CN109758144A - A method of brain function variation tendency is determined based on EEG signals - Google Patents
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Abstract
The present invention provides a kind of method for determining brain function variation tendency based on EEG signals, comprising: utilizes EEG signals acquisition device, obtains subject respectively in the EEG signals of first time and the second time；Determine the EEG signals corresponding brain early period association map with subject in first time；Determine the EEG signals corresponding later period brain association map with subject in the second time；It compares the brain early period association map and is associated with map with the later period brain, determine brain function variation tendency of the subject within the first time and described second time in this period.Method proposed by the present invention, consistency is good, and accuracy is high.
Description
Technical field
The present invention relates to EEG Processing technical fields, and in particular to a kind of to determine that brain function changes based on EEG signals
The method of trend.
Background technique
EEG signals have it is non-stationary, compared with characteristics such as strong background noises, the analysis and processing of EEG signals belong to more
Section's crossing research analyzes it more difficult with processing.
By scale count etc. means, from EEG signals extract characteristic information after brain function is evaluated, exist with
Lower two disadvantages:
One, there are one-sidedness, consistency is poor.
Two, quantization degree is insufficient, is affected by subjective factor.
Summary of the invention
The present invention proposes a kind of method for determining brain function variation tendency based on EEG signals, is commented with solving current brain function
The problem that valence method subjectivity is strong, accuracy is insufficient.
The present invention provides a kind of methods for determining brain function variation tendency based on EEG signals, comprising the following steps:
Step S1: utilizing EEG signals acquisition device, obtains subject respectively in the brain telecommunications of first time and the second time
Number, wherein at the first time before the second time, the second time and first time are apart from preset time interval；
Step S2: the EEG signals corresponding brain early period association map with subject in first time is determined；Determining and quilt
It tries to be associated with map in the corresponding later period brain of the EEG signals of the second time；
Step S3: comparison brain early period association map be associated with map with later period brain, determines subject at the first time with the
Brain function variation tendency in two times in this period.
Specifically,
EEG signals acquisition device includes 37 crosslinking electrode caps and eeg signal acquisition processing system；
When obtaining EEG signals, EEG signals are obtained from 37 crosslinking electrode caps using eeg signal acquisition processing system,
It wherein, include multiple groups eeg data in EEG signals, each group of eeg data is opposite with an electrode in 37 crosslinking electrode caps
It answers.
Specifically,
It determines that corresponding brain early period of EEG signals with subject in first time is associated with map, or determines and be tested the
The corresponding later period brain of the EEG signals of two times is associated with map, comprising:
According to the electrode in 37 crosslinking electrode caps respectively to be arranged on subject head, positional relationship when being tested head is set,
Generate brain network, wherein the node in brain network is corresponding with the electrode in 37 crosslinking electrode caps；
Coherence analysis is carried out to the eeg data in EEG signals, determines wantonly two groups of eeg datas in preassigned frequency
Coherent value at point is association of corresponding two electrodes of wantonly two groups of eeg datas between two nodes in brain network
Degree；
The degree of association between the node of brain network is mapped as to preset the straight line of color according to numerical values recited, and
It is arranged between two nodes of brain network, forms brain and be associated with map.
Specifically,
Comparison brain early period association map be associated with map with later period brain, determine subject at the first time and the second time this
Brain function variation tendency in one period, comprising:
The color difference comparison of map is associated with later period brain according to brain early period association map, determines the association between each node
Degree is increase, reduction or constant；
According to the degree of association variation tendency between whole nodes, determine subject at the first time and the second time this when
Brain function variation tendency in phase is enhancing, decrease or constant.
Specifically, coherence analysis uses following formula:
Wherein, CXY(f) it is cross-spectrum between x (t) and y (t)；CXX(f) be x (t) by Fourier transformation obtain from
Spectrum；CYYIt (f) is that y (t) is composed certainly by what Fourier transformation obtained；Respectively synchronously collected two groups of brains are electric by x (t) and y (t)
Data.
