CN112183331B - System and method for identifying electrocardiographic artifact of neonatal brain electrical signal - Google Patents
System and method for identifying electrocardiographic artifact of neonatal brain electrical signal Download PDFInfo
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Abstract
The invention discloses a system and a method for identifying electrocardio-artifact of a neonatal brain electrical signal, which firstly collect the neonatal brain electrical signal, carry out filtering pretreatment on the brain electrical signal, and then use the time lengthTIs divided into one sectionnAnd (3) identifying the electrocardio artifact of each segment, and determining whether the segment has the electrocardio artifact or not. The invention improves the recognition rate of the electrocardio-artifact in the neonatal brain electrical signal through the special electrocardio-artifact recognition step.
Description
Technical Field
The invention relates to a system and a method for identifying electrocardio-artifact of neonatal brain electrical signals.
Background
Various artifacts such as electrocardiographic artifacts exist in the neonatal electroencephalogram signals, and if the artifacts cannot be sufficiently identified, the artifacts play a misleading role in electroencephalogram signal reading.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention provides a system and a method for identifying electrocardio-artifact in neonatal brain electrical signals, which improve the identification rate.
In order to achieve the above object, the present invention adopts the following technical scheme: the system for identifying the electrocardio-artifact in the electroencephalogram signals of the newborns is characterized by comprising an electroencephalogram signal acquisition, preprocessing and segmentation module and an artifact identification module for identifying the artifact of each segment of electroencephalogram signals; the artifact identification module is an electrocardio artifact identification module.
The electroencephalogram signal acquisition, preprocessing and segmentation module is used for executing the following steps:
1. collecting neonatal brain electrical signals;
2. carrying out notch processing on the electroencephalogram signals acquired in the step 1, and then filtering;
3. and (3) dividing the electroencephalogram signal subjected to pretreatment (namely notch and filtering) in the step (2) into n sections by taking the duration T as one section.
The step 1 is an acquisition step, the step 2 is a preprocessing step, and the step 3 is a segmentation step.
Where T > =8s, and can be divided by 8, preferably t=32s (seconds).
Wherein the electroencephalogram signal (x (t)) is a sequence of values. Each time a data point (signal length + 1) is obtained, the amplitude is the size of this data point, and a sequence of values is obtained after multiple samples.
Here, the data of the brain electrical signals are directly given by a neonatal brain electrical measuring instrument. One section of electroencephalogram signal is an electroencephalogram data (namely an electroencephalogram signal after being collected, preprocessed and segmented), one section of electroencephalogram data is composed of amplitude values (namely x (t) and t=1, 2 and 3 …) obtained through each sampling, wherein the amplitude values are the ordinate of (b) of fig. 1, and t represents the sampling times and can be converted with the abscissa time of fig. 1. The amplitude obtained by each sampling refers to the amplitude obtained by collecting, preprocessing (notch and filtering) and then carrying out band-pass filtering of 10-30 Hz. All bold variables represent a matrix, i.e. a sequence of values. The non-bolded parameter represents a single variable, i.e., a numerical value. The data (Peak, loc, width, p, l, w, height, h, data 5) are all numerical sequences, and the length of the data is the number of the numerical sequences (i.e. the number of numerical values).
Herein, let the sampling rate of the signal be sr (i.e. the sampling rate of the electroencephalograph), and the duration of one section of electroencephalograph signal be T, then the sampling period c=1/sr, the total signal length L 0 Let sr×t (signal length, i.e. data length), the signal passes through L in common 0 Subsampling, including 1,2, 3 … L 0 Subsampling, detect L 0 Numerical values (also known as magnitudes). Herein, the unit of the time period T is seconds.
