CN113786200B - Electrocardiosignal processing method, electrocardiosignal processing device, electrocardiosignal processing equipment and readable medium - Google Patents
Electrocardiosignal processing method, electrocardiosignal processing device, electrocardiosignal processing equipment and readable medium Download PDFInfo
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Abstract
The embodiment of the invention discloses an electrocardiosignal processing method, a device, a system and a readable medium, wherein the method comprises the following steps: acquiring electrocardiogram data of a plurality of leads to be selected, and determining at least two leads from the plurality of leads to be selected as target leads according to the electrocardiogram data of each lead to be selected; determining data to be identified according to electrocardiogram data corresponding to the target lead, performing R wave identification on the data to be identified, and determining target characteristic data; and generating a target RR interval time curve according to the target characteristic data, and determining target reference data according to the target RR interval time curve. The invention improves the processing efficiency of the electrocardiosignal aiming at arrhythmia diagnosis.
Description
Technical Field
The present invention relates to the field of computer data processing, and in particular, to an electrocardiographic signal processing method, apparatus, device, and readable medium.
Background
With the acceleration of life rhythm and the change of dietary structure in modern industrial society, arrhythmia becomes an epidemic disease with high morbidity, poorer prognosis and larger harm. In the prior art, diagnosis of arrhythmia is generally obtained by extracting approximate waveform characteristics such as R wave, T wave, cardiac cycle, etc. contained in electrocardiogram data and analyzing whether the rhythm is normal.
In actual clinical diagnosis, however, there is an abnormal isorhythmic arrhythmia, which is characterized by extremely short-lived attacks, mild or absent symptoms, and more importantly, by an electrocardiogram whose waveform, rhythm and frequency are close to those of a normal basic rhythm. Therefore, the electrocardio analysis method in the prior art cannot extract the corresponding tiny waveform detail characteristics in the electrocardiogram corresponding to the arrhythmia of the rhythm, such as ultrashort array atrial flutter, potential atrial rhythm or slow rate atrial speed and the like. This delays the early detection and early treatment of abnormal arrhythmias.
Disclosure of Invention
In view of the above, it is necessary to provide an electrocardiographic signal processing method, an electrocardiographic signal processing apparatus, a computer device, and a readable medium.
A method of processing an electrical cardiac signal, the method comprising:
acquiring electrocardiogram data of a plurality of leads to be selected, and determining at least two leads from the plurality of leads to be selected as target leads according to the electrocardiogram data of each lead to be selected;
determining data to be identified according to electrocardiogram data corresponding to the target lead, performing R wave identification on the data to be identified, and determining target characteristic data;
and generating a target RR interval time curve according to the target characteristic data, and determining target reference data according to the target RR interval time curve.
Wherein, further, the determining at least two leads from the leads to be selected as target leads according to the electrocardiogram data of the leads to be selected comprises:
respectively determining electrocardiogram characteristic information of the electrocardiogram data of each lead to be selected, wherein the electrocardiogram characteristic information comprises at least one of R wave amplitude, R wave slope, T wave amplitude, T wave slope and/or R wave and T wave amplitude ratio;
and comparing the electrocardio characteristic information with preset waveform characteristics, and determining the target lead according to the comparison result of the preset waveform characteristics and the electrocardio characteristic information.
The determining the data to be identified according to the electrocardiogram data corresponding to the target lead comprises the following steps:
acquiring a data segment of which the R wave amplitude is smaller than a preset threshold value in electrocardiogram data corresponding to the target lead, and performing preset amplification processing on the data segment;
and filtering the electrocardiogram data corresponding to the target lead according to a preset frequency threshold, and acquiring the electrocardiogram data corresponding to the target lead after filtering as the data to be identified.
Furthermore, the target leads comprise a first target lead and a second target lead, and the target data to be identified comprises first target data to be identified and second target data to be identified;
the step of comparing the electrocardiographic characteristic information with preset waveform characteristics and determining the target lead according to the comparison result of the preset waveform characteristics and the electrocardiographic characteristic information comprises the following steps:
determining electrocardiogram data of which the R wave amplitude value meets a first preset condition, the T wave amplitude value meets a second preset condition and the R wave-T wave amplitude ratio meets a preset ratio threshold as the first target data to be identified according to the electrocardiogram characteristic information, and determining leads to be selected corresponding to the first target data to be identified as the first target leads;
and determining electrocardiogram data of which the R wave amplitude value meets a first preset condition and the T wave amplitude value does not meet a second preset condition as second target to-be-identified data according to the electrocardiogram characteristic information, and determining leads to be selected corresponding to the second target to-be-identified data as second target leads.
Further, the R-wave recognition of the target data to be recognized to determine target feature data includes:
determining cardiac cycle information corresponding to the target data to be identified, and determining target cardiac rhythm information according to the cardiac cycle information;
and determining a maximum amplitude point in the target data to be identified according to the electrocardio characteristic information, and determining R wave peak data in the target data to be identified as the target characteristic data according to the maximum amplitude point and the target cardiac rhythm information.