Specifically, after coherence analysis, determine that coherent value of the wantonly two groups of eeg datas at 10Hz Frequency point is wantonly two groups of brains
The degree of association of corresponding two electrodes of electric data between two nodes in brain network.
Specifically, brain network is the brain node topology figure of ideal hemisphere.
Specifically, when obtaining EEG signals using eeg signal acquisition processing system, setting sample frequency is 1000Hz,
The passband of bandpass filter is 0.05~50Hz.
Specifically, also synchronous when obtaining EEG signals from 37 crosslinking electrode caps using eeg signal acquisition processing system
Ground obtains from 37 crosslinking electrode caps and refers to electro-ocular signal；
Correspondingly, EEG signals acquisition device further includes EEG Processing software；
After obtaining EEG signals using eeg signal acquisition processing system, reference is combined using EEG Processing software
Electro-ocular signal carries out de-noising to EEG signals, the EEG signals after obtaining de-noising.
It specifically, include alpha E.E.G and gamma E.E.G in EEG signals.
The method provided by the invention for determining brain function variation tendency based on EEG signals, by the position of electrode in brain electricity cap
Relationship is combined with multiple groups EEG signals, determines the multidimensional incidence relation between the EEG signals obtained；It is closed based on this multidimensional
Connection relationship, determines variation tendency of the brain function in different times of subject, and then can complete the evaluation to subject brain function.
The method proposed by the present invention for determining brain function variation tendency based on EEG signals, based on to electroencephalogramsignal signal analyzing brain
Changes of function trend gets rid of the limitation for carrying out brain function analysis in conventional method from single angle.With traditional usage amount
Table point system is compared, the method proposed by the present invention for determining brain function variation tendency based on EEG signals, easy to operate, consistency
Good, accuracy is high, more objective and scientific.
Detailed description of the invention
By reference to the following drawings, exemplary embodiments of the present invention can be more fully understood by:
Fig. 1 is the process signal of the method that brain function variation tendency is determined based on EEG signals of one embodiment of the invention
Figure；
Fig. 2 is that another of the invention embodiment based on EEG signals determines that the process of method of brain function variation tendency is shown
It is intended to；
Fig. 3 is the schematic diagram of the collected 37 lead eeg data of one embodiment of the invention；
Fig. 4 is that the brain for the alpha E.E.G that subject executes enhancing brain function movement front and back in one embodiment of the invention closes
Join map schematic diagram；
Fig. 5 is that the brain for the gamma E.E.G that subject executes enhancing brain function movement front and back in one embodiment of the invention closes
Join map schematic diagram；
Fig. 6 is the schematic diagram of a scenario of the acquisition eeg data of one embodiment of the invention.
Specific embodiment
Exemplary embodiments of the present invention are introduced referring now to the drawings, however, the present invention can use many different shapes
Formula is implemented, and is not limited to the embodiment described herein, and to provide these embodiments be at large and fully disclose
The present invention, and the scope of the present invention is sufficiently conveyed to person of ordinary skill in the field.Show for what is be illustrated in the accompanying drawings
Term in example property embodiment is not limitation of the invention.In the accompanying drawings, identical cells/elements use identical attached
Icon note.
Unless otherwise indicated, term (including scientific and technical terminology) used herein has person of ordinary skill in the field
It is common to understand meaning.Further it will be understood that with the term that usually used dictionary limits, should be understood as and its
The context of related fields has consistent meaning, and is not construed as Utopian or too formal meaning.
The analyses of EEG signals and processing belong to interdisciplinary research, with it is non-stationary, compared with strong background noise etc.
Characteristic, thus it is more difficult to the analysis of EEG signals and processing.With the development of science and technology, according to the peculiar of EEG signals
Property combines some new theory and technology means with the analysis of EEG signals processing, proposes a variety of different brain electricity
Signal analysis method, and be widely used and develop.