The electrocardio artifact identification module is used for executing the following steps: 1) Taking a section of electroencephalogram signal, and carrying out band-pass filtering with cut-off frequency of 10-30Hz to obtain Data5; 2) Calculating all Peak values Peak of the Data5, wherein the position of the Peak (namely the sampling time point of the Peak, also called as the Peak position) Loc, the half-wave width and the Peak Height of the Peak are located; 3) Calculating a maximum value Max of Height, setting a threshold th6=r4×max, preferably r4=0.4 (0.3+.r4+.0.5); 4) Calculating data greater than th6 in Height to obtain wave Height h, corresponding wave crest value p, wave crest position l and half-wave width w; wherein h consists of data greater than th6 in Height; p, l, w are respectively the Peak value, the Peak position (namely the sampling time point where the Peak is located, the abscissa of fig. 1 (b)) and the half-wave Width corresponding to the data greater than th6 in the 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, w meet all conditions a) -d), judging that the section of data has the electrocardio artifact, and normally, the heart rate is in the range of 80-200;
a) The number of h (i.e. the number of values, if there are five wave height values in h, the number of h is 5) is greater than 80 x T/60 and less than 200 x T/60, T is the duration of the electroencephalogram signal;
b) The difference value of l is calculated to obtain l ', and then the average value of l' is calculated to obtainAnd->Here s is the unit: second, wherein the second is;
c) Max > th7, preferably th7=20μv (10μv.ltoreq.th7.ltoreq.50μv);
d) Averaging w to obtainAnd->Preferably, th8=0.005 s (0.ltoreq.th8.ltoreq.0.02 s), th9=0.05 s (0.02 s)<th 9.ltoreq.0.1 s), where s is the unit: second.
The electrocardiosignal can be recorded in most parts of the body surface through the volume conductor effect, and is also easily conducted to any reference electrode or recording electrode part of the brain electricity. When the electrocardiosignal interferes with one or a plurality of recording electrodes, the corresponding leads are seen to have approximately the same appearance interval, and positive phase or negative phase spike wave consistent with heart rate is equivalent to R wave of an electrocardiogram, and the amplitude can be high or low. It can be seen that the electrocardiographic artifact is characterized by periodicity and the waveform frequency is consistent with the R-wave. The frequency of the R wave is generally 10 Hz-30 Hz, so that the step 1) carries out band-pass filtering of 10-30Hz on the electroencephalogram signal, so that only the signal of the frequency component can be analyzed, and the interference of signals of other frequencies is reduced. In addition, the electrocardiosignals have good periodicity, so whether the electrocardiosignals have the electrocardiosignals artifact is verified by judging the periodicity of the signals. In step 2) all Peak positions Loc, amplitudes Peak, and corresponding half-wave width and wave Height in the signal are found. Because the amplitude of the waveform generated by the electrocardio artifact is relatively large, the effective data in the step 2) are screened out by using the steps 3) to 4), and the screened h, p, l and w are considered to be corresponding parameters representing electrocardio R waves if the electrocardio artifact exists. Step 5) to determine whether the data screened in step 4) meets the characteristics of electrocardiographic artifact. Since the heart rate of the infant is typically 80 to 200, the number of R-waves should occur at 80 x T/60 to 200 x T/60 during the period of time T, thereby forming condition a). The period of the electrocardiosignal can be calculated to be in the range of 60/200-60/80 s according to the heart rate, so that the interval time of R waves is too much, and the difference value of l is the interval between wave peaks, thereby forming the condition b). The condition c) is measured according to practical experiments and is a constraint on the signal amplitude. Since the frequency range of the R wave is 10 to 30Hz, the corresponding period is 1/30 to 1/10s, and the half-wave width is 1/60 to 1/20s accordingly, thereby obtaining the condition d). The range test for the specific th8 and th9 in condition d) is 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 electrocardiographic artifacts in neonatal electroencephalogram signals, which is characterized by comprising the steps of:
collecting neonatal brain electrical signals;
carrying out notch processing on the acquired electroencephalogram signals, and then filtering;
dividing the electroencephalogram signal subjected to notch and filtering treatment into n sections by taking the time length T as one section;
processing each section of electroencephalogram signal according to the following electrocardio artifact identification method, and judging whether artifact exists in the section of data;
the electrocardio artifact identification method comprises the following steps:
1. taking a section of electroencephalogram signal, and carrying out band-pass filtering with cut-off frequency of 10-30Hz to obtain Data5;
2. calculating all Peak values Peak, the position Loc of the Peak, the half-wave Width and the Peak Height of the Data5;
3. calculating the maximum value Max of the Height, setting a threshold value th6=r4×Max, preferably r4=0.4 (0.3 r4 is less than or equal to 0.5), and calculating data which is greater than th6 in the Height to obtain a wave Height (namely a wave peak Height) h, a corresponding wave peak value p, a wave peak position l and a half-wave width w;
4. if h, p, l and w meet all the following conditions, the data of the section have electrocardiographic artifact, and the heart rate is usually in the range of 80-200;
a) The number of h is more than 80 x T/60 and less than 200 x T/60, and T is the duration of the electroencephalogram signal;
b) The difference value of l is calculated to obtain l ', and then the average value of l' is calculated to obtainAnd->
c) Max > th7, preferably th7=20μv (10.ltoreq.th7.ltoreq.50μv);
d) Averaging w to obtain And->Preferably, th8=0.005 s (0.ltoreq.th8.ltoreq.0.02 s), th9=0.05 s (0.02 s)<th9≤0.1s)；
Preferably, the specific steps of carrying out notch processing and then filtering on the electroencephalogram signals are as follows: the electroencephalogram signal is subjected to power frequency noise removal (namely, 50Hz power frequency interference is subjected to notch treatment), then subjected to band-pass filtering with cutoff frequencies of 0.5Hz and 40Hz, and a second-order Butterworth filter can be used but is not limited to, so that the electroencephalogram signal which can be manually judged is obtained.
