CN100482155C - Instant detection system and detection method for state of attention based on interaction between brain and computer - Google Patents
Instant detection system and detection method for state of attention based on interaction between brain and computer Download PDFInfo
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- CN100482155C CN100482155C CNB2007100178108A CN200710017810A CN100482155C CN 100482155 C CN100482155 C CN 100482155C CN B2007100178108 A CNB2007100178108 A CN B2007100178108A CN 200710017810 A CN200710017810 A CN 200710017810A CN 100482155 C CN100482155 C CN 100482155C
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Abstract
A method based on the brain-machine interaction for detecting the instantaneous attention state includes such steps as extracting original electroencephalogram (EEG) signal, storing it in digital signal processor (DSP), calculating the two-spectra index and the parameters of weighted two-spectra center, recording the EEG signals after the person to be tested is response to target stimulating marker, superposing in DSP to obtain the event associated potential ERP, extracting its amplitude and delay, inputting them to a nerve network, calculating its node parameters, comparing the output on the response of said person, using the compared result as the monitor information for the retraining of nerve network, determining the node parameters of network again, and outputting the instantaneous attention state. Its system is also disclosed.
Description
Technical field
The invention belongs to technical field of information processing, relating to medical information handles, specifically a kind of instant detection that relates to the information interaction realization state of attention that utilizes computer and human brain, can be used for instant identification, provide foundation for making a definite diagnosis and cure the attention deficit hyperactivity disorder disease to the child attention state.
Background technology
Attention deficit hyperactivity disorder ADD is a modal behavior disorder disease of Childhood, this disease with the selectivity of active attention and poor stability, inflammable, easily to divert one's attention be principal character, common secondary obstacle has learning difficulty, conduct disorder and some dysthymic disorder, for example depressed, self-closing or autism etc.
Usually, clinically the diagnosis of ADD is mainly listened to the head of a family's the next subjective decision patient's of oral account the state of an illness by the doctor.In recent years, the equipment of some objective evaluation ADD is to begin development successively, as application number is 00218646.2,200420021337.2 all to disclose the relevant instrument of evaluation ADD with 200310109026.1 patent documentation, but these instruments all are to test at short notice, measure cornea and inter-retinal signal of telecommunication response curve by follow the trail of the objective luminous point motion of children's vision, curve and the canonical reference curve measured are compared, determine patient's disease kind and degree according to departure degree.Because ADD child attention at short notice may concentrate fully, particularly when seeing own interested thing, attention also may be quite concentrated in the short time, so, the physiology of said determination method is according to also unreliable, and this also is that described patented product is difficult to the main cause for clinicist's acceptance.
In addition, after the ADD child is made a definite diagnosis, the more important thing is treatment.Because the obvious effective rate of Drug therapy only is about 60%, and side effect is serious, therefore, the method for utilizing non-pharmaceutical method to intervene psychosoma class illness such as attention deficit hyperactivity disorder ADD in recent years causes people's attention.Wherein, generally use good effect and having no side effect clinically based on the neural feedback therapy of brain electricity biofeedback.For example application number is that the method for 200510124550.5 patent documentation record belongs to this method and rescues the ADD child, and still, there is the defective of following two aspects in the brain electricity feedback instrument that uses clinically at present, has limited the raising of its curative effect greatly.
(1) only is the attention state of determining the patient by simple brain electricity EEG frequency-domain analysis, promptly calculate what of θ, α ripple and β ripple in the electroencephalogram, some system directly is simplified to the size of only seeing θ/β ratio, because these standards are the same to each patient at any time, and in fact different patients' EEG performance is discrepant, even same patient now also changes at different mental status hypencephalon ammeters, therefore can't carry out personalization to the patient and determine according to patient's brain electricity EEG feature.
(2) because the simple relation between the waveform surveyed is to get by the electric EEG of comparison normal children and ADD child's brain, and not exclusively represent the patient to test at that time attention quality, thereby to carry out real-time biofeedback with these standards be unreasonable.
The content of invention
The objective of the invention is to overcome the shortcoming of above-mentioned prior art, instant detection system of a kind of state of attention based on brain-machine interaction and detection method thereof are provided, this method can be in experimenter and the interaction of computer long period, extract brain electricity and event related potential ERP, set up the neural Network Data Fusion analytical system that an adaptive personalization can dynamically update, and utilize the attention information of experimenter to comprising among the reaction of specific objective and the event related potential ERP, to the correction that exercises supervision of the node parameter of network, realize the personalized instant of patient's attention determined.
