Electrocardiogram data processing method and device, equipment and storage medium

Abstract

The invention relates to the technical field of electrocardio data processing, in particular to an electrocardio data processing method, device and equipment and a storage medium, and the electrocardio data processing method comprises the steps that historical electrocardio data sent by an acquisition terminal within a preset time period is acquired; periodically splitting the historical electrocardio data to obtain multiple groups of electrocardio data; carrying out average calculation on the plurality of groups of electrocardiograph data to obtain electrocardiograph sample data; sending the electrocardio sample data to an acquisition terminal, so that the acquisition terminal determines difference data, different from the electrocardio sample data in waveform, in the to-be-processed electrocardio data according to the electrocardio sample data; the difference data sent by the acquisition terminal and the electrocardiogram sample data are reconstructed, and reconstruction of the electrocardiogram data to be processed is completed. According to the method and the device, the accuracy of the electrocardio data obtained after reconstruction can be improved, so that the probability of remote misdiagnosis of medical staff is effectively reduced.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of electrocardiogram data processing, and in particular, to an electrocardiogram data processing method, device, equipment and storage medium. Background Art

[0002] With the rapid development of 5G (Fifth-generation, fifth-generation mobile communication technology) and digital medicine, emergency patients can complete pre-hospital remote diagnosis of their ECG data by sending their ECG data to the hospital's server via the Internet on the way to the hospital.

[0003] However, before transmitting the ECG data to the hospital's server, the ECG data needs to be compressed to avoid the transmission delay caused by its large transmission flow. After that, the hospital's server needs to reconstruct the ECG data so that medical staff can obtain the original ECG data before compression. However, the traditional method of compressing and reconstructing ECG data is usually difficult to accurately reproduce the original ECG data, which can easily cause medical staff to remotely misdiagnose patients. Therefore, in the remote diagnosis of patients, how to enable medical staff to obtain highly accurate ECG data is an urgent problem to be solved. Summary of the invention

[0004] The present application provides an electrocardiogram (ECG) data processing method, apparatus, device, and storage medium, which can improve the accuracy of the reconstructed ECG data, thereby effectively reducing the probability of remote misdiagnosis by medical staff.

[0005] In a first aspect, a method for processing electrocardiogram data is provided, which is applied to a server, and the method comprises:

[0006] Obtain historical ECG data within a preset time period sent by the acquisition terminal;

[0007] Periodically split the historical ECG data to obtain multiple groups of ECG data;

[0008] Perform average calculation on multiple sets of ECG data to obtain ECG sample data;

[0009] The ECG sample data is sent to the acquisition terminal, so that the acquisition terminal determines the difference data in the ECG data to be processed that is different from the ECG sample data waveform according to the ECG sample data;

[0010] The difference data sent by the acquisition terminal is reconstructed with the ECG sample data to complete the reconstruction of the ECG data to be processed.

[0011] In a second aspect, another electrocardiogram data processing method is provided, which is applied to an acquisition terminal, and the method includes:

[0012] Sending historical ECG data collected within a preset time period to the server, so that the server obtains ECG sample data based on the historical ECG data;

[0013] Extracting difference data from the to-be-processed ECG data that is different from the ECG sample data waveform according to the ECG sample data sent by the server;

[0014] The difference data is sent to the server side, so that the server side reconstructs the difference data and the ECG sample data to complete the reconstruction of the ECG data to be processed.

[0015] In a third aspect, an electrocardiogram data processing device is provided, which is applied to a server, and the device includes:

[0016] An acquisition module is used to acquire historical ECG data within a preset time period sent by the acquisition terminal;

[0017] A splitting module is used to periodically split the historical ECG data to obtain multiple groups of ECG data;

[0018] A sample data generation module is used to average multiple sets of ECG data to obtain ECG sample data;

[0019] A first sending module is used to send the ECG sample data to the acquisition terminal, so that the acquisition terminal determines the difference data in the ECG data to be processed that is different from the ECG sample data waveform according to the ECG sample data;

[0020] The reconstruction module is used to reconstruct the difference data sent by the acquisition terminal and the ECG sample data to complete the reconstruction of the ECG data to be processed.

[0021] In a fourth aspect, an electrocardiogram data processing device is provided, which is applied to an acquisition terminal, and the device includes:

[0022] The second sending module is used to send the historical ECG data collected within a preset time period to the server, so that the server obtains ECG sample data according to the historical ECG data;

[0023] An extraction module, used for extracting difference data different from the ECG sample data waveform in the ECG data to be processed according to the ECG sample data sent by the server;

[0024] The third sending module is used to send the difference data to the server side, so that the server side reconstructs the difference data and the ECG sample data to complete the reconstruction of the ECG data to be processed.

[0025] In a fifth aspect, an electronic device is provided, comprising: a processor and a memory, the memory being used to store a computer program, the processor being used to call and run the computer program stored in the memory, and executing the method in the first aspect or its various implementations.