The invention also provides a neonatal brain electrical measurement instrument using the identification system or the identification method. In addition to integration in neonatal brain electrical measurement devices, the aforementioned identification system or the aforementioned identification method may exist independently, namely: the electroencephalogram signals are extracted, and the identification program is carried out (the electroencephalogram signals are still collected by an electroencephalogram measuring instrument, and are extracted by an independent identification system, and the steps of preprocessing, segmentation and electrocardio artifact identification are the same.
The invention also provides a system for identifying the electrocardio-artifact of the neonatal brain wave signal, which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the program to realize the identification method.
Furthermore, the present invention includes 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 the brain electrical artifacts of a newborn, which automatically identify the heart electrical artifacts (the artifacts caused by the heart electrical signals of the newborn) in the brain electrical signals of the newborn through the artifact identification system. The method can help medical staff to read the neonatal electroencephalogram better, and reduce the difficulty of artificial artifact removal. It is worth mentioning that the object of the invention is not to diagnose a disease, but to identify an electrocardiographic artifact in a neonatal brain electrical signal.
Drawings
Fig. 1 (a) electroencephalogram signal with electrocardiographic artifact; fig. 1 (b): the signal obtained by filtering the signal in (a) of fig. 1 at 10-30Hz shows the wave height h, the peak value p, the peak position l and the half-wave width w; the ordinate of fig. 1 (a) and fig. 1 (b) are both amplitude values (μv), and the abscissa is both 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, peak Height; the Peak value Peak of the electroencephalogram with the electrocardio artifact, the position Loc of the Peak, the half-wave Width and the Peak Height refer to the graph; the ordinate of fig. 2 is amplitude (μv) and the abscissa is time(s).
Detailed Description
The invention is described in detail below with reference to the drawings and the specific embodiments.
The invention discloses a method for identifying the artifacts of the brain electrical signals of a newborn, wherein the identified artifacts comprise the electrocardio artifacts, the method firstly collects the brain electrical signals of the newborn, carries out notch and filtering pretreatment on the brain electrical signals, then takes a time length T as a section, divides the section into n sections, carries out the artifact identification on each section, and determines whether the section has the electrocardio artifacts. In the invention, all artifact identification is independently completed by the identification system and the method, and manual calculation and manual identification are not needed.
The steps are as follows:
1. and (3) collecting: collecting neonatal brain electrical signals;
2. pretreatment: carrying out 50Hz notch processing on the electroencephalogram signals acquired in the step 1, and then carrying out 0.5-40 Hz filtering;
3. segmentation: dividing the pre-processed (notched and filtered) electroencephalogram signal of step 2 into n segments with a duration T as one segment, preferably t=32s; due to the limited space of fig. 1, only 2s of the electroencephalogram signal is shown in fig. 1, which is a small portion of a segment of the electroencephalogram signal (32 s).
4. Processing each piece of electroencephalogram data by the following electrocardio artifact identification step, and judging whether the piece of data has artifact or not;
in the step 1, the electroencephalogram signal acquisition process is as follows: the existing neonatal brain electrical measurement instrument (for example, the model is CFM-I, the equipment name is neonatal brain electrical measurement instrument, the manufacturer is Nanjing Weisi medical science and technology Co., ltd.) can be used for acquiring brain electrical signals according to an instrument operation manual. In addition, any other existing neonatal brain electrical measuring instrument can be selected to complete signal acquisition.
