阅读说明：本技术 动态心电图分析方法、心电监测设备以及存储介质 (Dynamic electrocardiogram analysis method, electrocardiogram monitoring device and storage medium ) 是由 欧凤 邱四海 范健威 黄少雄 周峰 于 2020-05-12 设计创作，主要内容包括：本申请涉及心电监测技术领域,具体公开了一种动态心电图分析方法、心电监测设备以及存储介质,该方法包括：采集若干个导联的心电信号；基于分析参数评估导联的心电信号的信号质量；根据导联的心电信号的信号质量的评估结果,判断是否对导联的心电信号进行分析。通过上述方式,能够根据导联的心电信号的信号质量,判断是否对导联的心电信号进行分析。(The application relates to the technical field of electrocardiogram monitoring, and particularly discloses a dynamic electrocardiogram analysis method, electrocardiogram monitoring equipment and a storage medium, wherein the method comprises the following steps: collecting electrocardiosignals of a plurality of leads; evaluating the signal quality of the electrocardiosignals of the leads based on the analysis parameters; and judging whether to analyze the lead electrocardiosignals or not according to the evaluation result of the signal quality of the lead electrocardiosignals. By the above mode, whether the lead electrocardiosignal is analyzed or not can be judged according to the signal quality of the lead electrocardiosignal.)

1. A method for dynamic electrocardiogram analysis, the method comprising:

collecting electrocardiosignals of a plurality of leads;

evaluating a signal quality of the cardiac electrical signal of the lead based on an analysis parameter;

and judging whether to analyze the electrocardiosignals of the leads according to the evaluation result of the signal quality of the electrocardiosignals of the leads.

2. The method of claim 1, wherein prior to the step of evaluating signal quality of the cardiac electrical signal of the lead based on the analysis parameter, the method further comprises: preprocessing the electrocardiosignals of the leads.

3. The method of claim 1, wherein the step of evaluating the signal quality of the cardiac electrical signal of the lead based on the analysis parameters comprises:

determining whether the lead contains a noise signal based on the analysis parameters;

if so, segmenting the electrocardiosignals of the leads to obtain a plurality of unit signal segments;

acquiring noise information of a plurality of unit signal segments;

and judging whether the lead is a noise lead or a non-noise lead according to the noise signals of the unit signal sections.

4. The method of claim 3, wherein said step of determining whether said lead is a noisy lead or a non-noisy lead based on the noisy signals of a plurality of said unit signal segments comprises:

quantizing the noise information of the unit signal segments to obtain corresponding digital signals;

carrying out average filtering processing on the digital signals to obtain corresponding filtering values;

if the filtering numerical value is larger than a preset noise threshold value, the lead is judged to be the noise lead, or if the filtering numerical value is smaller than or equal to the preset noise threshold value, the lead is judged to be a non-noise lead.

5. The method of claim 3, wherein after the step of determining whether the lead is a noisy lead or a non-noisy lead based on the noisy signals of the plurality of unit signal segments, the method further comprises:

if all the leads are noise leads in the same preset time period, the electrocardiosignals of all the leads in the preset time period are not analyzed.

6. The method of claim 3, wherein the leads include a preset analysis lead and a non-preset analysis lead, and wherein after the step of determining whether the lead is a noisy lead or a non-noisy lead based on the noisy signals of the plurality of unit signal segments, the method further comprises:

if the preset analysis leads are all noise leads, searching non-noise leads in the non-preset analysis leads, and analyzing the electrocardiosignals of the non-noise leads in the non-preset analysis leads; alternatively, the first and second electrodes may be,

and if the non-noise leads exist in the preset analysis leads, analyzing the electrocardiosignals of the non-noise leads in the preset analysis leads.

