CN102789441A - Asynchronous brain-computer interface system based on steady state evoked potential and method for realizing asynchronous brain-computer interface system - Google Patents
Asynchronous brain-computer interface system based on steady state evoked potential and method for realizing asynchronous brain-computer interface system Download PDFInfo
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- CN102789441A CN102789441A CN2012102807961A CN201210280796A CN102789441A CN 102789441 A CN102789441 A CN 102789441A CN 2012102807961 A CN2012102807961 A CN 2012102807961A CN 201210280796 A CN201210280796 A CN 201210280796A CN 102789441 A CN102789441 A CN 102789441A
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Abstract
The invention provides an asynchronous brain-computer interface system based on steady state evoked potential and a method for realizing the asynchronous brain-computer interface system, wherein a stimulator, a task prompter, a signal collector, a signal processor and an output result and feedback device form a test system part of the system; and the stimulator, the signal collector, the signal processor and a control command conversion interface additionally form a control system part of the system. The steady state evoked potential signal of the brain which is induced by the stimulator is collected, is converted into a corresponding command, and is compared with a task prompt signal, and a result is fed back to a tested person; the asynchronous brain-computer interface system can further convert the command into a control command which can control external equipment; and the asynchronous brain-computer interface system facilitates system test, has high steady state evoked potential conversion rate and fast speed, and can be generally suitable for various applications.
Description
Technical field
The invention belongs to a kind of eeg signal classification processing scheme and the system design scheme of biomedical engineering, computer realm, particularly a kind of asynchronous brain machine interface system and its implementation based on steady-state induced current potential.
Background technology
In recent years, the brain-computer interface technology receives much concern.Brain-computer interface (BCI) is a kind of man machine interface's technology that directly people's electrical activity of brain mode switch is become the novelty of external control order, and the information of delivering to the external world under this technology is not through normal nervus peripheralis of brain and muscle output pathway with order.The BCI system can help the patient who suffers from paralysis, apoplexy to express their wish to the nurse personnel, even can control extraneous utility appliance and accomplish daily routines.Asynchronous BCI can make the individual go control according to the wish of oneself, is the developing direction of following BCI.
Utilizing current potential that the visual stimulus of fixed frequency flicker brings out to convert experimenter's visual activity to actual command based on the BCI of steady-state induced current potential (SSVEP), have higher speed and stability, is a focus of the research of present BCI.But present asynchronous SSVEP system is also not enough aspect accuracy and speed two, does not reach the needs of practical application.And it all is to application-specific basically, in case the algorithm change just needs great amount of time to come the performance of test macro, this makes the exploitation of asynchronous SSVEP system, and the improvement cycle is longer.
Summary of the invention
The purpose of this invention is to provide a kind of asynchronous brain machine interface system and its implementation based on steady-state induced current potential; Can conveniently carry out the test of system; And can generally be applicable to various controls application, accuracy rate and reaction velocity when improving SSVEP conversion actual command simultaneously.
In order to achieve the above object, technical scheme of the present invention provides a kind of asynchronous brain machine interface system based on steady-state induced current potential, and said system comprises:
Stimulator, it sends stimulus signal to the experimenter;
Signal picker, it obtains the brain of gathering the experimenter brings out formation through said stimulus signal steady-state induced electric potential signal;
Signal processor, it is connected with said signal picker signal, and said steady-state induced electric potential signal is changed into corresponding instruction;
The briefing device, it sends the briefing signal that is complementary with said stimulus signal to the experimenter;
Output result and feedback assembly, it is connected with said signal processor signal, said instruction and said briefing signal is compared, and comparative result is fed back to the experimenter;
The control command translation interface, it is connected with said signal processor signal, said instruction is further changed into the control command that can control external unit;
Wherein, said stimulator, briefing device, signal picker, signal processor, output result and feedback assembly form the test macro part of said system; Said stimulator, signal picker, signal processor, control command translation interface form the control system part of said system.