[0026] In a sixth aspect, a computer-readable storage medium is provided for storing a computer program, wherein the computer program enables a computer to execute the method in the first aspect or its various implementations.

[0027] Through the technical solution provided by the present application, by utilizing accurate ECG sample data obtained based on the patient's personal historical ECG data within a preset time period, and then determining based on the ECG sample data the difference data in the patient's to-be-processed ECG data that is different from the ECG sample data waveform, the ECG data reconstructed by the difference data and the ECG sample data can reproduce the patient's original ECG data; it can be seen that through the present application, the accuracy of the reconstructed ECG data can be improved, thereby effectively reducing the probability of misdiagnosis by medical staff.

[0028] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of 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 creative work.

[0030] Figure 1 An application scenario diagram provided for an embodiment of the present application;

[0031] Figure 2 A flowchart of an electrocardiogram data processing method provided in an embodiment of the present application;

[0032] Figure 3 A schematic diagram of ECG waveform data provided in an embodiment of the present application;

[0033] Figure 4 A schematic diagram of historical ECG data within a preset time period provided in an embodiment of the present application;

[0034] Figure 5 A schematic diagram of each R wave peak in historical ECG data provided in an embodiment of the present application;

[0035] Figure 6 A flowchart of another electrocardiogram data processing method provided in an embodiment of the present application;

[0036] Figure 7 A schematic diagram of an electrocardiogram data processing device provided in an embodiment of the present application;

[0037] Figure 8A schematic diagram of another electrocardiogram data processing device provided in an embodiment of the present application;

[0038] Fig. 9 It is a schematic block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0040] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0041] As mentioned above, before the ECG detection equipment transmits the ECG data collected from the patient on the way to the hospital's server, the ECG data needs to be compressed to avoid the problem of data transmission delay caused by the large transmission flow of the ECG data. The hospital's server then reconstructs the received ECG data to obtain the original ECG data before compression.

[0042] However, the existing method for compressing and reconstructing ECG data mainly uses the ECG data corresponding to the patient's first cardiac cycle as reference data to compress and reconstruct the patient's ECG data. However, since the existing ECG data corresponding to the first cardiac cycle is easily affected by the bumpy road or the patient's violent body movement during the ambulance transportation of the patient, the ECG data reconstructed using the reference data is different from the patient's ECG data, thereby reducing the accuracy of the reconstructed ECG data and easily causing misdiagnosis by medical staff.

[0043] In order to solve the above technical problems, the inventive concept of the present application is: obtaining historical ECG data within a preset time period sent by an acquisition terminal; periodically splitting the historical ECG data to obtain multiple groups of ECG data; averaging multiple groups of ECG data to obtain ECG sample data; sending the ECG sample data to the acquisition terminal so that the acquisition terminal can determine the difference data in the ECG data to be processed that is different from the ECG sample data waveform based on the ECG sample data; reconstructing the difference data sent by the acquisition terminal and the ECG sample data to complete the processing of the ECG data to be processed. The present invention utilizes the ECG sample data obtained based on the patient's personal historical ECG data within a preset time period to complete the reconstruction of the difference data in the ECG data to be processed that is different from the ECG sample data waveform, which can improve the accuracy of the ECG data obtained after reconstruction, thereby effectively reducing the probability of misdiagnosis by medical staff.

[0044] It should be understood that the technical solution of the present application can be applied to the following scenarios, but is not limited to:

[0045] In some possible implementations, Figure 1 An application scenario diagram provided for an embodiment of the present application, such as Figure 1 As shown, the application scenario may include an electronic device 110 and a network device 120. The electronic device 110 may establish a connection with the network device 120 via a wired network or a wireless network.

[0046] Exemplarily, the electronic device 110 may be a desktop computer, a laptop computer, a tablet computer, etc., but is not limited thereto. The network device 120 may be a terminal device or a server, but is not limited thereto. In one embodiment of the present application, the electronic device 110 may send a request message to the network device 120, and the request message may be used to request to obtain the historical ECG data within a preset time period sent by the acquisition terminal. Further, the electronic device 110 may receive a response message sent by the network device 120, and the response message includes obtaining the historical ECG data within a preset time period sent by the acquisition terminal.

[0047] also, Figure 1 An electronic device 110 and a network device 120 are provided as an example, but other numbers of electronic devices and network devices may actually be included, and the present application does not impose any limitation on this.

[0048] In other possible implementations, the technical solution of the present application may also be executed by the above-mentioned electronic device 110, or the technical solution of the present application may also be executed by the above-mentioned network device 120, and the present application does not impose any limitation on this.

[0049] After introducing the application scenarios of the embodiments of the present application, the technical solution of the present application will be described in detail below:

[0050] Figure 2 A flowchart of an electrocardiogram data processing method provided in an embodiment of the present application is provided. The method is applied to a server and can be performed by Figure 1 The electronic device 110 shown in the figure performs, but is not limited to this. Figure 2 As shown, the method may include the following steps:

[0051] S210: Acquire historical ECG data within a preset time period sent by the acquisition terminal.

