Method, device and equipment for assisting in identifying reduction of left ventricular systolic function after STEMI by synchronizing heart sound and electrocardio

Abstract

The invention provides a method, a device, equipment, a readable storage medium and a program product for synchronous heart sound and electrocardio-assisted recognition of left ventricular systolic function reduction after STEMI, and belongs to the technical field of heart information collection and recognition. A method for identifying reduction of the left ventricular systolic function after STEMI assisted by synchronizing heart sound and electrocardio comprises the steps that heart sound signals and electrocardio signals of a human body are synchronously collected, and corresponding electrocardio data and heart sound data are obtained respectively; acquiring an electromechanical activation time parameter from a Q wave in the electrocardiogram data to a peak value of a first heart sound in the heart sound data; acquiring an RR period parameter of a time limit between two adjacent R waves corresponding to the electro-mechanical activation time in the electrocardio data; and calculating the ratio of the electromechanical activation time to the RR period, taking the ratio as an electromechanical activation time parameter standardized according to the heart rate, judging whether the ratio is greater than a preset threshold value or not, and if so, judging that the systolic function of the left ventricle of the collected person is reduced. The left ventricular systolic function can be detected in an auxiliary mode by synchronously collecting the heart sound and electrocardiosignals, the method is simple, and the cost is low.

Description

Technical Field

[0001] The present disclosure relates to the technical field of cardiac information acquisition and recognition, and in particular, to a method, device, equipment, readable storage medium, and program product for synchronously assisting in the recognition of reduced left ventricular systolic function after STEMI by heart sound and electrocardiogram. Background Art

[0002] Heart failure (HF) is the end stage of various cardiovascular diseases. Currently, the mortality and readmission rates of heart failure patients remain a global public health problem. Although great progress has been made in the treatment of heart failure and the mortality rate has been decreasing year by year, China has entered an aging population, and the incidence of chronic diseases such as coronary heart disease, hypertension, diabetes, and obesity is on the rise, resulting in a continuous increase in the prevalence of heart failure. Therefore, early diagnosis and early treatment are the keys to the treatment of heart failure patients.

[0003] Acute myocardial infarction (AMI) is myocardial necrosis caused by acute and persistent ischemia and hypoxia of the coronary artery. It is a severe type of coronary heart disease and is mainly divided into two types: ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI). ST-segment elevation myocardial infarction is usually accompanied by a further deterioration of cardiac function, and heart failure associated with acute myocardial infarction has a very high mortality rate. Approximately 13% of acute myocardial infarction patients develop heart failure within 30 days, and the proportion of those developing heart failure within 1 year is approximately 20 - 30%. In addition, the incidence of heart failure after acute myocardial infarction is the highest in the first month and then gradually decreases until it reaches a stable level of 1.3 - 2.2% per year. Therefore, in the population of acute myocardial infarction patients, the screening and prevention of heart failure are crucial, and the optimal management of acute ST-segment elevation myocardial infarction requires accurate and reliable heart failure diagnosis.

[0004] In the prior art, diagnosing heart failure through blood tests (such as B-type natriuretic peptide BNP) has a "gray area" and is often affected by age, gender, and renal function, which limits its diagnostic ability. Echocardiography is an effective means of detecting and evaluating cardiac structure and function, but it may not be available in outpatient clinics and is costly. Moreover, factors such as the limited body position and poor acoustic window of heart failure patients have a greater impact on the accuracy of the results. Summary of the Invention

[0005] The present disclosure provides a method, an apparatus, a device, a readable storage medium, and a program product for synchronously assisting in identifying a reduction in left ventricular systolic function after STEMI, so as to solve the technical problems of limited usage environment and high cost of devices for detecting left ventricular systolic function in the prior art.

[0006] To solve the above technical problems, the present disclosure provides a method for synchronously assisting in identifying a reduction in left ventricular systolic function after STEMI, which is used to assist in diagnosing cardiac dysfunction in patients after ST-segment elevation myocardial infarction, and includes: Synchronously collect the heart sound signal and the electrocardiogram signal of a human body, and respectively obtain the corresponding electrocardiogram data and heart sound data; Obtain the electromechanical activation time parameter during the period from the Q wave in the electrocardiogram data to the peak of the first heart sound in the heart sound data; Obtain the RR interval parameter of the time limit between two adjacent R waves in the electrocardiogram data corresponding to the electromechanical activation time; Calculate the ratio of the electromechanical activation time to the RR interval as the electromechanical activation time parameter standardized by heart rate, and determine whether the electromechanical activation time standardized by heart rate is greater than a preset threshold. If so, it is determined that the left ventricular systolic function of the person being collected is reduced; if not, it is determined that the left ventricular systolic function of the person being collected is normal.

[0007] To solve the above technical problems, the present disclosure also provides a device for synchronously assisting in identifying a reduction in left ventricular systolic function after STEMI, which is characterized in that it is used to assist in diagnosing cardiac dysfunction in patients after ST-segment elevation myocardial infarction, and is used to implement the method described in any one of claims 1-6, and includes: A collection unit, including a sound sensor for synchronously collecting heart sound signals and electrodes for electrocardiogram signals, and respectively obtaining the corresponding heart sound data and electrocardiogram data; A processor unit, which is used to obtain the electromechanical activation time parameter during the period from the Q wave in the electrocardiogram data to the peak of the first heart sound in the heart sound data; obtain the RR interval parameter of the time limit between two adjacent R waves in the electrocardiogram data corresponding to the electromechanical activation time; calculate the ratio of the electromechanical activation time to the RR interval as the electromechanical activation time parameter standardized by heart rate, and determine whether the electromechanical activation time standardized by heart rate is greater than a preset threshold. If so, it is determined that the left ventricular systolic function of the person being collected is reduced; if not, it is determined that the left ventricular systolic function of the person being collected is normal.