Preferably, said stimulator is a visual stimulator, and it is included in four stimulating modules with different flicker frequencies of annular spread on the display interface of display;
The arrow of different directions appears having in said briefing device random time on said display interface; The direction of said arrow is corresponding with one of them said stimulating module residing position on display interface, watches attentively and corresponding that stimulating module of arrow direction with the prompting experimenter.
Said signal picker comprises online collecting device, wherein is provided with multiplying arrangement, can the steady-state induced electric potential signal of gathering from the brain scalp via a plurality of electrodes be changed into the discrete digital signal; Said signal picker is gathered the PO in occipital bone zone
3, PO
Z, PO
4, O
1, O
Z, O
2Electrode channel is as signal sampling channel, the ear-lobe of any side passage as a reference about also gathering, and with F
ZElectrode channel is as the ground connection passage;
Said signal picker also comprises the off-line loading equipment, can the signal data of testing acquisition in the past directly be loaded in the system, to substitute the data that online acquisition equipment is gathered, is convenient to after experiment the data to the experimenter and carries out analyzing and processing.
Said signal processor further comprises:
Based on the signal preprocessor of Laplce's combination, it is connected with said signal picker signal, and from said steady-state induced electric potential signal, removes noise;
Based on the feature extractor of canonical correlation analysis, it is connected with said signal preprocessor signal, and from said steady-state induced electric potential signal, extracts the signal characteristic of reflection experimenter intention;
Classify based on threshold value and to distinguish the work of experimenter's brain and the pattern classifier of idle condition, it is connected with said feature extractor signal, and said signal characteristic is converted into instruction exports.
Another technical scheme of the present invention provides a kind of implementation method of the asynchronous brain-computer interface based on steady-state induced current potential, uses above-mentioned system to realize;
Said method comprise to experimenter's use test Account Dept assign to verify asynchronous brain machine interface system performance below some steps:
Steps A 4, use output result and feedback assembly compare said instruction and said briefing signal, and comparative result are fed back to the experimenter;
Said method also comprises uses control system part some steps below the external unit transmitting control commands:
Step B1, use stimulator send stimulus signal to the experimenter;
Step B2, the brain that uses signal picker to obtain the collection experimenter bring out the steady-state induced electric potential signal of formation through said stimulus signal;
Step B3, use signal processor change into corresponding instruction with said steady-state induced electric potential signal;
Step B4, use control command translation interface further change into control command with said instruction and send to external unit.
Four stimulating modules of said stimulator control distribute on the display interface of display ringwise, and glimmer with different frequency of stimulation;
Said briefing device is based on random algorithm; One arrow is appeared on the said display interface with different directions; The direction of said arrow is corresponding with one of them said stimulating module residing position on display interface, watches attentively and corresponding that stimulating module of arrow direction with the prompting experimenter;
Direction shown in the directional information of the instruction representative of the more said signal processor output of said output result and feedback assembly and the arrow of said briefing device, when comparative result was inconsistent, the prompting experimenter adjusted the state of watching attentively next time.
Said signal picker will change into the discrete digital signal via the steady-state induced electric potential signal that a plurality of electrodes are gathered from the brain scalp through multiplying arrangement in a kind of online acquisition mode; Said signal picker is gathered the PO in occipital bone zone
3, PO
Z, PO
4, O
1, O
Z, O
2Electrode channel is as signal sampling channel, the ear-lobe of any side passage as a reference about also gathering, and with F
ZAs the ground connection passage; The steady-state induced electric potential signal amplitude of said signal sampling channel is greater than the steady-state induced electric potential signal amplitude of said reference channel;
Said signal picker is written in the mode at another kind of off-line, can the signal data of testing acquisition in the past directly be loaded in the asynchronous brain machine interface system, to substitute the data of online acquisition, is convenient to after experiment the data to the experimenter and carries out analyzing and processing.
