brain electricity suitable for motor learning point
Analysis algorithm can be converted to the signal from brain wave acquisition module such as: frequency, power spectrum, entropy, graph theory network parameter, is mixed at amplitude
The quantizating index such as ignorant and parting carry out feature extraction and classification, and it is single in index output that parser unit calculates the index generated
It is formatted specification and packing according to XML language format in member, and is exported in a wired or wireless manner by transmission assembly
To neural feedback module.
As shown in figure 4, neural feedback module includes transmission assembly, feedback model selecting unit, feedback model library, feedback instruction
Practice execution unit, feedback effects evaluation unit, feedback model and optimizes unit, feedback output unit, feedback output pattern base.Transmission
Component includes the transmission assembly being connected with brain wave acquisition module, ancillary equipment module and is connected with feedback output module
Transmission assembly, transmission assembly can be transmitted in a wired or wireless fashion.Brain electricity index from brain electricity analytical module and come
Feedback model is entered by transmission assembly in a wired or wireless manner from user's motor reaction index of ancillary equipment module
Selecting unit, feedback model selecting unit is arranged according to system selects the suitable mind for being suitable for motor learning in feedback model library
Through feedback model and training normal form, by feedback training execution unit generation specifically execute instruction, feedback output unit according to
It executes instruction and selects specified feedback output mode in feedback output pattern base, and by transmission assembly with wired or wireless
Form is output to feedback output module.In motor learning neural feedback training process, user is passed to by ancillary equipment
Motor reaction situation will enter feedback effects evaluation unit in real time, and feedback effects evaluation unit will assess the estimated effect of feedback model
Difference between fruit and practical implementation effect, and result is output to feedback model optimization unit, feedback model optimizes unit can
Parameter adjustment and optimization are carried out to feedback model to the characteristic parameter for generating user according to feedback effects evaluation index, to mention
The neural feedback training effect of high following same user or different users.
Ancillary equipment module can be set using mouse and/or handwriting pad and/or touch screen etc. based on the input of limb motion
It is standby, processing module is connected to by wireless or wired mode.
Feedback output module is display screen and/or virtual reality device and/or device for force feedback and/or sound and/or light
The output equipments such as stimulation and/or electro photoluminescence follower, are connected to processing module by wireless or wired mode.
The present invention is expanded using that can be wirelessly connected and user can be convenient for dress by battery powered brain wave acquisition module
The big application scenarios of brain-computer interface, and ancillary equipment module relevant to limb motion is introduced, it can be refreshing for motor learning
It is targetedly trained through feedback scene development, further, in neural feedback module there is feedback model library and passes through feedback effects
Evaluation unit and feedback model optimization unit can carry out real-time and targetedly optimization to feedback model, finally, passing through feedback
Output module and ancillary equipment module can set up the closed loop human-computer interaction of user and nervous feedback system, in conjunction with motor learning
Scene, the above improvement, which will be played, improves neural feedback effect, the especially positive effect of motor learning function improvement.
The brain electric nerve feedback training method improved for motor learning function of the invention the following steps are included:
(1) EEG signals of user are collected by the one or more wearable electrode for encephalograms of non-invasive, and brain is electric
Signal is transferred to brain wave acquisition module.
(2) portable to can be used battery powered brain wave acquisition module preliminary to carrying out after collected original EEG signals
Amplification, be filtered and be converted to digital signal, brain electricity analytical module is sent to by way of wirelessly or non-wirelessly.
(3) brain electricity analytical module carries out further analysis to EEG signals, extract frequency, amplitude, power spectrum, entropy,
The quantizating index such as graph theory network parameter, chaos and parting, and carry out feature extraction and classification, and index analysis result is passed through into nothing
Line or wired mode are sent to neural feedback module；
(4) a series of neural feedback training patterns suitable for motor learning enhancing training are built-in in neural feedback module
With training normal form, after selecting a kind of training pattern, on the one hand neural feedback module obtains the EEG signals from user, a side
Face obtains the motor message that user's operation support device generates, and is assessed and is compared, and by the brain electricity index of user and
The motor message that operation support device generates is passed through anti-by modes such as sound, image, force feedback movement, electro photoluminescence, light stimulus
Feedback output module feed back to user, allow user know in real time itself EEG signals variation state and rule with
And the state of the motor message generated self by motor performance ancillary equipment；
(5) neural feedback module can be according to the operating conditions of each user, the state of EEG signals and neural feedback mould
The estimated index of type generates the feature database of optimization, to carry out accumulation optimization to the effect of neural feedback training pattern, enhancing is same
One user and different user carry out training effect when motor learning enhancing neural feedback training.
Execution or the realization sequence of above-mentioned training method are not necessary, unless specified otherwise.That is, the element of method can be with
It is executed with any sequence, unless otherwise specified, and method may include than more or fewer elements disclosed herein.It can be with
Think, before another element, simultaneously or later executes or realize that element-specific is within the scope of the present invention.