The method provided by the invention for determining brain function variation tendency based on EEG signals, by the position of electrode in brain electricity cap
Relationship is combined with multiple groups EEG signals, determines the multidimensional incidence relation between the EEG signals obtained；It is closed based on this multidimensional
Connection relationship, determines variation tendency of the brain function in different times of subject, and then can complete the evaluation to subject brain function.
As shown in Figure 1, the method for determining brain function variation tendency based on EEG signals of the present embodiment, comprising:
Step S1: utilizing EEG signals acquisition device, obtains subject respectively in the brain telecommunications of first time and the second time
Number, wherein at the first time before the second time, the second time and first time are apart from preset time interval；
Step S2: the EEG signals corresponding brain early period association map with subject in first time is determined；Determining and quilt
It tries to be associated with map in the corresponding later period brain of the EEG signals of the second time；
Step S3: comparison brain early period association map be associated with map with later period brain, determines subject at the first time with the
Brain function variation tendency in two times in this period.
Specifically, EEG signals acquisition device includes 37 crosslinking electrode caps, eeg signal acquisition processing system
Neuroscan；
When obtaining EEG signals, obtained using eeg signal acquisition processing system Neuroscan from 37 crosslinking electrode caps
EEG signals, wherein it include multiple groups eeg data in EEG signals, one in each group of eeg data and 37 crosslinking electrode caps
Electrode is corresponding.
It is construed as, can according to need, the electrode number on subject scalp is flexibly set.Specifically, electric
Number of poles mesh is not more than 30.
Preferably, when obtaining EEG signals using eeg signal acquisition processing system Neuroscan, sample frequency is set
For 1000Hz, the passband of bandpass filter is 0.05~50Hz.
Preferably, EEG signals are being obtained from 37 crosslinking electrode caps using eeg signal acquisition processing system Neuroscan
When, it is also synchronously obtained from 37 crosslinking electrode caps and refers to electro-ocular signal；
Correspondingly, EEG signals acquisition device further includes EEG Processing software Curry；
It is soft using EEG Processing after obtaining EEG signals using eeg signal acquisition processing system Neuroscan
Part Curry, which is combined, carries out de-noising to EEG signals with reference to electro-ocular signal, the EEG signals after obtaining de-noising.
It is construed as, includes multiple groups in the EEG signals at the first time or after the corresponding de-noising of the second time with subject
Eeg data, each group of eeg data are corresponding with an electrode in 37 crosslinking electrode caps.
It is construed as, includes a variety of brain wave ingredients in the EEG signals after de-noising, such as alpha E.E.G, gamma E.E.G
Deng.
Specifically, it is determined that corresponding brain early period of EEG signals with subject in first time is associated with map, or, determine with
It is tested the corresponding later period brain of EEG signals in the second time and is associated with map, comprising:
According to the electrode in 37 crosslinking electrode caps respectively to be arranged on subject head, positional relationship when being tested head is set,
Generate brain network, wherein the node in brain network is corresponding with the electrode in 37 crosslinking electrode caps；
Coherence analysis is carried out to the eeg data in EEG signals, determines wantonly two groups of eeg datas in preassigned frequency
Coherent value at point is association of corresponding two electrodes of wantonly two groups of eeg datas between two nodes in brain network
Degree；
The degree of association between the node of brain network is mapped as to preset the straight line of color according to numerical values recited, and
It is arranged between two nodes of brain network, forms brain and be associated with map.
Specifically, coherence analysis uses following formula:
Wherein, CXY(f) it is cross-spectrum between x (t) and y (t)；CXX(f) be x (t) by Fourier transformation obtain from
Spectrum；CYYIt (f) is that y (t) is composed certainly by what Fourier transformation obtained；Respectively synchronously collected two groups of brains are electric by x (t) and y (t)
Data.
The brain network that brain network is abstracted as ideal hemisphere, the topology between node are shown in Fig. 4 and Fig. 5
Constitute brain network.It is construed as, it, can also be using other solids or ratio according to the needs that image viewing is shown
Relationship indicates the brain network.
