CN112438731A - Electrocardiosignal analysis method, electrocardiosignal analysis device and storage medium - Google Patents
Electrocardiosignal analysis method, electrocardiosignal analysis device and storage medium Download PDFInfo
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Abstract
The invention discloses an electrocardiosignal analysis method, an electrocardiosignal analysis device and a storage medium. The electrocardiosignal analysis method comprises the following steps: acquiring an electrocardiosignal; determining at least one electrocardiogram signal segment to be analyzed; respectively calculating the average area of the appointed wave bands of the electrocardiosignal fragments to be analyzed, wherein the appointed wave bands comprise at least one of ST band, T wave and ST-T wave band; and analyzing by using the average area of the appointed wave band of the electrocardiosignal segment to be analyzed. Through the mode, the electrocardiosignal analysis accuracy can be improved.
Description
Technical Field
The present application relates to the field of electrocardiography, and in particular, to an electrocardiographic signal analysis method, system, device, and storage medium.
Background
Electrocardiogram (ECG) has been widely used in clinical practice since its birth. At present, the body surface electrocardiosignals of a patient are mainly acquired clinically through examination modes such as a conventional electrocardiogram, a dynamic electrocardiogram, a exercise load test, a monitoring/remote electrocardiogram and the like, and preliminary diagnosis of myocardial related diseases such as myocardial ischemia, Myocardial Infarction (MI), Acute Coronary Syndrome (ACS) and the like is completed through ST-T evaluation.
The conventional electrocardiogram usually acquires 10s electrocardiogram signals, and the dynamic change process of the ST segment of the electrocardiogram of the subject 10s is difficult to reflect, so the amplitude of a certain point of the ST segment (generally, the starting point J of the ST segment) is usually used to determine the elevation/depression of the ST segment.
And long-time-course electrocardiographic examination such as exercise stress tests (usually over 5 minutes), 24h dynamic electrocardiography (Holter), telemetering/monitoring electrocardiography (over half an hour) and the like generally has long signal acquisition time, and can capture the electrocardiographic change process of a subject and some paroxysmal abnormality. The amplitude of a certain point of the ST segment (typically 40/60/80ms after the J point) is usually used in the diagnosis to determine the elevation/depression of the ST segment, and the ST change duration needs to satisfy a certain condition before it can be determined as abnormal.
In the process of collecting long-time-range electrocardiosignals such as a motion load test, a Holter, a telemetering/monitoring electrocardiogram and the like, because the collecting time is long, a patient is not braked in the collecting process, and the collecting process is easily influenced by noises such as motion interference, myoelectricity interference and the like, the amplitude measurement error of the ST section is larger, the judgment accuracy of the ST section abnormality is influenced, and further the diagnosis of related diseases of the myocardium is influenced. In addition, the heart rate of the long-term electrocardiosignal may have a larger range, and the duration of the ST segment itself may have a larger difference, so that the ST segment amplitude using a fixed observation point (e.g. 40/60/80ms after J point) has poor adaptability under different heart rates.
Disclosure of Invention
The application provides an electrocardiosignal analysis method, an electrocardiosignal analysis system, an electrocardiosignal analysis device and a storage medium, which can solve the problem that ST segment abnormity judgment accuracy is limited in the related technology to influence diagnosis of related diseases of myocardium.
In order to solve the technical problem, the application adopts a technical scheme that: provided is a method for analyzing an electrocardiosignal, comprising: acquiring an electrocardiosignal; determining at least one electrocardiogram signal segment to be analyzed; respectively calculating the average area of the appointed wave bands of the electrocardiosignal fragments to be analyzed, wherein the appointed wave bands comprise at least one of ST band, T wave and ST-T wave band; and analyzing by using the average area of the appointed wave band of the electrocardiosignal segment to be analyzed.
In order to solve the above technical problem, the present application adopts another technical solution that: the electrocardiosignal analysis system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring electrocardiosignals; the determining module is used for determining at least one electrocardiosignal segment to be analyzed; the calculating module is used for respectively calculating the average area of the appointed wave bands of the electrocardiosignal fragments to be analyzed, and the appointed wave bands comprise at least one of ST band, T wave and ST-T wave band; and the analysis module is used for analyzing by utilizing the average area of the appointed wave band of the electrocardiosignal segment to be analyzed.
