CN107510453A - A kind of prefrontal area brain electricity analytical method - Google Patents
A kind of prefrontal area brain electricity analytical method Download PDFInfo
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- CN107510453A CN107510453A CN201710949317.3A CN201710949317A CN107510453A CN 107510453 A CN107510453 A CN 107510453A CN 201710949317 A CN201710949317 A CN 201710949317A CN 107510453 A CN107510453 A CN 107510453A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
Abstract
The present invention is more particularly directed to a kind of prefrontal area brain electricity analytical method, obtains forehead benchmark EEG signals by test sample, and therefrom extract eye electrical noise average waveform.Remove using bandpass filtering and notch filter the high-frequency noise and Hz noise noise in brain electricity respectively in the real-time processing of eeg data, obtain the real-time initial filter EEG signals of forehead.Extracted according to default eye electrical noise amplitude threshold the blink cycle of the real-time initial filter EEG signals of forehead, and the noise jamming as caused by blink in the real-time initial filter EEG signals of forehead is offset using the method for superposition eye electrical noise average waveform.The prefrontal area brain electricity analytical method of the present invention, eye electricity acquisition electrode need not be set to carry out purifying denoising to the eeg data of single electrode, the signal to noise ratio of EEG signals can be improved, simultaneously because the method using advance extraction standard eye electrical waveform, the time of follow-up data processing is shortened, more meets the requirement of real-time.
Description
Technical field
The present invention relates to brain electricity analytical method, more particularly to a kind of prefrontal area brain electricity analytical method.
Background technology
Brain-computer interface equipment usually sets electrode in head part's prefrontal area, and being absorbed in for people is measured by the method for feature extraction
Degree.But the prefrontal area EEG signals that the lead of forehead brain area collects are highly prone to the interference of blink and are mixed into an electrical noise, lead
Cause the low signal to noise ratio of data, poor reliability, be difficult to extract feature.The removal of eye electrical noise relies on principal component analysis in the prior art
And Independent Component Analysis adds the complexity of equipment, it is necessary to individually set the eye electricity acquisition electrode around the eyes
Property, while the method for both denoisings is required to longer duration, it is difficult to meet the requirement of real-time.
The content of the invention
The defects of in order to overcome prior art, can be independent of eye electricity acquisition electrode it is an object of the invention to provide one kind
Brain electricity analytical method.
To achieve the above object, the present invention is achieved by the following technical solutions：A kind of prefrontal area brain electricity analytical method,
Comprise the steps：
Step 1, carry out test sample for forehead current potential and obtain T0 period forehead benchmark EEG signals, and from the forehead
Eye electrical noise average waveform is extracted in benchmark EEG signals；
Step 2, the real-time brain telecommunications of forehead of each sampled point m in the acquisition T1 periods of monitoring in real time is carried out for forehead current potential
Number, and the real-time EEG signals of the forehead are filtered by least one-level wave filter and acquire the real-time initial filter brain telecommunications of forehead
Number；
Step 3, it is determined that blink threshold value moment Tmp, by the real-time initial filter EEG signals sm of sampled point m forehead range value by
The moment where sampled point m is blink when being altered to be equal to default eye electrical noise amplitude threshold less than default eye electrical noise amplitude threshold
Threshold value moment Tmp, the period a before setting blink threshold value moment Tmp blinks the period as first, and sets the blink threshold value moment
Period b after Tmp was the second blink period, and the first blink period and the second blink period form a blink cycle；
Step 4, noise reduction process is carried out to the real-time initial filter EEG signals of forehead in the blink cycle, before in the blink cycle
The real-time initial filter EEG signals of volume and eye electrical noise average waveform are superimposed, balance out and are caused in the blink cycle due to blink
Noise jamming, so as to the real-time initial filter EEG signals of forehead after being corrected；And
Step 5, it is real-time using forehead in the real-time initial filter EEG signals replacement corresponding blink cycle of forehead after amendment
Initial filter EEG signals, so as to obtain real-time pure EEG signals curve.
