CN102783946A - Automatic brain source locating method and device - Google Patents

Abstract

The invention discloses an automatic brain source locating method and a device. The automatic brain source locating method is characterized in that: aiming at multi-channel electroencephalogram signals, firstly, the signals are segmented by utilizing the moving window technology; then, for each segment of data, a instantaneous amplitude value and phase information at a specified frequency range are extracted through harmonic wavelet transform; next, on the basis of synchronization technology, synchronization between two channels at the specified frequency range is calculated; and at last, synchronizing information at the segments is integrated, and synchronization degree of electroencephalogram signals of the channels is obtained, so that the location of a brain source is determined. The invention provides the automatic brain source locating method and the device which can help researchers to determine the brain source rapidly, thus providing the objective basis for understanding the relationship between the brain source and behaviors.

Description

A kind of from beating one's brains source location method and device

Technical field

The present invention relates to bioengineering field, particularly a kind of automatic brain source location method and apparatus is for the activity that discloses the brain district provides technological means.

Background technology

EEG signals have become a kind of important means of research brain science.EEG signals are general performances of neuron pool action potential in the cerebral tissue.The electrical potential activity of the whole brain of normal person only reaches 1,000,000/volt, and this mainly is because normal neural discharge is asynchronous.And brain is when needing the extraneous stimulation of process information, reflection; The most cells synchronization discharge of neuron colony; If this behavior trend is extreme; Promptly cause so-called supersynchronousization, the wave amplitude of brain wave sharply rises like this, on EEG signals, is rendered as abnormal ripples such as spike, sharp wave and sour jujube/sharp and slow wave complex.Research worker can be judged the position in brain source through analyzing these brain signals.Yet the EEG signals record not only can increase the burden of research worker for a long time, and unavoidably also can add some subjective selectivitys; Simultaneously, the EEG signals that interpretation for a long time is a large amount of cause research worker overtired and cause the rising of False Rate easily.Therefore, utilize Digital Signal Processing to realize the preparation judgement in brain source,, become a problem that presses for solution to improve the efficient of scientific research.

Existing brain source location method generally is the multichannel brain signal of telecommunication through non-volatile recording, according to eeg data, therefrom extracts correlated characteristic and confirms brain source Probability Area; These characteristics are included in performance number on wave character on the time domain, the frequency domain (like document: Michel CM, Murray M, Lantz G; Gonzalez S, Spinelli L, Grave de Peralta R.EEG source imaging.Clin Neurophysiol 115; 2004:2195-2222); Perhaps utilize component analysis techniques (independent component analysis or principal component analysis etc.) to extract the EEG signals characteristic component, with each passage EEG signals to the size of its contribution margin as characteristic (like document: Y.Stern, M.Y.Neufeld; S.Kipervasser; A.Zilberstein1, I.Fried, M.Teicher; E.Adi-Japha.Source localization of temporal lobe epilepsy using PCA-LORETA analysis on ictal EEG recordings.Journal of Clinical Neurophysiology 26 (2), 2009:109-116) etc.

From the ultimate principle method for designing of brain information processing, most of algorithm is not the angle from signal processing to above-mentioned technology, not from describing the basic law that brain signal is handled in essence; On the other hand, do not consider the phase information of signal, do not excavate the communication mechanism of phase place between the different cerebral district of brain signal.Present achievement in research thinks that the main mechanism of brain process information is synchronized oscillation, mainly is that expression brain district passes through a kind of inherent synchronization mechanism, could the more complicated cognitive information of integrated processing.

Summary of the invention

The purpose of this invention is to provide one accurately, brain source location method and device automatically, directly the vibration synchronizing process of integrated presentation brain information processing for the research of brain Cognitive Science provides new information, helps to further investigate the relation of brain function and behavior.

