CN108324271B - Electrocardiosignal identification method and system and electrocardiosignal monitoring equipment - Google Patents
Electrocardiosignal identification method and system and electrocardiosignal monitoring equipment Download PDFInfo
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
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- A—HUMAN NECESSITIES
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- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
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Abstract
The invention provides an electrocardiosignal identification method, an electrocardiosignal identification system and electrocardiosignal monitoring equipment, which relate to the technical field of electrocardio and comprise the following steps: acquiring an electrocardiosignal acquired in an acquisition period; calculating a standard deviation array and a subsection standard deviation array of the electrocardiosignals according to the electrocardiosignals; identifying whether the electrocardiosignals have large interference or not according to the standard deviation array and the sub-segment standard deviation array; if the electrocardiosignals do not have large interference, calculating an average peak isolation degree and a peak isolation degree array of the electrocardiosignals according to the standard deviation and the sub-segment standard deviation array; and identifying whether the electrocardiosignals have small interference or not according to the average peak isolation and the peak isolation array. The electrocardiosignal can be judged more carefully, so that more accurate data can be provided for later signal processing, and meanwhile, the electrocardiosignal acquired in one acquisition period is judged, so that the requirement of real-time analysis can be met, and the electrocardiosignal acquisition method is suitable for real-time electrocardio monitoring.
Description
Technical Field
The invention relates to the technical field of electrocardio, in particular to an electrocardiosignal identification method, an electrocardiosignal identification system and electrocardiosignal monitoring equipment.
Background
When the electrocardiogram monitoring technology is developed rapidly, a plurality of dynamic electrocardiogram monitoring devices for non-professionals are generated, however, errors can be generated under the conditions of muscle trembling, electromagnetic interference on instruments and the like in the process of electrocardiogram making, so that the computer automatic analysis algorithm is judged wrongly, wrong electrocardiogram analysis results are given, and misleading is formed for users. Therefore, accurate identification of the electrocardiographic waveform artifact is one of the problems that the dynamic electrocardiographic monitoring equipment needs to solve urgently.
The method for recognizing the artifact in the electrocardiogram mainly relates to a real-time electrocardiogram analysis method. The real-time electrocardio analysis means that a user acquires a small segment of signal and analyzes the signal once in the signal acquisition process, so that the user can feel a real-time analysis feeling. However, the existing real-time artifact identification method has incomplete judgment on the types of artifacts, rough judgment and limited application in real-time electrocardiogram analysis. If the pseudo-error waveform is recognized manually without depending on a recognition algorithm, a user needs a certain electrocardiogram professional knowledge, which also reduces the practicability of application.
Disclosure of Invention
In view of this, the present invention aims to provide an electrocardiographic signal recognition method, system and electrocardiographic monitoring device, which can perform more detailed judgment on an electrocardiographic signal, so as to provide accurate data for later signal processing.
In a first aspect, an embodiment of the present invention provides an electrocardiograph signal identification method, including: acquiring an electrocardiosignal acquired in an acquisition period; calculating a standard deviation array and a sub-segment standard deviation array of the electrocardiosignals according to the electrocardiosignals; identifying whether the electrocardiosignals have large interference or not according to the standard deviation and the sub-segment standard deviation array; if the electrocardiosignals do not have large interference, calculating an average peak isolation degree and a peak isolation degree array of the electrocardiosignals according to the standard deviation and the sub-segment standard deviation array; and identifying whether the electrocardiosignals have small interference or not according to the average peak isolation and the peak isolation array.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where the calculating a standard deviation array and a sub-segment standard deviation array of an electrocardiograph signal according to the electrocardiograph signal includes: calculating the standard deviation of the electrocardiosignals according to the electrocardiosignals; equally dividing the electrocardiosignal into a plurality of electrocardio waveform segments according to periods; obtaining a signal amplitude of each electrocardiographic waveform segment according to the plurality of electrocardiographic waveform segments; and calculating the sub-segment standard deviation of each electrocardiographic waveform segment according to the signal amplitude of each electrocardiographic waveform segment to form a sub-segment standard deviation array.