Said signal processor comprises two steps of Signal Pretreatment link:
The first step is that the steady-state induced electric potential signal that collects is carried out filtering and trap, signal is concentrated in the specific frequency range, and remove power frequency component;
Second step was to use Laplce's combined method that signal is strengthened, and weakened common noise simultaneously, promptly at PO
3, PO
Z, PO
4, O
1, O
Z, O
2In the electrode channel, with O
ZAs central electrode, and from PO
3, PO
Z, PO
4, O
1, O
2In 4 periphery electrodes choosing successively difference of forming symmetry come processing signals; Form weight matrix
WFor:
If
SBe to comprise 5 kinds to O
ZThe N that strengthens
t* 5 matrix supplies the follow-up signal processing links to use;
Said signal processor also comprises feature extraction step, seeing that the canonical correlation analysis algorithm is right
SCarry out feature extraction, and use 3 harmonic waves (sin (2 π
Ft), cos (2 π
Ft), sin (4 π
Ft), sin (4 π
Ft), cos (4 π
Ft), sin (6 π
Ft), cos (2 π
Ft)) signal as a reference, wherein
fBe the frequency of stimulation of stimulator, make each frequency of stimulation that one related coefficient characteristic all arranged.
Said signal processor further comprises the pattern classification link, adopts the threshold value sorting technique to distinguish the free time and the duty of experimenter's brain:
ρ wherein
MaxAnd ρ
SecBe respectively maximum and time big related coefficient in all coefficient of frequencies after the feature extraction step, said threshold value θ be between the 0-1 on the occasion of; If the left side of inequality is less than θ, asynchronous brain machine interface system will judge that brain is in duty, and according to ρ
MaxThe coefficient of frequency that is equaled is judged corresponding concrete duty; Otherwise system is in idle condition with judgement.
Said asynchronous brain machine interface system adopts the moving window method, and the signal that during whole experiment is carried out, obtains after always to pattern classification carries out analyzing and processing to form corresponding order; In the time delay of definition, when continuous order identical more than two and two produced, system only exported an order, and when being less than two orders, system does not export; And definition has or not the reaction time, will not carry out the output of task duty order in the reactionless time after system detects an order.
Asynchronous brain machine interface system and its implementation based on steady-state induced current potential according to the invention; Have following beneficial effect: the asynchronous SSVEP implementation of proposition has higher relatively accuracy rate and reaction velocity faster, can further be applied to real life.System design is not to application-specific, and behind the change algorithm, the checking meeting of algorithm performance is very convenient.And the strategy of asynchronous system is simple, efficient is high, has higher utility.
Description of drawings
Fig. 1 is the structural representation based on test macro part in the asynchronous brain machine interface system of steady-state induced current potential according to the invention;
Fig. 2 is the structural representation based on control system part in the asynchronous brain machine interface system of steady-state induced current potential according to the invention;
Fig. 3 is a kind of enforcement interface synoptic diagram based on visual stimulator and briefing device in the asynchronous brain machine interface system of steady-state induced current potential according to the invention;
Fig. 4 is the principle schematic of the asynchronous brain machine interface system asynchronous working based on steady-state induced current potential according to the invention;
Fig. 5 is a kind of display interface synoptic diagram based on output result and when feedback in the asynchronous brain machine interface system of steady-state induced current potential according to the invention.
Embodiment
The invention provides a kind of asynchronous brain machine interface system based on steady-state induced current potential (SSVEP).This system comprises two parts, test macro part and control system part.
The structure of said test macro part is as shown in Figure 1, mainly comprises following a few part: visual stimulator 10, briefing device 12, signal picker 20, signal processor 30, output result and feedback assembly 40.Signal processor 30 further comprises signal preprocessor 31, feature extractor 32 and pattern classifier 33.
And control system part of the present invention is on the basis of above-mentioned test macro part, to develop, and it is not directed against specific concrete application, but can transplant easily on concrete application system, and its structure is as shown in Figure 2.Promptly; Said control system part is not provided with briefing device 12 and output result and feedback assembly 40; And the connected mode and the principle of work of the visual stimulator 10, signal picker 20 and the signal processor 30 that are provided with are identical with the test macro part, and after signal processor 30, have increased control command translation interface 50.
