Electrocardiogram data analysis method, system and equipment and storage medium

Abstract

The invention relates to the technical field of data processing, and provides an electrocardiogram data analysis method, system and device and a storage medium. The method comprises the steps that an analysis end device receives a first electrocardiogram data set and a second electrocardiogram data set sent by a collection end device; wherein the first electrocardio data set is electrocardio data which is disassembled from acquired original electrocardio data by the acquisition end equipment and comprises a first signal feature of the original electrocardio data, and the second electrocardio data set is electrocardio data which comprises a second signal feature of the original electrocardio data; the first signal feature is a key signal feature, and the feature information amount of the second signal feature is greater than that of the first signal feature; performing pre-analysis processing on the first electrocardiogram data set to obtain a pre-analysis result; and based on the pre-analysis result, performing re-analysis processing on the second electrocardiogram data set to obtain a re-analysis result. By adopting the method, the waiting time of related personnel for checking the electrocardiogram data analysis result can be shortened.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and in particular, to a method, system, device, and storage medium for electrocardiogram (ECG) data analysis. Background Art

[0002] Currently, conventional ECG data analysis methods generally use a collection device to collect ECG data, and then upload the collected ECG data to an analysis device. The analysis device analyzes the ECG waveform to obtain and present the corresponding ECG data analysis results. However, due to the large amount of ECG data, both data upload and data analysis take a lot of time, resulting in a long waiting time for relevant personnel to see the ECG data analysis results. Summary of the Invention

[0003] In view of this, embodiments of this application provide a method, system, device, and storage medium for ECG data analysis, which can reduce the waiting time for relevant personnel to view the ECG data analysis results.

[0004] The first aspect of the embodiments of this application provides an ECG data analysis method applied to an analysis device, including:

[0005] Receiving a first ECG data set and a second ECG data set sent by a collection device; wherein, the first ECG data set is disassembled from the collected original ECG data by the collection device, and contains the ECG data of the first signal feature of the original ECG data, and the second ECG data set is the ECG data containing the second signal feature of the original ECG data; the first signal feature is a key signal feature, and the feature information amount of the second signal feature is more than that of the first signal feature;

[0006] Performing pre-analysis processing on the first ECG data set to obtain a pre-analysis result;

[0007] Based on the pre-analysis result, performing re-analysis processing on the second ECG data set to obtain a re-analysis result.

[0008] In an embodiment of the present application, after the acquisition device collects the original electrocardiogram (ECG) data, it disassembles the first ECG data set and the second ECG data set from the original ECG data, and sends both the first ECG data set and the second ECG data set to the analysis device. The first ECG data set contains the key signal features of the original ECG data, and the second ECG data set contains signal features with more feature information than the key signal features. It can be seen that the data volume of the first ECG data set is smaller than that of the second ECG data set. After receiving the first ECG data set, the analysis device can start pre-analysis processing, obtain the corresponding pre-analysis results and present them. In addition, the analysis device can also perform re-analysis processing on the second ECG data set in the background based on the pre-analysis results to obtain re-analysis results. Since the data volume of the first ECG data set is small, and the re-analysis process does not affect the relevant personnel's viewing of the pre-analysis results, the relevant personnel can view the pre-analysis results after waiting for a short time, that is, the waiting time for the relevant personnel to view the ECG data analysis results can be reduced.

[0009] In an implementation manner of the embodiment of the present application, based on the pre-analysis results, performing re-analysis processing on the second ECG data set to obtain re-analysis results includes:

[0010] Determine the abnormal data time period according to the first ECG data set;

[0011] Intercept the ECG data segment within the abnormal data time period from the second ECG data set;

[0012] Based on the pre-analysis results, perform re-analysis processing on the ECG data segment to obtain re-analysis results.

[0013] In an implementation manner of the embodiment of the present application, the pre-analysis results include the pre-analysis R-wave position detection results and the pre-analysis R-wave type detection results, and the re-analysis results include the R-wave position detection results of multiple channels included in the second ECG data set and the R-wave type detection results of multiple channels; after obtaining the re-analysis results, the method further includes:

[0014] Adjust the pre-analysis R-wave position detection results according to the R-wave position detection results of multiple channels;

[0015] Adjust the pre-analysis R-wave type detection results according to the R-wave type detection results of multiple channels.