With reference to the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the identifying, according to the standard deviation and the sub-segment standard deviation array, whether a large interference exists in the electrocardiographic signal includes: judging whether the standard deviation is larger than a first threshold value or not; if the amplitude value of the electrocardiosignal is larger than the amplitude value of the electrocardiosignal, judging that the artifact type of the electrocardiosignal amplitude sequence is large-amplitude interference; if not, judging whether all sub-segment standard deviations have sub-segment standard deviations larger than the first threshold value; if yes, acquiring the number of sub-segment standard deviations larger than the first threshold; judging whether the number of the sub-segment standard deviations larger than the first threshold is larger than a second threshold; if so, judging that the artifact type of the electrocardiosignal amplitude sequence is partial large-amplitude interference.
With reference to the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where the calculating, according to the standard deviation and the sub-segment standard deviation array, an average peak isolation and a peak isolation array of the electrocardiograph signal includes: calculating the sum of Euclidean distances of the signal amplitude of each electrocardiographic waveform segment; selecting a minimum value from the sum of Euclidean distances of signal amplitudes of a plurality of electrocardiographic waveform segments, and determining a reference signal amplitude corresponding to the minimum value; selecting a signal amplitude larger than the reference signal amplitude from the signal amplitudes of the plurality of electrocardiographic waveform segments; calculating the peak isolation of all signal amplitudes larger than the reference signal amplitude; according to the peak isolation degree, a peak isolation degree array is established; and obtaining the average peak isolation according to the peak isolation array.
With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the identifying, according to the average peak isolation and the peak isolation array, whether a small interference exists in the electrocardiograph signal includes: judging whether the average peak isolation degree is larger than a third threshold value or not; if the amplitude of the electrocardiosignal is larger than the amplitude of the electrocardiosignal, judging that the type of the artifact of the electrocardiosignal amplitude sequence is small interference; if not, judging whether the number of elements in the peak isolation degree array is larger than a fourth threshold value or not; if so, judging that the artifact type of the electrocardiosignal amplitude sequence is partial small-amplitude interference.
In a second aspect, an embodiment of the present invention further provides an electrocardiograph signal recognition system, including: the acquisition module is used for acquiring the electrocardiosignals acquired in one acquisition cycle; the calculation module is used for calculating a standard deviation array and a sub-segment standard deviation array of the electrocardiosignals according to the electrocardiosignals, and calculating an average peak isolation array and a peak isolation array of the electrocardiosignals according to the standard deviation array and the sub-segment standard deviation array if the electrocardiosignals have no large interference; the first identification module is used for identifying whether the electrocardiosignals have large interference or not according to the standard deviation and the sub-segment standard deviation array; and the second identification module is used for identifying whether the electrocardiosignals have small interference or not according to the average peak isolation degree and the peak isolation degree array.
With reference to the second aspect, an embodiment of the present invention provides a first possible implementation manner of the second aspect, where the calculating module is configured to: calculating the standard deviation of the electrocardiosignals according to the electrocardiosignals, equally dividing the electrocardiosignals into a plurality of electrocardiographic waveform segments according to the period, obtaining the signal amplitude of each electrocardiographic waveform segment according to the plurality of electrocardiographic waveform segments, calculating the sub-segment standard deviation of each electrocardiographic waveform segment according to the signal amplitude of each electrocardiographic waveform segment, and forming a sub-segment standard deviation array.
With reference to the second aspect, an embodiment of the present invention provides a second possible implementation manner of the second aspect, where the first identification module is configured to: judging whether the standard deviation is larger than a first threshold value, if so, judging that the artifact type of the electrocardiosignal amplitude sequence is large-amplitude interference, if not, judging whether all sub-segment standard deviations have sub-segment standard deviations larger than the first threshold value, if so, acquiring the number of the sub-segment standard deviations larger than the first threshold value, judging whether the number of the sub-segment standard deviations larger than the first threshold value is larger than a second threshold value, and if so, judging that the artifact type of the electrocardiosignal amplitude sequence is partial large-amplitude interference.
With reference to the second aspect, an embodiment of the present invention provides a third possible implementation manner of the second aspect, where the calculating module is configured to: calculating the sum of Euclidean distances of the signal amplitude of each electrocardiographic waveform segment; selecting a minimum value from the sum of Euclidean distances of signal amplitudes of a plurality of electrocardiographic waveform segments, and determining a reference signal amplitude corresponding to the minimum value; selecting a signal amplitude larger than the reference signal amplitude from the signal amplitudes of the plurality of electrocardiographic waveform segments; calculating the peak isolation of all signal amplitudes larger than the reference signal amplitude; according to the peak isolation degree, a peak isolation degree array is established; and obtaining the average peak isolation according to the peak isolation data array.