The object of the present invention is achieved like this:
The present invention is according to noticing that consciousness directly is controlled by brain, utilize cranial nerve information such as physiological signals such as electroencephalogram, event related potential to extract instant attention characteristics Billy and use the more rational feasibility of ocular physiology signal, determine the technical scheme of instant detection system of its state of attention and detection method thereof based on brain-machine interaction.
Less at the research of noting relevant spontaneous brain electricity specially at present, and notice that the research of event related potential is more relatively.Electroencephalo is learned and be studies show that: when the experimenter noticed a certain feature of stimulating factor, the specific brain zone neuron activity of being responsible for this category feature is processed will be strengthened, and the BEP wave amplitude increases.Studies have shown that the P300 wave amplitude among the event related potential ERP can be used as the evaluation index of intellectual work load.Attention is concentrated more, the corresponding increase of P300 wave amplitude.Existing studies show that, when the experimenter has the initiative attention state, on FZ that electrode for encephalograms distributes, CZ position, the P3-N2 peak-to-peak amplitude of its event related potential ERP significantly increases, and the electroencephalogram power of FZ, CZ position obviously increases, this has proved when experimenter's attention from another angle also and has concentrated that the intellectual work load is bigger.And the P2-N1 peak-peak amplitude of event related potential ERP reduces, and shows that brain may also be redistributed the efficient resource in the brain information processing procedure except that increasing the energy input under the active attention state.
Above research conclusion illustrates, can extract the eigenvalue of different attention states according to event related potential ERP.But, because the collection of event related potential ERP need obtain by additive process, therefore require external environment condition must give the experimenter tens times repetitive stimulation, along with the development of the interaction technique between computer and the brain, oneself does not have obstacle fully clinically to extract brain electricity EEG and event related potential ERP simultaneously.Technical scheme of the present invention adopts just from the brain electricity and the non-linear fusion of event related potential ERP characteristic information divides apoplexy due to endogenous wind accurately to extract personalized attention brain electrical feature.
The present invention adopts the ultimate principle of the instant extraction scheme of attention brain electrical feature to be, begin image data after connecting brain electricity and event related potential ERP test set to the experimenter, require the experimenter that two kinds of target identifications that constantly occur at random by a certain percentage on the screen are made a response, in this process, constantly write down brain, and behind certain hour, produce event related potential ERP by the addition method, and the event related potential ERP feature extraction that produces come out, carry out the integrated classification of data with neutral net with two spectrum index features of brain electricity, attention situation when drawing experimenter's data acquisition, and its data acquisition result and experimenter compared the response situation of screen request, the parameter to neutral net under the supervision of experimenter's response situation is adjusted.Along with the increase of testing time, the accuracy rate of system identification attention state is improved constantly, in continuous training and testing process, progressively form the instant detection system of attention of propertyization one by one.
According to above-mentioned principle, the instant detection system of state of attention based on brain-machine interaction provided by the invention comprises computer, brain wave acquisition electrode, pre-process circuit, digital signal processor DSP, wherein the brain wave acquisition electrode is to be provided with by the international standard system position of leading, this electrode links to each other with pre-process circuit by shielding line, pre-process circuit links to each other with computer through analog-digital converter, digital signal processor DSP is connected with computer bidirectional, and links to each other with dedicated handle; All EEG signals in the computer continuous record test process are also sent digital signal processor DSP that signal is carried out two spectrums and are calculated, and extract the two spectrum center WCOB of two spectrum index bic and weighting; Digital signal processor DSP adopts the addition method to extract the amplitude and the retardation of event related potential ERP and related potential simultaneously from EEG signals, and give computer with amplitude and these characteristic parameter data loopbacks of retardation of two spectrum center WCOB of two spectrum index bic, weighting and related potential, these data are given the state of attention of neutral net output on-demand system identification by computer as input signal.
The instant detection system of above-mentioned state of attention, wherein said dedicated handle are provided with two buttons, realize the reaction of experimenter to identifying on the screen by button.
The instant detection system of above-mentioned state of attention, wherein digital signal processor DSP adopts the addition method to extract event related potential ERP from EEG signals, handle is pressed to EEG signals behind few 1s superposes and obtain.
The instant detection system of above-mentioned state of attention, wherein digital signal processor DSP the mistake reaction of experimenter after seeing target stimulation sign or non-target stimulation sign, leak response situation and the response delay time is given computer, be used for backstage training for computer as supervision message to neutral net.