Further, after determining R-wave peak data in the target data to be identified as the target feature data according to the maximum amplitude point and the target cardiac rhythm information, the method further includes:
determining data, of which the cardiac rhythm does not meet a preset rhythm threshold value, in the target data to be identified as target abnormal data according to the target cardiac rhythm information;
matching the R wave crest corresponding to the first target data to be identified with the R wave crest corresponding to the second target data to be identified, and acquiring unmatched data in the first target data to be identified and the second target data to be identified as target abnormal data;
determining a heart beat interval corresponding to the target data to be identified according to the cardiac rhythm information, and acquiring data of which the heart beat interval does not meet a preset refractory period threshold value as the target abnormal data;
and identifying the target abnormal data according to a preset pattern identification algorithm, and determining R wave peak data in the target abnormal data as the target characteristic data.
Still further, the generating a target RR interval time curve according to the target feature data, and determining target reference data according to the target RR interval time curve include:
determining target RR interval value data corresponding to the target data to be identified according to the target characteristic data, acquiring time sequence information corresponding to the target characteristic data, and generating a target RR interval time curve according to the time sequence information and the target RR interval value data;
displaying the target RR interval time curve through a preset device, detecting an operation request for the target RR interval time curve, and determining the target reference data to be displayed according to the operation request and the target RR interval time curve;
and recognizing preset curve characteristics of the target reference data according to a preset algorithm, and displaying a curve characteristic recognition result through the preset device.
An apparatus for processing a cardiac electrical signal, the apparatus comprising:
a determination unit: the electrocardiogram data acquisition device is used for acquiring electrocardiogram data of a plurality of leads to be selected and determining at least two leads from the leads to be selected as target leads according to the electrocardiogram data of each lead to be selected;
an identification unit: the electrocardiogram data corresponding to the target lead is used as data to be identified, R wave identification is carried out on the data to be identified, and target characteristic data are determined;
a generation unit: the target characteristic data is used for generating a target RR interval time curve according to the target characteristic data, and target reference data is determined according to the target RR interval time curve.
Wherein the determining unit is further configured to:
respectively determining electrocardiogram characteristic information of the electrocardiogram data of each lead to be selected, wherein the electrocardiogram characteristic information comprises at least one of R wave amplitude, R wave slope, T wave amplitude, T wave slope and/or R wave and T wave amplitude ratio;
and comparing the electrocardio characteristic information with preset waveform characteristics, and determining the target lead according to the comparison result of the preset waveform characteristics and the electrocardio characteristic information.
The system is also used for acquiring a data segment of which the R wave amplitude is smaller than a preset threshold value in the electrocardiogram data corresponding to the target lead, and performing preset amplification processing on the data segment;
and filtering the electrocardiogram data corresponding to the target lead according to a preset frequency threshold, and acquiring the electrocardiogram data corresponding to the target lead after filtering as the data to be identified.
The identification unit is further configured to:
according to the electrocardiogram characteristic information, electrocardiogram data with the R wave amplitude value meeting a first preset condition, the T wave amplitude value meeting a second preset condition and the R wave-T wave amplitude ratio meeting a preset ratio threshold value are determined to be the first target data to be identified, and leads to be selected corresponding to the first target data to be identified are determined to be the first target leads;
and determining electrocardiogram data of which the R wave amplitude value meets a first preset condition and the T wave amplitude value does not meet a second preset condition as second target to-be-identified data according to the electrocardiogram characteristic information, and determining leads to be selected corresponding to the second target to-be-identified data as second target leads.
Still further, the identification unit is further configured to: determining cardiac cycle information corresponding to the target data to be identified, and determining target cardiac rhythm information according to the cardiac cycle information;
and determining a maximum amplitude point in the target data to be identified according to the electrocardio characteristic information, and determining R wave peak data in the target data to be identified as the target characteristic data according to the maximum amplitude point and the target cardiac rhythm information.
Still further, the determining unit further includes:
determining data, of which the cardiac rhythm does not meet a preset rhythm threshold value, in the target data to be identified as target abnormal data according to the target cardiac rhythm information;
matching the R wave crest corresponding to the first target data to be identified with the R wave crest corresponding to the second target data to be identified, and acquiring unmatched data in the first target data to be identified and the second target data to be identified as target abnormal data;
determining a heart beat interval corresponding to the target data to be identified according to the cardiac rhythm information, and acquiring data of which the heart beat interval does not meet a preset refractory period threshold value as the target abnormal data;
and identifying the target abnormal data according to a preset pattern identification algorithm, and determining R wave peak data in the target abnormal data as the target characteristic data.
Optionally, the determining unit further includes:
determining target RR interval value data corresponding to the target data to be identified according to the target characteristic data, acquiring time sequence information corresponding to the target characteristic data, and generating a target RR interval time curve according to the time sequence information and the target RR interval value data;
displaying the target RR interval time curve through a preset device, detecting an operation request for the target RR interval time curve, and determining the target reference data to be displayed according to the operation request and the target RR interval time curve;
and recognizing preset curve characteristics of the target reference data according to a preset algorithm, and displaying a curve characteristic recognition result through the preset device.
A computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the steps of the above-mentioned cardiac electrical signal processing method when executing the computer program.