In order to solve the above technical problem, the present application adopts another technical solution that: an electrocardiosignal analysis device is provided, which comprises a processor used for executing instructions to realize the electrocardiosignal analysis method.
In order to solve the above technical problem, the present application adopts another technical solution that: there is provided a storage medium storing instructions that, when executed, implement the aforementioned electrocardiosignal analyzing method.
The beneficial effect of this application is: by acquiring an electrocardiosignal; determining at least one electrocardiogram signal segment to be analyzed; respectively calculating the average area of the appointed wave bands of the electrocardiosignal fragments to be analyzed, wherein the appointed wave bands comprise at least one of ST band, T wave and ST-T wave band; analyzing by using the average area of the appointed wave band of the electrocardiosignal segment to be analyzed; compared with the amplitude, the parameter of the average area is less influenced by noise, the information of the duration time of the specified wave band is introduced, and the average area of the specified wave band of the electrocardiosignal segment to be analyzed is adopted for analysis, so that the accuracy of electrocardiosignal analysis can be improved, and the diagnosis accuracy of the related diseases of the myocardium can be further improved.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating a method for analyzing an ECG signal according to an embodiment of the present invention;
FIG. 2 is a schematic view of a specific flow chart of S2 in FIG. 1;
FIG. 3 is another detailed schematic flow chart of S2 in FIG. 1;
FIG. 4 is a schematic view of a specific flow chart of S3 in FIG. 1;
FIG. 5 is a schematic view of a specific flow chart of S32 in FIG. 4;
FIG. 6 is a schematic flow chart diagram illustrating a method for analyzing cardiac signals according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of an embodiment of an ECG signal analysis system according to the present invention;
FIG. 8 is a schematic structural diagram of an electrocardiosignal analyzer according to an embodiment of the present invention;
FIG. 9 is a schematic structural diagram of an embodiment of a storage medium according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
The terms "first", "second" and "third" in this application are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any indication of the number of technical features indicated. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. All directional indications (such as up, down, left, right, front, and rear … …) in the embodiments of the present application are only used to explain the relative positional relationship between the components, the movement, and the like in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indication is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
FIG. 1 is a schematic flow chart of an embodiment of a method for analyzing an electrocardiographic signal according to the present invention. It should be noted that, if the result is substantially the same, the flow sequence shown in fig. 1 is not limited in this embodiment.
As shown in fig. 1, the present embodiment includes:
s1: acquiring electrocardiosignals.
The physiological electrode can be used for connecting a human body and the electrocardio acquisition equipment to acquire electrocardiosignals of each lead of a testee. The method can carry out necessary preprocessing on the electrocardiosignal, such as filtering power frequency interference, baseline drift, myoelectric interference and the like. The cardiac electrical signals can then be displayed in accordance with the leads.
The cardiac signal comprises a plurality of heart beats (which may also be referred to as cardiac cycles), a heart beat/cardiac cycle being the start of one heart beat to the start of the next heart beat. Each heart beat/cycle includes a number of wave segments, mainly including QRS complexes (representing depolarization of the ventricles), ST segments (representing completion of ventricular depolarization), T waves (representing repolarization of the ventricles), etc.
S2: at least one cardiac signal segment to be analyzed is determined.
The subject does not stop during the acquisition of the long-term electrocardiosignals, and the heart rate may have large changes. Variations in heart rate may cause variations in ST segment and/or T wave duration and area, which in turn may affect the analysis results. In order to reduce the influence of the heart rate variation on the analysis result, the electrocardiosignal can be analyzed in a segmented mode.
The number of the electrocardiosignal segments to be analyzed can be one or more. If the number of the electrocardiosignal segments is more than one, the lengths of the different electrocardiosignal segments to be analyzed can be equal or unequal. The adjacent ecg signal segments to be analyzed may be continuous or discontinuous. All the electrocardiographic signal segments to be analyzed are combined to obtain a part or all of the electrocardiographic signals.
In the process of determining the electrocardiographic signal segment to be analyzed, the determination can be automatically performed without the participation of a user, for example, the electrocardiographic signal segment to be analyzed is obtained by dividing the electrocardiographic signal in a preset manner. Human-computer interaction may also be introduced, determined with reference to the selection result input by the user. The following two determination methods are exemplified.
