Intelligent grading early warning method, device and equipment for electrocardiogram critical value and storage medium

Abstract

The invention relates to an intelligent grading early warning method, device and equipment for an electrocardio critical value and a storage medium, and the method comprises the steps that an obtained electrocardio signal of a user is analyzed and processed, and arrhythmia features are determined; based on a preset multi-level grading standard, carrying out danger level judgment on the arrhythmia features, and determining a target danger level; according to the target danger level, a visual report is generated, and the visual report comprises a heart rate time sequence diagram and target guidance information associated with the target danger level; compared with the prior art, according to the technical scheme, the arrhythmia features can be determined by analyzing the electrocardiosignals, the danger level is judged according to the multi-level standard, and finally the visual report containing the target guidance information is generated, so that the problem of confusion after detection of a user can be effectively solved, a health management closed loop from detection to intervention is realized, and the user experience is improved. And meanwhile, the understanding and coping efficiency of the user on the electrocardio result is improved.

Description

Technical Field

[0001] This application relates to the field of medical and health technology, and in particular to an intelligent classification and early warning method, device, equipment and storage medium for critical electrocardiogram values. Background Technology

[0002] With the increasing awareness of health management and the widespread use of portable electrocardiogram (ECG) monitoring devices, users can conveniently and quickly collect their own ECG data, providing convenient conditions for daily heart health monitoring. The application of ECG monitoring technology in the field of civilian health management is becoming more and more widespread.

[0003] However, ordinary users lack professional medical knowledge and find it difficult to understand complex ECG diagnostic terminology, making it difficult to accurately judge the severity of test results and easily leading to post-test confusion. Furthermore, existing portable ECG monitoring devices lack differentiated processing mechanisms and clear intervention recommendations for results of different risk levels, leaving users unsure how to respond after obtaining the data. At the same time, the visualization of ECG data is too professional, such as the traditional RR interval grid diagram, which is not conducive to ordinary users intuitively understanding their own heart rhythm status.

[0004] The aforementioned problems prevent existing technologies from fully meeting users' needs for accurate interpretation of ECG monitoring results, tiered early warning, and subsequent health guidance, thus limiting the practical application value of portable ECG monitoring devices. Therefore, developing a system and method that can intelligently identify critical ECG values, provide scientific tiered early warning, offer clear intervention guidance, and possess user-friendly data visualization capabilities is an urgent need in the current medical and health technology field. Summary of the Invention

[0005] This application provides an intelligent grading and early warning method, device, equipment, and storage medium for critical electrocardiogram (ECG) values. By analyzing ECG signals to determine arrhythmia characteristics and judging the risk level according to multi-level standards, it finally generates a visual report containing target guidance information. This can effectively solve the problem of user confusion after examination, realize a closed loop of health management from examination to intervention, and improve the user's understanding and response efficiency of ECG results.

[0006] In a first aspect, this application provides an intelligent grading and early warning method for cardiac critical values, comprising: analyzing and processing the acquired electrocardiogram signals of a user to determine arrhythmia characteristics; determining the risk level of the arrhythmia characteristics based on a preset multi-level grading standard to determine a target risk level; and generating a visualization report based on the target risk level, wherein the visualization report contains target guidance information associated with the target risk level.

[0007] In one possible implementation, the step of analyzing and processing the acquired user's electrocardiogram (ECG) signal to determine arrhythmia characteristics specifically includes: preprocessing the ECG signal to obtain a preprocessed ECG signal; identifying the preprocessed ECG signal to obtain the heartbeat location; calculating the RR interval sequence and heart rate parameters based on the heartbeat location; and determining whether arrhythmia characteristics exist based on the RR interval sequence and the heart rate parameters, wherein the arrhythmia characteristics include at least one of atrial fibrillation characteristics, premature beat characteristics, tachycardia characteristics, severe tachycardia characteristics, bradycardia characteristics, severe bradycardia characteristics, and long pause characteristics.

[0008] In one possible implementation, the step of calculating the RR interval sequence and heart rate parameters based on the heartbeat location specifically includes: obtaining the time interval between adjacent heartbeat locations to obtain the RR interval sequence; calculating the average RR interval based on the RR interval sequence; and calculating the heart rate parameters based on the average RR interval.

[0009] In one possible implementation, determining the presence of arrhythmia features based on the RR interval sequence and the heart rate parameters specifically includes: calculating the rhythm variability index of the RR interval sequence; if the rhythm variability index is greater than a preset variability threshold, then atrial fibrillation features are determined to exist; if atrial fibrillation features are not present, then detecting whether there is an interval shorter than a preset premature beat interval threshold in the RR interval sequence; if so, premature beat features are determined to exist; if the average heart rate value in the heart rate parameters is greater than a first preset heart rate threshold and the average heart rate value is not greater than a second preset heart rate threshold, then atrial fibrillation features are determined to exist. The heart rate is assessed for the following characteristics: Tachycardia is assessed if the average heart rate value is greater than the second preset heart rate threshold, where the second preset heart rate threshold is greater than the first preset heart rate threshold; bradycardia is assessed if the average heart rate value is less than the third preset heart rate threshold and not less than a preset severe bradycardia threshold; severe bradycardia is assessed if the instantaneous heart rate values ​​corresponding to multiple consecutive heartbeat locations are all lower than the severe bradycardia threshold; and long pauses are assessed if the maximum interval value in the RR interval sequence is greater than a preset long pause threshold.