A computer-readable storage medium, in which a computer program is stored, which, when executed by a processor, causes the processor to carry out the steps of the above-mentioned cardiac signal processing method. In the embodiment of the invention, firstly, electrocardiogram data of a plurality of leads to be selected is obtained, at least two leads are determined from the plurality of leads to be selected as target leads according to the electrocardiogram data of the plurality of leads to be selected, then data to be identified are determined according to the electrocardiogram data corresponding to the target leads, R-wave identification is carried out on the data to be identified, target characteristic data are determined, finally, a target RR interval time curve is generated according to the target characteristic data, and target reference data are determined according to the target RR interval time curve.
Compared with the prior art which lacks the processing and extraction of the R-wave related characteristics in the electrocardiogram data, the method has the advantages that the electrocardiosignal processing efficiency for certain arrhythmia diseases is low, and the diagnosis efficiency is further low.
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 embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Wherein:
FIG. 1 shows a flow diagram of a method of cardiac electrical signal processing in one embodiment;
FIG. 2 shows a flow diagram of a method of target lead determination in one embodiment;
FIG. 3 is a diagram illustrating waveforms corresponding to a target lead in one embodiment;
FIG. 4 shows a flow diagram of a method of target lead determination in another embodiment;
FIG. 5 shows a flow diagram of a method for cardiac target feature data determination in one embodiment;
FIG. 6 is a flow chart of a method for processing a cardiac electrical signal in another embodiment;
FIG. 7 shows a flow diagram of a target reference data determination method in one embodiment;
FIG. 8 is a block diagram of an embodiment of an apparatus for processing cardiac electrical signals;
FIG. 9 is a diagram illustrating an internal structure of a computer device in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The present invention provides a method for processing an electrocardiographic signal, and in one embodiment, the present invention may be based on a computer processing device, such as a computer. Alternatively, the invention may be based on a cardiac signal acquisition and processing device, such as a portable ECG monitor.
Referring to fig. 1, an embodiment of the present invention provides an electrocardiograph signal processing method.
FIG. 1 shows a flow chart of a method for processing an electrical cardiac signal in one embodiment. The method for processing an electrocardiographic signal according to the present invention at least includes steps S1022 to S1026 shown in fig. 1, which are described in detail as follows:
in step S1022, electrocardiographic data of a plurality of leads to be selected is acquired, and at least two leads from the plurality of leads to be selected are determined as target leads according to the electrocardiographic data of each lead to be selected.
It should be noted that, the multiple candidate leads here may be 12 leads, 8 leads or 6 leads commonly used in electrocardiographic signal acquisition. In order to acquire as many candidate data as possible, thereby ensuring the accuracy of determining the target data for extracting the electrocardiographic feature data from the candidate data in the subsequent step, in an alternative embodiment, 12 leads are preferentially used as a plurality of leads to be selected here.
In addition, the electrocardiogram data may be acquired by a preset electrocardiogram signal acquisition device such as an electrocardiogram machine. And the electrocardiographic data may be data that is continuously acquired for a longer period of time in order to improve the determination from electrocardiographic data.
The role of selecting at least two leads from the leads to be selected as target leads here is: in order to extract a characteristic wave band (such as an R wave with the most obvious wave crest fluctuation in the whole cardiac cycle) with disease diagnosis significance from the electrocardiosignals of a person to be detected, filtering, variable amplification and other processing are carried out on the electrocardio data according to a preset analysis algorithm. If the method is carried out on the basis of the electrocardiosignal data acquired by the original leads, the waveform distortion and the distortion are caused when the processed electrocardiosignals are restored to the conventional electrocardiogram form, so that the deviation can be influenced when the electrocardiogram correspondingly output according to the leads is diagnosed.
Therefore, the target lead can be determined from the preset multi-lead, and the target lead channel is taken as a single isolated analysis channel. The data of the analysis channel is not used for restoring an electrocardiogram (final output of a general electrocardiogram device) and measuring and calculating related parameters, but is only used for analyzing and identifying the electrocardiogram characteristics such as R wave, and after the waveform identification and marking are finished and the result data and the characteristic variable output are finished, the at least two analysis channels are abolished or deleted.
In this embodiment, a target lead is determined from a plurality of preset leads, R-wave recognition is performed according to data of the target lead, and finally, a target RR-interval time curve and corresponding target parameter data are generated according to target feature data corresponding to the recognized R-wave, so that rapid extraction of the target parameter data is realized, and the processing efficiency of an electrocardiographic signal for diagnosing arrhythmia diseases is improved.
A particular process for determining a target lead from a plurality of candidate leads may include steps S1032-S1034 shown in fig. 2. Figure 2 shows a flow chart for determining a target lead in one embodiment.
In step S1032, electrocardiographic feature information of the electrocardiographic data of each lead to be selected is determined, where the electrocardiographic feature information includes at least one of R-wave amplitude, R-wave slope, T-wave amplitude, T-wave slope, and/or R-wave to T-wave amplitude ratio.
In order to understand the function of the electrocardiographic feature information, the waveform of the electrocardiogram and the physiological significance of various waveforms are briefly introduced.
A typical electrocardiogram includes 6 waves arranged from left to right in each cardiac cycle, which are called P-wave, Q-wave, R-wave, S-wave, T-wave and U-wave, and a cardiac cycle can be divided into the following time periods according to the distribution of different waveforms: P-R interval, QRS interval, Q-T interval, P-R segment, and S-T segment.