As shown in fig. 2, in an embodiment of the present invention, S2 includes:
s21: and receiving a first selection result from the human-computer interaction device.
The human-computer interaction means may comprise input means such as a touch screen, keyboard, mouse, etc. The user may observe the displayed cardiac signal and/or amplitude analysis results for one or more leads and input a first selection result to the human-computer interaction device to indicate the user selected cardiac signal segment. The first selection result may have different expressions according to the type of the human-computer interaction device.
S22: at least one first cardiac signal segment is determined based on the first selection.
The first selection result may have different expressions according to the type of the human-computer interaction device. And analyzing the first selection result according to the type of the man-machine interaction device, so as to obtain a starting point and an end point of the first electrocardiosignal segment.
For example, when the human-computer interaction device is a keyboard, the first selection result comprises a plurality of sets of time data input by the user, each set of time data represents a starting point and/or an ending point of a first electrocardiosignal segment, and at this time, the time data can be directly read from the first selection result to determine the first electrocardiosignal segment. Or, when the human-computer interaction device is a mouse/touch screen, the first selection result includes a plurality of positioning data and operation parameters input by the user, each positioning data is a position clicked/touched by the user, the operation parameters may include gesture parameters used when the user selects by using the mouse/touch screen, such as double-click/single-click/drag-and-drop/touch strength, the first selection result is analyzed, and the first electrocardiosignal segment may be determined by combining the displayed content and the selection mode of the first electrocardiosignal segment provided to the user.
S23: and taking each first electrocardiosignal segment as an electrocardiosignal segment to be analyzed, or performing first division on at least part of the first electrocardiosignal segments to obtain at least one electrocardiosignal segment to be analyzed.
The division parameters selected for different first cardiac signal segments may be the same or different, e.g., depending on the length of the first cardiac signal segment, to determine whether to perform the first division and the division parameters.
The partition parameters may include a partition mode and its associated parameters. For example, the division mode may be a division at a fixed time interval, and the related parameters may include the time interval and a processing mode of the non-integer division portion. If a certain first electrocardiosignal segment cannot be evenly divided by the time interval, for the part (namely, the part which is not evenly divided) with the final length smaller than the time interval, the part can be directly used as an electrocardiosignal segment to be analyzed without processing, and the part which is continuous and does not overlap with other first electrocardiosignal segments can be used for supplementing and then used as an electrocardiosignal segment to be analyzed. Of course, the division pattern may be of other types, for example, division may be performed according to a fixed number, and the like, and is not limited herein.
As shown in fig. 3, in another embodiment of the present invention, S2 includes:
s26: QRS and T waves are identified and located for each heart beat in the electrocardiosignal.
S27: and carrying out amplitude analysis on at least one of the ST segment, the T wave and the ST-T wave band of the electrocardiosignal to obtain a first analysis result.
For each heart beat in the electrocardiosignal, taking the starting point E of the QRS wave as a baseline reference point, calculating at least one of the amplitude STj of the ST segment at the J point of each heart beat, the amplitude STjx of the ST segment at X milliseconds (such as 60ms/80 ms) after the J point and the amplitude Ta of the T wave, and carrying out amplitude analysis to preliminarily judge whether the abnormality occurs. For ease of observation, the calculated amplitudes may be used to map an amplitude map of the specified band of the cardiac electrical signal.
S28: at least one first cardiac signal segment is determined based on the portion of the first analysis result where the abnormality is present.
The first electrocardiographic signal segment includes an electrocardiographic signal segment corresponding to a portion of the first analysis result in which the abnormality is present, and may further include portions before and/or after the electrocardiographic signal segment corresponding to a portion of the first analysis result in which the abnormality is present.
S29: and taking each first electrocardiosignal segment as an electrocardiosignal segment to be analyzed, or performing first division on at least part of the first electrocardiosignal segments to obtain at least one electrocardiosignal segment to be analyzed.
The division parameters selected for different first cardiac signal segments may be the same or different, e.g., depending on the length of the first cardiac signal segment, to determine whether to perform the first division and the division parameters.