[0008] To solve the above technical problems, the present disclosure also provides a computer device, including a memory, a processor, and a computer program stored on the memory, and is characterized in that the processor executes the computer program to implement the steps of the method described above.

[0009] To solve the above technical problems, the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and characterized in that when the computer program is executed by a processor, the steps of the above-described method are implemented.

[0010] To solve the above technical problems, the present disclosure also provides a computer program product, including a computer program, and characterized in that when the computer program is executed by a processor, the steps of the above-described method are implemented.

[0011] According to the technical solution of the present disclosure, compared with the prior art, the present disclosure can assist in detecting the left ventricular systolic function of cardiac dysfunction in patients after acute ST-segment elevation myocardial infarction by synchronously collecting heart sound signals, electrocardiogram signals and analyzing and calculating relevant systolic acoustic cardiogram parameters. The method is simple, has a low degree of application environment limitation, and has a low cost, greatly improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a flowchart of a method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI according to an embodiment of the present disclosure.

[0013] Figure 2 It is a schematic diagram of a device for synchronously assisting in identifying reduced left ventricular systolic function after STEMI according to an embodiment of the present disclosure.

[0014] Figure 3 It is a structural diagram of a system for synchronously assisting in identifying reduced left ventricular systolic function after STEMI according to an embodiment of the present disclosure.

[0015] Figure 4 It is a structural diagram of a terminal device according to an embodiment of the present disclosure.

[0016] Combined with the accompanying drawings and referring to the following specific embodiments, the above and other features and advantages of the various embodiments of the present disclosure will become more obvious. In the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic and the elements are not necessarily drawn to scale. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this disclosure belongs. Herein, the terms used in the specification of the application are only for describing specific embodiments and are not intended to limit the present disclosure. The term "including" and any corresponding variations in the specification and claims of the present disclosure are intended to cover non-exclusive inclusion.

[0018] References to "embodiments" in this specification mean that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of the present disclosure. The phrase appears in various places in the specification and is not necessarily referring to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will understand explicitly and implicitly that the embodiments described herein can be combined with other embodiments.

[0019] This disclosure is based on a study that synchronously analyzes phonocardiograms and electrocardiograms to evaluate the cardiac function, especially the left ventricular (LV) function and 30-day clinical outcomes of patients with acute ST-segment elevation myocardial infarction. To facilitate the description of this disclosure, the main concepts and parameters of this study are introduced below.

[0020] Echocardiography is mainly used to evaluate left ventricular systolic dysfunction (LVSD) in research and clinical practice. The ejection fraction (EF) refers to the proportion of blood pumped out by the heart during each contraction, usually expressed as a percentage, and it is an important indicator for evaluating cardiac function. The left ventricular ejection fraction (LVEF) refers to the proportion of the left ventricular stroke volume to the left ventricular end-diastolic volume. Generally, it is within the normal range between 50% and 70%. If it is lower than 50%, there is a high possibility of heart failure. The recognized threshold for reduced left ventricular systolic function (dLVEF) is a left ventricular ejection fraction below 50%. A decrease in left ventricular ejection fraction after myocardial infarction is associated with poor cardiovascular prognosis.

[0021] The parameters calculated by synchronously collecting phonocardiogram signals and electrocardiogram signals and analyzing them in this disclosure include, for example, systolic echocardiogram parameters. Among them, the systolic echocardiogram parameters include, for example: The electromechanical activation time (EMAT) reflects the time (electromechanical delay) required for the left ventricle to generate sufficient force to close the mitral valve, and is defined as the time from the start of left ventricular electrical activity (the onset of the Q wave on the electrocardiogram) to the peak of the first heart sound (S1, mitral valve closure), which reflects the left ventricular systolic function state. When the atrial and ventricular pressures are balanced, the mitral valve closes, indicating the start of left ventricular mechanical contraction. During the isovolumic contraction period, the pressure in the left ventricle rises. After exceeding the aortic pressure, the aortic valve opens, starting the isobaric contraction period of the left ventricle. If the EMAT is prolonged, it indicates impaired left ventricular systolic function and decreased systolic function. Conversely, it is related to shortened left ventricular systolic function and electromechanical delay.

[0022] The electromechanical activation time percentage (EMAT%), normalized by heart rate, refers to the proportion of EMAT in the cardiac cycle, reflecting the proportion of the time required for the left ventricle to contract and generate sufficient pressure to close the mitral valve in the cardiac cycle. EMAT% can be obtained by correcting EMAT with the heart rate (EMAT / RR interval), eliminating the influence of the basal heart rate on EMAT.

[0023] Pre-ejection Period (PEP): It involves the time required for the left ventricle to generate sufficient force to close the mitral valve and open the aortic valve. In this disclosure, PEP is defined as the time from the Q wave of the electrocardiogram (ECG) to the end of S1 (aortic valve opening), which can reflect changes in myocardial contractility, left ventricular end-diastolic volume, and aortic diastolic pressure. By correcting with the heart rate (PEP / RR interval), the pre-ejection period PEP% normalized by heart rate can be obtained.

[0024] Left Ventricular Systolic Time (LVST) represents the time period from mitral valve closure to aortic valve closure, that is, the time from the peak of the first heart sound S1 to the peak of the second heart sound S2 in the phonocardiogram (PCG). It is susceptible to the influence of heart rate and reflects the time from mitral valve closure, aortic valve opening into the systolic phase to aortic valve closure before entering the diastolic phase. After correcting with the heart rate (LVST / RR interval), the left ventricular systolic time LVST% normalized by heart rate is obtained.