The P wave represents the potential change generated when the atrium is excited, the starting point of the P wave represents that the excitation reaches the atrium from the sinus node, the ending point of the P wave represents that the atrium receives the excitation completely, and the P wave is in a round blunt shape and can be accompanied with a slight incisure. The time limit is generally not more than 0.11s, and the amplitude is generally not more than 0.25mV. And the Q wave, the R wave and the S wave form a QRS complex, the time limit of the QRS complex is not more than 0.11S, wherein the Q wave is the first downward wave in the QRS complex and has the amplitude less than 1/4 of the amplitude of the R wave in the same lead, the R wave is the first upward wave in the QRS complex and has the amplitude of not more than 0.25mV.
In step S1034, the electrocardiographic feature information is compared with a preset waveform feature, and the target lead is determined according to a comparison result between the preset waveform feature and the electrocardiographic feature information.
First, the preset waveform feature herein may be a standard electrocardiogram waveform.
Specifically, the reason for comparing with the preset waveform characteristics is that: the conventional electrocardiogram data is basically derived from twelve leads, and according to the analysis of the basic electrocardiogram heart rate data, from 12 lead channels, 2 ideal channels are finally selected, wherein the ideal channels are respectively as follows:
(1) The R wave is upright and of sufficient amplitude;
(2) The T wave is low or flat and the R/T amplitude ratio is large.
It is further specifically stated herein that the target lead includes a first target lead and a second target lead, and the target data to be recognized includes a first target data to be recognized and a second target data to be recognized.
The specific basis and process for determining the target lead can refer to the waveform characteristics of the target lead shown in fig. 3, where the waveform a in fig. 3 is the waveform characteristic data output by the first target lead here, and the waveform b is the waveform characteristic data output by the second target lead here.
Therefore, the electrocardiographic feature information is compared with a preset waveform feature, and the target lead is determined according to the comparison result of the preset waveform feature and the electrocardiographic feature information, which may further include at least steps S1042-S1044 shown in fig. 4.
In step S1042, according to the electrocardiographic feature information, electrocardiographic data in which the R-wave amplitude satisfies a first preset condition, the T-wave amplitude satisfies a second preset condition, and the R-wave to T-wave amplitude ratio satisfies a preset ratio threshold is determined as the first target data to be identified, and the lead to be selected corresponding to the first target data to be identified is determined as the first target lead.
Specifically, the first preset condition here may be that the R-wave amplitude is greater than a preset peak value, and the preset peak value may be set according to actual needs, for example, 30mm/s, and is not limited herein.
It should be noted that, in this embodiment, the reason for preferentially selecting the conditions of R wave height, T wave height, and R/T ratio increase is to avoid inaccuracy caused by R wave missing and T wave misjudgment through the identification of R waves.
The effect of the target lead in comparison with the above preset conditions is that if only one lead data with a specific waveform is identified and the characteristic waveform is identified only by the data, inaccuracy may occur, and therefore a second target lead, which is a characteristic that is both possessed and needs to be screened, is obtained.
And in step S1044, determining, according to the electrocardiographic feature information, electrocardiographic data in which the R-wave amplitude satisfies a first preset condition and the T-wave amplitude does not satisfy a second preset condition as the second target to-be-identified data, and determining a lead to be selected corresponding to the second target to-be-identified data as the second target lead.
The specific second preset condition is that the T-wave amplitude is greater than the preset peak value, and the preset peak value may be set according to actual needs, for example, 30mm/s, which is not specifically limited herein.
It should be noted that, in this embodiment, the reason for selecting the lead with high R wave (amplitude) and high T wave is to facilitate the elimination of high-amplitude interference waves with a form similar to that of the R wave but without the T wave in the following when performing digital processing of the subsequent analysis channel.
In step S1024, data to be identified is determined according to the electrocardiogram data corresponding to the target lead, R-wave identification is performed on the data to be identified, and target feature data is determined.
In addition, considering that environmental noise may exist or a part of poor quality or incomplete data may exist in electrocardiogram data caused by equipment during the actual acquisition process of the electrocardiogram signals of the various leads to be selected, a preprocessing process may be performed before determining the data to be identified, which may include steps S1052-S1054 shown in fig. 5.
In step S1052, a data segment of the electrocardiographic data corresponding to the target lead, in which the amplitude of the R wave is smaller than a preset threshold, is obtained, and preset amplification processing is performed on the data segment.
The preset threshold may be an amplitude threshold of the waveform, for example, may be 5 mm/standard gain, and may specifically be set according to an actual requirement, which is not limited herein.
Specifically, after R-wave amplitudes in the electrocardiogram data corresponding to the target leads are obtained, each R-wave amplitude is compared with a preset threshold, and preset amplification processing is performed on a data segment corresponding to the R-wave amplitude smaller than the preset threshold.
It should be noted that the preset enlarging process may be specifically implemented by performing an enhancement process on all data segments.
In step S1054, filtering the electrocardiographic data corresponding to the target lead according to a preset frequency threshold, and acquiring the electrocardiographic data corresponding to the target lead after the filtering as the data to be identified.
Specifically, filtering processing is performed on the electrocardiogram data corresponding to the target lead according to a preset frequency threshold so as to remove unsatisfactory interference data, obtain the electrocardiogram data corresponding to the target lead after filtering processing, and use the electrocardiogram data as data to be identified.
