CN108478224A - Intense strain detecting system and detection method based on virtual reality Yu brain electricity - Google Patents
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Abstract
The intense strain detecting system based on virtual reality Yu brain electricity that the invention discloses a kind of, mainly solution prior art detection process is very long, and testing cost is high and Detection accuracy is low, it is difficult to the problem of effectively detecting user's intense strain.It includes inducing module (1), signal synchronization module (2), informix module (3) and message processing module (4)：It induces module drive virtual reality device and shows stimulus material, by signal synchronization module generated time synchronizing signal and generate user feedback；Informix module acquires EEG signals, receives synchronizing signal and collects user feedback, delivers message processing module and is handled, provides mood testing result.The present invention shows stimulus material using virtual reality technology, objective analysis is combined with subjective assessment, enhance availability, the reliability and stability of system, accelerate detection speed, reduce testing cost, the Detection accuracy for improving system can be used for the education to specific user and psychological counseling.
Description
Technical field
The invention belongs to emotional state identification technology fields, are detected more particularly to a kind of intense strain to various people
System and detection method can be used for the education to specific user and psychological counseling.
Background technology
1. virtual reality technology
Virtual Reality refers to that comprehensive utilization computer system and all kinds of displays, control device generate the three-dimensional ring that can be interacted
Border, the technology that immersion experience is provided.This term was proposed in 1985 by Jarn Lanier at first.Virtual reality technology can
With high fidelity simulation real world, user is made to be handed over therewith by sense organ, limbs or auxiliary device in simulating three-dimensional environment
Mutually, to the feeling with " on the spot in person ".Its essential characteristic is feeling of immersion, interactivity and imagination.
In recent years, virtual reality was because it was in each neck such as amusement, game, education, medical treatment, artistic creation, engineering design
The great potential in domain and have attracted much attention.Duo Jia electronics equipment vendors are proposed the device suite of consumer level, based on virtual reality
Application software, game and panoramic video largely occur therewith.
2. eeg signal acquisition and treatment technology
EEG signals are generated by the bioelectric of cerebral neuron group, belong to autonomous potential activity.Studies have shown that brain
Contain the ingredient that can reflect human emotion in electric signal.EEG Processing technology can be applied to the research and development of brain-computer interface, brain
The diagnosis of portion's disease and human cognitive active studies etc..
Non-intrusion type brain electricity is connected with scalp by conductive paste using electrode to acquire EEG signals, and this kind of signal is very micro-
It is weak, easily by noise jamming, it usually needs be filtered and obtain useful information with feature extraction.
EEG signals are usually divided into the different rhythm and pace of moving things of δ, θ, α, β, γ these types by frequency range, containing in the different rhythm and pace of moving things can
Reflect the information of human physiology psychological condition, wherein：
Delta rhythm is predominantly located at 1~4Hz frequency ranges, the main deep sleep for reflecting people or special brain sufferer；
Theta rhythm is predominantly located at 4~8Hz frequency ranges, main to reflect people in sleep initial stage, meditation or sleepy, oppressive state；
Alpha rhythm is predominantly located at 8~12Hz frequency ranges, except reflection people is in state that is awake, quiet and closing one's eyes, further comprise with
The relevant μ waves of somatic movement；
Beta response is predominantly located at 12~30Hz frequency ranges, can reflect people be in nervous, excited or thought active,
State when attention is concentrated also contains some reflection relevant information of somatic movement；
Gamma rhythm is predominantly located at 30~60Hz frequency ranges, and it includes the thinking activities of higher level, such as emotional change, abstract think of
The states such as examine.
3. mood detects
Mood detection is the research hotspot of the crossing domains such as psychology and neuroengineering, is had broad application prospects.
Such as in production activity, it is operated in aerospace enterprise, state security department or mining site, builds great production task or high-risk work
Make the crowd under environment, spirit is frequently in high-pressure state, and mood detection is periodically carried out to it can find feelings in time
The individual of thread exception avoids its state of mind from continuing to deteriorate to prior involvement, reduces production risk, reduces security risk.
Education sector, mood detection is capable of providing valuable information, unhealthy to being in such as assessment of students', the psychologic status of teacher
The individual of state is intervened in time；Emotional state of the student in learning process is detected, is compareed with the education activities of teacher, from
And optimizes teaching environment, improves quality of instruction.
