WO2024148726A1 - Cardiac test assessment method, system and apparatus, and storage medium - Google Patents

Abstract

Disclosed in the present application are a cardiac test assessment method, system and apparatus, and a storage medium. The method comprises: collecting electrocardiogram signals of different patients, so as to identify abnormal data, wherein the abnormal data comprises at least one of abnormal heart rate data, abnormal electrocardiogram low-frequency component data, abnormal blood oxygen data, and abnormal blood pressure data; in response to the abnormal data, performing electrocardiogram high-frequency component analysis, so as to extract a first number of leads that meet a positive indicator, wherein the positive indicator indicates that a high-frequency morphology index of a corresponding lead is greater than a first threshold value; and determining the magnitudes of the first number of leads and a preset lead threshold value, wherein if the first number of leads is greater than the lead threshold value, an alarm reminder is outputted.

Description

Cardiac detection and evaluation method, system, storage medium and device

This application claims priority to the Chinese patent application filed with the China Patent Office on January 10, 2023, with application number 2023100325464, and application name “Cardiac Detection and Evaluation Method, System, Storage Medium and Device”, all contents of which are incorporated by reference in this application.

Technical Field

The present application relates to the field of smart medical technology, and more specifically, to a cardiac detection and evaluation method, system, storage medium and device.

Background technique

The ECG monitor is a sophisticated medical instrument that can monitor the patient's heart rate, blood pressure, electrocardiogram, blood oxygen saturation, respiration, body temperature and other physiological parameters. It is widely used in many places such as ICU, CCU, operating room, ward, etc. to achieve real-time detection of patients.

Traditional ECG monitors mainly focus on the ST segment of cardiac repolarization and low-frequency ECG signals. They have low detection sensitivity and accuracy in analyzing and monitoring the heart health of patients, and cannot effectively detect heart problems and changes in the condition. For hospitalized patients receiving cardiac treatment, the treatment effect cannot be evaluated in a timely manner.

Summary of the invention

According to the various embodiments disclosed in the present application, a heart detection and evaluation method, system, storage medium and device are provided, which are further combined with the analysis of the high-frequency components of the ECG. Since the high-frequency components of the ECG can reach the microvolt level, the heart state can be reflected in a timely manner. The detection has high sensitivity and accuracy, and can accurately indicate the risk of myocardial ischemia and heart failure problems.

The first aspect of the present application provides a heart detection and evaluation method, comprising the following steps:

Collect ECG signals from different patients to identify abnormal data, wherein the abnormal data includes at least one of abnormal heart rate data, abnormal ECG low-frequency component data, abnormal blood oxygen data or abnormal blood pressure data;

In response to the abnormal data, an ECG high-frequency component analysis is performed, and the QRS wave group data in the ECG high-frequency component is analyzed to extract the number of first leads that meet the positive index, wherein the positive index indicates that the high-frequency morphology index of the corresponding lead is greater than a first threshold value;

The difference between the first number of leads and a preset lead threshold is determined, wherein if the first number of leads is greater than the lead threshold, an alarm is output.

In this embodiment, the method further includes obtaining a second number of leads, wherein the second number of leads corresponds to the number of leads in which the high-frequency QRS envelope curve formed by the high-frequency QRS complex data in a resting state drops more than a preset second threshold.

In this solution, the acquisition of ECG signals of different patients to identify abnormal data specifically includes:

Based on the preset acquisition module, the patient's physiological information is collected and converted into electrical signals, which are input into the preset ECG monitoring module for monitoring;

Monitoring the patient's blood pressure based on the blood pressure monitoring unit in the electrocardiogram monitoring module to identify abnormal blood pressure data;

Monitoring the patient's blood oxygen based on the blood oxygen monitoring unit in the ECG monitoring module to identify abnormal blood oxygen data;

Monitoring the patient's ECG based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal ECG low-frequency component data;

The heart rate monitoring unit in the electrocardiogram monitoring module monitors the patient's heart rate to identify abnormal heart rate data.

In this solution, the high-frequency component analysis based on the abnormal data and the QRS wave group data in the high-frequency component of the electrocardiogram are analyzed to extract the number of first leads that meet the positive indicator, specifically including:

Align, filter and average the QRS wave group data in the high-frequency component of the ECG to form a high-frequency QRS envelope curve;

The total area of each amplitude reduction region in the high-frequency QRS envelope curve is obtained as a first total area, and the total area below the high-frequency QRS envelope curve is obtained as a second total area;

A high-frequency morphology index is obtained by calculating a ratio based on the first total area and the second total area, and the lead whose high-frequency morphology index is greater than a first threshold is taken as the positive indicator.