Further, the filtering processing of the electrocardiogram data corresponding to the target lead according to a preset frequency threshold specifically includes but is not limited to: aiming at 2Hz high-pass filtering, filtering out the ultralow frequency part to make the base line straight; aiming at filtering of a 50Hz alternating current interference frequency band, removing electromagnetic interference of a power supply main line and high-frequency radiation; frequent disorder wavelets (including P, low-amplitude T and u waves) with standard amplitude less than 0.3mV are processed in a sequence invariant or unmarked mode, and the like.
It should be noted that, in an alternative embodiment, while performing R-wave identification on the aforementioned second target lead, a potential determination 250ms after the R-wave peak point is also performed, so as to remove a high-amplitude interference wave without a T-wave.
The process of performing R-wave recognition on the target data to be recognized and determining target feature data may further include steps S1062-S1064 shown in fig. 6, which is described below with reference to fig. 6.
In step S1062, cardiac cycle information corresponding to the target data to be identified is determined, and target cardiac rhythm information is determined according to the cardiac cycle information.
That is, first, the cardiac cycle information corresponding to the target data to be identified is determined, and then each piece of cardiac rhythm information in the time range corresponding to the cardiac cycle information is found out as the target cardiac rhythm information.
It should be noted that the rhythm of the present embodiment refers to a heart rhythm, i.e., a rhythm of the rhythm, and the electrical activity of a normal heart rhythm (rhythm) originates from a sinus node, which is called a sinus rhythm, and the frequency of the sinus node is 60 to 100 times/minute (bpm) in a normal state. Beyond this frequency sinus tachycardia is called sinus tachycardia, and below this frequency sinus bradycardia is called sinus bradycardia. The atria, atrioventricular nodes, and ventricles except the sinoatrial node have different frequencies of self-pulsation rhythms and sites, and these self-pulsation rhythm sites are called ectopic rhythm sites.
In step S1064, a maximum amplitude point in the target data to be identified is determined according to the electrocardiographic feature information, and R-wave peak data in the target data to be identified is determined as the target feature data according to the maximum amplitude point and the target cardiac rhythm information.
In addition, it should be noted that, in practical application, some electrocardiographic signal data with abnormal characteristics may not be identified according to the above method, so in an alternative embodiment, the target data to be identified may be first screened, and data that cannot be applied to simple determination of an R-wave peak (maximum amplitude polar top method) according to a maximum amplitude point is determined and corresponding preset processing is performed.
First, in a specific embodiment, the method for determining the target anomaly data herein may include the following three methods:
firstly, data of which the cardiac rhythm does not meet a preset rhythm threshold value in the target data to be identified is determined as target abnormal data according to the target cardiac rhythm information.
That is, irregular rhythm data is used as the target abnormal data, because irregular rhythm data may be caused by missing signal acquisition, and the irregular rhythm represents the missing possible complete cardiac cycle, so that the waveform characteristics will change.
Secondly, matching the R wave crest corresponding to the first target data to be identified with the R wave crest corresponding to the second target data to be identified, and acquiring unmatched data in the first target data to be identified and the second target data to be identified as the target abnormal data.
That is to say, by matching the first target data to be identified with the second target data to be identified, data with inconsistent R-wave peak appearance characteristics (such as appearance time, R-wave amplitude value and the like) can be screened out and deleted.
Thirdly, determining the heart beat interval corresponding to the target data to be identified according to the cardiac rhythm information, and acquiring data of which the heart beat interval does not meet a preset refractory period threshold value as the target abnormal data.
In particular, the preset refractory period threshold may be a typical ventricular refractory period, such as 200ms.
After the target abnormal data is determined by the method, the target abnormal data can be identified according to a preset pattern identification algorithm, so that the R wave crest data in the target abnormal data is also determined as the target characteristic data.
In an alternative embodiment, the determination of the R-wave peak may be performed using integral mathematical pattern recognition (e.g., box counting) or maximum R-wave slope recognition.
In step S1026, a target RR interval time curve is generated according to the target feature data, and target reference data is determined according to the target RR interval time curve.
First, the X-Y axis of the target RR interval time curve is formed by using the 24 hours and the time length of each RR interval as Y values, so that when the Y value is larger or smaller (i.e. usually representing an upward or downward wave), it can be determined that an abnormality occurs, and then comprehensive determination is performed according to the curve of the time period adjacent to the abnormal time curve, so as to provide a basis for diagnosing the arrhythmia.
In addition, considering that after a target RR interval time curve is generated for the abscissa according to a certain monitoring time, the curve may be too long or too short, and the change of the ordinate is not obvious, and the like, so that it is difficult to judge and extract details when the displayed target RR interval time curve is displayed, the target RR interval time curve may be further processed according to an input operation request to obtain a target reference data, and final curve feature extraction and display are performed according to the reference data. Therefore, the specific step S1026 may further include at least steps S1072 to S1076 shown in fig. 7.
First, in step S1072, target RR interval value data corresponding to the target to-be-identified data is determined according to the target feature data, time series information corresponding to the target feature data is acquired, and the target RR interval time curve is generated according to the time series information and the target RR interval value data.
