CN115040136A - Electrocardiosignal baseline noise detection method and system - Google Patents
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Abstract
The invention discloses an electrocardiosignal baseline noise detection method and a system, after preprocessing and signal segmentation are carried out on the acquired non-pregnant adult electrocardiosignals, the R wave detection is carried out on the segmented electrocardiosignals, then the upper envelope line and the lower envelope line detection are carried out on the segmented electrocardiosignals, the time periods corresponding to the QRS waveforms on the upper envelope line and the lower envelope line are deleted, the upper envelope line and the lower envelope line which do not contain the QRS waveforms at the corresponding time points are taken as the baseline noise, the evaluation result of the baseline noise cannot be influenced by the QRS waveforms, the baseline noise of the electrocardiosignals can be accurately quantized, and the problem that the baseline noise of the electrocardiosignals cannot be accurately quantized by the existing electrocardiosignal baseline noise evaluation mode is solved, and is difficult to use for the technical problem of evaluating the baseline noise evaluation of the IN-FECG signal.
Description
Technical Field
The invention relates to the technical field of electrocardio monitoring, in particular to an electrocardiosignal baseline noise detection method and system.
Background
Ecg (electrocardiograph) signals are the primary choice for various health practitioners to determine important information about the human heart, being studied to diagnose and detect heart abnormalities, such as enlarged heart chambers, detection of cardiovascular disease, detection of ischemia, measurement of heart rate, biometric identification, and the like. Weak cardiac electrical signals are susceptible to various types of noise, such as: the existence of the noise, such as power supply noise, environmental noise, human body noise and the like, may damage the morphological characteristics of the electrocardiosignals, resulting in information errors and misdiagnosis. Therefore, it is necessary to evaluate the noise of the electrocardiosignal monitoring apparatus.
The non-invasive fetal electrocardiogram (IN-FECG) signal is acquired by an electrode placed on the abdomen of a pregnant woman, is weaker than an adult ECG signal, is usually only 10-20 microvolts and is easily submerged IN noise. However, since the measured object of the IN-FECG signal is a pregnant woman and cannot be actually measured at any time, the measured object needs to be changed to a non-pregnant woman adult, noise of the ECG monitoring device needs to be evaluated, and circuit noise of the ECG monitoring device needs to be quantified. The analysis signal used by the existing electrocardiosignal quality evaluation mode contains QRS waveform of the electrocardiosignal, and the change of the electrocardiosignal can seriously affect the evaluation result and can not correctly quantify the baseline noise of the electrocardiosignal. Therefore, the invention provides an electrocardiosignal baseline noise detection method and system, on one hand, a detected object is not required to be a pregnant woman, on the other hand, the baseline noise of the electrocardiosignal can be correctly quantified, and the method and system can be used for accurately evaluating the baseline noise of the IN-FECG signal.
Disclosure of Invention
The invention provides an electrocardiosignal baseline noise detection method and system, which are used for solving the technical problems that the existing electrocardiosignal baseline noise evaluation mode can not correctly quantify the baseline noise of electrocardiosignals and is difficult to be used for evaluating the baseline noise evaluation of IN-FECG signals.
In view of this, the first aspect of the present invention provides a method for detecting baseline noise of an electrocardiographic signal, including:
collecting electrocardiosignals of a non-pregnant adult;
preprocessing the electrocardiosignal, wherein the preprocessing comprises analog-to-digital conversion and filtering processing;
cutting the preprocessed electrocardiosignals by using the fixed window length and the sliding length to obtain a plurality of segmented electrocardiosignals, wherein the window length is equal to the sliding length;
performing R wave locus detection on each segmented electrocardiosignal, marking the R wave locus and the corresponding strength, and marking the segmented electrocardiosignal with a fixed length with a single QRS waveform;
carrying out peak envelope calculation on the preprocessed electrocardiosignals to obtain an upper envelope and a lower envelope of the window signals;
deleting the time periods corresponding to the QRS waveforms on the upper envelope line and the lower envelope line to obtain the upper envelope line and the lower envelope line which do not contain the QRS waveforms;
and subtracting the lower envelope curve of the waveform without QRS from the upper envelope curve of the waveform without QRS at the corresponding time point, calculating the mean value, and taking the mean value calculation result as the baseline noise.