In this scheme, the number of descents of the high-frequency QRS envelope curve formed by the high-frequency QRS wave group data in the resting state is obtained, including:

Align, filter and average the QRS wave group data in the high-frequency component of the ECG to form a high-frequency QRS envelope curve;

Counting the peak-to-peak values of each amplitude reduction region of the high-frequency QRS envelope curve of each lead, and determining the number of drops of the electrocardiogram signal in a resting state based on the total number of the peak-to-peak values; or

The area of the region where the amplitude of each high-frequency QRS envelope curve in each lead decreases is calculated to obtain the number of declines of the ECG signal in the resting state.

In this solution, the method further includes identifying an area decrease value of the amplitude reduction region, and outputting an alarm reminder when the area decrease value exceeds a preset decrease threshold.

The second aspect of the present application further provides a heart detection and evaluation system, including a memory and a processor, wherein the memory includes a heart detection and evaluation method program, and when the heart detection and evaluation method program is executed by the processor, the following steps are implemented:

Collect ECG signals from different patients to identify abnormal data, wherein the abnormal data includes at least one of abnormal heart rate data, abnormal ECG low-frequency component data, abnormal blood oxygen data or abnormal blood pressure data;

In response to the abnormal data, an ECG high-frequency component analysis is performed, and the QRS wave group data in the ECG high-frequency component is analyzed to extract the number of first leads that meet the positive index, wherein the positive index indicates that the high-frequency morphology index of the corresponding lead is greater than a first threshold value;

The difference between the first number of leads and a preset lead threshold is determined, wherein if the first number of leads is greater than the lead threshold, an alarm is output.

In this solution, when the heart detection and evaluation method program is executed by the processor, the following steps are also implemented:

A second lead number is obtained, wherein the second lead number corresponds to the number of leads whose number of drops of the electrocardiogram signal in a resting state exceeds a preset second threshold.

In this solution, the acquisition of ECG signals of different patients to identify abnormal data specifically includes:

Based on the preset acquisition module, the patient's physiological information is collected and converted into electrical signals, which are input into the preset ECG monitoring module for monitoring;

Monitoring the patient's blood pressure based on the blood pressure monitoring unit in the electrocardiogram monitoring module to identify abnormal blood pressure data;

Monitoring the patient's blood oxygen based on the blood oxygen monitoring unit in the ECG monitoring module to identify abnormal blood oxygen data;

Monitoring the patient's ECG based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal ECG low-frequency component data;

The heart rate monitoring unit in the electrocardiogram monitoring module monitors the patient's heart rate to identify abnormal heart rate data.

In this solution, the high-frequency component analysis based on the abnormal data and the QRS wave group data in the high-frequency component of the electrocardiogram are analyzed to extract the number of first leads that meet the positive indicator, specifically including:

Align, filter and average the QRS wave group data in the high-frequency component of the ECG to form a high-frequency QRS envelope curve;

The total area of each amplitude reduction region in the high-frequency QRS envelope curve is obtained as a first total area, and the total area below the high-frequency QRS envelope curve is obtained as a second total area;

A high-frequency morphology index is obtained by calculating a ratio based on the first total area and the second total area, and the lead whose high-frequency morphology index is greater than a first threshold is taken as the positive indicator.

In this scheme, the number of descents of the high-frequency QRS envelope curve formed by the high-frequency QRS wave group data in the resting state is obtained, including:

Align, filter and average the QRS wave group data in the high-frequency component of the ECG to form a high-frequency QRS envelope curve;

Counting the peak-to-peak values of each amplitude reduction region of the high-frequency QRS envelope curve of each lead, and determining the number of drops of the electrocardiogram signal in a resting state based on the total number of the peak-to-peak values; or

The area of the region where the amplitude of each high-frequency QRS envelope curve in each lead decreases is calculated to obtain the number of declines of the ECG signal in the resting state.

In this solution, the method further includes identifying an area decrease value of the amplitude reduction region, and outputting an alarm reminder when the area decrease value exceeds a preset decrease threshold.