That is to say; Electrode is obtained the SSVEP signal that brings out through visual stimulator 10 from scalp; After converting digital signal to through signal picker 20; Through signal preprocessor 31 removal noises, the respective algorithms that in feature extractor 32, is provided with then extracts the signal characteristic of reflection experimenter intention again, is converted into the concrete instruction that can control external unit through pattern classifier 33 these signal characteristics of processing back and exports.For described test macro part, can the instruction of output be compared with the briefing that initially provides to the experimenter, whether judge both consistent and to user feedback.And described control system part, the instruction that then will export further converts the control command that external unit can be accepted to.
Therefore, the present invention in the technical matters that the test macro part is solved is: the realization of (1) visual stimulator 10; (2) briefing of simulating reality situation; (3) signal acquisition method and channel selecting (4) signal processing method quickly and accurately; (5) output of simulating reality and feedback method.The technical matters that is solved in the control system part is: classification outputs to the conversion of control command.
Through a following preferred embodiment, the realization of technical scheme according to the invention is described:
The visual stimulus module 11 that the present invention uses in test macro part and control system part and the arrangement of briefing module have been shown among Fig. 3.
Exploitation for ease, visual stimulator 10 are intended and are adopted software programming on computer monitor, to realize.For example, visual stimulator 10 is realized on the VS2008 platform through VC++: this stimulator 10 is provided with 4 stimulating modules 11, make these stimulating modules 11 with annular spread around 19 inches LCD displays.Stimulating module 11 with the left side is initial, in the direction of the clock, makes the flicker frequency of these stimulating modules 11 be followed successively by 10Hz, 7.5Hz, 6.67Hz and 8.57Hz.Such design is to make things convenient for the user with stimulating module 11 and the such position relationship in upper left bottom right.
The acquisition method that signal picker 20 uses divides online and the off-line dual mode, and acquisition channel is chosen the strongest channel position of SSVEP response;
(i) adopt multiplying arrangement to gather the EEG signals that brought out by visual stimulator 10 from the brain scalp in the online acquisition mode, this multiplying arrangement can directly change into discrete data to the signal that collects, thus convenient later signal processing analysis.In order to obtain amplitude peak SSVEP signal, need the SSVEP amplitude of acquisition channel higher, the SSVEP amplitude of reference channel is lower.Theoretical according to neuro-physiology, SSVEP can detect maximum amplitude in the occipital bone zone, thus generally with the occipital bone zone as signal sampling channel; Ear-lobe compares that other brain electrode positions are far away according to brain, and the SSVEP amplitude is lower, so generally with ear-lobe channel position as a reference.Therefore, choose PO in the native system
3, PO
Z, PO
4, O
1, O
Z, O
2Six passages are as signal sampling channel, about the ear-lobe passage as a reference of any side, F
ZAs the ground connection passage.
(ii) to be written in the mode be that signal data with experiment in the past obtains directly was loaded in the system to off-line, substituting the data that online equipment collects, convenient the data of testing the back experimenter carried out analyzing and processing.
In the pre-service link of signal processor 30, adopt Laplce to make up preprocessed signal; In feature extraction step, (Canonical Correlation Analysis CCA) extracts the related coefficient characteristic of each frequency of stimulation in the SSVEP signal to adopt canonical correlation analysis; In the pattern classification link, use self-defining threshold value sorting technique to come differentiation work and idle condition.