With reference to the second aspect, an embodiment of the present invention provides a fourth possible implementation manner of the second aspect, where the second identification module includes: judging whether the average peak isolation degree is larger than a third threshold value or not; if the amplitude of the electrocardiosignal amplitude sequence is larger than the first threshold value, judging that the artifact type of the electrocardiosignal amplitude sequence is small amplitude interference, if the amplitude of the electrocardiosignal amplitude sequence is not larger than the first threshold value, judging whether the number of elements in the peak isolation degree array is larger than a fourth threshold value, and if the amplitude of the electrocardiosignal amplitude sequence is not larger than the second threshold value, judging that the artifact type of the electrocardiosignal amplitude sequence is partial small amplitude interference.
In a third aspect, an embodiment of the present invention further provides an electrocardiograph monitoring device, including a processor, and a memory connected to the processor; wherein the memory is configured to store one or more computer instructions, and the processor is configured to execute the computer instructions in the memory to identify whether there is interference in the acquired cardiac electrical signal by the method of any of the above embodiments.
The embodiment of the invention has the following beneficial effects: whether the acquired electrocardiosignals have large interference or not can be judged through the standard deviation array and the subsection standard deviation array of the electrocardiosignals, if not, whether the acquired electrocardiosignals have small interference or not can be judged according to the average wave peak isolation degree and the wave peak isolation degree array.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
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, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow chart of a method for recognizing an electrocardiosignal according to an embodiment of the present invention;
FIG. 2 is a schematic representation of an ECG signal;
FIG. 3 is a schematic representation of an ECG signal during a cycle;
fig. 4 is a flowchart of a method for determining large interference according to an embodiment of the present invention;
fig. 5 is a flowchart of a method for determining small interference according to an embodiment of the present invention;
FIG. 6 is a block diagram of an exemplary embodiment of an electrocardiosignal identification system;
fig. 7 is a structural diagram of an electrocardiograph monitoring device according to an embodiment of the present invention.
Icon:
200-an electrocardiosignal recognition system; 210-an obtaining module; 220-a calculation module; 230-a first identification module; 240-a second identification module; 300-an electrocardiographic monitoring device; 310-a processor; 320-a memory; 330-a bus; 340-communication interface.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present 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 electrocardiographic monitoring, the obtained electrocardiogram may have artifacts due to the interference in the electrocardiographic process, such as muscle vibration, electromagnetic interference received by the instrument, and the like, and the errors occurring in the interference are artifacts. Currently, the real-time analysis method is to collect a small signal every time during the process of collecting signals by a user, so as to give the user a sense of real-time analysis. However, the existing real-time artifact identification method has incomplete judgment on the types of artifacts, rough judgment and limited application in real-time electrocardiogram analysis. If the pseudo-error waveform is recognized manually without depending on a recognition algorithm, a user needs a certain electrocardiogram professional knowledge, which also reduces the practicability of application. Based on this, the electrocardiosignal identification method, the electrocardiosignal identification system and the electrocardiosignal monitoring equipment provided by the embodiment of the invention can judge whether the acquired electrocardiosignals have large interference or not through the standard deviation and subsection standard deviation arrays of the electrocardiosignals, and if the acquired electrocardiosignals do not have large interference or not, the acquired electrocardiosignals are judged to have small interference or not according to the average peak isolation degree and the peak isolation degree arrays. Furthermore, the invention does not need to carry out complex statistical analysis on a large amount of data, only needs to carry out statistical analysis on the electrocardiosignal amplitude sequence with a short period each time, has high running speed, can meet the requirement of real-time analysis, and can achieve better effect after a period of time.
To facilitate understanding of the embodiment, first, a detailed description is given to an electrocardiographic signal recognition method disclosed in the embodiment of the present invention, which is shown in fig. 1 and includes:
s110: acquiring the electrocardiosignals acquired in an acquisition period.
Shown in fig. 2, is the acquired electrocardiosignal. The user can use the dynamic electrocardiogram monitoring equipment to carry out electrocardiogram acquisition and acquire electrocardiogram signals acquired in one acquisition period, wherein the acquired electrocardiogram signals are actually signal amplitude sequences and recorded by an electrocardiogram curve with the abscissa as time and the ordinate as voltage.