[0025] Left Ventricular Ejection Time (LVET): It represents the time interval from aortic valve opening to closure, that is, the time interval of left ventricular ejection, between the end of S1 and the peak of S2. After normalization, it is related to the heart rate. The Left Ventricular Ejection Time Index (LVETI) means that gender-specific resting regression equations should be used for heart rate correction. By correcting with the heart rate (LVET / RR interval), the left ventricular ejection time LVET% normalized by heart rate can be obtained.

[0026] PEP / LVET: It is related to the ejection fraction. Due to left ventricular systolic dysfunction, there is an extension of PEP and a shortening of LVET. PEP / LVET is a more useful indicator of overall left ventricular performance. The correlation between PEP / LVET and the measurement of left ventricular performance is better than that of PEP or LVET, and it is considered independent of heart rate.

[0027] In addition, in statistics, the p-value is a tool used to determine whether a hypothesis test is significant. It reflects the degree of difference between the observed data and the expected data under the null hypothesis. When the p-value is less than the preset significance level, the null hypothesis can be rejected, indicating that there is a significant difference between the treatment group and the control group. A p-value less than 0.05 is a commonly accepted standard among researchers to determine whether the experimental results are statistically significant.

[0028] The principle on which this study is based is as follows.

[0029] Previous studies have demonstrated that the electromechanical activation time (EMAT) derived from PCG and ECG signals can identify heart failure patients with a left ventricular ejection fraction (LVEF) < 50%. An EMAT ≥ 104 ms is regarded as an abnormally prolonged systolic function, and an EMAT / RR (EMAT%) > 15% is considered abnormal in heart failure patients. In addition, the EMAT% of patients with acute decompensated heart failure changes over time during treatment and is considered a useful biomarker in heart failure management. Currently, few studies have utilized EMAT% as an indicator of cardiac function in patients with ST-segment elevation myocardial infarction. In this study, it was aimed to determine whether EMAT% from novel wearable technology can accurately identify cardiac dysfunction in patients after ST-segment elevation myocardial infarction and its predictive ability in predicting 30-day major adverse cardiovascular events (MACE).

[0030] The method adopted in this study is as follows.

[0031] A total of 264 STEMI patients were included. The left ventricular ejection fraction (LVEF) was determined by echocardiogram. On the first day of admission, the phonocardiogram signal PCG and the electrocardiogram signal ECG were simultaneously recorded using a wearable cardiac signal monitoring device. The PCG and ECG signals were analyzed to determine the electromechanical activation time (EMAT), EMAT / RR (EMAT%), pre-ejection period / RR (PEP%), left ventricular systolic time / RR (LVST%), left ventricular ejection time index (LVETI), etc., and statistical analysis was performed on the acoustic characteristic data. The primary endpoint was the major adverse cardiovascular event (MACE) occurring within 30 days after acute STEMI.

[0032] All patients completed 30-day follow-up. The study endpoint was major adverse cardiovascular events (MACE), including all-cause death, cardiac death, recurrent myocardial infarction, new-onset or exacerbated heart failure, cerebrovascular events, and malignant ventricular arrhythmias, which were diagnosed during telephone follow-up, outpatient visits, or readmissions. The diagnosis of new-onset or exacerbated heart failure was confirmed by two physicians based on all of the following criteria: a history of previous acute STEMI; new-onset or exacerbated heart failure during hospitalization or heart failure requiring readmission after discharge; clinical symptoms of heart failure during hospitalization including paroxysmal nocturnal dyspnea, orthopnea, and exertional dyspnea; physical examination symptoms including peripheral edema, rales, and jugular venous distension; NT-proBNP blood test exceeding the upper limit for the corresponding age group; LVEF < 50% defined by echocardiogram and the sole cause being acute STEMI; the use of intravenous diuretics, inotropic agents, or intra-aortic balloon counterpulsation during the treatment process. Malignant ventricular arrhythmias were defined as successful cardiopulmonary resuscitation or hemodynamic instability requiring assistance with a cardiac defibrillator.

[0033] The results obtained from this study are as follows.

[0034] Receiver operating characteristic (ROC) curve analysis showed that when EMAT% > 11.9% was used as the cut-off value for detecting LVEF < 50%, the sensitivity and specificity were 84% and 88%, respectively. In the group with EMAT% > 11.9%, PEP%, LVST%, LVET%, left ventricular end-diastolic volume (LVEDV), and left ventricular end-systolic volume (LVESV) were all significantly higher. Additionally, the incidence of MACE was significantly higher in the group with EMAT% > 11.9% (40.5% vs 6.7%, p < 0.001).

[0035] Therefore, synchronous measurement of PCG and ECG can be used as a candidate indicator for evaluating the contraction related to left ventricular systolic function in patients with acute STEMI, and EMAT% > 11.9% indicates deterioration of left ventricular systolic function.

[0036] To enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0037] The first aspect of the embodiments of the present disclosure is introduced below: a method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI by heart sound and electrocardiogram.

[0038] The method for synchronously assisting in identifying the reduction of left ventricular systolic function after STEMI according to the present disclosure is used to assist in diagnosing the cardiac dysfunction of patients after ST-segment elevation myocardial infarction. Here, first, a further explanation of this auxiliary diagnosis is made. The method of the present disclosure is the identification and analysis of abnormal heart sound signals and electrocardiogram signals caused by the reduction of left ventricular systolic function. In essence, it is still the identification and analysis of cardiac information, and the results of its identification and analysis are still a kind of cardiac information identification result. Only by means of the identification result of this method can the formation of the reduction of left ventricular systolic function be assisted in diagnosis. This method does not directly diagnose the disease of the reduction of left ventricular systolic function, but uses the identification and analysis results of cardiac information obtained by this method to assist in diagnosis.