[0010] In one possible implementation, the step of determining the risk level of the arrhythmia features based on a preset multi-level grading standard to identify a target risk level specifically includes: the preset multi-level grading standard includes at least a first risk level, a second risk level, and a third risk level; wherein, if the arrhythmia features include atrial fibrillation and at least one of the following features: a heart rate parameter greater than a preset heart rate threshold parameter, premature beats, severe bradycardia, severe tachycardia, or long pauses, it is determined to be at the first risk level; if the arrhythmia features include atrial fibrillation and at least one of the following features: a heart rate parameter not greater than a preset heart rate threshold parameter, bradycardia, or tachycardia, it is determined to be at the second risk level; if the arrhythmia features do not meet the determination requirements corresponding to the first or second risk level, it is determined to be at the third risk level.

[0011] In one possible implementation, the target guidance information associated with the target hazard level specifically includes: when the target hazard level is the first hazard level, the target guidance information is a first type of guidance information; when the target hazard level is the second hazard level, the target guidance information is a second type of guidance information that differs from the content of the first type of guidance information; and when the target hazard level is the third hazard level, the target guidance information is a third type of guidance information that recommends regular monitoring.

[0012] In one possible implementation, generating a visualization report based on the target risk level specifically includes: generating a heart rate time series graph based on the RR interval sequence, and obtaining associated target guidance information based on the target risk level; generating a visualization report based on the heart rate time series graph, the target risk level, and the target guidance information; wherein the presentation format of the visualization report is configured differently according to different target risk levels, and the differentiated configuration includes at least visual differences.

[0013] Secondly, this application provides an intelligent grading and early warning device for critical electrocardiogram (ECG) values, comprising: an ECG signal analysis module, a risk level determination module, and a visualization report generation module; wherein, the ECG signal analysis module is used to analyze and process the acquired ECG signals of the user to determine arrhythmia characteristics; the risk level determination module is used to determine the risk level of the arrhythmia characteristics based on a preset multi-level grading standard to determine a target risk level; the visualization report generation module is used to generate a visualization report based on the target risk level, wherein the visualization report includes target guidance information associated with the target risk level.

[0014] Thirdly, embodiments of this application also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0015] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0016] This application provides an intelligent classification and early warning method, device, equipment, and storage medium for critical electrocardiographic values, which has the following advantages compared with the prior art:

[0017] This method analyzes and processes the acquired electrocardiogram (ECG) signals of users to determine arrhythmia characteristics; based on a preset multi-level grading standard, it determines the risk level of the arrhythmia characteristics and identifies a target risk level; based on the target risk level, it generates a visual report, which includes target guidance information associated with the target risk level. Compared with existing technologies, the technical solution of this application addresses the problem that ordinary users find it difficult to understand professional ECG terminology and judge the severity of results. By analyzing ECG signals to determine arrhythmia characteristics and determining the risk level based on preset multi-level standards, it transforms professional ECG data into a clear risk level classification, reducing the understanding threshold for users. Secondly, by generating a visual report with associated guidance information based on the target risk level, it not only solves the deficiency of existing technologies in lacking differentiated processing and intervention suggestions, providing targeted response guidance for different risk level results, but also improves the problem of traditional ECG data presentation being too professional and user-unfriendly through visualization, helping users intuitively understand their own heart health status. It can effectively solve the problem of user confusion after examination, realize a closed loop of health management from examination to intervention, and improve the efficiency of users' understanding and response to ECG results. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0021] Figure 1 This is a flowchart illustrating an embodiment of an intelligent grading and early warning method for critical electrocardiogram values ​​provided in this application;

[0022] Figure 2 This is a schematic diagram of the structure of an embodiment of an intelligent grading and early warning device for critical electrocardiogram values ​​provided in this application;

[0023] Figure 3 This is a heart rate time-series graph of an embodiment of the intelligent classification and early warning method for electrocardiographic critical values ​​provided in this application;

[0024] Figure 4 This is a schematic diagram of a report template of an embodiment of the intelligent classification and early warning method for critical electrocardiogram values ​​provided in this application;

[0025] Figure 5 This is a schematic diagram of the structure of a computer device provided in this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] The following disclosure provides numerous different embodiments or examples for implementing various structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0028] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0029] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0030] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0031] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0032] Example 1, see Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of an intelligent grading and early warning method for critical electrocardiogram values ​​provided in this application, as shown below. Figure 1 As shown, the method includes steps 101-103, as detailed below:

[0033] Step 101: Analyze and process the acquired electrocardiogram (ECG) signals of the user to determine the characteristics of arrhythmia.

[0034] In one embodiment, the user's electrocardiogram (ECG) signal is acquired using various portable ECG acquisition devices.

[0035] Specifically, the portable ECG acquisition device is equipped with two exposed stainless steel electrodes; the user presses the two exposed stainless steel electrodes directly on the portable ECG acquisition device with their index fingers or thumbs; this contact method constitutes a simple surface circuit, which can acquire a single-lead ECG signal equivalent to lead I in a standard clinical 12-lead ECG, wherein lead I reflects the electrical activity of the heart in the left-right direction and can be used to identify a variety of common arrhythmias.

[0036] Specifically, once the contact between the user and the stainless steel electrode is stable, a preset timing module will be activated to continuously collect the user's single-lead electrocardiogram (ECG) signal for a preset time. During the collection process, the weak bioelectrical signals from the body surface are amplified by the hardware circuitry in the device and converted into digital signals by an analog-to-digital converter to obtain the user's ECG signal.

[0037] Preferably, the preset time includes, but is not limited to, 30 seconds. The preset time setting needs to ensure that a sufficient number of heartbeats can be captured to meet the minimum requirements for statistical analysis of heart rate and rhythm variability, while also ensuring the convenience of a single measurement and avoiding user fatigue or poor contact due to excessive time.

[0038] In one embodiment, before analyzing the electrocardiogram (ECG) signal, a series of standardized and automated cleaning and enhancement operations are required on the original ECG signal to eliminate noise interference and extract a clear ECG signal that can be accurately measured, so as to ensure the reliability of the subsequent analysis results.