Optionally, performing peak envelope calculation on the preprocessed electrocardiosignal to obtain an upper envelope and a lower envelope of the window signal, including:
searching sampling points meeting a first constraint condition in the preprocessed electrocardiosignals to obtain a first sampling point data set;
supplementing the first sampling point data set into a first interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the first interpolation data set as an upper envelope curve;
searching sampling points meeting a second constraint condition in the preprocessed electrocardiosignals to obtain a second sampling point data set;
supplementing the second sampling point data set into a second interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the second interpolation data set as a lower envelope curve;
the first constraint is:
wherein, t i Is as followsi sampling time points, k is the minimum peak interval,
for the ith sampling time point t i Corresponding segmented electrocardiosignals;
the second constraint is:
wherein, t j For the j-th sampling time point,
is the jth sampling time point t i Corresponding segmented electrocardiosignals.
Optionally, a plurality of QRS waveforms are contained within the window length.
Optionally, performing R-wave site detection on each segmented electrocardiographic signal, marking an R-wave site and corresponding strength, and taking the segmented electrocardiographic signals with fixed length to mark a single QRS waveform, including:
and (3) carrying out R wave locus detection on each segmented electrocardiosignal by using a Pan & Tompkins algorithm, marking the R wave locus and the corresponding strength, and marking the single QRS waveform by taking the segmented electrocardiosignals with fixed lengths.
Optionally, in pre-processing the cardiac electrical signal, the analog-to-digital conversion samples the cardiac electrical signal using a fixed sampling frequency.
Optionally, the fixed sampling frequency has a value in a range of 250Hz to 1000 Hz.
Optionally, the filtering process includes a high-pass filtering process, a low-pass filtering process, and a notch filtering process;
the high-pass filtering process comprises filtering the electrocardiosignal by using a Butterworth type infinite impulse response digital filter with the cutoff frequency of 1Hz-5 Hz;
the low-pass filtering process comprises filtering the electrocardiosignal by using a Butterworth type infinite impulse response digital filter with the cut-off frequency of 100Hz-150 Hz;
the notch filtering process includes filtering the electrocardiosignal using a single notch infinite impulse response digital filter with a cutoff frequency of 50Hz or 60Hz and a bandwidth of 5-10 Hz.
The second aspect of the present invention provides an electrocardiographic signal baseline noise detection system, comprising:
the signal acquisition module is used for acquiring electrocardiosignals of a non-pregnant woman and an adult;
the preprocessing module is used for preprocessing the electrocardiosignal, and the preprocessing comprises analog-to-digital conversion and filtering processing;
the signal segmentation module is used for cutting the preprocessed electrocardiosignals by using the fixed window length and the sliding length to obtain a plurality of segmented electrocardiosignals, wherein the window length is equal to the sliding length;
the R wave detection module is used for carrying out R wave site detection on each segmented electrocardiosignal, marking an R wave site and corresponding strength, and marking a single QRS waveform on the segmented electrocardiosignals with fixed length;
the envelope calculation module is used for carrying out peak envelope calculation on the preprocessed electrocardiosignals to obtain an upper envelope and a lower envelope of the window signals;
the envelope processing module is used for deleting the time periods corresponding to the QRS waveforms on the upper envelope and the lower envelope to obtain the upper envelope and the lower envelope which do not contain the QRS waveforms;
and the baseline noise evaluation module is used for subtracting the lower envelope curve without the QRS waveform from the upper envelope curve without the QRS waveform at the corresponding time point, calculating the mean value, and taking the mean value calculation result as baseline noise.
Optionally, the envelope calculation module is specifically configured to:
searching sampling points meeting a first constraint condition in the preprocessed electrocardiosignals to obtain a first sampling point data set;
supplementing the first sampling point data set into a first interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the first interpolation data set as an upper envelope line;
searching sampling points meeting a second constraint condition in the preprocessed electrocardiosignals to obtain a second sampling point data set;
supplementing the second sampling point data set into a second interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the second interpolation data set as a lower envelope curve;
the first constraint is:
wherein, t i For the ith sampling time point, k is the minimum peak interval,
for the ith sampling time point t i Corresponding segmented electrocardiosignals;
the second constraint is:
wherein, t j For the j-th sampling time point,
is the jth sampling time point t i Corresponding segmented electrocardiosignals.
Optionally, the R-wave detection module is specifically configured to:
and (3) carrying out R wave locus detection on each segmented electrocardiosignal by using a Pan & Tompkins algorithm, marking the R wave locus and the corresponding strength, and marking the single QRS waveform by taking the segmented electrocardiosignals with fixed lengths.
