CN113576414A - Abrupt signal identification method, positioning method and device - Google Patents
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Abstract
The invention provides a method for identifying, positioning and device of a mutation signal, wherein the method for identifying the mutation signal comprises the following steps: preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified; constructing a sliding window filter, and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter; calculating signal block energy of each of the plurality of signal blocks by a locally weighted linear regression method; when the energy of the signal block is larger than the threshold energy, the abrupt signal exists in the signal block corresponding to the energy of the signal block larger than the threshold energy. The invention reduces the calculation amount of the identification of the mutation signal and improves the speed and the accuracy of the identification of the mutation signal.
Description
Technical Field
The invention relates to the technical field of electrocardiogram signal processing, in particular to a method for identifying a mutation signal, a positioning method and a device.
Background
Electrocardiography (ECG) is a test that records the electrical activity of the heart as recorded by electrodes attached to the outer surface of the skin, which has become indisputable as a necessary means of cardiovascular disease diagnosis. But impedance changes between the recording electrodes and the skin due to more vigorous physical activity can result in the superimposition of abrupt signals in the ECG signal. The occurrence of a sudden change of signal can lead to inaccuracies in the electrocardiographic measurement. Therefore, it is very important to be able to effectively identify a sudden change signal in an ECG signal, thereby improving the accuracy of electrocardiographic measurement.
In the prior art, published "analysis method of mutation components in time-varying signals" by the public, a method for identifying a mutation signal in a time-varying signal is described, which identifies a mutation signal by identification feature extraction based on local sparse representation coefficients and an identification classifier construction based on a removal threshold and an insertion threshold.
The time-varying signal analysis method needs to analyze and process signals at each moment in the time-varying signal, the calculation amount is large, meanwhile, the sudden change signal in the ECG signal is not identified, and the sudden change signal is continuously used in the ECG signal, so that the R wave of the ECG signal is misjudged as the sudden change signal, and the identification is inaccurate.
Disclosure of Invention
In view of the above, it is desirable to provide a method, a device and a system for identifying a sudden change signal, which are used to solve the technical problems of large calculation amount and inaccurate identification in the prior art.
In order to solve the above technical problem, the present invention provides a method for identifying an abrupt change signal in a electrocardiogram signal, including:
preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
constructing a sliding window filter, and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
calculating signal block energy of each of the plurality of signal blocks by a locally weighted linear regression method;
and judging whether the energy of the signal block is greater than the threshold energy, wherein a sudden change signal exists in the signal block corresponding to the energy of the signal block greater than the threshold energy.
In one possible implementation, the signal block includes a plurality of time points and a plurality of electrocardiogram sub-signals in one-to-one correspondence with the time points; the separately calculating the signal block energy of each of the plurality of signal blocks by a local regression algorithm comprises:
determining a kernel function, a predicted time point in the signal block and a plurality of surrounding time points;
determining a plurality of weights of the plurality of surrounding time points one by one through the kernel function;
constructing a weight matrix according to the plurality of weights;
performing linear regression on the electrocardiogram sub-signals of the predicted time points based on the minimum mean square error, and obtaining regression parameters according to the weight matrix;
and determining the signal energy of the electrocardiogram sub-signals at the predicted time point according to the regression parameters and the predicted time point, wherein the signal energy of the electrocardiogram sub-signals at the predicted time point is the signal block energy of the signal block.
In one possible implementation, the weight is:
where ω (i, i) is the weight of the ith surrounding time point; x is the number ofiIs the time value of the ith surrounding time point; k is a control parameter; x is a time value of the predicted time point.
In one possible implementation manner, the signal block energy of the signal block is:
y＝ω'x
ω'＝(xTwx)-1xTWy
wherein y is the signal block energy of the signal block; omega' is a regression parameter; x is the number ofTA transposed matrix for x; w is a weight matrix; m is the total number of surrounding time points.
In one possible implementation, the preprocessing the initial electrocardiogram signal includes:
first filtering the initial electrocardiogram signal by a high-pass filter;
and/or the presence of a gas in the gas,
the initial electrocardiogram signal is filtered a second time by a low pass filter.
