CN112183331A - System and method for identifying electrocardiogram artifact of neonatal electroencephalogram signal - Google Patents

System and method for identifying electrocardiogram artifact of neonatal electroencephalogram signal Download PDF

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CN112183331A
CN112183331A CN202011036973.2A CN202011036973A CN112183331A CN 112183331 A CN112183331 A CN 112183331A CN 202011036973 A CN202011036973 A CN 202011036973A CN 112183331 A CN112183331 A CN 112183331A
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施雯
黄河
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Nanjing Vishee Medical Technology Co Ltd
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Abstract

The invention discloses a system and a method for recognizing electrocardiogram artifact of a newborn electroencephalogram signalTIs divided intonAnd identifying the electrocardio artifact of each section to determine whether the section has the electrocardio artifact or not. The method improves the identification rate of the electrocardiographic artifact in the neonatal electroencephalogram signal through a special electrocardiographic artifact identification step.

Description

System and method for identifying electrocardiogram artifact of neonatal electroencephalogram signal
Technical Field
The invention relates to a system and a method for identifying electrocardiogram artifact of a neonatal electroencephalogram signal.
Background
Various artifacts, such as electrocardio artifacts, exist in the electroencephalogram signals of the newborn, and if the artifacts cannot be fully identified, the electroencephalogram signals are misled.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention provides a system and a method for identifying the electrocardiogram artifact in the electroencephalogram signals of the newborn, which improve the identification rate.
In order to achieve the above object, the present invention adopts the following technical solutions: an identification system for electrocardio-artifact in a brain electric signal of a newborn is characterized by comprising an electroencephalogram signal acquisition, preprocessing and segmentation module and an artifact identification module for identifying artifact of each section of brain electric signal; the artifact identification module is an electrocardiogram artifact identification module.
The electroencephalogram signal acquisition, preprocessing and segmentation module is used for executing the following steps:
1. collecting the brain electrical signals of the newborn;
2. carrying out notch processing on the electroencephalogram signals collected in the step 1, and then filtering;
3. and (3) dividing the electroencephalogram signal subjected to the preprocessing (namely, notching and filtering) in the step (2) into n sections by taking the time length T as one section.
The step 1 is an acquisition step, the step 2 is a pretreatment step, and the step 3 is a segmentation step.
Where T is 8s and is divisible by 8, preferably 32s (seconds).
Wherein the electroencephalogram signal (x (t)) is a numerical sequence. Each sampling is carried out to obtain a data point (signal length +1), the amplitude is the size of the data point, and a numerical value sequence is obtained through multiple sampling.
In the text, the data of the electroencephalogram signals are directly given by the neonate electroencephalogram measuring instrument. A segment of electroencephalogram signal is a segment of electroencephalogram data (i.e., an electroencephalogram signal after collection, preprocessing and segmentation, the segment of electroencephalogram data is composed of an amplitude (i.e., x (t)), which is obtained by sampling each time (i.e., t is 1, 2 and 3.), the amplitude is a vertical coordinate of fig. 1(b), and t represents the sampling times and can be converted with a horizontal coordinate of fig. 1 in time). The amplitude obtained by each sampling refers to the amplitude obtained by acquisition, pretreatment (notch and filtering) and band-pass filtering of 10-30 Hz. In this context, all bold variables represent a matrix, i.e. a sequence of values. The non-bolded parameter represents a single variable, i.e., a value. The Data (Peak, Loc, Width, p, l, w, Heigtht, h, Data5) in this text are numerical sequences, and the length of the Data is the number of the numerical sequences (i.e. the number of numerical values).
Here, let us say the sampling rate of the signalFor sr (i.e. the sampling rate of the electroencephalograph), the duration of a segment of an electroencephalogram signal is T, then the sampling period C is 1/sr, and the total signal length L0T (signal length, data length), which is passed through L0Sub-sampling, including 1 st, 2 nd, 3 rd 3 … L0Sub-sampling, detecting L0Individual values (also known as amplitudes). Herein, the unit of the time length T is seconds.
