CN110059550A - A kind of intelligent assistant learning system based on EEG signals - Google Patents
A kind of intelligent assistant learning system based on EEG signals Download PDFInfo
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- CN110059550A CN110059550A CN201910180523.1A CN201910180523A CN110059550A CN 110059550 A CN110059550 A CN 110059550A CN 201910180523 A CN201910180523 A CN 201910180523A CN 110059550 A CN110059550 A CN 110059550A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
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- G—PHYSICS
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- G06F2218/12—Classification; Matching
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Abstract
The present invention provides a kind of intelligent assistant learning system based on EEG signals, including wearable device and terminal device, wherein wearable device includes: image capture module；Electroencephalogramsignal signal acquisition module, for acquiring the EEG signals of user；Main control module, main control module are connected with image capture module and electroencephalogramsignal signal acquisition module respectively, and for being handled EEG signals and being analyzed, and based on the analysis results, control image capture module starts to acquire the image of user at the moment；Wireless sending module, wireless sending module are connected with main control module, and for sending the image of image capture module acquisition, terminal device includes: wireless receiving module, for receiving the image of image capture module acquisition；Picture recognition module, picture recognition module are connected with wireless receiving module, for being identified the image that image capture module acquires to obtain effective image；Memory module, memory module are connected with picture recognition module, for storing to effective image.
Description
Technical field
The present invention relates to Intelligent auxiliary equipment technical fields, and in particular to a kind of intelligent assisted learning based on EEG signals
System.
Background technique
Senior middle school is acquired from small, everyone will learn many knowledge, write many operations also accordingly to carry out knowledge
Consolidation.But some topics that will not be done are frequently encountered when doing one's assignment, the students' union having afterwards is concerning the pride not
It goes to inquire other people, or has forgotten this problem as time goes by.Over time, student without carrying out correlation because know
The exercise of point is known so as to cause imperfect, teaching is learnt, and for family and itself causes to bear.If at this time going to look into again
Leakage is filled a vacancy, and is not only found these topics and is needed the more time, even if but also have found, student can not also may absorb this for the moment
A little knowledge.
Summary of the invention
The present invention is to solve student to be difficult to carry out induction-arrangement to more difficult knowledge in learning process, leads to learning efficiency
The technical problem of difference, provides a kind of intelligent assistant learning system based on EEG signals.
The technical solution adopted by the invention is as follows:
A kind of intelligent assistant learning system based on EEG signals, including wearable device and terminal device, wherein described
Wearable device includes: image capture module；Electroencephalogramsignal signal acquisition module, the electroencephalogramsignal signal acquisition module is for acquiring user
EEG signals；Main control module, the main control module respectively with described image acquisition module and the electroencephalogramsignal signal acquisition module
It is connected, the main control module controls described image for the EEG signals to be handled and analyzed based on the analysis results
Acquisition module starts to acquire the image of the user at the moment；Wireless sending module, the wireless sending module and the master control
Module is connected, and the wireless sending module is used to send the image of described image acquisition module acquisition, and the terminal device includes:
Wireless receiving module, the wireless receiving module and the wireless sending module are wirelessly connected to receive described image acquisition
The image of module acquisition；Picture recognition module, described image identification module are connected with the wireless receiving module, and described image is known
The image that other module is used to acquire described image acquisition module is identified to obtain effective image；Memory module, it is described to deposit
Storage module is connected with described image identification module, and the memory module is for storing the effective image.
The wearable device is the equipment of earphone forms, and the wearable device includes two shells, connection described two
The head beam of a shell and the first support and second support being connected with the head beam, wherein the eeg signal acquisition mould
Block is arranged on the housing, and described image acquisition module is arranged in the first support, and the main control module is arranged in institute
Tou Liangshang is stated, the wireless sending module is arranged in the second support.
The electroencephalogramsignal signal acquisition module includes: eeg signal acquisition device, and the eeg signal acquisition device is for acquiring original
Beginning EEG signals；Signal amplifier, the signal amplifier is for amplifying the original EEG signals.
The main control module includes: EEG Processing unit, and the EEG Processing unit and the signal amplify
Device be connected, the EEG Processing unit for the amplified EEG signals are filtered and noise reduction and obtain brain electricity
Data；Data processing unit, the data processing unit are connected with the EEG Processing unit, the data processing unit
For extracting corresponding focus according to the eeg data；Analyze comparison unit, the analysis comparison unit respectively with it is described
Data processing unit is connected with described image acquisition module, and the analysis comparison unit is for extracting the data processing unit
Focus be compared with default focus range, and be in time control except the default focus range in the focus
Described image acquisition module starting processed.