The method of mood detection at present is broadly divided into the detection based on non-physiological signal and based on physiological signal, wherein being based on
The detection of non-physiological signal includes the detection to expression, voice or posture；Detection based on physiological signal includes to electrocardio, brain
The detection of electricity, myoelectricity, breath signal.Since EEG signals are directly related to consciousness, it is difficult to it is hidden, inhibit and cover up, it is based on brain
The mood detection of electricity is concerned.
Intense strain is in actual life generally existing.Psychology and pedagogy think that intense strain appropriate can be concentrated
Attention, raising working efficiency, and the overstretched adverse reaction that may cause Human Physiology psychology, it could even be possible to causing to compare
More serious consequence.Therefore the technology of effectively detection intense strain is extremely important, has larger application potential.But in emotion meter
Calculation field, basic emotion that is nervous and being not belonging to people, but a variety of emotional states are compounded on the basis of autospecific, because
The design and aimed detection of this intense strain detecting system have much difficulty.
Current existing intense strain detecting system, it is a variety of to generally require complex electrocardio, myoelectricity, blood pressure, brain electricity, posture etc.
Physiology, non-physiological signal can be just detected, and prepare and implementation process is extremely cumbersome, substance and time cost are higher；In addition,
The stimulation means of such system are mostly that image or video are played in flat-panel screens at present, and it is poor that user substitutes into sense, it is difficult to induce
The emotional state of high quality.The presence of these two aspects factor, leads to that the detection process of such system is very long, testing cost is high, and
Detection accuracy is low, cannot effectively detect the intense strain of user.
Invention content
It is a kind of based on the tight of virtual reality and brain electricity it is an object of the invention in view of the above shortcomings of the prior art, provide
Mood detecting system and detection method are opened, to accelerate detection speed, reduces testing cost, Detection accuracy is improved, effectively detects
Go out the intense strain of user.
To achieve the above object, the present invention uses following scheme：
1. a kind of intense strain detecting system based on virtual reality Yu brain electricity, the nervous feelings based on virtual reality Yu brain electricity
Thread detecting system, including induce module, signal synchronization module, informix module and message processing module, it is characterised in that：
Induce module, including virtual reality projection submodule and projection feedback submodule；
Informix module, including brain wave acquisition submodule and feedback capture submodule；
The virtual reality shows submodule, and for showing audiovisual materials, generated time label, the label pass through letter simultaneously
Number synchronization module generated time synchronizing signal is sent to brain wave acquisition submodule to time synchronizing signal and the brain electricity that acquires in real time
After signal carries out synthesis, it is transferred to message processing module and is handled；
Submodule is fed back in the projection, for showing feedback form after audiovisual materials are shown, after user fills in
Feedback result is sent to feedback capture submodule to be collected feedback information, and by the transmission of feedback information of collection to information
Processing module is handled；
The feedback capture submodule, the feedback data for collecting projection feedback submodule generation, and will be collected into
Transmission of feedback information is handled to message processing module.
2. the intense strain detection method based on virtual reality Yu brain electricity, which is characterized in that including：
1) off-line training：
1a) virtual reality device is used to show video, induces the anxiety of user or loosen mood；
It 1b) acquires user's EEG signals, receiving time synchronizing signal in display process and collects user feedback, be integrated into use
Family integrated data；
1c) integrated data is pre-processed successively, feature extraction and tagsort, obtains grader；
2) on-line checking：
Ballot ratio 2a) is set, in 2e) correction judgement result；
2b) use virtual reality device projection and 1a) different video, the anxiety of user is induced again or loosens mood；
User's EEG signals in the display process, receiving time synchronizing signal 2c) are acquired, pretreatment is carried out and feature carries
Take, and use 1c) in obtained grader classify to the data after feature extraction；
2d) the real-time display classification results and keep a record；
2e) to 2d) in record classification results in 2a) in setting ratio vote：If in classification results " anxiety "
Poll be more than this ratio, then user emotion is determined as " anxiety ", is otherwise determined as " loosening ".