A third aspect of the present application provides a computer-readable storage medium, which includes a heart detection and evaluation method program for a machine. When the heart detection and evaluation method program is executed by a processor, the steps of the heart detection and evaluation method are implemented.

A fourth aspect of the present application provides a cardiac detection and evaluation device, wherein the device implements the cardiac detection and evaluation method, including:

A high-frequency QRS ECG analysis module, an ECG monitoring module wirelessly connected to the high-frequency QRS, and an acquisition module wirelessly connected to the ECG monitoring module, wherein:

The acquisition module includes a number of sensors for collecting the patient’s physiological information and converting it into electrical signals for input into the ECG monitoring module;

The ECG monitoring module includes a blood pressure monitoring unit, a heart rate monitoring unit, a blood oxygen monitoring unit and an ST segment ECG monitoring unit, which are used to monitor the vital signs of different patients based on the electrical signals input by the acquisition module;

The high-frequency QRS ECG analysis module is used to analyze the monitoring data input by the ECG monitoring module to output an alarm reminder.

The details of one or more embodiments of the present application are set forth in the following drawings and description. Other features and advantages of the present application will become apparent from the description, drawings, and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

FIG1 shows a flow chart of a cardiac detection and evaluation method of the present application;

FIG2 is a schematic diagram showing an amplitude reduction region of a heart detection and evaluation method of the present application;

FIG3 shows a block diagram of a heart detection and evaluation system of the present application;

FIG. 4 shows a block diagram of a cardiac detection and evaluation system according to the present application.

Detailed ways

In order to more clearly understand the above-mentioned purposes, features and advantages of the present application, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present application is not limited to the specific embodiments disclosed below.

FIG1 shows a flow chart of a heart detection and evaluation method of the present application.

As shown in FIG1 , the present application discloses a heart detection and evaluation method, comprising the following steps:

S102, collecting ECG signals of different patients to identify abnormal data, wherein the abnormal data includes at least one of abnormal heart rate data, abnormal ECG low frequency component data, abnormal blood oxygen data or abnormal blood pressure data;

S104, in response to the abnormal data, performing an ECG high frequency component analysis, analyzing the QRS wave group data in the ECG high frequency component to extract the number of first leads that meet the positive indicator, wherein the positive indicator indicates that the high frequency morphology index of the corresponding lead is greater than a first threshold value;

S106, determining the difference between the first number of leads and a preset lead threshold, wherein if the first number of leads is greater than the lead threshold, outputting an alarm reminder.

It should be noted that, in this embodiment, the physiological information of the patient is collected to generate an electrical signal so as to identify abnormal data based on the electrocardiogram signals of different patients. Accordingly, the collected physiological information includes heart rate, blood pressure, etc. Therefore, the abnormal data at least includes abnormal heart rate data, abnormal electrocardiogram low-frequency component data, abnormal blood oxygen data and abnormal blood pressure data. In actual application, it can be a combination of one or more abnormal data, and high-frequency component analysis is performed based on the abnormal data, including extracting the number of first leads that meet the positive indicators for judgment, and comparing with the lead threshold, wherein the lead threshold is "3". When the number of the first leads that meet the positive indicators is greater than "3", it can accurately indicate the risk of myocardial ischemia, thereby outputting the corresponding alarm reminder. For the description of the positive indicators, please refer to the subsequent description.

In the above-mentioned heart detection and evaluation method, by further cooperating with the analysis of the high-frequency components of the ECG, because the high-frequency components of the ECG can reach the microvolt level, it can reflect the heart state in a timely manner. The detection has high sensitivity and accuracy, and can accurately indicate the risk of myocardial ischemia and heart failure problems.

According to an embodiment of the present application, the method also includes obtaining a second number of leads, wherein the second number of leads corresponds to the number of leads in which the high-frequency QRS envelope curve formed by the high-frequency QRS complex data in a resting state drops more than a preset second threshold.

It should be noted that, in the present embodiment, the above-mentioned embodiment illustrates the use of the first lead number to compare with the lead threshold to output an alarm reminder of myocardial ischemia, while in the present embodiment, the second lead number is obtained for judgment. If the second lead number exceeds the second threshold, it can further indicate that the heart has a heart failure problem, wherein the second threshold is "3", and the second lead number is the number of times the ECG signal shows a downward trend, wherein the downward trend of the ECG signal is used to characterize the appearance of a reduced amplitude area (Reduced Amplitude Zone, RAZ) in the QRS waveform of the ECG signal corresponding to the resting state, as shown in Figure 2, the reduced amplitude area refers to the concave area S formed between point A and point B in the QRS waveform of the ECG signal corresponding to the resting state.