S120: and calculating the standard deviation array and the sub-segment standard deviation array of the electrocardiosignals according to the electrocardiosignals.
As an example, step S120 includes: calculating the standard deviation of the electrocardiosignals according to the electrocardiosignals; equally dividing the electrocardiosignal into a plurality of electrocardio waveform segments according to the period; obtaining a signal amplitude of each electrocardiographic waveform segment according to the plurality of electrocardiographic waveform segments; and calculating the sub-segment standard deviation of each electrocardiographic waveform segment according to the signal amplitude of each electrocardiographic waveform segment to form a sub-segment standard deviation array.
The term that the electrocardiographic signal is equally divided into a plurality of electrocardiographic waveform segments according to the period means that one beat is counted as one period, and as shown in fig. 3, the time of one beat includes a P-R interval, a Q-T interval and a U-wave time. The electrocardiosignal acquired in one period comprises a plurality of one-time beats, and the one-time beats are divided into electrocardio waveform segments.
In some embodiments, before step S120, the method may further include: and carrying out data preprocessing on the acquired electrocardiosignals to filter baseline drift interference and high-frequency noise so as to obtain preprocessed electrocardio waveform data.
S130: and identifying whether the electrocardiosignals have large interference or not according to the standard deviation array and the sub-segment standard deviation array.
In some embodiments, as shown in fig. 4, step S130 specifically includes:
s131: it is determined whether the standard deviation is greater than a first threshold.
Wherein the first threshold is obtained by testing a plurality of times of known data. That is, the first threshold is a threshold that indicates that the acquired cardiac signal amplitude sequence has received a large interference when the calculated standard deviation is greater than the threshold. If so, go to step S132; if not, step S133 is performed.
S132: and judging the artifact type of the electrocardiosignal amplitude sequence as large-amplitude interference.
The term "significant interference" means that the periodicity of the electrocardiographic waveform is disordered, and the P wave, QRS wave, T wave, and U wave of the electrocardiographic waveform are unclear. For example, referring to fig. 3, the electrocardiogram is shown without interference, in which the amplitudes of P-wave, T-wave and U-wave are significantly smaller than the amplitude of R-wave, and when the type of artifact of the acquired ecg signal amplitude sequence is judged to be large interference, the presented electrocardiogram is unclear as P-wave, QRS-wave, T-wave and U-wave of the electrocardiogram, and the acquired amplitudes change disorderly.
S133: it is determined whether a sub-segment standard deviation greater than a first threshold exists. If so, step S134 and step S135 are performed.
Wherein, the step S135: and judging whether the number of the sub-segment standard deviations larger than the first threshold is larger than a second threshold in a second threshold, wherein the second threshold is a natural number, and the second threshold is used for comparing the number of the sub-segment standard deviations larger than the first threshold with the critical value to judge whether part of the interference is greatly interfered. Wherein the second threshold is based on the cardiac signal acquired during a cycle. For example, when 20 electrocardiographic waveform segments of one beat are acquired in one acquisition period, when the standard deviation of 10 electrocardiographic waveform segments in the 20 electrocardiographic waveform segments is greater than the first threshold, that is, the artifact type of the 10 electrocardiographic waveform segments is large interference, and the 10 is the second threshold. Of course, the value of the second threshold may be determined according to the number of electrocardiographic waveform segments acquired in one acquisition cycle. If so, go to step S136, and if not, go to step S140.
S136: and judging the artifact type of the electrocardiosignal amplitude sequence as partial large interference.
The term "partially large interference" means that the periodicity of the electrocardiographic waveform having a portion of the electrocardiographic waveform segment in one acquisition cycle is very disturbed, and the P wave, QRS wave, T wave, and U wave of the electrocardiographic waveform are not known.
In some embodiments, before step S130, the method further includes: and (3) establishing an array of signal amplitude values of a plurality of electrocardiographic waveform segments, and judging that the currently acquired electrocardiographic signals are in a no-signal state when the length of the array is judged to be 0. I.e. no signal is acquired.
S140: and if the electrocardiosignals do not have large interference, calculating the average peak isolation and the peak isolation array of the electrocardiosignals according to the standard deviation and the sub-segment standard deviation array.