The present invention utilizes said system to carry out the instant method that detects of attention brain electrical feature, comprises the steps:
(1) the brain wave acquisition electrode is placed on experimenter's the scalp according to international 10-20 standard, extracts original brain electricity EEG signal and be input to computer;
(2) computer disturbs to reject to the eeg data of gathering and handles, and this deposit data is arrived digital signal processor DSP;
(3) digital signal processor DSP carries out segmentation to the brain electricity of gathering, and carries out two spectrum calculating, the calculating of two spectrum index and the two spectrum of weighting center calculation successively;
(4) experimenter reacts to target stimulation sign and non-target stimulation sign that computer shows by using dedicated handle, and computer identifies reacted EEG signals with the experimenter to target stimulation and carries out record, and gives digital signal processor DSP with this signal;
(5) digital signal processor DSP superposes to the EEG signals of being imported, and obtains event related potential ERP, and extracts the amplitude and the retardation of this event related potential waveform;
(6) amplitude of the two spectrum centers of described pair of spectrum index, weighting, event related potential waveform and retardation are inputed to neutral net and determine the node parameter of network, finish training neutral net by back propagation algorithm;
(7) experimenter is carried out in the process of follow-on test, output result that neutral net is up-to-date and experimenter neutral net output latest result with on once export the reaction that between the result target stimulation is identified, comprise that mistake reaction, leakage reaction and response delay contrast, and the result that will contrast sends into neutral net as the supervision message that neutral net is trained again, redefine the node parameter of network, the final accurate identification that realizes the attention immediate status.
The present invention utilizes the complementarity of multi-source information because the active attention information that contains in brain electricity EEG and the event related potential ERP signal is combined, and has remedied to utilize single brain electricity EEG to carry out drawback and the deficiency that quality is levied surely; Simultaneously owing to adopt the reaction that the output result of neutral net and experimenter are identified target stimulation, comprise that mistake reaction, leakage reaction and response delay contrast, and the result that will contrast sends into neutral net as the supervision message that neutral net is trained again, so can redefine the node parameter of network, the final accuracy of realizing human body attention test identification.The present invention can increase substantially the effective percentage of clinical attention power accuracy rating of tests and the behavior intervention of ADD psychology, in cognitive psychology research significant values is arranged also.
Purpose of the present invention, feature and advantage will be in conjunction with the embodiments, make following further instruction with reference to accompanying drawing.
Description of drawings
Fig. 1 is a system of the present invention schematic block diagram;
Fig. 2 is procedure figure of the present invention;
Fig. 3 is that the present invention gathers brain electricity electrode used therein scattergram;
Fig. 4 is the two spectrograms under different attention state situations;
Fig. 5 utilizes back propagation algorithm to determine the flow chart of neutral net node parameter.
The specific embodiment
With reference to Fig. 1, the instant detection system of state of attention of the present invention is made up of brain wave acquisition electrode, pre-process circuit, 12 analog-digital converters, digital signal processor DSP, dedicated handle and computers, wherein dedicated handle is provided with two buttons, realizes the reaction of experimenter to identifying on the screen by button; Pre-process circuit comprises brain electric standard physiological signal amplifier and band filter, and this amplifier comprises preamplifier, post amplifier, and this wave filter comprises 0.5～70Hz band filter and 60Hz power frequency notch filter; Store in the computer and reject interferential preprocessor, data convey program, and realize neural network structure, training program.The mutual relation of these assemblies is: the brain wave acquisition electrode links to each other with the brain electric standard physiological signal amplifier of pre-process circuit by shielding line, be connected to 12 analog-digital converters by wave filter, the data output of this analog-digital converter links to each other with computer by USB interface, by computer the brain electric standard physiological signal of gathering is carried out the dynamic data analyzing and processing; Digital signal processor DSP is connected with computer bidirectional, and digital signal processor DSP is connected with dedicated handle simultaneously; All EEG signals in the computer continuous record test process also send the DSP signal processor that EEG signals is carried out two spectrum calculating, two spectrum index and the two spectrum of weighting center calculation successively, and give computer with the characteristic parameter loopback that calculates; Simultaneously the EEG signals also handle pressed behind the 1s at least of digital signal processor DSP superposes, it is 50 times that the present invention sets synergetic number of times, the brain wave patterns that obtains after stack is finished is event related potential ERP, extract the characteristic parameter of this event related potential ERP amplitude and deferred message and give computer, after computer is received the characteristic parameter that digital signal processor DSP sends here, give neutral net with these characteristic parameter data as input, neutral net is carried out the data fusion analysis according to these characteristic parameters of computer input, the result of determination of output state of attention; In addition, digital signal processor DSP also send the response situation of experimenter after seeing target stimulation or non-target stimulation sign and is transferred to computer by button, comprise reaction by mistake, leak reaction, response delay time, be used for the backstage of neutral net is trained as supervision message for computer.This target stimulation or non-target stimulation sign are that the program that weaves in advance before the test beginning is stored in the hard disc of computer, are played back under experimenter's operation by main control computer, and wherein target stimulation is designated roundel, accounts for 20%; Non-target stimulation is designated square thing, accounts for 80%, and the experimenter sees that circular sign presses left button, sees that square sign presses right button.