The electrocardio artifact identification module is used for executing the following steps: 1) taking a section of electroencephalogram signal, and performing band-pass filtering with the cutoff frequency of 10-30Hz to obtain Data 5; 2) calculating all Peak values Peak of the Data5, the positions of the peaks (namely the sampling time points of the peaks, also called Peak positions) Loc, the half-wave Width Width and the Peak Height; 3) calculating the maximum value Max of Height, and setting the threshold th6 ═ r4 ×, preferably, r4 ═ 0.4(0.3 ≦ r4 ≦ 0.5); 4) calculating data larger than th6 in Height to obtain wave Height h, corresponding wave peak value p, wave peak position l and half wave width w; where h consists of data in Height greater than th 6; p, l and w are respectively a wave Peak value, a wave Peak position (namely a sampling time point where the wave Peak is located, the abscissa in fig. 1 (b)), and a half wave Width corresponding to the data larger than th6 in Height (see fig. 1, p is the same as Peak in calculation mode, l is the same as Loc in calculation mode, and Width is the same as w in calculation mode);
5) if h, p, l and w meet all the conditions of a) to d), judging that the section of data has the electrocardio artifact, and normally, judging that the heart rate range is 80-200;
a) the number of h (namely the number of values, if there are five wave height values in h, the number of h is 5) is more than 80T/60 and less than 200T/60, and T is the duration of the electroencephalogram signal;
b) obtaining a difference value l' by calculating the average value of l
Figure BDA0002705364310000021
Figure BDA0002705364310000022
And is
Figure BDA0002705364310000023
Where s is a radicalBit: second;
c) max > th7, preferably th7 ≦ 20 μ V (10 μ V ≦ th7 ≦ 50 μ V);
d) averaging w to obtain
Figure BDA0002705364310000024
Figure BDA0002705364310000025
And is
Figure BDA0002705364310000026
Preferably, th8 ≦ 0.005s (0. ltoreq. th 8. ltoreq.0.02 s), th9 ≦ 0.05s (0.02 s. ltoreq. th 9. ltoreq.0.1 s), where s is the unit: and second.
The electrocardiosignals can be recorded on most parts of the body surface through the volume conductor effect and can be easily transmitted to any reference electrode or recording electrode part of the brain electricity. When the electrocardiosignal interferes one or more recording electrodes, it can be seen that the corresponding leads have positive phase or negative phase sharp-like waves with approximately same intervals and consistent with the heart rate, which is equivalent to the R wave of the electrocardiogram, and the amplitude can be high or low. The visible electrocardio-artifact is characterized by periodicity and consistent waveform frequency with R wave. The frequency of the R wave is generally 10 Hz-30 Hz, so that the step 1) firstly carries out band-pass filtering of 10-30Hz on the electroencephalogram signals, thereby only analyzing the signals of the frequency component and reducing the interference of the signals of other frequencies. In addition, the electrocardiosignal has good periodicity, so whether the electrocardio-artifact exists or not is verified by judging the periodicity of the signal. All Peak positions Loc, amplitudes Peak, and corresponding half-wave widths Width and wave heights Height in the signal are found in the step 2). Because the amplitude of the waveform generated by the electrocardio-artifact is larger, the effective data in the step 2) is screened out by using the steps 3) -4), and if the electrocardio-artifact exists, the screened h, p, l and w are corresponding parameters representing the electrocardio-R wave. And 5) judging whether the data screened in the step 4) meet the characteristics of the electrocardio artifact or not. Since the heart rate of a child patient is usually 80 to 200, the number of occurrences of R-wave should be 80 × T/60 to 200 × T/60 in a time period of duration T, thereby establishing condition a). According to the heart rate, the period range of the electrocardiosignals can be calculated to be 60/200-60/80 s, so that the interval time of R waves is too much, and the difference value of l is the interval between peak values, thereby forming the condition b). The condition c) is determined by practical experiments and is a constraint on the amplitude of the signal. Since the frequency range of the R wave is 10-30Hz, the corresponding period is 1/30-1/10 s, and the half wave width is 1/60-1/20 s correspondingly, thereby obtaining the condition d). The range tests of the specific th8 and th9 in condition d) were experimentally obtained, in order to be able to obtain a more preferred threshold range.