According to the technical scheme, the electrocardiosignal baseline noise detection method and the electrocardiosignal baseline noise detection system have the following advantages:
the invention provides an electrocardiosignal baseline noise detection method, which comprises the steps of preprocessing collected non-pregnant adult electrocardiosignals, carrying out signal segmentation, carrying out R wave detection on the segmented electrocardiosignals, carrying out upper envelope detection and lower envelope detection on the segmented electrocardiosignals, deleting time periods corresponding to QRS waveforms on upper and lower envelopes to obtain upper envelopes and lower envelopes without QRS waveforms, taking the average value of the upper envelopes without QRS waveforms and the lower envelopes without QRS waveforms at corresponding time points as baseline noise, not influencing the evaluation result of the baseline noise due to QRS waveforms, correctly quantizing the baseline noise of the electrocardiosignals, and solving the technical problems that the existing electrocardiosignal baseline noise evaluation mode cannot correctly quantize the baseline noise of the electrocardiosignals and is difficult to be used for evaluating the baseline noise of IN-FECG signals.
The electrocardiosignal baseline noise detection method provided by the invention samples electrocardiosignals by using the fixed sampling frequency, can avoid the problem that the baseline noise evaluation result is influenced because different sampling frequencies can generate different results due to frequency spectrum aliasing under the condition that an interference source of electrocardio monitoring equipment hardware is not changed, and can also avoid the problem that the baseline noise evaluation result is influenced because different sampling frequencies can generate different results due to frequency leakage under the condition that the interference source of electrocardio monitoring equipment software is not changed by using different window lengths.
According to the electrocardiosignal baseline noise detection method provided by the invention, the window length contains a plurality of QRS waveforms, so that the problem that follow-up processing cannot be normally carried out due to lack of QRS waveforms in the window caused by over-small window length can be solved.
The electrocardiosignal baseline noise detection system provided by the invention is used for executing the electrocardiosignal baseline noise detection method provided by the invention, the principle and the effect of the electrocardiosignal baseline noise detection system are the same as those of the electrocardiosignal baseline noise detection method provided by the invention, and the details are not repeated herein.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other related drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for detecting baseline noise of an electrocardiographic signal according to the present invention;
fig. 2 is a schematic structural diagram of an electrocardiograph signal baseline noise detection system provided in the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 invention.
For easy understanding, referring to fig. 1, the present invention provides an embodiment of a method for detecting baseline noise of an electrocardiograph signal, including:
In the embodiment of the present invention, the object to be measured is selected as a non-pregnant adult, and the electrocardiographic signal is collected by the electrode placed on the abdominal skin surface of the non-pregnant adult and recorded as the original signal x (t).
And 102, preprocessing the electrocardiosignal, wherein the preprocessing comprises analog-to-digital conversion and filtering processing.
It should be noted that, the original signal x (t) is preprocessed, and the original signal x (t) is sampled by the analog-to-digital converter to obtain the discrete signal s (t). Wherein, for the discrete signal s (t), the following is satisfied:
f s for the sampling frequency, i.e. f s The fixed value ranges from 250Hz to 1000 Hz. The filtering process is mainly to filter out known interference signals through a filter. The filtering process of the part mainly comprises high-pass filtering process, low-pass filtering process and notch filtering processFiltering;
the high-pass filtering process comprises filtering the electrocardiosignal by using a Butterworth type infinite impulse response digital filter with the cutoff frequency of 1Hz-5 Hz;
the low-pass filtering process comprises filtering the electrocardiosignal by using a Butterworth type infinite impulse response digital filter with the cut-off frequency of 100Hz-150 Hz;
the notch filtering process includes filtering the cardiac signal using a single notch infinite impulse response digital filter with a cutoff frequency of 50Hz or 60Hz and a bandwidth of 5-10 Hz.
And 103, cutting the preprocessed electrocardiosignals by using the fixed window length and the sliding length to obtain a plurality of segmented electrocardiosignals, wherein the window length is equal to the sliding length.
In the embodiment of the present invention, the electrocardiographic signal s (t) is cut by using the fixed window length and the sliding length, so as to obtain a plurality of segmented electrocardiographic signals.