Concrete, the Signal Pretreatment link was divided into for two steps: the first step is that the EEG signals that collect are carried out filtering and trap, EEG signals is concentrated in the specific frequency range, and remove power frequency component; Second step was that signal is strengthened, and weakened common noise simultaneously, extracted characteristic better with convenient later feature extraction algorithm, and the method for using Laplce to make up is here handled.The difference that Laplce's combined method gets up to form symmetry with the signal combination of a central electrode and four surround electrodes is come processing signals.The present invention uses six electrode (PO
3, PO
Z, PO
4, O
1, O
Z, O
2) obtain the EEG signal, owing to compare O with other 5 passages
ZSSVEP response stronger, so use O here
ZAs central electrode, 4 periphery electrodes are chosen weight matrix successively from 5 remaining electrodes then
WFor:
Therefore,
SBe to comprise 5 kinds to O
ZThe N that strengthens
t* 5 matrix.Next,
STo enter into follow-up signal processing as input signal handles.
Feature extraction step is in view of the superiority of canonical correlation analysis (CCA) algorithm, so select for use CCA to come S is carried out feature extraction.Reference signal is used 3 harmonic wave (sin (2 π
Ft), cos (2 π
Ft), sin (4 π
Ft), sin (4 π
Ft), cos (4 π
Ft), sin (6 π
Ft), cos (2 π
Ft)), wherein
fIt is the frequency of stimulation of stimulator 10.
The pattern classification link adopts self-defining threshold value sorting technique.Through the CCA method, each frequency of stimulation all has a related coefficient characteristic, through observing maximum correlation coefficient ρ
MaxWith the ratio of inferior big related coefficient probably be about 2 times, some in addition near 3 times.When the experimenter is in resting state, when promptly not watching any one stimulating module 11 attentively, the result of each related coefficient is more approaching, maximum correlation coefficient ρ
MaxWith inferior big related coefficient ratio probably be about 1.So we consider to use the method for threshold value classification to distinguish free time and duty:
ρ wherein
MaxAnd ρ
SecIt is respectively maximum and inferior big related coefficient in all coefficient of frequencies.If the left side of inequality is less than θ, system will judge that brain is in duty, and according to ρ
MaxThe coefficient of frequency that is equaled, which kind of duty decides is.Otherwise system will be judged as idle condition.Here threshold value θ be between the 0-1 on the occasion of, the size of threshold value difference according to each experimenter's difference and to some extent, operated by rotary motion is about 0.75.
In order to guarantee the accuracy of real-time and order output, signal will carry out analyzing and processing always during whole experiment is carried out.Here native system at first adopts the method for moving window to come composite signal.As shown in Figure 4, supposing once to test length is 120s, and length of window is 3s, and each second to front slide once.Detect with this strategy, will all there be classification results in system in each second, and duty usually continues more than one second, and this just causes the situation of repetition output command easily.And when the experimenter does not watch particular stimulation attentively (idle condition), the stimulation that the experimenter is glimmered is easily disturbed, and produces undesirable order output.For fear of the generation of these situation, we define the time delay (dwelling time) of 2s: when continuous two and two above same commands, system only exports an order, and when being less than two, system does not export; And define two seconds reactionless time (refractory time), promptly system detects the output that will not carry out the order of task duty in the order 2s afterwards.
Among the output result and feedback element of test macro part according to the invention; Output is the result export the system model sorting result; A certain stimulation order through being watched attentively with the user compares; Feedback fraction is presented on the computer monitor: if consistent, will feed back at center, stimulator 10 interface " Good ", otherwise feedback " Error ".The user can be according to feedback result, and state is watched in adjustment attentively next time, and the interface is as shown in Figure 5.
Similar in most of structure in the said control system part and the test macro part, be summarized as follows:
20 fens online and two kinds of embodiments of off-line of signal picker, the online acquisition passage is chosen PO
3, PO
Z, PO
4, O
1, O
Z, O
2Six passages; Situation when the off-line collection can be reduced online acquisition is convenient to carry out data analysis.
Signal processor 30 comprises three links: signal preprocessor 31, feature extractor 32 and pattern classifier 33; The Signal Pretreatment link adopts the method for Laplce's combination; Pretreated signal is sent into feature extraction step; Adopt the CCA method to extract characteristic in this link, at last the characteristic of extracting is sent into the pattern classification link, use threshold value classification output result.