In one possible implementation, the window length of the sliding window filter is equal to the step size.
In another aspect, the present invention further provides a method for locating a mutation signal, comprising:
preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
constructing a sliding window filter, and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
calculating signal block energy of each of the plurality of signal blocks by a locally weighted linear regression method;
traversing the signal blocks along the time sequence, determining the signal block state of each signal block according to the signal block energy of the signal block, and positioning the abrupt change signal according to the signal block state.
In one possible implementation, the signal block state includes a sudden change start, a sudden change neutralization and a sudden change end; the positioning the abrupt signal according to the signal block state comprises:
judging whether the number of signal blocks between a first signal block of which the signal block state is abrupt change end and a second signal block of which the signal block state immediately after the first signal block is abrupt change start is smaller than a threshold number or not;
and if the number of the signal blocks between the first signal block and the second signal block is less than the threshold number, changing the signal block state of the second signal block into abrupt change.
In another aspect, the present invention further provides a device for identifying a mutation signal, including:
the first preprocessing unit is used for preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
the first blocking unit is used for constructing a sliding window filter and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
a first energy calculation unit for calculating a signal block energy of each of the plurality of signal blocks by a local weighted linear regression method, respectively;
and the identification unit is used for judging whether the energy of the signal block is greater than the threshold energy or not, and the signal block corresponding to the energy of the signal block greater than the threshold energy has a sudden change signal.
In another aspect, the present invention further provides a device for locating a mutation signal, including:
the second preprocessing unit is used for preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
the second block dividing unit is used for constructing a sliding window filter and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
a second energy calculation unit for calculating a signal block energy of each of the plurality of signal blocks by a local weighted linear regression method, respectively;
and the positioning unit is used for traversing the plurality of signal blocks along the time sequence, determining the signal block state of each signal block according to the signal block energy of the signal block, and positioning the mutation signal according to the signal block state.
The beneficial effects of adopting the above embodiment are: according to the abrupt change signal identification method provided by the invention, the electrocardiogram signal to be identified is divided into a plurality of signal blocks by constructing the sliding window filter, then the signal block energy of each signal block is calculated by a local weighted linear regression algorithm, and whether the abrupt change signal exists in the signal blocks is identified according to the signal block energy, instead of calculating the signal energy of each moment in the electrocardiogram signal to be identified, so that the calculated amount is reduced, and the speed of identifying the abrupt change signal is further improved. Furthermore, the method for identifying the sudden change signals calculates the energy of the signal block of each signal block by the local weighted linear regression method, can remove the R wave in the signal block, and does not influence the sudden change signals, thereby avoiding misjudging the R wave in the electrocardiogram signals to be identified as the sudden change signals and improving the accuracy of identifying the sudden change signals. Furthermore, the signal block energy of each signal block is independently calculated, so that the independence of each signal block is improved, the mutual influence among the signal blocks is avoided, and the accuracy of abrupt signal identification is further improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of an embodiment of a method for identifying a mutation signal according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating an embodiment of S101 according to the present invention;
FIG. 3 is a flowchart illustrating an embodiment of S103 according to the present invention;
FIG. 4 is a schematic flowchart of an embodiment of a method for locating a mutation signal according to the present invention;
FIG. 5 is a flowchart illustrating an embodiment of S404 according to the present invention;
FIG. 6 is a flowchart illustrating an embodiment of S504 according to the present invention;
fig. 7 is a schematic structural diagram of an embodiment of a device for identifying a sudden change signal according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an embodiment of a sudden change signal positioning device according to an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. 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.
In the following, the terms "first", "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the embodiments of the present application, "a plurality" means two or more unless otherwise specified. "and/or" describes the association relationship of the associated objects, meaning that three relationships may exist, for example: a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The invention provides a method for identifying a mutation signal, a method for positioning the mutation signal and a device thereof, which are respectively explained below.
As shown in fig. 1, a schematic flow chart of an embodiment of an abrupt change signal identification method provided in an embodiment of the present invention is provided, the abrupt change signal identification method is used for identifying an abrupt change signal in a electrocardiogram signal, and the fault risk prediction analysis method includes:
s101, preprocessing an initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
wherein, the electrocardiogram signal to be identified is a time continuous signal.