In order to reach above-mentioned target, technical scheme of the present invention is:

A kind of from beating one's brains the source location device, comprise

Eeg signal acquisition equipment is used to gather original EEG signals;

A/D converter will be simulated the accurate digital signal that changes into of EEG signals;

The EEG signals amplifier is used for EEG signals are amplified;

Also comprise the EEG Processing device, the EEG Processing device is at first with the EEG signals segmentation; Extract instantaneous amplitude and the phase information of the multichannel brain signal of telecommunication on designated frequency band then; Confirm interchannel in twos synchronous intensity on the designated frequency band then; Confirm the brain source location matrix on each designated frequency band; Confirm the average intensity synchronously of each passage and other all interchannels at last; Average intensity synchronously is used for weighing near the brain region of this electrode and the power of other interregional synchronicitys, and numerical value is big more, and then synchronicity is strong more, and expression might be the brain source region more.

The EEG signals segmentation adopts the moving window technology to carry out segment processing.

Utilize humorous wavelet transformation to extract instantaneous amplitude and phase information on the designated frequency band.

Instantaneous amplitude and the phase information concrete steps of utilizing humorous wavelet transformation to extract on the designated frequency band are following: set frequency range to be investigated and be [f _L, f _H],

Humorous small echo has compact frequency domain representation form, and it is defined as

$H_{m,n}\left(w\right)=\left\{\begin{array}{cc}\frac{1}{(n-m)2\mathrm{\&pi;}}& \mathrm{<figure-callout\; id="2"\; label="m"\; filenames="HDA00002032984200031.png"\; state="\{\{state\}\}">m</figure-callout>}2\mathrm{\&pi;}\&le;w\&le;\mathrm{<figure-callout\; id="2"\; label="n"\; filenames="HDA00002032984200031.png"\; state="\{\{state\}\}">n</figure-callout>}2\mathrm{\&pi;}\\ 0& \mathrm{elsewhere}\end{array}\right.---\left(1\right)$

Wherein, m and n are scale parameters; Humorous wavelet transformation utilizes fast Fourier transform to realize, this algorithm was accomplished through three steps: (a) treat processing signals x (t) and carry out Fourier transform, obtain its frequency spectrum X (w); (b) with X (w) with (m, n) conjugate multiplication of the box-like spectrum H (w) of humorous small echo on the yardstick obtains W (w); Required frequency range [f _L, f _H] following with the relation of scale parameter m, n:

$m=f_L\&CenterDot;\frac{N}{f_s}$ (2)

$n=f_H\&CenterDot;\frac{N}{f_s}$

Wherein, f _sBe sample frequency, N is counting of Fourier transformation; (c) W (w) is carried out inverse fourier transform, promptly obtain humorous wavelet conversion coefficient w (t), this coefficient is a plural number, and its imaginary part is the Hilbert conversion of real part, and its instantaneous phase can be calculated as follows:

φ(t)=tan ^-1(imag(w(t))/real(w(t)))(3)

Instantaneous amplitude does

$A\left(t\right)=\sqrt{{\left(\mathrm{real}\left(w\left(t\right)\right)\right)}^2+{\left(\mathrm{imag}\left(w\left(t\right)\right)\right)}^2}---\left(4\right)$

Obtain each passage EEG signals EEG like this _i(t), i=1,2 ..., L (L is a port number) is at [f _L, f _H] instantaneous amplitude A on the frequency range _i(t) and phase information

Confirm that the concrete steps of interchannel synchronous intensity are following in twos on the designated frequency band: two passages of the synchronous intensity of set-up and calculated are respectively EEG _i(t) and EEG _j(t), i, j=1,2 ..., L; I ≠ j, corresponding instantaneous amplitude A _i(t), A _j(t) and phase information

Phase contrast is defined as so

Definition Phase synchronization intensity factor

Wherein, M is a signal length, considers the influence of amplitude, and it is following to define synchronous intensity factor again:

${\mathrm{IPSI}}_{\mathrm{ij}}=\frac{<A_i\left(t\right)>+<A_j\left(t\right)>}{2}\&CenterDot;{\mathrm{PSI}}_{\mathrm{ij}}---\left(7\right)$