Another object of the present invention is to provide a method for identifying cardiac artifacts in electrical brain signals of a newborn, comprising the steps of:
collecting the brain electrical signals of the newborn;
carrying out notch processing on the acquired electroencephalogram signals, and then filtering;
dividing the electroencephalogram signal subjected to notch and filtering into n sections by taking the time length T as one section;
processing each section of electroencephalogram signals according to the following electrocardio-artifact identification method, and judging whether artifacts exist in the section of data;
the electrocardio artifact identification method comprises the following steps:
1. taking a section of electroencephalogram signal, and performing band-pass filtering with the cutoff frequency of 10-30Hz to obtain Data 5;
2. calculating all Peak values Peak, Peak positions Loc, half-wave Width and Peak Height of the Data 5;
3. calculating the maximum value Max of Height, setting the threshold th6 ═ r4 ×, preferably, r4 ═ 0.4(0.3 ≦ r4 ≦ 0.5), calculating the data greater than th6 in Height to obtain the wave Height (i.e. peak Height) h, and the corresponding wave peak value p, and the peak position l, half-wave width w;
4. if h, p, l and w meet all the following conditions, the section of data has electrocardio artifact, and the heart rate range is usually 80-200;
a) the number of h is more than 80 × T/60 and less than 200 × T/60, and T is the duration of the electroencephalogram signal;
b) obtaining l 'by calculating difference value of l'Then calculating the average value of l' to obtain
Figure BDA0002705364310000031
Figure BDA0002705364310000032
And (b) and (c).
Figure BDA0002705364310000033
c) Max > th7, preferably th7 ═ 20 μ V (10 ≦ th7 ≦ 50 μ V);
d) averaging w to obtain
Figure BDA0002705364310000034
Figure BDA0002705364310000035
And is
Figure BDA0002705364310000036
Preferably, th8 ≦ 0.005s (0 ≦ th8 ≦ 0.02s), th9 ≦ 0.05s (0.02 ≦ th9 ≦ 0.1 s);
preferably, the specific steps of performing notch processing on the electroencephalogram signal and then filtering are as follows: the method comprises the steps of removing power frequency noise of the electroencephalogram signals (namely carrying out notch processing on power frequency interference of 50 Hz), then carrying out band-pass filtering with the cut-off frequency of 0.5Hz and 40Hz, and obtaining the electroencephalogram signals which can be manually interpreted by using but not limited to a second-order Butterworth filter.
The invention also provides a newborn electroencephalograph using the identification system or the identification method. Besides being integrated in the neonatal electroencephalograph, the aforementioned identification system or the aforementioned identification method can exist independently, namely: extracting the electroencephalogram signals, and carrying out the identification procedure (the electroencephalogram signals are still collected by an electroencephalogram measuring instrument, the electroencephalogram signals are extracted by an independent identification system, and the steps of preprocessing, segmenting and identifying the electrocardio-artifact are the same).
The invention also provides a system for identifying the electrocardiogram artifact of the neonatal electroencephalogram signal, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the identification method.
Furthermore, the invention also comprises a non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that the program is executed by a processor for implementing the aforementioned identification method.
Compared with the prior art, the invention has the beneficial effects that: the invention provides a system and a method for identifying newborn brain electrical artifact, which can automatically identify the newborn brain electrical artifact (artifact caused by the newborn brain electrical signal). The method can help medical staff to better read the neonatal electroencephalogram and reduce the difficulty of artificially eliminating the artifact. It is worth mentioning that the object of the invention is not to diagnose diseases, but to identify cardiac artefacts in the electrical brain signals of the newborn.
Drawings
FIG. 1(a) is an electroencephalogram signal with an electrocardiographic artifact, and (b) is a signal obtained after the signal in the diagram (a) is filtered by 10-30Hz, and the wave height h, the wave peak value p, the wave peak position l and the half-wave width w are shown; the ordinate of fig. 1(a) and 1(b) is amplitude (μ V) and the abscissa is time(s);
FIG. 2 is a schematic diagram of a random signal for the purpose of showing the meaning of Peak value Peak, Peak position Loc, half-wave Width, and Peak Height; the Peak value Peak, the Peak position Loc, the half-wave Width Width and the Peak Height of the electroencephalogram signal with the electrocardio-artifact are referred to the graph; fig. 2 shows the amplitude (μ V) on the ordinate and the time(s) on the abscissa.
Detailed Description
The invention is described in detail below with reference to the figures and the embodiments.
The invention discloses a method for identifying artifact of a newborn brain electrical signal, wherein the identified artifact comprises an electrocardiogram artifact, the method comprises the steps of collecting the newborn brain electrical signal, carrying out notch and filtering pretreatment on the brain electrical signal, dividing the brain electrical signal into n sections by taking a time length T as one section, identifying the artifact of each section, and determining whether the section has the electrocardiogram artifact. In the invention, all the artifact identification is independently completed by the identification system and the identification method without manual calculation and manual identification.