[0039] Figure 1 This is a flowchart of the method for synchronously assisting in identifying the reduction of left ventricular systolic function after STEMI provided by an embodiment of the present disclosure. As Figure 1 shown, the method for synchronously assisting in identifying the reduction of left ventricular systolic function after STEMI, which is used to assist in diagnosing the cardiac dysfunction of patients after ST-segment elevation myocardial infarction, includes the following steps: S11, synchronously collect the heart sound signal and electrocardiogram signal of the human body, and respectively obtain the corresponding electrocardiogram data and heart sound data. Here, for example, the heart sound signal and electrocardiogram signal of the human body are synchronously collected through the subsequent acquisition unit, and the corresponding electrocardiogram data and heart sound data are respectively obtained. After each echocardiogram is completed, the patch of the acquisition unit is attached to the mitral auscultation area of the patient, and each recording of the electrocardiogram signal, that is, the ECG signal, and the heart sound signal, that is, the PCG signal, is, for example, 60 seconds. Here, the echocardiogram and the collection of synchronous PCG and ECG signals are performed by different doctors.

[0040] S12, according to the synchronously collected electrocardiogram data and heart sound data, obtain the electromechanical activation time parameter EMAT during the period from the Q wave in the electrocardiogram data to the peak of the first heart sound in the heart sound data. Considering that EMAT is affected by heart rate and its sensitivity is lower than EMAT%, the present disclosure uses EMAT% as a parameter to divide the patients into two groups and compare the acoustic cardiac map parameters between the two groups.

[0041] S13, according to the obtained electromechanical activation time EMAT, obtain the time limit between two adjacent R waves in the electrocardiogram data corresponding to the electromechanical activation time EMAT as the RR period parameter for heart rate correction, and use it for subsequent analysis and calculation of each parameter standardized by heart rate.

[0042] S14. Calculate the ratio of the electromechanical activation time EMAT to the RR interval as the electromechanical activation time parameter EMAT% normalized by heart rate, and determine whether the electromechanical activation time EMAT% normalized by heart rate is greater than a preset threshold. If so, it is determined that the left ventricular systolic function of the subject is reduced; if not, it is determined that the left ventricular systolic function of the subject is normal.

[0043] In one or more embodiments, the preset threshold is at least 11.9%. Table 1 below summarizes the area under the ROC curve (AUC), the critical value, and the corresponding specificity and sensitivity of each echocardiogram parameter. The AUC of EMAT is 0.84 (95% confidence interval 0.79–0.88; P < 0.001). In patients with acute ST-segment elevation myocardial infarction (STEMI), the critical point of EMAT is 92 milliseconds to evaluate the left ventricular ejection fraction (LVEF). The AUC of EMAT% is 0.91 (95% confidence interval 0.87–0.94; P < 0.001), and its critical value is 11.9% for evaluating the performance of dLVEF in STEMI patients. If EMAT% ≤ 11.9% is used as the critical value for judging EF ≥ 50%, the sensitivity is 84% and the specificity is 88%. A high correlation was observed between EMAT% (r = 0.66, P < 0.001) and EMAT (r = 0.54, P < 0.001) and LVEF.

[0044] Table 1 Performance of echocardiogram parameters

[0045] In one or more embodiments, the method of the present disclosure further includes: obtaining the pre-ejection period parameter PEP from the Q wave to the end of the first heart sound, and calculating the pre-ejection period PEP% normalized by heart rate to assist in determining whether the left ventricular systolic function of the subject has decreased.

[0046] In one or more embodiments, the method of the present disclosure further includes: obtaining the left ventricular ejection time parameter LEVT from the end of the first heart sound S1 to the peak of the second heart sound S2 in the heart sound data, and calculating the ratio PEP / LEVT of the pre-ejection period parameter PEP to the left ventricular ejection time parameter LEVT to assist in determining whether the left ventricular systolic function of the subject has decreased.

[0047] Here, for example, the Pearson correlation test is used to evaluate the correlation between each systolic echocardiogram parameter (such as EMAT, EMAT%, PEP%, etc.) and LVEF. In addition, to determine the optimal cut-off value of each systolic echocardiogram parameter (such as EMAT, EMAT%, PEP%, etc.) related to the LVEF category (LVEF < 50% vs. LVEF ≥ 50%), the receiver operating characteristic (ROC) curve analysis is adopted. For all analyses, a two-tailed P < 0.05 is considered statistically significant.

[0048] In one or more embodiments, the method of the present disclosure further includes: comparing the collected and analyzed parameters and data with echocardiogram data to further confirm the accuracy or relevance of the analyzed data and results.

[0049] As shown in Table 2 below, the systolic echocardiogram and echocardiogram data of the two groups are presented. Compared with the group with EMAT% ≤ 11.9%, the left ventricular ejection fraction LVEF of the group with EMAT% > 11.9% is lower (45.5% vs. 58%, p < 0.001), but EMAT (99 ms vs. 81 ms, p < 0.001), PEP% (16.5% vs. 12%, p < 0.001), LVST% (41.34 vs. 37.98, p < 0.001), PEP / LVET (0.44 vs. 0.34, p < 0.001), left ventricular end-diastolic volume (LVEDV, 138 ml vs. 114 ml, p < 0.001) and left ventricular end-systolic volume (LVESV, 67.5 ml vs. 45 ml, p < 0.001) are all higher.

[0050] Table 2 Systolic Echocardiogram and Echocardiogram Parameters

[0051] In summary, except for LVST% and LVETI, all systolic echocardiogram parameters were significantly correlated with LVEF. Among them, the highest correlation was found between EMAT% > 11.9% and ejection fraction EF < 50%, which could be used to assist in identifying reduced left ventricular systolic function. The critical value of EMAT% was 11.9%, and EMAT% > 11.9% represented abnormal prolongation of left ventricular systolic function. All systolic echocardiogram parameters in the EMAT% > 11.9% group were abnormally prolonged, which was consistent with the echocardiogram results. Compared with the EMAT% ≤ 11.9% group, patients in the EMAT% > 11.9% group had lower left ventricular ejection fraction LVEF, but higher EMAT, PEP%, LVST%, LVET%, LVEDV, and LVESV. This disclosure for the first time uses electrocardiogram (ECG) and phonocardiogram (PCG) to indicate reduced left ventricular systolic function and demonstrates this strong correlation in post-STEMI patients.