Specifically, comparison brain early period association map be associated with map with later period brain, determines subject at the first time with the
Brain function variation tendency in two times in this period, comprising:
The color difference comparison of map is associated with later period brain according to brain early period association map, determines the association between each node
Degree is increase, reduction or constant；
According to the degree of association variation tendency between whole nodes, determine subject at the first time and the second time this when
Brain function variation tendency in phase is enhancing, decrease or constant.
It is construed as, within first time and the second time in this period, subject, which can execute, such as to be practised the qigong, practises
Practice square dance, body-building, jogging, climb the mountain etc. is intended to enhance the movement (namely brain function drill program) of brain function.
When it is implemented, as shown in Fig. 2, based on the method that EEG signals determine brain function variation tendency, including following step
It is rapid:
The relative position between scalp electrode is chosen as the data source for determining brain network node topology, and determines brain
The coherence analysis result of electric signal is the Measure Indexes of brain function；Secondly, to the association between the brain network node of graph of building
Feature is for statistical analysis, to compare the brain function variation tendency that subject executes brain function enhancing movement front and back.
Specifically, using following hardware and software device: 37 lead brain electricity cap, eeg signal acquisition processing system (Neuroscan)
And its subsidiary EEG Processing software Curry7, Matlab2014b software and the brain function write based on Matlab are connected
Analyze program.
Specifically, 37 to lead brain electricity cap include 30 for the electrodes of scalp to be arranged in, and is respectively used to be arranged after the ear of left and right
2 reference electrodes, 4 eye electricity electrodes and 1 grounding electrode.Specifically, EEG signals are acquired using following steps, to obtain
Test data:
(1) experimental situation: experiment is carried out in quiet environment, and e.g., the air-conditioned room for selecting sound-proofing strong is test room, control
Room temperature processed is 22-26 DEG C, indoor relative humidity 25-40%.Main examiner person and subject are turned off mobile phone.After test starts, remove
Test is abnormal outer, main examiner person and tested no talk.
(2) prepare before brain electrical testing: subject has cleaned scalp drying hair before testing.Main examiner person first check for by
The hair humidity of examination；After determining hair dryer, subject and main examiner person enter test room, are seated at comfortable soft chair
On.
A. main examiner removes the skin keratin on each auxiliary electrode point with scrub cream, and auxiliary electrode includes: VEOU, is set to
1cm on left eyebrow；
VEOL is set to 1cm under left eye, can recorde to obtain vertical eye electricity by VEOU and VEOL；
HEOR is set to by right eye outer canthus at 1cm；
HEOL is set to by left eye outer canthus at 1cm, can recorde to obtain horizontal eye electricity by HEOR and HEOL.
Main examiner removes the skin keratin on each reference electrode with scrub cream, and reference electrode includes: A1, A2, wherein A1,
A2 is located at bilateral mastoid process after ear；
It is construed as, above each reference electrode and each auxiliary electrode are the attachment of 37 crosslinking electrode caps.
B. main examiner person is 37 crosslinking electrode cap of subject wears, determines that lead PZ face crown median line and two have sharp ears connect
The Baihui acupoint of the intersection point of line；
To after reference electrode and auxiliary electrode injection conductive paste, the corresponding of the tested Head And Face of aforementioned setting is sticked at adhesive plaster
Position, after adjustment thread gluing keeps subject perception comfortable, injection conductive paste is between scalp and electrode, making each electrode point impedance drop
To 5 kilo-ohms or less.
It should be noted that the purpose of injection conductive paste is to reduce impedance；If impedance in 20 minutes can not be dropped also, explanation
Brain electricity cap or other equipment are problematic.By the way that the time is arranged, can effectively device for transferring or line fault, guarantee brain electricity cap
The effective electrical potential information at scalp can be collected.
(3) eeg signal acquisition: before test starts, main examiner person fills in record sheet, main examination, subject's signature.
