CN103995799B - 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 based on FFT spectrum correction and its device

Technical field

The present invention relates to digital processing field, more particularly, to a kind of connect based on the frequency plot brain machine of FFT spectrum correction Mouth coding/decoding method and its device, the frequency of the brain-computer interface device pumping signal to the steady-state induced current potential of view-based access control model for the present invention is deposited In frequency deviation, phase information is extracted by FFT spectrum correction method and realizes order decoding.

Background technology

Brain-computer interface^[1](Brain-Computer Interface, be abbreviated as BCI) be human brain and computer or other A kind of direct communication and control passage set up between electronic equipment, it does not rely on the normal output channel of brain (peripheral neverous system and musculature), is a kind of brand-new communication and control mode^[2].It is intended to set up human brain and the external world Directly communication channel, identifies that by extracting the feature of EEG signals brain instructs, is finally completed brain to external equipment Directly control.

The main purpose of research brain-computer interface technology is the control device designed based on EEG signals, to realize and outside The exchange of environment and control^[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, is abbreviated as SSVEP)^[4]Because having the non-property invaded, system configuration is simple, the conversion of training time short and its high information The advantage of rate, being often selected as in recent years is the good carrier of brain order.So-called Steady State Visual Evoked Potential, that is, when by one More than certain fixed frequency (6Hz) visual stimuli when, produce one is continuously had with driving frequency for the brain visual cortex of people Close the response of (at the fundamental frequency of driving frequency or frequency multiplication), it can be to reliably applied to brain machine interface system.

And weighing one of standard of SSVEP-BCI systematic function is exactly this system producible command number (i.e. target excitation Block), command number is more, and corresponding execution action is also more, and system is also more perfect.SSVEP command recognition side the most frequently used at present Method is to be realized by extracting the frequency information of EEG signals^[5-7], and for using LCD (Liquid Crystal Display, liquid crystal display) the SSVEP signal that produces of excitation, because its driving frequency is by whole to the refreshing frequency of LCD Number frequency dividing obtains, thus its driving frequency number is restricted；In addition, the driving frequency being obtained by integral frequency divisioil at these In, certainly exist some because there is frequency shift (FS) and cannot direct detection driving frequency^[8,9], this is accomplished by new by introducing Frequency detecting algorithm (i.e. frequency coding/decoding method) solving this problem.For increasing number of targets, researcher is also had to employ multifrequency Rate excitation carries out SSVEP signal induction, extracts the feature of signal by canonical correlation analysis (CCA) method^[10,11].But with top Method all only lays particular emphasis on increases order number of targets by abundant frequency coding.For the basic command recognition solving under finite frequency number Problem, not only will improve frequency coding algorithm, also will 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, Obviously, this behave substantially increases incentives target number.Due in frequency plot hybrid coding^[12,13]SSVEP system in, Increased phase information on the basis of frequency coding, thus require its decoding process can accurately extract frequecy characteristic, can carry again Take phase property.The method proposing in document [12] as Tsing-Hua University, gives multiple initial in coding to same driving frequency Phase place and increased number of targets, decoding when then by the FFT spectral peak with reference to SSVEP signal at range value and phase value come area Divide different incentives targets；SSVEP Energizing cycle is then divided into flicker period and silence period by document [14], in coding, Produce the phase place of mark different target feature by arranging different silence period length, in decoding, then consider all quiet Silent segmentation situation is done to SSVEP response signal and is split, and calculates the time domain average energy of different segmentations, then with these energy differences Different is according to identifying the incentives target of out of phase.

Obviously, document [14] is carried out in the time domain due to decoding process, therefore higher to noise sensitivity；Document [12] Decoding be directly realized by FFT frequency domain, but investigation the document parameter can find, its driving frequency is all chosen for The integral multiple (frequency deviation just corresponding to each driving frequency is 0 so that direct FFT survey is mutually error free) of FFT frequency resolution, thus Its incentives target number is still restricted (same restriction exists in document [6,10,12,15]).Why choose no frequency deviation Driving frequency, is to lead to survey mutually inaccurate inherent shortcoming around being opened under offset frequency situation FFT spectrum leakage.Because there is spectrum to let out Leakage, even for simple signal, all can there is very big error in the phase value on its peak value spectral line；Become when signal comprises multiple frequencies Timesharing, disturbs between the spectrum that each composition leads to because of spectrum leakage, then can increase survey phase error further^[16-18].Therefore have for raising Frequency efficiency in limit bandwidth, the FFT phase decoding problem that there is Steady State Visual Evoked Potential during frequency deviation in the urgent need to address.