The partition parameters may include a partition mode and its associated parameters. For example, the division mode may be a division at a fixed time interval, and the related parameters may include the time interval and a processing mode of the non-integer division portion. If a certain first electrocardiosignal segment cannot be evenly divided by the time interval, for the part (namely, the part which is not evenly divided) with the final length smaller than the time interval, the part can be directly used as an electrocardiosignal segment to be analyzed without processing, and the part which is continuous and does not overlap with other first electrocardiosignal segments can be used for supplementing and then used as an electrocardiosignal segment to be analyzed. Of course, the division pattern may be of other types, for example, division may be performed according to a fixed number of segments, and the like, and is not limited herein. If the correlation parameter includes both the time interval and the number of segments, and there is a length of the first cardiac signal segment that is greater than the product of the time interval and the number of segments, the excess portion can be discarded.
S3: and respectively calculating the average area of the appointed wave band of the electrocardiosignal segment to be analyzed.
The specified band includes at least one of an ST segment, a T wave, and an ST-T band, and the ST-T band is a band composed of an ST segment and a T wave with a start point of the ST segment as a start point and an end point of the T wave as an end point.
In the related art, only the change of the ST segment is used as an evaluation index of the myocardial-related diseases; in fact, after myocardial cell injury, action potentials in the depolarization period and the repolarization period have influence, which is shown on an electrocardiogram, namely, the whole QRS-ST-T wave has a certain change, so that the introduction of T waves into a specified wave band can further utilize useful information contained in electrocardiosignals, and the analysis accuracy is improved.
The average area can be calculated for some or all heart beats in the cardiac electrical signal segment to be analyzed. The start and end points of the specified band need to be determined prior to calculation. And respectively calculating each electrocardiosignal segment to be analyzed to obtain the average area of the appointed wave band of each electrocardiosignal segment to be analyzed.
As shown in fig. 4, in an embodiment of the present invention, S3 includes:
s31: a plurality of heartbeats to be analyzed in a cardiac electrical signal segment to be analyzed is determined.
The heart beats can be classified according to the morphology of QRS waves, and classified into normal, ventricular (V), interference (X), and others (such as ventricular fusion waves). The heart beat to be analyzed is the heart beat with normal QRS wave in the electrocardiosignal segment to be analyzed, namely the heart beat classified into normal class according to the morphology of the QRS wave. The abnormal QRS wave in ventricular (V), interference (X) and other (such as ventricular fusion wave) heartbeats can cause abnormal performance of the designated wave band, and therefore, the abnormal QRS wave is not used for calculating the average area so as to avoid the interference of the abnormal QRS wave on the analysis result of the designated wave band.
S32: the directed area of the assigned band for each heart beat to be analyzed is calculated separately.
The directed area of the specified band can be calculated based on the feature points of each heart beat to be analyzed, respectively. Or determining representative heartbeats and applying the feature points representing heartbeats to all heartbeats to be analyzed to calculate the directed area of the specified waveband of each heart beat to be analyzed.
The characteristic points include a start point and an end point of the specified band. The start point of the ST segment is J, the end point of the ST segment (i.e., the start point of the T wave) is Tn, and the end point of the T wave is Tf. When the designated wave band only comprises an ST segment, the characteristic points comprise J points and Tn points; when the designated wave band only comprises T waves, the characteristic points comprise Tn points and Tf points; when the designated band includes an ST-T band, the feature points include J points and Tf points. In addition, the feature points may further include the start point E of the QRS wave, which may be used to determine a baseline for subsequent area calculations.
The characteristic points can be obtained by detecting the characteristic points of the heart beat to be analyzed; or the characteristic point coordinates input by the user are received; or firstly detecting the characteristic points of the heart beat to be analyzed and displaying the detection result, then receiving the calibration data input by the user and carrying out accurate positioning calibration on the detection.
As shown in fig. 5, in a specific embodiment of the present invention, in the case of representing a heart beat, S32 includes:
s321: representative heartbeats were determined.
In determining representative heart beats, the determination may be made automatically without user involvement, for example, by taking an average template of all heart beats to be analyzed as representative heart beats. Specifically, all heartbeats to be analyzed may be aligned, correlated, superimposed, averaged, and the like, and an average template thereof may be obtained.