The overall segmented cardiac signal cut over the window length w can be represented as:
S w (t)＝[s 1 ,s 2 ,…,s y ]
wherein S is w (t) is the preprocessed electrocardiosignal s 1 ,s 2 ,…,s y The electrocardiosignals S (t) are segmented electrocardiosignals 1 to y obtained after cutting by the window length w.
The window length and the sliding length of the cutting electrocardiosignal S (t) are equal, namely the window length is not overlapped with the signal between the windows, so that the problem of inaccurate noise evaluation result caused by signal overlapping is avoided. In order to prevent the follow-up processing from being carried out normally, the window length is not suitable to be too small, a plurality of QRS waveforms are contained in the window, the window time length is more than 4 seconds, namely w is more than 4f s 。
And step 104, carrying out R wave site detection on each segmented electrocardiosignal, marking an R wave site and corresponding strength, and marking a single QRS waveform on the segmented electrocardiosignals with fixed length.
Note that Pan can be used&Tompkins's calculatorThe method carries out R wave site detection on each segmented electrocardiosignal. The detected R wave corresponding sampling time point set is recorded as T m ＝[t m1 ,t m2 ,…,t mn ]Wherein, t m1 ,t m2 ,…,t mn The sampling time points corresponding to the 1 st to nth R waves. Marking the whole QRS wave by using a fixed time length, and setting the time length before the peak of the R wave as t rleft The time length after the peak of the R wave is set as t rright Then for t m1 For the R wave of (1), the QRS time period is t m1 -t rleft To t m1 +t rright By analogy, for t mn For the R wave of (1), the QRS time period is t mn -t rleft To t mn +t rright 。
And 105, performing peak envelope calculation on the preprocessed electrocardiosignals to obtain an upper envelope and a lower envelope of the window signals.
The preprocessed electrocardiographic signal S is w (t) calculating the peak envelope to obtain the upper envelope E of the window signal up And a lower envelope E lo . In particular, the upper envelope E up The calculation process of (2) is as follows:
searching sampling points meeting a first constraint condition in the preprocessed electrocardiosignals to obtain a first sampling point data set;
and supplementing the first sampling point data set into a first interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the first interpolation data set as an upper envelope line.
The first constraint is:
wherein, t i K is the minimum peak value interval at the ith sampling time point, the value range is 10-20,
for the ith sampling time point t i Correspond toThe segmented cardiac signal of (2).
T satisfying a first constraint i Is denoted as data set t i And f, the data set is discontinuous in the whole window length, and the number of elements is less than the whole window length w. Will data set t i The complement is a set of elements with a number equal to the length w of the whole window, denoted as E up ＝[e u1 ,e u2 ,…,e uw ]，E up Is a signal S w (t) an upper envelope.
Lower envelope E lo The calculation process of (2) is as follows:
searching sampling points meeting a second constraint condition in the preprocessed electrocardiosignals to obtain a second sampling point data set;
and supplementing the second sampling point data set into a second interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the second interpolation data set as a lower envelope curve.
The second constraint is:
wherein, t j For the j-th sampling time point,
is the jth sampling time point t i Corresponding segmented electrocardiosignals.
T satisfying the second constraint j Is denoted as data set t j And f, the data set is discontinuous in the whole window length, and the number of elements is less than the whole window length w. Will data set t j The complement is a set of elements with a number equal to the length w of the whole window, denoted as E lo ＝[e l1 ,e l2 ,…,e lw ]，E lo Is a signal S w (t) lower envelope.
Note that, the signals of the time periods corresponding to the QRS waveforms on the upper envelope and the lower envelope are deleted, and the upper envelope and the lower envelope not containing the QRS waveforms are obtained and are respectively denoted as E u And E l 。
And step 107, subtracting the lower envelope curve of the waveform without QRS from the upper envelope curve of the waveform without QRS at the corresponding time point, calculating a mean value, and taking the mean value calculation result as baseline noise.
It should be noted that, the mean value is calculated by subtracting the lower envelope curve of the waveform without QRS from the upper envelope curve of the waveform without QRS at the corresponding time point, so as to obtain the baseline noise, where the expression formula is:
where I is the baseline noise. The unit of I is the same as the unit converted by the analog-to-digital converter in step 101, i.e. volt, microvolt, millivolt, etc. The larger I represents that the noise generated by hardware and the surrounding environment to equipment is larger, and the corresponding signal quality is poorer; smaller I means less noise generated by the hardware and the surrounding environment to the device, and the better the corresponding signal quality.
