CN103995799A - Frequency phase brain-computer interface decoding method and device based on FFT spectrum correction - Google Patents

Abstract

The invention discloses a frequency phase brain-computer interface decoding method based on FFT spectrum correction. The method comprises the steps that digital sampling is carried out on collected SSVEP signals to obtain N discrete samples, windowing is carried out on the discrete samples for FFT analysis, and the spectrum of the SSVEP signals is obtained; a peak value spectrum is sought out, the phase value of the peak value spectrum is recorded, the secondary high spectrum position needs to be determined, and a ratio is obtained; a frequency offset estimated value is obtained through the ratio, and corresponding phase estimated values are obtained based on the frequency offset estimated value; a stimulation object is recognized by solving measurement phase errors of two corrected stimulation frequencies. According to the decoding device, the collected signals are sampled by an analog-digital converter to obtain a sample sequence, the collected signals enter into a DSP device in a parallel digital input mode, internal processing is carried out, and parameter estimation of the signals is obtained; then a command sent by a tested person is displayed through an output drive and a display module of the output drive, and finally external equipment responds to the corresponding command.

Description

Frequency plot brain-computer interface coding/decoding method and the device thereof based on FFT spectrum, proofreaied and correct

Technical field

The present invention relates to digital processing field, relate in particular to a kind of frequency plot brain-computer interface coding/decoding method and device thereof of proofreading and correct based on FFT spectrum, when the present invention exists frequency deviation to the frequency of the brain-computer interface device pumping signal based on the steady-state induced current potential of vision, by FFT spectrum correction method, extract phase information and realize command decode.

Background technology

Brain-computer interface ^[1](Brain-Computer Interface, brief note is BCI) be a kind of direct communication and control passage of setting up between human brain and computing machine or other electronic equipments, it does not rely on the normal output channel (peripheral neverous system and musculature) of brain, is a kind of brand-new communication and control mode ^[2].It is intended to set up human brain and extraneous direct communication channel, by extracting the feature of EEG signals, identifies brain instruction, finally completes the direct control of brain to external unit.

The fundamental purpose of research brain-computer interface technology is the control device of designing based on EEG signals, to realize and the exchanging and control of external environment condition ^[3].Therefore brain-computer interface has profound significance in field of medical analysis and clinical practice.

In the selection of EEG signals, Steady State Visual Evoked Potential (Steady-State Visual Evoked Potential, notes by abridging as SSVEP) ^[4]cause has non-infringement, system configuration is simple, the training time is short and the advantage of high information conversion ratio, and being often selected as is in recent years the good carrier of brain order.So-called Steady State Visual Evoked Potential, when being subject to a visual stimuli that is greater than certain fixed frequency (6Hz), the response at continuous relevant with excitation frequency (fundamental frequency of excitation frequency or the frequency multiplication place) that people's brain visual cortex produces, it can be applied to brain machine interface system reliably.

And one of standard of weighing SSVEP-BCI system performance is exactly the producible command number of this system (being target excitation piece), command number is more, and corresponding performing an action is also more, and system is also more perfect.The most frequently used SSVEP command identifying method is to realize by extracting the frequency information of EEG signals at present ^[5-7], and for the SSVEP signal that adopts LCD (Liquid Crystal Display, liquid crystal display) excitation to produce, because its excitation frequency is to obtain by the refreshing frequency integral frequency divisioil to LCD, thereby its excitation frequency number is restricted; In addition, in the excitation frequency obtaining by integral frequency divisioil at these, certainly exist the excitation frequency that some cannot direct-detection because there is frequency shift (FS) ^[8,9], this just needs to solve this problem by introducing new frequency detecting algorithm (being frequency coding/decoding method).For increasing number of targets, also there is researcher to adopt multi-frequency excitation to carry out SSVEP signal induction, by canonical correlation analysis (CCA) method, extract the feature of signal ^[10,11].But all only laying particular emphasis on by enriching frequency coding, above method increases order number of targets.For the basic command recognition problem solving under finite frequency number, not only to improve frequency coding algorithm, also to improve existing frequency decoding detection algorithm.