The method comprises the following steps:
1. collecting: collecting the brain electrical signals of the newborn;
2. pretreatment: carrying out 50Hz notch treatment on the electroencephalogram signals collected in the step 1, and then carrying out 0.5-40 Hz filtering;
3. segmenting: dividing the electroencephalogram signal preprocessed (trapped and filtered) in the step 2 into n sections by taking the time length T as one section, preferably T-32 s; due to the space of FIG. 1, only 2s of brain electrical signal is shown in FIG. 1, which is a small portion of a segment of brain electrical signal (32 s).
4. Carrying out the following electrocardio-artifact identification step processing on each section of electroencephalogram data, and judging whether artifact exists in the section of data;
in the step 1, the electroencephalogram signal acquisition process is as follows: the electroencephalogram signal can be acquired by using the existing neonate electroencephalogram measuring instrument (for example, model: CFM-I, equipment name: neonate electroencephalogram measuring instrument, manufacturer: Nanjing Webster medical science and technology Co., Ltd.) according to the instrument operation manual. In addition, any other existing neonate brain electrical measuring instrument can be selected to complete signal acquisition.
In the step 2), power frequency noise removal (i.e., notch processing is performed on power frequency interference of 50 Hz) is performed on the electroencephalogram signals, then band-pass filtering with cutoff frequencies of 0.5Hz (lower limit frequency) and 40Hz (upper limit frequency) is performed, and a second-order Butterworth filter can be used, but not limited to, to obtain the electroencephalogram signals which can be manually interpreted.
Electrocardiographic artifact identification
1. Taking a section of electroencephalogram signals, and performing band-pass filtering with the cutoff frequency of 10-30Hz (the upper limit frequency is 30Hz, and the lower limit frequency is 10Hz) to obtain Data 5; the Data form of the electroencephalogram Data5 is x (t), t is 1, 2, …, L0(representing sampling times), Data5 is composed of the amplitude obtained by each sampling (i.e. x (t), t is 1, 2, 3.), and formula x (t) further contains sampling time information t; that is, each data point obtained by sampling comprises amplitude and sampling frequency information, and sampling frequency information are obtainedThe sampling time can be obtained by sample time conversion; the amplitude is the ordinate shown in fig. 1 (b).
2. Calculating all Peak values Peak, Peak positions Loc, half-wave Width and Peak Height of the Data 5;
3. calculating the maximum value Max of Height, setting the threshold th6 to r4 Max and r4 to 0.4, and calculating the data which is larger than th6 in Height to obtain h, the corresponding wave peak value p, the wave peak position l and the half wave width w;
4. if h, p, l and w meet all the following conditions, the section of data has electrocardio artifact, and the heart rate range is usually 80-200;
a) the number of h is more than 80 × T/60 and less than 200 × T/60, and T is the duration of the electroencephalogram signal;
b) obtaining a difference value l' by calculating the average value of l
Figure BDA0002705364310000051
Figure BDA0002705364310000052
And is
Figure BDA0002705364310000053
c)Max＞th7，th7＝20μV；
d) Averaging w to obtain
Figure BDA0002705364310000054
Figure BDA0002705364310000055
And is
Figure BDA0002705364310000056
th8＝0.005s，th9＝0.05s；
In the step b), the specific process of obtaining l' by calculating the difference value of l is as follows: assume that there are v values in l (peak positions, unit s, v peak positions are l respectively1、l2、l3…lv-1、lvL' a value obtained by subtracting a previous value from a subsequent valueIs made of (i.e.)'1＝l2-l1、l′2＝l3-l2、l′3＝l4-l3…l′v-1＝lv-lv-1(ii) a And l 'is l'1、l′2…l′v-1The composition, i.e. l' consists of v-1 values, the average of the v-1 values being obtained
Figure BDA0002705364310000061
Specifically, the maximum values are found from Data5, all the maximum values are the Peak values (the ordinate of the maximum value point, the unit is μ V), and the maximum value sequence (i.e. all the maximum values) constitutes Data Peak; the positions of all maxima constitute the data Loc; the half wave widths corresponding to all the wave crests form data Width, and the heights of all the wave crests form data Height. Each wave crest corresponds to the position, height and half wave width of one wave crest. The maximum values correspond to maximum points (which are data points having a maximum value on the ordinate), and the positions of all the maximum values are the abscissas of all the maximum points (fig. 1(b) and 2).