[0052] Here, the historical ECG data may be ECG (electrocardiogram) waveform data, such as Figure 3 and Figure 4 As shown, the ECG waveform data has a periodic continuity feature, and therefore, selecting the historical ECG data as the ECG waveform data can facilitate the periodic splitting of the historical ECG data in step S220.

[0053] It should be noted that the length of the preset time period is greater than the length of time the ECG monitor takes to collect the ECG of the patient once. For example, the time the ECG monitor takes to collect the ECG of the patient once is 200ms, and the preset time period is 10s. It can be seen that the historical ECG data within the preset time period includes the ECG data corresponding to the ECG monitor's multiple consecutive ECG collections of the patient.

[0054] In this step, considering that the P wave, QRS complex and T wave corresponding to the first cardiac cycle in the prior art are used as ECG sample data, which are easily affected by bumpy road conditions or violent patient movements during transportation, the historical ECG data of the patient within a preset time period sent by the acquisition terminal is obtained here, so that the ECG sample data of the patient is obtained based on the historical ECG data within a period of time, thereby improving the reliability of the ECG sample data, and effectively avoiding the problem in the prior art that ECG sample data is prone to abnormalities due to the construction of ECG data with a single waveform, and can serve as an accurate reference for the reconstruction of the ECG data to be processed on the server side in step S250.

[0055] S220, periodically splitting the historical electrocardiogram data to obtain multiple groups of electrocardiogram data.

[0056] It should be noted that each set of electrocardiographic data may include electrocardiographic data of multiple consecutive cardiac cycles; wherein the cardiac cycles corresponding to the multiple sets of electrocardiographic data have the same cycle length and number; and the electrocardiographic data of each cardiac cycle includes a waveform diagram having a P wave, a QRS complex and a T wave.

[0057] In this step, multiple groups of ECG data with the same time length are obtained by periodically splitting the historical ECG data, so that ECG sample data with multiple waveform bitmaps can be constructed through the multiple groups of ECG data in step S230.

[0058] S230, performing average calculation on multiple groups of electrocardiogram data to obtain electrocardiogram sample data.

[0059] Here, the point data at the same position in multiple sets of electrocardiographic data can be superimposed and averaged, and then based on the means and the positions corresponding to the means, an electrocardiographic sample data that is closest to all the electrocardiographic data participating in the average calculation can be generated.

[0060] In this step, the ECG sample data obtained by averaging multiple sets of ECG data is not only closest to the waveform of each ECG data, but also can avoid abnormal situations caused by noise interference, so that the acquisition terminal can accurately determine the difference data using the ECG sample data as a reference.

[0061] S240, sending the ECG sample data to the acquisition terminal, so that the acquisition terminal determines, based on the ECG sample data, difference data in the ECG data to be processed that is different from the ECG sample data waveform.

[0062] Here, the ECG data to be processed may be ECG data collected from the patient by an ECG monitor after a preset time period; and the ECG data to be processed may include ECG data corresponding to at least one cardiac cycle.

[0063] Exemplarily, after the acquisition terminal receives the ECG sample data, the difference data can be determined in the following manner: the ECG data to be processed is compared with the ECG sample data in waveform, segment data inconsistent with the ECG sample data waveform is determined, and the segment data is sent to the server as difference data.

[0064] In this step, the ECG sample data is sent to the acquisition terminal through the server to realize the waveform comparison between the ECG sample data and the ECG data to be processed on the acquisition terminal, so as to reduce the workload of the server and reduce the amount of data sent by the acquisition terminal to the server.

[0065] S250, reconstructing the difference data sent by the acquisition terminal and the ECG sample data to complete the reconstruction of the ECG data to be processed.

[0066] It can be understood that after receiving the difference data sent by the acquisition terminal, the server side reconstructs the ECG sample data and the difference data stored therein to complete the reconstruction of the ECG data to be processed on the server side.

[0067] Here, after the server completes processing the ECG data to be processed, the server sends the processed ECG data to the subscriber, so that the doctor at the subscriber can read the ECG data of the patient.

[0068] By adopting the above method, the server side obtains multiple groups of ECG data by periodically splitting the historical ECG data within a preset time period; then, the server side can use the multiple groups of ECG data to determine the ECG sample data that is most similar to each group of ECG data, effectively avoiding the problem of data anomaly caused by high-frequency noise interference in the ECG sample data constructed with ECG data of a single waveform, so as to improve the accuracy of the ECG sample data; and after the server side sends the ECG sample data to the acquisition terminal, the acquisition terminal can determine the difference data in the ECG data to be processed that is different from the ECG sample data waveform according to the ECG sample data, so that the server side can compare the difference data with the ECG sample data. The sample data is reconstructed to complete the processing of the ECG data to be processed, so that medical staff can use the processed ECG data to realize remote ECG diagnosis of the patient. It can be seen that the server uses the accurate ECG sample data obtained based on the patient's personal historical ECG data within a preset time period, and then determines the difference data in the patient's ECG data to be processed that is different from the ECG sample data waveform based on the ECG sample data, so that the ECG data reconstructed by the difference data and the ECG sample data can reproduce the patient's original ECG data; it can be seen that through this application, the accuracy of the reconstructed ECG data can be improved, thereby effectively reducing the probability of misdiagnosis by medical staff.