The main control module further includes power supply unit, and the power supply unit is used to power for the wearable device.
Whether content of the described image identification module for identification in described image contains examination question, and by the figure containing examination question
As being used as the effective image.
Described image acquisition module includes camera.
The terminal device is computer.
Beneficial effects of the present invention:
The present invention acquires user's EEG signals by wearable device, and is used according to the analysis results acquisition to EEG signals
The image of family at the moment, identifys and stores effective image by terminal device, and thereby, it is possible to facilitate student to more difficult knowledge progress
Induction-arrangement saves the time, substantially increases learning efficiency.
Detailed description of the invention
Fig. 1 is the block diagram of the intelligent assistant learning system based on EEG signals of the embodiment of the present invention；
Fig. 2 is the block diagram of the wearable device of one embodiment of the invention；
Fig. 3 is the structural schematic diagram of the wearable device of one embodiment of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
As shown in Figure 1, the intelligent assistant learning system based on EEG signals of the embodiment of the present invention, including wearable device
100 and terminal device 200.Wherein, wearable device 100 includes image capture module 110, electroencephalogramsignal signal acquisition module 120, master
Module 130 and wireless sending module 140 are controlled, electroencephalogramsignal signal acquisition module 120 is used to acquire the EEG signals of user；Main control module
130 are connected with image capture module 110 and electroencephalogramsignal signal acquisition module 120 respectively, main control module 130 be used for EEG signals into
Row processing and analysis, and control image capture module 110 starts to acquire the image of user at the moment based on the analysis results；Wireless hair
Module 140 is sent to be connected with main control module 130, wireless sending module 140 is used to send the image of the acquisition of image capture module 110.
Terminal device 200 include wireless receiving module 210, picture recognition module 220 and memory module 230, wireless receiving module 210 with
Wireless sending module 140 is wirelessly connected to receive the image of the acquisition of image capture module 110；Picture recognition module 220 with
Wireless receiving module 210 be connected, picture recognition module 220 be used for the image that image capture module 110 acquires identified with
Obtain effective image；Memory module 230 is connected with picture recognition module 220, and memory module 230 is for depositing effective image
Storage.
Further, as shown in Fig. 2, electroencephalogramsignal signal acquisition module 120 includes that eeg signal acquisition device 121 and signal amplify
Device 122, eeg signal acquisition device 121 for acquiring original EEG signals, signal amplifier 122 be used for original EEG signals into
Row amplification.Main control module 130 includes EEG Processing unit 131, data processing unit 132, analysis comparison unit 133 and electricity
Source unit 134, EEG Processing unit 131 are connected with signal amplifier 122, and EEG Processing unit 131 is used for putting
EEG signals after big are filtered and noise reduction and obtain eeg data；Data processing unit 132 and EEG Processing unit
131 are connected, and data processing unit 132 is used to extract corresponding focus according to eeg data；Analyze comparison unit 133 respectively with
Data processing unit 132 is connected with image capture module 110, and analysis comparison unit 133 is for extracting data processing unit 132
Focus be compared with default focus range, and be in except default focus range in focus that time control is imaged to adopt
Collect module 110 to start；Power supply unit 134 is used to power for wearable device 100.
In one particular embodiment of the present invention, image capture module 110 includes camera.Terminal device 200 can be
Computer.
In one embodiment of the invention, wearable as shown in figure 3, wearable device 110 is the equipment of earphone forms
Equipment 110 include two shells 01, the head beam 02 of two shells 01 of connection and the first support 03 that is connected with head beam 02 and
Second support 04.Wherein, electroencephalogramsignal signal acquisition module 120 is arranged on shell 01, and image capture module 110 is arranged at first
On frame 03, main control module 130 is arranged on head beam 02, and wireless sending module 140 is arranged in second support 04.
Further, the back side of wearable device 100 is additionally provided with battery, power switch and external power source interface.Battery and
It can be 100 continued power of wearable device by power switch that external power source interface is logical, this has been greatly reinforced for brain electricity
The reliability of the continued power of the wearable device of signal monitoring ensure that its working time.