Content of the invention

The invention provides a kind of frequency plot brain-computer interface coding/decoding method based on FFT spectrum correction and its device, this Bright can exist under various drift condition in SSVEP driving frequency, accurately extract its just phase information, have high accuracy of identification, Described below：

A kind of frequency plot brain-computer interface coding/decoding method based on FFT spectrum correction, the method comprising the steps of：

(1) digital sample is carried out to the Steady State Visual Evoked Potential signal SSVEP of collection, obtain N number of discrete sample, then from Scattered sample adding window makees FFT analysis, draws the frequency spectrum X of SSVEP signal_f(k), k=0 ..., N-1；

(2) search out positioned at k=k^*The peak value spectrum X at place_f(k^*), and record its phase valueSecond highest spectral position separately need to be determined And try to achieve ratio v；

(3) offset estimation value is worth to by ratio vRespective phase estimate is obtained based on this

(4) by obtaining two driving frequencies f₁With f₂Correction after measurement phase differenceSharp to identify Encourage target.

Described ratio v is specially：

Described offset estimation valueIt is specially：

Described phase estimation valueIt is specially：

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

Described measurement phase differenceIt is specially：

It is respectively the delay phase under different driving frequencies,It is respectively different sharp Encourage the excitation phase under frequency.

A kind of frequency plot brain-computer interface decoding apparatus based on FFT spectrum correction, described decoding apparatus include：Analog-to-digital conversion Device, DSP device, output driving and its display module, signal x (t) collecting is obtained through the sampling of described analog-to-digital conversion device Sample sequence x (n), enters described DSP device in the form of Parallel Digital input, through the inter-process of described DSP device, obtains Parameter Estimation to signal；Show the order that experimenter sends by described output driving and its display module again, finally outside Equipment responds corresponding order.

Phase extraction method based on FFT spectrum correction proposed by the present invention, if be applied to Practical Project field and clinical doctor Field, can produce following beneficial effect：

Due to relaxing the requirement to driving frequency, increased target number of blocks, therefore greatly enriched to local environment Control operation.

Due to the phase decoding high precision of the present invention, therefore advantageously reduce the operational error of external device.

Core trimming process due to the present invention with rapid configuration, therefore can be conducive to system upgrade it is adaptable to different should Use demand.

Brief description

Fig. 1 is the basic composition 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 FFT spectrum correction；

Fig. 3 is Frequency offset estimation and phase estimation value in the case of nothing is made an uproar；

Fig. 4 is plus Frequency offset estimation and phase estimation value in the case of making an uproar；

Fig. 5 is two object block excitation display devices；

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

Fig. 7 is DSP internal processes flow graph.

Specific embodiment

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

For breaking through this bottleneck, the present invention on the basis of hybrid frequency phase-difference type energisation mode, usage frequency and phase Position carries out hybrid coding and makees decoding process it is proposed that a kind of new frequency plot based on FFT spectrum correction to SSVEP signal Brain-computer interface coding/decoding method and its device.The method can be improved SSVEP pumping signal and exist under offset frequency situation because FFT spectrum is let out Leakage and the problem of indeterminacy phase place, accurately calculate corresponding excitation phase value, and identify object block, be finally reached relax right The restriction of target excitation frequency, the purpose of increase incentives target number.

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

(1) the various Evoked ptential generation excitations comprising different frequency and first phase information (i.e. coding information) are produced by extraneous Signal；

(2) in cortical electrode or scalp electrode, electroneurographic signal is acquired, and carries out multichannel amplification, filtering and A/ D changes, and completes to pre-process；

(3) feature extraction and control command generate：Utilize signal transacting and algorithm for pattern recognition, extract Evoked ptential Characteristic information, and classified, decoded and changed, produced the control command corresponding with nervous activity pattern；

(4) external environment condition and equipment are manipulated using the control command producing.