[0069] In some possible embodiments, periodically splitting historical ECG data to obtain multiple sets of ECG data may include the following steps:

[0070] S310, extracting the positions corresponding to the peaks of each R wave in the historical ECG data.

[0071] Here, the historical ECG data can be decomposed in the frequency domain based on the sym4 wavelet which has a high degree of matching with the ECG data, and the positions corresponding to the peaks of each R wave in the historical ECG data can be extracted.

[0072] S320, periodically splitting the historical ECG data according to the positions corresponding to the peaks of each R wave to obtain multiple groups of ECG data.

[0073] Here, the electrocardiogram data is the electrocardiogram data corresponding to one electrocardiogram acquisition of the patient by the electrocardiogram monitor within a preset time period; the electrocardiogram data includes R wave peaks corresponding to multiple cardiac cycles within one electrocardiogram acquisition time of the patient by the electrocardiogram monitor.

[0074] Since ECG data, especially ECG waveform data, has the characteristics of periodic continuity, and the ECG monitor collects ECG data from the patient multiple times within a preset time period, the continuous historical ECG data are periodically split according to the positions corresponding to each R wave peak in the historical ECG data, so that each group of ECG data split from the historical ECG data can correspond one to one with the ECG data corresponding to each ECG collection of the patient by the ECG monitor.

[0075] By adopting the above method, it is possible to obtain electrocardiogram data that corresponds one-to-one to the electrocardiogram data obtained by the electrocardiogram monitor for each electrocardiogram collection of the patient within a preset time period, so that the waveform of the electrocardiogram sample data obtained based on multiple groups of electrocardiogram data is similar to the waveform of the electrocardiogram data collected by the electrocardiogram monitor once within the preset time period, so that the collection terminal can use the electrocardiogram sample data as a reference to accurately determine the difference data in the to-be-processed electrocardiogram data collected by the electrocardiogram monitor once, and then reconstruct the electrocardiogram data that can display the patient's corresponding electrocardiogram data collected by the electrocardiogram monitor once through the difference data and the electrocardiogram sample data.

[0076] Furthermore, performing average calculation on multiple sets of ECG data to obtain ECG sample data may include the following steps:

[0077] S410, for each set of electrocardiographic data, determine the P wave start point and the T wave end point in the electrocardiographic data according to the corresponding position of each R wave peak in the electrocardiographic data.

[0078] Exemplarily, the starting point of the P wave and the ending point of the T wave in the cardiac electronic data can be determined as follows: traverse all R wave peaks in the cardiac electronic data to determine the R wave peak at the first position and the R wave peak at the last position; traverse the cardiac electronic data before the R wave peak at the first position to find the starting point of the P wave before the R wave peak, and use the starting point of the P wave as the starting point of the P wave in the cardiac electronic data; traverse the cardiac electronic data after the R wave peak at the last position to find the ending point of the T wave after the R wave peak, and use the ending point of the T wave as the ending point of the T wave in the cardiac electronic data.

[0079] In this step, the P wave starting point and T wave ending point in each set of cardiac electronic data are determined to eliminate the data with unclear waveforms at both ends of each set of cardiac electronic data, so as to facilitate the superposition and average calculation of each point data in multiple sets of cardiac electronic data in step S420.

[0080] S420, performing average calculation on each point data between the P wave starting point and the T wave ending point in the multiple sets of ECG data to obtain ECG sample data.

[0081] Exemplarily, when averaging each point data between the P wave starting point and the T wave ending point in multiple sets of cardiac electronic data, the following methods can be included: aligning the P wave starting points of multiple sets of cardiac electronic data, and aligning the T wave ending points of multiple sets of cardiac electronic data, so that the P waves, QRS complexes and T waves in the multiple sets of cardiac electronic data are aligned respectively; superimposing the point data located at the same position in the aligned multiple sets of cardiac electronic data and calculating the average value; generating ECG sample data similar to the multiple sets of cardiac electronic data based on the calculated average values ​​corresponding to each point data and the positions corresponding to each point data.

[0082] Here, by averaging the data of each point between the starting point of the P wave and the end point of the T wave in multiple sets of electrocardiographic data, the obtained ECG sample data can be made similar to the multiple sets of electrocardiographic data. At the same time, it can also facilitate waveform comparison between the ECG sample data and the ECG data to be processed, so as to speed up the efficiency of waveform comparison between the ECG sample data and the ECG data to be processed.