It will be readily appreciated that the target RR interval value data herein includes RR interval durations for each cardiac cycle. The usefulness of obtaining this RR interval duration information is:
in an alternative embodiment, the detection time variable may be used as an abscissa, i.e., from left to right, from the detection start time (i.e., the start time point of the electrocardiographic signal acquisition is marked as 0 on the abscissa) to the detection end time, and the value of the abscissa ranges from 0 to 24 hours (a target RR interval time curve records the change of the RR interval duration within 24 hours at most).
And the ordinate information is the RR interval duration corresponding to each detection moment, and finally, a corresponding target RR interval time curve is generated by using the abscissa and the ordinate. That is, the target RR interval time curve represents each RR interval time length value included in the detection cycle arranged in time sequence, that is, the start point away from the ordinate is subjected to the non-linear processing, and the top end connects the top point of the next R wave by the solid line, and the above steps are repeated until the end of the electrocardiographic monitoring action. It should be noted that, in contrast to the conventional recording and comparison of RR interval durations for a single time period, the advantage of the longitudinal arrangement and comparison of RR interval durations according to the time sequence information is as follows: in combination with the description of the waveform characteristics of the electrocardiogram of the patient with the arrhythmia in the background art, when a spike wave with an upward peak appears in the target RR interval time curve, a sudden elongation of the RR interval can be described, which corresponds to an RR interval that is too long due to the absence of a premature atrial contraction (one of possible pathological causes) in the electrocardiogram segment. Since the rhythms of both sides of the spike wave are sinus rhythms (i.e., there are equal rhythms), the RR interval lengths of the two adjacent sections of the front and back curves of the spike wave are substantially equal. Therefore, the characteristics of the electrocardiogram waveform signals of the equal rhythm arrhythmia can be well reflected according to the target RR interval time curve.
In step S1074, the target RR interval time curve is displayed by a preset device, an operation request for the target RR interval time curve is detected, and the target reference data is determined to be displayed according to the operation request and the target RR interval time curve.
For example, the display of the target RR interval time curve may be performed on a preset display screen of an electrocardiograph, or may be performed through a computer or a mobile phone used by a relevant person.
In consideration of practical application, doctors and other related personnel may need to intercept, enlarge or label some characteristic curve segments on the basis of the target RR interval time curve according to medical knowledge and diagnosis requirements. Therefore, in a specific embodiment, the operation request detected here may be an operation request made for the target RR interval time curve, such as moving, enlarging, reducing, clipping, flipping, color or text labeling.
The specific process of operating on the target RR interval time curve according to the operation request to determine the target reference data may be as follows:
in presenting a target RR-interval time curve of a subject a to a preset electrocardiograph, an operation request of the type of enlarging and intercepting a curve portion over a certain time interval (e.g. 9. Therefore, a curve of the abscissa of 9-9.
In step S1076, a preset curve feature is identified for the target reference data according to a preset algorithm, and a curve feature identification result is displayed by the preset device.
That is, further, after the target reference data is determined according to the foregoing steps, the peak information in the target parameter data may be obtained according to a preset algorithm, for example, according to a certain screening algorithm, and the specific peak information may include a peak amplitude, a peak duration, a peak occurrence frequency, a peak occurrence time period, and the like, and considering that the target parameter data is determined according to the target RR interval time curve, the final curve feature recognition result may be to further extract the waveform feature of the target RR interval time curve after the target operation for displaying.
FIG. 8 is a block diagram of an electrocardiographic signal processing device according to an embodiment.
Referring to FIG. 8, an apparatus 1080 for processing cardiac signals according to an embodiment of the present invention comprises: determination section 1082, recognition section 1084, and generation section 1086.
Wherein the determination unit 1082: the electrocardiogram data acquisition device is used for acquiring electrocardiogram data of a plurality of leads to be selected and determining at least two leads from the leads to be selected as target leads according to the electrocardiogram data of each lead to be selected;
the identifying unit 1084: the electrocardiogram data corresponding to the target lead is used as data to be identified, R wave identification is carried out on the data to be identified, and target characteristic data are determined;
the generation unit 1086: the target characteristic data is used for generating a target RR interval time curve according to the target characteristic data, and target reference data is determined according to the target RR interval time curve.
Wherein the determining unit 1082 is further configured to:
respectively determining electrocardiogram characteristic information of the electrocardiogram data of each lead to be selected, wherein the electrocardiogram characteristic information comprises at least one of R wave amplitude, R wave slope, T wave amplitude, T wave slope and/or R wave and T wave amplitude ratio;
and comparing the electrocardio characteristic information with preset waveform characteristics, and determining the target lead according to the comparison result of the preset waveform characteristics and the electrocardio characteristic information.
The electrocardiogram data acquisition unit is also used for acquiring a data segment of which the R wave amplitude is smaller than a preset threshold value in the electrocardiogram data corresponding to the target lead and carrying out preset amplification processing on the data segment;
and filtering the electrocardiogram data corresponding to the target lead according to a preset frequency threshold, and acquiring the electrocardiogram data corresponding to the target lead after filtering as the data to be identified.