[0039] In one embodiment, the electrocardiogram (ECG) signal is preprocessed to obtain a preprocessed ECG signal.

[0040] Specifically, the preprocessing includes filtering and noise reduction of the electrocardiogram (ECG) signal to remove various types of interference from the original ECG signal.

[0041] Specifically, the ECG signal is first filtered using a narrowband notch filter to obtain a first filtered ECG signal; the first filtered ECG signal is then second filtered using a low-pass filter to obtain a second filtered ECG signal; and the second filtered ECG signal is then third filtered using a high-pass filter to obtain a third filtered ECG signal, which is then used as a preprocessed ECG signal.

[0042] Preferably, the narrowband notch filter is a 50Hz or 60Hz narrowband notch filter; the low-pass filter is a low-pass filter with a cutoff frequency of 40Hz; and the high-pass filter is a high-pass filter with a cutoff frequency of 0.67Hz.

[0043] Specifically, firstly, a 50Hz or 60Hz narrowband notch filter is used to specifically eliminate power frequency interference; a low-pass filter with a cutoff frequency of 40Hz is used to suppress high-frequency noise introduced by muscle tremors, equipment noise, etc.; at the same time, a high-pass filter with a cutoff frequency of 0.67Hz is used to filter out slow baseline drift caused by breathing, slight body movements, etc. After the above three filtering steps, the original ECG signal mainly retains the core ECG components with frequency components between 0.67Hz and 40Hz, namely the P wave, QRS complex, and T wave, thus obtaining a clean pre-processed ECG signal with clear waveform and stable baseline.

[0044] In one embodiment, the preprocessed electrocardiogram signal is identified to obtain the heartbeat location.

[0045] Specifically, the heartbeat location of the preprocessed electrocardiogram signal is identified based on the Pan-Tompkins algorithm.

[0046] Specifically, the preprocessed ECG signal is subjected to feature enhancement processing to generate an intermediate signal containing the enhanced pulse sequence; the intermediate signal is subjected to adaptive threshold detection to identify multiple peak positions; and each peak position is determined as the heartbeat position.

[0047] Preferably, the peak position is the R-wave peak position.

[0048] Specifically, when performing feature enhancement processing on the preprocessed ECG signal to generate an intermediate signal containing the enhanced pulse sequence, the preprocessed ECG signal is differentiated to obtain a first-order differential signal; the first-order differential signal is squared to obtain a square signal; and the square signal is integrated through a sliding window to generate the intermediate signal.

[0049] Specifically, when performing adaptive threshold detection on the intermediate signal and identifying multiple peak positions, a detection threshold is dynamically set based on the current or historical amplitude information of the intermediate signal; based on the detection threshold, candidate peak positions exceeding the threshold are identified from the intermediate signal; and according to a preset peak determination rule, a valid cardiac peak position is determined from the candidate peak positions.

[0050] Specifically, the preset peak determination rule is to set a minimum peak interval time; if the time interval between multiple identified candidate peak positions is less than the minimum interval time, then the candidate peak with the largest amplitude is retained as the valid heartbeat peak position.

[0051] In one embodiment, the RR interval sequence and heart rate parameters are calculated based on the heartbeat location.

[0052] Specifically, the time interval between adjacent heartbeat positions is obtained to obtain the RR interval sequence; the average RR interval is calculated based on the RR interval sequence, and the heart rate parameters are calculated based on the average RR interval.

[0053] Specifically, based on each identified heartbeat location, the time difference between every two adjacent heartbeat locations is calculated, and the time difference is used as the RR interval. Each RR interval is then arranged in chronological order to obtain an RR interval sequence. The RR interval sequence directly reflects the cycle length of each heartbeat and its changes over time, and can be used to analyze the regularity and variability of heart rhythm.

[0054] Specifically, the arithmetic mean of the RR interval sequence is calculated and used as the average RR interval; the average RR interval represents the average length of the cardiac cycle during the measurement period.

[0055] Specifically, the average RR interval is substituted into the preset average heart rate calculation formula to calculate the average heart rate, wherein the preset average heart rate calculation formula is: average heart rate = 60 / average RR interval (seconds), in beats / minute.

[0056] Specifically, each RR interval can be substituted into a preset instantaneous heart rate calculation formula to calculate the instantaneous heart rate corresponding to each RR interval, and the instantaneous heart rates corresponding to each RR interval can be arranged in chronological order to obtain an instantaneous heart rate sequence. The preset instantaneous heart rate calculation formula is: instantaneous heart rate = 60 / RR interval.

[0057] Specifically, the average heart rate is used as a heart rate parameter, or the average heart rate and the instantaneous heart rate are used as heart rate parameters.

[0058] In one embodiment, based on the RR interval sequence and the heart rate parameters, it is determined whether there are arrhythmia features, wherein the arrhythmia features include at least one of atrial fibrillation features, premature beat features, tachycardia features, severe tachycardia features, bradycardia features, severe bradycardia features, and long pause features.

[0059] In one embodiment, the rhythm variability index of the RR interval sequence is calculated. If the rhythm variability index is greater than a preset variability threshold, then atrial fibrillation characteristics are determined to exist.

[0060] Specifically, the root mean square value of the time difference between adjacent RR intervals in the RR interval sequence is calculated, and the root mean square value is used as the rhythm variation index of the RR interval sequence.

[0061] Specifically, the preset variation threshold is determined by training and validating an electrocardiogram database containing a large number of known atrial fibrillation cases and non-atrial fibrillation cases, aiming to maximize the accuracy and specificity of atrial fibrillation detection; if the calculated rhythm variation index is greater than the preset variation threshold, atrial fibrillation characteristics are determined to exist.