[0052] As mentioned above, the primary endpoint of the study in this disclosure was major adverse cardiovascular events (MACE) occurring within 30 days after acute STEMI. According to the statistical results, 46 patients (17.4%) had major adverse cardiovascular events (MACE), including 17 cases of all-cause death, 15 cases of cardiac death, 22 cases of acute congestive heart failure, and 7 cases of malignant ventricular arrhythmia. As shown in Table 3 below, the incidence of MACE in the EMAT% > 11.9% group was significantly higher (40.5% vs 6.7%, p < 0.001). The study in this disclosure was the first to show the relationship between systolic left ventricular parameters measured by echocardiogram and MACE at 30 days after STEMI. The incidence of MACE events with EMAT% > 11.9% was much higher than that of the control group.

[0053] Table 3 Incidence of MACE

[0054] According to research, a randomized single-blind trial using regular assessment of echocardiogram parameters found that EMAT% ≥ 15 significantly reduced heart failure readmission or all-cause mortality within 1 year for guiding outpatient management of acute heart failure. The change in EMAT before and after dialysis was related to the overall and cardiovascular mortality of dialysis patients during a 2.9-year follow-up.

[0055] Furthermore, in this embodiment, the present disclosure further includes: based on the existing phonocardiogram (PCG) and electrocardiogram (ECG) signals, integrating parameters such as blood oxygen saturation (SpO2), non-invasive blood pressure (NIBP), and respiratory rate to construct a multi-modal physiological signal fusion model. Align the time axes of each signal through a time synchronization algorithm, extract cross-modal features (such as the delay relationship between the Q wave of the electrocardiogram and the descending segment of the blood oxygen waveform), and establish a joint diagnostic index. By introducing the "cardio-pulmonary coupling coefficient (CPC)", quantify the dynamic association between cardiac contraction and respiratory cycle, and combine with EMAT% to enhance the sensitivity to early cardiac insufficiency.

[0056] Furthermore, in this embodiment, the present disclosure further includes: establishing a user database model. By establishing a personalized threshold model, through input parameters: age, gender, BMI, diabetes history, resting heart rate, medication history (such as beta-blockers), etc. for feature engineering, using a gradient boosting decision tree (GBDT) regression model to output an individualized EMAT% threshold. For example: elderly patients (>65 years old): threshold = 11.9% + 0.1×age coefficient; diabetic patients: threshold = 11.9% - 0.3×blood glucose control level (HbA1c%). And conduct machine learning and comparison analysis on user data to give early warnings to users who may have abnormal heart sound signals caused by reduced left ventricular systolic function; among them, user data at least includes: heart sound signals, electrocardiogram signals, and recognition results. It also includes data filtering and validity analysis of the collected information. For valid data, use a signal processing method based on continuous wavelet transform for preliminary feature extraction, and use an artificial intelligence algorithm based on deep learning to further extract heart sound signals and electrocardiogram signals, so as to obtain accurate electrocardiograms, phonocardiograms, and corresponding energy distribution maps. After processing and analyzing the current collected user data using the analysis algorithm, then conduct user data comparison, that is, compare the analyzed user data with the user's historical data, and at the same time compare it with the known diseased data to determine whether the heart sound signal and electrocardiogram signal are developing in the direction of forming abnormal murmurs caused by reduced left ventricular systolic function, or have already formed abnormal murmurs caused by reduced left ventricular systolic function, and then determine the user's physical health status. The analysis results of user data can be directly displayed and alarmed, and at the same time, the analysis results can be submitted to the nurse station and other medical assistance systems, data centers, and the patient's attending doctor through the network. If it is found that the user information is abnormal, such as a significant change compared with the user's historical data, and the data pattern is close to the known diseased data, then an alarm is issued to remind the user to pay attention to the risk. Furthermore, when it is determined according to data analysis that the frequency threshold of the current user is much higher than the feature threshold, it means that the user is in an emergency state. At this time, the database system can send a rescue signal to the outside world. For example, send a help signal to the emergency center or a pre-set emergency contact to improve the timeliness of rescue.

[0057] The second aspect of the present disclosure is introduced below: a device for synchronously assisting in identifying reduced left ventricular systolic function after STEMI by combining heart sound and electrocardiogram.

[0058] The device for synchronously assisting in identifying reduced left ventricular systolic function after STEMI provided in this embodiment is used to assist in diagnosing cardiac dysfunction in patients after ST-segment elevation myocardial infarction, and to implement the method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI as described above. As Figure 2 shown, the device 200 for synchronously assisting in identifying reduced left ventricular systolic function after STEMI includes: an acquisition unit 201, which includes a sound sensor for synchronously acquiring heart sound signals and electrodes for electrocardiogram signals, and respectively obtains corresponding heart sound data and electrocardiogram data. Here, the acquisition unit 201 may also include a heart sound processing unit and / or an electrocardiogram processing unit. The heart sound processing unit is used to process the heart sound signals collected by the sound sensor to obtain preset parameters of the heart sound signals, and the preset parameters at least include time, frequency, and energy; the electrocardiogram processing unit is used to process the electrocardiogram signals collected by the electrodes.

[0059] A processor unit 202 is configured to obtain an electromechanical activation time parameter during the period from the Q wave in the electrocardiogram data to the peak of the first heart sound in the heart sound data; obtain an RR interval parameter of the time limit between two adjacent R waves corresponding to the electromechanical activation time in the electrocardiogram data; calculate the ratio of the electromechanical activation time to the RR interval as an electromechanical activation time parameter standardized by heart rate, and determine whether the electromechanical activation time standardized by heart rate is greater than a preset threshold. If so, it is determined that the left ventricular systolic function of the subject is reduced; if not, it is determined that the left ventricular systolic function of the subject is normal.