Wherein,<>Average on the express time, with its normalization, obtain nIPSI _Ij:

${\mathrm{nIPSI}}_{\mathrm{ij}}=\frac{{\mathrm{IPSI}}_{\mathrm{ij}}}{\underset{i,j,i\&NotEqual;j}{\max }\left({\mathrm{IPSI}}_{\mathrm{ij}}\right)}---\left(8\right)$

With nIPSI _IjArrange according to matrix form, the position of i=j wherein, promptly the element on the diagonal of matrix all gets 0, obtains interchannel in twos cogradient matrix on this frequency range

The concrete steps of confirming the brain source location matrix on each designated frequency band are following: along with the passing of moving window, can obtain the interchannel in twos cogradient matrix E on this designated frequency band on each time period _k[i, j], k represent the time hop count k=1 that chooses, 2 ..., K; The meansigma methods of getting last cogradient matrix of all time periods is as the brain source location matrix E on the designated frequency band _Ave[i, j], $E_{\mathrm{Ave}}[i,j]=\frac{1}{K}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{E}_k[i,j];$

Confirm each passage and other all interchannel average strength S synchronously _i,

A kind of from beating one's brains the source location method, may further comprise the steps:

(1) EEG signals segmentation;

(2) extract instantaneous amplitude and the phase information of the multichannel brain signal of telecommunication on designated frequency band;

(3) confirm interchannel in twos synchronous intensity on the designated frequency band;

(4) confirm brain source location matrix on each designated frequency band;

(5) confirm the average intensity synchronously of each passage and other all interchannels; Average intensity synchronously is used for weighing near the brain region of this electrode and the power of other interregional synchronicitys, and numerical value is big more, and then synchronicity is strong more, and expression might be the brain source region more.

EEG signals segmentation in the said step (1) adopts the moving window technology to carry out segment processing.

Utilize humorous wavelet transformation to extract instantaneous amplitude and phase information on the designated frequency band in the said step (2).

Instantaneous amplitude and the phase information concrete steps of utilizing humorous wavelet transformation to extract on the designated frequency band are following: set frequency range to be investigated and be [f _L, f _H],

Humorous small echo has compact frequency domain representation form, and it is defined as

$H_{m,n}\left(w\right)=\left\{\begin{array}{cc}\frac{1}{(n-m)2\mathrm{\&pi;}}& \mathrm{<figure-callout\; id="2"\; label="m"\; filenames="HDA00002032984200031.png"\; state="\{\{state\}\}">m</figure-callout>}2\mathrm{\&pi;}\&le;w\&le;\mathrm{<figure-callout\; id="2"\; label="n"\; filenames="HDA00002032984200031.png"\; state="\{\{state\}\}">n</figure-callout>}2\mathrm{\&pi;}\\ 0& \mathrm{elsewhere}\end{array}\right.$

Wherein, m and n are scale parameters; Humorous wavelet transformation utilizes fast Fourier transform to realize, this algorithm was accomplished through three steps: (a) treat processing signals x (t) and carry out Fourier transform, obtain its frequency spectrum X (w); (b) with X (w) with (m, n) conjugate multiplication of the box-like spectrum H (w) of humorous small echo on the yardstick obtains W (w); Required frequency range [f _L, f _H] following with the relation of scale parameter m, n:

$m=f_L\&CenterDot;\frac{N}{f_s}$

$n=f_H\&CenterDot;\frac{N}{f_s}$

Wherein, f _sBe sample frequency, N is counting of Fourier transformation; (c) W (w) is carried out inverse fourier transform, promptly obtain humorous wavelet conversion coefficient w (t), this coefficient is a plural number, and its imaginary part is the Hilbert conversion of real part, and its instantaneous phase can be calculated as follows:

φ(t)=tan ^-1(imag(w(t))/real(w(t)))