Obviously, in above step, feature extraction unit is divided into of paramount importance link in brain machine interface system, only extracts Accurately signal characteristic expand the identification range of signal characteristic, could improve the discernible number of targets of system, abundant brain machine connects The external control function of mouth.

As shown in Fig. 2 being to obtain accurate signal just phase information under there is offset frequency situation, need to signal be corrected asking Phase place.Its correction decoder process is as follows：

Firstly, it is necessary to digital sample is carried out to the SSVEP signal of collection, obtain N number of discrete sample, then to this discrete sample Adding window makees FFT (FFT) analysis, draws the frequency spectrum X of SSVEP signal_f(k), k=0 ..., N-1；

Secondly, for obtaining frequency offseting value, need to search out positioned at k=k^*The peak value spectrum X at place_f(k^*), and record its phase valueSeparately need to determine that (if second highest spectrum is located on the left of spectral peak, this position is designated as k to second highest spectral position^*-1；If being located on the right side of spectral peak, remember For k^*, and try to achieve following ratio v+1)；

Finally, offset estimation value is worth to by vRespective phase estimate is obtained based on thisIt is respectively

In Fig. 2, change driving frequency, the excitation parameter such as first phase and sampling rate in any case, can quickly obtain standard True Frequency Estimation output and phase estimation output.

In formula (3),For the SSVEP measurement phase place after correction, it is not that the excitation phase of SSVEP (is designated as).As figure Between SSVEP excitation and response, shown in 1, there is the reaction time of human brain, this brain response delay can accordingly produce because of people Different delay phaseFollowing relation is met between this three

Because decoding is according to excitation phaseRather than measurement phase placeIt is thus desirable to further determining that delay phase

Present invention introduces double frequency SSEVP incentive program, by obtaining two driving frequencies f₁With f₂Correction after measurement phase Potential differenceTo identify incentives target.This phase difference is

In formula (5), when driving frequency f₁And f₂Very close to when, delay phase difference is negligible, therefore target identification when Then can use measurement phase difference to replace actual phase difference, easily identify target excitation block.

This experiment is divided into the emulation experiment for checking spectrum correction principle and the actual experiment two for SSVEP decoding Point.

Emulation experiment

In this emulation experiment, burst is { x (n)=a cos (ω₀n+θ₀)+w (n), n=0,1 ..., N-1 }, wherein a =1, θ₀=60 °, N=16, Δ ω=2 π/16, ω₀=(3+ Δ β) Δ ω.W (n) is 0 average, σ²The additive white noise of variance, It is used for simulating the ambient noise in SSVEP signal.The feasibility of bearing calibration to illustrate the invention, separately below to different frequency deviations Δ β situation makees direct FFT and FFT correction comparison, makes frequency deviation value Δ β with 0.1 as stepping, changes, then distinguish between 0 to 0.9 Try to achieve this corresponding Frequency Estimation of ten offset frequency situation and first phase is estimated.

In experiment, signal to noise ratio snr is defined as

First, compareed in the case of nothing is made an uproar, Fig. 3 gives two methods corresponding Frequency offset estimation Δ β and phase Position estimates (wherein directly FFT is marked, and the estimate after correction is ' × ') with ' o '.Fig. 3 shows, in the case of nothing is made an uproar, directly The estimated frequency error of FFT method between -0.5 Δ ω～0.5 Δ ω, and the error after correcting between -0.0039 Δ ω and Between 0.0032 Δ ω, it is negligible by contrast.And the estimate error from the point of view of phase estimation value angle, after correction Scope very little, between -0.6390 °～-0.0009 °, and then very big error, no in direct FFT method phase error Method is used for representing first phase value.

There iing the correction performance in the case of making an uproar for checking this method, original signal sequence added and makes an uproar, signal to noise ratio snr is set to 6dB, Corresponding direct FFT compares as shown in Figure 4 with after correction.

Fig. 4 (a) shows, in signal to noise ratio snr=6dB, the estimated frequency error after correction be respectively positioned on -0.0259 Δ ω～ Between 0.0659 Δ ω, though having increased compared to situation of no making an uproar, the frequency values estimating for direct FFT method still may be used Approximately ignore.And phase estimation value, between (- 14 °～-5 °), also can accurately identify phase information.