[0060] Among them, the processor unit 202 can also determine the first heart sound, second heart sound, etc. of the heart sound signal according to the electrocardiogram signal, and determine the systolic period according to the first heart sound and the second heart sound.

[0061] In addition, in some optional embodiments, a circuit module is provided in the processor unit 202. The sound sensor and the electrodes are integrally arranged and connected to the circuit module to transmit the collected heart sound signals and electrocardiogram signals to the circuit module for processing to obtain stable heart sound signals and electrocardiogram signals.

[0062] In addition, in some alternative embodiments, the acquisition unit 201 further includes an adhesive patch. The adhesive patch is made of a medical-grade silicone material and is used to fix the acquisition unit 201 to the human skin. The provision of the adhesive patch can ensure the normal use of the acquisition unit 201 and minimize the impact on the user's daily life and work, facilitating long-term wearing and testing by the user. The above-mentioned wearable acquisition unit 201 breaks through the above limitations by adopting remote non-invasive detection. This device enables patients themselves to continuously use it outside the hospital environment. On the other hand, the wearable acquisition unit 201 can facilitate remote medical guidance and overall management during the entire monitoring process. This feature is particularly beneficial for the elderly and rural patients as it allows for continuous and easy-to-use monitoring outside the clinical environment. In addition, the device can be integrated with a mobile phone application to further ensure that patients can independently manage their health while maintaining close communication with medical institutions.

[0063] Further, in the embodiments of the present disclosure, the device 200 for synchronously assisting in identifying the reduction of left ventricular systolic function after STEMI by heart sound and electrocardiogram further includes: a database unit for establishing a user database model, performing machine learning and comparison analysis on user data, and giving early warnings to users who may have abnormal heart sound signals caused by the reduction of left ventricular systolic function; wherein, the user data at least includes: heart sound signals, electrocardiogram signals, and identification results.

[0064] In addition, in some alternative embodiments, the database unit may store information such as user name, gender, age, height, weight, medical records, and cardiac monitoring data. The database unit can receive the human vital sign data transmitted from the user terminal device, automatically store and file it, automatically perform analysis, feature extraction, and identification, etc., and then transmit the analysis results (such as analysis reports, health suggestions, or disease early warnings, etc.) to the user terminal device through the communication unit. Of course, the database unit may also not send its analysis results, but instead, the user can log in to the cloud data center through the user terminal device to view them. In addition, on the premise of user permission, the collected human vital sign data and analysis results can also be called by professional medical personnel or institutions as a reference for further medical examinations or diagnoses. Also on the premise of user permission, experts in third-party medical research, data analysis, data statistics, and data mining can conduct more in-depth analysis and research on the data. Their research results can be uploaded to the database unit for users to view. Users can also select and customize different analysis and feature extraction algorithms on the database unit and pay usage fees to the algorithm developers through the database unit, etc.

[0065] In addition, in some alternative embodiments, the database unit may process relevant data based on artificial intelligence technology. Among them, Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results. The database unit can learn based on a dataset of human body feature monitoring data from one or more users. Machine learning algorithms can discover patterns and relationships among several independent variables and dependent variables that can be derived from the data. Continuous consideration of these variables or other learned variables continuously updated from the algorithms can allow the machine learning algorithms to probabilistically determine, for example, classify, diagnose, and / or predict the status of patients. As an example, the machine learning algorithm can be configured to employ any one or more of Bayesian, random forest, decision tree, linear regression, deep learning, neural network, and / or dimensionality reduction techniques.

[0066] The following introduces another aspect of the embodiments of the present disclosure: a system for synchronously assisting in identifying reduced left ventricular systolic function after STEMI by heart sound and electrocardiogram.

[0067] As Figure 3 shown, the system structure may include terminal devices 301, 302, 303, 304, 307, a network 305, and a server 306. The network 305 is used to provide a medium for communication links between the terminal devices 301, 302, 303, 304, 307 and the server 306.

[0068] In this embodiment, the electronic device (such as the terminal devices 301, 302, 303, or 304 shown in the figure) on which the method runs can transmit various information through the network 305. The network 305 can include various connection types, such as wired, wireless communication links, or fiber optic cables, etc. It should be noted that the above wireless connection methods may include, but are not limited to, 3G / 4G / 5G connections, Wi-Fi connections, Bluetooth connections, WiMAX connections, Zigbee connections, UWB connections, local area networks ("LAN"), wide area networks ("WAN"), the Internet (for example, the Internet), and end-to-end networks (for example, ad hoc end-to-end networks), as well as other network connection methods known now or developed in the future. The network 305 can communicate using any currently known or future-developed network protocol such as HTTP (Hyper Text Transfer Protocol), and can be interconnected with digital data communication in any form or medium (for example, a communication network).

[0069] Users can use terminal devices 301, 302, 303, 304 to interact with server 306 via network 305 to receive or send messages, etc. Various client applications can be installed on terminal devices 301, 302, 303, or 304, such as video live streaming and playback applications, web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0070] Terminal devices 301, 302, 303, or 304 can be various electronic devices with a touch display screen and / or supporting web browsing, including but not limited to mobile terminals such as smartphones, tablets, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, MP4 (Moving Picture Experts Group Audio Layer IV) players, head-mounted display devices, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PMPs (Portable Multimedia Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and such as digital TVs, desktop computers, etc.

[0071] Server 306 can be a server that provides various services, such as a background server that provides support for the pages displayed on or the data transmitted by terminal devices 301, 302, 303, or 304. Server 306 can be, for example, a local server or a cloud server.