Compared with the prior art, the present invention has the following advantages：
The first, the present invention induces subject's mood using virtual reality system, utilizes the spy of virtual reality " on the spot in person "
Property improves irritation level, enhances the availability of system；
The second, objective analysis is combined by the present invention with subjective assessment, at the subjective feeling and EEG signals of subject
The procedure correlation of reason, the method for optimizing separation valid data improve conventional thought lower band and are in a bad mood the EEG signals of information
It is difficult to the defect accurately intercepted and captured；
Third, the present invention provided in message processing module cover alternatives, be applicable to different subjects and
All kinds of experimental situations enhance the robustness of system, effectively improve intense strain Detection accuracy.
Description of the drawings
Fig. 1 is that the present invention is based on the intense strain detecting system block diagrams of virtual reality and brain electricity.
Fig. 2 is that the present invention is based on the intense strain detection method flow charts of virtual reality and brain electricity.
Specific implementation mode
Referring to Fig.1, the present invention is based on the intense strain detecting systems of virtual reality and brain electricity, including induce module 1, signal
Synchronization module 2, informix module 3 and message processing module 4, wherein：
It includes virtual reality projection submodule 11 and projection feedback submodule 12 to induce module 1；
Informix module 3 includes brain wave acquisition submodule 31 and feedback capture submodule 32；
Message processing module 4 includes pretreatment submodule 41, feature extraction submodule 42 and tagsort submodule 43.
The virtual reality projection submodule 11 drives virtual reality device to show, and " loosening " " anxiety " is two kinds of to be regarded
Frequently, corresponding EEG signals are generated to induce user, generated time label is sent to signal synchronization module 2 simultaneously for projection；
The projection feedback submodule 12 shows feedback page after projection, and feedback result is sent to feedback and is received
Collect submodule 32；
The signal synchronization module 2 will mark and be converted into synchronizing signal the time, be sent to brain wave acquisition submodule 31；
The brain wave acquisition submodule 31 acquires EEG signals and merges it with time synchronizing signal, is sent to pretreatment
Submodule 41；
The feedback capture submodule 32 collects feedback result, and sends it to pretreatment submodule 41；
The pretreatment submodule 41, which receives, merges signal and feedback result, utilizes the time synchronizing signal merged in signal
And user feedback, it is extracted from EEG signals and is sent to extracting sub-module 42 with the higher signal data of the mood degree of correlation；
The feature extraction submodule 42 converts signal data to more efficient characteristic, and characteristic is sent
Classify to tagsort submodule 43 to characteristic, and calculates in off-line training step that can to distinguish two class moods special
The grader of sign, on-line checking stage classify to the characteristic of real-time reception using this grader.
The system is divided into two kinds of operating modes of off-line training and on-line checking, and off-line training establishes point for user's individual
Class device, on-line checking are measured in real time the EEG signals of user using this grader, and user feedback is combined to realize result
Correction.Its detailed description is shown in following " the intense strain detection method based on virtual reality Yu brain electricity ".
With reference to Fig. 2, the present invention is based on the intense strain detection method of virtual reality and brain electricity, including off-line training with online
Detection, wherein：
Step 1, off-line training.
1.1) virtual reality device is used to show video, wherein " anxiety " video selects terrible, terrified, disaster or action
Piece segment, " loosening " video selects natural land, the easily video clips such as amusement, to induce the anxiety of user or loosen mood；
1.2) it uses non-intrusion type brain wave acquisition equipment to acquire EEG signals, while receiving time synchronizing signal, and collects
Field feedback：
1.2a) show the user feedback page, content of pages includes loosening-nervous measuring scale and the explanation to table meaning
Word：This loosens-nervous measuring scale is as shown in table 1, using 1~9 this nine numerical value indicate users loosen or tensity,
Wherein " 1 " indicates extremely to loosen, and " 5 " indicate to loosen, nervous middle state, and " 9 " indicate extreme anxiety, numerical value by 1 to 5 according to
Secondary increase, expression are loosened mood and are weakened successively；Numerical value is successively increased by 5 to 9, indicates that intense strain enhances successively；
Sense of reality when 1.2b) user is according to viewing video, loosen at this-nervous measuring scale in hook under corresponding scores
Choosing；
The score 1.2c) is recorded as field feedback；