S102, constructing a sliding window filter, and dividing an electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
s103, respectively calculating the signal block energy of each signal block in the plurality of signal blocks by a local weighted linear regression method;
s104, judging whether the energy of the signal block is larger than the threshold energy or not, wherein a mutation signal exists in the signal block corresponding to the energy of the signal block larger than the threshold energy.
Compared with the prior art, the abrupt change signal identification method provided by the embodiment of the invention divides the electrocardiogram signal to be identified into a plurality of signal blocks by constructing the sliding window filter, then calculates the signal block energy of each signal block, identifies whether the abrupt change signal exists in the signal block according to the signal block energy, and calculates the signal energy of each moment in the electrocardiogram signal to be identified, so that the calculated amount is reduced, and the speed of identifying the abrupt change signal is further improved. Furthermore, the method for identifying the sudden change signals calculates the energy of the signal block of each signal block by the local weighted linear regression method, can remove the R wave in the signal block, and does not influence the sudden change signals, thereby avoiding misjudging the R wave in the electrocardiogram signals to be identified as the sudden change signals and improving the accuracy of identifying the sudden change signals. Furthermore, the signal block energy of each signal block is independently calculated, so that the independence of each signal block is improved, the mutual influence among the signal blocks is avoided, and the accuracy of abrupt signal identification is further improved.
Since the ecg signal is a signal of the electrical activity of the heart recorded by the electrodes attached to the outer surface of the skin, the rhythm of the human body 'S breathing, the movements of the limbs, etc. may cause the baseline wandering, and meanwhile, since each human body' S skin surface has a potential of about 30mV, the emg may be generated, and in order to eliminate the influence of the baseline wandering and the emg on the identification of the abrupt signal, as shown in fig. 2, step S101 includes:
s201, carrying out primary filtering on the initial electrocardiogram signal through a high-pass filter;
and/or the presence of a gas in the gas,
and S202, carrying out secondary filtering on the initial electrocardiogram signal through a low-pass filter.
The high-pass filter is used for carrying out primary filtering on the initial electrocardiogram signal, so that a low-frequency baseline can be eliminated, the low-pass filter is used for carrying out secondary filtering on the initial electrocardiogram signal, high-frequency electromyographic noise can be eliminated, and the accuracy of identifying the mutation signal is improved.
It should be understood that: step S101 may be: first filtering the initial electrocardiogram signal only by a high-pass filter; step S101 may also be: second filtering the initial electrocardiogram signal by only a low-pass filter; step S101 may also be: after the initial electrocardiogram signal is first filtered by the high-pass filter, the initial electrocardiogram signal is second filtered by the low-pass filter.
It should be noted that: when the first filtering and the second filtering are performed on the initial electrocardiogram signal at the same time, the sequence of the above steps S201 and S202 may be adjusted, that is: the initial electrocardiogram signal may be first filtered a second time by a low pass filter and then first filtered by a high pass filter.
In a specific embodiment, the low pass filter and the high pass filter are both FIR least-square filters, which have linear phases, do not cause waveform distortion, and are computationally inexpensive.
Wherein the cut-off frequency of the high-pass filter is 0.67Hz, and the cut-off frequency of the low-pass filter is 150 Hz.
Further, the signal block comprises a plurality of time points and a plurality of electrocardiogram sub-signals which are in one-to-one correspondence with the time points; in some embodiments of the present invention, as shown in fig. 3, step S103 comprises:
s301, determining a kernel function, a prediction time point in a signal block and a plurality of surrounding time points;
s302, determining a plurality of weights of a plurality of surrounding time points one by one through kernel functions;
s303, constructing a weight matrix according to the weights;
s304, performing linear regression on the electrocardiogram sub-signals at the predicted time points based on the minimum mean square error, and obtaining regression parameters according to the weight matrix;
s305, determining the signal energy of the electrocardiogram sub-signals at the prediction time point according to the regression parameters and the prediction time point, wherein the signal energy of the electrocardiogram sub-signals at the prediction time point is the signal block energy of the signal block.