[0072] It should be understood that Figure 3 the numbers of terminal devices, networks, and servers in

[0073] are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, networks, and servers.

[0074] Next, another aspect of the embodiments of the present disclosure will be introduced: terminal devices.

[0075] Referring to Figure 4 , which shows a schematic structural diagram of an electronic device (such as Figure 3 the terminal device or server in

[0076] such as Figure 4As shown, the electronic device 400 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 401 for controlling the overall operation of the electronic device. The processing device may include one or more processors to execute instructions to complete all or part of the steps of the above method. In addition, the processing device 401 may also include one or more modules for processing interactions with other devices.

[0077] The storage device 402 is used to store various types of data. The storage device 402 may include various types of computer-readable storage media or combinations thereof. For example, it may be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or component.

[0078] The sensor device 403 is used to sense the information of a specified measured quantity and convert it into an available output signal according to a certain rule, and may include one or more sensors. For example, it may include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor, etc., for detecting changes in the open / closed state, relative positioning, acceleration / deceleration, temperature, humidity, and light of the electronic device.

[0079] The processing device 401, the storage device 402, and the sensor device 403 are connected to each other through a bus 404. The input / output (I / O) interface 405 is also connected to the bus 404.

[0080] The multimedia device 406 may include input devices such as a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, etc. to receive input signals from the user. The various input devices can cooperate with the various sensors of the above sensor device 403 to complete, for example, gesture operation input, image recognition input, distance detection input, etc.; the multimedia device 406 may also include output devices such as a liquid crystal display (LCD), a speaker, a vibrator, etc.

[0081] The power supply device 407 is used to provide power for various devices in the electronic device, and may include a power management system, one or more power supplies, and components for distributing power to other devices.

[0082] The communication device 408 can allow the electronic device 400 to communicate with other devices wirelessly or wiredly to exchange data.

[0083] Each of the above devices can also be connected to the I / O interface 405 to implement the applications of the electronic device 400.

[0084] It should be understood that although each block in the block diagrams of the accompanying drawings may represent a module, a part of the module contains one or more executable instructions for implementing the specified logical functions, but these modules are not necessarily executed sequentially. Each module and functional unit in the device embodiments of the present disclosure may be integrated in a processing module, or each unit may exist physically alone, or two or more modules or functional units may be integrated in one module. Each of the above integrated modules may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium. The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disc, etc.

[0085] Although Figure 4 an electronic device with various devices is shown, it should be understood that it is not required to implement or have all the shown devices. Instead, more or fewer devices may be implemented or had.

[0086] In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments of the present disclosure include a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program codes for executing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device, or installed from the storage device. When the computer program is executed by the processing device, the above-mentioned functions defined in the methods of the embodiments of the present disclosure are executed.

[0087] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0088] It should be noted that the computer-readable medium described above can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. In the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable signal medium can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0089] The above computer-readable medium can be included in the above electronic device; or it can exist separately without being assembled into the electronic device.

[0090] The computer program code for performing the operations of the present disclosure can be written in one or more programming languages or combinations thereof. The above programming languages include but are not limited to object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network connection, or it can be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0091] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0092] The units involved in the embodiments described in the present disclosure can be implemented in software or in hardware. In some cases, the name of the unit does not constitute a limitation on the unit itself.

[0093] The functions described above herein can be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), and so on.

[0094] Next, the features of the above embodiments according to the present disclosure are briefly summarized and listed.

[0095] According to one or more embodiments of the present disclosure, a method for synchronously assisting in the identification of reduced left ventricular systolic function after STEMI using heart sound and electrocardiogram is provided for assisting in the diagnosis of cardiac dysfunction in patients after ST-segment elevation myocardial infarction, including: Synchronously collecting a human heart sound signal and an electrocardiogram signal, and respectively obtaining corresponding electrocardiogram data and heart sound data; Obtaining an electromechanical activation time parameter during the period from the Q wave in the electrocardiogram data to the peak of the first heart sound in the heart sound data; Obtaining an RR interval parameter of the time limit between two adjacent R waves in the electrocardiogram data corresponding to the electromechanical activation time; Calculate the ratio of the electromechanical activation time to the RR interval as the electromechanical activation time parameter normalized by heart rate, and determine whether the electromechanical activation time normalized by heart rate is greater than a preset threshold. If so, it is determined that the left ventricular systolic function of the subject is reduced; if not, it is determined that the left ventricular systolic function of the subject is normal.

[0096] According to one or more embodiments of the present disclosure, there is provided a method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI, including: the preset threshold is at least 11.9%.

[0097] According to one or more embodiments of the present disclosure, there is provided a method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI, further including: Obtain the pre-ejection period parameter of the time from the Q wave to the end of the first heart sound, and calculate the pre-ejection period normalized by heart rate to assist in determining whether the left ventricular systolic function of the subject has decreased.

[0098] According to one or more embodiments of the present disclosure, there is provided a method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI, further including: obtaining the left ventricular ejection time parameter from the end of the first heart sound to the peak of the second heart sound in the heart sound data, and calculating the ratio of the pre-ejection period parameter to the left ventricular ejection time parameter to assist in determining whether the left ventricular systolic function of the subject has decreased.

[0099] According to one or more embodiments of the present disclosure, there is provided a method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI, The method is also used to predict the incidence of major adverse cardiovascular events.

[0100] According to one or more embodiments of the present disclosure, there is provided a method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI, Establish a user database model, perform machine learning and comparison analysis on user data, and give early warnings to users who may have reduced left ventricular systolic function; Wherein, the user data at least includes: the heart sound signal, the electrocardiogram signal, and the recognition result.