With reference to Fig. 2, it is as follows to utilize system of the present invention to carry out the process of instant attention test:
Step 1. is placed on the brain wave acquisition electrode on experimenter's the scalp according to the system position of leading by international standard shown in Figure 3, original brain electricity EEG signal is extracted in, filtering big by general brain tele-release, this brain wave acquisition electrode comprises two reference electrode A1, A2 on 16 test electrode Fp1, Fp2, F3, F4, F7, F8, C3, C4, T3, T4, T5, T6, P3, P4, O1, O2 and the ears that are distributed in head.
Step 2. becomes digital signal to deliver to computer original brain electricity EEG analog signal conversion, computer is after rejecting interferential pretreatment to these data, send EEG signals data copy portion to data signal processor DSP again, ready for extracting event related potential ERP.
Step 3. data signal processor DSP is divided into one section to the brain electric information of gathering by per 512, and carries out following two spectrum and calculate.
(1) make x (n) be brain electricity time series to be analyzed, its three rank cumulant C
3x(m
1, m
2) be:
C
3x(m
1，m
2)＝E[x(n)x(n+m
1)x(n+m
2)]
M in the formula
1, m
2Be different retardations,
X (n+m
1) be through m
1Time series after the delay,
X (n+m
2) be through m
2Time series after the delay,
E[] be mathematic expectaion;
(2) with two spectrum B of x (n)
x(ω
1, ω
2) be defined as C
3x(m
1, m
2) two-dimensional fourier transform, promptly
Fig. 4 is the two spectrograms of brain electricity in typical case, wherein, (A) is the situation of experimenter when focusing one's attention on, and (B) is the situation of experimenter when not focusing one's attention on.As seen, two spectral amplitudes are apparently higher than figure B among the figure A, and its peak value position is also obviously different, therefore extracts the amplitude and the peak value coordinate positions of two spectrums from the two spectrograms of brain electricity, just can include the characteristic information of experimenter's state of attention.
Step 4. is calculated two spectrum indexs, promptly for stochastic process { x
1, if it is a Gauss distribution, then to all m
1, m
2, its three rank cumulant C (m
1, m
2)=0, its pair spectrum B (ω
1, ω
2) amplitude also be zero, thereby | B (ω
1, ω
2) | can be used as stochastic process { x
1Depart from a measurement of Gauss distribution.Consideration standardizes to multispectral with power spectrum, claims its standardization result to be two spectrum indexs, so two spectrum indexs of definition stochastic process { x (n) } are defined as:
P wherein
x(ω) be power spectrum.
Step 5. is calculated the two spectrum center WCOB of weighting, being about to WCOB is defined as with two spectrums to be weights at the energy of every bit, to ask the weighted mean of all point coordinates on whole bifrequency plane, obtain a plane coordinates, suppose that (x, two spectrums of y) locating are B to this plane coordinates point
Xy, then can calculate the coordinate position WCOB (f of the two spectrum center WCOB of weighting by following formula
1m, f
2m) be:
Step 6 experimenter is by using dedicated handle, target stimulation sign and non-target stimulation sign that computer shows are reacted, it is experimenter's left button by lower handle when seeing circular sign, see the right button of square when sign by lower handle, and be transferred to computer by digital signal processor DSP, computer identifies reacted EEG signals with the experimenter to each target stimulation and carries out record, and the counter again digital signal processor DSP of giving of the EEG signals that will write down.