The identifying unit 1084 is further configured to:
determining electrocardiogram data of which the R wave amplitude value meets a first preset condition, the T wave amplitude value meets a second preset condition and the R wave-T wave amplitude ratio meets a preset ratio threshold as the first target data to be identified according to the electrocardiogram characteristic information, and determining leads to be selected corresponding to the first target data to be identified as the first target leads;
and determining electrocardiogram data of which the R wave amplitude value meets a first preset condition and the T wave amplitude value does not meet a second preset condition as second target to-be-identified data according to the electrocardiogram characteristic information, and determining leads to be selected corresponding to the second target to-be-identified data as second target leads.
Still further, the identifying unit 1084 is further configured to: determining cardiac cycle information corresponding to the target data to be identified, and determining target cardiac rhythm information according to the cardiac cycle information;
and determining a maximum amplitude point in the target data to be identified according to the electrocardio characteristic information, and determining R wave peak data in the target data to be identified as the target characteristic data according to the maximum amplitude point and the target cardiac rhythm information.
Still further, the determining unit 1082 further comprises:
determining data of which the cardiac rhythm does not meet a preset rhythm threshold value in the target data to be identified as target abnormal data according to the target cardiac rhythm information;
matching the R wave crest corresponding to the first target data to be identified with the R wave crest corresponding to the second target data to be identified, and acquiring unmatched data in the first target data to be identified and the second target data to be identified as the target abnormal data;
determining a heart beat interval corresponding to the target data to be identified according to the cardiac rhythm information, and acquiring data of which the heart beat interval does not meet a preset refractory period threshold value as the target abnormal data;
and identifying the target abnormal data according to a preset pattern identification algorithm, and determining R wave peak data in the target abnormal data as the target characteristic data.
Optionally, the determining unit 1082 further includes:
determining target RR interval value data corresponding to the target data to be identified according to the target characteristic data, acquiring time series information corresponding to the target characteristic data, and generating a target RR interval time curve according to the time series information and the target RR interval value data;
displaying the target RR interval time curve through a preset device, detecting an operation request for the target RR interval time curve, and determining the target reference data to be displayed according to the operation request and the target RR interval time curve;
and recognizing preset curve characteristics of the target reference data according to a preset algorithm, and displaying a curve characteristic recognition result through the preset device.
FIG. 9 is a diagram illustrating an internal structure of a computer device in one embodiment. The computer device may specifically be a terminal, and may also be a server. As shown in fig. 9, the computer device includes a processor, a memory, and a processing module, a presentation module, and an acquisition module connected by a system bus. Wherein the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program which, when executed by the processor, causes the processor to implement the present electrocardiosignal processing method. The internal memory may also have a computer program stored therein, which, when executed by the processor, causes the processor to perform the present method of cardiac electrical signal processing. Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is proposed, comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of:
determining at least two leads from the leads to be selected as target leads according to the electrocardiogram data of each lead to be selected, comprising the following steps:
respectively determining electrocardiogram characteristic information of electrocardiogram data of each lead to be selected, wherein the electrocardiogram characteristic information comprises at least one of R wave amplitude, R wave slope, T wave amplitude, T wave slope and/or R wave and T wave amplitude ratio;
and comparing the electrocardio characteristic information with the preset waveform characteristic, and determining the target lead according to the comparison result of the preset waveform characteristic and the electrocardio characteristic information.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (8)
1. A method of processing an electrical cardiac signal, the method comprising:
acquiring electrocardiogram data of a plurality of leads to be selected, and determining at least two leads from the plurality of leads to be selected as target leads according to the electrocardiogram data of each lead to be selected;
determining target data to be identified according to electrocardiogram data corresponding to the target leads, performing R-wave identification on the target data to be identified, and determining target characteristic data;
generating a target RR interval time curve according to the target characteristic data, and determining target reference data according to the target RR interval time curve;
the R-wave recognition of the target data to be recognized and the determination of the target feature data include:
determining cardiac cycle information corresponding to the target data to be identified, and determining target cardiac rhythm information according to the cardiac cycle information;
determining a maximum amplitude point in the target data to be identified according to the electrocardiogram characteristic information of the electrocardiogram data of each lead to be selected, and determining R wave peak data in the target data to be identified as the target characteristic data according to the maximum amplitude point and the target cardiac rhythm information;
the target data to be identified comprises first target data to be identified and second target data to be identified;
after determining the R wave peak data in the target data to be identified as the target characteristic data according to the maximum amplitude point and the target cardiac rhythm information, the method further comprises the following steps:
determining data, of which the cardiac rhythm does not meet a preset rhythm threshold value, in the target data to be identified as target abnormal data according to the target cardiac rhythm information;
matching the R wave crest corresponding to the first target data to be identified with the R wave crest corresponding to the second target data to be identified, and acquiring unmatched data in the first target data to be identified and the second target data to be identified as the target abnormal data;
determining a heart beat interval corresponding to the target data to be identified according to the cardiac rhythm information, and acquiring data of which the heart beat interval does not meet a preset refractory period threshold value as the target abnormal data;
and identifying the target abnormal data according to a preset pattern identification algorithm, and determining R wave peak data in the target abnormal data as the target characteristic data.