7. The method of claim 3, wherein said step of determining whether said lead contains a noise signal based on said analysis parameters comprises: judging whether the lead electrocardiosignal is at least one of a lead falling signal, an electrocardiosignal with overloaded signal, an electrocardiosignal in an electromyographic noise section and a motion interference signal;

after the step of determining whether the lead contains a noise signal based on the analysis parameters, the method further comprises: if yes, judging that the lead contains the noise signal.

8. The method of claim 7,

if the electrocardiosignals are all straight lines within the width range of a first preset window, judging that the electrocardiosignals of the leads are lead falling signals;

if the duration of the amplitude of the electrocardiosignal exceeding the dynamic voltage range of the dynamic electrocardiosignal acquisition equipment exceeds a preset duration threshold within the width range of a second preset window, judging that the electrocardiosignal of the lead is the electrocardiosignal with signal overload;

if the ratio of the electrocardiosignals with the frequency less than the preset frequency to the electromyographic noise with the frequency more than the preset frequency is less than or equal to a preset ratio threshold value, judging that the electrocardiosignals of the leads are electrocardiosignals in an electromyographic noise section;

and if the electrocardiosignals deviate from the baseline value and the amplitude accumulated value of the electrocardiosignals is larger than a preset amplitude threshold value within the width range of a third preset window, judging that the electrocardiosignals of the leads are motion noise signals.

9. The method of claim 1, wherein after the step of determining whether to analyze the cardiac electrical signal of the lead based on the result of the evaluation of the signal quality of the cardiac electrical signal of the lead, the method further comprises:

performing characteristic analysis on the dynamic electrocardiogram data corresponding to the electrocardiosignals to generate a dynamic electrocardiogram analysis report;

displaying and/or interpreting the holter analysis report.

10. The method of claim 9, wherein said step of characterizing said ecg data corresponding to said ecg signal comprises:

constructing an electrocardiogram analysis model;

performing heart beat detection on dynamic electrocardiogram data based on the electrocardiogram analysis model to obtain heart beat data, wherein each heart beat data corresponds to one heart beat cycle, and the heart beat data comprises the morphology and the amplitude of an ST segment, a p wave and a T wave of each heart beat cycle and start-stop time data;

the method includes classifying heartbeat data and performing data processing on the classified heartbeat data, wherein the data processing includes at least one of electrocardiogram preprocessing, arrhythmia analysis, ST-segment analysis, and heart rate variability analysis.

11. An electrocardiographic monitoring device, comprising:

a processor and a memory coupled to the processor;

wherein the memory is configured to store one or more computer instructions and the processor is configured to execute the computer instructions in the memory to implement the holter analysis method of any of claims 1-10.

12. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for dynamic electrocardiogram analysis according to any one of claims 1 to 10.

Technical Field

The application relates to the technical field of electrocardiogram monitoring, in particular to a dynamic electrocardiogram analysis method, electrocardiogram monitoring equipment and a storage medium.

Background

The dynamic electrocardiogram can continuously record the whole process of the electrocardiogram activity for more than 24 hours, including the electrocardiogram information under different conditions of rest, activity, dining, work, study, sleep and the like.

The dynamic electrocardiogram analysis system mainly comprises three parts of electrocardiosignal acquisition equipment, a lead system and computer analysis software. The signal acquisition recorder is responsible for recording and storing the 24-hour or even multi-day electrocardiogram data of the patient.

The inventor of the application discovers that in the long-term research and development process, the frequent change of the body of a patient in daily activities is large, the received noise conditions are more, partial noise signals can be filtered in the prior art, but the noise caused by stronger motion noise or poor electrode loose contact and the like can not be well filtered out, and the subsequent heart beat detection and classification accuracy is poor.

Disclosure of Invention

Based on this, the present application provides a dynamic electrocardiogram analysis method, an electrocardiogram monitoring apparatus, and a storage medium, which can determine whether to analyze a lead electrocardiogram signal according to the signal quality of the lead electrocardiogram signal.