Step 7 digital signal processor DSP superposes to 50 brain electric informations gathering, obtains event related potential ERP, and calculates amplitude and the retardation of event related potential ERP.
Step 8 is with above-mentioned couple of spectrum index bic
2x(ω
1, ω
2), the coordinate position WCOB (f of the two spectrum center WCOB of weighting
1m, f
2m), amplitude and the retardation of event related potential ERP, as the input of neutral net, be used for neutral net is trained; This neutral net adopts general four layers of forward direction multitiered network, and initial weight is the BP algorithm with the random number in (0,0.5) to the most frequently used back propagation algorithm in the training employing feedforward network of neutral net, determines the node parameter of network according to flow process shown in Figure 5:
(1) compose (between 0～0.5) random value that non-zero is less for each node weight vector of neutral net.The characteristic parameter that extracts is input to the input layer of neutral net as the network input vector;
(2) the actual output of calculating neutral net compares reality output and desirable output, calculates difference wherein;
(3) judge whether this difference meets a predefined tolerance standard, if difference can be tolerated (5) step below then changeing; If following (4) step is carried out in not tolerable of difference;
(4) oppositely successively calculate every layer of neuronic partial gradient by the standard BP algorithm formula, revise node parameter one by one;
(5) judge whether to have trained the sample vector of all input characteristic parameters,, change (1) if do not have; If trained, then finish whole training process.
The neutral net that step 9 is finished training is used for experimenter's state of attention is detected, and exports its testing result.
Step 10 is being carried out the experimenter in the process of follow-on test, output result that neutral net is up-to-date and experimenter neutral net output latest result with on once export the reaction that between the result target stimulation is identified, comprise that mistake reaction, leakage reaction and response delay contrast, and the result that will contrast sends into neutral net as the supervision message that neutral net is trained, and 8 flow process redefines the node parameter of neutral net set by step.
Above-mentioned training process makes the node parameter of neutral net to dynamically update, improve constantly the accuracy of the instant test of state of attention, final realize that by instrument people's state of attention being carried out objective, personalization tests immediately, gets rid of the inaccurate problem of identification that anthropic factor causes.
The present invention not only can be used for the detection to childhood hyperkinetic syndrome more than 6 years old, also can be used for adult state of attention is detected immediately.
Claims (4)
1. instant detection system of the state of attention based on brain-machine interaction, comprise computer, brain wave acquisition electrode, pre-process circuit, digital signal processor DSP, it is characterized in that the brain wave acquisition electrode is to place by the international standard system position of leading, this electrode links to each other with pre-process circuit by shielding line, and pre-process circuit links to each other with computer through analog-digital converter; Digital signal processor DSP is connected with computer bidirectional, and links to each other with dedicated handle; All EEG signals in the computer continuous record test process are also given digital signal processor DSP and are carried out two spectrum calculating, extract the two spectrum centers of two spectrum indexs and weighting; Digital signal processor DSP adopts the addition method to extract amplitude and the retardation of event related potential ERP and related potential ERP from EEG signals, and give computer with amplitude and these characteristic parameter data loopbacks of retardation of two spectrum centers of two spectrum indexs, weighting and related potential ERP, give neutral net with these data as input signal by computer, by the instant state of attention of neutral net output identification.
2, the instant detection system of state of attention according to claim 1 is characterized in that dedicated handle is provided with two buttons, and the experimenter realizes the reaction to identifying on the screen by pushing button.
3, the instant detection system of state of attention according to claim 1 and 2, it is characterized in that digital signal processor DSP adopts the addition method to extract event related potential ERP from EEG signals, is by digital signal processor DSP handle to be depressed to EEG signals behind few 1s to superpose and obtain.
4. the instant detection system of state of attention according to claim 1 and 2, it is characterized in that digital signal processor DSP the mistake reaction of experimenter after seeing target stimulation sign or non-target stimulation sign, leak response situation and the response delay time is given computer, be used for training for computer as supervision message to neutral net.
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| CN108766532A (en) * | 2018-05-11 | 2018-11-06 | 深圳市心流科技有限公司 | Improve teaching method, device and the computer readable storage medium of attention |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108766532A (en) * | 2018-05-11 | 2018-11-06 | 深圳市心流科技有限公司 | Improve teaching method, device and the computer readable storage medium of attention |
| WO2022077936A1 (en) * | 2020-10-16 | 2022-04-21 | 杭州师范大学 | Electroencephalogram feedback delay-based sustained attention regulation and control system |
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