According to the embodiment of the invention, the weights of a plurality of surrounding times are determined according to the kernel function, so that the R wave in the electrocardiogram signal can be eliminated, the R wave is prevented from being identified as the mutation signal, and the accuracy of the mutation signal identification is improved.
In one embodiment, the weights are:
where ω (i, i) is the weight of the ith surrounding time point; x is the number ofiIs the time value of the ith surrounding time point; k is a control parameter; x is a time value of the predicted time point.
As can be seen from the above equation: the weight of the surrounding time points far from the predicted time point is small, and the weight of the surrounding time points near the predicted time point is large.
In one embodiment, the signal block energy of the signal block is:
y＝ω'x
ω'＝(xTwx)-1xTWy
wherein y is the signal block energy of the signal block; omega' is a regression parameter; x is the number ofTA transposed matrix for x; w is a weight matrix; m is the total number of surrounding time points.
In order to know the energy difference between adjacent signal blocks to facilitate analysis of the electrocardiogram signal, in some embodiments of the present invention, the average energy of two adjacent signal blocks needs to be calculated. In some embodiments of the present invention, the signal energy at the tail time point in the previous signal block is taken as its average energy, and the signal energy at the head time point in the subsequent signal block is taken as its average energy, so that, in some embodiments of the present invention, the window length of the sliding window filter is equal to the step size.
Wherein, the tail time point refers to the last time point in the signal block, and the head time point refers to the first time point in the signal block.
Therefore, in the embodiment of the present invention, the predicted time points are the head time point and the tail time point, respectively.
On the other hand, an embodiment of the present invention further provides a method for locating a sudden change signal in a electrocardiogram signal, as shown in fig. 4, the method for locating a sudden change signal includes:
s401, preprocessing an initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
s402, constructing a sliding window filter, and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
s403, respectively calculating the signal block energy of each signal block in the plurality of signal blocks by a local weighted linear regression method;
s404, traversing the plurality of signal blocks along the time sequence, determining the signal block state of each signal block according to the signal block energy of each signal block, and positioning the mutation signal according to the signal block state.
Compared with the prior art, the abrupt change signal positioning method provided by the embodiment of the invention divides the electrocardiogram signal to be identified into a plurality of signal blocks by constructing the sliding window filter, then calculates the signal block energy of each signal block by the local weighted linear regression method, and determines the signal block state of each signal block according to the signal block energy so as to position the abrupt change signal instead of calculating the signal block energy of each moment in the electrocardiogram signal to be identified, thereby reducing the calculation amount. Furthermore, the method for identifying the mutation signal calculates the signal block energy of each signal block by the local weighted linear regression method, can remove the R wave in the signal block, and does not influence the mutation signal, thereby avoiding misjudging the R wave in the electrocardiogram signal to be identified as the mutation signal and improving the accuracy of positioning the mutation signal. Furthermore, the signal block energy of each signal block is independently calculated, so that the independence of each signal block is improved, the mutual influence among the signal blocks is avoided, and the accuracy of positioning the mutation signal is further improved.
In some embodiments of the present invention, the signal block status includes abrupt start, abrupt middle and abrupt end, where the signal block status is that the signal block with abrupt start is an abrupt start signal block, the signal block status is that the signal block with abrupt start is an abrupt middle signal block, and the signal block status is that the signal block with abrupt end is an abrupt end signal block.
In an embodiment of the present invention, as shown in fig. 5, step S404 specifically includes:
and S501, marking the signal block with the first energy exceeding the threshold energy in the plurality of signal blocks as S.
S502, if the energy of the first signal block S1 after the signal block S exceeds the threshold energy, the signal block S1 is marked as D, otherwise, the signal block S is marked as SE.
And S503, if the energy of the first signal block D1 behind any signal block D exceeds the threshold energy, marking the signal block D1 as D, otherwise marking the signal block D as DE.
And S504, marking the signal block with the DE or SE mark as S, wherein the first signal block with the energy exceeding the threshold energy is detected after the signal block with the DE or SE mark.