[0062] In one embodiment, if there are no atrial fibrillation features, the system detects whether there is an interval shorter than a preset premature beat interval threshold in the RR interval sequence. If such an interval exists, the system determines that premature beat features are present.

[0063] Specifically, because atrial fibrillation causes all RR intervals to become of varying lengths and irregular, this overall disorder can mask the characteristics of individual premature heartbeats, easily leading to misdiagnosis or missed diagnosis. Therefore, the system only initiates a specific detection for premature beats after confirming that the overall rhythm is not atrial fibrillation, that is, the heart rhythm is basically regular or shows other regularities. This ensures the specificity of the detection and avoids misdiagnosing the irregularity of atrial fibrillation as frequent premature beats.

[0064] Specifically, by scanning the entire RR interval sequence, each RR interval is compared with a preset premature beat interval threshold. The preset premature beat interval threshold is usually calculated based on the average normal cardiac cycle of the user or a population, such as the average of several nearby RR intervals, and set as a proportion, for example, shorter than 80% of the average RR interval. If an RR interval is significantly shorter than the intervals before and after it, and is lower than this preset premature beat interval threshold, it indicates that the heartbeat is likely caused by premature impulses from ectopic pacemakers such as the ventricle or atrium, which is consistent with the electrophysiological characteristics of premature beats. When such short intervals are detected, the presence of premature beat characteristics can be determined.

[0065] In one embodiment, if the average heart rate value in the heart rate parameters is greater than a first preset heart rate threshold and the average heart rate value is not greater than a second preset heart rate threshold, then it is determined that there is a tachycardia feature.

[0066] Specifically, the average heart rate value is a comprehensive statistical result of all heartbeat cycles during the entire acquisition period, reflecting the overall workload and pacing frequency of the heart during the measurement. The first preset heart rate threshold is a crucial dividing point, typically set at 100 bpm. This value is not arbitrarily set but is rooted in clinical medical diagnostic standards: in a resting state, an adult's heart rate consistently exceeding 100 bpm is defined as tachycardia. When the average heart rate value calculated by the system is greater than the first preset heart rate threshold, it indicates that the heart's pumping frequency has exceeded the normal resting range and entered an abnormally accelerated state.

[0067] Specifically, the second preset heart rate threshold is a key dividing point that is higher than the first preset heart rate, usually set to 150 bpm. When the system has determined that the average heart rate exceeds the first preset heart rate threshold, i.e., there is a tachycardia feature, it will further compare the average heart rate with the second preset heart rate threshold. If the average heart rate value is not greater than the second preset heart rate threshold, it means that the abnormal acceleration of the heart has not yet reached a more serious level. Therefore, the system automatically determines that there is a tachycardia feature.

[0068] In one embodiment, if the average heart rate value is greater than the second preset heart rate threshold, then it is determined that there are characteristics of severe tachycardia; wherein, the second preset heart rate threshold is greater than the first preset heart rate threshold.

[0069] Specifically, if the average heart rate value is greater than the second preset heart rate threshold, it means that the abnormal acceleration of the heart has reached a more serious level; therefore, it is automatically determined that there are serious tachycardia characteristics.

[0070] In one embodiment, if the average heart rate value is less than a third preset heart rate threshold and the average heart rate value is not less than a preset severe bradycardia threshold, then bradycardia is determined to exist.

[0071] Specifically, the third preset heart rate threshold is usually set to 60 beats per minute (bpm). This value is the lower limit of the normal heart rate range for adults at rest, which is widely used in clinical medicine. After calculating the average heart rate during the measurement period, the system directly compares the average heart rate with the third preset heart rate threshold. If the average heart rate is less than 60 bpm, it indicates that the overall heart rate is lower than the normal level at rest. The system then determines whether the average heart rate is less than the preset severe bradycardia threshold. If not, the system automatically determines that bradycardia is present. This determination is based on the average heart rate over a sustained period of time, rather than instantaneous fluctuations, thus avoiding misjudgments caused by transient sinus arrhythmia or respiratory sinus arrhythmia.

[0072] Specifically, the preset severe lag threshold is usually set to a very low 40 times per minute (bpm).

[0073] In one embodiment, if the instantaneous heart rate values ​​corresponding to multiple consecutive heartbeat locations are all lower than the severe bradycardia threshold, then it is determined that there is a severe bradycardia feature.

[0074] Specifically, by acquiring the instantaneous heart rate sequence, it is determined whether there are multiple consecutive heartbeat locations where the instantaneous heart rate value is lower than a preset severe bradycardia threshold. If so, it indicates that the heart has been in an extremely slow beating state and is automatically determined to have severe bradycardia.

[0075] Preferably, the consecutive plurality is four consecutive.

[0076] In one embodiment, if the maximum interval value in the RR interval sequence is greater than a preset long interval threshold, then a long interval feature is determined to exist.

[0077] Specifically, after calculating the complete RR interval sequence, the maximum interval value, i.e., the longest heartbeat interval, is found. The preset long interval threshold is usually set to 2.0 seconds. This value has clear clinical significance: in normal heart rhythms or most common arrhythmias, the RR interval usually does not reach such a long duration. If the maximum interval value exceeds 2.0 seconds, it means that the silence period between two effective heartbeats is too long, which may lead to insufficient blood perfusion to vital organs such as the brain, causing blurred vision, dizziness, or even syncope, which is a clear danger signal. Therefore, when the system detects that the maximum interval value of the RR interval sequence is greater than the long interval threshold, it directly determines that a long interval feature exists, regardless of the overall average heart rate value at this time.