When introducing the element of the present invention or embodiment, the article " one ", "one", "the" and " described " refer to that there are one
A or multiple elements."include", "comprise", " having " are intended to inclusive, and mean may be used also in addition to listed element
To there is other elements.
Since can various changes be made in the said goods and method without departing from the scope of the invention,
Included in description above and all the elements for being shown in the accompanying drawings should all be interpreted it is illustrative and not restrictive.
It is emphasized that embodiment of the present invention be it is illustrative, without being restrictive, therefore packet of the present invention
Include and be not limited to embodiment described in specific embodiment, it is all by those skilled in the art according to the technique and scheme of the present invention
The other embodiments obtained, also belong to the scope of protection of the invention.
Claims (8)
1. a kind of method of the brain electric nerve feedback training system improved for motor learning function, described to be used for motor learning function
The brain electric nerve feedback training system that can improve includes brain wave acquisition module, brain electricity analytical module, neural feedback module, assists setting
Standby module and feedback output module, the brain wave acquisition module are connected with brain electricity analytical module, brain wave acquisition module acquisition
EEG signals are simultaneously transferred to brain electricity analytical module, and the brain electricity analytical module carries out feature extraction to EEG signals and classifies and pass
It is defeated by neural feedback module, the neural feedback module and brain electricity analytical module and feedback output module, ancillary equipment module phase
The optimization and adjustment function of brain electric nerve feedback training are realized in connection, it is characterised in that the following steps are included:
Step 1: acquiring the EEG signals of user by one or more electrode for encephalograms, and EEG signals are transferred to brain electricity and are adopted
Collect module；
Step 2: brain wave acquisition module is to carrying out preliminary amplification, be filtered and be converted to number after collected EEG signals
Signal is sent to brain electricity analytical module by way of wirelessly or non-wirelessly；
Step 3: brain electricity analytical module carries out further analysis to EEG signals, extracts frequency, amplitude, power spectrum, entropy, figure
By network parameter, chaos and parting index, carry out feature extraction and classification, and index analysis result is passed through wirelessly or non-wirelessly
Mode is sent to neural feedback module；
Step 4: a series of neural feedback training patterns suitable for motor learning enhancing training are built-in in neural feedback module
With training normal form, after selecting a kind of training pattern, on the one hand neural feedback module obtains the EEG signals from user, another
Aspect obtains the motor message that user's operation support device module generates, and is assessed and is compared, and the brain of user is electric
The motor message that index and operation support device module generate passes through feedback output module feedback to user, so that user is real
When know itself EEG signals variation state and rule and self by motor performance ancillary equipment module generate fortune
The state of dynamic signal；
Step 5: neural feedback module is according to the operating conditions of each user, the state of EEG signals and neural feedback model
It is expected that index generates the feature database of optimization, accumulation optimization is carried out to the effect of neural feedback training pattern.
2. the method for the brain electric nerve feedback training system according to claim 1 improved for motor learning function,
Be characterized in that: the brain wave acquisition module includes electrode for encephalograms, acquisition component, Power Supply Assembly, CPU, processing component and transmission group
Part；The CPU is connected with processing component, acquisition component and transmission assembly to be realized to the control functions of modules；The confession
Electrical component is connected with CPU, acquisition component, processing component and transmission assembly to be realized to the function of supplying power of modules；It is described to adopt
Collection component connect acquisition EEG signals with human body by electrode for encephalograms；The transmission assembly is connected with brain electricity analytical module；Institute
Stating transmission assembly is wireless transmission unit or wire transmission unit.
3. the method for the brain electric nerve feedback training system according to claim 2 improved for motor learning function,
Be characterized in that: the electrode for encephalograms is one or more, and electrode for encephalograms is noninvasive wearable electrode for encephalograms.
4. the method for the brain electric nerve feedback training system according to claim 1 improved for motor learning function,
Be characterized in that: the brain electricity analytical module includes that two transmission assemblies, pretreatment unit, parser unit and index output are single
Member；The pretreatment unit is connected by a transmission assembly with brain wave acquisition module, pretreatment unit, parser unit
It is sequentially connected and connects with index output unit, the index output unit is connected by another transmission assembly with neural feedback module
It connects, described two transmission assemblies are wireless transmission unit or wire transmission unit.
5. the method for the brain electric nerve feedback training system according to claim 1 improved for motor learning function,
Be characterized in that: the neural feedback module includes two transmission assemblies, feedback model selecting unit, feedback model library, feedback instruction
Practice execution unit, feedback effects evaluation unit, feedback model optimization unit, feedback output unit and feedback output pattern base；Institute
It states feedback model selecting unit and is connected by a transmission assembly with brain electricity analytical module and ancillary equipment module, feedback model
Selecting unit, feedback model library, feedback model optimization unit are sequentially connected and connect, the feedback training execution unit respectively with feedback
Model selection unit, feedback output unit are connected, and feedback training execution unit, feedback effects evaluation unit, feedback model are excellent
Change unit, which is sequentially connected, to be connect, and the feedback output unit is connected with feedback output pattern base, which also passes through
Another output precision is connected with feedback output module, and described two transmission assemblies are wireless transmission unit or wire transmission list
Member.