Wherein, the step 1 further comprises following sub-steps：
Sub-step 1-1, carry out test sample for forehead current potential and obtain T0 period forehead benchmark EEG signals, before described
Volume benchmark EEG signals carry out bandpass filtering according to default eye electrical noise frequency range and obtain forehead benchmark initial filter electro-ocular signal；
Sub-step 1-2, by each data point amplitude xn of forehead benchmark initial filter EEG signals and default eye electrical noise amplitude
Threshold value is compared, when xn less than default eye electrical noise amplitude threshold by being altered to be equal to default eye electrical noise amplitude threshold,
The period a before the data point is set as the first test blink period, the period b after the data point is set and is tested for second and blinked
At the moment section, the first test blink period and the second test blink period form a test blink cycle, extract institute
It is the signal of blinking in the blink cycle to state the forehead benchmark initial filter EEG signals in the test blink cycle；
Sub-step 1-3, the signal of blinking in all blink cycles in the T0 periods is averaged, obtains an electrical noise average wave
Shape.
Wherein, at least one-level wave filter includes the low pass filter that one-level is used to remove high-frequency noise.
Wherein, when carrying out brain wave acquisition using AC-powered, at least one-level wave filter is also used for including one-level
The notch filter of Hz noise is removed, the trap frequency of the notch filter is identical with the frequency of the alternating current.
Wherein, the filtering upper limit of the low pass filter is 60Hz.
Wherein, the default eye electrical noise frequency range is 1-10Hz.
Wherein, the default eye electrical noise amplitude threshold is 100 microvolts, a length of 50 milliseconds during the continuity of the period a, institute
A length of 300 milliseconds are stated during period b continuity.
Wherein, a length of 30 seconds during the continuity of the T0 periods.
Step 3 and step 4 further comprise following sub-step：
Sub-step 3-4-1, by the real-time initial filter EEG signals of the forehead of each sampled point and default eye electrical noise amplitude threshold
It is compared, when the real-time initial filter EEG signals sm of sampled point m forehead range value is less than default eye electrical noise amplitude threshold,
Sub-step 3-4-2 is performed, when the real-time initial filter EEG signals sm of sampled point m forehead range value is more than default eye electrical noise amplitude
During threshold value, the moment where sampled point m corresponds to the threshold value moment Tmp that blinks, and performs sub-step 3-4-3；
Sub-step 3-4-2, enter row major using the real-time initial filter EEG signals sm of the forehead as primary pure EEG signals
Output, makes m=m+1 continue executing with step 3-4-1；And
Sub-step 3-4-3, eye electricity is carried out to the primary pure EEG signals in the first blink period a before sampled point m
Noise reduction amendment, the primary pure EEG signals that first was blinked in period a and the first blink of the eye electrical noise average waveform
Period is superimposed, so as to acquire the pure brain wave patterns of amendment between sampled point m-a to sampled point m；In blink threshold value moment Tmp
The real-time initial filter EEG signals of forehead in the second blink period b afterwards carry out eye electricity noise reduction, before in the second blink period b
The real-time initial filter EEG signals of volume are superimposed with the second blink period of the eye electrical noise average waveform, so as to acquire sampled point m
Exported to the pure brain wave patterns of amendment between sampled point m+b；The amendment integrated between sampled point m-a to sampled point m is pure
It is bent to obtain pure EEG signals in real time to the pure brain wave patterns of amendment between sampled point m+b for net brain wave patterns and sampled point m
Line, m=m+b+1 is made to perform sub-step 3-4-1.
Compared with prior art, the invention has the advantages that：
A kind of prefrontal area brain electricity analytical method of the present invention, can be in the case where being not provided with eye electricity acquisition electrode, to preceding
Mixed eye electrical noise is removed in frontal region EEG signals, removes high-frequency noise with reference to low pass filter, and filter using trap
Ripple device removes Hz noise, therefore the brain electricity analytical method of the present invention has the advantages of signal to noise ratio is high；Due to taking advance extraction
The method of eye electrical noise average waveform, reduce the computing capability requirement to follow-up real time data processing, it is possible to increase at data
The speed of reason, real-time is good, suitable popularization and application.