According to an embodiment of the present application, collecting ECG signals of different patients to identify abnormal data specifically includes:

Based on the preset acquisition module, the patient's physiological information is collected and converted into electrical signals, which are input into the preset ECG monitoring module for monitoring;

Monitoring the patient's blood pressure based on the blood pressure monitoring unit in the electrocardiogram monitoring module to identify abnormal blood pressure data;

Monitoring the patient's blood oxygen based on the blood oxygen monitoring unit in the ECG monitoring module to identify abnormal blood oxygen data;

Monitoring the patient's ECG based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal ECG low-frequency component data;

The heart rate monitoring unit in the electrocardiogram monitoring module monitors the patient's heart rate to identify abnormal heart rate data.

It should be noted that, in this embodiment, the identified abnormal data includes abnormal blood pressure data, abnormal blood oxygen data and abnormal heart rate data. Specifically, the patient's blood pressure is monitored by the blood pressure monitoring unit in the ECG monitoring module to identify abnormal blood pressure data; and the patient's blood oxygen is monitored based on the blood oxygen monitoring unit in the ECG monitoring module to identify abnormal blood oxygen data; and the patient's ECG is monitored based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal ECG low-frequency component data; and the patient's ECG is monitored based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal ECG low-frequency component data.

According to an embodiment of the present application, the high-frequency component analysis based on the abnormal data and the QRS wave group data in the high-frequency component of the electrocardiogram are analyzed to extract the number of first leads that meet the positive indicator, specifically including:

Align, filter and average the QRS wave group data in the high-frequency component of the ECG to form a high-frequency QRS envelope curve;

The total area of each amplitude reduction region in the high-frequency QRS envelope curve is obtained as a first total area, and the total area below the high-frequency QRS envelope curve is obtained as a second total area;

A high-frequency morphology index is obtained by calculating a ratio based on the first total area and the second total area, and the lead whose high-frequency morphology index is greater than a first threshold is taken as the positive indicator.

It should be noted that, in this embodiment, the first threshold value is "15%". When the ratio of the first total area to the second total area is greater than "15%", it indicates that the current lead meets the positive indicators, wherein the first total area is the total area of each amplitude reduction region of the ECG signal corresponding to the resting state; the second total area is the total area under the envelope of the ECG signal corresponding to the resting state.

According to an embodiment of the present application, obtaining the number of descent times of a high-frequency QRS envelope curve formed by high-frequency QRS complex data in a resting state includes:

Align, filter and average the QRS wave group data in the high-frequency component of the ECG to form a high-frequency QRS envelope curve;

Counting the peak-to-peak values of each amplitude reduction region of the high-frequency QRS envelope curve of each lead, and determining the number of drops of the electrocardiogram signal in a resting state based on the total number of the peak-to-peak values; or

The area of the region where the amplitude of each high-frequency QRS envelope curve in each lead decreases is calculated to obtain the number of declines of the ECG signal in the resting state.

It should be noted that in this embodiment, in a specific example, by counting the peak-to-peak values of each amplitude reduction region of the ECG signal corresponding to the resting state, the total number of peak-to-peak values of the ECG signal corresponding to the resting state can be determined as the number of times the ECG signal corresponding to the resting state shows a downward trend (or, by calculating the area of each amplitude reduction region in each lead exceeding a preset threshold to count the number of times the ECG signal shows a downward trend). After counting the number of times the ECG signal corresponding to the resting state shows a downward trend for each lead respectively, and comparing the number of times the ECG signal corresponding to the resting state shows a downward trend for each lead with the second threshold, the number of leads whose number of times the ECG signal corresponding to the resting state shows a downward trend exceeding the second threshold can be obtained, that is, the number of the second leads. Through the above analysis, it can be further suggested that the heart may have heart failure problems.

According to an embodiment of the present application, the method further includes identifying an area decrease value of the amplitude reduction region, and outputting an alarm reminder when the area decrease value exceeds a preset decrease threshold.

It should be noted that, in this embodiment, the drop threshold is "40%". When the area drop value corresponding to a certain lead exceeds "40%", an alarm reminder also needs to be output.