The invention provides an electrocardiosignal baseline noise detection method, which comprises the steps of preprocessing collected non-pregnant adult electrocardiosignals, carrying out signal segmentation, carrying out R wave detection on the segmented electrocardiosignals, carrying out upper envelope detection and lower envelope detection on the segmented electrocardiosignals, deleting time periods corresponding to QRS waveforms on upper and lower envelopes to obtain upper envelopes and lower envelopes without QRS waveforms, taking the average value of the upper envelopes without QRS waveforms and the lower envelopes without QRS waveforms at corresponding time points as baseline noise, not influencing the evaluation result of the baseline noise due to QRS waveforms, correctly quantizing the baseline noise of the electrocardiosignals, and solving the technical problems that the existing electrocardiosignal baseline noise evaluation mode cannot correctly quantize the baseline noise of the electrocardiosignals and is difficult to be used for evaluating the baseline noise of IN-FECG signals.
The electrocardiosignal baseline noise detection method provided by the invention samples electrocardiosignals by using the fixed sampling frequency, can avoid the problem that the baseline noise evaluation result is influenced because different sampling frequencies can generate different results due to frequency spectrum aliasing under the condition that an interference source of electrocardio monitoring equipment hardware is not changed, and can also avoid the problem that the baseline noise evaluation result is influenced because different sampling frequencies can generate different results due to frequency leakage under the condition that the interference source of electrocardio monitoring equipment software is not changed by using different window lengths.
According to the electrocardiosignal baseline noise detection method provided by the invention, the window length contains a plurality of QRS waveforms, so that the problem that follow-up processing cannot be normally carried out due to lack of QRS waveforms in the window caused by over-small window length can be solved.
For easy understanding, referring to fig. 2, an embodiment of a system for detecting baseline noise of an electrocardiograph signal according to the present invention includes:
the signal acquisition module is used for acquiring electrocardiosignals of a non-pregnant woman and an adult;
the preprocessing module is used for preprocessing the electrocardiosignal, and the preprocessing comprises analog-to-digital conversion and filtering processing;
the signal segmentation module is used for cutting the preprocessed electrocardiosignals by using the fixed window length and the sliding length to obtain a plurality of segmented electrocardiosignals, wherein the window length is equal to the sliding length;
the R wave detection module is used for carrying out R wave site detection on each segmented electrocardiosignal, marking an R wave site and corresponding strength, and marking a single QRS waveform on the segmented electrocardiosignals with fixed length;
the envelope calculation module is used for carrying out peak envelope calculation on the preprocessed electrocardiosignals to obtain an upper envelope and a lower envelope of the window signals;
the envelope processing module is used for deleting the time periods corresponding to the QRS waveforms on the upper envelope and the lower envelope to obtain the upper envelope and the lower envelope which do not contain the QRS waveforms;
and the baseline noise evaluation module is used for subtracting the lower envelope curve without the QRS waveform from the upper envelope curve without the QRS waveform at the corresponding time point, calculating the mean value, and taking the mean value calculation result as baseline noise.
The envelope calculation module is specifically configured to:
searching sampling points meeting a first constraint condition in the preprocessed electrocardiosignals to obtain a first sampling point data set;
supplementing the first sampling point data set into a first interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the first interpolation data set as an upper envelope curve;
searching sampling points meeting a second constraint condition in the preprocessed electrocardiosignals to obtain a second sampling point data set;
supplementing the second sampling point data set into a second interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the second interpolation data set as a lower envelope curve;
the first constraint is:
wherein, t i For the ith sampling time point, k is the minimum peak interval,
for the ith sampling time point t i Corresponding segmented electrocardiosignals;
the second constraint is:
wherein, t j For the j-th sampling time point,
is the jth sampling time point t i Corresponding segmented electrocardiosignals.
The R wave detection module is specifically used for:
and (3) carrying out R wave locus detection on each segmented electrocardiosignal by using a Pan & Tompkins algorithm, marking the R wave locus and the corresponding strength, and marking the single QRS waveform by taking the segmented electrocardiosignals with fixed lengths.
The window length contains a plurality of QRS waveforms.
The fixed sampling frequency ranges from 250Hz to 1000 Hz.