[0083] As another example, when performing waveform comparison between ECG sample data and ECG data to be processed, it can include: determining the starting point of the P wave and the ending point of the T wave in the ECG data to be processed; aligning the starting point of the P wave in the ECG sample data with the starting point of the P wave in the ECG data to be processed, and aligning the ending point of the T wave in the ECG data to be processed, so that the P wave, QRS complex and T wave in the ECG data to be processed and the ECG sample data are aligned respectively; performing waveform judgment on each of the aligned P waves, QRS complexes and T waves, so as to determine the P wave and / or QRS complex and / or T wave in the ECG data to be processed that is different from the waveform of the ECG sample data.

[0084] The above method can not only speed up the calculation efficiency of ECG sample data, but also speed up the waveform comparison efficiency between the obtained ECG sample data and the ECG data to be processed, thereby improving the efficiency of the acquisition terminal in determining the difference data.

[0085] In some possible embodiments, reconstructing the difference data sent by the acquisition terminal and the ECG sample data to complete the reconstruction of the ECG data to be processed may include the following steps:

[0086] S510 . For each difference data, determine the reconstruction position of the difference data in the ECG sample data according to the position information of the difference data in the ECG data to be processed.

[0087] It should be noted that when the acquisition terminal sends the difference data to the server, the location information of each difference data in the ECG data to be processed is also sent to the server.

[0088] Exemplarily, when determining the reconstruction position of the difference data in the ECG sample data, the following method can be used: according to the position information of the difference data in the ECG data to be processed, determine the P wave or QRS complex or T wave corresponding to the difference data in the ECG data to be processed, so as to use the P wave or QRS complex or T wave corresponding to the difference data as the target wave; according to the position of the target wave in the ECG data to be processed, determine the position corresponding to the target wave in the ECG sample data, and determine the position as the reconstruction position of the difference data. For example, according to the position information of the difference data in the ECG data to be processed, determine the P wave in the third cardiac cycle as the target wave; according to the position of the P wave in the ECG data to be processed, determine the P wave in the third cardiac cycle in the ECG sample data, and determine the position of the P wave in the third cardiac cycle in the ECG sample data as the reconstruction position of the difference data.

[0089] In this step, the reconstructed position of the difference data in the ECG sample data can be quickly determined through the position information of each difference data in the ECG data to be processed, so as to quickly and accurately replace the difference data with the ECG sample data in step S520.

[0090] S520: Replace the data at the reconstructed position in the ECG sample data with the difference data, and complete the reconstruction of the difference data on the ECG sample data.

[0091] Here, the server side replaces the data at the reconstructed position in the ECG sample data with the difference data sent by the acquisition terminal, thereby completing the reconstruction of the difference data on the ECG sample data, thereby greatly reducing the repeated sending of similar data in the ECG sample data by the acquisition terminal, thereby improving the efficiency of the server side in reconstructing the ECG sample data.

[0092] By adopting the above method, the reconstruction position of the difference data in the ECG sample data can be quickly determined to improve the efficiency of reconstructing the difference data on the ECG sample data, thereby achieving an improvement in the processing efficiency of the ECG data to be processed.

[0093] In some possible embodiments, before periodically splitting the historical ECG data to obtain multiple groups of ECG data, the method may further include: performing noise filtering on the historical ECG data to filter high-frequency noise signals in the historical ECG data.

[0094] Here, the historical ECG data can be filtered by wavelet transform to filter the high-frequency noise signals in the historical ECG data, so as to filter the noise signals generated by the bumpy road or the large body movement of the patient in the historical ECG data.

[0095] It should be noted that when the historical ECG data is ECG waveform data, in the process of performing wavelet transform on the ECG waveform data to filter the high-frequency noise signal, although the original vital sign signal of the patient will be distorted in a small range, since the original vital sign signal is ultimately used as ECG sample data extraction, the small range distortion of the original vital sign signal does not affect the reliability of the ECG sample data.

[0096] By adopting the above method, high-frequency noise signals in historical ECG data can be filtered to avoid interference signals caused by road bumps during transportation or large body movements of patients, so that the ECG sample data finally generated by the historical ECG data obtained by this method can completely avoid interference signals and improve the reliability of the ECG sample data.

[0097] Figure 5 A flowchart of an electrocardiogram data processing method provided in an embodiment of the present application, the method is applied to an acquisition terminal, and can be performed by Figure 1 The electronic device 110 shown in the figure performs, but is not limited to this. Figure 3 As shown, the method may include the following steps:

[0098] S610: Send historical ECG data collected within a preset time period to a server, so that the server obtains ECG sample data according to the historical ECG data.

[0099] Here, after the acquisition terminal sends the historical ECG data collected within a preset time period to the server, the server can obtain the ECG sample data through the methods provided in steps S220 and S230.

[0100] The ECG data to be processed may be ECG data collected from the patient by an ECG monitor after a preset time period; and the ECG data to be processed may include ECG data corresponding to at least one cardiac cycle.

[0101] In this step, the historical ECG data collected within a preset time period is sent to the server side through the acquisition terminal to complete the determination of the ECG sample data on the server side, which reduces the workload of the acquisition terminal and enables the server side to store the ECG sample data so that the difference data can be reconstructed through the ECG sample data stored on the server side.