Brief description of the drawings
Fig. 1 is the brain wave acquisition equipment schematic diagram using the prefrontal area brain electricity analytical method of the present invention；
Fig. 2 is the flow chart using the prefrontal area brain electricity analytical method of the present invention；
Fig. 3 is the real-time EEG signals of forehead obtained using prefrontal area brain electricity analytical method of the present invention；
Fig. 4 is the blink cycle schematic diagram obtained using prefrontal area brain electricity analytical method of the present invention；
Fig. 5 is the eye electrical noise average waveform schematic diagram obtained using prefrontal area brain electricity analytical method of the present invention；
Fig. 6 is the schematic diagram of the real-time initial filter EEG signals of forehead obtained using prefrontal area brain electricity analytical method of the present invention；
And
Fig. 7 is to obtain reality using the real-time initial filter EEG signals of forehead after being corrected in prefrontal area brain electricity analytical method of the present invention
When pure EEG signals curve synoptic diagram.
Embodiment
Describe exemplary embodiment, feature and the aspect of the present invention in detail below with reference to accompanying drawing.In order to better illustrate
The present invention, numerous details is given in embodiment below.It will be appreciated by those skilled in the art that do not have
Some details, the present invention can equally be implemented.Do not retouched in detail for method well known to those skilled in the art, means
State, in order to highlight the purport of the present invention.
As shown in Figure 1 and Figure 2, the prefrontal area of an adult subjects is gathered using wearable brain wave acquisition equipment
EEG signals, the brain wave acquisition equipment include brain wave acquisition module, purification blocks and wireless communication module, the purification blocks
Denoising purifying is carried out to the EEG signals collected from the prefrontal area brain electricity analytical method of the present invention, then via wireless telecommunications
Module wirelessly exports.The brain wave acquisition module include a forehead electrode being placed at subject's F3 electrodes, be fixed on by
The left ear electrode of the left ear of examination person and the auris dextra electrode for being fixed on subject's auris dextra, and the skin for left ear electrode to be collected
Current potential refers to the skin potential that auris dextra electrode collects, the Scalp Potential that forehead electrode is collected as ground signalling
Signal is converted into the TGAM chips of forehead EEG signal output, and the forehead EEG signal is ordered respectively according to the period residing for it
The entitled forehead benchmark EEG signals positioned at initialization period and the real-time EEG signals of forehead positioned at the real-time collection period.
In use, data collection and analysis is carried out using following step 1 to step 5 altogether：
Step 1, brain wave acquisition equipment is initialized 30 seconds first, in this is 30 seconds, the brain wave acquisition module collection head
Skin current potential is simultaneously converted into forehead benchmark EEG signals and exported to initialization submodule, and the initialization submodule is from the forehead base
Eye electrical noise average waveform is extracted in quasi- EEG signals, specifically includes following sub-step 1-1 to sub-step 1-3：
Sub-step 1-1, bandpass filtering is carried out according to default eye electrical noise frequency range to the forehead benchmark EEG signals,
The bandpass filtering for carrying out 1-10Hz obtains forehead benchmark initial filter electro-ocular signal.
Sub-step 1-2, by each data point amplitude xn of forehead benchmark initial filter EEG signals and default eye electrical noise amplitude
Threshold value is compared, and the default eye electrical noise amplitude threshold is 100 microvolts.When xn is equal to 100 by being altered to less than 100 microvolts
During microvolt, as shown in figure 4,50 milliseconds before setting the data point blink the period for the first test, after setting the data point
300 milliseconds for second test blink the period, it is described first test blink the period and it is described second test blink the period form one
In the individual test blink cycle, it is blinking in the blink cycle to extract the forehead benchmark initial filter EEG signals in the test blink cycle
Eye signal.
Sub-step 1-3, the signal of blinking initialized in 30 seconds in all blink cycles is averaged, obtained as shown in Figure 5
Eye electrical noise average waveform, and preserve into the memory cell of amendment submodule.
Step 2, after the completion of initialization, real-time collection is proceeded by.The brain wave acquisition module continues to gather Scalp Potential,
Obtain each sampled point m real-time EEG signals of forehead as shown in Figure 3.In denoising submodule, by the real-time brain of the forehead
50Hz notch filter is carried out after the low pass filter progress LPF that electric signal passes through one-level 60Hz again, is acquired such as Fig. 6
The real-time initial filter EEG signals of shown forehead, due to only having done filtering process, the real-time initial filter EEG signals of the forehead now obtained
Sample rate it is identical with the real-time EEG signals of the forehead.
