CN116196013B - Electrocardiogram data processing method, device, computer equipment and storage medium - Google Patents
Electrocardiogram data processing method, device, computer equipment and storage medium Download PDFInfo
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- CN116196013B CN116196013B CN202310451338.8A CN202310451338A CN116196013B CN 116196013 B CN116196013 B CN 116196013B CN 202310451338 A CN202310451338 A CN 202310451338A CN 116196013 B CN116196013 B CN 116196013B
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Abstract
The application relates to an electrocardio data processing method, an electrocardio data processing device, computer equipment and a storage medium. The method comprises the following steps: acquiring a high-frequency QRS envelope curve in a resting state; determining the number of target leads and the number of positive leads according to the high-frequency QRS envelope curve; the target number of leads is the number of leads with the corresponding wave peaks exceeding a first threshold and the corresponding lead positive index indicating positive; the number of positive leads is the number of leads indicated as positive by the corresponding lead positive index; if the number of the target leads exceeds a second threshold, determining a type index according to the number of the positive leads; determining corresponding reference characteristics according to the type index according to the high-frequency QRS envelope curve; and determining a target risk assessment level according to the reference characteristics. The method can accurately and efficiently evaluate the risk of myocarditis in a noninvasive manner for reference by doctors, so that the doctors can efficiently and accurately identify the heart health condition of the testee by combining clinical symptoms.
Description
Technical Field
The present application relates to the field of electrocardiographic data processing technology, and in particular, to an electrocardiographic data processing method, an electrocardiographic data processing device, a computer device, and a storage medium.
Background
With the continuous improvement of living standard and the continuous increase of working pressure, the exercise time of people is continuously reduced, so that cardiovascular diseases (such as myocarditis/myocardial injury and the like) are increasingly younger and more generalized.
Currently, an invasive method such as a subendocardial myocardial biopsy is generally used to perform myocarditis risk assessment, but the invasive assessment method may have a more or less influence on the physical health of a subject.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an electrocardiographic data processing method, apparatus, computer device, and storage medium capable of accurately and efficiently assessing risk of myocarditis in a noninvasive manner.
A method of electrocardiographic data processing, the method comprising:
acquiring a high-frequency QRS envelope curve in a resting state;
determining a target lead number and a positive lead number according to the high-frequency QRS envelope curve; the target number of leads is the number of leads with the corresponding wave peaks exceeding a first threshold and the corresponding lead positive index indicating positive; the number of the positive leads is the number of leads indicated as positive by the positive index of the corresponding leads;
if the target lead number exceeds a second threshold, determining a type index according to the positive lead number;
Determining corresponding reference characteristics according to the type index according to the high-frequency QRS envelope curve;
and determining a target risk assessment grade according to the reference characteristics.
In one embodiment, if the type index is a first type index, the reference feature corresponding to the type index includes a target frequency morphology index; the determining corresponding reference features according to the type index according to the high-frequency QRS envelope curve comprises the following steps:
determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; a high frequency morphology index corresponding to each of the leads is determined based on the high frequency QRS envelope curve.
In one embodiment, if the type index is a second type index, the reference features corresponding to the type index include a target frequency morphology index and a limb lead average peak voltage; the determining corresponding reference features according to the type index according to the high-frequency QRS envelope curve comprises the following steps:
determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high-frequency morphological index corresponding to each lead is determined based on the high-frequency QRS envelope curve;
determining peak voltages of all limb leads according to the high-frequency QRS envelope curve; the leads include the limb lead and a chest lead;
And averaging the peak voltages of the limb leads to obtain the average peak voltage of the limb leads.
In one embodiment, if the type index is a third type index, the reference features corresponding to the type index include QRS time limit, target high-frequency morphology index, average peak voltage of limb leads and high-frequency morphology index corresponding to each lead; the determining corresponding reference features according to the type index according to the high-frequency QRS envelope curve comprises the following steps:
determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high-frequency morphological index corresponding to each lead is determined based on the high-frequency QRS envelope curve;
determining the peak voltage of the QRS time limit and each limb lead according to the high-frequency QRS envelope curve; the leads include the limb lead and a chest lead;
and averaging the peak voltages of the limb leads to obtain the average peak voltage of the limb leads.
In one embodiment, the determining the target risk assessment level according to the reference feature includes:
determining the scores of the corresponding leads according to the high-frequency morphological indexes, determining weights according to the QRS time limit, and obtaining risk assessment scores according to the scores of the leads and the weights;
And obtaining a target risk assessment grade according to the target high-frequency morphological index, the average peak voltage of the limb leads and the risk assessment score.
In one embodiment, the method further comprises:
acquiring low-frequency electrocardiograph data;
analyzing the low-frequency electrocardio data to obtain ST segment characteristics;
the determining a target risk assessment level according to the reference features comprises the following steps:
and determining a corresponding target risk assessment grade according to the reference characteristic and the ST segment characteristic.
In one embodiment, the method further comprises:
and determining a corresponding attention level according to the target risk assessment level and the type index.
An electrocardiographic data processing device, the device comprising:
the acquisition module is used for acquiring a high-frequency QRS envelope curve in a resting state;
the index determining module is used for determining the number of target leads and the number of positive leads according to the high-frequency QRS envelope curve; the target number of leads is the number of leads with the corresponding wave peaks exceeding a first threshold and the corresponding lead positive index indicating positive; the number of the positive leads is the number of leads indicated as positive by the positive index of the corresponding leads;
the type determining module is used for determining a type index according to the number of the positive leads if the number of the target leads exceeds a second threshold value;
The index determining module is further used for determining corresponding reference characteristics according to the high-frequency QRS envelope curve and the type index;
and the evaluation module is used for determining a target risk evaluation grade according to the reference characteristics.