Instantaneous amplitude does

$A\left(t\right)=\sqrt{{\left(\mathrm{real}\left(w\left(t\right)\right)\right)}^2+{\left(\mathrm{imag}\left(w\left(t\right)\right)\right)}^2}$

Obtain each passage EEG signals EEG like this _i(t), i=1,2 ..., L (L is a port number) is at [f _L, f _H] instantaneous amplitude A on the frequency range _i(t) and phase information

Confirm in the step (3) that the concrete steps of interchannel synchronous intensity are following in twos on the designated frequency band: two passages of the synchronous intensity of set-up and calculated are respectively EEG _i(t) and EEG _j(t), i, j=1,2 ..., L; I ≠ j, corresponding instantaneous amplitude A _i(t), A _j(t) and phase information

Phase contrast is defined as so

Definition Phase synchronization intensity factor

Wherein, M is a signal length, considers the influence of amplitude, and it is following to define synchronous intensity factor again:

${\mathrm{IPSI}}_{\mathrm{ij}}=\frac{<A_i\left(t\right)>+<A_j\left(t\right)>}{2}\&CenterDot;{\mathrm{PSI}}_{\mathrm{ij}}$

Wherein,<>Average on the express time, with its normalization, obtain nIPSI _Ij:

${\mathrm{nIPSI}}_{\mathrm{ij}}=\frac{{\mathrm{IPSI}}_{\mathrm{ij}}}{\underset{i,j,i\&NotEqual;j}{\max }\left({\mathrm{IPSI}}_{\mathrm{ij}}\right)}$

With nIPSI _IjArrange according to matrix form, the position of i=j wherein, promptly the element on the diagonal of matrix all gets 0, obtains interchannel in twos cogradient matrix on this frequency range

The concrete steps of confirming the brain source location matrix on each designated frequency band in the step (4) are following: along with the passing of moving window, can obtain the interchannel in twos cogradient matrix E on this designated frequency band on each time period _k[i, j], k represent the time hop count k=1 that chooses, 2 ..., K; The meansigma methods of getting last cogradient matrix of all time periods is as the brain source location matrix E on the designated frequency band _Ave[i, j], $E_{\mathrm{Ave}}[i,j]=\frac{1}{K}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{E}_k[i,j];$

Confirm each passage and other all interchannel average strength S synchronously in the step (5) _i, $S_i=\frac{1}{L-1}\underset{j=1,j\&NotEqual;i}{\overset{L}{\mathrm{\&Sigma;}}}{\left(E_{\mathrm{Ave}}\right)}_{\mathrm{Ij}}.$

Finally utilize image processing techniques, the average strength S synchronously of each passage is presented on the X-Y scheme.

The present invention compared with prior art, its advantage comprises:

(1) the present invention utilizes humorous wavelet transformation to extract the prompting message on the required frequency range of multichannel brain signal of telecommunication meaning in office, lays the foundation for further calculating synchronously, makes that simultaneously on a plurality of frequency ranges, analyzing the brain source becomes possibility;

(2) the present invention proposes improved phase synchronization method as a kind of new synchronous intensity factor; Calculate interchannel in twos synchronous intensity matrix at different frequency range; And then obtain near the brain region of each electrode and other interregional total intensity indexs synchronously, be used to identify the zone in brain source.

Description of drawings

Fig. 1 is a workflow sketch map of the present invention.

The multichannel brain signal of telecommunication that Fig. 2 gathers for scalp is the cerebration sync period between two vertical dotted lines wherein.

Fig. 3 is the positioning result in brain source.First row from left to right is respectively an interchannel in twos synchronizing information matrix on the different frequency range (θ (4-8Hz), α (8-12Hz), β (12-30Hz), γ (30-80Hz)); Second row is each brain electric channel and all other interchannel average intensity synchronously on the different frequency range; Last column is that each passage on the different frequency range and all other interchannel average intensity synchronously are presented at the result on the X-Y scheme.