[0016] In an implementation manner of the embodiment of the present application, adjusting the pre-analysis R-wave position detection results according to the R-wave position detection results of multiple channels includes:

[0017] For each RR time period in the pre-analysis R-wave position detection result, detect whether there is an R wave that meets the preset conditions within the RR time period of the R-wave position detection result of each channel; if the ratio of the number of target channels included in multiple channels to the number of multiple channels is greater than the first threshold, supplement R waves within the RR time period of the pre-analysis R-wave position detection result; where the RR time period is the time period between two adjacent R-wave positions in the pre-analysis R-wave position detection result, and the target channel is the channel where there is an R wave that meets the preset conditions within the RR time period of the corresponding R-wave position detection result.

[0018] In an implementation manner of the embodiment of the present application, detecting whether there is an R wave that meets the preset conditions within the RR time period of the R-wave position detection result of each channel respectively includes:

[0019] Calculate the average value of the interval durations of each R-wave position in the pre-analysis R-wave position detection result to obtain the average RR interval;

[0020] For each channel, if there is a target R wave with an amplitude greater than the second threshold within the RR time period of the R-wave position detection result of the channel, the number of R waves of the same type as the target R wave in the R-wave position detection result of the channel is greater than the third threshold, and the target RR interval is within the interval range constructed according to the average RR interval, it is determined that there is an R wave that meets the preset conditions within the RR time period of the R-wave position detection result of the channel; where the target RR interval is the duration between the target R wave and the start point of the RR time period.

[0021] In an implementation manner of the embodiment of the present application, adjusting the pre-analysis R-wave type detection result according to the R-wave type detection results of multiple channels includes:

[0022] For the R-wave type at each position in the pre-analysis R-wave type detection result, adjust the R-wave type to the target type at the corresponding position in the R-wave type detection results of multiple channels; where the target type is the type of the largest number of same-type R waves at the corresponding position in the R-wave type detection results of multiple channels.

[0023] The second aspect of the embodiment of the present application provides an electrocardiogram data analysis method applied to a collection end device, including:

[0024] Obtain a first electrocardiogram data set and a second electrocardiogram data set; where the first electrocardiogram data set is disassembled from the collected original electrocardiogram data by the collection end device and contains the electrocardiogram data of the first signal characteristics of the original electrocardiogram data, and the second electrocardiogram data set is the electrocardiogram data containing the second signal characteristics of the original electrocardiogram data; the first signal characteristic is a key signal characteristic, and the characteristic information amount of the second signal characteristic is more than that of the first signal characteristic.

[0025] Send the first electrocardiogram (ECG) data set and the second ECG data set to the analysis terminal device to instruct the analysis terminal device to perform pre-analysis processing on the first ECG data set to obtain a pre-analysis result, and based on the pre-analysis result, perform re-analysis processing on the second ECG data set to obtain a re-analysis result.

[0026] In an implementation manner of the embodiments of the present application, the original ECG data includes ECG data of multiple channels; the first ECG data set is obtained in the following manner:

[0027] For the ECG data of each channel, detect the average value of all signal peaks of the ECG data within a specified time period;

[0028] From the ECG data of multiple channels, select the ECG data of one channel whose difference between the corresponding average value and the set peak value is the smallest as the first ECG data set.

[0029] A third aspect of the embodiments of the present application provides an analysis terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the ECG data analysis method provided in the first aspect of the embodiments of the present application.

[0030] A fourth aspect of the embodiments of the present application provides a collection terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the ECG data analysis method provided in the second aspect of the embodiments of the present application.

[0031] A fifth aspect of the embodiments of the present application provides an ECG data analysis system, which includes the analysis terminal device provided in the third aspect of the embodiments of the present application and the collection terminal device provided in the fourth aspect of the embodiments of the present application.

[0032] A sixth aspect of the embodiments of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the ECG data analysis method provided in the first aspect of the embodiments of the present application, or implements the ECG data analysis method provided in the second aspect of the embodiments of the present application.