A computer device comprising a memory having a computer program stored therein and a processor that when executing the computer program performs the steps of the method embodiments.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs steps in various method embodiments.
According to the electrocardio data processing method, the electrocardio data processing device, the computer equipment and the storage medium, the target lead number for evaluating whether myocarditis is likely or not is obtained through analyzing the high-frequency QRS envelope curve in the resting state, the type index for distinguishing the type of myocarditis is obtained under the condition that the myocarditis is likely, the high-frequency QRS envelope curve is subjected to data processing according to the type index to obtain corresponding reference characteristics, and the reference index is subjected to evaluation analysis to obtain the target risk evaluation grade for representing the risk of myocarditis, so that the myocarditis risk can be accurately and efficiently evaluated in a noninvasive mode for reference by doctors, and the doctor can conveniently and efficiently and accurately identify the heart health condition of a testee by combining clinical symptoms.
Drawings
FIG. 1 is a flow diagram of a method of processing electrical data in a center, according to one embodiment;
fig. 2 is a schematic representation of a high frequency QRS envelope curve in one embodiment;
FIG. 3 is a flow chart of a method of processing electrical data in a center according to another embodiment;
FIG. 4 is a block diagram of the structure of a central electronic data processing device according to one embodiment;
fig. 5 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The electrocardio data processing method provided by the application can be applied to a terminal, a server and an interactive system comprising the terminal and the server, and is realized through the interaction between the terminal and the server, and is not particularly limited. The terminal may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, electrocardiograph monitoring devices and portable wearable devices, and the server may be implemented by a separate server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 1, there is provided an electrocardiographic data processing method, which is applied to a server, for example, and specifically includes the following steps:
s102, acquiring a high-frequency QRS envelope curve in a resting state.
Specifically, electrocardiographic data acquired in a resting electrocardiographic detection process is acquired and used as resting electrocardiographic data, wherein a detected person is in a resting state in the resting electrocardiographic detection process. And processing the resting electrocardiograph data to obtain a high-frequency QRS envelope curve of the testee in a resting state. It is understood that the rest electrocardiographic data of each lead is respectively processed to obtain a corresponding high-frequency QRS envelope curve.
In one embodiment, the resting electrocardiographic data comprises a plurality of QRS complexes. And sequentially aligning, averaging and high-frequency filtering the QRS complex in the resting electrocardio data to obtain a high-frequency QRS envelope curve. It is understood that the high frequency QRS envelope curve corresponds to high frequency QRS complex data, based on which a corresponding high frequency QRS envelope curve can be formed. In one or more embodiments of the present application, acquiring the high-frequency QRS envelope curve may be understood as acquiring high-frequency QRS complex data for forming the high-frequency QRS envelope curve, specifically, sequentially performing alignment, averaging, and high-frequency filtering on QRS complexes in resting electrocardiographic data, to obtain high-frequency QRS complex data for forming a corresponding high-frequency QRS envelope curve. It can be understood that the QRS complex in the resting electrocardiograph data may be sequentially subjected to high-frequency filtering, alignment and averaging to obtain a high-frequency QRS envelope curve, or the high-frequency electrocardiograph data may be extracted from the resting electrocardiograph data, and the QRS complex in the high-frequency electrocardiograph data may be sequentially subjected to alignment and averaging to obtain a high-frequency QRS envelope curve, which is not particularly limited herein.
S104, determining the number of target leads and the number of positive leads according to the high-frequency QRS envelope curve; the target number of leads is the number of leads with the corresponding wave peaks exceeding a first threshold and the corresponding lead positive index indicating positive; the number of positive leads is the number of leads indicated as positive by the corresponding lead positive index.
Wherein the number of peaks refers to the total number of peaks on the high frequency QRS envelope curve. The number of peaks on the high frequency QRS envelope curve is correlated with the myocardial cell viability corresponding to the respective leads, and the number of peaks exceeds a first threshold value, representing a decrease in the viability of the respective myocardial cells. It will be appreciated that the number of peaks on the high frequency QRS envelope curve may be determined in particular by means provided in the art and is not specifically limited herein. The first threshold may be customized according to actual requirements, such as 3.
Specifically, the high-frequency QRS envelope curve corresponding to each lead is analyzed, the number of target leads is obtained by screening and counting the leads with the corresponding wave peaks exceeding a first threshold and the positive indexes indicated as positive by the corresponding leads, and the number of positive leads is obtained by screening and counting the leads with the positive indexes indicated as positive.
In one embodiment, the corresponding number of peaks and lead positive indicators are determined from the high frequency QRS envelope curve for each lead, so that the target number of leads and the number of positive leads are determined from the corresponding number of peaks and lead positive indicators for each lead.
In one embodiment, a respective lead positive indicator is determined from the high frequency QRS envelope curve of each lead in order to screen for leads for which the lead positive indicator indicates positive, and the number of positive leads is determined, and a respective peak number is determined from the high frequency QRS envelope curve of each lead screened in order to further determine the target number of leads.
In one embodiment, the high frequency QRS envelope curve of each lead is analyzed to obtain the total area of each amplitude reduction region on the high frequency QRS envelope curve as a first total area, the total area below the high frequency QRS envelope curve as a second total area, and the ratio of the first total area to the second total area is taken as the high frequency morphology index of the corresponding lead. Further, if the high-frequency morphological index corresponding to the lead is greater than or equal to a target threshold value, representing the possibility of myocardial ischemia, determining the lead positive index corresponding to the lead as positive, otherwise, determining the corresponding lead positive index as negative. The target threshold may be defined according to the actual situation, for example, 8%, or may be dynamically determined according to the age of the testee, for example, if the age of the testee is greater than 50 years old, the target threshold may be but not limited to 8%, if the age of the testee is less than or equal to 50 years old, the target threshold may be but not limited to 15%, or may be dynamically determined by statistically analyzing the high-frequency morphology indexes of a plurality of testees, for example, the high-frequency morphology indexes of each testee are sorted from large to small, the high-frequency morphology indexes of the first three are averaged to obtain a high-frequency morphology index average value, and then the high-frequency morphology index average values of a plurality of testees are averaged to obtain the target threshold. It is to be understood that the setting manner of the target threshold is not particularly limited herein.