The brain wave acquisition device and its subsidiary EEG Processing software produced using Neuroscan company, the U.S.
Curry7 carries out the acquisition of EEG signals, and setting sample rate is 1000S/s, and filtering band logical is 0.05~50Hz, and two main examinations exist
Subject starts to acquire EEG signals after entering state, and acquisition scene is as shown in Figure 6.
The one group of EEG signals collected are as shown in Figure 3.
Specifically, data prediction is carried out using following steps:
It is filtered using EEG signals of the Curry7 software to acquisition, eliminates the pre- place such as eye electricity artefact noise in brain electricity
Reason removes the noise in EEG signals.
The step of analyzing the EEG signals after de-noising is as follows:
If two between EEG signals x (t) and y (t) there are incidence relation, both coherent calculation it is as follows:
In above formula, CXY(f) it is cross-spectrum between x (t) and y (t)；CXX(f) be x (t) by Fourier transformation obtain from
Spectrum；CYYIt (f) is that y (t) is composed certainly by what Fourier transformation obtained.
Coherent calculation is carried out according to relevant formula in the eeg data for executing the acquisition of 37 leads；Take this Frequency point of 10Hz
Locate the coherent value of these eeg datas；It is drawn according to the coherence factor size between every two network node based on alpha E.E.G
Brain association map it is as shown in Figure 4.
Coherent calculation is carried out according to relevant formula to the eeg data that 37 leads obtain；Take at this Frequency point of 10Hz these
The coherent value of eeg data；The brain based on gamma E.E.G is drawn according to the coherence factor size between every two network node
It is as shown in Figure 5 to be associated with map.
In figures 4 and 5, bonding strength of the coherence factor greater than 0.7 is indicated with red；Green indicates that coherence factor exists
Bonding strength between 0.4~0.6；Black indicates connection of the bonding strength less than 0.4.
Fig. 4 (a) is the brain association map that subject executes the alpha E.E.G before enhancing brain function movement；Fig. 4 (b) is quilt
The brain that examination executes enhancing brain function post exercise alpha E.E.G is associated with map；Fig. 5 (a) is that subject executes enhancing brain function fortune
The E.E.G brain of gamma before dynamic is associated with map；Fig. 5 (b) is the E.E.G brain that subject executes enhancing brain function post exercise gamma
Portion is associated with map.
Figure 4, it is seen that in the brain association map of alpha E.E.G, before red line significantly more than practises the qigong, explanation
After practising the qigong, the brain internal energy of subject enhances；Full figure is made a general survey of, it can also be seen that before and after practising the qigong, alpha E.E.G
Connection between different zones node increases.
From figure 5 it can be seen that the accounting of the lines of each color is substantially without change in the brain association map of gamma E.E.G
Change, illustrate after practising the qigong, the unobvious setting of brain internal energy enhancing is constant；Full figure is made a general survey of, it can also be seen that practising the qigong
Front and back, connection of the gamma E.E.G between different zones node are basically unchanged.
The method for determining brain function variation tendency based on EEG signals, based on to electroencephalogramsignal signal analyzing brain function variation become
Gesture gets rid of the limitation for carrying out brain function analysis in conventional method from single angle.Scale point system phase is used with traditional
Than the method that should determine brain function variation tendency based on EEG signals, easy to operate, consistency is good, and accuracy is high, more objective
And science.
The present invention is described by reference to a small amount of embodiment above.However, it is known in those skilled in the art,
As defined by subsidiary Patent right requirement, in addition to the present invention other embodiments disclosed above equally fall in this hair
In bright range.
Normally, all terms used in the claims are all solved according to them in the common meaning of technical field
It releases, unless in addition clearly being defined wherein.All references " one // be somebody's turn to do [device, component etc.] " are explained with being all opened
For at least one example in device, component etc., unless otherwise expressly specified.The step of any method disclosed herein, does not all have
Necessity is run with disclosed accurate sequence, unless explicitly stated otherwise.