6. the method for the brain electric nerve feedback training system according to claim 1 improved for motor learning function,
Be characterized in that: the ancillary equipment module is mouse, handwriting pad or touch screen.
7. the method for the brain electric nerve feedback training system according to claim 1 improved for motor learning function,
Be characterized in that: the feedback output module is display screen, virtual reality device, device for force feedback, sound output device, light stimulus
Output device or electro photoluminescence output device.
8. the method for the brain electric nerve feedback training system according to claim 1 improved for motor learning function,
Be characterized in that: the brain electricity analytical module and neural feedback module are made of FPGA circuitry or brain electricity analytical module and nerve
Feedback module be standalone module and be connected to form by wirelessly or non-wirelessly transmission mode or brain electricity analytical module and nerve it is anti-
Feedback module is the software run on computers and other modules are connected with this system by universal computer architecture.
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Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106491123A (en) * | 2016-12-22 | 2017-03-15 | 首都师范大学 | Physiological signal record system and its recorder |
| CN106725455A (en) * | 2016-12-22 | 2017-05-31 | 蓝色传感（北京）科技有限公司 | It is used for the training system and method for brain ability training based on sensor feedback |
| CN106691441A (en) * | 2016-12-22 | 2017-05-24 | 蓝色传感（北京）科技有限公司 | Attention training system based on brain electricity and movement state feedback and method thereof |
| CN107577343B (en) * | 2017-08-25 | 2020-04-28 | 北京航空航天大学 | Attention training and evaluation device based on force touch feedback and electroencephalogram signal analysis |
| CN108814594B (en) * | 2018-04-18 | 2021-01-29 | 深圳大学 | Real-time neural feedback device, system, method and computer storage medium |
| CN109859570A (en) * | 2018-12-24 | 2019-06-07 | 中国电子科技集团公司电子科学研究院 | A kind of brain training method and system |
| CN110302462B (en) * | 2019-08-06 | 2022-04-19 | 张铎 | Neural feedback training system based on electroencephalogram signals |
| CN111920408B (en) * | 2020-08-11 | 2023-04-07 | 深圳大学 | Signal analysis method and component of electroencephalogram nerve feedback system combined with virtual reality |
| CN113729709B (en) * | 2021-09-23 | 2023-08-11 | 中科效隆(深圳)科技有限公司 | Nerve feedback device, nerve feedback method, and computer-readable storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101923392A (en) * | 2010-09-02 | 2010-12-22 | 上海交通大学 | Asynchronous brain-computer interactive control method for EEG signal |
| CN102319067A (en) * | 2011-05-10 | 2012-01-18 | 北京师范大学 | Nerve feedback training instrument used for brain memory function improvement on basis of electroencephalogram |
| CN102722255A (en) * | 2012-06-29 | 2012-10-10 | 上海海事大学 | Neurofeedback-based motor imagery brain computer interface (BCI) interactive training system and method |
| WO2012161657A1 (en) * | 2011-05-20 | 2012-11-29 | Nanyang Technological University | Systems, apparatuses, devices, and processes for synergistic neuro-physiological rehabilitation and/or functional development |
| CN104510467A (en) * | 2014-12-08 | 2015-04-15 | 华南理工大学 | Wearable device based electroencephalograph detection device |
| US20160074657A1 (en) * | 2014-12-23 | 2016-03-17 | Advance Electronic And Medical Industries Company Limited | Head-wearing wireless control transcranial electrical stimulation device |
| CN105468143A (en) * | 2015-11-17 | 2016-04-06 | 天津大学 | Feedback system based on motor imagery brain-computer interface |
-
2016
- 2016-06-14 CN CN201610415788.1A patent/CN105962935B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101923392A (en) * | 2010-09-02 | 2010-12-22 | 上海交通大学 | Asynchronous brain-computer interactive control method for EEG signal |
| CN102319067A (en) * | 2011-05-10 | 2012-01-18 | 北京师范大学 | Nerve feedback training instrument used for brain memory function improvement on basis of electroencephalogram |
| WO2012161657A1 (en) * | 2011-05-20 | 2012-11-29 | Nanyang Technological University | Systems, apparatuses, devices, and processes for synergistic neuro-physiological rehabilitation and/or functional development |
| CN102722255A (en) * | 2012-06-29 | 2012-10-10 | 上海海事大学 | Neurofeedback-based motor imagery brain computer interface (BCI) interactive training system and method |
| CN104510467A (en) * | 2014-12-08 | 2015-04-15 | 华南理工大学 | Wearable device based electroencephalograph detection device |
| US20160074657A1 (en) * | 2014-12-23 | 2016-03-17 | Advance Electronic And Medical Industries Company Limited | Head-wearing wireless control transcranial electrical stimulation device |
| CN105468143A (en) * | 2015-11-17 | 2016-04-06 | 天津大学 | Feedback system based on motor imagery brain-computer interface |
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