Table 1 loosens-intense strain assessment scale
1.3) pretreatment as follows, spy are carried out to the EEG signals, time synchronizing signal and field feedback that 1.2) obtain
Sign extraction and tagsort：
1.3a) setting time window length；
High-pass filtering 1.3b) is done to EEG signals, removes the unrelated ingredient of low frequency in signal, and according to synchronizing signal and use
Family feedback extraction and the relevant EEG signals of mood；
Filtered signal is split by the time window length of setting 1.3c), obtains slice signal, completes pre- place
Reason；
Dimensionality reduction parameter 1.3d) is set；
1.3e) to slice signal application Hanning window to enhance its frequency domain characteristic, and make Fast Fourier Transform (FFT), by signal by
Time domain transforms to frequency domain, obtains the frequency spectrum of signal；
1.3f) on the signal spectrum that transformation obtains, 2~4Hz of calculating, 4~8Hz, 8~16Hz, 16~32Hz and 32~
Energy-distributing feature in five frequency ranges of 64Hz obtains energy-distributing feature vector, this five frequency range Inertial manifolds brain telecommunications
This five kinds of main rhythm and pace of moving things of δ, θ, α, β, γ in number contain and the relevant information of mood.Wherein delta rhythm is predominantly located at 1~4Hz, θ sections
Rule is predominantly located at 4~8Hz, and alpha rhythm is predominantly located at 8~12Hz, and beta response is predominantly located at 12~30Hz, and gamma rhythm is predominantly located at 30
~60Hz.The circular of energy-distributing feature is the Fourier spectrum coefficient summation to this five frequency ranges, i.e. BPn=∑
afft(x), wherein BPnFor energy-distributing feature, afftFor Fourier spectrum coefficient, x is time-domain signal；
It is 1.3g) stability for enhancing grader, it includes screening to need the dimension for reducing energy-distributing feature vector, method
Go out a part and the higher electrode of the mood signal degree of correlation, the energy feature of the symmetrical signal of electrode position is enabled to subtract each other.According to setting
The dimensionality reduction parameter set is, it can be achieved that a variety of dimension reduction methods combine, to obtain symmetry energy feature, completion feature extraction；
1.3h) support vector machines train classification models is used to obtain grader, completes tagsort.
Step 2, on-line checking.
2.1) ballot ratio is set；
2.2) use virtual reality device show with 1.1) different video, the anxiety of induction user or loosen feelings again
Thread；
2.3) user's EEG signals in the display process, receiving time synchronizing signal are acquired, carries out pretreatment and spy successively
Sign extraction, obtains characteristic, and tagsort is carried out to characteristic using the grader obtained in 1.3)；
2.4) it the real-time display classification results and keeps a record；
2.5) it is voted in 2.1) the middle ratio set 2.4) the middle classification results recorded：If " tight in classification results
" poll be more than this ratio, then user emotion is determined as " anxiety ", is otherwise determined as " loosening ".The judgement be to
The judgement of family whole emotional state during watching video.
Above description is only the specific example of the present invention, does not constitute any limitation of the invention, it is clear that for
It, all may be without departing substantially from the principle of the invention, knot after having understood present disclosure and principle for one of skill in the art
In the case of structure, various modifications in form and details and change are carried out, but these amendments based on inventive concept and change
Become still within the claims of the present invention.
Claims (7)
1. the intense strain detecting system based on virtual reality Yu brain electricity, including induce module (1), signal synchronization module (2), letter
Cease integration module (3) and message processing module (4), it is characterised in that：
Induce module (1), including virtual reality projection submodule (11) and projection feedback submodule (12)；
Informix module (3), including brain wave acquisition submodule (31) and feedback capture submodule (32)；
The virtual reality projection submodule (11), for showing audiovisual materials, generated time label, the label pass through letter simultaneously
Number synchronization module (2) generated time synchronizing signal is sent to brain wave acquisition submodule (31) to time synchronizing signal and acquisition in real time
EEG signals carry out it is comprehensive after, be transferred to message processing module (4) and handled；
The projection feedback submodule (12), for showing feedback form after audiovisual materials are shown, after user fills in
Feedback result is sent to feedback capture submodule (32) to be collected feedback information, and the transmission of feedback information of collection is given
Message processing module (4) is handled；
The feedback capture submodule (32), the feedback data generated for collecting projection feedback submodule (12), and will collect
To transmission of feedback information handled to message processing module (4).
