CN111700610A - Method, device and system for analyzing electroencephalogram outbreak suppression mode and storage medium thereof - Google Patents
Method, device and system for analyzing electroencephalogram outbreak suppression mode and storage medium thereof Download PDFInfo
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- A—HUMAN NECESSITIES
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Abstract
The invention discloses an analysis method, a device and a system of an electroencephalogram outbreak suppression mode and a storage medium thereof, wherein the method comprises the following steps: acquiring an electroencephalogram signal; carrying out segmentation processing on the electroencephalogram signals through a statistical variable point algorithm to obtain segmented electroencephalogram signals; calculating the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals; and analyzing the segmented electroencephalogram signals according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval. The statistical variable point algorithm is used for carrying out segmentation processing, and the electroencephalogram inhibition interval and/or the corresponding electroencephalogram outbreak interval are/is obtained through analysis of the absolute amplitude mean value calculated by the segmented computer signals, so that the technical problem that the existing electroencephalogram signal outbreak inhibition mode analysis is lack of a unified analysis method is solved.
Description
Technical Field
The invention relates to the field of electroencephalogram signal processing, in particular to an electroencephalogram outbreak suppression mode analysis method, device and system and a storage medium thereof.
Background
At present, in the field of electroencephalogram signal processing, analysis and processing aiming at an explosion suppression mode are always a big problem in the field, the explosion suppression mode is an explosion electroencephalogram brain electrical activity characteristic which appears after electroencephalograms with extremely low amplitude or equipotentials appear and then appears with high amplitude, and the purpose is to divide an electroencephalogram signal under continuous time into an electroencephalogram suppression interval section and an electroencephalogram explosion interval section. The outbreak inhibition mode is originally discovered on organisms anesthetized by the isopentbarbital in 1949, and symptoms such as anesthesia, traumatic brain injury, hypothermia, hypoxemia and the like all show the outbreak inhibition phenomenon of electroencephalogram from then on, for example, the electroencephalogram signal frequency of a brain electrical explosion zone section and the time of the brain electrical inhibition zone section in anesthesia depth monitoring, and the anesthesia concentration have an important relationship, wherein existing researches show that the longer the time of a single electroencephalogram inhibition zone section of the electroencephalogram is, the deeper the anesthesia depth is shown, and the evolution of the outbreak inhibition mode also provides important prognosis information. In addition, in addition to the pathological conditions mentioned above, it will also have a certain reference effect on other brain activities.
However, in the prior art, the burst suppression mode is analyzed by electroencephalograph experts through visual analysis and judgment of electroencephalograms, or a fixed threshold is set to determine the burst suppression mode of electroencephalograms. However, the method is time-consuming and labor-consuming through intuitive analysis and judgment of electroencephalograph experts, and given results may be different due to inconsistent judgment standards of each expert. Therefore, a set of standard, reliable and quantifiable analysis method is lacked in the analysis of the explosion suppression mode of the electroencephalogram signal.
Therefore, the inventor finds that in the prior art, due to the lack of a uniform standard and a quantifiable analysis method, the technical problem that the explosion suppression mode analysis of the electroencephalogram signals is inaccurate exists.
Disclosure of Invention
The application provides an analysis method of an electroencephalogram outbreak suppression mode, which comprises the following steps:
acquiring an electroencephalogram signal;
carrying out segmentation processing on the electroencephalogram signals through a statistical variable point algorithm to obtain segmented electroencephalogram signals;
calculating the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals;
and analyzing the segmented electroencephalogram signals according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval.
In an embodiment, the obtaining of the segmented electroencephalogram signal by performing the segmentation processing according to the electroencephalogram signal through a statistical variable point algorithm includes:
filtering the EEG signal at 3.5-30Hz to obtain the EEG signal without artifact interference;
and carrying out segmentation processing on the electroencephalogram signal without artifact interference through a statistical variable point algorithm to obtain the segmented electroencephalogram signal.
In an embodiment, the obtaining of the segmented electroencephalogram signal by performing the segmentation processing according to the electroencephalogram signal through a statistical variable point algorithm includes:
segmenting the electroencephalogram signal through a statistical variable point algorithm to obtain a segmented electroencephalogram signal to be detected;
calculating an absolute amplitude mean value of the segmented electroencephalogram signals to be detected according to the segmented electroencephalogram signals to be detected;
judging whether the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected meets a preset combination condition or not,
and if the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected accords with the preset combination condition, respectively taking the adjacent segmented electroencephalograms to be detected as segmented electroencephalograms.