Peak defines: a numerical value sequence consisting of the amplitudes corresponding to the maximum values in the Data 5;
loc defines: the sequence of sampling time points corresponding to the sequence number (the sequence number represents the sampling times) in Data5 where the maximum value point in Peak is located, for example, if the ith Data d in Data5 is a maximum value (the sequence number is i, namely the ith sampling, where d refers to the ordinate, namely the amplitude of the ith Data point), then d is one of the Peak Data, and the sampling time point corresponding to d is i/sr, which is in units of s (seconds), where sr is the sampling rate, which is in units of Hz, then i/sr is one of the Loc values; loc in s (seconds);
height definition: let Peak and Loc be known to Data5, the ith Data d is a maximum value, d is one of Peak, the corresponding Data in Loc is i/sr, then search forward from the ith-1 Data in Data5, find the ith-a0Data d0(a0＜i，d0Is the i-a0Data point ordinate, i.e. amplitude, andd0for the first data satisfying the condition in the forward search process starting from the i-1 st data), the data is a maximum value, and d0Satisfy d0If d is greater than d, if d satisfying the condition cannot be found0Then d is0Let d be the value of the first Data in Data50Sequence number i in Data50Then, starting from the (i +1) th data, searching backwards until the (i + a) th data is found1Data d1(i+a1Data length of ≦ Data5), the Data is a maximum (d)1Is the (i + a) th1Data point ordinate, i.e. amplitude, and d1Satisfy d1> d (and d)1The first data meeting the condition in the process of searching backwards from the (i +1) th data), if d meeting the condition cannot be found1Then d is1Let d be the value of the last Data in Data51Sequence number i in Data51Respectively find Data5 at i0Between-i (i.e. ith)0All data between data and ith data (ordinate, i.e. amplitude, ith)0The data, i-th data, are also included, e.g. i-th0D 'if the data is minimum'0Is the ith0Data) of minimum value d'0，i～i1In (i.e., ith data to ith data)1All data between the data, i.e. ordinate (i.e. amplitude), i1The data, i-th data, are also included, e.g. i-th1D 'if the data is minimum'1Is the ith1Data) of minimum value d'1D 'is d'0And d'1If the value is larger, the wave Height corresponding to the ith data d is d-d', and the wave heights corresponding to all the values in Peak are obtained to form Height; the wave height unit is μ V;
width definition: let Peak, Loc, Height be known to Data5, the ith Data d is a maximum value, d is one of Peak, and the corresponding wave Height is dhIn Data5, the i-b is found by searching from the i-1 st Data0(b0< i) data having a value of d2Satisfy d2＜d-dh2 (i.e. the
Figure BDA0002705364310000062
) And d is2The first data meeting the condition in the process of searching from the i-1 th data onward, if the data meeting the condition can not be found, d2For the first Data in Data5, corresponding to b0I-1, then search backward in Data5 starting from the i +1 th Data until the i + b th Data is found1Data (i + b)1Data length of ≦ Data5), the value of the Data being d3Satisfy d3＜d-dh2 (i.e. the
Figure BDA0002705364310000071
Figure BDA0002705364310000072
) And d is3The first data meeting the condition in the process of searching backwards from the (i +1) th data, if the data meeting the condition cannot be found, d3For the last Data in Data5, corresponding to b1＝L0-i, wherein L0For Data5, the Data length is such that d corresponds to a half-wave width of (b)1+b0) And/sr, wherein sr is a sampling rate (unit Hz), the unit of half wave Width is s (second), and the Width is formed by calculating the half wave widths corresponding to all the values in Peak.
a0、a1、b0、b1Are all positive integers. In the above, the ith data d refers to the amplitude obtained by the ith sampling (ordinate in fig. 1 (b)). The amplitude obtained by the ith sampling refers to the amplitude obtained by the ith acquisition, preprocessing (notch and filtering) and band-pass filtering of 10-30 Hz.
In step 3, Max is the maximum value in Height, then the threshold th6 ═ r4 × Max is set, and data larger than th6 are screened out in Height, so as to obtain the wave Height h, the corresponding wave peak value p, the wave peak position l and the half wave width w (fig. 1). p is defined as Peak, l is defined as Loc, and Width is defined as w.