In order to guarantee the accuracy of real-time and order output, the signal that collects uses the policy groups organization data of moving window, and the strategy of employing 2s time delay and reactionless time 2s limits the classification results of exporting.
The distinctive link of said control system part is that the result that pattern classification is exported is converted into control command, thus the concrete application system of controlling and driving.Native system provides control command translation interface 50, can be according to concrete application, and will export the result and be mapped in the control commands corresponding and go.Pattern classification specifically can adopt the mode of clipbook communication to realize to the conversion of control command; Be about to shear plate as a media; The result of pattern classification is sent in the shear plate according to using required command forms; Application can be read in the shear plate according to certain speed and ordered, thereby realizes the control to using.
Although content of the present invention has been done detailed introduction through above-mentioned preferred embodiment, will be appreciated that above-mentioned description should not be considered to limitation of the present invention.After those skilled in the art have read foregoing, for multiple modification of the present invention with to substitute all will be conspicuous.Therefore, protection scope of the present invention should be limited appended claim.
Claims (10)
1. asynchronous brain machine interface system based on steady-state induced current potential is characterized in that said system comprises:
Stimulator, it sends stimulus signal to the experimenter;
Signal picker, it obtains the brain of gathering the experimenter brings out formation through said stimulus signal steady-state induced electric potential signal;
Signal processor, it is connected with said signal picker signal, and said steady-state induced electric potential signal is changed into corresponding instruction;
The briefing device, it sends the briefing signal that is complementary with said stimulus signal to the experimenter;
Output result and feedback assembly, it is connected with said signal processor signal, said instruction and said briefing signal is compared, and comparative result is fed back to the experimenter;
The control command translation interface, it is connected with said signal processor signal, said instruction is further changed into the control command that can control external unit;
Wherein, said stimulator, briefing device, signal picker, signal processor, output result and feedback assembly form the test macro part of said system; Said stimulator, signal picker, signal processor, control command translation interface form the control system part of said system.
2. according to claim 1 based on the asynchronous brain machine interface system of steady-state induced current potential, it is characterized in that,
Said stimulator is a visual stimulator, and it is included in four stimulating modules with different flicker frequencies of annular spread on the display interface of display;
The arrow of different directions appears having in said briefing device random time on said display interface; The direction of said arrow is corresponding with one of them said stimulating module residing position on display interface, watches attentively and corresponding that stimulating module of arrow direction with the prompting experimenter.
3. like the said asynchronous brain machine interface system of claim 2, it is characterized in that based on steady-state induced current potential,
Said signal picker comprises online collecting device, wherein is provided with multiplying arrangement, can the steady-state induced electric potential signal of gathering from the brain scalp via a plurality of electrodes be changed into the discrete digital signal; Said signal picker is gathered the PO in occipital bone zone
3, PO
Z, PO
4, O
1, O
Z, O
2Electrode channel is as signal sampling channel, the ear-lobe of any side passage as a reference about also gathering, and with F
ZElectrode channel is as the ground connection passage;
Said signal picker also comprises the off-line loading equipment, can the signal data of testing acquisition in the past directly be loaded in the system, to substitute the data that online acquisition equipment is gathered, is convenient to after experiment the data to the experimenter and carries out analyzing and processing.
4. like the said asynchronous brain machine interface system of claim 3, it is characterized in that based on steady-state induced current potential,
Said signal processor further comprises:
Based on the signal preprocessor of Laplce's combination, it is connected with said signal picker signal, and from said steady-state induced electric potential signal, removes noise;
Based on the feature extractor of canonical correlation analysis, it is connected with said signal preprocessor signal, and from said steady-state induced electric potential signal, extracts the signal characteristic of reflection experimenter intention;
Classify based on threshold value and to distinguish the work of experimenter's brain and the pattern classifier of idle condition, it is connected with said feature extractor signal, and said signal characteristic is converted into instruction exports.