In the step 2), the electroencephalogram signal is subjected to power frequency noise removal (namely, 50Hz power frequency interference is subjected to notch treatment), and then subjected to band-pass filtering with cutoff frequency of 0.5Hz (lower limit frequency) and 40Hz (upper limit frequency), and a second-order butterworth filter can be used, but is not limited to, to obtain the electroencephalogram signal which can be manually judged.
Electrocardiogram artifact identification
1. Taking a section of electroencephalogram signal, and carrying out band-pass filtering (with the upper limit frequency of 30Hz and the lower limit frequency of 10 Hz) with the cutoff frequency of 10-30Hz to obtain Data5; the Data form of the brain electrical Data5 is x (t), t=1, 2, …, L 0 (representing the number of samples), data5 consists of the amplitude obtained for each sample (i.e., x (t), t=1, 2, 3 …), equation x (t) also contains the number of samples information t; each data point obtained by sampling comprises amplitude and sampling frequency information, and sampling time can be obtained by converting the sampling frequency and the sampling time; the amplitude is the ordinate shown in fig. 1 (b).
2. Calculating all Peak values Peak, the position Loc of the Peak, the half-wave Width and the Peak Height of the Data5;
3. calculating the maximum value Max of the Height, setting a threshold value th6=r4×Max, and setting a threshold value r4=0.4, and calculating data larger than th6 in the Height to obtain h, a corresponding peak value p, a peak position l and a half-wave width w;
4. if h, p, l and w meet all the following conditions, the data of the section have electrocardiographic artifact, and the heart rate is usually in the range of 80-200;
a) The number of h is more than 80 x T/60 and less than 200 x T/60, and T is the duration of the electroencephalogram signal;
b) The difference value of l is calculated to obtain l ', and then the average value of l' is calculated to obtainAnd->
c)Max>th7，th7＝20μV；
d) Averaging w to obtainAnd->th8＝0.005s,th9＝0.05s；
In the step b), the specific process of obtaining the l' by calculating the difference value of the l is as follows: let v values in l (peak positions, units s, v peak positions are respectively l 1 、l 2 、l 3 …l v-1 、l v L 'is formed from the value obtained by subtracting the previous value from the next value (i.e., l' 1 ＝l 2 —l 1 、l′ 2 ＝l 3 —l 2 、l′ 3 ＝l 4 —l 3 …l′ v-1 ＝l v —l v-1 The method comprises the steps of carrying out a first treatment on the surface of the And l 'is represented by l' 1 、l′ 2 …l′ v-1 The composition, i.e.l', consists of v-1 values, the average of which v-1 values is obtained
Specifically, the maxima are found from Data5, all the maxima are Peak values (the ordinate of the maxima points is in μv), and the maxima sequence (i.e. all the maxima) forms the Data Peak; all the positions of the maxima form data Loc; the half-wave Width corresponding to all wave peaks constitutes data Width, and the Height of all wave peaks constitutes data Height. Each wave peak corresponds to the position, the height and the half wave width of one wave peak. The maxima described above correspond to the maxima points (which are data points whose ordinate is the maximum), and the positions of all maxima, that is, the abscissa of all maxima points (fig. 1 (b), fig. 2).
Peak definition: a numerical sequence consisting of amplitude values corresponding to maximum value points in the Data5;
loc definition: if the i-th Data d in Data5 is a maximum value (the serial number is i, i.e. the i-th sample, where d is the ordinate, i.e. the amplitude of the i-th Data point), d is a Data in Peak, and the sampling time point corresponding to d is i/sr in s (seconds), where sr is the sampling rate in Hz, and i/sr is a value in Loc; loc units are s (seconds);
height definition: assuming that Peak and Loc are known for Data5, the ith Data d is a maximum value, d is one Data in Peak, and the corresponding Data in Loc is i/sr, searching from the ith-1 Data forward in Data5 until the ith-a is found 0 Data d 0 (a 0 <i，d 0 Is the i-a 0 Data point ordinate, i.e. amplitude, and d 0 To find the first data satisfying the condition in the process from the i-1 st data onward), the data is a maximum value, and d 0 Satisfy d 0 >d, if d meeting the condition cannot be found 0 D is then 0 For the value of the first Data in Data5, set d 0 The sequence number in Data5 is i 0 Then, searching backward from the (i+1) th data until the (i+a) th data is found 1 Data d 1 (i+a 1 Data length of +.Data 5), which is a maximum value (d 1 Is the (i+a) 1 Data point ordinate, i.e. amplitude, and d 1 Satisfy d 1 >d (and d) 1 To find the first data satisfying the condition in the process from the (i+1) th data, if d satisfying the