It should be understood that, although the various steps in the flowchart of FIG. 1 are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in FIG. 1 may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

FIG3 shows a block diagram of a heart detection and evaluation system of the present application.

As shown in FIG3 , the present application discloses a heart detection and evaluation system, including a memory and a processor, wherein the memory includes a heart detection and evaluation method program, and when the heart detection and evaluation method program is executed by the processor, the following steps are implemented:

Collecting ECG signals of different patients to identify abnormal data, wherein the abnormal data at least includes abnormal heart rate data, abnormal blood oxygen data and abnormal blood pressure data;

Performing high-frequency component analysis based on the abnormal data, analyzing the QRS wave group data in the high-frequency component of the electrocardiogram to extract the number of first leads that meet the positive index, wherein the positive index indicates that the high-frequency morphology index of the corresponding lead is greater than a first threshold value;

The difference between the first number of leads and a preset lead threshold is determined, wherein if the first number of leads is greater than the lead threshold, an alarm is output, otherwise no alarm is output.

It should be noted that, in this embodiment, the physiological information of the patient is collected to generate an electrical signal so as to identify abnormal data based on the electrocardiogram signals of different patients. Accordingly, the collected physiological information includes heart rate, blood pressure, etc. Therefore, the abnormal data at least includes abnormal heart rate data, abnormal electrocardiogram low-frequency component data, abnormal blood oxygen data and abnormal blood pressure data. In actual application, it can be a combination of one or more abnormal data, and high-frequency component analysis is performed based on the abnormal data, including extracting the number of first leads that meet the positive indicators for judgment, and comparing with the lead threshold, wherein the lead threshold is "3". When the number of the first leads that meet the positive indicators is greater than "3", it can accurately indicate the risk of myocardial ischemia, thereby outputting the corresponding alarm reminder. For the description of the positive indicators, please refer to the subsequent description.

According to an embodiment of the present application, when the heart detection and evaluation method program is executed by the processor, the following steps are also implemented:

A second number of leads is obtained, wherein the second number of leads corresponds to the number of leads whose number of drops of a high-frequency QRS envelope curve formed by high-frequency QRS complex data in a resting state exceeds a preset second threshold.

It should be noted that, in the present embodiment, the above-mentioned embodiment illustrates the use of the first lead number to compare with the lead threshold to output an alarm reminder of myocardial ischemia, while in the present embodiment, the second lead number is obtained for judgment. If the second lead number exceeds the second threshold, it can further indicate that the heart has a heart failure problem, wherein the second threshold is "3", and the second lead number is the number of times the ECG signal shows a downward trend, wherein the downward trend of the ECG signal is used to characterize the appearance of a reduced amplitude area (Reduced Amplitude Zone, RAZ) in the QRS waveform of the ECG signal corresponding to the resting state, as shown in Figure 2, the reduced amplitude area refers to the concave area S formed between point A and point B in the QRS waveform of the ECG signal corresponding to the resting state.

According to an embodiment of the present application, collecting ECG signals of different patients to identify abnormal data specifically includes:

Based on the preset acquisition module, the patient's physiological information is collected and converted into electrical signals, which are input into the preset ECG monitoring module for monitoring;

Monitoring the patient's blood pressure based on the blood pressure monitoring unit in the electrocardiogram monitoring module to identify abnormal blood pressure data;

Monitoring the patient's blood oxygen based on the blood oxygen monitoring unit in the ECG monitoring module to identify abnormal blood oxygen data;

Monitoring the patient's ECG based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal ECG low-frequency component data;

The heart rate monitoring unit in the electrocardiogram monitoring module monitors the patient's heart rate to identify abnormal heart rate data.

It should be noted that, in this embodiment, the identified abnormal data includes abnormal blood pressure data, abnormal blood oxygen data and abnormal heart rate data. Specifically, the patient's blood pressure is monitored by the blood pressure monitoring unit in the ECG monitoring module to identify abnormal blood pressure data; and the patient's blood oxygen is monitored based on the blood oxygen monitoring unit in the ECG monitoring module to identify abnormal blood oxygen data; and the patient's ECG is monitored based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal ECG low-frequency component data; and the patient's ECG is monitored based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal ECG low-frequency component data.