Or human-computer interaction may be introduced, the heart beat to be analyzed may be displayed, and the selection result input by the user is received to determine the representative heart beat. For example, a second selection result from the human-computer interaction device can be received; analyzing the second selection result according to the type and the display content of the man-machine interaction device, so as to obtain the heart beat selected by the user; if only one heart beat selected by the user is selected, the heart beat selected by the user is directly used as a representative heart beat, otherwise, the average value of the heart beats selected by the user can be obtained and used as the representative heart beat. The second selection result may have different forms of presentation depending on the type of the human-computer interaction device.
S322: the characteristic points representing the heart beats are taken as the characteristic points of all heart beats to be analyzed.
The feature points include a start point and an end point of the specified band, and further, the feature points may include a start point E of the QRS wave. Applying the characteristic points representing the heart beats to all heart beats to be analyzed, the process of locating a plurality of heart beats to be analyzed can be omitted.
S323: and respectively calculating the directed area of the appointed wave band of each heart beat to be analyzed based on the characteristic points.
The directional area is an area of a specified band with respect to a base line, and an area of a portion above the base line is a positive direction area and an area of a portion below the base line is a negative direction area.
Optionally, after the directed areas of the specified bands of all cardiac beats to be analyzed are calculated, the directed areas may be displayed in an unlimited manner, such as an independent list, an independent directed area trend graph, and a mark in other electrocardiogram signal correlation graphs (for example, a directed area is displayed in an electrocardiogram or an amplitude graph of the specified band of the electrocardiogram signal).
S33: and calculating the average value of the directed areas of the appointed wave bands of all heart beats to be analyzed as the average area of the appointed wave bands of the electrocardiosignal segments to be analyzed.
Optionally, after the average area is calculated, the average area may be displayed in an unlimited manner, such as an independent list, an independent average area trend graph, and identifications in other electrocardiographic signal correlation graphs.
S4: and analyzing by using the average area of the appointed wave band of the electrocardiosignal segment to be analyzed.
Specifically, the average area of the specified waveband of each electrocardiosignal segment to be analyzed is compared with an area threshold value to obtain an analysis result. The area threshold may be pre-stored, learned from clinical data, or user-entered, without limitation. If the average area of the designated wave band of the electrocardiosignal segment to be analyzed is larger than the area threshold, the analysis result is abnormal, otherwise, the analysis result is normal.
Optionally, the analysis result may be displayed. The display modes are not limited, such as an independent list, an independent directed area trend graph, and a mark in other electrocardiographic signal correlation graphs (for example, a mark is performed on an electrocardiographic signal segment to be analyzed by using a color corresponding to an analysis result in an amplitude graph of an appointed waveband of the electrocardiographic signal or the electrocardiographic signal).
Through the implementation of the embodiment, compared with the amplitude, the parameter of the average area is less influenced by noise, the information of the duration time of the specified waveband is introduced, and the average area of the specified waveband of the electrocardiosignal segment to be analyzed is adopted for analysis, so that the accuracy of electrocardiosignal analysis can be improved, and the diagnosis accuracy of the related diseases of the myocardium can be improved.
The complete process of electrocardiosignal analysis is illustrated below with reference to the accompanying drawings, in which the same parts as in the previous embodiment are not repeated.
As shown in fig. 6, a specific embodiment of the electrocardiosignal analyzing method of the present invention includes:
s101: acquiring electrocardiosignals.
S102: QRS and T waves are identified and located for each heart beat in the electrocardiosignal.
S103: and analyzing at least one amplitude value of an ST section, a T wave and an ST-T wave band on the electrocardiosignal to obtain a first analysis result.
S104: at least one first cardiac signal segment is determined based on the portion of the first analysis result where the abnormality is present.
S105: and performing first division on each first electrocardiosignal segment to obtain a plurality of electrocardiosignal segments to be analyzed.
The duration of the first ecg segment Seg is denoted as tlast minutes, and the first ecg segment Seg is divided into N consecutive segments as N ecg signal segments to be analyzed at a set time interval T minutes, which are denoted as Seg1, Seg2, and Seg3 … … SegN, respectively. When T last is less than N T, the last section can be processed according to the actual length, or when the electrocardiogram fragment to be analyzed still has continuous enough unselected electrocardiogram signals, the electrocardiogram fragment is automatically complemented to SegN, and the signal duration is also T minutes.