In recent years, for improving the performance of brain machine interface system, the concept of frequency plot hybrid coding enters our visual field, and obviously, this behave has improved incentives target number greatly.Due at frequency plot hybrid coding ^[12,13]sSVEP system in, on the basis of frequency coding, increased phase information, thereby required its decode procedure can accurately extract frequecy characteristic, can extract phase characteristic again.As the method for Tsing-Hua University in document [12] proposition, when coding, same excitation frequency is given a plurality of initial phases and increased number of targets, when decoding, by range value and the phase value at the FFT spectrum place, peak in conjunction with SSVEP signal, distinguish different incentives targets; Document [14] is divided into SSVEP Energizing cycle flicker period and silence period, when coding, by being set, different silence period length produces the phase place of sign different target feature, when decoding, consider that all silent segment situations do and cut apart SSVEP response signal, and calculate the time domain average energy of different segmentations, then take these capacity volume variances as the incentives target according to identifying out of phase.

Obviously, document [14] is because decode procedure carries out in time domain, therefore higher to noise sensitivity; The decoding of document [12] directly realizes in FFT frequency domain, but the parameter of the investigation document can be found, its excitation frequency is all chosen for the integral multiple of FFT frequency resolution, and (just in time the frequency deviation of corresponding each excitation frequency is 0, direct FFT is surveyed mutually error free), thereby its incentives target number is still restricted, (same restriction is also present in document [6,10,12,15] in).Why choosing the excitation frequency without frequency deviation, is to cause surveying mutually inaccurate inherent shortcoming in order to get around FFT spectrum leakage under offset frequency situation.Because exist spectrum to leak, even for simple signal, all can there is very large error in the phase value on its peak value spectral line; When signal comprises a plurality of frequency content, each composition leaks between the spectrum causing and disturbs because of spectrum, can further increase and survey phase error ^[16-18].Therefore for improving the frequency efficiency in finite bandwidth, the FFT phase decoding problem of Steady State Visual Evoked Potential while there is frequency deviation in the urgent need to address.

Summary of the invention

The invention provides a kind of frequency plot brain-computer interface coding/decoding method and device thereof of proofreading and correct based on FFT spectrum, the present invention can exist under various drift condition in SSVEP excitation frequency, accurately extracts its just phase information, has high accuracy of identification, described below:

A frequency plot brain-computer interface coding/decoding method of proofreading and correct based on FFT spectrum, said method comprising the steps of:

(1) the Steady State Visual Evoked Potential signal SSVEP gathering is carried out to digital sample, obtain N discrete sample, then discrete sample windowing does fast fourier transform analysis, draw the frequency spectrum X of SSVEP signal _f(k), k=0 ..., N-1;

(2) search out and be positioned at k=k ^*the peak value spectrum X at place _f(k ^*), and record its phase value separately need determine time high spectral position and try to achieve ratio v;

(3) by ratio v value, obtain frequency deviation estimated value based on this, obtain respective phase estimated value

(4) by obtaining two excitation frequency f ₁with f ₂correction after measure phase difference identify incentives target.

Described ratio v is specially:

$v=\frac{\left|X_f\left(k^{*}\right)\right|}{\max \left(\right|X_f(k^{*}+1)|,|X_f(k^{*}-1)\left|\right)}.$

Described frequency deviation estimated value be specially:

$\mathrm{\Δ}\widehat{\mathrm{\β}}=(v-2)/(v+1);$

Described phase estimation value be specially:

Wherein, for the corresponding phase value in peak value place.

Described measure phase difference be specially:

be respectively the time delay phase place under different excitation frequencies, be respectively the excitation phase under different excitation frequencies.

A kind of frequency plot brain-computer interface decoding device of proofreading and correct based on FFT spectrum, described decoding device comprises: analog-to-digital conversion device, DSP device, output drive and display module, the signal x (t) collecting is obtained to sample sequence x (n) through described analog-to-digital conversion device sampling, form with Parallel Digital input enters described DSP device, through the inter-process of described DSP device, obtain the parameter estimation of signal; By described output driving and display module thereof, show the order that experimenter sends again, last order corresponding to external-device response.