According to an embodiment of the present application, the high-frequency component analysis based on the abnormal data and the QRS wave group data in the high-frequency component of the electrocardiogram are analyzed to extract the number of first leads that meet the positive indicator, specifically including:

Align, filter and average the QRS wave group data in the high-frequency component of the ECG to form a high-frequency QRS envelope curve;

The total area of each amplitude reduction region in the high-frequency QRS envelope curve is obtained as a first total area, and the total area below the high-frequency QRS envelope curve is obtained as a second total area;

A high-frequency morphology index is obtained by calculating a ratio based on the first total area and the second total area, and the lead whose high-frequency morphology index is greater than a first threshold is taken as the positive indicator.

It should be noted that, in this embodiment, the first threshold value is "15%". When the ratio of the first total area to the second total area is greater than "15%", it indicates that the current lead meets the positive indicators, wherein the first total area is the total area of each amplitude reduction region of the ECG signal corresponding to the resting state; the second total area is the total area under the envelope of the ECG signal corresponding to the resting state.

According to an embodiment of the present application, obtaining the number of descent times of a high-frequency QRS envelope curve formed by high-frequency QRS complex data in a resting state includes:

Align, filter and average the QRS wave group data in the high-frequency component of the ECG to form a high-frequency QRS envelope curve;

Counting the peak-to-peak values of each amplitude reduction region of the high-frequency QRS envelope curve of each lead, and determining the number of drops of the electrocardiogram signal in a resting state based on the total number of the peak-to-peak values; or

The area of the region where the amplitude of each high-frequency QRS envelope curve in each lead decreases is calculated to obtain the number of declines of the ECG signal in the resting state.

It should be noted that in this embodiment, in a specific example, by counting the peak-to-peak values of each amplitude reduction region of the ECG signal corresponding to the resting state, the total number of peak-to-peak values of the ECG signal corresponding to the resting state can be determined as the number of times the ECG signal corresponding to the resting state shows a downward trend (or, by calculating the area of each amplitude reduction region in each lead exceeding a preset threshold to count the number of times the ECG signal shows a downward trend). After counting the number of times the ECG signal corresponding to the resting state shows a downward trend for each lead respectively, and comparing the number of times the ECG signal corresponding to the resting state shows a downward trend for each lead with the second threshold, the number of leads whose number of times the ECG signal corresponding to the resting state shows a downward trend exceeding the second threshold can be obtained, that is, the number of the second leads. Through the above analysis, it can be further suggested that the heart may have heart failure problems.

According to an embodiment of the present application, the method further includes identifying an area decrease value of the amplitude reduction region, and outputting an alarm reminder when the area decrease value exceeds a preset decrease threshold.

It should be noted that, in this embodiment, the drop threshold is "40%". When the area drop value corresponding to a certain lead exceeds "40%", an alarm reminder also needs to be output.

A third aspect of the present application provides a computer-readable storage medium, which includes a heart detection and evaluation method program. When the heart detection and evaluation method program is executed by a processor, the steps of the heart detection and evaluation method are implemented.

As shown in FIG. 4 , the fourth aspect of the present application provides a cardiac detection and evaluation device, wherein the device implements the cardiac detection and evaluation method, including:

A high-frequency QRS ECG analysis module, an ECG monitoring module wirelessly connected to the high-frequency QRS ECG analysis module, and an acquisition module wirelessly connected to the ECG monitoring module, wherein:

The acquisition module includes a number of sensors for collecting the patient’s physiological information and converting it into electrical signals for input into the ECG monitoring module;

The ECG monitoring module includes a blood pressure monitoring unit, a heart rate monitoring unit, a blood oxygen monitoring unit and an ST segment ECG monitoring unit, which are used to monitor the vital signs of different patients based on the electrical signals input by the acquisition module;

The high-frequency QRS ECG analysis module is used to analyze the monitoring data input by the ECG monitoring module to output an alarm reminder.