And S106, if the target lead number exceeds a second threshold, determining a type index according to the positive lead number.
The second threshold may be customized according to practical situations, for example, 2, which is not specifically limited herein. The type index is used to distinguish between myocarditis types and can be understood as myocarditis type indexes including, but not limited to, a first type index, a second type index and a third type index, wherein the first type index is used for representing acute myocarditis, the second type index is used for representing chronic myocarditis, and the third type index is used for representing fulminant myocarditis.
Specifically, the target lead number can be used to evaluate the likelihood of myocarditis, and if the target lead number is greater than or equal to the second threshold value, to characterize the likelihood of myocarditis in the corresponding subject, the type indicator is determined according to the positive lead number, that is, the myocarditis is shaped according to the positive lead number, so as to determine the target risk evaluation level of myocarditis according to the reference feature corresponding to the type indicator.
In one embodiment, if the target number of leads is greater than or equal to the second threshold, the number of positive leads is compared with each preset number interval, respectively, to determine the corresponding type indicator. If the number of positive leads belongs to the first number interval, the corresponding type index is determined as the first type index, if the number of positive leads belongs to the second number interval, the corresponding type index is determined as the second type index, and if the number of positive leads belongs to the third number interval, the corresponding type index is determined as the third type index. The preset number interval comprises a first number interval, a second number interval and a third number interval, the upper limit of the first number interval is smaller than the lower limit of the second number interval, and the upper limit of the second number interval is smaller than the lower limit of the third number interval. It can be understood that the division of each preset number interval can be determined according to practical situations, for example, the first number interval is [0,3], the second number interval is [4,5], the third number interval is [6 ], the total number of leads is the total number of leads used for acquiring electrocardiographic data in the resting electrocardiographic detection process, and the total number of leads can be dynamically determined according to practical requirements.
S108, corresponding reference characteristics are determined according to the type index according to the high-frequency QRS envelope curve.
Specifically, each type index corresponds to a corresponding reference feature, and after the type index is determined, the reference feature corresponding to the type index is determined according to the high-frequency QRS envelope curve.
In one embodiment, the reference features corresponding to the first type of index include, but are not limited to, a target frequency morphology index, the reference features corresponding to the second type of index include, but are not limited to, a target frequency morphology index and limb lead average peak voltage, and the reference features corresponding to the third type of index include, but are not limited to, a target frequency morphology index, limb lead average peak voltage, QRS time limit, and high frequency morphology index corresponding to each lead.
S110, determining a target risk assessment level according to the reference characteristics.
Specifically, the target risk assessment level is used for representing the size of the risk of the occurrence of the myocarditis, for example, the higher the target risk assessment level is, the larger the risk of the occurrence of the myocarditis can be represented, so that a doctor can refer to the risk in the diagnosis process, and the doctor can conveniently and accurately identify the heart health condition of the testee in combination with clinical symptoms, so that further diagnosis and treatment or detection reference suggestions are given. It can be appreciated that when outputting the target risk assessment level, at least one of the type index and/or the reference feature corresponding to the type index can also be output for reference by the doctor, so that the doctor can more efficiently and accurately identify the heart health condition of the testee.
In one embodiment, the level of interest is determined based on the target risk assessment level and the corresponding type indicator. The attention level represents the difference of attention degree for doctors to refer to, so that the doctors can accurately identify the heart health condition according to the attention level and clinical symptoms, and accordingly diagnosis and treatment reference suggestions are given.
According to the electrocardio data processing method, the target lead number for evaluating whether myocarditis is likely is obtained by analyzing the high-frequency QRS envelope curve in the resting state, the type index for distinguishing the myocarditis type is obtained under the condition that the myocarditis is likely, the corresponding reference characteristic is obtained by carrying out data processing on the high-frequency QRS envelope curve according to the type index, and the target risk evaluation grade for representing the myocarditis risk is obtained by evaluating and analyzing the reference index, so that the myocarditis risk can be accurately and efficiently evaluated in a noninvasive mode for reference by doctors, and the doctor can conveniently and efficiently and accurately identify the heart health condition of a testee by combining clinical symptoms.
In one embodiment, if the type indicator is a first type indicator, the reference feature corresponding to the type indicator includes a target frequency morphology index; s108 includes: determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high frequency morphology index corresponding to each lead is determined based on the high frequency QRS envelope curve.
Wherein the target high frequency morphology index may be used to characterize the extent of myocardial damage, e.g., a greater target high frequency morphology index may indicate a greater extent of myocardial damage. Specifically, if the type index is determined to be the first type index according to the number of the positive leads, and the possibility of existence of acute myocarditis is represented, comparing the high-frequency morphology indexes corresponding to the leads, taking the maximum value of the screened high-frequency morphology indexes as a target frequency morphology index, or screening three high-frequency morphology indexes before sorting under the condition that the high-frequency morphology indexes of the leads are sorted in a large-to-small mode, taking the average value of the three screened high-frequency morphology indexes as the target frequency morphology index, so as to determine the target risk assessment grade according to the target frequency morphology index. It can be understood that in this embodiment, the corresponding high-frequency morphology index may be recalculated according to the high-frequency QRS envelope curve of each lead, or the high-frequency morphology index determined for each lead in the process of determining the lead positive index of each lead may be directly obtained, which is not particularly limited.