[0102] S620: Extracting difference data that is different from the ECG sample data waveform in the ECG data to be processed according to the ECG sample data sent by the server.

[0103] Exemplarily, the difference data in the to-be-processed ECG data that is different from the ECG sample data waveform can be extracted by the following method: after the acquisition terminal receives the to-be-processed ECG data acquired by the ECG monitor for a patient, each point data in the ECG sample data sent by the server is compared with the point data in the to-be-processed ECG data to determine whether there are data points in the to-be-processed ECG data that have a large difference in value from the ECG sample data; if there are data points in the to-be-processed ECG data that have a large difference in value from the ECG sample data, then the difference data in the to-be-processed ECG data that is different from the ECG sample data waveform is determined based on the data points in the to-be-processed ECG data that have a large difference in value from the ECG sample data.

[0104] S630, sending the difference data to the server, so that the server reconstructs the difference data and the ECG sample data, and completes the processing of the ECG data to be processed.

[0105] Here, when the acquisition terminal sends difference data to the server, only the difference data that is different from the ECG sample data waveform is sent, so that the ECG data to be processed can be sent to the server in a differential manner, reducing the frequency of repeated sending of data that is the same as the ECG sample data in the ECG data to be processed; at the same time, the server can restore the patient's ECG data by reconstructing the ECG sample data and difference data stored locally, thereby realizing lossless compression of the ECG data to be processed.

[0106] By adopting the above method, the acquisition terminal sends the historical ECG data collected within a preset time period to the server; then, the server can obtain ECG sample data based on the historical ECG data; the acquisition terminal then extracts the difference data that is different from the ECG sample data waveform in the ECG data to be processed based on the ECG sample data sent by the server, so that the acquisition terminal sends the difference data to the server in a differential manner, and then the server reconstructs the difference data and the ECG sample data to complete the processing of the ECG data to be processed, so that it is convenient for medical staff to use the processed ECG data to realize remote ECG diagnosis of patients. It can be seen that the acquisition terminal uses the ECG sample data obtained based on the patient's personal historical ECG data within the preset time period to determine the difference data in the patient's ECG data to be processed that is different from the ECG sample data waveform, and then sends the difference data to the server, so that the server completes the reconstruction of the ECG data to be processed based on the ECG sample data and the difference data, which can improve the accuracy of the reconstructed ECG data, thereby effectively reducing the probability of misdiagnosis by medical staff.

[0107] The ECG data processing method provided in the present application includes the details of the interaction between an ECG detection device installed at the acquisition terminal and a server running the server side during operation; the process of the method is described below with reference to the following example, which includes 10 steps S1-S10.

[0108] S1, the acquisition terminal sends the historical ECG data collected within a preset time period to the server;

[0109] S2, the server side obtains the historical ECG data within a preset time period sent by the acquisition terminal;

[0110] S3, the server extracts the position corresponding to each R wave peak in the historical ECG data;

[0111] S4, the server periodically splits the historical ECG data according to the positions corresponding to the peaks of each R wave to obtain multiple groups of ECG data;

[0112] S5. The server determines the P wave starting point and T wave ending point in the cardiac electronic data for each set of cardiac electronic data according to the corresponding positions of each R wave peak in the cardiac electronic data;

[0113] S6, the server side averages the data of each point between the P wave starting point and the T wave ending point in the multiple sets of ECG data to obtain ECG sample data, and sends the ECG sample data to the server side;

[0114] S7, the acquisition terminal extracts difference data different from the ECG sample data waveform in the ECG data to be processed according to the ECG sample data sent by the server;

[0115] S8, the acquisition terminal sends the difference data to the server;

[0116] S9, the server determines, for each difference data, a reconstructed position of the difference data in the ECG sample data according to the position information of the difference data in the ECG data to be processed;

[0117] S10. The server replaces the data at the reconstructed position in the ECG sample data with the difference data, thereby completing the reconstruction of the difference data on the ECG sample data.

[0118] Figure 6 FIG. 7 is a schematic diagram of an electrocardiogram data processing device 700 according to an embodiment of the present invention. The device 700 is applied to a server, such as Figure 6 As shown, the apparatus 700 includes:

[0119] The acquisition module 710 is used to acquire the historical ECG data within a preset time period sent by the acquisition terminal;

[0120] The splitting module 720 is used to periodically split the historical ECG data to obtain multiple groups of ECG data;

[0121] The sample data generating module 730 is used to average multiple sets of ECG data to obtain ECG sample data;

[0122] The first sending module 740 is used to send the ECG sample data to the acquisition terminal, so that the acquisition terminal determines the difference data in the ECG data to be processed that is different from the ECG sample data waveform according to the ECG sample data;

[0123] The reconstruction module 750 is used to reconstruct the difference data sent by the acquisition terminal and the ECG sample data to complete the reconstruction of the ECG data to be processed.