It should be noted that wireless communication is adopted between the acquisition module, the ECG monitoring module and the high-frequency QRS ECG analysis module to facilitate data transmission. In order to reduce the monitoring cost, a central monitoring mode can be adopted, that is, one high-frequency QRS ECG analysis module is communicatively connected with multiple ECG monitoring modules, and each ECG monitoring module is used to monitor different patients. The communication method can be as follows: Method 1: The acquisition module inputs the collected ECG signals of different patients into the corresponding ECG monitoring module, and the ECG monitoring module uploads the detected abnormal data to the high-frequency QRS ECG analysis module, and the high-frequency QRS ECG analysis module starts analysis. This working method can reduce the operating cost of the high-frequency QRS analysis module; Method 2: The acquisition module inputs the collected ECG signals of different patients into the corresponding ECG monitoring module, and each ECG monitoring module inputs the ECG data into the high-frequency QRS ECG analysis module. The high-frequency QRS ECG analysis module automatically adjusts the analysis frequency according to the patient's heart risk level (such as the number of positive leads exceeds "8", and analysis is performed once every "30" minutes), according to the set time or according to the number of positive leads in a certain period of time (such as the positive leads increase from "3" to "5"), and/or the change trend of the number of first leads (increases from "3" to "5").

The present application discloses a cardiac detection and evaluation method, system, storage medium and device, which can further cooperate with the analysis of the high-frequency components of the ECG. Since the high-frequency components of the ECG can reach the microvolt level, they can reflect the heart state in a timely manner, have high detection sensitivity and accuracy, and can accurately indicate the risk of myocardial ischemia and heart failure problems.

In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

A person skilled in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, etc. Various media that can store program codes.

Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can essentially or in other words, the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, disks, or optical disks.

Claims (8)