condition cannot be found 1 D is then 1 Let d be the value of the last Data in Data5 1 The sequence number in Data5 is i 1 Respectively find the Data5 in i 0 Between i (i.e. ith 0 All data between the data and the ith data (all are on the ordinate, i.e. amplitude, ith 0 The data, i.e. the i 0 The data is smallest, d' 0 Is the ith 0 Data) minimum value d' 0 ，i～i 1 Between (i.e. the ith data to the ith 1 All data between the data, i.e. ordinate (i.e. amplitude), ith 1 The data, i.e. the i 1 The data is smallest, d' 1 Is the ith 1 Data) minimum value d' 1 Let d 'be d' 0 And d' 1 If the wave height corresponding to the ith data d is d-d', obtaining the waves corresponding to all the values in PeakHigh constitutes Height; wave height unit is mu V;
width definition: let Data5 be known as Peak, loc, height, the ith Data d be a maximum, d be one of the Data in Peak, the corresponding wave height be dh, find Data5 from the ith-1 Data onward, find the ith-b all the time 0 (b 0 <i) Data of value d 2 Satisfy d 2 <d-d h /2And d 2 In order to search for the first data meeting the condition in the process from the i-1 data, if the data meeting the condition cannot be found, d 2 For the first Data in Data5, corresponding b 0 =i-1, then look backward in Data5 starting from the (i+1) th Data, finding the (i+b) th Data all the time 1 Data (i+b) 1 Data length of +.Data 5), the Data having a value of d 3 Satisfy d 3 <d-d h /2/> And d 3 In order to search the first data meeting the condition in the process from the (i+1) th data backwards, if the data meeting the condition cannot be found, d 3 For the last Data in Data5, corresponding b 1 ＝L 0 -i, wherein L 0 For Data5, then d corresponds to a half-bandwidth of (b 1 +b 0 ) And (2) sr is the sampling rate (unit Hz), the half-wave Width unit is s (seconds), and the half-wave Width corresponding to all the values in Peak is obtained to form Width.
a 0 、a 1 、b 0 、b 1 Are all positive integers. In the above, the i-th data d refers to the amplitude value obtained by the i-th sampling (the ordinate of fig. 1 (b)). The amplitude obtained by the ith sample refers to the amplitude obtained by the ith acquisition, preprocessing (notch and filter) and bandpass filtering at 10-30 Hz.
In step 3, max is the maximum value in Height, then a threshold th6=r4×max is set, and data greater than th6 is screened out in Height to obtain a wave Height h, a corresponding peak value p, a peak position l, and a half-wave width w (fig. 1). p is defined as Peak, l is defined as Loc, and Width is defined as w.
In fact, h is selected from the Height (h is composed of part or all of the data in the Height), and p is composed of Peak values in Peak corresponding to all of the wave Height values in h respectively (p is composed of part or all of the data in Peak); l consists of peak positions in Loc corresponding to all wave height values in h respectively (l consists of part or all 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 point, and the maximum point has a certain wave Height value, a wave peak position and a half wave width. The h has c1 wave height values, c1 wave height values are all screened from the c wave height values, c1 wave height values correspond to c1 maximum value points, and the values of Peak, loc, width corresponding to the c1 maximum value points are respectively added into p, l and w. The "data" in some or all of the data in this section refers to a wave height value (μv), a wave peak position(s), and a half-wave width(s), respectively.
The four judging conditions of the electrocardio artifact are based on that the normal heart rate of the newborn is 120-160, but in some special cases, the heart rate can be 60-240, a large probability value of 80-200 is taken, so that conditions a and b are obtained, conditions c and d complement conditions a and b, and the heart rate is obtained through a real data test.
The invention also provides a neonatal brain electrical measurement instrument using the identification system or the identification method. In addition to integration in neonatal brain electrical measurement devices, the aforementioned identification system or the aforementioned identification method may exist independently, namely: the electroencephalogram signals are extracted, and the identification program is carried out (the electroencephalogram signals are still collected by an electroencephalogram measuring instrument, and are extracted by an independent identification system, and the steps of preprocessing, segmentation and electrocardio artifact identification are the same.
The invention also provides a system for identifying the electrocardio-artifact of the neonatal brain wave signal, which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the program to realize the identification method.