In one aspect, the present application provides a method for dynamic electrocardiogram analysis, including: collecting electrocardiosignals of a plurality of leads; evaluating the signal quality of the electrocardiosignals of the leads based on the analysis parameters; and judging whether to analyze the lead electrocardiosignals or not according to the evaluation result of the signal quality of the lead electrocardiosignals.

On the other hand, this application provides an electrocardio monitoring facilities, includes: a processor and a memory coupled to the processor; wherein the memory is used for storing one or more computer instructions, and the processor is configured to execute the computer instructions in the memory to realize the aforementioned analysis method of dynamic electrocardiogram.

In yet another aspect, the present application provides a storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the aforementioned method for dynamic electrocardiogram analysis.

The beneficial effect of this application is: different from the situation of the prior art, the method and the device can evaluate the signal quality of the filtered electrocardiosignals of each lead based on the analysis parameters, judge whether to analyze the electrocardiosignals of each lead according to the signal quality of the electrocardiosignals of each lead, do not analyze the electrocardiosignals with serious noise, effectively improve the accuracy of an automatic analysis result, assist a doctor to quickly finish a dynamic electrocardio analysis report, and improve the analysis efficiency.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts. Wherein:

FIG. 1 is a schematic flow chart of a first embodiment of a dynamic electrocardiogram analysis method of the present application;

FIG. 2 is a schematic flow chart of a second embodiment of the dynamic electrocardiogram analysis method of the present application;

FIG. 3 is a schematic flow chart of step S20 in FIG. 1;

FIG. 4 is a schematic flow chart of step S24 in FIG. 3;

FIG. 5 is another schematic flow chart of step S20 in FIG. 1;

FIG. 6 is a schematic flow chart of step S20 in FIG. 1;

FIG. 7 is a schematic flow chart of a third embodiment of the dynamic electrocardiogram analysis method of the present application;

FIG. 8 is a schematic flow chart of step S50 in FIG. 7;

FIG. 9 is a schematic structural diagram of an embodiment of an electrocardiograph monitoring device according to the present application.

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 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.

Referring to fig. 1, the present application provides a dynamic electrocardiogram analysis method, which includes:

s10: collecting a plurality of leads of electrocardiosignals.

The dynamic electrocardiogram is generally detected by 12-lead or 18-lead dynamic electrocardiosignal acquisition equipment. In the practical application of this application can adopt multiple heart electrograph signal acquisition electrode sensor, like gold matter, silver matter, paster, electrically conductive cloth etc. be connected with measurand's body surface through multiple mode. Acquiring electrocardiosignals of leads I, II, III, aVR, aVL, aVF, V1, V2, V3, V4, V5 and V6 or electrocardiosignals of leads I, II, III, avR, avL, avF, V1, V2, V3, V4, V5, V6, V7, V8, V9, V3R, V4R and V5R of the tested person according to an electrocardiogram measurement standard at a preset position of the connection.

S20: evaluating the signal quality of the electrocardiosignals of the leads based on the analysis parameters.

Specifically, the analysis parameter refers to a parameter set by a clinician according to dynamic electrocardiographic data corresponding to the electrocardiographic signal, where the analysis parameter may include at least one of a start, a peak or trough, and an end position of a P wave, a start, a peak or trough, and an end position of a T wave, a start, a peak or trough, and an end position of a QRS complex, whether the subject is equipped with a pacemaker, and a noise removal processing parameter.

S30: and judging whether to analyze the lead electrocardiosignals or not according to the evaluation result of the signal quality of the lead electrocardiosignals.

Specifically, the signal quality of each lead electrocardiosignal is judged, and whether different processing and analysis are carried out on the lead electrocardiosignals is judged according to the evaluation result of the signal quality. For example, when all leads have noise in the same time period, the electrocardiogram signal of the segment is considered to be interfered by the noise and is not suitable for analyzing the electrocardiogram signal.