The phase extraction method of proofreading and correct based on FFT spectrum that the present invention proposes, if be applied to Practical Project field and clinical medicine domain, can produce following beneficial effect:

Due to the requirement of having relaxed excitation frequency, increased object block quantity, therefore greatly enriched the control operation to environment of living in.

Because phase decoding precision of the present invention is high, therefore be conducive to reduce the misoperation of external device.

Can rapid configuration due to core trimming process of the present invention, therefore be conducive to system upgrade, be applicable to different application demands.

Accompanying drawing explanation

Fig. 1 is the basic comprising block diagram of brain machine interface system;

Fig. 2 is the design general flow chart of the frequency plot brain-computer interface coding/decoding method based on the correction of FFT spectrum;

Fig. 3 is without making an uproar situation lower frequency bias estimation and phase estimation value;

Fig. 4 is for adding make an uproar situation lower frequency bias estimation and phase estimation value;

Fig. 5 is two object block excitation display devices;

Fig. 6 is the hardware implementation figure of the frequency plot brain-computer interface decoding device based on the correction of FFT spectrum;

Fig. 7 is DSP internal processes flow graph.

Embodiment

For making the object, technical solutions and advantages of the present invention clearer, below embodiment of the present invention is described further in detail.

For breaking through this bottleneck, the present invention is on the basis of hybrid frequency phase-difference type energisation mode, frequency of utilization and phase place are carried out hybrid coding to SSVEP signal and are done decoding and process, and have proposed a kind of novel frequency plot brain-computer interface coding/decoding method and the device thereof based on FFT spectrum, proofreaied and correct.The method can be improved SSVEP pumping signal and exist under offset frequency situation because FFT spectrum is leaked and the problem of indeterminacy phase place, accurately calculate corresponding excitation phase value, and identify object block, finally reach the object of relaxing the restriction of target excitation frequency, increase incentives target number.

Fig. 1 is the basic comprising block diagram of brain machine interface system, and brain machine interface system is broadly divided into four ingredients:

(1) by the external world, produce the various current potentials that bring out that comprise different frequency and first phase information (being coded message) and generate pumping signal;

(2) at cortical electrode or scalp electrode, electroneurographic signal is gathered, and carry out hyperchannel amplification, filtering and A/D conversion, complete pre-service;

(3) feature extraction and control command generate: utilize signal to process and algorithm for pattern recognition, extract the characteristic information that brings out current potential, and classify, decode and change, produce the control command corresponding with nervous activity pattern;

(4) utilize the control command producing to handle external environment condition and equipment.

Obviously, in above step, feature extraction is partly of paramount importance link in brain machine interface system, only extracts signal characteristic accurately and expands the identification range of signal characteristic, could raising system discernible number of targets, enrich the external control function of brain-computer interface.

As shown in Figure 2, existing under offset frequency situation as obtaining accurately just phase information of signal, need proofread and correct and ask phase place signal.Its correction decoder process is as follows:

First, need to carry out digital sample to the SSVEP signal gathering, obtain N discrete sample, then this discrete sample windowing is done to fast fourier transform (FFT) analysis, draw the frequency spectrum X of SSVEP signal _f(k), k=0 ..., N-1;

Secondly, for obtaining frequency offseting value, need search out and be positioned at k=k ^*the peak value spectrum X at place _f(k ^*), and record its phase value separately need to determine that (if inferior high spectrum is positioned at left side, spectrum peak, this position is designated as k to time high spectral position ^*-1; If be positioned at spectrum right side, peak, be designated as k ^*+ 1), and try to achieve following ratio v;

$v=\frac{\left|X_f\left(k^{*}\right)\right|}{\max \left(\right|X_f(k^{*}+1)|,|X_f(k^{*}-1)\left|\right)}---\left(1\right)$

Finally, by v value, obtain frequency deviation estimated value based on this, obtain respective phase estimated value be respectively

$\mathrm{\Δ}\widehat{\mathrm{\β}}=(v-2)/(v+1)---\left(2\right)$

In Fig. 2, change in any case the parameters such as excitation frequency, excitation first phase and sampling rate, can obtain fast Frequency Estimation output accurately and phase estimation output.