The specific embodiment

Device of the present invention at first is to gather EEG signals.The collection of EEG signals is accomplished by eeg signal acquisition equipment; The special Ag/AgCl electrode of general employing; Perhaps existing proprietary electrode for encephalograms medicated cap; Cooperate eeg amplifier to obtain EEG signals, convert the brain electric analoging signal that obtains to digital signal through A/D converter then, and with the digital signal input processor.Present embodiment is a long-time scalp EEG signal record, and is as shown in Figure 2.When gathering EEG signals, the electrode putting position leads according to the 10-20 international standard, and other adds two electrode T1, the T2 of temples.Sample frequency f _s=250Hz adopts average reference electrode recording mode.Signal through the 0.5-80Hz bandpass filtering, is removed noise jamming.Fig. 1 is a workflow diagram of the present invention, and the step of processor processes EEG signals is following:

Step 1 adopts the moving window technology that selected EEG signals data are carried out segment processing.Selecting every segment length is 4 seconds, and 50% overlaps.

Step 2; To every segment signal; Utilize humorous wavelet transformation, extract instantaneous amplitude and phase information on θ (4-8Hz), α (8-12Hz), β (12-30Hz), γ (30-80Hz) frequency range, present embodiment is that example is to calculate the synchronous intensity between the passage in twos with θ (4-8Hz) frequency range.

Step 3 based on the instantaneous amplitude and the phase information of each passage EEG signals on θ (4-8Hz) frequency range, is calculated interchannel in twos synchronous intensity.Suppose that wherein two passages that will calculate synchronous intensity are respectively EEG _i(t) and EEG _j(t), i, j=1,2 ..., L; I ≠ j promptly is total up to L passage, and the phase information on the frequency range that two passages of this that calculate extract does

With Amplitude information is A _i(t) and A _j(t).Utilize formula (5) to calculate phase contrast

And then application of formula (6) is calculated two interchannel Phase synchronization factor PSI _IjBut the factor of amplitude is not taken into account, the synchronous intensity factor IPSI of application of formula (7) computed improved _Ij, because each element IPSI _IjValue not between 0-1, utilize wherein maximum element, with each element normalization, obtain ${\mathrm{NIPSI}}_{\mathrm{Ij}}=\frac{{\mathrm{IPSI}}_{\mathrm{Ij}}}{\underset{i,j,i\&NotEqual;j}{\mathrm{Max}}\left({\mathrm{IPSI}}_{\mathrm{Ij}}\right)}.$

With nIPSI _IjArrange according to matrix form, the position of i=j wherein, promptly the element on the diagonal of matrix all gets 0, obtains interchannel in twos cogradient matrix on this frequency range

Step 4, along with sliding window is passed, but repeating step 2 and 3 calculate a plurality of interchannel in twos cogradient matrix E on each time period, θ (4-8Hz) frequency range _k[i, j], k represent the time hop count k=1 that chooses, 2 ... The EEG signals length overall that K, present embodiment choose is 1min, i.e. 60s, and selecting every segment length is 4 seconds, 50% overlaps; Promptly the 1st time period was 0-4s, and the 2nd time period was 2-6s, and the 3rd time period was 4-8s, and the like, the final time section is 56-60s; Be 29 sections altogether, so K=29, on θ (4-8Hz) frequency range, the interchannel in twos cogradient matrix from the 1st time period to last the 29th time period is respectively E like this ₁[i, j], E ₂[i, j] ... E ₂₉[i, j].Consider the intersegmental property of there are differences of each minute, get the meansigma methods of last cogradient matrix of all time periods, as the brain source location matrix E on this designated frequency band _Ave[i, j],

The brain source location matrix that uses the same method and can obtain other several frequency ranges shown in Fig. 3 first row, from left to right is respectively interchannel in twos brain source location matrix E on the different frequency range (θ, α, β, γ) _Ave[i, j].