[0033] It can be understood that the beneficial effects of the above second aspect to the sixth aspect can refer to the relevant descriptions in the above first aspect, and will not be elaborated here. Description of the Drawings

[0034] Figure 1 is a schematic diagram of an ECG data analysis system provided by the embodiments of the present application;

[0035] Figure 2It is a flowchart of a method for analyzing electrocardiogram data provided by an embodiment of the present application;

[0036] Figure 3 It is a schematic flowchart of a lead optimization operation provided by an embodiment of the present application;

[0037] Figure 4 It is a schematic flowchart of data compression for electrocardiogram data after lead optimization operation provided by an embodiment of the present application;

[0038] Figure 5 It is a schematic diagram of the overall working principle of an electrocardiogram data analysis system provided by an embodiment of the present application;

[0039] Figure 6 It is a schematic diagram of the working principle of an analysis terminal device provided by an embodiment of the present application;

[0040] Figure 7 It is a schematic flowchart of the operation for adjusting the R-wave position globally for multiple channels of an analysis terminal device provided by an embodiment of the present application;

[0041] Figure 8 It is a schematic flowchart of the operation for adjusting the R-wave position in an abnormal data segment of an analysis terminal device provided by an embodiment of the present application;

[0042] Figure 9 It is a schematic flowchart of the operation for adjusting the R-wave type globally for multiple channels of an analysis terminal device provided by an embodiment of the present application;

[0043] Figure 10 It is a schematic flowchart of the operation for adjusting the R-wave type in an abnormal data segment of an analysis terminal device provided by an embodiment of the present application;

[0044] Figure 11 It is a schematic diagram of the structure of an electrocardiogram data analysis device applied to a collection terminal device provided by an embodiment of the present application;

[0045] Figure 12 It is a schematic diagram of the structure of an electrocardiogram data analysis device applied to an analysis terminal device provided by an embodiment of the present application;

[0046] Figure 13 It is a schematic diagram of a terminal device provided by an embodiment of the present application. Detailed implementation manners

[0047] In the following description, specific details such as specific system architectures and technologies are presented for purposes of illustration rather than limitation in order to provide a thorough understanding of the embodiments of the present application. However, those skilled in the art should understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from obscuring the description of the present application. Additionally, in the description of the specification and the appended claims of the present application, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0048] The analysis of electrocardiogram (ECG) data is of great significance for medical staff to study the condition of patients. Conventional ECG data analysis methods generally use the acquisition device at the collection end to collect ECG data, and then upload the collected ECG data to the analysis device at the analysis end. The analysis device analyzes the ECG waveform and obtains and presents the corresponding ECG data analysis results. In the above process, medical staff need to wait for the data import time and the data analysis time to see the corresponding ECG waveform analysis results, which takes a long time. To address the above problems, the embodiments of the present application provide an ECG data analysis method, system, device, and storage medium, which can reduce the waiting time for relevant personnel to view the ECG data analysis results. For more specific technical implementation details of the embodiments of the present application, please refer to the following embodiments.

[0049] As Figure 1 shown, it is a schematic diagram of an ECG data analysis system provided by an embodiment of the present application. In Figure 1Among them, it includes a collection - end device and an analysis - end device, and a communication connection can be established between them in a wireless or wired manner. Among them, the collection - end device can be various types of electrocardiogram (ECG) data collection devices, mainly used for collecting the original ECG data of patients, and performing certain pre - processing on the original ECG data. Specifically, it can disassemble a first ECG data set containing the first signal feature from the original ECG data, where the first signal feature can be a key signal feature. In addition, the collection - end device can also determine a second ECG data set containing the second signal feature according to the original ECG data, and the feature information amount of the second signal feature is more than that of the first signal feature. In actual operation, the original ECG data can be directly used as the second ECG data set, or certain pre - processing (such as denoising and waveform arrangement, etc.) can be performed on the original ECG data, and the pre - processed original ECG data is used as the second ECG data set. The collection - end device will send both the obtained first ECG data set and the second ECG data set to the analysis - end device. The collection - end device generally has multiple data collection channels, such as 8 channels or 16 channels. Each channel corresponds to a lead method respectively, and its data sampling rate can generally be values such as 125Hz, 128Hz, 250Hz, 500Hz, and 1000Hz, etc. The higher the sampling rate, the higher the accuracy but the larger the corresponding data volume. The analysis - end device can be various types of ECG data analysis devices, mainly used for pre - analyzing or precisely analyzing the received ECG data, obtaining and presenting the ECG data analysis results. Regarding Figure 1 For the specific working principle of the system shown, reference can be made to the method embodiments described below.