In formula (3), for the SSVEP after proofreading and correct measures phase place, be not that the excitation phase of SSVEP (is designated as ).As shown in Figure 1, between SSVEP excitation and response, there is the reaction time of human brain, the time delay phase place that the corresponding generation of this brain response delay meeting varies with each individual between this three, meet following relation

Because decoding is according to excitation phase rather than measurement phase place therefore need further to determine time delay phase place

The present invention introduces double frequency SSEVP incentive program, by obtaining two excitation frequency f ₁with f ₂correction after measure phase difference identify incentives target.This phase differential is

In formula (5), as excitation frequency f ₁and f ₂while approaching very much, time delay phase difference value can be ignored, thus target when identification available measure phase difference replace actual phase difference, identify easily target excitation piece.

This experiment is divided into for verifying the emulation experiment of spectrum correction principle and the actual experiment two parts of decoding for SSVEP.

Emulation experiment

In this emulation experiment, burst is { x (n)=acos (ω ₀n+ θ ₀)+w (n), n=0,1 ..., N-1}, a=1 wherein, θ ₀=60 °, N=16, π/16, Δ ω=2, ω ₀=(3+ Δ β) Δ ω.W (n) is 0 average, σ ²the additive white noise of variance, is used for simulating the ground unrest in SSVEP signal.Feasibility for explanation bearing calibration of the present invention, respectively different frequency deviation Δ β situations are done to direct FFT and FFT correction contrast below, make frequency deviation value Δ β take 0.1 as stepping, between 0 to 0.9, change, then try to achieve respectively Frequency Estimation corresponding to these ten offset frequency situation and first phase estimation.

In experiment, signal to noise ratio snr is defined as

$\mathrm{SNR}=10{{\log }_{10}}^{\frac{a^2}{2{\mathrm{\σ}}^2}}---\left(6\right)$

First, without making an uproar in situation, contrasting, Fig. 3 has provided Frequency offset estimation Δ β corresponding to two kinds of methods and phase estimation (wherein directly ' o ' mark for FFT, the estimated value after correction is ' * ').Fig. 3 shows, without making an uproar in situation, directly the estimated frequency error of FFT method is between-0.5 Δ ω～0.5 Δ ω, and error after proofreading and correct is between-0.0039 Δ ω and 0.0032 Δ ω, negligible by contrast.And from phase estimation value angle, the estimated value error range after correction is very little, between-0.6390 °～-0.0009 °, there is very large error in FFT method phase error directly, cannot be used for representing first phase value.

For checking this method is in the correcting feature having in the situation of making an uproar, original signal sequence is added and made an uproar, signal to noise ratio snr is made as 6dB, and corresponding direct FFT contrasts as shown in Figure 4 with after correction.

Fig. 4 (a) shows, when signal to noise ratio snr=6dB, estimated frequency error after correction is all between-0.0259 Δ ω～0.0659 Δ ω, though than increasing to some extent without the situation of making an uproar, the frequency values estimating for direct FFT method still can be similar to and ignore.And phase estimation value is between (14 °～-5 °), also can identify more exactly phase information.

Above nothing make an uproar and have the situation of making an uproar two kinds of simulation results shows feasibility and the accuracy of this bearing calibration, when frequency deviation exists, also can estimate exactly signal frequency and initial phase information.For SSVEP-BCIs, just mean the phase place requirement that can greatly relax excitation frequency, make optional frequency while being necessary for frequency resolution integral multiple (but not) all can be used as excitation frequency, proportion phase place hybrid coding can increase incentives target number greatly.

SSVEP surveys experiment mutually

(1) experimental provision

In this SSVEP-BCI system, survey and test mutually the frequency plot hybrid coding platform of building by University of Macao, and adopt the FFT spectrum means for correcting that the present invention proposes to carry out phase characteristic extraction and target classification identification.Test set sample frequency f _s=600Hz, the display that one 22 inches of experiment needs, refreshing frequency 120Hz, screen resolution are 1680 * 1050, as shown in Figure 5.

SSVEP excitation is to obtain by the line scan signals of this display is done to frequency division.In experiment, indicator screen is divided into two the incentives target pieces in left and right, and each object block is comprised of two sub-piecemeals; During coding, give these two sub-piecemeals with different flicker frequencies and phase place, during decoding, by detecting every pair of phase differential corresponding to object block, determine the target that experimenter watches attentively.