When the preset analysis leads (namely the leads set by a user for analysis such as heart beat detection) have noise, searching the leads without noise in the non-analysis leads for the electrocardio analysis of the section of electrocardiosignals; when the electrocardiosignals of the preset analysis leads are all noiseless interference signals, the preset analysis leads are used for carrying out subsequent electrocardio analysis according to the conventional flow.

Different from the situation of the prior art, the method and the device can evaluate the signal quality of the filtered electrocardiosignals of each lead based on the analysis parameters, judge whether to analyze the electrocardiosignals of each lead according to the signal quality of the electrocardiosignals of each lead, do not analyze the electrocardiosignals with serious noise, effectively improve the accuracy of an automatic analysis result, assist a doctor to quickly finish a dynamic electrocardio analysis report, and improve the analysis efficiency.

Referring to fig. 2, in an embodiment, before step S20, the method further includes:

s40: preprocessing the electrocardiosignals of the leads.

Because the electrocardiogram is accompanied with the daily activities of the person to be measured, and the daily activities bring noises to the electrocardiogram to a certain extent, a lot of noises are usually coupled to the original signals in the process of acquiring the electrocardiogram signals. The main noise source can be divided into high-frequency noise and low-frequency noise, the high-frequency noise comprises power frequency and myoelectricity noise, and the low-frequency noise is baseline drift noise.

In order to accurately evaluate the signal quality of the electrocardiographic signals of the leads, the present embodiment performs noise removal processing on the electrocardiographic signals of the leads of the subject before step S20. Specifically, in this step, a discrete wavelet transform method can be used to eliminate high-frequency noise, and a zero-phase digital filtering method is used to eliminate low-frequency baseline wander noise, so that the signal quality evaluation of the lead electrocardiosignals is more accurate and reliable.

Referring to fig. 3, in an embodiment, the step S20 includes:

s21: determining whether the lead contains a noise signal based on the analysis parameters.

Specifically, whether the lead electrocardiosignal is at least one of a lead-off signal, an electrocardiosignal with an overloaded signal, an electrocardiosignal in an electromyographic noise section and a motion interference signal is judged. If yes, the lead is determined to contain a noise signal. At this time, the process proceeds to step S22.

S22: and segmenting the electrocardiosignals of the leads to obtain a plurality of unit signal segments.

Specifically, the noise segment window width of the lead containing the noise signal is obtained, the least common divisor of the noise segment window widths is used as the minimum signal segment of noise information fusion, and the electrocardiosignal of the lead is divided by taking the minimum signal segment as a unit to obtain a plurality of unit signal segments.

S23: noise information of a plurality of unit signal segments is acquired.

S24: and judging whether the lead is a noise lead or a non-noise lead according to the noise signals of the unit signal sections.

Specifically, whether the electrocardiosignals of the unit signal segment are lead-off signals and/or whether the signals are overloaded and/or whether the electrocardiosignals are located in an electromyographic noise segment and/or whether the electrocardiosignals are motion noise signals is evaluated. If the electrocardiosignal of the A unit signal segment is a lead falling signal, and/or the electrocardiosignal of the A unit signal segment is a signal overload, and/or the A unit signal segment is an electromyographic noise segment, and/or the electrocardiosignal of the A unit signal segment is a motion noise signal, judging that the A unit signal segment is a noise signal segment; otherwise, the A unit signal segment is judged to be a noiseless signal segment.

Referring to fig. 4, in the present embodiment, step S24 includes:

s241: and quantizing the noise information of the unit signal segments to obtain corresponding digital signals.

Specifically, in order to avoid that the detected noise interference signal segment is too short, the integration can be performed according to the noise information of a plurality of unit signal segments, and a specific implementation may be to quantize the noise information into a digital signal, for example, the noise signal segment can be quantized to 1, and the noise-free signal segment can be quantized to 0.

S242: and carrying out average filtering processing on the digital signals to obtain corresponding filtering values.

Specifically, the digital signal quantized in step S241 is subjected to average filtering processing with a window of M to obtain a corresponding filtering value.