In one particular embodiment of the present invention, by taking user is the student to do one's assignment as an example, picture recognition module 220 can
Whether the content in identification image contains examination question, and will contain the image of examination question as effective image.It can pre-set specially
The nominal threshold value or rated range of note degree.As long as should be noted that focus in the normal range (NR) of setting, camera will not
Work.But work as user, such as when the attention of student done one's assignment has a big drop, for example focus suddenly drops to 25
Hereinafter, showing that student has been likely encountered problem, camera will work at this time, be continuously shot picture at the moment.But focus
Decline might not show that student encounters problem, it is also possible to be the decline of focus caused by student deserts, at this moment computer
The effect of end image recognition, which has just played, to be come out, it is responsible for filtering out satisfactory image and carries out arrangement classification, thus side
Just student carries out subsequent review.
The above-mentioned intelligent assistant learning system based on EEG signals when in use, first by student by wearable device 100
It is worn on head, and adjusts the position of camera, guarantee to turn on the power switch, Xue Shengkai in front of camera face student sight
Beginning does the homework.Eeg signal acquisition device starts to acquire the EEG signals of student, and EEG signals pass through a series of processing, and are formed
Corresponding data.Data extraction is quantified as focus by data processing unit, and is transferred to analysis comparison unit, and analysis comparison is single
Member is by the amplitude of the practical focus handled by data processing unit and preset focus amplitude rated value or specified model
It encloses and compares, the output end for analyzing comparison unit is electrically connected to camera, when practical focus amplitude is less than focus amplitude
When rated value or over range, controllable camera continuously takes pictures to the situation before Eyes of Students, and by wirelessly sending out
Send module that acquired image is transferred to computer.The image that computer is responsible for for wireless receiving module being collected into identifies.It answers
When understanding, the photo of camera shooting might not be the topic that student place is done entirely, and the focus of student is by other each
The influence of aspect, when student is when pondering deeply, the focus of brain can be maintained at a specific range, and only encountering will not
When the topic done, because acute variation occurs for anxiety and the flurried focus that will lead to.But focus be not it is unalterable,
As the time, little by little past, the energy of student constantly declined, focus also constantly declines, and what this when, camera photographed can
Can be the stupefied thing seen that comes back when student deserts, this when how from photo needed for automatic identification in computer, just
Need the image identification function using computer.Do not include examination question image in image if it is determined that collecting, then deletes picture, if
Judgement is collected comprising examination question image in image, then can carry out classification and ordination to image according to the time, and store the image on electricity
In brain, facilitate subsequent check.
Brain wave is some spontaneous rhythmic neural electrical activities, frequency variation range per second between 1~30 time,
The brain wave of normal person can be greatly classified into this four waves of δ (1~3Hz), θ (4~7Hz), α (8~13Hz), β (14~30Hz)
Section.
δ wave: frequency is 1~3Hz, and amplitude is 20~200 μ V.When people is infancy or intellectual development be immature, adult
Under extremely tired and lethargic sleep or narcosis, this wave band can be recorded in temporal lobe and top.
θ wave: frequency is 4~7Hz, and amplitude is 5~20 μ V.Adult's wish baffle or depression and mental patient
In this wave it is extremely significant.But this wave is the main component in the electroencephalogram of juvenile (10~17 years old).
α wave: frequency is 8~13Hz (average 10Hz), and amplitude is 20~100 μ V.It is the base of normal brain electric wave
This rhythm and pace of moving things, if not additional stimulation, frequency is fairly constant.People is awake, quiet and the rhythm and pace of moving things is the most when closing one's eyes
Obviously, it opens eyes (by light stimulus) or when receiving other stimulations, α wave disappears at once.
β wave: frequency is 14~30Hz, and amplitude is 100~150 μ V.Occur when nervous and excited or excited
This wave, when people wakes from a nightmare with a start, the slow wave rhythm and pace of moving things originally can be substituted by the rhythm and pace of moving things immediately.
In conclusion show that student is normally learning at this time when equipment detects θ wave and α wave for student, and
When equipment detects other brain waves, show that trouble occurs in student, the starting of this when of camera records relevant figure
As data.Obtained result is stored in computer, and file type can be picture file, is also possible to some other Doctype
File.It can perhaps mobile phone be checked or is sent to teacher or parent by technological means such as networks by computer
To be inquired.
Intelligent assistant learning system according to an embodiment of the present invention based on EEG signals is acquired by wearable device and is used
Family EEG signals, and according to the image of analysis results acquisition user at the moment to EEG signals, it is identified and is deposited by terminal device
Effective image is stored up, thereby, it is possible to facilitate student to carry out induction-arrangement to more difficult knowledge, the time is saved, substantially increases
Practise efficiency.
In the description of the present invention, the meaning of " plurality " is two or more, unless otherwise specifically defined.