[0050] Please refer to Figure 2 , which shows an ECG data analysis method provided by an embodiment of the present application, including:

[0051] 201. The collection - end device acquires the original ECG data;

[0052] This ECG data analysis method is applied to an ECG data analysis system as shown in Figure 1 . First, the collection - end device collects the ECG data of the patient to obtain the original ECG data. Since the collection - end device generally has multiple data collection channels, the original ECG data obtained here can be the ECG data of multiple channels, such as 8 - channel ECG data or 16 - channel ECG data, etc.

[0053] Divided according to different channel numbers, different sampling rates, and different data precisions, the data volume of common ECG data can refer to Table 1.

[0054] Table 1

[0055] Data Type 1 24 hours * 60 minutes * 60 seconds * 125 Hz * 1 channel * 8 bits ≈10.3 MB Data Type 2 24 hours * 60 minutes * 60 seconds * 125 Hz * 1 channel * 12 bits ≈15.5 MB Data Type 3 24 hours * 60 minutes * 60 seconds * 125 Hz * 1 channel * 16 bits ≈20.6 MB Data Type 4 24 hours * 60 minutes * 60 seconds * 125 Hz * 8 channels * 16 bits ≈164.8 MB Data Type 5 24 hours * 60 minutes * 60 seconds * 128 Hz * 8 channels * 16 bits ≈168.7 MB Data Type 6 24 hours * 60 minutes * 60 seconds * 250 Hz * 8 channels * 16 bits ≈329.6 MB Data Type 7 24 hours * 60 minutes * 60 seconds * 256 Hz * 8 channels * 16 bits ≈337.4 MB Data Type 8 24 hours * 60 minutes * 60 seconds * 500 Hz * 8 channels * 16 bits ≈659.2 MB Data Type 9 24 hours * 60 minutes * 60 seconds * 1000 Hz * 8 channels * 16 bits ≈1318.4 MB

[0056] Table 1 shows the 24-hour data volume of 9 types of electrocardiogram data. For example, for data type 8, 24 hours * 60 minutes * 60 seconds represents the number of seconds in a day, 500Hz represents the data sampling rate, 8 channels represent having 8 data acquisition channels, 16 bits represent the data accuracy, and its data volume is approximately 659.2MB.

[0057] 202. The acquisition device determines a first electrocardiogram data set and a second electrocardiogram data set according to the original electrocardiogram data;

[0058] After the acquisition device obtains the original electrocardiogram data, it disassembles a first electrocardiogram data set from the original electrocardiogram data, which contains the key signal features of the original electrocardiogram data. In addition, it will also determine a second electrocardiogram data set with a larger amount of signal features contained according to the original electrocardiogram data. It can be seen that the first electrocardiogram data set and the second electrocardiogram data set are generated from the same-source data (i.e., the original electrocardiogram data). Specifically, the acquisition device can perform signal feature analysis on the original electrocardiogram data, select the electrocardiogram data of a single channel or multiple channels with better signal quality in the original electrocardiogram data that can clearly reflect the electrocardiogram signal features, and then perform a certain data compression process on the selected electrocardiogram data to obtain a first electrocardiogram data set with a data volume much smaller than the original electrocardiogram data. The acquisition device can directly use the original electrocardiogram data as the second electrocardiogram data set, or perform a certain preprocessing (such as denoising and waveform sorting, etc.) on the original electrocardiogram data, and use the preprocessed original electrocardiogram data as the second electrocardiogram data set.

[0059] In an embodiment of the present application, the original electrocardiogram data includes electrocardiogram data of multiple channels; the acquisition device determines a first electrocardiogram data set according to the original electrocardiogram data, including:

[0060] (1) The acquisition device detects the average value of all signal peaks of the electrocardiogram data of each channel within a specified time period;

[0061] (2) The acquisition device selects the electrocardiogram data of one channel with the smallest difference between the corresponding average value and the set peak value from the electrocardiogram data of multiple channels as the first electrocardiogram data set.