In an embodiment, the determining whether the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected meets a predetermined merging condition further includes:
and if the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected does not accord with the preset combination condition, combining the adjacent segmented electroencephalograms to be detected to be used as the segmented electroencephalograms.
In an embodiment, after the step of obtaining the electroencephalogram suppression section and/or the corresponding electroencephalogram explosion section through the segmented electroencephalogram signal according to the absolute amplitude mean value, the method further includes:
and when the electroencephalogram inhibition interval and the corresponding electroencephalogram outbreak interval are obtained, calculating to obtain a single outbreak time ratio according to the time of the electroencephalogram inhibition interval and the corresponding electroencephalogram outbreak interval.
The present application also provides an analysis apparatus of an electroencephalogram explosion suppression pattern, the apparatus including:
the acquisition module is used for acquiring an electroencephalogram signal;
the segmentation module is used for carrying out segmentation processing on the electroencephalogram signal through a statistical variable point algorithm to obtain a segmented electroencephalogram signal; the device is also used for calculating the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals;
and the analysis module is used for analyzing the segmented electroencephalogram signals according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval.
In one embodiment, the apparatus further comprises:
the filtering module is used for filtering the electroencephalogram signals at 3.5-30Hz to obtain the electroencephalogram signals without artifact interference;
the segmentation module is also used for carrying out segmentation processing on the electroencephalogram signal without artifact interference through a statistical variable point algorithm to obtain the segmented electroencephalogram signal. In an embodiment, the calculation module is further configured to calculate a single burst time ratio according to the time of the electroencephalogram suppression section and the corresponding electroencephalogram burst section when the electroencephalogram suppression section and the corresponding electroencephalogram burst section are obtained.
In one embodiment, the present application further provides a system for analyzing a brain electrical burst suppression pattern, the system comprising:
the acquisition device is used for acquiring an electroencephalogram signal;
the processor unit is used for carrying out segmentation processing on the electroencephalogram signals through a statistical variable point algorithm to obtain segmented electroencephalogram signals; calculating the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals; obtaining an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval through the analysis of the segmented electroencephalogram signals according to the absolute amplitude mean value;
and the display is used for displaying the electroencephalogram signal, and the electroencephalogram inhibition interval section and/or the corresponding electroencephalogram outbreak interval section on the image corresponding to the electroencephalogram signal.
In an embodiment, the present application further provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the steps of the method for analyzing a brain electrical burst suppression pattern.
Based on the above embodiment, the statistical variable point algorithm is used for carrying out segmentation processing, segmenting the electroencephalogram signal to obtain the segmented electroencephalogram signal, and analyzing the segmented electroencephalogram signal according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval after the absolute amplitude mean value is calculated through the segmented computer signal. The utility model provides a unified analysis method for the electroencephalogram signal, which solves the technical problem that the existing electroencephalogram signal outbreak suppression mode analysis lacks a unified analysis method.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a schematic flow chart of the method for analyzing the burst suppression pattern of electroencephalogram according to the present invention;
FIG. 2 is a schematic diagram of an image of a function x (t) of the electroencephalogram signal according to the present invention;
FIG. 3 is a schematic diagram of a segmented electroencephalogram image of an electroencephalogram signal segmented by a statistical variable point algorithm according to the present invention;
FIG. 4 is a schematic diagram of a segmented interval of the combined segmented electroencephalogram signal according to the present invention;
FIG. 5 is a single burst time ratio image diagram of the electroencephalogram suppression segment and the corresponding electroencephalogram burst segment according to the present invention;
FIG. 6 is a schematic diagram of an analysis apparatus for electroencephalogram burst suppression mode according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The applicant finds that the quantitative analysis of the electroencephalogram explosion suppression mode in the prior art has a huge problem. Firstly, the electroencephalogram outbreak suppression mode is two segments of computer signals in a time range in the electroencephalogram signals, namely an electroencephalogram suppression section and an electroencephalogram outbreak section. The analysis of the brain wave explosion suppression mode is to find the time range and identify the brain wave suppression interval and the brain wave explosion interval by analyzing the time range. It should be noted that the electroencephalogram signals described above can be understood as a function of the corresponding voltage of the electroencephalogram and time.