[0078] In one embodiment, if, based on the RR interval sequence and the heart rate parameters, it is determined that there is no atrial fibrillation feature, premature beat feature, tachycardia feature, severe tachycardia feature, bradycardia feature, severe bradycardia feature, or long pause feature, then the arrhythmia feature is set to "no arrhythmia observed".

[0079] Step 102: Based on the preset multi-level grading standard, determine the risk level of the arrhythmia characteristics and identify the target risk level.

[0080] In one embodiment, the preset multi-level classification standard includes at least a first hazard level, a second hazard level, and a third hazard level.

[0081] Specifically, the first danger level is a critical value level, which is triggered for serious electrocardiographic abnormalities that may endanger life or require immediate medical intervention, including any of the following: atrial fibrillation with a heart rate >110 bpm (rapid atrial fibrillation, which can easily lead to heart failure and thrombosis); frequent premature beats (frequent premature heartbeats, which may induce more serious arrhythmias); severe tachycardia (average heart rate >150 bpm, which may lead to myocardial ischemia); severe bradycardia (instantaneous heart rate value <40 bpm corresponding to 4 consecutive heartbeats, which may cause syncope and sudden death); long intervals (maximum RR interval >2.0 seconds, indicating the risk of cardiac conduction block).

[0082] Specifically, the first danger level is a high-risk level. Such abnormalities pose an immediate health threat and require the highest level of warning to force users to seek medical attention in order to avoid delaying treatment.

[0083] Specifically, the second risk level is the abnormal value level, wherein the triggering conditions for the abnormal value level are for electrocardiogram conditions with health abnormalities but which do not require emergency intervention at present, including any one of the following: atrial fibrillation with a heart rate <110 bpm (slow atrial fibrillation, low short-term risk); tachycardia (average heart rate >100 bpm and ≤150 bpm, mostly related to exercise and emotions); bradycardia (average heart rate <60 bpm and no instantaneous heart rate value <40 bpm corresponding to 4 consecutive heartbeats).

[0084] Specifically, the second danger level is a medium-risk level. Such abnormalities require a combination of the user's physical symptoms to determine whether to seek medical attention, in order to avoid over-treatment. At the same time, users are reminded to pay attention to subsequent changes.

[0085] Specifically, the third danger level is a normal value level, wherein the triggering condition for the normal value level is that no ECG abnormalities corresponding to the first danger level and the second danger level are detected, and the RR interval sequence is stable and the heart rate is within the normal range.

[0086] Specifically, the third danger level is a low-risk level, confirming that the user's current electrocardiogram status is normal, and strengthening daily monitoring habits through regular measurement reminders to prevent potential risks.

[0087] Specifically, by using a pre-defined multi-level grading standard, all grading conditions are based on specific numerical values ​​rather than vague descriptions, ensuring that the system can automatically determine the grading through algorithms and avoid errors from human interpretation.

[0088] In one embodiment, a corresponding color label is set for each level of hazard, such as a first color label for the first hazard level, a second color label for the second hazard level, and a third color label for the third hazard level. This reduces the user's understanding cost, allowing them to quickly identify the risk level without professional knowledge, which is suitable for the scenario of non-professional users in portable monitoring devices.

[0089] Preferably, the first color label includes, but is not limited to, red; the second color label includes, but is not limited to, yellow; and the third color label includes, but is not limited to, green. Furthermore, the first color label, the second color label, and the third color label are different colors from each other to clearly distinguish different hazard levels.

[0090] In one embodiment, if the arrhythmia features include the atrial fibrillation feature, and there is at least one of the following features: heart rate parameter greater than a preset heart rate threshold parameter, premature beat feature, severe bradycardia feature, severe tachycardia feature, or long pause feature, it is determined to be at the first danger level.

[0091] Specifically, the preset heart rate threshold parameter is 110 bpm; if the heart rate parameter is greater than 110 bpm, it indicates that there is a heart rate parameter greater than the preset heart rate threshold parameter.

[0092] In one embodiment, if the atrial fibrillation feature is present in the arrhythmia features, and at least one of the following features is present (heart rate parameter not greater than a preset heart rate threshold parameter, bradycardia feature, or tachycardia feature), it is determined to be at the second danger level.

[0093] In one embodiment, if the arrhythmia characteristics do not meet the determination requirements corresponding to the first or second risk level, they are determined to be at the third risk level.

[0094] Step 103: Generate a visualization report based on the target hazard level, wherein the visualization report contains target guidance information associated with the target hazard level.

[0095] In one embodiment, the target guidance information associated with the target hazard level specifically includes: when the target hazard level is the first hazard level, the target guidance information is a first type of guidance information; when the target hazard level is the second hazard level, the target guidance information is a second type of guidance information that differs from the content of the first type of guidance information; and when the target hazard level is the third hazard level, the target guidance information is a third type of guidance information that recommends regular monitoring.

[0096] Specifically, for the first type of guidance information: since the core characteristic of the first level of danger is the existence of an immediate health threat, the core of the first type of guidance information is to recommend immediate medical attention. This first type of information includes: a first urgency alert, a first medical advice, and a first precaution. The first urgency alert is emphasized through prominent text (e.g., "Your current ECG results show critical values; you need to seek medical attention immediately"), sound, or pop-up warnings to prevent users from ignoring the risk. The first medical advice is basic guidance, such as suggesting prioritizing the cardiology emergency department to help users efficiently access medical resources. The first precaution reminds users to avoid strenuous activity and maintain emotional stability before seeking medical attention to reduce risks during the journey. The essence of the first type of guidance information is risk emergency guidance, aiming to enable users to receive professional medical intervention in the shortest possible time to avoid life-threatening situations.