S243: and if the filtering numerical value is greater than the preset noise threshold value, judging the lead to be a noise lead, or if the filtering numerical value is less than or equal to the preset noise threshold value, judging the lead to be a non-noise lead.

In this embodiment, after the lead drop determination, the signal overload determination, the myoelectric noise determination, and the motion noise determination are performed on a plurality of unit signal segments, and the signal quality of each lead electrocardiographic signal is determined after fusion is performed according to the noise determination result of each lead, which can solve the problem that the detection error is large due to the fact that the detected noise interferes with the signal segment too short in the prior art.

Referring to fig. 5, after the step S24, the method further includes:

s25: if all leads are noise leads in the same preset time period, the electrocardiosignals of all leads in the preset time period are not analyzed.

In this embodiment, the leads include preset analysis leads and non-preset analysis leads, and referring to fig. 6, after step S24, the method further includes:

s26: if the preset analysis leads are all noise leads, searching non-noise leads in the non-preset analysis leads, and analyzing the electrocardiosignals of the non-noise leads in the non-preset analysis leads.

Or, S27: and if the non-noise leads exist in the preset analysis leads, analyzing the electrocardiosignals of the non-noise leads in the preset analysis leads.

Specifically, when all leads have noise in the same preset time period, the electrocardiosignals in the preset time period are considered to be interfered by the noise, and the electrocardiosignals are not suitable for analyzing the electrocardiosignals; when the preset analysis leads (namely the leads set by a user for analysis such as heart beat detection) have noise, searching the leads without noise in the non-analysis leads for the electrocardio analysis of the section of electrocardiosignals; when the electrocardiosignals of the preset analysis leads are all noiseless interference signals, the preset analysis leads are used for carrying out subsequent electrocardio analysis according to the conventional flow. For example, the electrocardiosignals to be analyzed are conventional 12-lead signals, i.e. including I, II, III, aVR, aVL, aVF, V1, V2, V3, V4, V5 and V6, and the analysis leads to be set are II, V1 and V5; when noise interference exists in II, V1 and V5 within a certain time period, searching a lead without noise in other lead signals within the corresponding time period, such as V6 for subsequent electrocardio analysis; when II, V1, V5 have no noise interference in a certain time period, the set analysis leads II, V1, V5 are used for subsequent electrocardio analysis.

Through the mode, the embodiment can avoid analyzing the noise interference of the leads to influence the accuracy of the algorithm analysis result, and the performance of the automatic analysis result is improved.

In this embodiment, if all the electrocardiographic signals are straight lines within the first preset window width range, the electrocardiographic signal of the lead is determined to be a lead-off signal.

The step of collecting a plurality of leads of electrocardiosignals comprises: and collecting a plurality of lead electrocardiosignals by dynamic electrocardiosignal collecting equipment. If the duration that the amplitude of the electrocardiosignal exceeds the dynamic voltage range of the dynamic electrocardiosignal acquisition equipment exceeds a preset duration threshold within the second preset window width range, the electrocardiosignal of the lead is judged to be the electrocardiosignal with signal overload.

Specifically, the signal overload judgment is mainly determined according to the dynamic voltage range acquired by the dynamic electrocardiosignal acquisition equipment, and if the amplitude of the acquired signal exceeds the dynamic voltage range of the dynamic electrocardiosignal acquisition equipment, the signal is truncated at a position exceeding the dynamic voltage range. According to the characteristic, when the length of the truncation of the electrocardiosignal exceeds a set threshold a in the second preset window width range, the section of the electrocardiosignal is considered to be signal overload, for example, the dynamic voltage range of the dynamic electrocardiosignal acquisition equipment is-5 mV to 5mV, the set window width is 5s, the threshold is 3s, and when the length of the truncation of the electrocardiosignal is greater than 3s, the section of the electrocardiosignal is considered to be signal overload.