[0062] This processing method is that the acquisition device selects the electrocardiogram data of one channel with the highest data quality from the electrocardiogram data of multiple channels as the first electrocardiogram data set. Since one channel corresponds to one lead method, the selected electrocardiogram data here is also the electrocardiogram data of the lead method with the highest data quality. Therefore, this processing method can also be called the lead optimization operation. In the lead optimization operation, first, for the electrocardiogram data of each channel, the average value of all signal peaks of the electrocardiogram data within a specified time period is detected, and then the electrocardiogram data of one channel with the smallest difference between the corresponding average value and the set peak value is selected as the first electrocardiogram data set.

[0063] As shown Figure 3 in the figure, it is a schematic flowchart of a lead optimization operation provided by an embodiment of the present application. Assuming there are a total of 8 channels, namely channel 1, channel 2, …, channel 8, the following operations are performed on the electrocardiogram data of each channel: The signals in a certain period of time in the front (such as 2 minutes) are not analyzed because the signals in the front may not be very stable, so this part of the signals is discarded during analysis; A certain period of time after a certain duration is obtained, for example, a time period with a duration of 16 seconds is intercepted, and then all signal peaks within this time period are detected, and the average value of these signal peaks is calculated. All leads are traversed, that is, all channels are calculated in the same way to obtain the average value of the signal peaks corresponding to each lead respectively. Finally, the electrocardiogram data of the lead whose average value of the signal peaks is closest to the set peak is selected as the first electrocardiogram data set. The set peak here can be determined according to empirical values. For example, if the normal electrocardiogram signal amplitude of the population is about 1 mV, then the set peak can be taken as 1 mV.

[0064] As another example, if the lead optimization operation is not performed, the electrocardiogram data of a certain lead can also be default selected as the first electrocardiogram data set.

[0065] In an embodiment of the present application, after obtaining the first electrocardiogram data set through the lead optimization operation, the first electrocardiogram data set can be further compressed to further reduce the data volume of the first electrocardiogram data set.

[0066] As shown Figure 4 in the figure, it is a schematic flowchart of data compression for the electrocardiogram data after the lead optimization operation provided by an embodiment of the present application. In Figure 4 , the original data represents the electrocardiogram data of a single channel obtained after the lead optimization operation. First, the electrocardiogram data can be compressed in terms of precision. For example, the precision of the electrocardiogram data can be compressed from 0.0025 mV per digital unit to 0.02 mV per digital unit, sacrificing data precision to compress the data volume. Then, the electrocardiogram data can be downsampled. For example, the sampling rate is reduced from 500 Hz to 125 Hz, and the signals with amplitudes exceeding the threshold value are limited within the threshold value. For example, the signals exceeding ±2.5 mV are all modified to signals within the range of ±2.5 mV. Finally, the first electrocardiogram data set after data compression can be obtained. The 24-hour data volume of this first electrocardiogram data set = 24 hours * 60 minutes * 60 seconds * 125 Hz * 1 channel * 8 bits ≈ 10 MB, which is significantly reduced compared with the multi-channel original electrocardiogram data shown in Table 1.

[0067] 203. The acquisition-end device sends the first electrocardiogram data set and the second electrocardiogram data set to the analysis-end device;

[0068] After the acquisition device disassembles the first electrocardiogram (ECG) data set and the second ECG data set from the original ECG data, it will send both the first ECG data set and the second ECG data set to the analysis device, and then the analysis device will perform analysis and processing on the two parts of ECG data. In addition, the acquisition device can also perform pre-analysis processing on the first ECG data set by itself to obtain a pre-analysis result, which can be displayed on the screen of the acquisition device or sent to the screen of the analysis device for display.

[0069] 204. The analysis device receives the first ECG data set and the second ECG data set sent by the acquisition device;

[0070] When the analysis device receives the first ECG data set and the second ECG data set sent by the acquisition device, since the data volume of the first ECG data set is much smaller than that of the second ECG data set, the analysis device will first receive the entire first ECG data set. At this time, the analysis device can start the pre-analysis processing for the first ECG data set without waiting for the second ECG data set to be completely received. For example, when the acquisition device uploads the two parts of ECG data to the analysis device, since the data volume of the first ECG data set is reduced by about 65 times compared to the data volume of the second ECG data set, the upload time of the first ECG data set will also be reduced by about 65 times compared to the second ECG data set.