[0097] Specifically, for the second type of guidance information: since the core characteristic of the second risk level is the presence of abnormalities but no immediate threat, the core of the second type of guidance information is to choose whether to seek medical attention based on one's own symptoms; the second type of indicator information includes: symptom inquiry and judgment, retest reminder, and lifestyle suggestions; among which, the symptom inquiry and judgment prompts users to make decisions based on their current physical feelings (e.g., "Do you have symptoms such as dizziness, chest tightness, or fatigue? If so, it is recommended to seek medical attention promptly; if not, you can observe for 1-2 days and then retest"); the retest reminder suggests that users measure again in different scenarios (e.g., at rest, after activity) to rule out "abnormalities caused by accidental factors" (e.g., transient tachycardia after exercise); the lifestyle suggestions provide adjustment suggestions for possible triggers (e.g., "If tachycardia occurs frequently, it is recommended to reduce the intake of coffee and strong tea, and avoid staying up late"); the essence of the second type of guidance information is risk observation and decision-making assistance, which avoids increasing the burden on users due to excessive medical treatment and also prevents delays in intervention for potential problems due to ignoring abnormalities.

[0098] Specifically, regarding the third type of guidance information: since the core characteristic of the third risk level is a normal ECG result with no abnormal risk, the core of the third type of guidance information is to recommend regular monitoring to maintain a healthy state. This third type of indicator information includes: monitoring frequency recommendations, health maintenance tips, and abnormal warning guidance. The monitoring frequency recommendations provide a regular monitoring cycle based on the user's situation (e.g., "healthy adults are advised to measure once a month," "those with a family history of heart disease are advised to measure once a week"). Health maintenance tips include basic cardiac health advice (e.g., "maintaining regular exercise and a low-salt diet helps maintain a normal heart rhythm"). Abnormal warning guidance reminds users that "if discomfort such as chest pain or palpitations occurs, even if regular monitoring is normal, timely examination is necessary" to avoid overlooking "occasional abnormalities." The essence of the third type of guidance information is risk observation and decision support, avoiding both increased user burden due to excessive medical visits and delays in intervention for potential problems due to ignoring abnormalities.

[0099] In one embodiment, by setting associated target guidance information for the target risk level, ordinary users can understand the direction of action and solve the problem of detection confusion simply by following the guidance information without having to understand professional terms such as atrial fibrillation and RR interval. Furthermore, based on the binding of guidance information and risk level, the graded early warning is no longer just a simple result display, but a complete health solution, truly realizing a closed loop from detection to intervention.

[0100] In one embodiment, a heart rate time series graph is generated based on the RR interval sequence, and associated target guidance information is obtained based on the target risk level; a visualization report is generated based on the heart rate time series graph, the target risk level, and the target guidance information; wherein the presentation format of the visualization report is configured differently according to different target risk levels, and the differentiated configuration includes at least visual differences.

[0101] Specifically, when generating a heart rate time series graph based on the RR interval sequence, the instantaneous heart rate sequence corresponding to the RR interval sequence is obtained. Multiple data points corresponding to the instantaneous heart rate sequence are generated with time as the horizontal axis and instantaneous heart rate value as the vertical axis. A vertical line graph is then formed based on these multiple data points, and this vertical line graph serves as the heart rate time series graph. Figure 3 As shown, Figure 3 This is a heart rate time-series graph, which is an embodiment of the intelligent classification and early warning method for electrocardiographic critical values ​​provided in this application.

[0102] Specifically, the heart rate time series graph can intuitively reflect the stability of the rhythm. If it is sinus rhythm (normal rhythm), the heart rate time series graph will show small and gentle fluctuations, with the heart rate value concentrated in the range of 60-100 bpm. If it is atrial fibrillation (abnormal rhythm), the heart rate time series graph will show irregular and large fluctuations due to the drastic variation of the RR interval. This allows ordinary users to perceive whether the heart rhythm is normal simply by observing the fluctuations in the graph, without needing to understand professional terminology.

[0103] Specifically, by pre-setting a hazard level-guidance information mapping rule base, the system can automatically and accurately match and call the corresponding target guidance information based on the input hazard level.

[0104] Specifically, the system uses the generated heart rate time series graph, the determined target risk level, and the obtained target guidance information as core materials, and automatically assembles them according to a preset report template to generate a comprehensive visual report; such as Figure 4 As shown, Figure 4 This is a schematic diagram of a report template of an embodiment of the intelligent classification and early warning method for critical electrocardiogram values ​​provided in this application.

[0105] Preferred, such as Figure 4 As shown, the visualization report also displays the average heart rate value and the identified arrhythmia features.

[0106] Preferred, such as Figure 4 As shown, the system also obtains user information, data acquisition time and duration for collecting electrocardiogram (ECG) signals from the user, and combines the ECG signals presented in ECG format, the user information, the data acquisition time and duration, with the aforementioned heart rate time series graph, the determined target risk level, and the obtained target guidance information to generate a visualization report, thereby enriching the information presentation dimensions of the visualization report.

[0107] Specifically, the differentiated configuration of the presentation format of the visualization report is used to distinguish the different hazard levels corresponding to the visualization report.

[0108] Specifically, the differentiated configuration includes at least visual differences, which are related to the color labels corresponding to different hazard levels. Based on the color labels corresponding to different hazard levels, the visualization report is set with a corresponding color tone. For example, for the visualization report corresponding to the first hazard level, a red border, a red warning icon, and a highlighted red title are used to create a sense of urgency; for the visualization report corresponding to the second hazard level, yellow visual elements are used to remind attention and caution; and for the visualization report corresponding to the third hazard level, a green tone is used to convey a signal of safety and encouragement.