Actually, h is selected from Height (h is composed of part or all of data in Height), p is composed of wave Peak values in Peak corresponding to all wave Height values in h respectively (p is composed of part or all of data in Peak); l is composed of peak positions in Loc corresponding to all the wave height values in h respectively (l is composed of part or all of data in Loc); w is composed of half-wave widths in Width corresponding to all wave height values in h respectively (w is composed of part or all of data in Width). For example, there are c wave Height values (peak Height values) in Height, and each wave Height value corresponds to a maximum value point, and the maximum value point has a certain wave Height value, wave peak position, and half wave width. And c1 wave height values exist in h, c1 wave height values are screened from the c wave height values, c1 wave height values correspond to c1 maximum value points, and p, l and w are added to Peak, Loc and Width numerical values corresponding to the c1 maximum value points respectively. The "data" in part or all of the data in this paragraph refers to a wave height value (μ V), a wave peak position(s), and a half wave width(s), respectively.
The four judgment conditions of the electrocardio artifact are that the normal heart rate of the newborn is 120-160, but in some special cases, the heart rate can be 60-240, wherein an approximate value of 80-200 is taken, so that the conditions a and b are obtained, and the conditions c and d are complementary to the conditions a and b and are obtained through real data testing.
The invention also provides a newborn electroencephalograph using the identification system or the identification method. Besides being integrated in the neonatal electroencephalograph, the aforementioned identification system or the aforementioned identification method can exist independently, namely: extracting the electroencephalogram signals, and carrying out the identification procedure (the electroencephalogram signals are still collected by an electroencephalogram measuring instrument, the electroencephalogram signals are extracted by an independent identification system, and the steps of preprocessing, segmenting and identifying the electrocardio-artifact are the same).
The invention also provides a system for identifying the electrocardiogram artifact of the neonatal electroencephalogram signal, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the identification method.
Furthermore, the invention also comprises a non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that the program is executed by a processor for implementing the aforementioned identification method.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It should be understood by those skilled in the art that the above embodiments do not limit the present invention in any way, and all technical solutions obtained by using equivalent alternatives or equivalent variations fall within the scope of the present invention.

Claims (9)

1. An identification system for the electrocardio-artifact of the electroencephalogram signals of the neonate is characterized by comprising an electroencephalogram signal acquisition, preprocessing and segmentation module and an artifact identification module for identifying the artifact of each section of electroencephalogram signals; the artifact identification module is an electrocardiogram artifact identification module.
2. The system for identifying electrical cardiac artifacts in neonatal brain electrical signals as claimed in claim 1, wherein said electroencephalogram signal acquisition, preprocessing and segmentation module is adapted to perform the following steps:
1. collecting the brain electrical signals of the newborn;
2. carrying out notch processing on the electroencephalogram signals collected in the step 1, and then filtering;
3. and (3) dividing the electroencephalogram signal preprocessed in the step (2) into n sections by taking the time length T as one section and the unit of T as s (second).
3. The system for recognizing the electrical cardiac artifacts of the electrical brain signals of a newborn infant according to claim 1,
the electrocardio artifact identification module is used for executing the following steps: 1) taking a section of electroencephalogram signal, and performing band-pass filtering with the cutoff frequency of 10-30Hz to obtain Data 5; 2) calculating all Peak values Peak, Peak positions Loc, half-wave Width and Peak Height of the Data 5; 3) calculating the maximum value Max of Height, setting a threshold th 6-r 4-Max, wherein r4 is more than or equal to 0.3 and less than or equal to 0.5; 4) calculating data larger than th6 in Height to obtain wave Height h, corresponding wave peak value p, wave peak position l and half wave width w;
5) if h, p, l and w meet all the conditions of a) to d), judging that the electroencephalogram data has the electrocardio-artifact;
a) the number of h is more than 80 × T/60 and less than 200 × T/60, and T is the duration of the electroencephalogram signal;
b) obtaining a difference value l' by calculating the average value of l
Figure FDA0002705364300000011
Figure FDA0002705364300000012
And is
Figure FDA0002705364300000013
Where s is the unit: second;
c)Max＞th7，10μV≤th7≤50μV；
d) averaging w to obtain