Above nothing is made an uproar and is had two kinds of simulation results shows feasibility of this bearing calibration and the accuracy of the situation of making an uproar, in frequency Also signal frequency and original phase information can be estimated exactly in the presence of partially.It is meant that can for SSVEP-BCIs Significantly to relax the phase requirements to driving frequency so that optional frequency (rather than when being necessary for frequency resolution integral multiple) all may be used As driving frequency, incentives target number can be greatly increased using frequency plot hybrid coding.

SSVEP surveys and mutually tests

(1) experimental provision

In this SSVEP-BCI system, survey and mutually test the frequency plot hybrid coding platform built by University of Macao, and Carry out phase property using FFT proposed by the present invention spectrum means for correcting to extract and target classification identification.The set sampling of experiment Frequency f_s=600Hz, one 22 inches of experiment needs, refreshing frequency 120Hz, screen resolution are 1680 × 1050 display, As shown in Figure 5.

SSVEP excitation is to be obtained by doing frequency dividing to the line scan signals of this display.In experiment, indicator screen is divided into The two incentives target blocks in left and right, each object block is made up of two sub-piecemeals；During coding, give this two sub-piecemeals with different Flicker frequency and phase place, during decoding, determine, by detecting the corresponding phase difference of each pair object block, the target that experimenter watches attentively.

As previously described, because the delay phase that brain response delay can produce, therefore the selection of two driving frequencies is very Important must be requested that two frequency phase-differences seldom, so just negligible this delay phase of counteracting.SSVEP by two object block Measurement phase difference is expressed as again

In formula (7), if working as driving frequency f₁And f₂Very close to when, delay phase differenceIt is negligible, Then can use measurement phase difference to replace actual phase difference during target identification, easily identify target excitation block.

And this SSVEP survey mutually test in choose two test frequencies be respectively refreshing frequency 120Hz 10 frequency dividing and 11 frequency dividings, i.e. 12Hz (two first phases of inclusion are the excitation of 0 ° and 180 °) and 10.9Hz (two first phases of inclusion are 0 ° of excitation). Its corresponding target block driving frequency and object block frequency coding table are as shown in table 1

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

Obviously, selected two frequencies of table 1 still suffer from certain intervals, and many experiments find, at this moment the prolonging of two driving frequencies When phase difference valueBe relatively fixed as 36 °, therefore practical application when need to measurement phase difference on the basis of deduct 36 ° Object block could more accurately be identified.

(2) experimentation and result

Three experimenters (S1, S2, S3) are entered with row energization induce, 13 electrode positions of collection (PO3, PO5, PO7, POZ, PO4, PO6, PO8, P1, O1, OZ and O2) the SSVEP signal that produces, signal connects USB interface note by Electroencephalo signal amplifier Record, sample frequency is 600Hz.This experiment collection EEG signals is divided into 5 wheels, and each wheel comprises 10 collections.Encourage every time Therapy lasted 8 seconds, in whole process, experimenter requires and focuses on, and wherein encouraging first 2 seconds is time, latter 6 seconds Then require experimenter to watch corresponding flicker excitation block as requested attentively, watch order attentively according to ' 1212121212 ' alternately.

Obviously, frequency resolution Δ f=f can be obtained_s/ N=1/6Hz, driving frequency 12/ Δ f=72, exactly integral multiple, And 10.9Hz/ Δ f=65.4545, it is non-integral multiple, therefore, surveys phase according to direct FFT, then inevitably result in survey phase not Accurately.Therefore using adding window and the FFT method that corrects carries out surveying phase.

In this is surveyed and mutually tests, it is broadly divided into following step：

Step1：SSVEP signal through pretreatment is used respectively two kinds of different schemes (direct FFT survey phase scheme with FFT correcting scheme) working frequency and phase estimation, obtain two groups of surveys and be mutually worth

Step2：Ask for the measurement phase difference value estimating in step 1It is used for replacing actual phase difference

Step3：Substitute into (7) and ask for phase difference value

Step4：With the criterion shown in formula (8), the phase difference value that Step3 calculates is differentiated, to determine object block p；

In formula (8), M is number of targets, C_kFor preferable cluster centre accordingly.Only need during the classification therefore judging this object block From R₁To R_MIn find out maximum p and (seek R_kValue is closest to k value corresponding when 1), the object block label as being identified.