A heart detection and evaluation method, characterized by comprising: Collect ECG signals from different patients to identify abnormal data, wherein the abnormal data includes at least one of abnormal heart rate data, abnormal ECG low-frequency component data, abnormal blood oxygen data or abnormal blood pressure data; In response to the abnormal data, an ECG high-frequency component analysis is performed, and the QRS wave group data in the ECG high-frequency component is analyzed to extract the number of first leads that meet the positive index, wherein the positive index indicates that the high-frequency morphology index of the corresponding lead is greater than a first threshold value; Determine the size of the first lead number and a preset lead threshold, wherein if the first lead number is greater than the lead threshold, output an alarm reminder; The method further includes: obtaining a second number of leads, wherein the second number of leads corresponds to the number of leads whose number of declines of the high-frequency QRS envelope curve formed by the high-frequency QRS wave group data in a resting state exceeds a preset second threshold; In response to the abnormal data, an analysis of the high-frequency components of the ECG is performed, and the QRS wave group data in the high-frequency components of the ECG is analyzed to extract the number of first leads that meet the positive indicators, specifically including: Align, filter and average the QRS complex data in the high-frequency components of the ECG to form a high-frequency QRS envelope curve; The total area of each amplitude reduction region in the high-frequency QRS envelope curve is obtained as the first total area, and the total area below the high-frequency QRS envelope curve is obtained as the second total area; A high-frequency morphology index is obtained by calculating a ratio based on the first total area and the second total area, and a lead whose high-frequency morphology index is greater than a first threshold is taken as the positive indicator; Among them, the number of drops of the high-frequency QRS envelope curve formed by obtaining the high-frequency QRS wave group data in the resting state includes: Align, filter and average the QRS complex data in the high-frequency components of the ECG to form a high-frequency QRS envelope curve; Count the peak-to-peak values of each amplitude reduction area of the high-frequency QRS envelope curve of each lead, and determine the number of decreases of the ECG signal in the resting state based on the total number of peak-to-peak values; or The area of the region where the amplitude of each high-frequency QRS envelope curve in each lead decreases is calculated to obtain the number of declines of the ECG signal in the resting state. A cardiac detection and evaluation method according to claim 1, characterized in that said collecting ECG signals of different patients to identify abnormal data specifically includes: Based on the preset acquisition module, the patient’s physiological information is collected and converted into electrical signals which are input into the preset ECG monitoring module for monitoring; Monitor the patient’s blood pressure based on the blood pressure monitoring unit in the ECG monitoring module to identify abnormal blood pressure data; Monitor the patient’s blood oxygen based on the blood oxygen monitoring unit in the ECG monitoring module to identify abnormal blood oxygen data; Monitor the patient's ECG based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal data of the ECG low-frequency components; The heart rate monitoring unit in the ECG monitoring module monitors the patient's heart rate to identify abnormal heart rate data. The heart detection and evaluation method according to claim 1, characterized in that the method further comprises: Identify the area decrease value of the amplitude reduction region, and output an alarm reminder when the area decrease value exceeds the preset decrease threshold. A heart detection and evaluation system, characterized in that it includes a memory and a processor, wherein the memory includes a heart detection and evaluation method program, and when the heart detection and evaluation method program is executed by the processor, the following steps are implemented: Collect ECG signals from different patients to identify abnormal data, wherein the abnormal data includes at least one of abnormal heart rate data, abnormal ECG low-frequency component data, abnormal blood oxygen data or abnormal blood pressure data; In response to the abnormal data, an analysis of the ECG high-frequency components is performed, and the QRS wave group data in the ECG high-frequency components is analyzed to extract the number of first leads that meet the positive indicator, wherein the positive indicator indicates that the high-frequency morphology index of the corresponding lead is greater than a first threshold value; Determine the size of the first lead number and a preset lead threshold, wherein if the first lead number is greater than the lead threshold, output an alarm reminder; The method further includes: obtaining a second number of leads, wherein the second number of leads corresponds to the number of leads whose number of declines of the high-frequency QRS envelope curve formed by the high-frequency QRS wave group data in a resting state exceeds a preset second threshold; In response to the abnormal data, an analysis of the high-frequency components of the ECG is performed, and the QRS wave group data in the high-frequency components of the ECG is analyzed to extract the number of first leads that meet the positive indicators, specifically including: Align, filter and average the QRS complex data in the high-frequency components of the ECG to form a high-frequency QRS envelope curve; The total area of each amplitude reduction region in the high-frequency QRS envelope curve is obtained as the first total area, and the total area below the high-frequency QRS envelope curve is obtained as the second total area; A high-frequency morphology index is obtained by calculating a ratio based on the first total area and the second total area, and a lead whose high-frequency morphology index is greater than a first threshold is taken as the positive indicator; Among them, the number of drops of the high-frequency QRS envelope curve formed by obtaining the high-frequency QRS wave group data in the resting state includes: Align, filter and average the QRS complex data in the high-frequency components of the ECG to form a high-frequency QRS envelope curve; Count the peak-to-peak values of each amplitude reduction area of the high-frequency QRS envelope curve of each lead, and determine the number of decreases of the ECG signal in the resting state based on the total number of peak-to-peak values; or The area of the region where the amplitude of each high-frequency QRS envelope curve in each lead decreases is calculated to obtain the number of declines of the ECG signal in the resting state. A heart detection and evaluation system according to claim 4, characterized in that when the heart detection and evaluation method program is executed by the processor, the following steps are also implemented: Based on the preset acquisition module, the patient’s physiological information is collected and converted into electrical signals which are input into the preset ECG monitoring module for monitoring; Monitor the patient’s blood pressure based on the blood pressure monitoring unit in the ECG monitoring module to identify abnormal blood pressure data; Monitor the patient’s blood oxygen based on the blood oxygen monitoring unit in the ECG monitoring module to identify abnormal blood oxygen data; Monitor the patient's ECG based on the ST segment ECG monitoring unit in the ECG monitoring module to identify abnormal data of the ECG low-frequency components; The heart rate monitoring unit in the ECG monitoring module monitors the patient's heart rate to identify abnormal heart rate data. The cardiac detection and evaluation system according to claim 4 is characterized in that when the cardiac detection and evaluation method program is executed by the processor, the following steps are also implemented: Identify the area decrease value of the amplitude reduction region, and output an alarm reminder when the area decrease value exceeds a preset decrease threshold. A computer-readable storage medium, characterized in that the computer-readable storage medium includes a heart detection and evaluation method program, and when the heart detection and evaluation method program is executed by a processor, the steps of a heart detection and evaluation method as described in any one of claims 1 to 3 are implemented. A cardiac detection and evaluation device, the device implementing a cardiac detection and evaluation method as described in any one of claims 1 to 3, characterized in that it comprises: A high-frequency QRS ECG analysis module, an ECG monitoring module wirelessly connected to the high-frequency QRS ECG analysis module, and an acquisition module wirelessly connected to the ECG monitoring module, wherein: The acquisition module includes a number of sensors for collecting the patient’s physiological information and converting it into electrical signals for input into the ECG monitoring module; The ECG monitoring module includes a blood pressure monitoring unit, a heart rate monitoring unit, a blood oxygen monitoring unit and an ST segment ECG monitoring unit, which are used to monitor the vital signs of different patients based on the electrical signals input by the acquisition module; The high-frequency QRS ECG analysis module is used to analyze the monitoring data input by the ECG monitoring module to output an alarm reminder.