[0109] Example 2, see Figure 2 , Figure 2 This is a schematic diagram of an embodiment of the intelligent grading and early warning device for critical electrocardiogram (ECG) values ​​provided in this application. Corresponding to the above-described intelligent grading and early warning method for critical ECG values, this application also provides an intelligent grading and early warning device for critical ECG values. This intelligent grading and early warning device for critical ECG values ​​includes modules for executing the above-described intelligent grading and early warning method for critical ECG values. This intelligent grading and early warning device for critical ECG values ​​can be configured in a desktop computer, tablet computer, laptop computer, or other terminal. Specifically, this intelligent grading and early warning device for critical ECG values ​​includes an ECG signal analysis module 201, a danger level determination module 202, and a visualization report generation module 203.

[0110] The electrocardiogram signal analysis module 201 is used to analyze and process the acquired electrocardiogram signals of the user to determine the characteristics of arrhythmia.

[0111] The risk level determination module 202 is used to determine the risk level of the arrhythmia characteristics based on a preset multi-level grading standard, and to determine the target risk level.

[0112] The visualization report generation module 203 is used to generate a visualization report based on the target hazard level, wherein the visualization report contains target guidance information associated with the target hazard level.

[0113] In one embodiment, the electrocardiogram (ECG) signal analysis module 201 is used to analyze and process the acquired ECG signal of the user to determine arrhythmia characteristics. Specifically, it includes: preprocessing the ECG signal to obtain a preprocessed ECG signal; identifying the preprocessed ECG signal to obtain the heartbeat location; calculating the RR interval sequence and heart rate parameters based on the heartbeat location; and determining whether arrhythmia characteristics exist based on the RR interval sequence and the heart rate parameters. The arrhythmia characteristics include at least one of atrial fibrillation characteristics, premature beat characteristics, tachycardia characteristics, severe tachycardia characteristics, bradycardia characteristics, severe bradycardia characteristics, and long pause characteristics.

[0114] In one embodiment, the electrocardiogram signal analysis module 201 is used to calculate the RR interval sequence and heart rate parameters based on the heartbeat location, specifically including: obtaining the time interval between adjacent heartbeat locations to obtain the RR interval sequence; calculating the average RR interval based on the RR interval sequence, and calculating the heart rate parameters based on the average RR interval.

[0115] In one embodiment, the electrocardiogram signal analysis module 201 is used to determine whether there are arrhythmia features based on the RR interval sequence and the heart rate parameters. Specifically, this includes: calculating the rhythm variability index of the RR interval sequence; if the rhythm variability index is greater than a preset variability threshold, then atrial fibrillation features are determined to exist; if atrial fibrillation features are not present, then detecting whether there are intervals in the RR interval sequence shorter than a preset premature beat interval threshold; if so, premature beat features are determined to exist; if the average heart rate value in the heart rate parameters is greater than a first preset heart rate threshold and the average heart rate value is not greater than a second preset heart rate threshold, then... The following criteria are used to determine the presence of tachycardia: If the average heart rate value is greater than the second preset heart rate threshold, then a severe tachycardia is determined to exist; wherein the second preset heart rate threshold is greater than the first preset heart rate threshold; If the average heart rate value is less than the third preset heart rate threshold and the average heart rate value is not less than a preset severe bradycardia threshold, then a bradycardia is determined to exist; If the instantaneous heart rate values ​​corresponding to multiple consecutive heartbeat locations are all lower than the severe bradycardia threshold, then a severe bradycardia is determined to exist; If the maximum interval value in the RR interval sequence is greater than a preset long pause threshold, then a long pause is determined to exist.

[0116] In one embodiment, the risk level determination module 202 is used to determine the risk level of the arrhythmia feature based on a preset multi-level grading standard, and to determine a target risk level. Specifically, the preset multi-level grading standard includes at least a first risk level, a second risk level, and a third risk level. Specifically, if the arrhythmia feature includes atrial fibrillation and at least one of the following features: a heart rate parameter greater than a preset heart rate threshold parameter, premature beats, severe bradycardia, severe tachycardia, or long pauses, it is determined to be at the first risk level. If the arrhythmia feature includes atrial fibrillation and at least one of the following features: a heart rate parameter not greater than a preset heart rate threshold parameter, bradycardia, or tachycardia, it is determined to be at the second risk level. If the arrhythmia feature does not meet the determination requirements corresponding to the first or second risk level, it is determined to be at the third risk level.

[0117] In one embodiment, the target guidance information associated with the target hazard level in the visualization report generation module 203 specifically includes: when the target hazard level is the first hazard level, the target guidance information is a first type of guidance information; when the target hazard level is the second hazard level, the target guidance information is a second type of guidance information that differs from the content of the first type of guidance information; and when the target hazard level is the third hazard level, the target guidance information is a third type of guidance information that recommends regular monitoring.

[0118] In one embodiment, the visualization report generation module 203 is used to generate a visualization report based on the target risk level, specifically including: generating a heart rate time series graph based on the RR interval sequence, and obtaining associated target guidance information based on the target risk level; generating a visualization report based on the heart rate time series graph, the target risk level, and the target guidance information; wherein the presentation format of the visualization report is configured differently according to different target risk levels, and the differentiated configuration includes at least visual differences.

[0119] The aforementioned intelligent grading and early warning device for critical ECG values ​​can implement the intelligent grading and early warning method for critical ECG values ​​described in the above method embodiments. The options described in the above method embodiments are also applicable to this embodiment and will not be detailed here.

[0120] like Figure 5 As shown, Figure 5 This is a schematic diagram of the structure of a computer device provided in this application; it includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 communicate with each other through the communication bus 114, and the memory 113 is used to store computer programs.

[0121] In one embodiment of this application, the processor 111, when executing the program stored in the memory 113, implements the intelligent grading and early warning method for ECG critical values ​​provided in any of the foregoing method embodiments.