In one embodiment, if the type indicator is the first type indicator, the target high frequency morphology index is in positive correlation with the target risk assessment level, e.g., the greater the target high frequency morphology index, the higher the corresponding target risk assessment level. The target risk assessment level corresponds to the first preset index intervals, and the target high-frequency morphological index is matched with each first preset index interval to determine the target risk assessment level. Each first preset index interval can be specifically defined according to actual conditions. For example, assume that the target risk assessment level includes a first level, a second level, a third level, and a fourth level that are sequentially increased, and the first preset index intervals corresponding to the four levels are [ target threshold, 24.9% ], [25%,34.9% ], [35%,39.9% ], and [40%,100% ], where the target threshold is a target threshold for determining the lead positive index in each embodiment, and the target threshold is 15% for example, and the target risk assessment level is determined as the first level if the target frequency morphology index is [15%,24.9% ], and so on.
In the above embodiment, if the type index is the first type index, that is, if the subject has the possibility of acute myocarditis, the target risk assessment level for representing the risk of occurrence of myocarditis of the subject is rapidly and accurately determined according to the high-frequency morphological indexes corresponding to the leads, so as to be referred by a doctor, so that the doctor can accurately identify the heart health condition of the subject in combination with clinical symptoms.
In one embodiment, if the type indicator is a second type indicator, the reference features corresponding to the type indicator include a target frequency morphology index and a limb lead average peak voltage; s108 includes: determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high-frequency morphological indexes corresponding to the leads are determined based on a high-frequency QRS envelope curve; determining peak voltage of each limb lead according to the high-frequency QRS envelope curve; the leads include limb leads and chest leads; and averaging the peak voltages of the limb leads to obtain the average peak voltage of the limb leads.
Wherein, the average peak voltage of the limb leads is related to the heart contraction function and the blood pumping capacity, and specifically has positive correlation relation, and the larger the average peak voltage of the limb leads is, the stronger the heart contraction function and the blood pumping capacity are. Leads, i.e., electrocardiogram leads, include limb leads and chest leads.
Specifically, if the type index is determined to be the second type index according to the number of the positive leads, and the possibility of the chronic myocarditis is represented, the target frequency morphology index is determined according to the high frequency morphology index corresponding to each lead, the corresponding peak voltage is determined according to the high frequency QRS envelope curve of each limb lead, the average peak voltage of each limb lead is obtained by averaging the peak voltages of each limb lead, and the target risk assessment grade is determined according to the target frequency morphology index and the average peak voltage of each limb lead. It can be appreciated that the process flow of determining the target frequency morphology index according to the high frequency morphology index of each lead may refer to the corresponding process flow in each embodiment, and will not be described herein.
In one embodiment, if the type indicator is the second type indicator, the target risk assessment level is in positive correlation with the target high-frequency morphology index and in negative correlation with the average peak voltage of the limb leads, e.g., the smaller the average peak voltage of the limb leads, the greater the target high-frequency morphology index, the higher the corresponding target risk assessment level. And determining a target risk assessment grade by matching the target high-frequency morphological index with each first preset index interval and matching the average peak voltage of the limb leads with each preset voltage interval. Each preset voltage interval can be specifically defined according to actual conditions.
In one embodiment, a first risk assessment level is determined based on the target frequency morphology index, a second risk assessment level is determined based on the average peak voltage of the limb leads, and a target risk assessment level is determined based on the first risk assessment level and the second risk assessment level. When determining the target risk assessment grade, the average peak voltage of the limb leads can be used as a main reference characteristic, and the target high-frequency morphological index is used as an auxiliary reference characteristic. Taking the example that the first risk assessment level and the second risk assessment level comprise four levels, if the first risk assessment level and the second risk assessment level are both the first level, determining the target risk assessment level as the first level, if the first risk assessment level is the second level and the second risk assessment level is the first level, determining the target risk assessment level as the second level, if the first risk assessment level is the first level and the second risk assessment level is the second level, determining the target risk assessment level as the fifth level, and the like.
The process flow of determining the first risk assessment level according to the target frequency morphology index is not described herein again, and when the specific reference type index is the first type index, the process flow of determining the target risk assessment level based on the target frequency morphology index in each embodiment is described herein. The average peak voltage of the limb leads is inversely related to the second risk assessment level, e.g., the smaller the average peak voltage of the limb leads, the higher the second risk assessment level. The second risk assessment level corresponds to a preset voltage interval, and the average peak voltage of the limb leads is matched with each preset voltage interval to determine the second risk assessment level.
For example, assuming that the second risk assessment level includes a first level, a second level, a third level, and a fourth level that are sequentially increased, the preset voltage intervals corresponding to the four levels are sequentially greater than or equal to 5.1, [4.1,5], [3.1,4] and [0,3], the unit is uv (microvolts), if the average peak voltage of the limb leads is greater than or equal to 5.1, the second risk assessment level is determined as the first level, and so on.
In the above embodiment, if the type index is the second type index, that is, if the subject has a possibility of chronic myocarditis, the target risk assessment level for representing the risk of occurrence of myocarditis of the subject is rapidly and accurately determined according to the high-frequency morphological index corresponding to each lead and the average value of the peak voltages of each limb lead, so as to be referred by a doctor, so that the doctor can accurately identify the heart health condition of the subject in combination with clinical symptoms.