Furthermore, the present invention includes 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.
It will be appreciated by those skilled in the art that 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 has shown and described the basic principles, principal features and advantages of the invention. It will be appreciated by persons skilled in the art that the above embodiments are not intended to limit the invention in any way, and that all technical solutions obtained by means of equivalent substitutions or equivalent transformations fall within the scope of the invention.
Claims (7)
1. The system for identifying the electrocardio-artifact of the neonatal brain electrical signal is characterized by comprising an electroencephalogram signal acquisition, preprocessing and segmentation module and an artifact identification module for identifying the artifact of each segment of brain electrical signal; the artifact identification module is an electrocardiographic artifact identification module;
the electroencephalogram signal acquisition, preprocessing and segmentation module is used for executing the following steps:
1) Collecting neonatal brain electrical signals;
2) Carrying out notch processing on the electroencephalogram signals acquired in the step 1), and then filtering;
3) Dividing the electroencephalogram signal preprocessed in the step 2) into n sections by taking the duration T as one section and the unit of T as s seconds;
the electrocardio artifact identification module is used for executing the following steps:
1) Taking a section of electroencephalogram signal, and carrying out band-pass filtering with cut-off frequency of 10-30Hz to obtain Data5;
2) Calculating all Peak values Peak, the position Loc of the Peak, the half-wave Width and the Peak Height of the Data5; the Peak value Peak is a numerical sequence composed of amplitude values corresponding to maximum value points in the Data5; the position Loc of the Peak is a sequence of sampling time points corresponding to the Data5 by Peak values Peak; the wave heights corresponding to all the values in the Peak value Peak form a Peak Height; the half-wave Width corresponding to all the values in the Peak value Peak constitutes a half-wave Width;
3) Calculating the maximum value Max of the peak Height, and setting a threshold value th6=r4 Max, wherein r4 is more than or equal to 0.3 and less than or equal to 0.5;
4) The data with the Height higher than th6 form wave Height h, and then the wave crest value p, the wave crest position l and the half-wave width w corresponding to the wave Height h are obtained; the Peak value p consists of Peak value data in Peak values Peak corresponding to all the wave height values in the wave height h respectively; the wave crest position l consists of wave crest position data in the position Loc of the wave crest, wherein the wave crest position data in the position Loc of the wave crest correspond to all wave crest values in the wave crest h respectively; the half wave Width w consists of half wave Width data in half wave Width corresponding to all wave height values in wave height h respectively;
5) If the wave height h, the wave crest value p, the wave crest position l and the half-wave width w meet all the conditions of a) to d), judging that the section of the electroencephalogram signal has electrocardiographic artifact;
a) The number of data in the wave height h is more than 80 x T/60 and less than 200 x T/60, and T is the duration of the electroencephalogram signal;
b) Calculating the difference value of the peak positions l to obtain a peak position difference value l ', and calculating the average value of the peak position difference values l' to obtain the average value of the peak position difference values And->Here s is the unit: second, wherein the second is;
c) The maximum value Max of the peak Height is greater than a threshold th7, and 10 mu V is less than or equal to the threshold th7 and less than or equal to 50 mu V;
d) Averaging the half-wave width w to obtain a half-wave width average value And-> Threshold th8 is 0.02s,0.02s<Threshold th9 is less than or equal to 0.1s.