Carry out frequency plot with two schemes (direct FFT method and bearing calibration) to SSVEP signal respectively to identify and sort out (classification is two classes (excitation block 1 and 2), M=2), table 2 is given and different experimenters is added with the mesh that different length hanning window obtains Mark recognition accuracy.

The target identification accuracy rate of table 2 different window length difference experimenter

In table 2, C_FFT represents FFT spectrum correction method, and FFT is direct method.It is seen that, the accuracy rate of target identification is not Only relevant with window length, also with much relations are had using method, corrected accuracy rate apparently higher than direct FFT method, put down All accuracys rate exceed more than 10%.

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

The estimation phase place of the different experimenter of table 3 and feature recognition R_k(means standard deviation)

As known from Table 3, identification incentives target block only need to find out R₁, R₂, R₃And R₄In closest to 1 value.

(1) for driving frequency, the direct FFT for 10.9Hz surveys phase situation, and situation about not correcting, due to driving frequency 10.9Hz is not the integral multiple of frequency resolution, from table 3 the 2nd rowData it may be clearly seen that to should frequency Survey phase average and can there is very big deviation (preferable first phase value is 0 °, and actual survey is mutually worth deviation maximum close to 90 °).

(2) driving frequency is introduced to the survey phase situation of FFT correction for 10.9Hz, although driving frequency 10.9Hz is not The integral multiple of frequency resolution, from table 3 the 2nd rowData it may be clearly seen that to should frequency survey phase average only Only exist less deviation (preferable first phase value is 0 °, and actual survey is mutually worth substantially no more than 30 ° of deviation).

(3) for 12Hz, phase situation is surveyed for driving frequency, because driving frequency 12Hz is exactly the integral multiple of resolution ratio, that is, There is not frequency deviation, from table 3 the 1st rowData it may be clearly seen that the survey phase effect of two schemes is about the same, all than Relatively accurately (preferable average is 0 ° and 180 °, all small range distributions near this two preferable averages of surveyed phase place).

(4) arrange from table 3 the 1stWith the 2nd rowIt is also seen that the standard deviation of its survey phase data is all attached at 36 ° Nearly small range distribution, demonstrates the correctness of the 36 ° of brain time delay phase differences setting 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 often maximum R of row_kValue It is marked with shade, corresponding k value is target p), because in this M=4 imaginary object block, corresponding to the mesh of k=2 The object block of mark block and k=4 assumes that, only corresponds to the object block (corresponding to the object block of j=1) of k=1 and k=3 Object block (corresponding to the object block of j=2) is only possible excitation, therefore p value during correct target identification also should be limited to p=1 With two kinds of situations of p=3, and its error probability is big compared to during M=2.It is seen that the C_FFT decoding introducing correction is corresponding The measured value of p=1 and p=3 is above direct FFT and surveys phase decoder situation, therefore compared to direct FFT method, the inventive method is more Reliable.

In a word, can be seen that FFT spectrum correction method proposed by the present invention from above-mentioned emulation experiment can be in any frequency deviation In the case of, by being corrected quickly and accurately extracting the phase information of signal；SSVEP survey contrasts experiment and also demonstrate that this Method can be completely used for projects, realizes the target identification of brain-computer interface exactly.

Referring to Fig. 6, based on the frequency plot brain-computer interface decoding apparatus of FFT spectrum correction, by signal x (t) collecting warp Cross A/D (analog-to-digital conversion device) sampling and obtain sample sequence x (n), enter DSP device in the form of Parallel Digital input, through DSP The internal algorithm of device is processed, and obtains the parameter Estimation of signal；Relend and help output driving and its display module display experimenter to send out The order going out, the corresponding order of last external-device response.

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

(1) call core algorithm, the parameter Estimation completing to gather signal processes (Frequency Estimation and phase estimation)；

(2) FFT spectrum correction is carried out to signal, phase estimation result is substituted into discriminate, carry out object block identification concurrent Go out the corresponding command to export in real time to driving and display module.