In one embodiment, if the type index is a third type index, the reference features corresponding to the type index include QRS time limit, target high frequency morphology index, average peak voltage of limb leads and high frequency morphology index corresponding to each lead; s108 includes: determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high-frequency morphological indexes corresponding to the leads are determined based on a high-frequency QRS envelope curve; determining the peak voltage of the QRS time limit and each limb lead according to the high-frequency QRS envelope curve; the leads include limb leads and chest leads; and averaging the peak voltages of the limb leads to obtain the average peak voltage of the limb leads.
Wherein the QRS time period is the duration from the start of the QRS complex to the end of the QRS complex, and the prolongation of the QRS time period is related to conduction block. If there is a likelihood of myocarditis, the QRS time limit is associated with the risk of myocarditis, specifically in a positive correlation, for example, the wider the QRS time limit, the higher the risk of myocarditis is characterized. Specifically, if the type index is determined to be a third type index according to the number of positive leads, and the possibility of the occurrence of the fulminant myocarditis is represented, the target frequency morphology index is determined according to the high frequency morphology index corresponding to each lead, the corresponding peak voltage is determined according to the high frequency QRS envelope curve of each limb lead, the average peak voltage of each limb lead is obtained by averaging the peak voltages of each limb lead, and the QRS time limit is determined according to the high frequency QRS envelope curve of each lead, so that the target risk assessment grade is determined according to the target frequency morphology index, the average peak voltage of each limb lead, the QRS time limit and the high frequency morphology index of each lead. It can be appreciated that the process flow of determining the target frequency morphology index according to the high frequency morphology index of each lead may refer to the corresponding process flow in each embodiment, and will not be described herein.
In one embodiment, if the type indicator is a third type indicator, a risk assessment score is determined according to the QRS time limit and the high frequency morphology index of each lead, so as to determine a target risk assessment level according to the target frequency morphology index, the average peak voltage of the limb leads, and the risk assessment score. Wherein the risk assessment score is related to cardiac performance grading, the higher the risk assessment score, the higher the level of the corresponding cardiac performance grading, the more the performance of the characterized heart decreases.
In one embodiment, if the type indicator is a third type indicator, the target risk assessment level is in positive correlation with the target high-frequency morphology index, in negative correlation with the average peak voltage of the limb leads, and in positive correlation with the risk assessment score, e.g., the smaller the average peak voltage of the limb leads, the greater the target high-frequency morphology index, and the higher the risk assessment score, the higher the corresponding target risk assessment level. The target high-frequency morphological indexes are matched with all the first preset index intervals, average peak voltage of limb leads is matched with all the preset voltage intervals, and risk assessment scores are matched with all the preset score intervals, so that the target risk assessment grade is determined. Each preset fraction interval can be specifically defined according to actual conditions.
In one embodiment, a first risk assessment level is obtained according to the target frequency morphology index, a second risk assessment level is obtained according to the average peak voltage of the limb leads, a third risk assessment level is obtained according to the risk assessment score, and a target risk assessment level is obtained according to the first risk assessment level, the second risk assessment level and the third risk assessment level. When determining the target risk assessment grade, the risk assessment score can be used as a main reference feature, and the average peak voltage of the limb leads and the target high-frequency morphology index are used as auxiliary reference features, wherein the reference priority of the average peak voltage of the limb leads is higher than the reference priority of the target high-frequency morphology index. Taking the first risk assessment level, the second risk assessment level and the third risk assessment level as examples, if the first risk assessment level, the second risk assessment level and the third risk assessment level are all the first level, the target risk assessment level is determined to be the first level, if the first risk assessment level is the second level, the second risk assessment level is the first level, and the third risk assessment level is the first level, the target risk assessment level is determined to be the second level, if the first risk assessment level is the first level, and the second risk assessment level is the second level, the third risk assessment level is the first level, the target risk assessment level is determined to be the fifth level, and so on.
The process flow of determining the first risk assessment level according to the target frequency morphology index and determining the second risk assessment level according to the average peak voltage of the limb leads may refer to the corresponding process flow in each embodiment, and will not be described herein. The risk assessment score is positively correlated with the third risk assessment level, e.g., the higher the risk assessment score, the higher the third risk assessment level. The third risk assessment level corresponds to the preset score intervals, and the third risk assessment level is determined by matching the risk assessment score with each preset score interval.
For example, assume that the third risk assessment level includes a first level, a second level, a third level, and a fourth level that are sequentially increased, the predetermined score intervals corresponding to the four levels are sequentially [0, 15], [16, 30], [31, 40] and [41, 100], and if the risk assessment score is [0, 15], the third risk assessment level is determined as the first level, and so on.
In one embodiment, the QRS time limit may be determined according to the high frequency QRS envelope curve of any lead, or the average value of the QRS time limit corresponding to each lead may be used as the QRS time limit for determining the target risk assessment level, or the QRS time limit may be determined according to the low frequency electrocardiographic data in the resting electrocardiographic data, which is not limited herein.
In the above embodiment, if the type index is the third type index, that is, if the subject has a possibility of developing myocarditis, the target risk assessment level for representing the risk of developing myocarditis of the subject is rapidly and accurately determined according to the high-frequency morphological index corresponding to each lead, the average value of the peak voltage of each limb lead, the QRS time limit and the high-frequency morphological index of each lead, so as to be referred by a doctor, so that the doctor can accurately identify the heart health condition of the subject in combination with clinical symptoms.
In one embodiment, S110 includes: determining the scores of the corresponding leads according to the high-frequency morphological indexes, determining weights according to the QRS time limit, and obtaining risk assessment scores according to the scores and the weights of the leads; and obtaining a target risk assessment grade according to the target frequency morphology index, the average peak voltage of the limb leads and the risk assessment score.