2. system according to claim 1, which is characterized in that described information processing module (4) includes：
Pre-process submodule (41), for brain wave acquisition submodule (31) and feedback capture submodule (32) transmission information into
Row pretreatment, pretreated data transfer carry out feature extraction to feature extraction submodule (42)；
Feature extraction submodule (42) extracts the data transfer after feature for carrying out feature extraction to pretreated data
Tagsort is carried out to tagsort submodule (43)；
Tagsort submodule (43) is calculated disaggregated model and shows for classifying to the data after feature extraction
Classification results.
3. the intense strain detection method based on virtual reality Yu brain electricity, which is characterized in that including：
1) off-line training：
1a) virtual reality device is used to show video, induces the anxiety of user or loosen mood；
It 1b) acquires user's EEG signals, receiving time synchronizing signal in display process and collects user feedback, it is comprehensive to be integrated into user
Close data；
1c) integrated data is pre-processed successively, feature extraction and tagsort, obtains grader；
2) on-line checking：
Ballot ratio 2a) is set, in 2e) correction judgement result；
2b) use virtual reality device projection and 1a) different video, the anxiety of user is induced again or loosens mood；
User's EEG signals in the display process, receiving time synchronizing signal 2c) are acquired, pretreatment and feature extraction are carried out, and
Use 1c) in obtained grader classify to the data after feature extraction；
2d) the real-time display classification results and keep a record；
2e) to 2d) in record classification results in 2a) in setting ratio vote：If the ticket of " anxiety " in classification results
Number is more than this ratio, then user emotion is determined as " anxiety ", be otherwise determined as " loosening ".
4. according to the method described in claim 3, it is characterized in that, step 1b) in collect user feedback, as follows into
Row：
1b1) show the user feedback page, content of pages includes loosening-nervous measuring scale and the explanation word to table meaning：
This loosens-nervous measuring scale using 1~9 this nine numerical value indicate users loosen or tensity, wherein " 1 " indicates extreme
Relaxation state, " 5 " indicate to loosen, nervous middle state, and " 9 " indicate that extreme tense situation, numerical value are gradually increased by 1 to 5,
Expression is loosened mood and is gradually being weakened；Numerical value is gradually increased by 5 to 9, indicates that intense strain gradually increases；
Sense of reality when 1b2) user is according to viewing video, loosen at this-nervous measuring scale in choose corresponding score；
1b3) score that record is chosen is as user feedback data, the user feedback data and user's EEG signals, time synchronization
Signal integration is 1b) in user's integrated information.
5. according to the method described in claim 3, it is characterized in that, step 1c) in pretreatment, be that time window length is first set；
Again from user's integrated data, EEG signals data are extracted according to synchronizing signal and user feedback, and do to the signal extracted
The unrelated ingredient of low frequency in signal is removed in high-pass filtering；Then filtered signal is divided by the time window length of setting
It cuts.
6. according to the method described in claim 3, it is characterized in that, step 1c) in feature extraction include：
First, dimensionality reduction parameter is set；
Then, Hanning window is used on signal after singulation, and does Fast Fourier Transform (FFT)；
Then, on the obtained signal spectrum of transformation, according to preset frequency band parameters respectively to 2~4Hz, 4~8Hz, 8~
The energy of 16Hz, 16~32Hz and the signal in 32~64Hz, five frequency ranges is summed, and energy-distributing feature vector is obtained；
Then, according to the dimensionality reduction parameter of setting, the energy-distributing feature on partial electrode is deleted, or electrode position is symmetrically believed
Number energy feature subtract each other, to reduce feature vector dimension, enhance grader stability.
7. according to the method described in claim 3, it is characterized in that, step 1c) in tagsort, be to the feature after dimensionality reduction
Using support vector machines train classification models, to obtain grader.
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Cited By (8)
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| CN109471532A (en) * | 2018-10-31 | 2019-03-15 | 北京津发科技股份有限公司 | Multichannel man-machine environment test data synchronous platform experimental design work system and method |
| CN111026265A (en) * | 2019-11-29 | 2020-04-17 | 华南理工大学 | System and method for continuously labeling emotion labels based on VR scene videos |
| CN111134669A (en) * | 2020-04-08 | 2020-05-12 | 成都泰盟软件有限公司 | Visual evoked potential acquisition method and device |
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