5. the implementation method based on the asynchronous brain-computer interface of steady-state induced current potential uses the described system of claim 1 to realize, it is characterized in that,
Said method comprise to experimenter's use test Account Dept assign to verify asynchronous brain machine interface system performance below some steps:
Steps A 1, use stimulator send stimulus signal to the experimenter, and use the briefing device to send the briefing signal that is complementary with said stimulus signal to the experimenter;
Steps A 2, the brain that uses signal picker to obtain the collection experimenter bring out the steady-state induced electric potential signal of formation through said stimulus signal;
Steps A 3, use signal processor change into corresponding instruction with said steady-state induced electric potential signal;
Steps A 4, use output result and feedback assembly compare said instruction and said briefing signal, and comparative result are fed back to the experimenter;
Said method also comprises uses control system part some steps below the external unit transmitting control commands:
Step B1, use stimulator send stimulus signal to the experimenter;
Step B2, the brain that uses signal picker to obtain the collection experimenter bring out the steady-state induced electric potential signal of formation through said stimulus signal;
Step B3, use signal processor change into corresponding instruction with said steady-state induced electric potential signal;
Step B4, use control command translation interface further change into control command with said instruction and send to external unit.
6. like the implementation method of the said asynchronous brain-computer interface based on steady-state induced current potential of claim 5, it is characterized in that,
Four stimulating modules of said stimulator control distribute on the display interface of display ringwise, and glimmer with different frequency of stimulation;
Said briefing device is based on random algorithm; One arrow is appeared on the said display interface with different directions; The direction of said arrow is corresponding with one of them said stimulating module residing position on display interface, watches attentively and corresponding that stimulating module of arrow direction with the prompting experimenter;
Direction shown in the directional information of the instruction representative of the more said signal processor output of said output result and feedback assembly and the arrow of said briefing device, when comparative result was inconsistent, the prompting experimenter adjusted the state of watching attentively next time.
7. like the implementation method of the said asynchronous brain-computer interface based on steady-state induced current potential of claim 6, it is characterized in that,
Said signal picker will change into the discrete digital signal via the steady-state induced electric potential signal that a plurality of electrodes are gathered from the brain scalp through multiplying arrangement in a kind of online acquisition mode; Said signal picker is gathered the PO in occipital bone zone
3, PO
Z, PO
4, O
1, O
Z, O
2Electrode channel is as signal sampling channel, the ear-lobe of any side passage as a reference about also gathering, and with F
ZAs the ground connection passage; The steady-state induced electric potential signal amplitude of said signal sampling channel is greater than the steady-state induced electric potential signal amplitude of said reference channel;
Said signal picker also is written in the mode at a kind of off-line, and the signal data that experiment is in the past obtained directly was loaded in the asynchronous brain machine interface system, to substitute the data of online acquisition, is convenient to after experiment the data to the experimenter and carries out analyzing and processing.
8. like the implementation method of the said asynchronous brain-computer interface based on steady-state induced current potential of claim 7, it is characterized in that,
Said signal processor comprises two steps of Signal Pretreatment link:
The first step is that the steady-state induced electric potential signal that collects is carried out filtering and trap, signal is concentrated in the specific frequency range, and remove power frequency component;
Second step was to use Laplce's combined method, signal is strengthened weaken common noise simultaneously, promptly at PO
3, PO
Z, PO
4, O
1, O
Z, O
2In the electrode channel, with O
ZAs central electrode, and from PO
3, PO
Z, PO
4, O
1, O
2In 4 periphery electrodes choosing successively difference of forming symmetry come processing signals, form weight matrix
WFor:
If
SBe to comprise 5 kinds to O
ZThe N that strengthens
t* 5 matrix supplies the follow-up signal processing links to use;
Said signal processor also comprises feature extraction step, seeing that the canonical correlation analysis algorithm is right
SCarry out feature extraction, and use 3 harmonic waves (sin (2 π
Ft), cos (2 π
Ft), sin (4 π
Ft), sin (4 π
Ft), cos (4 π
Ft), sin (6 π
Ft), cos (2 π
Ft)) signal as a reference, wherein
fBe the frequency of stimulation of stimulator, make each frequency of stimulation that one related coefficient characteristic all arranged.