The filtering treatment comprises high-pass filtering treatment, low-pass filtering treatment and notch filtering treatment;
the high-pass filtering process comprises filtering the electrocardiosignal by using a Butterworth type infinite impulse response digital filter with the cutoff frequency of 1Hz-5 Hz;
the low-pass filtering process comprises filtering the electrocardiosignal by using a Butterworth type infinite impulse response digital filter with the cut-off frequency of 100Hz-150 Hz;
the notch filtering process includes filtering the cardiac signal using a single notch infinite impulse response digital filter with a cutoff frequency of 50Hz or 60Hz and a bandwidth of 5-10 Hz.
The electrocardiosignal baseline noise detection system provided by the invention is used for preprocessing the acquired non-pregnant adult electrocardiosignals and segmenting the signals, then carrying out R wave detection on the segmented electrocardiosignals, then carrying out upper envelope detection and lower envelope detection on the segmented electrocardiosignals, deleting time periods corresponding to QRS waveforms on upper and lower envelopes to obtain upper envelopes and lower envelopes without QRS waveforms, and taking the mean value of the upper envelopes without QRS waveforms and the lower envelopes without QRS waveforms at corresponding time points as baseline noise, so that the evaluation result of the baseline noise is not influenced by the QRS waveforms, the baseline noise of the electrocardiosignals can be correctly quantized, and the technical problems that the baseline noise of the electrocardiosignals cannot be correctly quantized IN the existing electrocardiosignal baseline noise evaluation mode and the baseline noise evaluation of IN-FECG signals is difficult to use are solved.
The electrocardiosignal baseline noise detection system provided by the invention samples electrocardiosignals by using the fixed sampling frequency, can avoid the problem that the baseline noise evaluation result is influenced because different sampling frequencies can generate different results due to frequency spectrum aliasing under the condition that an interference source of electrocardio monitoring equipment hardware is not changed, and can also avoid the problem that the baseline noise evaluation result is influenced because different sampling frequencies can generate different results due to frequency leakage under the condition that the interference source of electrocardio monitoring equipment software is not changed by using different window lengths.
According to the electrocardiosignal baseline noise detection system provided by the invention, the window length contains a plurality of QRS waveforms, so that the problem that follow-up processing cannot be normally carried out due to the lack of QRS waveforms in the window caused by the over-small window length can be prevented.
The electrocardiosignal baseline noise detection system provided by the embodiment of the invention is used for executing the electrocardiosignal baseline noise detection method in the electrocardiosignal baseline noise detection method embodiment, the principle of the electrocardiosignal baseline noise detection system is the same as that of the electrocardiosignal baseline noise detection method in the electrocardiosignal baseline noise detection method embodiment, and the details are not repeated here.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for detecting baseline noise of electrocardiosignals is characterized by comprising the following steps:
collecting electrocardiosignals of a non-pregnant woman adult;
preprocessing the electrocardiosignal, wherein the preprocessing comprises analog-to-digital conversion and filtering processing;
cutting the preprocessed electrocardiosignals by using the fixed window length and the sliding length to obtain a plurality of segmented electrocardiosignals, wherein the window length is equal to the sliding length;
performing R wave locus detection on each segmented electrocardiosignal, marking the R wave locus and the corresponding strength, and marking the segmented electrocardiosignal with a fixed length with a single QRS waveform;
carrying out peak envelope calculation on the preprocessed electrocardiosignals to obtain an upper envelope and a lower envelope of the window signals;
deleting the time periods corresponding to the QRS waveforms on the upper envelope line and the lower envelope line to obtain the upper envelope line and the lower envelope line which do not contain the QRS waveforms;
and subtracting the lower envelope curve of the waveform without QRS from the upper envelope curve of the waveform without QRS at the corresponding time point, calculating the mean value, and taking the mean value calculation result as the baseline noise.
2. The method for detecting baseline noise of electrocardiosignals according to claim 1, wherein the peak envelope calculation is performed on the preprocessed electrocardiosignals to obtain an upper envelope and a lower envelope of a window signal, and the method comprises the following steps:
searching sampling points meeting a first constraint condition in the preprocessed electrocardiosignals to obtain a first sampling point data set;
supplementing the first sampling point data set into a first interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the first interpolation data set as an upper envelope line;
searching sampling points meeting a second constraint condition in the preprocessed electrocardiosignals to obtain a second sampling point data set;
supplementing the second sampling point data set into a second interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the second interpolation data set as a lower envelope curve;
the first constraint is:
wherein, t i For the ith sampling time point, k is the minimum peak interval, s ti For the ith sampling time point t i Corresponding segmented electrocardiosignals;
the second constraint is:
wherein, t j For the j-th sampling time point,
is the jth sampling time point t i Corresponding segmented electrocardiosignals.