Step 3, real-time blink threshold value moment Tmp of the subject in the collection period in real time is determined, before each sampled point
The range value of the real-time initial filter EEG signals of volume is compared with 100 microvolts, when the width of the real-time initial filter EEG signals of the forehead
Value from when becoming higher than 100 microvolt less than 100 microvolts, definition now at the time of for blink threshold value moment Tmp, before corresponding Tmp
50 milliseconds of period was defined as the first blink period, and correspondingly 300 milliseconds of period was defined as the second blink period after Tmp, right
50 milliseconds to 300 milliseconds after Tmp before Tmp of period is answered to be defined as the blink cycle of this blink.
Step 4, noise reduction process is carried out to the real-time initial filter EEG signals of forehead in the blink cycle, before in the blink cycle
The real-time initial filter EEG signals of volume and correct submodule eye electrical noise average waveform it is superimposed, balance out it is described blink the cycle in by
In noise jamming caused by blink, so as to the real-time initial filter EEG signals of forehead after being corrected.
Step 5, it is real-time using forehead in the real-time initial filter EEG signals replacement corresponding blink cycle of forehead after amendment
Initial filter EEG signals, so as to obtain real-time pure EEG signals as shown in Figure 7, by it is described in real time pure EEG signals export to
Wireless communication module, and further spread out of by the way of wireless data transmission.
Finally it should be noted that：Above-described embodiments are merely to illustrate the technical scheme, rather than to it
Limitation；Although the present invention is described in detail with reference to the foregoing embodiments, it will be understood by those within the art that：
It can still modify to the technical scheme described in previous embodiment, or which part or all technical characteristic are entered
Row equivalent substitution；And these modifications or substitutions, the essence of appropriate technical solution is departed from various embodiments of the present invention technical side
The scope of case.
Claims (9)
- A kind of 1. prefrontal area brain electricity analytical method, it is characterised in that：Comprise the following steps：Step 1, carry out test sample for forehead current potential and obtain T0 period forehead benchmark EEG signals, and from the forehead benchmark Eye electrical noise average waveform is extracted in EEG signals；Step 2, the real-time EEG signals of forehead of each sampled point m in the acquisition T1 periods of monitoring in real time are carried out for forehead current potential, And the real-time EEG signals of the forehead are filtered by least one-level wave filter and obtain the real-time initial filter EEG signals of forehead；Step 3, it is determined that blink threshold value moment Tmp, by the real-time initial filter EEG signals s of sampled point m foreheadmRange value by less than The moment where sampled point m is blink threshold value when default eye electrical noise amplitude threshold is altered to be equal to default eye electrical noise amplitude threshold Moment Tmp, set blink threshold value moment Tmp before period a for first blink the period, and set blink threshold value moment Tmp it Period b afterwards was the second blink period, and the first blink period and the second blink period form a blink cycle；Step 4, noise reduction process is carried out to the real-time initial filter EEG signals of forehead in the blink cycle, the forehead blinked in the cycle is real When initial filter EEG signals and eye electrical noise average waveform it is superimposed, balance out it is described blink the cycle in made an uproar caused by blink Acoustic jamming, so as to the real-time initial filter EEG signals of forehead after being corrected；AndStep 5, the real-time initial filter of forehead in the corresponding blink cycle is replaced using the real-time initial filter EEG signals of forehead after amendment EEG signals, so as to obtain real-time pure EEG signals curve.
- 2. prefrontal area brain electricity analytical method according to claim 1, it is characterised in that under the step 1 further comprises State sub-step：Sub-step 1-1, carry out test sample for forehead current potential and obtain T0 period forehead benchmark EEG signals, to the forehead base Quasi- EEG signals carry out bandpass filtering according to default eye electrical noise frequency range and obtain forehead benchmark initial filter electro-ocular signal；Sub-step 1-2, by each data point amplitude x of forehead benchmark initial filter EEG signalsnEnter with default eye electrical noise amplitude threshold Row compares, and works as xnDuring by being altered to be equal to default eye electrical noise amplitude threshold less than default eye electrical noise amplitude threshold, setting should Period a before data point blinks the period for the first test, when setting the period b after the data point and being blinked for the second test Section, the first test blink period and the second test blink period form a test blink cycle, extract the survey Forehead benchmark initial filter EEG signals in the examination blink cycle are the signal of blinking in the blink cycle；AndSub-step 1-3, the signal of blinking in all blink cycles in the T0 periods is averaged, obtains an electrical noise average waveform.