It may be noted that due to employing digitized method of estimation, thus determine the complexity, in real time of Fig. 6 decoding apparatus The principal element of degree and stability is not the periphery connection of DSP device in Fig. 6, but the program storage of DSP device inside The kernel estimation algorithm that device is stored.

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

" the FFT spectrum correcting algorithm " that proposed this kernel estimation algorithm is implanted in DSP device by the present invention, based on this Complete high accuracy, low complex degree, efficient phase estimation.

Fig. 7 flow process is divided into several steps as follows：

(1) need first to be required according to concrete application, the sampling number N of the signal and number of times i of duplicate measurements is set, and according to Specifically need setting accuracy requirement.

This step is proposition real needs in terms of engineering, so that follow-up process is targetedly processed.

(2) and then, the CPU main controller in DSP device from I/O port read sampled data, enter internal RAM.

(3) follow-up " DC processing ", is the impact in order to eliminate the flip-flop in measured signal.Otherwise, direct current The presence of composition, can reduce certainty of measurement.Flip-flop is easy to measure it is only necessary to the mean value calculating sampling point can get.

(4) carry out FFT spectrum correction by the processing procedure of Fig. 2 present invention and estimate that phase value is the most crucial portion of DSP algorithm Point, after running this algorithm, you can obtain phase measurement.

(5) judging whether this method meets demand, if being unsatisfactory for, program returns, again setting sample frequency as requested Carry out next round phase measurement and sort out identification.

(6) until identification target is correct, correct control command can be sent.Repeat above measurement process i time.

(7) exported to outside display drive device by the output bus of DSP, command instruction is passed to external equipment.As Control the switch of TV and adjust platform, control the wind-speed gear of electric fan, control moving forward and backward of wheelchair.

It may be noted that realizing so that whole parameter estimation operation becomes more flexible due to employing DSP device, can basis The concrete condition of the various components that signal is comprised, changes the inner parameter setting of algorithm, such as sampling number by flexible in programming N, sample rate f_sDeng.

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To the model of each device in addition to doing specified otherwise, the model of other devices is not limited the embodiment of the present invention, As long as the device of above-mentioned functions can be completed.

It will be appreciated by those skilled in the art that accompanying drawing is the schematic diagram of a preferred embodiment, the embodiments of the present invention Sequence number is for illustration only, does not represent the quality of embodiment.

The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all spirit in the present invention and Within principle, any modification, equivalent substitution and improvement made etc., should be included within the scope of the present invention.

Claims (3)

1. a kind of based on FFT spectrum correction frequency plot brain-computer interface coding/decoding method it is characterised in that methods described include following Step：

(1) digital sample is carried out to the Steady State Visual Evoked Potential signal SSVEP of collection, obtain N number of discrete sample, to discrete sample This adding window makees FFT analysis, draws the frequency spectrum X of SSVEP signal_f(k), k=0 ..., N-1；

(2) search out positioned at k=k^*The peak value spectrum X at place_f(k^*), and record its phase valueSecond highest spectral position separately need to be determined and ask Obtain ratio v；

(3) offset estimation value is worth to by ratio vRespective phase estimate is obtained based on this

(4) by obtaining two driving frequencies f₁With f₂Correction after measurement phase differenceTo identify excitation mesh Mark；

Wherein, described ratio v is specially：

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

Wherein, described offset estimation valueIt is specially：

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

Wherein, described phase estimation valueIt is specially：

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

2. a kind of frequency plot brain-computer interface coding/decoding method based on FFT spectrum correction according to claim 1, its feature exists In described measurement phase differenceIt is specially：

Wherein,It is respectively the delay phase under different driving frequencies,It is respectively different sharp Encourage the excitation phase under frequency.

3. a kind of solution for implementing the frequency plot brain-computer interface coding/decoding method based on FFT spectrum correction described in claim 1 Code device, described decoding apparatus include：Analog-to-digital conversion device, DSP device, output driving and its display module it is characterised in that

Signal x (t) collecting is obtained sample sequence x (n) through the sampling of described analog-to-digital conversion device, with Parallel Digital input Form enters described DSP device, through the inter-process of described DSP device, obtains the parameter Estimation of signal；Again by described defeated Go out to drive and its display module shows the order that sends of experimenter, the corresponding order of last external-device response.