In 2012, the american clinical neuroscience gave a quantitative description of the burst suppression of the brain electrical activity in the EEG description standard:
firstly, in an explosion suppression event, the duration of a brain wave explosion time period is at least more than 0.5s and can last to 30s at most;
second, for a brain electrical suppression interval, the voltage amplitude must be less than 50% of the background voltage amplitude, and the duration of the brain electrical suppression interval in a burst suppression event should exceed 50% of the entire event.
Although a quantitative criterion for the duration and amplitude variation of the burst suppression pattern of the brain electrical activity is given above, the electroencephalogram amplitude varies widely, and different subjects are in the same amplitude of brain electrical activity, but their brain electrical states are different, and different recordings may differ depending on the physical condition of the subject and the measurement factors, such as electrode type, electrode position, impedance and amplifier.
When the electroencephalogram amplitude range varies, the threshold is difficult to determine. Although the signal complexity characteristic of entropy is robust to the dynamic range, it is still difficult to describe the characteristics when the dynamic range changes.
FIG. 1 is a schematic flow chart of the method for analyzing the electroencephalogram burst suppression mode according to the present invention. As shown in fig. 1, in one embodiment, the present application provides a method for analyzing an electroencephalogram burst suppression pattern, the method comprising:
and S101, acquiring an electroencephalogram signal.
In this step, the electroencephalogram signal of the test target needs to be acquired, and it is noted that the electroencephalogram signal is a signal under uniform sampling and can be represented by x (t), that is, a function of time and voltage, and t > 0. In addition, the time domain function of x (t) can be converted into a frequency domain function through Fourier transform, and the function is marked as Sxx(w) ═ 0, | w | > B, where B is a constant. When the frequency domain function is qualified, the following processing can be better performed.
FIG. 2 is a schematic diagram of an image of an electroencephalogram signal x (t) function according to the present invention, and FIG. 2 shows that an electroencephalogram signal under uniform sampling expressed by an x (t) function is obtained, and x (t) satisfies a frequency domain function S after Fourier transformxx(w) ═ 0, | w | > B, where B is a constant;
FIG. 3 is a schematic diagram of a segmented electroencephalogram image of an electroencephalogram signal segmented by a statistical variable point algorithm. As shown in figure 3 of the drawings,
and S102, carrying out segmentation processing according to the electroencephalogram signals through a statistical variable point algorithm to obtain segmented electroencephalogram signals.
The step provides a specific step of carrying out segmentation processing on the electroencephalogram signal through a statistical variable point algorithm, wherein a sliding window W is arranged on the uniformly sampled electroencephalogram signal sequence, and the window length of the sliding window is
The sliding step length is s, the EEG signal with uniform sampling in a window can be written as X ═ X1,x2,…,xn1,2, … n, where i is the sampling instant, the electroencephalogram signals within the window are assumed to be at an unknown instant τ1,τ2,…,τK-1Mutations occurred, where K is the number of unknown data segments and K-1 is the number of transition points.
And taking K-2 according to the formula to determine the point change time of the brain electrical signal in the window. As the duration of the explosion section or the suppression section of the explosion suppression mode of the electroencephalogram signal is at least 0.5s, the window sliding step length s is taken to be 0.5s, so that all possible positions of the explosion suppression variable points of the electroencephalogram can be found, and the brain electrical sequence of the scoring section is Y1,Y2,…,YLWhere L is the number of segments.
K is an integer, and let τ ═ K1,τ2,…,τK-1) Is a sequence of integers. Where 0 < tau1＜τ2＜…＜τK-1< n. For any K equal to or greater than 1 and equal to or less than K, a penalty function for the statistic theta is constructed
Suppose for each k there is an estimate of θ
So that the penalty function J takes the minimum value, then
The statistic theta is taken as the variance, and then the penalty function is
S103, calculating the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals.
This step provides a method for calculating the absolute amplitudes of the segmented electroencephalogram signalsThe specific steps of the value, obtaining the segmented brain electric sequence Y on the surface1,Y2,…,YLWhere L is the number of segments, then for each segmented brain electrical sequence Yj＝(yj,1,yj,2,…,yj,N) The mean absolute magnitude of which can be expressed as
And S104, analyzing the segmented electroencephalogram signals according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval.
In this step, a specific implementation manner is provided for obtaining the electroencephalogram suppression section and/or the corresponding electroencephalogram outbreak section according to the absolute amplitude mean analysis, and a mean sequence T ═ is obtained according to the absolute amplitude mean formula in the previous step (T ═ is1,T2,…,TH) And searching for a minimum value of T in the sequence, wherein the electroencephalogram section corresponding to each minimum value is the suppression section of the electroencephalogram in the burst suppression mode, and the next adjacent section is the burst section.