In some embodiments, calculating an average peak isolation and a peak isolation array for the cardiac signal based on the standard deviation and the sub-segment standard deviation array comprises: calculating the sum of Euclidean distances of the signal amplitude of each electrocardiographic waveform segment; selecting a minimum value from the sum of Euclidean distances of signal amplitudes of a plurality of electrocardiographic waveform segments, and determining a reference signal amplitude corresponding to the minimum value; selecting a signal amplitude larger than a reference signal amplitude from the signal amplitudes of the plurality of electrocardiographic waveform segments; calculating the peak isolation of all signal amplitudes larger than the reference signal amplitude; according to the peak isolation degree, a peak isolation degree array is established; and obtaining the average peak isolation according to the peak isolation array.
For example, when 20 electrocardiographic waveform segments of one acquisition period are obtained, there are 20 signal amplitudes, the euclidean distance between each signal amplitude and other signal amplitudes is calculated, after the euclidean distances are obtained, the sum of the euclidean distances of one signal amplitude is calculated, that is, the 20 euclidean distances corresponding to the 20 electrocardiographic waveform segments are calculated, the sum of the 20 euclidean distances is compared, the minimum value of the sum of the 20 euclidean distances is selected, and the signal amplitude corresponding to the minimum value is determined to be the reference signal amplitude.
Wherein the reference signal amplitude acts as: the electrocardio main wave is the threshold value of the amplitude of the R wave. And after obtaining the threshold value, comparing the threshold value with the signal amplitudes of 20 electrocardiographic waveform segments, selecting the signal amplitude larger than the threshold value, and determining the position of the signal amplitude in the acquired electrocardiographic signal. In particular, since the electrocardiographic signal is recorded in the form of time on the abscissa and voltage on the ordinate, the specific position information can be expressed in terms of time.
After the position information is obtained, the peak isolation of the signal amplitude is calculated. The peak isolation is the number of peaks satisfying a condition within a certain range centered on a peak itself. For example, referring to fig. 2, if the third signal amplitude is the signal amplitude of the peak isolation to be calculated, the number of peaks satisfying the condition is found in a range equal to the left certain range and the right certain range by taking the position of the third signal amplitude as the center. The peak satisfying the condition here means that the magnitude of the peak value is a certain proportion of the signal amplitude of the peak isolation to be calculated, and the certain proportion ranges from [0.5,0.9 ]. Specifically, if there is a signal amplitude whose peak value is larger than the peak isolation degree to be calculated within a certain range centered on the position of the signal amplitude of the peak isolation degree to be calculated, the peak isolation degree of the signal amplitude of the peak isolation degree to be calculated is 0.
Wherein, the average peak isolation is the arithmetic mean of the peak isolation array.
S150: and identifying whether the electrocardiosignals have small interference or not according to the average peak isolation and the peak isolation array.
Referring to fig. 5, identifying whether there is a small interference in the electrocardiographic signal according to the average peak isolation and the peak isolation array includes:
s151: and judging whether the average peak isolation degree is larger than a third threshold value.
Specifically, the third threshold value is a critical value for determining two types of data from known normal electrocardiographic data and electrocardiographic data with a small interference. If yes, go to step S152; if not, step S153 is performed.
S152: and judging the artifact type of the electrocardiosignal amplitude sequence as small interference.
As shown in fig. 2 and 3, in the amplitude of the electrocardiosignal without interference, the amplitudes of the P wave, the T wave and the U wave are significantly smaller than the amplitude of the R wave, and the small-amplitude interference means that at least one of the amplitudes of the P wave, the T wave and the U wave is equivalent to the amplitude of the R wave, or is a certain proportion of the amplitude of the R wave, where the certain proportion may be [0.5,0.9], and we define this interference as the small-amplitude interference. The small-amplitude interference can determine P waves, R waves, T waves and U waves, but the amplitude contrast between the P waves, the T waves, the U waves and the R waves is not obvious.
S153: and judging whether the number of elements in the peak isolation degree array is larger than a fourth threshold value. If so, go to step S154; if not, step S155 is performed.
S154: and judging the artifact type of the electrocardiosignal amplitude sequence as partial small-amplitude interference.
Partial small amplitude interference means the situation with the above-mentioned small amplitude interference with a partial electrocardiographic waveform segment within one acquisition cycle.
S155: it is determined that the signal has not received interference.