[0101] According to one or more embodiments of the present disclosure, there is provided a device for synchronously assisting in identifying reduced left ventricular systolic function after STEMI, which is used to assist in diagnosing cardiac dysfunction in patients after ST-segment elevation myocardial infarction and is used to implement the above method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI, including: The acquisition unit includes a sound sensor for synchronously acquiring heart sound signals and electrodes for electrocardiogram signals, and respectively obtains corresponding heart sound data and electrocardiogram data; The processor unit is configured to obtain an electromechanical activation time parameter during the period from the Q wave in the electrocardiogram data to the peak of the first heart sound in the heart sound data; obtain an RR interval parameter of the time limit between two adjacent R waves corresponding to the electromechanical activation time in the electrocardiogram data; calculate a ratio of the electromechanical activation time to the RR interval as an electromechanical activation time parameter normalized by heart rate, and determine whether the electromechanical activation time parameter normalized by heart rate is greater than a preset threshold. If so, it is determined that the left ventricular systolic function of the subject is reduced; if not, it is determined that the left ventricular systolic function of the subject is normal.

[0102] According to one or more embodiments of the present disclosure, there is provided a device for synchronously assisting in identifying reduced left ventricular systolic function after STEMI, the device for synchronously assisting in identifying reduced left ventricular systolic function after STEMI further includes: The database unit is configured to establish a user database model, perform machine learning and comparison analysis on user data, and give an early warning to users who may have abnormal heart sound signals caused by reduced left ventricular systolic function; Wherein, the user data at least includes: the heart sound signal, the electrocardiogram signal, and the identification result.

[0103] According to one or more embodiments of the present disclosure, there is provided a computer device, including a memory, a processor, and a computer program stored on the memory, wherein the processor executes the computer program to implement the steps of the method as described in any one of the above.

[0104] According to one or more embodiments of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the steps of the method as described in any one of the above.

[0105] According to one or more embodiments of the present disclosure, there is provided a computer program product, including a computer program, wherein the computer program, when executed by a processor, implements the steps of the method as described in any one of the above.

[0106] The above description is only a preferred embodiment of the present disclosure and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present disclosure.

[0107] In addition, although the operations are depicted in a particular order, this should not be construed as requiring that the operations be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although a number of specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features described in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, the various features described in the context of a single embodiment may also be implemented separately or in any suitable sub-combination in multiple embodiments.

[0108] Although the subject matter has been described in language specific to structural features and / or methodological logical acts, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. On the contrary, the specific features and acts described above are merely example forms for implementing the claims.

Claims

1. A method for synchronously assisting in identifying reduced left ventricular systolic function after STEMI by heart sound and electrocardiogram, characterized in that, For assisting in the diagnosis of cardiac dysfunction in patients after ST-segment elevation myocardial infarction, including: Synchronously collecting the heart sound signal and electrocardiogram signal of the human body, and respectively obtaining the corresponding electrocardiogram data and heart sound data; Obtaining the electromechanical activation time parameter during the period from the Q wave in the electrocardiogram data to the peak of the first heart sound in the heart sound data; Obtaining the RR interval parameter of the time limit between two adjacent R waves corresponding to the electromechanical activation time in the electrocardiogram data; Calculating the ratio of the electromechanical activation time to the RR interval as the electromechanical activation time parameter standardized by heart rate, and determining whether the electromechanical activation time standardized by heart rate is greater than a preset threshold. If so, it is determined that the left ventricular systolic function of the person being collected is reduced; if not, it is determined that the left ventricular systolic function of the person being collected is normal.

2. The method according to claim 1, characterized in that The preset threshold is at least 11.9%.

3. The method according to claim 1, characterized in that, It also includes: Obtaining the pre-ejection period parameter of the time from the Q wave to the end of the first heart sound, and calculating the pre-ejection period standardized by heart rate to assist in determining whether the left ventricular systolic function of the person being collected has decreased.

4. The method according to claim 3, characterized in that, It also includes: Obtaining the left ventricular ejection time parameter from the end of the first heart sound to the peak of the second heart sound in the heart sound data, and calculating the ratio of the pre-ejection period parameter to the left ventricular ejection time parameter to assist in determining whether the left ventricular systolic function of the person being collected has decreased.

5. The method according to any one of claims 1-4, wherein The method is also used to predict the incidence of major adverse cardiovascular events.

6. The method according to claim 1, characterized in that, It also includes: Establishing a user database model, performing machine learning and comparison analysis on user data, and giving early warnings to users who may have reduced left ventricular systolic function; Wherein, the user data at least includes: the heart sound signal, the electrocardiogram signal, and the recognition result.

7. A device for synchronously assisting in identifying the reduction of left ventricular systolic function after STEMI, characterized in that, For assisting in the diagnosis of cardiac dysfunction in patients after ST-segment elevation myocardial infarction, and for implementing the method according to any one of claims 1-6, including: An acquisition unit, including a sound sensor for synchronously collecting the heart sound signal and an electrode for collecting the electrocardiogram signal, and respectively obtaining the corresponding heart sound data and electrocardiogram data; A processor unit, for obtaining the electromechanical activation time parameter during the period from the Q wave in the electrocardiogram data to the peak of the first heart sound in the heart sound data; obtaining the RR interval parameter of the time limit between two adjacent R waves corresponding to the electromechanical activation time in the electrocardiogram data; calculating the ratio of the electromechanical activation time to the RR interval as the electromechanical activation time parameter standardized by heart rate, and determining whether the electromechanical activation time standardized by heart rate is greater than a preset threshold. If so, it is determined that the left ventricular systolic function of the person being collected is reduced; if not, it is determined that the left ventricular systolic function of the person being collected is normal.

8. A computer device, comprising a memory, a processor, and a computer program stored on the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The computer program, when executed by a processor, implements the steps of the method according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, The computer program, when executed by a processor, implements the steps of the method according to any one of claims 1-6.

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