And if the ratio of the electrocardiosignals with the frequency less than the preset frequency to the electromyographic noise with the frequency more than the preset frequency is less than or equal to a preset ratio threshold value, judging that the electrocardiosignals of the leads are the electrocardiosignals in the electromyographic noise section.

Specifically, the electromyographic noise section is judged mainly according to the frequency range of the electromyographic signals of the body surface skin of the tested person between 0Hz and 1000Hz, the maximum frequency of a power spectrum is usually between 30Hz and 300Hz, and the frequency range of P-QRS-T waves of the electrocardiosignals is mostly below 30 Hz. Considering the difference between the frequency ranges of the electromyographic noise and the electrocardiosignals, the frequency more than 30Hz can be set as the electromyographic noise, and the frequency less than 30Hz can be set as the electrocardio component. Whether the electrocardiosignal is positioned in the myoelectric noise section is judged through the calculation of the signal-to-noise ratio (signal-to-noise ratio) between the electrocardiosignal and the myoelectric noise, and if so, the unit signal section is the myoelectric noise section.

And if the electrocardiosignals deviate from the baseline value and the amplitude accumulated value of the electrocardiosignals is greater than the preset amplitude threshold value within the width range of the third preset window, judging the electrocardiosignals of the leads to be motion noise signals.

Referring to fig. 7, in an embodiment, after the step S30, the method further includes:

s50: and performing characteristic analysis on the dynamic electrocardiogram data corresponding to the electrocardiosignals to generate a dynamic electrocardiogram analysis report.

Specifically, the processor is loaded with an electrocardiogram analysis model, and performs characteristic analysis on dynamic electrocardiogram data corresponding to the electrocardiosignals of the leads to be analyzed. The heart beat type can be automatically marked through an electrocardiogram analysis model, typical electrocardiogram waveforms can be automatically acquired from dynamic electrocardiogram data, and abnormal waveforms such as premature beats, ST segment uplifting and downward shifting and the like can be further detected. Furthermore, by means of the electrocardiogram analysis model, heart rate calculation, arrhythmia analysis, heart rate variability analysis and myocardial ischemia analysis can be carried out, and a dynamic electrocardiogram analysis report can be generated.

S60: displaying and/or interpreting the dynamic electrocardiogram analysis report.

Specifically, the display content not only includes the display content of a general dynamic electrocardiogram analysis system, but also can perform differential display on the signal with serious noise interference judged by the signal quality, and if the signal is gray, a clinician can conveniently and quickly identify the signal in the noise section; in addition, since the diagnostic result of the clinician is affected by the effective data analysis duration, the present embodiment also interprets the effective data analysis time (where the effective data analysis time is the data acquisition duration-the severe noise interference duration), so as to facilitate the clinician to quickly know the signal quality and confirm the diagnostic result.

In this way, this embodiment can carry out quick, accurate analysis to developments heart electrograph data, produces the analysis report, helps current developments heart electrograph analysis personnel to improve analysis efficiency, and the problem that developments heart electrograph analysis personnel resource is deficient is solved in the phase change.

Referring to fig. 8, further, the step S50 includes:

s51: and constructing an electrocardiogram analysis model.

S52: and performing heart beat detection on the dynamic electrocardiogram data based on the electrocardiogram analysis model to obtain heart beat data.

Wherein each heartbeat data corresponds to a heartbeat cycle, and the heartbeat data comprises the morphology and amplitude of the ST segment, the p-wave and the T-wave and the start-stop time data of each heartbeat cycle.

S53: the heart beat data is classified, and the classified heart beat data is processed.

Specifically, the detailed characteristic information of P-waves and T-waves splits the ventricular heart beat classification into finer heart beat classifications, including: ventricular premature beat (V), Ventricular Escape (VE), accelerated ventricular premature beat (VT), subdividing supraventricular heartbeat-like into supraventricular premature beat (S), atrial escape (SE), Junctional Escape (JE), and atrial accelerated premature beat (AT), etc.