Referring to fig. 6, the cardiac signal identification system 200 includes: an acquisition module 210, a calculation module 220, a first identification module 230, and a second identification module 240.
The obtaining module 210 is configured to obtain an electrocardiographic signal acquired in one acquisition cycle. The calculating module 220 is connected to the obtaining module 210, and is configured to calculate a standard deviation array and a sub-segment standard deviation array of the electrocardiographic signal according to the electrocardiographic signal, and if the electrocardiographic signal does not have a serious interference phenomenon, calculate an average peak isolation and a peak isolation array of the electrocardiographic signal according to the standard deviation array and the sub-segment standard deviation array. The first identification module 230 is connected to the calculation module 220, and is configured to identify whether the electrocardiographic signal has a large interference according to the standard deviation and the sub-segment standard deviation array. The second identification module 240 and the calculation module 220 are configured to identify whether the electrocardiograph signal has small interference according to the average peak isolation and the peak isolation array.
In some embodiments, the calculation module 220 is configured to: calculating the standard deviation of the electrocardiosignals according to the electrocardiosignals, equally dividing the electrocardiosignals into a plurality of electrocardio waveform segments according to the period, obtaining the signal amplitude of each electrocardio waveform segment according to the plurality of electrocardio waveform segments, calculating the sub-segment standard deviation of each electrocardio waveform segment according to the signal amplitude of each electrocardio waveform segment, and forming a sub-segment standard deviation array.
In some embodiments, the first identification module 230 is configured to: judging whether the standard deviation is larger than a first threshold value, if so, judging that the artifact type of the electrocardiosignal amplitude sequence is large-amplitude interference, if not, judging whether all sub-segment standard deviations have sub-segment standard deviations larger than the first threshold value, if so, acquiring the number of the sub-segment standard deviations larger than the first threshold value, judging whether the number of the sub-segment standard deviations larger than the first threshold value is larger than a second threshold value, and if so, judging that the artifact type of the electrocardiosignal amplitude sequence is partial large-amplitude interference.
In some embodiments, the calculation module 220 is configured to: calculating the sum of Euclidean distances of the signal amplitude of each electrocardiographic waveform segment; selecting a minimum value from the sum of Euclidean distances of signal amplitudes of a plurality of electrocardiographic waveform segments, and determining a reference signal amplitude corresponding to the minimum value; selecting a signal amplitude larger than a reference signal amplitude from the signal amplitudes of the plurality of electrocardiographic waveform segments; calculating the peak isolation of all signal amplitudes larger than the reference signal amplitude; according to the peak isolation degree, a peak isolation degree array is established; and obtaining the average peak isolation according to the peak isolation data array.
In some embodiments, the second identification module 240 includes: judging whether the average peak isolation degree is larger than a third threshold value or not; if the amplitude of the electrocardiosignal amplitude sequence is larger than the first threshold, judging that the artifact type of the electrocardiosignal amplitude sequence is too small, if the amplitude of the electrocardiosignal amplitude sequence is not larger than the second threshold, judging whether the number of elements in the wave crest isolation degree array is larger than a fourth threshold, and if the number of elements in the wave crest isolation degree array is larger than the fourth threshold, judging that the artifact type of the electrocardiosignal amplitude sequence is small disturbance.
The system provided by the embodiment of the present invention has the same implementation principle and technical effect as the foregoing method embodiment, and for the sake of brief description, no mention is made in the system embodiment, and reference may be made to the corresponding contents in the foregoing method embodiment.
Referring to fig. 7, the ecg monitoring device 300 includes a processor 310, a memory 320 coupled to the processor 310; wherein the memory 320 is configured to store one or more computer instructions, and the processor 310 is configured to execute the computer instructions in the memory 320 to identify whether the acquired cardiac electrical signal is interfered by the method according to any of the above embodiments.
Referring again to fig. 7, further comprising: a bus 330 and a communication interface 340, the processor 310, the communication interface 340 and the memory 320 being connected by the bus 330.
The Memory 320 may include a Random Access Memory (RAM) and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 340 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
Bus 330 can be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 7, but this does not indicate only one bus or one type of bus.
The memory 320 is used for storing a program, the processor 310 executes the program 401 after receiving an execution instruction, and the method executed by the apparatus defined by the flow process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 310, or implemented by the processor 310.