Figure FDA0002705364300000014
Figure FDA0002705364300000015
And is
Figure FDA0002705364300000016
0≤th8≤0.02s，0.02s≤th9≤0.1s。
4. A method for identifying electrocardio-artifact in a brain electric signal of a newborn is characterized by comprising the following steps:
collecting the brain electrical signals of the newborn;
carrying out notch processing on the electroencephalogram signals, and then filtering;
dividing the electroencephalogram signal into n sections by taking the time length T as one section;
processing each section of electroencephalogram signals according to the following electrocardio-artifact identification method, and judging whether artifacts exist in the section of data;
the electrocardio artifact identification method comprises the following steps:
1. taking a section of electroencephalogram signal, and performing band-pass filtering with the cutoff frequency of 10-30Hz to obtain Data 5;
2. calculating all Peak values Peak, Peak positions Loc, half-wave Width and Peak Height of the Data 5;
3. calculating the maximum value Max of Height, setting a threshold th 6-r 4-Max, setting r4 more than or equal to 0.3 and less than or equal to 0.5, and calculating data more than th6 in Height to obtain the wave Height h, the corresponding wave peak value p, the wave peak position l and the half wave width w;
4. if h, p, l and w meet all the following conditions, the section of data has electrocardio artifact;
a) the number of h is more than 80 × T/60 and less than 200 × T/60, and T is the duration of the electroencephalogram signal;
b) obtaining a difference value l' by calculating the average value of l
Figure FDA0002705364300000021
Figure FDA0002705364300000022
And is
Figure FDA0002705364300000023
c)Max＞th7，10μV≤th7≤50μV；
d) Averaging w to obtain
Figure FDA0002705364300000024
Figure FDA0002705364300000025
Eyes of a user
Figure FDA0002705364300000026
Preferably, 0. ltoreq. th 8. ltoreq.0.02 s, 0.02 s. ltoreq. th 9. ltoreq.0.1 s.
5. The method for identifying the neonatal brain electrical signal artifact as claimed in claim 4, wherein the specific steps of performing notch processing on the brain electrical signal and then performing filtering are as follows: and removing power frequency noise of the electroencephalogram signal, carrying out notch processing on power frequency interference of 50Hz, and then carrying out band-pass filtering with the cut-off frequency of 0.5Hz and 40Hz, wherein a second-order Butterworth filter can be used for, but is not limited to, obtaining the electroencephalogram signal which can be manually interpreted.
6. The method of claim 4, wherein the identification of the neonatal brain electrical signal artifact,
peak defines: a numerical value sequence consisting of the amplitudes corresponding to the maximum values in the Data 5;
loc defines: a sequence of sampling time points corresponding to the sequence number in Data5 where the maximum point in Peak is located;
height definition: let Peak and Loc be known to Data5, the ith Data d is a maximum value, d is one of Peak, the corresponding Data in Loc is i/sr, then search forward from the ith-1 Data in Data5, find the ith-a0Data d0The data is a maximum, and d0Satisfy d0If d is greater than d, if d satisfying the condition cannot be found0Then d is0Let d be the value of the first Data in Data50Sequence number i in Data50Then, starting from the (i +1) th data, searching backwards until the (i + a) th data is found1Data d1The data is a maximum, and d1Satisfy d1If d is greater than d, if d satisfying the condition cannot be found1Then d is1Let d be the value of the last Data in Data51Sequence number i in Data51Respectively find Data5 at i0Minimum value d 'between i'0，i～i1D 'to'iD 'is d'0And d'iIf the Peak value is larger than the preset value, the wave Height corresponding to d is d-d', and the wave heights corresponding to all the values in Peak are obtained to form Height;
width definition: let Peak, Loc, Height be known to Data5, the ith Data d is a maximum value, d is one of Peak, and the corresponding wave Height is dhIn Data5, the i-b is found by searching from the i-1 st Data0A data having a value d2Satisfy d2＜d-dhIf no data satisfying the condition can be found, d2For the first Data in Data5, corresponding to b0I-1, then search backward in Data5 starting from the i +1 th Data until the i + b th Data is found1Data having a value d3Satisfy d3＜d-dhIf no data satisfying the condition can be found, d3For the last Data in Data5, corresponding to b1＝L0-i, wherein L0For Data5, the Data length is such that d corresponds to a half-wave width of (b)1+b0) And/sr, wherein sr is a sampling rate and is in Hz, and the width is formed by obtaining the half-wave widths corresponding to all values in Peak.
7. A neonatal electroencephalograph using the identification system of any one of claims 1 to 3 or the identification method of any one of claims 4 to 6.
8. A system for identifying cardiac electrical artefacts in neonatal brain electrical signals, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to carry out the identification method according to any one of claims 4 to 6.
9. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that the program is processed for execution for implementing the identification method according to any one of claims 4-6.
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