Claims (10)
1. a kind of method for determining brain function variation tendency based on EEG signals, which comprises the following steps:
Step S1: utilizing EEG signals acquisition device, obtains the EEG signals being tested in first time and the second time respectively,
In, the first time, second time and the first time were between the preset time before the second time
Every；
Step S2: the EEG signals corresponding brain early period association map with subject in first time is determined；It determines and exists with subject
The corresponding later period brain of the EEG signals of second time is associated with map；
Step S3: the brain early period association map is compared with the later period brain and is associated with map, determines the subject described
Brain function variation tendency in first time and described second time in this period.
2. the method according to claim 1, wherein
The EEG signals acquisition device includes 37 crosslinking electrode caps and eeg signal acquisition processing system；
When obtaining EEG signals, brain telecommunications is obtained from the 37 crosslinking electrode cap using the eeg signal acquisition processing system
Number, wherein including multiple groups eeg data in the EEG signals, in eeg data described in each group and the 37 crosslinking electrode cap
An electrode it is corresponding.
3. the method according to claim 1, wherein
EEG signals corresponding early period brain of the determination with subject in first time is associated with map, or determines with subject the
The corresponding later period brain of the EEG signals of two times is associated with map, comprising:
Positional relationship when being tested head is set according to the electrode in 37 crosslinking electrode caps respectively to be arranged on subject head, is generated
Brain network, wherein the node in the brain network is corresponding with the electrode in 37 crosslinking electrode caps；
Coherence analysis is carried out to the eeg data in the EEG signals, determines wantonly two groups of eeg datas in preassigned frequency
The coherent value at point place be described in two nodes of corresponding two electrodes of wantonly two groups of eeg datas in the brain network it
Between the degree of association；
The degree of association between the node of brain network is mapped as to preset the straight line of color according to numerical values recited, and is arranged
Between two nodes of the brain network, the brain association map is formed.
4. the method according to claim 1, wherein
The comparison brain early period association map is associated with map with the later period brain, determines the subject described first
Brain function variation tendency in time and described second time in this period, comprising:
The color difference comparison of map is associated with the later period brain according to brain early period association map, is determined between each node
The degree of association is increase, reduction or constant；
According to the degree of association variation tendency between whole nodes, determine subject the first time and second time this
Brain function variation tendency in one period is enhancing, decrease or constant.
5. according to the method described in claim 3, it is characterized in that,
The coherence analysis uses following formula:
Wherein, CXY(f) it is cross-spectrum between x (t) and y (t)；CXXIt (f) is that x (t) is composed certainly by what Fourier transformation obtained；CYY
It (f) is that y (t) is composed certainly by what Fourier transformation obtained；X (t) and y (t) are respectively synchronously collected two groups of eeg datas.
6. according to the method described in claim 5, it is characterized in that,
After coherence analysis, determine that coherent value of the wantonly two groups of eeg datas at 10Hz Frequency point is wantonly two groups of eeg datas pair
The degree of association of two electrodes answered between two nodes in the brain network.
7. according to the method described in claim 3, it is characterized in that,
The brain network is the brain node topology figure of ideal hemisphere.
8. according to the method described in claim 2, it is characterized in that,
When obtaining EEG signals using eeg signal acquisition processing system, setting sample frequency is 1000Hz, bandpass filter
Passband be 0.05~50Hz.
9. according to the method described in claim 2, it is characterized in that,
When obtaining EEG signals from the 37 crosslinking electrode cap using eeg signal acquisition processing system, also synchronously from described
37 crosslinking electrode caps, which obtain, refers to electro-ocular signal；
Correspondingly, the EEG signals acquisition device further includes EEG Processing software；
After obtaining EEG signals using eeg signal acquisition processing system, using the EEG Processing software in conjunction with described
De-noising is carried out to the EEG signals with reference to electro-ocular signal, the EEG signals after obtaining de-noising.
10. according to the method described in claim 2, it is characterized in that,
It include alpha E.E.G and gamma E.E.G in the EEG signals.
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