In this embodiment, the electroencephalogram signal is analyzed by a variable point algorithm, and a specific implementation manner of an electroencephalogram suppression interval section and/or a corresponding electroencephalogram burst interval section is finally obtained. Firstly, acquiring an electroencephalogram signal, then carrying out segmentation processing on the electroencephalogram signal through a statistical variable point algorithm to obtain a segmented electroencephalogram signal, then calculating an absolute amplitude mean value of the segmented computer signal according to the segmented electroencephalogram signal, and finally analyzing the segmented electroencephalogram signal according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval section and/or a corresponding electroencephalogram outbreak interval section. In this embodiment, a method for performing an analysis of an explosion suppression pattern on an electroencephalogram signal through a statistical transformation algorithm is provided, so as to solve the problem that a set of standard, reliable and quantifiable analysis methods for an explosion suppression pattern is lacking in the prior art.
In one embodiment, the acquiring the electroencephalogram signal according to the above includes:
s201, performing band-pass filtering with the passband frequency of 3.5 Hz-30 Hz on the electroencephalogram signal to obtain the electroencephalogram signal without artifact interference;
in the step, a specific step of removing artifact interference in the electroencephalogram signal is provided, namely the influence of artifact interference on the electroencephalogram signal is eliminated.
In addition, in x (t) corresponding to the electroencephalogram signals, the burst suppression mode characteristics of the electroencephalogram in the frequency range of 3.5 Hz-30 Hz are more obvious, because the suppression section electroencephalogram in the frequency range has almost no energy, and the energy of the electroencephalogram in the burst section is mainly concentrated in the frequency range.
S202, carrying out segmentation processing on the electroencephalogram signal without artifact interference through a statistical variable point algorithm to obtain the segmented electroencephalogram signal.
In the step, a specific step of carrying out a statistical variable point algorithm on the electroencephalogram signals with the artifact interference removed for segmentation is provided.
In this embodiment, a specific implementation manner is provided for obtaining the segmented electroencephalogram signal by segmenting the electroencephalogram signal after removing the interference frequency band.
In an embodiment, the obtaining of the segmented electroencephalogram signal by performing the segmentation processing according to the electroencephalogram signal through a statistical variable point algorithm includes:
s301, segmenting according to the electroencephalogram signals through a statistical variable point algorithm to obtain segmented electroencephalogram signals to be detected.
And in the step, the electroencephalogram signal to be detected is obtained by segmenting through the electroencephalogram signal statistical variable point algorithm.
S302, calculating an absolute amplitude mean value of the segmented electroencephalogram signals to be detected according to the segmented electroencephalogram signals to be detected.
In this step, a specific implementation manner for calculating the segmented electroencephalogram signal to be detected is provided, and then a judgment condition that whether the segmented electroencephalogram signal to be detected meets the condition that the amplitude of the electroencephalogram of the inhibition section in the explosion inhibition mode of the electroencephalogram signal is smaller than 50% of the background voltage is required is used.
S303, judging whether a preset combination condition is met or not according to the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected, and if the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected meets the preset combination condition, respectively taking the adjacent segmented electroencephalograms to be detected as segmented electroencephalograms.
In this step, a specific implementation manner for judging whether the adjacent segmented electroencephalograms to be detected need to be combined is provided.
In the explosion suppression mode of the electroencephalogram signal, the amplitude of the electroencephalogram of a suppression section must be smaller than that of the background voltage by 50%, and in order to describe the characteristic, the amplitude comparison is carried out on the segmented electroencephalogram by utilizing the absolute amplitude mean value of adjacent segmented electroencephalograms, namely the amplitude comparison is carried out on the segmented electroencephalograms, namely
Where α is an empirical coefficient.
In this embodiment, a specific implementation manner is provided in which the electroencephalogram signal is segmented to obtain the segmented electroencephalogram signal to be detected, and whether the segmented electroencephalogram signal to be detected meets the predetermined merging condition is determined, first, the segmented electroencephalogram signal to be detected is segmented by a statistical variable point algorithm according to the electroencephalogram signal. And then, calculating the absolute amplitude mean value of the segmented electroencephalogram signals to be detected according to the segmented electroencephalogram signals to be detected. And finally, judging whether a preset combination condition is met or not according to the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected, and if the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected meets the preset combination condition, respectively taking the adjacent segmented electroencephalograms to be detected as segmented electroencephalograms.