Step 5 is based on interchannel in twos brain source location matrix E on each frequency range _Ave[i, j] utilizes formula (9), calculates each passage and other all interchannel average strength S synchronously _i, promptly each electrode place brain scalp region and other interregional synchronicitys are big or small.Like each brain electric channel of Fig. 3 second behavior different frequency range (θ, α, β, γ) and all other interchannel average intensity synchronously.

In order to show result of calculation more intuitively, with the synchronicity size of each passage, utilize image processing techniques, be presented on the relevant position of big brain mapping.Shown in Fig. 3 last column, be the synchronous intensity result of calculation of each passage on the different frequency range.

Fig. 3 is the positioning result in brain source.First row from left to right is respectively an interchannel in twos brain source location matrix on the different frequency range (θ (4-8Hz), α (8-12Hz), β (12-30Hz), γ (30-80Hz)); When interchannel synchronous intensity is big more, the color of figure is dark more; Compare 4 kinds of different frequency bands, there is certain difference in brain source location matrix.Second row is other interchannel average intensity synchronously of each brain electric channel and all on the different frequency range, can find that different passages under the different frequency bands are to whole synchronous influence degree.Last column is that each passage on the different frequency range and all other interchannel average intensity synchronously are presented at the result on the X-Y scheme, and by comparison, brain source (color is deep) concentrated the front portion that is distributed in right brain.

Claims (10)

1. the source location device that beats one's brains certainly comprises

Eeg signal acquisition equipment is used to gather original EEG signals;

A/D converter will be simulated the accurate digital signal that changes into of EEG signals;

The EEG signals amplifier is used for EEG signals are amplified;

It is characterized in that, also comprise the EEG Processing device, the EEG Processing device is at first with the EEG signals segmentation; Extract instantaneous amplitude and the phase information of the multichannel brain signal of telecommunication on designated frequency band then; Confirm interchannel in twos synchronous intensity on the designated frequency band then; Confirm the brain source location matrix on each designated frequency band; Confirm the average intensity synchronously of each passage and other all interchannels at last; Average intensity synchronously is used for weighing near the brain region of this electrode and the power of other interregional synchronicitys, and numerical value is big more, and then synchronicity is strong more, and expression might be the brain source region more.

2. a kind of source location device that beats one's brains certainly according to claim 1 is characterized in that the EEG signals segmentation adopts the moving window technology to carry out segment processing.

3. a kind of source location device that beats one's brains certainly according to claim 1 is characterized in that, utilizes humorous wavelet transformation to extract instantaneous amplitude and phase information on the designated frequency band.

4. a kind of source location device that beats one's brains certainly according to claim 3 is characterized in that instantaneous amplitude and the phase information concrete steps of utilizing humorous wavelet transformation to extract on the designated frequency band are following: sets frequency range to be investigated and is [fL, fH],

Humorous small echo has compact frequency domain representation form, and it is defined as

$H_{m,n}\left(w\right)=\left\{\begin{array}{cc}\frac{1}{(n-m)2\mathrm{\&pi;}}& m2\mathrm{\&pi;}\&le;w\&le;n2\mathrm{\&pi;}\\ 0& \mathrm{elsewhere}\end{array}\right.$

Wherein, m and n are scale parameters; Humorous wavelet transformation utilizes fast Fourier transform to realize, this algorithm was accomplished through three steps: (a) treat processing signals x (t) and carry out Fourier transform, obtain its frequency spectrum X (w); (b) with X (w) with (m, n) conjugate multiplication of the box-like spectrum H (w) of humorous small echo on the yardstick obtains W (w); Required frequency range [f _L, f _H] following with the relation of scale parameter m, n:

$m=f_L\&CenterDot;\frac{N}{f_s}$

$n=f_H\&CenterDot;\frac{N}{f_s}$

Wherein, f _sBe sample frequency, N is counting of Fourier transformation; (c) W (w) is carried out inverse fourier transform, promptly obtain humorous wavelet conversion coefficient w (t), this coefficient is a plural number, and its imaginary part is the Hilbert conversion of real part, and its instantaneous phase can be calculated as follows:

φ(t)=tan ^-1(imag(w(t))/real(w(t)))

Instantaneous amplitude does

$A\left(t\right)=\sqrt{{\left(\mathrm{real}\left(w\left(t\right)\right)\right)}^2+{\left(\mathrm{imag}\left(w\left(t\right)\right)\right)}^2}$

Obtain each passage EEG signals EEG like this _i(t), i=1,2 ..., L, L is a port number, at [f _L, f _H] instantaneous amplitude A on the frequency range _i(t) and phase information

5. according to claim 4 a kind of from beating one's brains the source location device, it is characterized in that confirm that the concrete steps of interchannel synchronous intensity are following in twos on the designated frequency band: two passages of the synchronous intensity of set-up and calculated are respectively EEG _i(t) and EEG _j(t), i, j=1,2 ..., L; I ≠ j, corresponding instantaneous amplitude A _i(t), A _j(t) and phase information

Phase contrast is defined as so

Definition Phase synchronization intensity factor

Wherein, M is a signal length, considers the influence of amplitude, and it is following to define synchronous intensity factor again:

${\mathrm{IPSI}}_{\mathrm{ij}}=\frac{<A_i\left(t\right)>+<A_j\left(t\right)>}{2}\&CenterDot;{\mathrm{PSI}}_{\mathrm{ij}}$

Wherein,<>Average on the express time, with its normalization, obtain nIPSL _Ij:

${\mathrm{nIPSI}}_{\mathrm{ij}}=\frac{{\mathrm{IPSI}}_{\mathrm{ij}}}{\underset{i,j,i\&NotEqual;j}{\max }\left({\mathrm{IPSI}}_{\mathrm{ij}}\right)}$

With nIPSI _IjArrange according to matrix form, the position of i=j wherein, promptly the element on the diagonal of matrix all gets 0, obtains interchannel in twos cogradient matrix on this frequency range

The concrete steps of confirming the brain source location matrix on each designated frequency band are following: along with the passing of moving window, can obtain the interchannel in twos a plurality of cogradient matrix E on this designated frequency band on each time period _k[i, j], k represent the time hop count k=1 that chooses, 2 ..., K; The meansigma methods of getting last cogradient matrix of all time periods is as the brain source location matrix E on the designated frequency band _Ave[i, j], $E_{\mathrm{Ave}}[i,j]=\frac{1}{K}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{E}_k[i,j];$

Confirm each passage and other all interchannel average strength S synchronously _i,

6. the source location method that beats one's brains certainly is characterized in that, may further comprise the steps:

(1) EEG signals segmentation;

(2) extract instantaneous amplitude and the phase information of the multichannel brain signal of telecommunication on designated frequency band;

(3) confirm interchannel in twos synchronous intensity on the designated frequency band;

(4) confirm brain source location matrix on each designated frequency band;

(5) confirm the average intensity synchronously of each passage and other all interchannels; Average intensity synchronously is used for weighing near the brain region of this electrode and the power of other interregional synchronicitys, and numerical value is big more, and then synchronicity is strong more, and expression might be the brain source region more.

7. a kind of source location method that beats one's brains certainly according to claim 1 is characterized in that EEG signals segmentation in the said step (1) adopts the moving window technology to carry out segment processing.

8. a kind of source location method that beats one's brains certainly according to claim 1 is characterized in that, utilizes humorous wavelet transformation to extract instantaneous amplitude and phase information on the designated frequency band in the said step (2).