Specifically, the high-frequency morphological index of each lead is matched with each second preset index interval to determine the score of the corresponding lead, the QRS time limit is matched with each preset time limit interval to determine the weight, the scores of the leads are summed, and the product of the sum value of the scores of the leads and the weight is used as a risk assessment score so as to obtain a target risk assessment grade according to the target high-frequency morphological index, the average peak voltage of the limb leads and the risk assessment score. Wherein, each second preset index interval is associated with a score, and each preset time limit interval is associated with a weight.
For example, the second preset index interval includes [10%,19.9% ], 20%,29.9% ], 30%,39.9% ], 40%,49.9% ] and 50%,100% ], the respective scores of the five intervals are 1,2,3,4 and 5, respectively, and if the high frequency morphology index is at [10%,19.9% ], the score of the corresponding lead is 1, and so on. It will be appreciated that in this example, if the high frequency morphology index is less than 10%, the score of the corresponding lead is 0. The preset time limit intervals comprise [0, 119], [120, 149], and 150 or more, wherein the unit is ms (millisecond), and weights corresponding to the three preset time limit intervals are respectively 1, 1.25 and 1.5.
In the above embodiment, the risk assessment score is determined based on the score determined by the high frequency morphology index of each lead and the weight determined by the QRS time limit, so that the target risk assessment level is quickly and accurately determined by combining the target frequency morphology index with the average peak voltage of the limb leads.
In one embodiment, the electrocardiographic data processing method further includes: acquiring low-frequency electrocardiograph data; analyzing the low-frequency electrocardio data to obtain ST segment characteristics; s110 includes: and determining a corresponding target risk assessment grade according to the reference characteristics and the ST segment characteristics.
The ST segment features comprise types of ST segments, the ST segments refer to wave bands from the end point of a QRS complex to the beginning point of a T wave in low-frequency electrocardio data, and the types of the ST segments comprise positive, suspected positive and negative. Specifically, low-frequency electrocardiographic data are acquired, ST segments are extracted from the low-frequency electrocardiographic data, the extracted ST segments are analyzed to obtain corresponding ST segment characteristics, and a target risk assessment grade is determined by combining reference characteristics determined according to type indexes.
It will be appreciated that the ST segment may be analyzed to obtain corresponding ST segment characteristics with reference to the prior art, and will not be described in detail herein. For example, the ST segment feature is determined to be suspected positive if any of three conditions occur, including: the ST segment horizontal or downward inclined pressure is greater than or equal to 0.1mV, and the duration is less than 2 minutes; ST segment horizontal or downward inclined pressure is greater than or equal to 0.05 to 0.1mV; the ST segment is lowered by 0.10-0.20mV like a horizontal type.
In one embodiment, in embodiments where the target risk assessment level is determined from the reference features, the target risk assessment level is further determined in conjunction with the ST segment features. It will be appreciated that, for the same reference feature, the target risk assessment level corresponding to the ST segment feature being positive is higher than the target risk assessment level corresponding to the ST segment feature being suspected positive, and the target risk assessment level corresponding to the ST segment feature being suspected positive is higher than the target risk assessment level corresponding to the ST segment feature being negative, and specific examples of determining the target risk assessment level in combination with the reference feature and the ST segment feature are not illustrated herein.
In one embodiment, the low frequency electrocardiographic data may be acquired during a resting electrocardiographic detection process. The rest electrocardio data acquired in the rest electrocardio detection process comprise high-frequency electrocardio data and low-frequency electrocardio data, and the high-frequency electrocardio data and the low-frequency electrocardio data can be extracted from the rest electrocardio data by analyzing the rest electrocardio data.
In the above embodiment, the objective risk assessment level is determined by combining the ST segment characteristics obtained by low-frequency electrocardiographic data analysis, so that the accuracy of myocarditis risk assessment can be improved.
In one embodiment, determining the target number of leads from the high frequency QRS envelope curve includes: screening leads with positive indexes indicated as positive according to the high-frequency QRS envelope curve; the total number of leads whose corresponding peaks exceed a first threshold is determined as a target number of leads.
Specifically, a high-frequency morphological index of a corresponding lead is determined according to a high-frequency QRS envelope curve, a lead positive index of the corresponding lead is determined according to the high-frequency morphological index, leads with positive indexes indicated as positive are screened from the leads, the high-frequency QRS envelope curve of each screened lead is analyzed to obtain a corresponding peak number, the leads with the peak number larger than or equal to a first threshold value are further screened from the screened leads, and the total number of the further screened leads is determined as a target lead number.
In one embodiment, the electrocardiographic data processing method further includes: and determining a corresponding attention level according to the target risk assessment level and the type index.
Specifically, after determining the target risk assessment level according to the process flow in the embodiments, the attention level is also determined in combination with the corresponding type index for reference by the doctor. In one embodiment, the type index is used as a main material, the target risk assessment level is used as an auxiliary material to determine the attention level, specifically, the attention level corresponding to the third type index is higher than the attention level corresponding to the second type index, the attention level corresponding to the second type index is higher than the attention level corresponding to the first type index, and for the same type index, the attention level is determined based on the target risk assessment level, wherein the higher the target risk assessment level is, the higher the attention level is. Taking the example that the target risk assessment level includes four levels, if the type index is a third type index and the target risk assessment level is a fourth level, the attention level is determined to be a first attention level, if the type index is a third type index and the target risk assessment level is a first level, the attention level is determined to be a fourth attention level, and if the type index is a second type index and the target risk assessment level is a fourth level, the attention level is determined to be a fifth attention level, so that the description is omitted.