In an embodiment, the determining whether the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected meets a predetermined merging condition further includes:
and if the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected does not accord with the preset combination condition, combining the adjacent segmented electroencephalograms to be detected to be used as the segmented electroencephalograms.
In this embodiment, a specific implementation is provided in which the absolute amplitude mean value does not meet the predetermined combination condition, and the adjacent segmented electroencephalograms to be detected need to be combined, and after combination, a formula may be further required
And judging, namely, not combining again until the combination is not needed any more, and finally taking the combined segmented electroencephalogram signal to be detected which accords with the formula as the segmented electroencephalogram signal.
In an embodiment, after the step of segmenting the electroencephalogram signal according to the statistical variable point segmentation method to obtain an electroencephalogram suppression interval section and/or an electroencephalogram explosion interval section, the method further includes:
and when the electroencephalogram inhibition interval and the corresponding electroencephalogram outbreak interval are obtained, calculating to obtain a single outbreak time ratio according to the time of the electroencephalogram inhibition interval and the corresponding electroencephalogram outbreak interval.
A specific implementation of calculating the single burst time ratio is provided in this embodiment, as it is also very important measurement data about the burst suppression period.
Fig. 5 is a schematic diagram of a single burst time ratio image of a brain electrical suppression block segment and a corresponding brain electrical burst segment of the present invention, as shown in fig. 5, the single burst time ratio formula is:
FIG. 6 is a schematic diagram of an analysis apparatus for electroencephalogram burst suppression mode according to the present invention. As shown in fig. 6, the present application also provides an apparatus for analyzing a brain electrical burst suppression pattern, the apparatus including:
an obtaining module 101, configured to obtain an electroencephalogram signal;
the segmentation module 102 is configured to perform segmentation processing on the electroencephalogram signal through a statistical variable point algorithm to obtain a segmented electroencephalogram signal;
the computing module 103 is further configured to compute an absolute amplitude mean of the segmented computer signals according to the segmented electroencephalogram signals;
and the analysis module 104 is used for analyzing the segmented electroencephalogram signals according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval.
In one embodiment, the apparatus further comprises:
the filtering module 105 is used for filtering the electroencephalogram signals at 3.5-30Hz to obtain the electroencephalogram signals without artifact interference;
the segmentation module 102 performs segmentation processing on the electroencephalogram signal without artifact interference through a statistical variable point algorithm to obtain the segmented electroencephalogram signal. In an embodiment, the calculating module 102 is further configured to calculate, when the electroencephalogram suppression section and the corresponding electroencephalogram burst section are obtained, a single burst time ratio according to the time of the electroencephalogram suppression section and the corresponding electroencephalogram burst section.
In one embodiment, the present application further provides a system for analyzing a brain electrical burst suppression pattern, the system comprising:
the acquisition device is used for acquiring an electroencephalogram signal;
the processor unit is used for carrying out segmentation processing on the electroencephalogram signal through a statistical variable point algorithm to obtain a segmented electroencephalogram signal; calculating the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals; obtaining an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval through the analysis of the segmented electroencephalogram signals according to the absolute amplitude mean value;
and the display is used for displaying the electroencephalogram signal, and the electroencephalogram inhibition interval section and/or the corresponding electroencephalogram outbreak interval section on the image corresponding to the electroencephalogram signal.
In an embodiment, the present application further provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the steps of the method for analyzing a brain electrical burst suppression pattern.
In practical applications, the computer readable medium may be included in the apparatus/device/system described in the above embodiments, or may exist alone without being assembled into the apparatus/device/system. The above-mentioned computer-readable storage medium carries one or more programs which, when executed, implement the image data processing method of the described data.
According to embodiments disclosed herein, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example and without limitation: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing, without limiting the scope of the present disclosure. In the embodiments disclosed herein, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for analyzing a burst suppression pattern of an electroencephalogram, the method comprising:
acquiring an electroencephalogram signal;
carrying out segmentation processing on the electroencephalogram signals through a statistical variable point algorithm to obtain segmented electroencephalogram signals;
calculating the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals;
and analyzing the segmented electroencephalogram signals according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval.