2. The method for identifying the electrocardio artifact in the neonatal brain electrical signal is characterized by comprising the following steps of:
collecting neonatal brain electrical signals;
carrying out notch processing on the electroencephalogram signals, and then filtering;
dividing an electroencephalogram signal into n sections by taking a time length T as one section;
processing each section of electroencephalogram signal according to the following electrocardio artifact identification method, and judging whether artifact exists in the section of data;
the electrocardio artifact identification method comprises the following steps:
1) Taking a section of electroencephalogram signal, and carrying out band-pass filtering with cut-off frequency of 10-30Hz to obtain Data5;
2) Calculating all Peak values Peak, the position Loc of the Peak, the half-wave Width and the Peak Height of the Data5; the Peak value Peak is a numerical sequence composed of amplitude values corresponding to maximum value points in the Data5; the position Loc of the Peak is a sequence of sampling time points corresponding to the Data5 by Peak values Peak; the wave heights corresponding to all the values in the Peak value Peak form a Peak Height; the half-wave Width corresponding to all the values in the Peak value Peak constitutes a half-wave Width;
3) Calculating the maximum value Max of the peak Height, and setting a threshold value th6=r4 Max, wherein r4 is more than or equal to 0.3 and less than or equal to 0.5;
4) The data with the Height higher than th6 form wave Height h, and then the wave crest value p, the wave crest position l and the half-wave width w corresponding to the wave Height h are obtained; the Peak value p consists of Peak value data in Peak values Peak corresponding to all the wave height values in the wave height h respectively; the wave crest position l consists of wave crest position data in the position Loc of the wave crest, wherein the wave crest position data in the position Loc of the wave crest correspond to all wave crest values in the wave crest h respectively; the half wave Width w consists of half wave Width data in half wave Width corresponding to all wave height values in wave height h respectively;
5) If the wave height h, the wave crest value p, the wave crest position l and the half wave width w meet all the following conditions, the section of the electroencephalogram signal has electrocardio artifact;
a) The number of data in the wave height h is more than 80 x T/60 and less than 200 x T/60, and T is the duration of the electroencephalogram signal;
b) Calculating the difference value of the peak positions l to obtain a peak position difference value l ', and calculating the average value of the peak position difference values l' to obtain the average value of the peak position difference values And->
c) The maximum value Max of the peak Height is greater than a threshold th7, and 10 mu V is less than or equal to the threshold th7 and less than or equal to 50 mu V;
d) Averaging the half-wave width w to obtain a half-wave width average value And-> Threshold th8 is 0.02s,0.02s<Threshold th9 is less than or equal to 0.1s.
3. The method for identifying the electrocardiographic artifact in the neonatal electroencephalogram according to claim 2, wherein the specific steps of performing notch processing and then filtering on the electroencephalogram are as follows: and (3) removing power frequency noise from the electroencephalogram signal, carrying out notch processing on 50Hz power frequency interference, and then carrying out band-pass filtering with cutoff frequencies of 0.5Hz and 40Hz to obtain the electroencephalogram signal which can be manually judged.
4. The method for recognizing the electrocardiographic artifact in the brain signals of the newborn according to claim 2, wherein,
the peak Height definition: assuming that the known Peak value Peak and the Peak position Loc of the Data5, the ith Data d is a maximum value, d is one Data in the Peak value Peak, and the corresponding Data in the Peak position Loc is i/sr, searching forward from the ith-1 Data in the Data5 until the ith-a is found 0 Data d 0 The data is a maximum value, and d 0 Satisfy d 0 >d, if d meeting the condition cannot be found 0 D is then 0 Setting d as the value of the first Data in Data5 0 The sequence number in the Data5 is i 0 Then, searching backward from the (i+1) th data until the (i+a) th data is found 1 Data d 1 The data is a maximum value, and d 1 Satisfy d 1 >d, if d meeting the condition cannot be found 1 D is then 1 Setting d as the value of the last Data in Data5 1 The sequence number in the Data5 is i 1 Dividing intoThe Data5 is found in i 0 Minimum d 'between i' 0 ，i～i 1 Minimum value d 'between' 1 Let d 'be d' 0 And d' 1 If the wave Height corresponding to d is d-d', obtaining the wave heights corresponding to all the values in the Peak value Peak to form a Peak Height;
the half-wave Width definition: let d be a maximum value, d be one of the Peak values Peak, and the corresponding wave Height be d, given that the Peak value Peak, the position Loc where the Peak is located, and the Peak Height are known for Data5 h The Data5 is searched from the i-1 Data onward until the i-b is found 0 Data of value d 2 Satisfies the following conditionsIf the data meeting the condition cannot be found, d 2 Data5, corresponding b 0 =i-1, then find backward from the (i+1) -th Data in the Data5, find the (i+b) -th Data all the time 1 Data of value d 3 Satisfy->If the data meeting the condition cannot be found, d 3 Last Data in Data5, corresponding b 1 ＝L 0 -i, wherein L 0 For the Data length of Data5, then the half-bandwidth corresponding to d is (b 1 +b 0 ) And (3) the sr is the sampling rate, the unit Hz, and the half-wave Width corresponding to all the values in the Peak value Peak is obtained to form the half-wave Width.
5. Neonatal brain electrical measurement apparatus using the identification system of claim 1 or the identification method of any one of claims 2-4.
6. A system for identifying electrocardiographic artifacts 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 implement the identification method of any one of claims 2-4.
7. 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 identification method according to any of claims 2-4.
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