And then respectively executing S106-S110 for each electrocardiosignal segment to be analyzed.
S106: a plurality of heartbeats to be analyzed in a cardiac electrical signal segment to be analyzed is determined.
The number of heartbeats to be analyzed is M.
S107: representative heartbeats were determined.
S108: the characteristic points representing the heart beats are taken as the characteristic points of all heart beats to be analyzed.
S109: and respectively calculating the directed area of the appointed wave band of each heart beat to be analyzed based on the characteristic points.
The designated bands in this embodiment include an ST segment and an ST-T band. And (3) calculating the ST-segment directed area of each heart beat to be analyzed one by taking the point E as a base line, and recording the ST-T-segment directed area as STA (k), wherein k is 1,2 and 3 … … M.
S110: and calculating the average value of the directed areas of the appointed wave bands of all heart beats to be analyzed as the average area of the appointed wave bands of the electrocardiosignal segments to be analyzed.
The average area of the ST segment is:
the average area of the ST-T wave band is as follows:
in other embodiments, it may be chosen to calculate the average area directly after completing the calculation of the directional areas of all ST-segments/ST-T-bands, and then calculate the average area of ST-T-bands/ST-segments.
S111: and analyzing by using the average area of the appointed wave band of the electrocardiosignal segment to be analyzed.
S112: the analysis results and/or the average area are displayed.
Referring to fig. 7, fig. 7 is a schematic structural diagram of an electrocardiograph signal analysis system according to an embodiment of the present invention. As shown in fig. 7, the system 20 includes an acquisition module 21, a determination module 22, a calculation module 23, and an analysis module 24.
The obtaining module 21 is configured to obtain an electrocardiographic signal.
A determining module 22, configured to determine at least one cardiac signal segment to be analyzed.
The calculating module 23 is configured to calculate an average area of specified bands of the electrocardiographic signal segments to be analyzed, where the specified bands include at least one of an ST segment, a T wave, and an ST-T band.
And the analysis module 24 is configured to perform analysis by using the average area of the specified waveband of the electrocardiographic signal segment to be analyzed.
The specific functions of the various modules, as well as possible further divisions and other components, may be referred to in the description of the various embodiments of the electrocardiosignal analysis method of the present invention.
Referring to fig. 8, fig. 8 is a schematic structural diagram of an electrocardiograph signal analysis device according to an embodiment of the present invention. As shown in fig. 8, the apparatus 30 includes a processor 31.
The processor 31 may also be referred to as a CPU (Central Processing Unit). The processor 31 may be an integrated circuit chip having signal processing capabilities. The processor 31 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The apparatus 30 may further comprise a memory (not shown) for storing instructions and data required for the processor 31 to operate.
The processor 31 is configured to execute instructions to implement the methods provided by any of the embodiments of the electrocardiosignal analyzing method of the present invention and any non-conflicting combinations thereof.
Referring to fig. 9, fig. 9 is a schematic structural diagram of a storage medium according to an embodiment of the invention. The storage medium 40 of the embodiment of the present invention stores instructions that, when executed, implement the methods provided by any embodiment and any non-conflicting combination of the electrocardiosignal analysis method of the present invention. The instructions may form a program file stored in the storage medium in the form of a software product, so as to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute all or part of the steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a mobile hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or terminal devices, such as a computer, a server, a mobile phone, and a tablet.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, 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 through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
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 integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. The above embodiments are merely examples and are not intended to limit the scope of the present disclosure, and all modifications, equivalents, and flow charts using the contents of the specification and drawings of the present disclosure or those directly or indirectly applied to other related technical fields are intended to be included in the scope of the present disclosure.
Claims (15)
1. An electrocardiosignal analysis method, comprising:
acquiring an electrocardiosignal;
determining at least one electrocardiogram signal segment to be analyzed;
respectively calculating the average area of the appointed wave bands of the electrocardiosignal fragments to be analyzed, wherein the appointed wave bands comprise at least one of ST band, T wave and ST-T wave band;
and analyzing by using the average area of the appointed wave band of the electrocardiosignal segment to be analyzed.