As shown in fig. 2, a schematic representation of a high frequency QRS envelope curve is provided in one embodiment. Fig. 2 illustrates a high frequency QRS envelope curve corresponding to limb lead iii, with time (t) on the abscissa, voltage (U) on the ordinate, and uv (microvolts) on the ordinate, wherein the high frequency QRS envelope curve corresponds to a peak number of 3, and a corresponds to a peak point in the high frequency QRS envelope curve, the voltage corresponding to the peak point is the peak voltage corresponding to limb lead iii, and the high frequency morphology index corresponding to limb lead iii is 12.6%. It is to be understood that fig. 2 is by way of example only and is not intended to be limiting in any way.
As shown in fig. 3, in one embodiment, there is provided an electrocardiographic data processing method, specifically including the following steps:
s302, acquiring a high-frequency QRS envelope curve in a resting state.
S304, determining the number of target leads and the number of positive leads according to a high-frequency QRS envelope curve; the target number of leads is the number of leads with the corresponding wave peaks exceeding a first threshold and the corresponding lead positive index indicating positive; the number of positive leads is the number of leads indicated as positive by the corresponding lead positive index.
S306, if the target lead number exceeds the second threshold, determining a type index according to the positive lead number.
S308, if the type index is the first type index, determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high frequency morphology index corresponding to each lead is determined based on the high frequency QRS envelope curve.
S310, determining a target risk assessment grade according to the target frequency morphology index.
S312, if the type index is the second type index, determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high frequency morphology index corresponding to each lead is determined based on the high frequency QRS envelope curve.
S314, determining peak voltages of all limb leads according to the high-frequency QRS envelope curve; the leads include limb leads and chest leads.
S316, the peak voltage of each limb lead is averaged to obtain the average peak voltage of the limb lead.
And S318, determining a target risk assessment grade according to the target frequency morphology index and the average peak voltage of the limb leads.
S320, if the type index is a third type index, determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high frequency morphology index corresponding to each lead is determined based on the high frequency QRS envelope curve.
S322, determining the peak voltage of the QRS time limit and each limb lead according to the high-frequency QRS envelope curve; the leads include limb leads and chest leads.
S324, the peak voltage of each limb lead is averaged to obtain the average peak voltage of the limb lead.
S326, determining the scores of the corresponding leads according to the high-frequency morphological indexes, determining weights according to the QRS time limit, and obtaining risk assessment scores according to the scores and the weights of the leads.
And S328, obtaining a target risk assessment grade according to the target frequency morphology index, the average peak voltage of the limb leads and the risk assessment score.
In the above embodiment, whether the myocarditis is likely to exist is estimated according to the number of the target leads, and in the case that the myocarditis is likely to exist is determined, a type index for distinguishing the type of myocarditis is determined according to the number of the positive leads, and corresponding reference characteristics are determined according to the type index, so that the risk of myocarditis is rapidly and accurately estimated according to the reference characteristics, and a corresponding target risk assessment grade is obtained for a doctor to refer to, so that the doctor can accurately identify the heart health condition of the testee in combination with clinical symptoms.
It should be understood that, although the steps in the flowcharts of fig. 1 and 3 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least a portion of the steps in fig. 1 and 3 may include a plurality of steps or stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the execution of the steps or stages is not necessarily sequential, but may be performed in turn or alternately with at least a portion of the steps or stages in other steps or other steps.
In one embodiment, as shown in FIG. 4, there is provided an electrocardiographic data processing apparatus 400 comprising: an acquisition module 401, an index determination module 402, a type determination module 403, and an evaluation module 404, wherein:
the acquiring module 401 is configured to acquire a high-frequency QRS envelope curve in a rest state.
An index determination module 402, configured to determine a target number of leads and a positive number of leads according to the high frequency QRS envelope curve; the target number of leads is the number of leads with the corresponding wave peaks exceeding a first threshold and the corresponding lead positive index indicating positive; the number of positive leads is the number of leads indicated as positive by the corresponding lead positive index.
The type determining module 403 is configured to determine a type indicator according to the number of positive leads if the target number of leads exceeds the second threshold.
The index determination module 402 is further configured to determine a corresponding reference feature according to the type index according to the high frequency QRS envelope curve.
An evaluation module 404 is configured to determine a target risk evaluation level according to the reference feature.
In one embodiment, if the type indicator is a first type indicator, the reference feature corresponding to the type indicator includes a target frequency morphology index; the index determining module 402 is further configured to determine a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high frequency morphology index corresponding to each lead is determined based on the high frequency QRS envelope curve.
In one embodiment, if the type indicator is a second type indicator, the reference features corresponding to the type indicator include a target frequency morphology index and a limb lead average peak voltage; the index determining module 402 is further configured to determine a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high-frequency morphological indexes corresponding to the leads are determined based on a high-frequency QRS envelope curve; determining peak voltage of each limb lead according to the high-frequency QRS envelope curve; the leads include limb leads and chest leads; and averaging the peak voltages of the limb leads to obtain the average peak voltage of the limb leads.
In one embodiment, if the type index is a third type index, the reference features corresponding to the type index include QRS time limit, target high frequency morphology index, average peak voltage of limb leads and high frequency morphology index corresponding to each lead; the index determining module 402 is further configured to determine a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high-frequency morphological indexes corresponding to the leads are determined based on a high-frequency QRS envelope curve; determining the peak voltage of the QRS time limit and each limb lead according to the high-frequency QRS envelope curve; the leads include limb leads and chest leads; and averaging the peak voltages of the limb leads to obtain the average peak voltage of the limb leads.
In one embodiment, the evaluation module 404 is further configured to determine the scores of the corresponding leads according to the high frequency morphology index, determine the weights according to the QRS time limit, and obtain the risk evaluation score according to the scores and weights of the leads; and obtaining a target risk assessment grade according to the target frequency morphology index, the average peak voltage of the limb leads and the risk assessment score.