As previously mentioned, because brain response postpones the time delay phase place that can produce, therefore the selection of two excitation frequencies is very important, necessarily require two frequency phase-differences seldom, so just can ignore and offset this time delay phase place.The SSVEP measure phase difference of two object block is expressed as again

In formula (7), if as excitation frequency f ₁and f ₂while approaching very much, time delay phase difference value can ignore, during target identification, available measure phase difference replaces actual phase difference, identifies easily target excitation piece.

And at this SSVEP, survey 10 frequency divisions and 11 frequency divisions that two test frequencies choosing in experiment are mutually respectively refreshing frequency 120Hz, i.e. 12Hz (comprising that two first phases are the excitation of 0 ° and 180 °) and 10.9Hz (comprising that two first phases are the excitation of 0 °).Its corresponding target block excitation frequency and object block frequency coding table are as shown in table 1

Table 1 half-court mixed excitation phase encoding parameters of display table

Obviously, still there is certain intervals in selected two frequencies of table 1, many experiments discovery, at this moment the time delay phase difference value of two excitation frequencies relatively be fixed as 36 °, so need on the basis of measure phase difference, deduct 36 ° of ability during practical application and identify more accurately object block.

(2) experimentation and result

Three experimenters (S1, S2, S3) are encouraged to induction, gather 13 electrode positions (PO3, PO5, PO7, POZ, PO4, PO6, PO8, P1, O1, OZ and O2) the SSVEP signal that produces, signal connects USB interface record by Electroencephalo signal amplifier, and sample frequency is 600Hz.This experiment collection EEG signals is divided into 5 and takes turns, and each is taken turns and comprises 10 collections.Each excitation Therapy lasted 8 seconds, in whole process, experimenter requires to focus one's attention on, and wherein encourages first 2 seconds for setup time, within latter 6 seconds, require experimenter to watch as requested corresponding flicker excitation block attentively, watch order attentively and hocket according to ' 1212121212 '.

Obviously, can obtain frequency resolution Δ f=f _s/ N=1/6Hz, excitation frequency 12/ Δ f=72, is integral multiple just, and 10.9Hz/ Δ f=65.4545, for non-integral multiple, therefore, if adopt direct FFT to survey phase, will inevitably cause surveying the inaccurate of phase.Therefore the FFT method that adopts windowing and proofread and correct is surveyed phase.

At this, survey in experiment mutually, be mainly divided into following step:

Step1: to use respectively two kinds of different schemes (directly FFT surveys phase scheme and FFT correcting scheme) working frequency and phase estimation through pretreated SSVEP signal, obtain two groups and survey value mutually

Step2: ask for the measure phase difference value estimating in step 1 be used for replacing actual phase difference

Step3: phase difference value is asked in substitution (7)

Step4: differentiate with the phase difference value that the criterion shown in formula (8) is calculated Step3, to determine object block p;

In formula (8), M is number of targets, C _kfor corresponding desirable cluster centre.Therefore only need be from R while judging the classification of this object block ₁to R _min find out maximal value p and (seek R _kvalue is close to 1 o'clock corresponding k value), be identified object block label.

(classification is two classes (excitation blocks 1 and 2) to use respectively two schemes (directly FFT method and bearing calibration) to carry out frequency plot identification classification to SSVEP signal, M=2), table 2 provides different experimenters is added to the target recognition accuracy that different length hanning window obtains.

The long different experimenters' of table 2 different window target recognition accuracy

In table 2, C_FFT represents FFT spectrum correction method, and FFT is direct method.Be not difficult to find, the accuracy rate of target identification is not only long relevant with window, also with employing method have much relations, through the accuracy rate of overcorrect, apparently higher than direct FFT method, Average Accuracy exceeds more than 10%.

Choosing window length is below 4 seconds, and number of targets M is set to 4, supposes that corresponding phase place is respectively 0 °, 90 °, 180 °, 270 °, again SSVEP signal is processed by two kinds of methods, and the accuracy rate result of contrast target identification is as shown in the table:

The different experimenters' of table 3 estimation phase place and feature identification R _k(means standard deviation)

As known from Table 3, identification incentives target piece only need be found out R ₁, R ₂, R ₃and R ₄in approach 1 value most.