[0124] In some implementations, the splitting module 720 includes:

[0125] An extraction unit, used to extract the position corresponding to each R wave peak in the historical ECG data;

[0126] The splitting unit is used to periodically split the historical ECG data according to the position corresponding to each R-wave peak to obtain multiple groups of ECG data; the ECG data is the ECG data corresponding to one ECG acquisition of the patient by the ECG monitor within a preset time period; the ECG data includes the R-wave peaks corresponding to multiple cardiac cycles within the time of one ECG acquisition of the patient by the ECG monitor.

[0127] In some implementations, the sample data generation module 730 includes:

[0128] A start and end point determination unit, for determining, for each set of cardiac electronic data, a P wave start point and a T wave end point in the cardiac electronic data according to positions corresponding to respective R wave peaks in the cardiac electronic data;

[0129] The sample data generating unit is used to perform average calculation on each point data between the P wave starting point and the T wave ending point in multiple sets of ECG data to obtain ECG sample data.

[0130] In some implementations, the reconstruction module 750 includes:

[0131] A reconstruction position determination unit, used for determining, for each difference data, a reconstruction position of the difference data in the ECG sample data according to the position information of the difference data in the ECG data to be processed;

[0132] The replacement unit is used to replace the data at the reconstructed position in the ECG sample data with the difference data, so as to complete the reconstruction of the difference data on the ECG sample data.

[0133] In some possible implementations, the apparatus 700 further includes:

[0134] The filtering module is used to filter the noise of the historical ECG data to complete the filtering of the high-frequency noise signals in the historical ECG data.

[0135] Figure 8FIG. 8 is a schematic diagram of an electrocardiogram data processing device 800 according to an embodiment of the present invention. The device 800 is applied to a collection terminal, such as Figure 8 As shown, the device 800 includes:

[0136] The second sending module 810 is used to send the historical ECG data collected within a preset time period to the server, so that the server obtains ECG sample data according to the historical ECG data;

[0137] An extraction module 820 is used to extract difference data different from the ECG sample data waveform in the ECG data to be processed according to the ECG sample data sent by the server;

[0138] The third sending module 830 is used to send the difference data to the server side, so that the server side reconstructs the difference data and the ECG sample data to complete the reconstruction of the ECG data to be processed.

[0139] It should be understood that the embodiment of the electrocardiogram data processing device and the embodiment of the electrocardiogram data processing method may correspond to each other, and similar descriptions may refer to the embodiment of the electrocardiogram data processing method. To avoid repetition, they will not be described here. Specifically, Figure 7 The device 700 shown, and Figure 8 The device 800 shown can execute the above-mentioned ECG data processing method embodiment, and the above-mentioned and other operations and / or functions of each module in the device 700 and the device 800 are respectively for realizing the corresponding processes in the above-mentioned ECG data processing method, which will not be repeated here for the sake of brevity.

[0140] In the above, the apparatus 700 and the apparatus 800 of the embodiment of the present invention are described from the perspective of functional modules in conjunction with the accompanying drawings. It should be understood that the functional module can be implemented in the form of hardware, can be implemented in the form of software instructions, or can be implemented in the form of a combination of hardware and software modules. Specifically, the steps of the ECG data processing method and the detection method embodiment in the embodiment of the present invention can be completed by the hardware integrated logic circuit and / or software instructions in the processor, and the steps of the ECG data processing method and the detection method disclosed in the embodiment of the present invention can be directly embodied as a hardware decoding processor to execute, or can be executed by a combination of hardware and software modules in the decoding processor. Optionally, the software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps in the above-mentioned ECG data processing method and the detection method embodiment in conjunction with its hardware.

[0141] Fig. 9 is a schematic block diagram of an electronic device 110 according to an embodiment of the present invention.

[0142] like Fig. 9 As shown, the electronic device 110 may include:

[0143] The memory 111 and the processor 112, the memory 111 is used to store the computer program and transmit the program code to the processor 112. In other words, the processor 112 can call and run the computer program from the memory 111 to implement the method in the embodiment of the present invention.

[0144] For example, the processor 112 may be configured to execute the above method embodiments according to instructions in the computer program.

[0145] In some embodiments of the present invention, the electronic device 110 may include but is not limited to:

[0146] General-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc.

[0147] In some embodiments of the present invention, the memory 111 includes but is not limited to:

[0148] Volatile memory and / or non-volatile memory. Among them, the non-volatile memory can be read-only memory (ROM), programmable ROM (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM) or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM).

[0149] In some embodiments of the present invention, the computer program may be divided into one or more modules, which are stored in the memory 111 and executed by the processor 112 to complete the method provided by the present invention. The one or more modules may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the controller.

[0150] like Fig. 9 As shown, the electronic device 110 may further include:

[0151] The transceiver 113 may be connected to the processor 112 or the memory 111 .

[0152] The processor 112 may control the transceiver 113 to communicate with other devices, specifically, to send information or data to other devices, or to receive information or data sent by other devices. The transceiver 113 may include a transmitter and a receiver. The transceiver 113 may further include an antenna, and the number of antennas may be one or more.