The processor 310 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 310. The Processor 310 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 320, and the processor 310 reads the information in the memory 320 and completes the steps of the method in combination with the hardware.
Unless specifically stated otherwise, the relative steps, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present invention.
In all examples shown and described herein, any particular value should be construed as merely exemplary, and not as a limitation, and thus other examples of example embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, in the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the term "connected" should be interpreted broadly, e.g., as being fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "inner", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the several embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other ways. The above-described system embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and there may be other divisions in actual implementation, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (11)
1. An electrocardiosignal identification method is characterized by comprising the following steps:
acquiring an electrocardiosignal acquired in an acquisition period;
calculating a standard deviation array and a sub-segment standard deviation array of the electrocardiosignals according to the electrocardiosignals;
identifying whether the electrocardiosignals have large interference or not according to the standard deviation and the sub-segment standard deviation array; the large interference refers to that the periodicity of the electrocardiographic wave is very disordered and the P wave, the QRS wave, the T wave and the U wave of the electrocardiographic wave are not clear;
if the electrocardiosignals do not have large interference, calculating an average peak isolation degree and a peak isolation degree array of the electrocardiosignals according to the standard deviation and the sub-segment standard deviation array; the peak isolation degree refers to the number of peaks satisfying the condition within a certain range with one peak as the center; the wave crest value meeting the condition refers to that the size of the wave crest value is a certain proportion of the signal amplitude of the isolation degree of the wave crest to be calculated;
identifying whether the electrocardiosignals have small interference or not according to the average peak isolation and the peak isolation array; the small-amplitude interference means that at least one signal amplitude of the P wave, the T wave and the U wave is equal to or a certain proportion of the amplitude of the R wave;
wherein the range of the certain ratio is [0.5,0.9 ].
2. The method for identifying an electrocardiographic signal according to claim 1, wherein the calculating a standard deviation array of an electrocardiographic signal and a standard deviation array of a sub-segment according to the electrocardiographic signal comprises:
calculating the standard deviation of the electrocardiosignals according to the electrocardiosignals;
equally dividing the electrocardiosignal into a plurality of electrocardio waveform segments according to periods;
obtaining a signal amplitude of each electrocardiographic waveform segment according to the plurality of electrocardiographic waveform segments;
and calculating the sub-segment standard deviation of each electrocardiographic waveform segment according to the signal amplitude of each electrocardiographic waveform segment to form a sub-segment standard deviation array.
3. The method for identifying electrocardiosignals according to claim 2, wherein identifying whether the electrocardiosignals have substantial interference according to the standard deviation and the sub-segment standard deviation array comprises:
judging whether the standard deviation is larger than a first threshold value or not;
if the amplitude value of the electrocardiosignal is larger than the amplitude value of the electrocardiosignal, judging that the artifact type of the electrocardiosignal amplitude sequence is large-amplitude interference;
if not, judging whether all sub-segment standard deviations have sub-segment standard deviations larger than the first threshold value;
if yes, acquiring the number of sub-segment standard deviations larger than the first threshold;
judging whether the number of the sub-segment standard deviations larger than the first threshold is larger than a second threshold;
if so, judging that the artifact type of the electrocardiosignal amplitude sequence is partial large-amplitude interference.
4. The method for identifying an ecg signal of claim 2, wherein calculating an average peak isolation and a peak isolation array of the ecg signal according to the standard deviation and the sub-segment standard deviation array comprises:
calculating the sum of Euclidean distances of the signal amplitude of each electrocardiographic waveform segment;
selecting a minimum value from the sum of Euclidean distances of signal amplitudes of a plurality of electrocardiographic waveform segments, and determining a reference signal amplitude corresponding to the minimum value;
selecting a signal amplitude larger than the reference signal amplitude from the signal amplitudes of the plurality of electrocardiographic waveform segments;
calculating the peak isolation of all signal amplitudes larger than the reference signal amplitude;
according to the peak isolation degree, a peak isolation degree array is established;
and obtaining the average peak isolation according to the peak isolation array.
5. The method for identifying electrocardiosignals according to claim 4, wherein the identifying whether the electrocardiosignals have small interference according to the average peak isolation and the peak isolation array comprises:
judging whether the average peak isolation degree is larger than a third threshold value or not;
if the amplitude of the electrocardiosignal is larger than the amplitude of the electrocardiosignal, judging that the type of the artifact of the electrocardiosignal amplitude sequence is small interference;
if not, judging whether the number of elements in the peak isolation degree array is larger than a fourth threshold value or not;
if so, judging that the artifact type of the electrocardiosignal amplitude sequence is partial small-amplitude interference.