[0122] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0123] Therefore, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, wherein when the computer program is executed by a processor, it implements the steps of the intelligent grading and early warning method for ECG critical values ​​as provided in any of the foregoing method embodiments.

[0124] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk, or any other physical storage medium capable of storing program code. The computer-readable storage medium can be non-volatile or volatile.

[0125] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0126] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0127] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0128] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0129] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0130] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Since these modifications and variations fall within the scope of the claims and their equivalents, this application also intends to include these modifications and variations.

[0131] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for intelligent hierarchical early warning of critical electrocardiographic values, characterized in that, include: The acquired electrocardiogram (ECG) signals of users are analyzed and processed to determine the characteristics of arrhythmias; Based on a preset multi-level grading standard, the risk level of the arrhythmia characteristics is determined, and the target risk level is identified. A visualization report is generated based on the target hazard level, wherein the visualization report contains target guidance information associated with the target hazard level.

2. The method as described in claim 1 above, characterized in that, The process of analyzing and processing the acquired electrocardiogram (ECG) signals of the user to determine the characteristics of arrhythmia specifically includes: The electrocardiogram (ECG) signal is preprocessed to obtain a preprocessed ECG signal; The preprocessed electrocardiogram signal is then identified and processed to obtain the heartbeat location; Based on the heartbeat location, calculate the RR interval sequence and heart rate parameters; Based on the RR interval sequence and the heart rate parameters, it is determined whether there are arrhythmia features, wherein the arrhythmia features include at least one of atrial fibrillation features, premature beat features, tachycardia features, severe tachycardia features, bradycardia features, severe bradycardia features, and long pause features.

3. The method as described in claim 2 above, characterized in that, The calculation of the RR interval sequence and heart rate parameters based on the heartbeat location specifically includes: The time intervals between adjacent heartbeat locations are obtained to obtain the RR interval sequence; The mean RR interval is calculated based on the RR interval sequence, and the heart rate parameters are calculated based on the mean RR interval.

4. The method as described in claim 3 above, characterized in that, The determination of whether arrhythmia characteristics exist based on the RR interval sequence and the heart rate parameters specifically includes: Calculate the rhythm variability index of the RR interval sequence. If the rhythm variability index is greater than a preset variability threshold, then atrial fibrillation characteristics are determined to exist. If no atrial fibrillation features are present, then the presence of an interval shorter than a preset premature beat interval threshold in the RR interval sequence is detected. If such an interval exists, the presence of premature beat features is determined. If the average heart rate value in the heart rate parameters is greater than the first preset heart rate threshold, and the average heart rate value is not greater than the second preset heart rate threshold, then it is determined that there is a tachycardia feature. If the average heart rate value is greater than the second preset heart rate threshold, then a severe tachycardia is determined to exist; wherein, the second preset heart rate threshold is greater than the first preset heart rate threshold; If the average heart rate value is less than a third preset heart rate threshold, and the average heart rate value is not less than a preset severe bradycardia threshold, then bradycardia is determined to exist. If the instantaneous heart rate values ​​corresponding to multiple consecutive heartbeat locations are all lower than the severe bradycardia threshold, then it is determined that there are severe bradycardia characteristics. If the maximum interval value in the RR interval sequence is greater than the preset long interval threshold, then the presence of a long interval feature is determined.

5. The method as described in claim 4 above, characterized in that, The method of determining the risk level of the arrhythmia characteristics based on a preset multi-level grading standard and identifying the target risk level specifically includes: The preset multi-level classification standard includes at least a first hazard level, a second hazard level, and a third hazard level; If the arrhythmia features include the atrial fibrillation feature, and there is at least one of the following features: heart rate parameter greater than a preset heart rate threshold parameter, premature beat feature, severe bradycardia feature, severe tachycardia feature, or long pause feature, it is determined to be the first danger level. If the atrial fibrillation feature is present among the arrhythmia features, and at least one of the following features exists (heart rate parameter not greater than a preset heart rate threshold parameter, bradycardia feature, or tachycardia feature), it is determined to be at the second risk level. If the arrhythmia characteristics do not meet the determination requirements corresponding to the first or second risk level, they are determined to be at the third risk level.

6. The method as described in claim 5 above, characterized in that, The target guidance information associated with the target hazard level specifically includes: When the target hazard level is the first hazard level, the target guidance information is the first type of guidance information; When the target hazard level is the second hazard level, the target guidance information is a second type of guidance information that differs from the content of the first type of guidance information; When the target hazard level is the third hazard level, the target guidance information is the third type of guidance information that recommends regular monitoring.

7. The method as described in claim 2 above, characterized in that, The step of generating a visualization report based on the target hazard level specifically includes: Obtain the instantaneous heart rate sequence corresponding to the RR interval sequence, use time as the horizontal axis and instantaneous heart rate value as the vertical axis to generate multiple data points corresponding to the instantaneous heart rate sequence, form a vertical line graph based on the multiple data points, and use the vertical line graph as a heart rate time series graph; And based on the target hazard level, obtain associated target guidance information; A visual report is generated based on the heart rate time series graph, the target risk level, and the target guidance information; The presentation format of the visualization report is configured differently according to different target hazard levels, and the differentiating configuration includes at least visual differences.

8. An intelligent grading and early warning device for critical electrocardiogram values, characterized in that, include: ECG signal analysis module, risk level determination module, and visual report generation module; The electrocardiogram (ECG) signal analysis module is used to analyze and process the acquired ECG signals of the user to determine the characteristics of arrhythmia. The risk level determination module is used to determine the risk level of the arrhythmia characteristics based on a preset multi-level grading standard, and to determine the target risk level. The visualization report generation module is used to generate a visualization report based on the target hazard level, wherein the visualization report contains target guidance information associated with the target hazard level.

9. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, can implement the method as described in any one of claims 1-7.

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