And circularly executing the steps S502 to S504 on the signal blocks along the time sequence to finish marking all the signal blocks.
Wherein, the mark S or SE represents the mutation start, namely the initial region of the mutation signal; marker D represents among the mutations; the marker DE or SE represents the end of the mutation, i.e.the end region of the mutation signal.
Further, in order to avoid transient occurrence of the abrupt change signal due to factors such as external signal interference or vibration of the detection device, and further cause the energy of the signal block to be less than the threshold energy, which results in inaccurate identification of the abrupt change signal, in some embodiments of the present invention, as shown in fig. 6, after step S504, the method further includes:
s601, judging whether the number of signal blocks between a first signal block with a signal block state of abrupt change ending and a second signal block with a signal block state of abrupt change starting immediately behind the first signal block is less than a threshold number;
s602, if the number of the signal blocks between the first signal block and the second signal block is less than the threshold number, changing the signal block state of the second signal block into abrupt change.
By comparing the number of signal blocks between the first signal block and the second signal block with the threshold number, when the number of signal blocks between the first signal block and the second signal block is less than the threshold number, it indicates that the time from the start of the abrupt change to the end of the abrupt change is less than the threshold time, that is: the mutation signal does not end. The accuracy of positioning the mutation signal is improved.
Specifically, if the signal block B2 with the SE flag (or S flag) is after the signal block B3 with the DE flag (or SE flag), and the signal block between B3 and B2 is not marked, and the number of sliders between B3 and B2 is less than the threshold number, the flag of the signal block B2 is modified to D, and the flag of the signal block B3 is modified to D.
It should be noted that: the principle and specific embodiment of each step in the mutation signal positioning method provided in the above embodiment can be referred to the corresponding content in the above mutation signal identification method embodiment, and details are not described here.
In order to better implement the method for identifying a mutation signal in the embodiment of the present invention, on the basis of the method for identifying a mutation signal, as shown in fig. 7, correspondingly, an embodiment of the present invention further provides a device 700 for identifying a mutation signal, including:
a first preprocessing unit 701, configured to preprocess the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
a first block dividing unit 702, configured to construct a sliding window filter, and divide the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
a first energy calculation unit 704 for calculating a signal block energy of each of the plurality of signal blocks by a local weighted linear regression method, respectively;
and an identifying unit 704, configured to, when the energy of the signal block is greater than the threshold energy, identify that an abrupt signal exists in the signal block corresponding to the energy of the signal block greater than the threshold energy.
Here, it should be noted that: the mutation signal identification apparatus 700 provided in the foregoing embodiment may implement the technical solutions described in the foregoing embodiments of the mutation signal identification method, and the specific implementation principles of the modules or units may refer to the corresponding contents in the foregoing embodiments of the mutation signal identification method, and are not described herein again.
In order to better implement the method for identifying a mutation signal in the embodiment of the present invention, on the basis of the method for identifying a mutation signal, as shown in fig. 8, correspondingly, the embodiment of the present invention further provides a device 800 for locating a mutation signal, including:
a second preprocessing unit 801, configured to preprocess the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
the second partitioning unit 802 is configured to construct a sliding window filter, and divide the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
a second energy calculation unit 803 for calculating a signal block energy of each of the plurality of signal blocks by a local weighted linear regression method, respectively;
the positioning unit 804 is configured to traverse the plurality of signal blocks along the time sequence, determine a signal block state of each signal block according to the signal block energy of each signal block, and position the abrupt change signal according to the signal block state.
Here, it should be noted that: the mutation signal positioning apparatus 800 provided in the foregoing embodiment can implement the technical solutions described in the foregoing mutation signal positioning method embodiments, and the specific implementation principles of the modules or units may refer to the corresponding contents in the foregoing mutation signal positioning method embodiments, and are not described herein again.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer-readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The method for identifying a mutation signal, the method for positioning and the device provided by the invention are described in detail above, a specific example is applied in the text to explain the principle and the implementation mode of the invention, and the description of the above embodiment is only used to help understand the method and the core idea of the invention; meanwhile, for those skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. An abrupt signal identification method for identifying an abrupt signal in a electrocardiogram signal, comprising:
preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
constructing a sliding window filter, and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
calculating signal block energy of each of the plurality of signal blocks by a locally weighted linear regression method;
and judging whether the energy of the signal block is greater than the threshold energy, wherein a sudden change signal exists in the signal block corresponding to the energy of the signal block greater than the threshold energy.