Wherein the data processing includes at least one of electrocardiogram preprocessing, arrhythmia analysis, ST segment analysis, and heart rate variability analysis.

The specific contents are as follows:

and (4) electrocardiogram preprocessing, including denoising processing and R wave position detection on the electrocardiogram.

Arrhythmia analysis, namely arrhythmia analysis of the preprocessed electrocardiogram signals, wherein the arrhythmia analysis comprises minimum heart rate, maximum heart rate, average heart rate, ventricular anomaly detection and frequency statistics, bigeminal rhythm detection, paired ventricular anomaly statistics, string ventricular anomaly statistics, ventricular tachycardia detection, supraventricular bradycardia detection, asystole detection and the like. Wherein, the index and the threshold for judging the arrhythmia can be set.

And ST segment analysis, namely performing S-T segment detection on the preprocessed electrocardiogram signals, and judging the raising and lowering of the S-T segment according to set indexes. To assist in myocardial ischemia analysis.

And HRV analysis, namely performing heart rate variability analysis according to the R wave detection result in the electrocardiogram preprocessing result, wherein the heart rate variability analysis comprises day and night analysis and the heart rate variability analysis result based on the motion situation.

Referring to fig. 9, the present application provides an electrocardiographic monitoring device 100.

The electrocardiographic monitoring device 100 includes: a processor 101 and a memory 102 connected to the processor 101.

Wherein the memory 102 is used for storing one or more computer instructions, and the processor 101 is configured to execute the computer instructions in the memory to implement the steps in the above-mentioned method for dynamic electrocardiogram analysis, and the detailed description of the related contents refers to the above-mentioned method section, which is not described in detail herein.

In an embodiment of the present Application, the Processor 101 may be at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller, and a microprocessor. It is understood that the electronic devices for implementing the above processor functions may be other devices, and the embodiments of the present application are not limited in particular. The camera module 1 may further comprise a memory 102, the memory 102 may be connected to the processor 101, wherein the memory 102 is configured to store executable program code comprising computer operating instructions, and the memory 102 may comprise a high-speed RAM memory and may further comprise a non-volatile memory, such as at least two disk memories.

In practical applications, the Memory 102 may be a volatile Memory (volatile Memory), such as a Random-Access Memory (RAM); or a non-volatile Memory (non-volatile Memory), such as a Read-Only Memory (ROM), a flash Memory (flash Memory), a Hard Disk (Hard Disk Drive, HDD) or a Solid-State Drive (SSD); or a combination of the above types of memories and provides instructions and data to the processor 101.

Different from the situation of the prior art, the method and the device can evaluate the signal quality of the filtered electrocardiosignals of each lead based on the analysis parameters, judge whether to analyze the electrocardiosignals of each lead according to the signal quality of the electrocardiosignals of each lead, do not analyze the electrocardiosignals with serious noise, effectively improve the accuracy of an automatic analysis result, assist a doctor to quickly finish a dynamic electrocardio analysis report, and improve the analysis efficiency.

The present application provides a storage medium, on which a program is stored, the program, when executed by a processor, implements the steps in the above-mentioned method for dynamic electrocardiogram analysis, and the detailed description of the related contents refers to the above-mentioned method section, which is not described in detail herein.

Specifically, the program instructions corresponding to a method for analyzing a dynamic electrocardiogram according to the present embodiment may be stored on a storage medium such as an optical disc, a hard disk, or a usb disk.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of implementations of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart block or blocks and/or flowchart block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks in the flowchart and/or block diagram block or blocks.

Different from the situation of the prior art, the method and the device can evaluate the signal quality of the filtered electrocardiosignals of each lead based on the analysis parameters, judge whether to analyze the electrocardiosignals of each lead according to the signal quality of the electrocardiosignals of each lead, do not analyze the electrocardiosignals with serious noise, effectively improve the accuracy of an automatic analysis result, assist a doctor to quickly finish a dynamic electrocardio analysis report, and improve the analysis efficiency.

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.