9. a kind of source location method that beats one's brains certainly according to claim 8 is characterized in that instantaneous amplitude and the phase information concrete steps of utilizing humorous wavelet transformation to extract on the designated frequency band are following: set frequency range to be investigated and be [f _L, f _H],

Humorous small echo has compact frequency domain representation form, and it is defined as

$H_{m,n}\left(w\right)=\left\{\begin{array}{cc}\frac{1}{(n-m)2\mathrm{\&pi;}}& m2\mathrm{\&pi;}\&le;w\&le;n2\mathrm{\&pi;}\\ 0& \mathrm{elsewhere}\end{array}\right.$

Wherein, m and n are scale parameters; Humorous wavelet transformation utilizes fast Fourier transform to realize, this algorithm was accomplished through three steps: (a) treat processing signals x (t) and carry out Fourier transform, obtain its frequency spectrum X (w); (b) with X (w) with (m, n) conjugate multiplication of the box-like spectrum H (w) of humorous small echo on the yardstick obtains W (w); Required frequency range [f _L, f _H] following with the relation of scale parameter m, n:

$m=f_L\&CenterDot;\frac{N}{f_s}$

$n=f_H\&CenterDot;\frac{N}{f_s}$

Wherein, f _sBe sample frequency, N is counting of Fourier transformation; (c) W (w) is carried out inverse fourier transform, promptly obtain humorous wavelet conversion coefficient w (t), this coefficient is a plural number, and its imaginary part is the Hilbert conversion of real part, and its instantaneous phase can be calculated as follows:

φ(t)=tan ^-1(imag(w(t))/real(w(t)))

Instantaneous amplitude does

$A\left(t\right)=\sqrt{{\left(\mathrm{real}\left(w\left(t\right)\right)\right)}^2+{\left(\mathrm{imag}\left(w\left(t\right)\right)\right)}^2}$

Obtain each passage EEG signals EEG like this _i(t), i=1,2 ..., L, L is a port number, at [f _L, f _H] instantaneous amplitude A on the frequency range _i(t) and phase information

10. a kind of source location method that beats one's brains certainly according to claim 9 is characterized in that confirm in the step (3) that the concrete steps of interchannel synchronous intensity are following in twos on the designated frequency band: two passages of the synchronous intensity of set-up and calculated are respectively EEG _i(t) and EEG _j(t), i, j=1,2 ..., L; I ≠ j, corresponding instantaneous amplitude A _i(t), A _j(t) and phase information

Phase contrast is defined as so

Definition Phase synchronization intensity factor

Wherein, M is a signal length, considers the influence of amplitude, and it is following to define synchronous intensity factor again:

${\mathrm{IPSI}}_{\mathrm{ij}}=\frac{<A_i\left(t\right)>+<A_j\left(t\right)>}{2}\&CenterDot;{\mathrm{PSI}}_{\mathrm{ij}}$

Wherein,<>Average on the express time, with its normalization, obtain nIPSL _Ij:

${\mathrm{nIPSI}}_{\mathrm{ij}}=\frac{{\mathrm{IPSI}}_{\mathrm{ij}}}{\underset{i,j,i\&NotEqual;j}{\max }\left({\mathrm{IPSI}}_{\mathrm{ij}}\right)}$

With nIPSI _IjArrange according to matrix form, the position of i=j wherein, promptly the element on the diagonal of matrix all gets 0, obtains interchannel in twos cogradient matrix on this frequency range

The concrete steps of confirming the brain source location matrix on each designated frequency band in the step (4) are following: along with the passing of moving window, can obtain a plurality of interchannel in twos cogradient matrix E on this designated frequency band on each time period _k[i, j], k represent the time hop count k=1 that chooses, 2 ..., K; The meansigma methods of getting last cogradient matrix of all time periods is as the brain source location matrix E on the designated frequency band _Ave[i, j],

Confirm each passage and other all interchannel average strength S synchronously in the step (5) _i, $S_i=\frac{1}{L-1}\underset{j=1,j\&NotEqual;i}{\overset{L}{\mathrm{\&Sigma;}}}{\left(E_{\mathrm{Ave}}\right)}_{\mathrm{Ij}}.$

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