9. like the implementation method of the said asynchronous brain-computer interface based on steady-state induced current potential of claim 8, it is characterized in that,
Said signal processor further comprises the pattern classification link, adopts the threshold value sorting technique to distinguish the free time and the duty of experimenter's brain:
ρ wherein
MaxAnd ρ
SecBe respectively maximum and time big related coefficient in all coefficient of frequencies after the feature extraction step, said threshold value θ be between the 0-1 on the occasion of; If the left side of inequality is less than θ, asynchronous brain machine interface system will judge that brain is in duty, and according to ρ
MaxThe coefficient of frequency that is equaled is judged corresponding concrete duty; Otherwise system is in idle condition with judgement.
10. like the implementation method of claim 5 or 8 said asynchronous brain-computer interfaces based on steady-state induced current potential, it is characterized in that,
Said asynchronous brain machine interface system adopts the moving window method, and the signal that during whole experiment is carried out, obtains after always to pattern classification carries out analyzing and processing to form corresponding order; In the time delay of definition, when continuous order identical more than two and two produced, system only exported an order, and when being less than two orders, system does not export; And definition has or not the reaction time, will not carry out the output of task duty order in the reactionless time after system detects an order.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN107957780A (en) * | 2017-12-07 | 2018-04-24 | 东南大学 | A kind of brain machine interface system based on Steady State Visual Evoked Potential physiological property |
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| CN103093085B (en) * | 2012-12-31 | 2016-01-20 | 清华大学 | Based on the analytical approach of the steady-state induced current potential of canonical correlation analysis |
| CN103093085A (en) * | 2012-12-31 | 2013-05-08 | 清华大学 | Steady state evoked potential analysis method based on canonical correlation analysis |
| CN104606030A (en) * | 2015-01-06 | 2015-05-13 | 上海交通大学 | Lower limb on-line walking rehabilitation system and method fused with autokinetic movement consciousness |
| CN107957780B (en) * | 2017-12-07 | 2021-03-02 | 东南大学 | Brain-computer interface system based on steady-state visual evoked potential physiological characteristics |
| CN107957780A (en) * | 2017-12-07 | 2018-04-24 | 东南大学 | A kind of brain machine interface system based on Steady State Visual Evoked Potential physiological property |
| CN108294748A (en) * | 2018-01-23 | 2018-07-20 | 南京航空航天大学 | A kind of eeg signal acquisition and sorting technique based on stable state vision inducting |
| CN109656356A (en) * | 2018-11-13 | 2019-04-19 | 天津大学 | A kind of asynchronous control system of SSVEP brain-computer interface |
| CN110379376A (en) * | 2019-07-04 | 2019-10-25 | 北京航空航天大学 | A kind of liquid crystal display and its stimulus patterns display methods for SSVEP |
| CN110379376B (en) * | 2019-07-04 | 2020-11-24 | 北京航空航天大学 | Liquid crystal display for SSVEP and stimulation pattern display method thereof |
| CN110367982A (en) * | 2019-07-10 | 2019-10-25 | 西安交通大学 | The colour vision functional check method of view-based access control model Evoked ptential |
| WO2022001098A1 (en) * | 2020-07-03 | 2022-01-06 | 福州大学 | Precise visual stimulation control method in brain-computer interface |
| CN112001305A (en) * | 2020-08-21 | 2020-11-27 | 西安交通大学 | Feature optimization SSVEP asynchronous recognition method based on gradient lifting decision tree |
| CN112001305B (en) * | 2020-08-21 | 2022-08-05 | 西安交通大学 | Feature optimization SSVEP asynchronous recognition method based on gradient lifting decision tree |
| CN112633312A (en) * | 2020-09-30 | 2021-04-09 | 深圳睿瀚医疗科技有限公司 | Automatic optimization algorithm based on SSMVEP-ERP-OSR mixed brain-computer interface |
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