2. The method for processing electrocardiographic signals according to claim 1, wherein the determining at least two leads from the leads to be selected as target leads according to the electrocardiographic data of the leads to be selected comprises:
respectively determining the electrocardiogram characteristic information of the electrocardiogram data of each lead to be selected, wherein the electrocardiogram characteristic information comprises at least one of R wave amplitude, R wave slope, T wave amplitude, T wave slope and/or R wave and T wave amplitude ratio;
and comparing the electrocardio characteristic information with preset waveform characteristics, and determining the target lead according to the comparison result of the preset waveform characteristics and the electrocardio characteristic information.
3. The method for processing the electrocardiographic signal according to claim 1, wherein the determining the target data to be identified according to the electrocardiographic data corresponding to the target lead comprises:
acquiring a data segment of which the R wave amplitude is smaller than a preset threshold value in electrocardiogram data corresponding to the target lead, and performing preset amplification processing on the data segment;
and filtering the electrocardiogram data corresponding to the target lead according to a preset frequency threshold, and acquiring the electrocardiogram data corresponding to the target lead after filtering as the target data to be identified.
4. The method for processing a cardiac signal according to claim 2, wherein the target leads include a first target lead, a second target lead;
the step of comparing the electrocardiographic characteristic information with preset waveform characteristics and determining the target lead according to the comparison result of the preset waveform characteristics and the electrocardiographic characteristic information comprises the following steps:
determining electrocardiogram data of which the R wave amplitude value meets a first preset condition, the T wave amplitude value meets a second preset condition and the R wave-T wave amplitude ratio meets a preset ratio threshold as the first target data to be identified according to the electrocardiogram characteristic information, and determining leads to be selected corresponding to the first target data to be identified as the first target leads;
and determining electrocardiogram data of which the R wave amplitude value meets a first preset condition and the T wave amplitude value does not meet a second preset condition as second target to-be-identified data according to the electrocardiogram characteristic information, and determining leads to be selected corresponding to the second target to-be-identified data as second target leads.
5. The method for processing an electrocardiographic signal according to claim 1, wherein the generating a target RR interval time curve according to the target feature data and determining target reference data according to the target RR interval time curve comprises:
determining target RR interval value data corresponding to the target data to be identified according to the target characteristic data, acquiring time sequence information corresponding to the target characteristic data, and generating a target RR interval time curve according to the time sequence information and the target RR interval value data;
displaying the target RR interval time curve through a preset device, detecting an operation request for the target RR interval time curve, and determining the target reference data to display according to the operation request and the target RR interval time curve;
and recognizing preset curve characteristics of the target reference data according to a preset algorithm, and displaying a curve characteristic recognition result through the preset device.
6. An apparatus for processing a cardiac electrical signal, the apparatus comprising:
a determination unit: the electrocardiogram data acquisition device is used for acquiring electrocardiogram data of a plurality of leads to be selected and determining at least two leads from the leads to be selected as target leads according to the electrocardiogram data of each lead to be selected;
an identification unit: the electrocardiogram data corresponding to the target lead is used as target data to be identified, R wave identification is carried out on the target data to be identified, and target characteristic data are determined;
a generation unit: the target characteristic data is used for generating a target RR interval time curve according to the target characteristic data, and target reference data is determined according to the target RR interval time curve;
the identification unit is specifically configured to:
determining cardiac cycle information corresponding to the target data to be identified, and determining target cardiac rhythm information according to the cardiac cycle information;
determining a maximum amplitude point in the target data to be identified according to the electrocardiogram characteristic information of the electrocardiogram data of each lead to be selected, and determining R wave peak data in the target data to be identified as the target characteristic data according to the maximum amplitude point and the target cardiac rhythm information;
the target data to be identified comprises first target data to be identified and second target data to be identified;
after determining the R wave peak data in the target data to be identified as the target characteristic data according to the maximum amplitude point and the target cardiac rhythm information, the method further comprises the following steps:
determining data of which the cardiac rhythm does not meet a preset rhythm threshold value in the target data to be identified as target abnormal data according to the target cardiac rhythm information;
matching the R wave crest corresponding to the first target data to be identified with the R wave crest corresponding to the second target data to be identified, and acquiring unmatched data in the first target data to be identified and the second target data to be identified as the target abnormal data;
determining a heart beat interval corresponding to the target data to be identified according to the cardiac rhythm information, and acquiring data of which the heart beat interval does not meet a preset refractory period threshold value as the target abnormal data;
and identifying the target abnormal data according to a preset pattern identification algorithm, and determining R wave peak data in the target abnormal data as the target characteristic data.
7. A readable storage medium storing a computer program which, when executed by a processor, causes the processor to carry out the steps of the method according to any one of claims 1 to 5.
8. A computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to carry out the steps of the method according to any one of claims 1 to 5.
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| CN116369931B (en) * | 2023-03-14 | 2024-05-28 | 中国人民解放军总医院第一医学中心 | QTd-based electrocardiosignal processing method, device and storage medium |
| CN117379062B (en) * | 2023-12-12 | 2024-04-05 | 浙江好络维医疗技术有限公司 | Single-lead dry electrode electrocardiogram P wave identification method, device, equipment and medium |
| CN117462141B (en) * | 2023-12-25 | 2024-03-26 | 深圳市先健心康医疗电子有限公司 | Electrocardiosignal detection method, electrocardiosignal detection device, computer equipment and storage medium |
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