(1) the direct FFT that is 10.9Hz for excitation frequency surveys phase situation, and the situation of not proofreading and correct, because excitation frequency 10.9Hz is not the integral multiple of frequency resolution, from table 3 the 2nd row data can be clear that and can have very large deviation (desirable first phase value is 0 °, and actual survey is worth mutually deviation maximum and approaches 90 °) to survey phase average that should frequency.

(2) the survey phase situation that the introducing FFT that is 10.9Hz for excitation frequency proofreaies and correct, although excitation frequency 10.9Hz is not the integral multiple of frequency resolution, from table 3 the 2nd row data can be clear that survey phase average that should frequency is only existed to less deviation (desirable first phase value is 0 °, and actual survey is worth mutually deviation and is substantially no more than 30 °).

(3) for excitation frequency, be that 12Hz surveys phase situation, because excitation frequency 12Hz is the integral multiple of resolution just, do not have frequency deviation, from table 3 the 1st row data can be clear that the survey phase effect of two schemes is about the same, all relatively accurately (desirable average is 0 ° and 180 °, near all distributions among a small circle these two desirable averages of the phase place of surveying).

(4) from table 3 the 1st row with the 2nd row also can find out, its standard deviation of surveying phase data all distributes among a small circle near 36 °, has verified 36 ° of correctness that brain time delay phase is poor of establishing in advance.

(5) observe classification results R in table 3 _k(k=1,2,3,4, M=4) corresponding p value (in table 5, the R of every row maximum _kvalue has been done mark with shade, corresponding k value is target p), because in this M=4 imaginary object block, corresponding to the object block of k=2 and the object block of k=4, suppose, only corresponding to the object block (being the object block of corresponding j=1) of k=1 and the object block (being the object block of corresponding j=2) of k=3, be only possible excitation, therefore p value during correct target identification also should be limited to p=1 and two kinds of situations of p=3, and its error probability is wanted greatly during than M=2.The decode measured value of corresponding p=1 and p=3 of the C_FFT that is not difficult find to introduce to proofread and correct is all surveyed phase decoder situation higher than direct FFT, therefore than direct FFT method, the inventive method is more reliable.

In a word, from above-mentioned emulation experiment, can find out, the FFT spectrum correction method that the present invention proposes can, the in the situation that of any frequency deviation, extract the phase information of signal rapidly by carrying out calibration accuracy; SSVEP survey contrasts experiment and has also confirmed that the method can, for projects, realize the target identification of brain-computer interface completely exactly.

Referring to Fig. 6, the frequency plot brain-computer interface decoding device of proofreading and correct based on FFT spectrum, by the signal x (t) collecting, through A/D (analog-to-digital conversion device), sampling obtains sample sequence x (n), form with Parallel Digital input enters DSP device, internal algorithm through DSP device is processed, and obtains the parameter estimation of signal; Relend and help output driving and display module thereof to show the order that experimenter sends, last order corresponding to external-device response.

Wherein, the DSP of Fig. 7 (Digital Signal Processor, digital signal processor) is core devices, in signal parameter estimation procedure, completes following major function:

(1) call core algorithm, the parameter estimation that completes collection signal is processed (Frequency Estimation and phase estimation);

(2) signal is carried out to FFT Spectrum Correction, by phase estimation result substitution discriminant, carry out object block identification and send the corresponding command exporting in real time driving and display module to.

Need point out, owing to having adopted digitized method of estimation, thereby determined the complexity of Fig. 6 decoding device, in real time the principal element of degree and degree of stability is not that the periphery of DSP device in Fig. 6 is connected, but the kernel estimation algorithm that the program storage of DSP device inside is stored.

The internal processes flow process of DSP device as shown in Figure 7.

The present invention implants proposed " FFT Spectrum Correction algorithm " this kernel estimation algorithm in DSP device, based on this, completes high precision, low complex degree, efficient phase estimation.

Fig. 7 flow process is divided into following several step:

(1) first need according to concrete application requirements, the sampling number N of signalization and the number of times i of duplicate measurements, and setting accuracy requirement according to specific needs.