6. An electrocardiosignal recognition system, comprising:
the acquisition module is used for acquiring the electrocardiosignals acquired in one acquisition cycle;
the calculation module is used for calculating a standard deviation array and a sub-segment standard deviation array of the electrocardiosignals according to the electrocardiosignals, and calculating an average peak isolation array and a peak isolation array of the electrocardiosignals according to the standard deviation array and the sub-segment standard deviation array if the electrocardiosignals have no large interference; the large interference refers to that the periodicity of the electrocardiographic wave is very disordered and the P wave, the QRS wave, the T wave and the U wave of the electrocardiographic wave are not clear; the peak isolation degree refers to the number of peaks satisfying the condition within a certain range with one peak as the center; the wave crest value meeting the condition refers to that the size of the wave crest value is a certain proportion of the signal amplitude of the isolation degree of the wave crest to be calculated;
the first identification module is used for identifying whether the electrocardiosignals have large interference or not according to the standard deviation and the sub-segment standard deviation array;
the second identification module is used for identifying whether the electrocardiosignals have small interference or not according to the average peak isolation degree and the peak isolation degree array; the small-amplitude interference means that at least one signal amplitude of the P wave, the T wave and the U wave is equal to or a certain proportion of the amplitude of the R wave;
wherein the range of the certain ratio is [0.5,0.9 ].
7. The system of claim 6, wherein the computing module is configured to: calculating the standard deviation of the electrocardiosignals according to the electrocardiosignals, equally dividing the electrocardiosignals into a plurality of electrocardiographic waveform segments according to the period, obtaining the signal amplitude of each electrocardiographic waveform segment according to the plurality of electrocardiographic waveform segments, calculating the sub-segment standard deviation of each electrocardiographic waveform segment according to the signal amplitude of each electrocardiographic waveform segment, and forming a sub-segment standard deviation array.
8. The system for cardiac signal identification according to claim 7, wherein the first identification module is configured to: judging whether the standard deviation is larger than a first threshold value, if so, judging that the artifact type of the electrocardiosignal amplitude sequence is large-amplitude interference, if not, judging whether all sub-segment standard deviations have sub-segment standard deviations larger than the first threshold value, if so, acquiring the number of the sub-segment standard deviations larger than the first threshold value, judging whether the number of the sub-segment standard deviations larger than the first threshold value is larger than a second threshold value, and if so, judging that the artifact type of the electrocardiosignal amplitude sequence is partial large-amplitude interference.
9. The system of claim 7, wherein the computing module is configured to: calculating the sum of Euclidean distances of the signal amplitude of each electrocardiographic waveform segment; selecting a minimum value from the sum of Euclidean distances of signal amplitudes of a plurality of electrocardiographic waveform segments, and determining a reference signal amplitude corresponding to the minimum value; selecting a signal amplitude larger than the reference signal amplitude from the signal amplitudes of the plurality of electrocardiographic waveform segments; calculating the peak isolation of all signal amplitudes larger than the reference signal amplitude; according to the peak isolation degree, a peak isolation degree array is established; and obtaining the average peak isolation according to the peak isolation data array.
10. The system of claim 9, wherein the second identification module comprises: judging whether the average peak isolation degree is larger than a third threshold value or not; if the amplitude of the electrocardiosignal amplitude sequence is larger than the first threshold value, judging that the artifact type of the electrocardiosignal amplitude sequence is small amplitude interference, if the amplitude of the electrocardiosignal amplitude sequence is not larger than the first threshold value, judging whether the number of elements in the peak isolation degree array is larger than a fourth threshold value, and if the amplitude of the electrocardiosignal amplitude sequence is not larger than the second threshold value, judging that the artifact type of the electrocardiosignal amplitude sequence is partial small amplitude interference.
11. An electrocardiograph monitoring device comprising a processor, a memory connected to said processor; wherein the memory is for storing one or more computer instructions, the processor being configured to execute the computer instructions in the memory to identify whether there is interference with the acquired cardiac electrical signal by the method of any one of claims 1 to 5.
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