2. The method of claim 1,
the determining of at least one cardiac signal segment to be analyzed comprises:
receiving a first selection result from the human-computer interaction device;
determining at least one first cardiac signal segment from the first selection;
and taking each first electrocardiosignal segment as one electrocardiosignal segment to be analyzed, or performing first division on at least part of the first electrocardiosignal segments to obtain at least one electrocardiosignal segment to be analyzed.
3. The method of claim 1,
the determining of at least one cardiac signal segment to be analyzed comprises:
identifying and positioning QRS waves and T waves of each heart beat in the electrocardiosignal;
performing amplitude analysis on at least one of an ST segment, a T wave and an ST-T wave band on the electrocardiosignal to obtain a first analysis result;
determining at least one first cardiac signal segment from the portion of the first analysis result where the abnormality is present;
and taking each first electrocardiosignal segment as one electrocardiosignal segment to be analyzed, or performing first division on at least part of the first electrocardiosignal segments to obtain at least one electrocardiosignal segment to be analyzed.
4. The method of claim 1,
the calculating the average area of the designated wave band of the electrocardiosignal segment to be analyzed comprises the following steps:
determining a plurality of heartbeats to be analyzed in the cardiac electrical signal segment to be analyzed;
respectively calculating the directed area of the appointed wave band of each heart beat to be analyzed;
and calculating the average value of the directed areas of the specified wave bands of all the heart beats to be analyzed as the average area of the specified wave bands of the electrocardiosignal segments to be analyzed.
5. The method of claim 4,
the heart beat to be analyzed is the heart beat with normal QRS wave in the electrocardiosignal segment to be analyzed.
6. The method of claim 4,
the respectively calculating the directed area of the appointed wave band of each heart beat to be analyzed comprises the following steps:
determining a representative heart beat;
taking the characteristic points representing the heart beats as the characteristic points of all the heart beats to be analyzed, wherein the characteristic points comprise the starting point and the end point of the specified wave band;
and respectively calculating the directed area of the appointed wave band of each heart beat to be analyzed based on the characteristic points.
7. The method of claim 4,
the determining to represent a heart beat includes:
acquiring an average template of all the heart beats to be analyzed as the representative heart beats; or
And receiving a second selection result from the human-computer interaction device, and taking the heart beat to be analyzed corresponding to the second selection result as the representative heart beat.
8. The method of claim 4,
the respectively calculating the directed area of the appointed wave band of each heart beat to be analyzed comprises the following steps:
and calculating the directed area of the specified wave band based on the characteristic points of each heart beat to be analyzed, wherein the characteristic points comprise the starting point and the end point of the specified wave band.
9. The method of claim 4, further comprising:
and showing the directed area of the designated wave bands of all the heartbeats to be analyzed.
10. The method of claim 1,
the analysis by using the average area of the appointed wave band of the electrocardiosignal segment to be analyzed comprises the following steps:
and respectively comparing the average area of the specified wave band of the electrocardiosignal segment to be analyzed with an area threshold value to obtain an analysis result, wherein if the average area of the specified wave band of the electrocardiosignal segment to be analyzed is larger than the area threshold value, the analysis result is abnormal.
11. The method of claim 10, further comprising:
and displaying the analysis result.
12. The method of claim 11,
the displaying the analysis result comprises:
and identifying the electrocardiosignal segment to be analyzed by using the color corresponding to the analysis result in an electrocardiogram or the amplitude diagram of the appointed wave band of the electrocardiosignal.
13. An electrocardiosignal analysis system, comprising:
the acquisition module is used for acquiring electrocardiosignals;
the determining module is used for determining at least one electrocardiosignal segment to be analyzed;
the calculation module is used for calculating the average area of the appointed wave bands of the electrocardiosignal fragments to be analyzed respectively, wherein the appointed wave bands comprise at least one of ST band, T wave and ST-T wave band;
and the analysis module is used for analyzing by utilizing the average area of the appointed wave band of the electrocardiosignal segment to be analyzed.
14. An electrocardiosignal analysis device is characterized by comprising a processor,
the processor is configured to execute instructions to implement the method of any one of claims 1-12.
15. A storage medium storing instructions that, when executed, implement the method of any one of claims 1-12.
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