In one embodiment, the obtaining module 401 is further configured to obtain low-frequency electrocardiographic data; analyzing the low-frequency electrocardio data to obtain ST segment characteristics; the evaluation module 404 is further configured to determine a corresponding target risk evaluation level according to the reference feature and the ST segment feature.
In one embodiment, the index determination module 402 is further configured to screen the leads with positive index indication as positive according to the high frequency QRS envelope curve; the total number of leads whose corresponding peaks exceed a first threshold is determined as a target number of leads.
For specific limitations of the electrocardiographic data processing device, reference may be made to the above limitation of the electrocardiographic data processing method, and no further description is given here. The above-mentioned various modules in the electrocardiographic data processing device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing a high frequency QRS envelope curve. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of processing electrocardiographic data.
It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In an embodiment, there is also provided a computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. A method of electrocardiographic data processing, the method comprising:
acquiring a high-frequency QRS envelope curve in a resting state;
determining a target lead number and a positive lead number according to the high-frequency QRS envelope curve; the target number of leads is the number of leads with the corresponding wave peaks exceeding a first threshold and the corresponding lead positive index indicating positive; the number of the positive leads is the number of leads indicated as positive by the positive index of the corresponding leads;
If the target lead number exceeds a second threshold, determining a type index according to the positive lead number; the type index is used for distinguishing the type of myocarditis;
determining corresponding reference characteristics according to the type index according to the high-frequency QRS envelope curve;
determining a target risk assessment level according to the reference features;
the step of determining the lead positive index comprises the following steps:
analyzing the high-frequency QRS envelope curve of each lead to obtain the total area of each amplitude reduction region on the corresponding high-frequency QRS envelope curve as a first total area, and the total area below the corresponding high-frequency QRS envelope curve as a second total area;
taking the ratio of the first total area to the second total area as a high-frequency morphological index of the corresponding lead;
and determining the lead positive index corresponding to the lead with the corresponding high-frequency morphological index larger than or equal to the target threshold value as positive.
2. The method of claim 1, wherein if the type indicator is a first type indicator, the reference feature corresponding to the type indicator includes a target frequency morphology index; the determining corresponding reference features according to the type index according to the high-frequency QRS envelope curve comprises the following steps:
Determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; a high frequency morphology index corresponding to each of the leads is determined based on the high frequency QRS envelope curve.
3. The method of claim 1, wherein if the type indicator is a second type indicator, the reference feature corresponding to the type indicator includes a target frequency morphology index and a limb lead average peak voltage; the determining corresponding reference features according to the type index according to the high-frequency QRS envelope curve comprises the following steps:
determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high-frequency morphological index corresponding to each lead is determined based on the high-frequency QRS envelope curve;
determining peak voltages of all limb leads according to the high-frequency QRS envelope curve; the leads include the limb lead and a chest lead;
and averaging the peak voltages of the limb leads to obtain the average peak voltage of the limb leads.
4. The method of claim 1, wherein if the type indicator is a third type indicator, the reference features corresponding to the type indicator include QRS time limit, target high frequency morphology index, average peak voltage of limb leads, and high frequency morphology index corresponding to each lead; the determining corresponding reference features according to the type index according to the high-frequency QRS envelope curve comprises the following steps:
Determining a target frequency morphology index according to the high frequency morphology index corresponding to each lead; the high-frequency morphological index corresponding to each lead is determined based on the high-frequency QRS envelope curve;
determining the peak voltage of the QRS time limit and each limb lead according to the high-frequency QRS envelope curve; the leads include the limb lead and a chest lead;
and averaging the peak voltages of the limb leads to obtain the average peak voltage of the limb leads.
5. The method of claim 4, wherein said determining a target risk assessment level from said reference feature comprises:
determining the scores of the corresponding leads according to the high-frequency morphological indexes, determining weights according to the QRS time limit, and obtaining risk assessment scores according to the scores of the leads and the weights;
and obtaining a target risk assessment grade according to the target high-frequency morphological index, the average peak voltage of the limb leads and the risk assessment score.
6. The method according to claim 1, wherein the method further comprises:
acquiring low-frequency electrocardiograph data;
analyzing the low-frequency electrocardio data to obtain ST segment characteristics;
the determining a target risk assessment level according to the reference features comprises the following steps:
And determining a corresponding target risk assessment grade according to the reference characteristic and the ST segment characteristic.
7. The method according to any one of claims 1 to 6, further comprising:
and determining a corresponding attention level according to the target risk assessment level and the type index.
8. An electrocardiographic data processing device, the device comprising:
the acquisition module is used for acquiring a high-frequency QRS envelope curve in a resting state;
the index determining module is used for determining the number of target leads and the number of positive leads according to the high-frequency QRS envelope curve; the target number of leads is the number of leads with the corresponding wave peaks exceeding a first threshold and the corresponding lead positive index indicating positive; the number of the positive leads is the number of leads indicated as positive by the positive index of the corresponding leads;
the type determining module is used for determining a type index according to the number of the positive leads if the number of the target leads exceeds a second threshold value; the type index is used for distinguishing the type of myocarditis;
the index determining module is further used for determining corresponding reference characteristics according to the high-frequency QRS envelope curve and the type index;
The evaluation module is used for determining a target risk evaluation grade according to the reference characteristics;
the index determining module is further used for analyzing the high-frequency QRS envelope curve of each lead to obtain the total area of each amplitude reduction area on the corresponding high-frequency QRS envelope curve as a first total area, and the total area below the corresponding high-frequency QRS envelope curve as a second total area; taking the ratio of the first total area to the second total area as a high-frequency morphological index of the corresponding lead; and determining the lead positive index corresponding to the lead with the corresponding high-frequency morphological index larger than or equal to the target threshold value as positive.
9. A computer device comprising a memory and a processor, the memory having stored therein a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
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