In the present invention unless specifically defined or limited otherwise, term " installation ", " connected ", " connection ", " fixation " etc.
Term shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or integral；It can be mechanical connect
It connects, is also possible to be electrically connected；It can be directly connected, can also can be in two elements indirectly connected through an intermediary
The interaction relationship of the connection in portion or two elements.It for the ordinary skill in the art, can be according to specific feelings
Condition understands the concrete meaning of above-mentioned term in the present invention.
In the present invention unless specifically defined or limited otherwise, fisrt feature in the second feature " on " or " down " can be with
It is that the first and second features directly contact or the first and second features pass through intermediary mediate contact.Moreover, fisrt feature exists
Second feature " on ", " top " and " above " but fisrt feature be directly above or diagonally above the second feature, or be merely representative of
First feature horizontal height is higher than second feature.Fisrt feature can be under the second feature " below ", " below " and " below "
One feature is directly under or diagonally below the second feature, or is merely representative of first feature horizontal height less than second feature.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office
It can be combined in any suitable manner in one or more embodiment or examples.In addition, without conflicting with each other, the skill of this field
Art personnel can tie the feature of different embodiments or examples described in this specification and different embodiments or examples
It closes and combines.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (8)
1. a kind of intelligent assistant learning system based on EEG signals, which is characterized in that including wearable device and terminal device,
Wherein,
The wearable device includes:
Image capture module；
Electroencephalogramsignal signal acquisition module, the electroencephalogramsignal signal acquisition module are used to acquire the EEG signals of user；
Main control module, the main control module are connected with described image acquisition module and the electroencephalogramsignal signal acquisition module respectively, institute
Main control module is stated for the EEG signals to be handled and analyzed, and controls described image acquisition module based on the analysis results
Starting is to acquire the image of the user at the moment；
Wireless sending module, the wireless sending module are connected with the main control module, and the wireless sending module is for sending
The image of described image acquisition module acquisition,
The terminal device includes:
Wireless receiving module, the wireless receiving module and the wireless sending module are wirelessly connected to receive described image
The image of acquisition module acquisition；
Picture recognition module, described image identification module are connected with the wireless receiving module, and described image identification module is used for
The image of described image acquisition module acquisition is identified to obtain effective image；
Memory module, the memory module are connected with described image identification module, and the memory module is used for the effectively figure
As being stored.
2. the intelligent assistant learning system according to claim 1 based on EEG signals, which is characterized in that described wearable
Equipment is the equipment of earphone forms, the wearable device include two shells, the described two shells of connection head beam and with
The first support and second support that the head beam is connected, wherein the electroencephalogramsignal signal acquisition module is arranged on the housing,
Described image acquisition module is arranged in the first support, and the main control module is arranged on the head beam, the wireless hair
Module is sent to be arranged in the second support.
3. the intelligent assistant learning system according to claim 1 or 2 based on EEG signals, which is characterized in that the brain
Electrical signal collection module includes:
Eeg signal acquisition device, the eeg signal acquisition device is for acquiring original EEG signals；
Signal amplifier, the signal amplifier is for amplifying the original EEG signals.
4. the intelligent assistant learning system according to claim 3 based on EEG signals, which is characterized in that the master control mould
Block includes:
EEG Processing unit, the EEG Processing unit is connected with the signal amplifier, at the EEG signals
Reason unit is for being filtered the amplified EEG signals and noise reduction and obtaining eeg data；
Data processing unit, the data processing unit are connected with the EEG Processing unit, the data processing unit
For extracting corresponding focus according to the eeg data；
Analyze comparison unit, the analysis comparison unit respectively with the data processing unit and described image acquisition module phase
Even, the analysis comparison unit is for comparing the focus that the data processing unit extracts with default focus range
Compared with, and the starting of described image acquisition module is controlled when the focus is in except the default focus range.
5. the intelligent assistant learning system according to claim 4 based on EEG signals, which is characterized in that the master control mould
Block further includes power supply unit, and the power supply unit is used to power for the wearable device.
6. the intelligent assistant learning system according to claim 5 based on EEG signals, which is characterized in that described image is known
Whether content of the other module for identification in described image contains examination question, and will contain the image of examination question as the effectively figure
Picture.
7. the intelligent assistant learning system according to claim 6 based on EEG signals, which is characterized in that described image is adopted
Collecting module includes camera.
8. the intelligent assistant learning system according to claim 1 based on EEG signals, which is characterized in that the terminal is set
Standby is computer.
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