3. The method of claim 1, wherein the window length comprises a plurality of QRS waveforms.
4. The method for detecting baseline noise of electrocardiosignals according to claim 1, wherein the step of performing R wave site detection on each segmented electrocardiosignal, marking an R wave site and corresponding strength, and taking the segmented electrocardiosignals with fixed length to perform marking of a single QRS waveform comprises the following steps:
and (3) carrying out R wave locus detection on each segmented electrocardiosignal by using a Pan & Tompkins algorithm, marking the R wave locus and the corresponding strength, and marking the single QRS waveform by taking the segmented electrocardiosignals with fixed lengths.
5. The method for detecting baseline noise of an electrocardiosignal according to claim 1, wherein when the electrocardiosignal is preprocessed, analog-to-digital conversion is used for sampling the electrocardiosignal by using a fixed sampling frequency.
6. The method for detecting baseline noise of electrocardiosignals according to claim 5, wherein the fixed sampling frequency is within a range of 250Hz to 1000 Hz.
7. The method for detecting baseline noise of electrocardiosignals according to claim 1, wherein the filtering process comprises a high-pass filtering process, a low-pass filtering process and a notch filtering process;
the high-pass filtering process comprises filtering the electrocardiosignal by using a Butterworth type infinite impulse response digital filter with the cutoff frequency of 1Hz-5 Hz;
the low-pass filtering process comprises filtering the electrocardiosignal by using a Butterworth type infinite impulse response digital filter with the cut-off frequency of 100Hz-150 Hz;
the notch filtering process includes filtering the electrocardiosignal using a single notch infinite impulse response digital filter with a cutoff frequency of 50Hz or 60Hz and a bandwidth of 5-10 Hz.
8. An electrocardiosignal baseline noise detection system, comprising:
the signal acquisition module is used for acquiring electrocardiosignals of a non-pregnant woman and an adult;
the preprocessing module is used for preprocessing the electrocardiosignal, and the preprocessing comprises analog-to-digital conversion and filtering processing;
the signal segmentation module is used for cutting the preprocessed electrocardiosignals by using the fixed window length and the sliding length to obtain a plurality of segmented electrocardiosignals, wherein the window length is equal to the sliding length;
the R wave detection module is used for carrying out R wave site detection on each segmented electrocardiosignal, marking an R wave site and corresponding strength, and marking a single QRS waveform on the segmented electrocardiosignals with fixed length;
the envelope calculation module is used for carrying out peak envelope calculation on the preprocessed electrocardiosignals to obtain an upper envelope and a lower envelope of the window signals;
the envelope processing module is used for deleting the time periods corresponding to the QRS waveforms on the upper envelope and the lower envelope to obtain the upper envelope and the lower envelope which do not contain the QRS waveforms;
and the baseline noise evaluation module is used for subtracting the lower envelope curve without the QRS waveform from the upper envelope curve without the QRS waveform at the corresponding time point, calculating the mean value, and taking the mean value calculation result as baseline noise.
9. The system for detecting baseline noise of electrocardiographic signals according to claim 8, wherein the envelope calculation module is specifically configured to:
searching sampling points meeting a first constraint condition in the preprocessed electrocardiosignals to obtain a first sampling point data set;
supplementing the first sampling point data set into a first interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the first interpolation data set as an upper envelope line;
searching sampling points meeting a second constraint condition in the preprocessed electrocardiosignals to obtain a second sampling point data set;
supplementing the second sampling point data set into a second interpolation data set with the element number equal to the window length by using a cubic spline interpolation method, and taking the second interpolation data set as a lower envelope curve;
the first constraint is:
wherein, t i For the ith sampling time point, k is the minimum peak interval,
for the ith sampling time point t i Corresponding segmented electrocardiosignals;
the second constraint is:
wherein, t j For the j-th sampling time point,
is the jth sampling time point t i Corresponding segmented electrocardiosignals.
10. The system for detecting baseline noise of electrocardiographic signals according to claim 8, wherein the R-wave detection module is specifically configured to:
and (3) carrying out R wave locus detection on each segmented electrocardiosignal by using a Pan & Tompkins algorithm, marking the R wave locus and the corresponding strength, and marking the single QRS waveform by taking the segmented electrocardiosignals with fixed lengths.
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