- 3. prefrontal area brain electricity analytical method according to claim 1, it is characterised in that at least one-level wave filter includes one-level For removing the low pass filter of high-frequency noise.
- 4. prefrontal area brain electricity analytical method according to claim 3, it is characterised in that when using AC-powered progress brain During electricity collection, at least one-level wave filter also includes the notch filter that one-level is used to remove Hz noise, the trap filter The trap frequency of ripple device is identical with the frequency of the alternating current.
- 5. prefrontal area brain electricity analytical method according to claim 3, it is characterised in that in the filtering of the low pass filter It is limited to 60Hz.
- 6. prefrontal area brain electricity analytical method according to claim 2, it is characterised in that the default eye electrical noise frequency model Enclose for 1-10Hz.
- 7. prefrontal area brain electricity analytical method according to claim 2, it is characterised in that the default eye electrical noise amplitude threshold It is worth for 100 microvolts, a length of 50 milliseconds during the continuity of the period a, a length of 300 milliseconds during the continuity of the period b.
- 8. prefrontal area brain electricity analytical method according to claim 1, it is characterised in that a length of during the continuity of the T0 periods 30 seconds.
- 9. prefrontal area brain electricity analytical method according to claim 1, it is characterised in that step 3 and step 4 further comprise Following step：Step 3-4-1, the real-time initial filter EEG signals of the forehead of each sampled point are compared with default eye electrical noise amplitude threshold Compared with as the real-time initial filter EEG signals s of sampled point m foreheadmRange value when being less than default eye electrical noise amplitude threshold, perform step Rapid 3-4-2, as the real-time initial filter EEG signals s of sampled point m foreheadmRange value when being more than default eye electrical noise amplitude threshold, Moment where sampled point m corresponds to the threshold value moment Tmp that blinks, and performs step 3-4-3；Step 3-4-2, by the real-time initial filter EEG signals s of the foreheadmEnter row major output as primary pure EEG signals, make m =m+1 continues executing with step 3-4-1；AndStep 3-4-3, eye electricity noise reduction is carried out to the primary pure EEG signals in the first blink period a before sampled point m and repaiied Just, the primary pure EEG signals first blinked in period a and the first blink period of the eye electrical noise average waveform fold Add, so as to acquire the pure brain wave patterns of amendment between sampled point m-a to sampled point m；After the threshold value moment Tmp that blinks The real-time initial filter EEG signals of forehead in second blink period b carry out eye electricity noise reduction, and the forehead that second was blinked in period b is real-time Initial filter EEG signals are superimposed with the second blink period of the eye electrical noise average waveform, so as to acquire sampled point m to sampling The pure brain wave patterns of amendment between point m+b are exported；Integrate the pure brain electricity of amendment between sampled point m-a to sampled point m Waveform and sampled point m obtain pure EEG signals curve in real time, make m=to the pure brain wave patterns of amendment between sampled point m+b M+b+1 performs step 3-4-1.
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| CN114159064A (en) * | 2022-02-11 | 2022-03-11 | 深圳市心流科技有限公司 | Electroencephalogram signal based concentration assessment method, device, equipment and storage medium |
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| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
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| CB03 | Change of inventor or designer information | ||
| CB03 | Change of inventor or designer information |
Inventor after: Wang Bo Inventor after: Ma Changshu Inventor after: Zhao Lun Inventor after: Shi Guowei Inventor after: Yan Tianyi Inventor before: Yan Tianyi Inventor before: Ma Changshu Inventor before: Zhao Lun Inventor before: Wang Bo Inventor before: Shi Guowei |
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| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: No. 518 Xingguo Road, Nanchang, Jiangxi Province Co-patentee after: Beijing wing Stone Technology Co., Ltd. Patentee after: Nanchang Police Dog Base of Ministry of Public Security Address before: Room 1, room 128, room 6, Summer Palace, Summer Palace, Beijing, Beijing Co-patentee before: Nanchang Police Dog Base of Ministry of Public Security Patentee before: Beijing wing Stone Technology Co., Ltd. |