This step is from engineering aspect, to propose real needs, so that follow-up flow process is processed targetedly.

(2) then, the CPU primary controller in DSP device, from I/O port reads sampled data, enters internal RAM.

(3) follow-up " DC processing " is in order to eliminate the impact of the flip-flop in measured signal.Otherwise the existence of flip-flop, can reduce measuring accuracy.Flip-flop is easy to measure, and only needs the mean value that calculates sampling point to obtain.

(4) by Fig. 2 processing procedure of the present invention, carry out FFT Spectrum Correction and estimate that phase value is the most crucial part of DSP algorithm, move after this algorithm, can obtain phase measurement.

(5) judge whether this method satisfies the demands, if do not meet, program is returned, and again sets as requested sample frequency and carries out next round phase measurement and sort out identification.

(6) until identification target is correct, can send correct control command.Repeat above measuring process i time.

(7) output bus by DSP exports outside display drive device to, and command instruction is passed to external unit.As the switch of controlling TV with adjust platform, control electric fan wind-speed gear, control seesawing of wheelchair etc.

Need point out, owing to having adopted DSP device to realize, make whole parameter estimation operation become more flexible, the concrete condition of the various components that can comprise according to signal, the inner parameter that changes algorithm by flexible in programming arranges, as sampling number N, sample rate f _sdeng.

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The embodiment of the present invention to the model of each device except do specified otherwise, the model of other devices does not limit, as long as can complete the device of above-mentioned functions, all can.

It will be appreciated by those skilled in the art that accompanying drawing is the schematic diagram of a preferred embodiment, the invention described above embodiment sequence number, just to describing, does not represent the quality of embodiment.

The foregoing is only preferred embodiment of the present invention, in order to limit the present invention, within the spirit and principles in the present invention not all, any modification of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.

Claims (5)

1. a frequency plot brain-computer interface coding/decoding method of proofreading and correct based on FFT spectrum, is characterized in that, said method comprising the steps of:

(1) the Steady State Visual Evoked Potential signal SSVEP gathering is carried out to digital sample, obtain N discrete sample, to discrete sample, fast fourier transform analysis is done in windowing, draws the frequency spectrum X of SSVEP signal _f(k), k=0 ..., N-1;

(2) search out and be positioned at k=k ^*the peak value spectrum X at place _f(k ^*), and record its phase value separately need determine time high spectral position and try to achieve ratio v;

(3) by ratio v value, obtain frequency deviation estimated value based on this, obtain respective phase estimated value

(4) by obtaining two excitation frequency f ₁with f ₂correction after measure phase difference identify incentives target.

2. a kind of frequency plot brain-computer interface coding/decoding method of proofreading and correct based on FFT spectrum according to claim 1, is characterized in that, described ratio v is specially:

$v=\frac{\left|X_f\left(k^{*}\right)\right|}{\max \left(\right|X_f(k^{*}+1)|,|X_f(k^{*}-1)\left|\right)}.$

3. a kind of frequency plot brain-computer interface coding/decoding method of proofreading and correct based on FFT spectrum according to claim 1, is characterized in that described frequency deviation estimated value be specially:

$\mathrm{\Δ}\widehat{\mathrm{\β}}=(v-2)/(v+1);$

Described phase estimation value be specially:

Wherein, for the corresponding phase value in peak value place.

4. a kind of frequency plot brain-computer interface coding/decoding method of proofreading and correct based on FFT spectrum according to claim 1, is characterized in that described measure phase difference be specially:

Wherein, be respectively the time delay phase place under different excitation frequencies, be respectively the excitation phase under different excitation frequencies.

5. a frequency plot brain-computer interface decoding device of proofreading and correct based on FFT spectrum, described decoding device comprises: analog-to-digital conversion device, DSP device, output drive and display module, it is characterized in that,

The signal x (t) collecting is obtained to sample sequence x (n) through described analog-to-digital conversion device sampling, and the form of inputting with Parallel Digital enters described DSP device, through the inter-process of described DSP device, obtains the parameter estimation of signal; By described output driving and display module thereof, show the order that experimenter sends again, last order corresponding to external-device response.