2. The method for analyzing brain electrical burst suppression pattern according to claim 1, wherein said obtaining a segmented brain electrical signal by performing a segmentation process according to said brain electrical signal through a statistical variable point algorithm comprises:
filtering the EEG signal at 3.5-30Hz to obtain the EEG signal without artifact interference;
and carrying out segmentation processing on the electroencephalogram signal without artifact interference through a statistical variable point algorithm to obtain the segmented electroencephalogram signal.
3. The method for analyzing an electroencephalogram explosion suppression pattern according to claim 1 or 2, wherein the obtaining of the segmented electroencephalogram signal by performing the segmentation processing according to the electroencephalogram signal through a statistical variable point algorithm comprises:
segmenting the electroencephalogram signal through a statistical variable point algorithm to obtain a segmented electroencephalogram signal to be detected;
calculating an absolute amplitude mean value of the segmented electroencephalogram signals to be detected according to the segmented electroencephalogram signals to be detected;
judging whether the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected meets a preset combination condition or not,
and if the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected accords with the preset combination condition, respectively taking the adjacent segmented electroencephalograms to be detected as segmented electroencephalograms.
4. The method for analyzing EEG burst suppression pattern according to claim 3, wherein said determining whether a predetermined merging condition is met according to said mean absolute amplitude of adjacent segmented EEG signals to be detected further comprises:
and if the absolute amplitude mean value of the adjacent segmented electroencephalograms to be detected does not accord with the preset combination condition, combining the adjacent segmented electroencephalograms to be detected to be used as the segmented electroencephalograms.
5. The method for analyzing EEG burst suppression pattern according to claim 1, wherein after said step of obtaining an EEG suppression interval and/or a corresponding EEG burst interval from said segmented EEG signal according to said absolute amplitude mean, said method further comprises:
and when the electroencephalogram inhibition interval and the corresponding electroencephalogram outbreak interval are obtained, calculating to obtain a single outbreak time ratio according to the time of the electroencephalogram inhibition interval and the corresponding electroencephalogram outbreak interval.
6. An apparatus for analyzing a burst suppression pattern of brain electrical activity, the apparatus comprising:
the acquisition module is used for acquiring an electroencephalogram signal;
the segmentation module is used for carrying out segmentation processing on the electroencephalogram signal through a statistical variable point algorithm to obtain a segmented electroencephalogram signal;
the computing module is also used for computing the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals;
and the analysis module is used for analyzing the segmented electroencephalogram signals according to the absolute amplitude mean value to obtain an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval.
7. The device for analyzing a pattern of suppression of brain electrical bursts according to claim 5, further comprising:
the filtering module is used for filtering the electroencephalogram signals at 3.5-30Hz to obtain the electroencephalogram signals without artifact interference;
the segmentation module is also used for carrying out segmentation processing on the electroencephalogram signal without artifact interference through a statistical variable point algorithm to obtain the segmented electroencephalogram signal.
8. The electroencephalogram explosion suppression pattern analysis apparatus according to claim 7,
the calculation module is further used for calculating a single-burst time ratio according to the time of the electroencephalogram inhibition interval and the corresponding electroencephalogram burst interval when the electroencephalogram inhibition interval and the corresponding electroencephalogram burst interval are obtained.
9. An analysis system for a pattern of suppression of brain electrical bursts, the system comprising:
the acquisition device is used for acquiring an electroencephalogram signal;
the processor unit is used for carrying out segmentation processing on the electroencephalogram signals through a statistical variable point algorithm to obtain segmented electroencephalogram signals; calculating the absolute amplitude mean value of the segmented computer signals according to the segmented electroencephalogram signals; obtaining an electroencephalogram inhibition interval and/or a corresponding electroencephalogram outbreak interval through the analysis of the segmented electroencephalogram signals according to the absolute amplitude mean value;
and the display is used for displaying the electroencephalogram signal, and the electroencephalogram inhibition interval section and/or the corresponding electroencephalogram outbreak interval section on the image corresponding to the electroencephalogram signal.
10. A computer-readable storage medium on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method for analyzing a brain electrical burst suppression pattern according to any one of claims 1 to 5.
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| CN114246594A (en) * | 2021-12-17 | 2022-03-29 | 天津大学 | Electroencephalogram signal processing method, and training method and device of background electroencephalogram prediction model |
| CN114469138A (en) * | 2022-01-13 | 2022-05-13 | 博睿康医疗科技(上海)有限公司 | Method, system and medium for detecting electroencephalogram outbreak suppression mode based on time-frequency domain |
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