[0153] It should be understood that the various components in the electronic device are connected via a bus system, wherein the bus system includes not only a data bus but also a power bus, a control bus and a status signal bus.

[0154] The present invention also provides a computer storage medium having a computer program stored thereon, which, when executed by a computer, enables the computer to perform the method of the above method embodiment. In other words, an embodiment of the present invention also provides a computer program product containing instructions, which, when executed by a computer, enables the computer to perform the method of the above method embodiment.

[0155] When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (Digital Subscriber Line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integration. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (Digital Video Disc, DVD)), or a semiconductor medium (e.g., a solid-state drive (Solid State Disk, SSD)), etc.

[0156] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0157] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the module is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0158] The modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. For example, each functional module in each embodiment of the present application may be integrated into a processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0159] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in this application, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for processing electrocardiogram data, characterized in that: Applied to the server side, the method includes: Obtain historical ECG data within a preset time period sent by the acquisition terminal; Periodically splitting the historical ECG data to obtain multiple groups of ECG data; Performing average calculation on the multiple groups of ECG data to obtain ECG sample data; Sending the ECG sample data to the acquisition terminal, so that the acquisition terminal determines, based on the ECG sample data, difference data in the ECG data to be processed that is different from the ECG sample data waveform; The difference data sent by the acquisition terminal and the ECG sample data are reconstructed to complete the reconstruction of the ECG data to be processed.

2. The method according to claim 1, characterized in that The historical ECG data is periodically split to obtain multiple sets of ECG data, including: Extracting the positions corresponding to the peaks of each R wave in the historical ECG data; The historical ECG data are periodically split according to the positions corresponding to the respective R-wave peaks to obtain a plurality of groups of ECG data; the ECG data are the ECG data corresponding to one ECG acquisition of the patient by the ECG monitor within the preset time period; the ECG data include R-wave peaks corresponding to a plurality of cardiac cycles within one ECG acquisition time of the patient by the ECG monitor.

3. The method according to claim 2, characterized in that The plurality of groups of electrocardiogram data are averaged to obtain electrocardiogram sample data, including: For each group of the cardiac electronic data, determining the P wave starting point and the T wave ending point in the cardiac electronic data according to the positions corresponding to the respective R wave peaks in the cardiac electronic data; The data of each point between the P wave starting point and the T wave ending point in the plurality of groups of the electrocardiogram data are averaged to obtain the electrocardiogram sample data.

4. The method according to claim 1, characterized in that The step of reconstructing the difference data and the ECG sample data sent by the acquisition terminal to complete the reconstruction of the ECG data to be processed includes: For each of the difference data, determining a reconstruction position of the difference data in the electrocardiogram sample data according to the position information of the difference data in the electrocardiogram data to be processed sent by the acquisition terminal; The data at the reconstructed position in the electrocardiogram sample data is replaced with the difference data, thereby completing the reconstruction of the difference data on the electrocardiogram sample data.

5. The method according to claim 1, characterized in that Before periodically splitting the historical ECG data to obtain multiple groups of ECG data, the method further includes: The historical ECG data is subjected to noise filtering to complete filtering of high-frequency noise signals in the historical ECG data.

6. A method for processing electrocardiogram data, characterized in that: Applied to a collection terminal, the method includes: Sending historical ECG data collected within a preset time period to a server, so that the server obtains ECG sample data according to the historical ECG data; Extracting difference data different from the waveform of the ECG sample data in the ECG data to be processed according to the ECG sample data sent by the server; The difference data is sent to the server end, so that the server end reconstructs the difference data and the ECG sample data to complete the reconstruction of the ECG data to be processed.

7. An electrocardiogram data processing device, characterized in that: Applied to the server side, the device includes: An acquisition module is used to acquire historical ECG data within a preset time period sent by the acquisition terminal; A splitting module, used for periodically splitting the historical ECG data to obtain multiple groups of ECG data; A sample data generation module, used for averaging multiple groups of ECG data to obtain ECG sample data; A first sending module, used for sending the ECG sample data to the acquisition terminal, so that the acquisition terminal determines the difference data in the ECG data to be processed that is different from the ECG sample data waveform according to the ECG sample data; A reconstruction module is used to reconstruct the difference data sent by the acquisition terminal and the ECG sample data to complete the reconstruction of the ECG data to be processed.

8. An electrocardiogram data processing device, characterized in that: Applied to the acquisition terminal, the device includes: A second sending module, used for sending historical ECG data collected within a preset time period to a server end, so that the server end obtains ECG sample data according to the historical ECG data; An extraction module, configured to extract difference data different from the waveform of the ECG sample data in the ECG data to be processed according to the ECG sample data sent by the server; The third sending module is used to send the difference data to the server end, so that the server end reconstructs the difference data and the ECG sample data to complete the reconstruction of the ECG data to be processed.

9. An electronic device, characterized in that: include: A processor and a memory, the memory being used to store a computer program, and the processor being used to call and run the computer program stored in the memory to execute the method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: Used to store a computer program, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 6.

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