2. The abrupt signal identification method according to claim 1, wherein the signal block includes a plurality of time points and a plurality of electrocardiogram sub-signals in one-to-one correspondence with the plurality of time points; the separately calculating the signal block energy of each of the plurality of signal blocks by a locally weighted linear regression algorithm comprises:
determining a kernel function, a predicted time point in the signal block and a plurality of surrounding time points;
determining a plurality of weights of the plurality of surrounding time points one by one through the kernel function;
constructing a weight matrix according to the plurality of weights;
performing linear regression on the electrocardiogram sub-signals of the predicted time points based on the minimum mean square error, and obtaining regression parameters according to the weight matrix;
and determining the signal energy of the electrocardiogram sub-signals at the predicted time point according to the regression parameters and the predicted time point, wherein the signal energy of the electrocardiogram sub-signals at the predicted time point is the signal block energy of the signal block.
3. The method according to claim 2, wherein the weight is:
where ω (i, i) is the weight of the ith surrounding time point; x is the number ofiIs the time value of the ith surrounding time point; k is a control parameter; x is a time value of the predicted time point.
4. The method according to claim 3, wherein the signal block energy of the signal block is:
y＝ω'x
ω'＝(xTwx)-1xTWy
wherein y is the signal block energy of the signal block; omega' is a regression parameter; x is the number ofTA transposed matrix for x; w is a weight matrix; m is the total number of surrounding time points.
5. The method according to claim 1, wherein the preprocessing the initial electrocardiogram signal comprises:
first filtering the initial electrocardiogram signal by a high-pass filter;
and/or the presence of a gas in the gas,
the initial electrocardiogram signal is filtered a second time by a low pass filter.
6. The method of claim 1, wherein the sliding window filter has a window length equal to the step size.
7. A method for locating a mutation signal, comprising:
preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
constructing a sliding window filter, and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
calculating signal block energy of each of the plurality of signal blocks by a locally weighted linear regression method;
traversing the signal blocks along the time sequence, determining the signal block state of each signal block according to the signal block energy of the signal block, and positioning the abrupt change signal according to the signal block state.
8. The method according to claim 7, wherein the signal block status comprises mutation start, mutation neutralization and mutation end; the positioning the abrupt signal according to the signal block state comprises:
judging whether the number of signal blocks between a first signal block of which the signal block state is abrupt change end and a second signal block of which the signal block state immediately after the first signal block is abrupt change start is smaller than a threshold number or not;
and if the number of the signal blocks between the first signal block and the second signal block is less than the threshold number, changing the signal block state of the second signal block into abrupt change.
9. An abrupt signal identification apparatus, comprising:
the first preprocessing unit is used for preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
the first blocking unit is used for constructing a sliding window filter and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
a first energy calculation unit for calculating a signal block energy of each of the plurality of signal blocks by a local weighted linear regression method, respectively;
and the identification unit is used for judging whether the energy of the signal block is greater than the threshold energy or not, and the signal block corresponding to the energy of the signal block greater than the threshold energy has a sudden change signal.
10. An abrupt signal positioning device, comprising:
the second preprocessing unit is used for preprocessing the initial electrocardiogram signal to generate an electrocardiogram signal to be identified;
the second block dividing unit is used for constructing a sliding window filter and dividing the electrocardiogram signal to be identified into a plurality of signal blocks through the window filter;
a second energy calculation unit for calculating a signal block energy of each of the plurality of signal blocks by a local weighted linear regression method, respectively;
and the positioning unit is used for traversing the plurality of signal blocks along the time sequence, determining the signal block state of each signal block according to the signal block energy of the signal block, and positioning the mutation signal according to the signal block state.
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