[0071] 205. The analysis device performs pre-analysis processing on the first ECG data set to obtain a pre-analysis result;

[0072] The analysis device can perform various types of pre-analysis processing on the first ECG data set to obtain a pre-analysis result. For example, it can perform R-wave position detection processing and R-wave type detection processing on the first ECG data set to obtain the positions of each R wave (represented by the pre-analysis R-wave position detection result) and the types of each R wave (represented by the pre-analysis R-wave type detection result) included in the first ECG data set as the pre-analysis result. In actual operation, the pre-analysis result can be output through conventional ECG data presentation methods such as heart rate trend graphs, scatter plots, histograms, electrocardiograms, page scan graphs, and superimposed graphs. After the analysis device obtains the pre-analysis result, it can immediately output the pre-analysis result without waiting for the reception and re-analysis process of the second ECG data set. Therefore, relevant personnel can view the pre-analysis result after waiting for a shorter time, which can reduce the waiting time for relevant personnel to view the analysis result of the ECG data.

[0073] 206. The analysis device performs re-analysis processing on the second ECG data set based on the pre-analysis result to obtain a re-analysis result.

[0074] After the analysis terminal device receives the second electrocardiogram data set, it can start the re-analysis process for the second electrocardiogram data set based on the pre-analysis result. Since the first electrocardiogram data set is single-channel and low-precision electrocardiogram data, while the second electrocardiogram data set is multi-channel and high-precision electrocardiogram data, the accuracy of the re-analysis result will definitely be higher than that of the pre-analysis result. Therefore, the pre-analysis result can be adjusted using the re-analysis result in the subsequent process. In actual operation, the re-analysis process for the second electrocardiogram data set can include: conventional electrocardiogram data analysis operations such as R-wave position detection, R-wave type detection, ST analysis, QT analysis, TWA analysis, HRV / HRT / ACDC analysis, and VCG analysis. The corresponding re-analysis result can also be output through conventional electrocardiogram data presentation methods such as heart rate trend charts, scatter plots, histograms, electrocardiograms, page scan charts, and superimposed charts.

[0075] In an embodiment of the present application, the pre-analysis result includes the pre-analysis R-wave position detection result and the pre-analysis R-wave type detection result; the re-analysis result includes the R-wave position detection results of multiple channels included in the second electrocardiogram data set and the R-wave type detection results of multiple channels; after obtaining the re-analysis result, the method further includes:

[0076] (1) Adjust the pre-analysis R-wave position detection result according to the R-wave position detection results of multiple channels;

[0077] (2) Adjust the pre-analysis R-wave type detection result according to the R-wave type detection results of multiple channels.

[0078] The pre-analysis results include the pre-analysis R-wave position detection results and the pre-analysis R-wave type detection results. The pre-analysis R-wave position detection results are the positions of each R-wave included in the first electrocardiogram dataset, and the pre-analysis R-wave type detection results are the types of each R-wave included in the first electrocardiogram dataset. When the analysis terminal device performs re-analysis processing on the second electrocardiogram dataset, it can perform re-analysis on the electrocardiogram data of all channels included in the second electrocardiogram dataset, or only perform re-analysis on the electrocardiogram data of some channels included in the second electrocardiogram dataset. Here, the re-analysis can include two parts: the adjustment of the R-wave position detection results and the adjustment of the R-wave type detection results. Specifically, the analysis terminal device first performs multi-channel R-wave position detection processing and R-wave type detection processing on the second electrocardiogram dataset, so as to obtain the R-wave position detection results of multiple channels included in the second electrocardiogram dataset and the R-wave type detection results of multiple channels. For example, assuming that the obtained electrocardiogram data is from channel 1 to channel 8, the R-wave position detection processing and R-wave type detection processing are respectively performed on the electrocardiogram data of channel 1 to channel 8, so as to obtain the R-wave position detection results and R-wave type detection results of channel 1: respectively representing the positions of each R-wave and the types of each R-wave included in the electrocardiogram data of channel 1; the R-wave position detection results and R-wave type detection results of channel 2: respectively representing the positions of each R-wave and the types of each R-wave included in the electrocardiogram data of channel 2... and so on. After the analysis terminal device obtains the R-wave position detection results of multiple channels, it can adjust the pre-analysis R-wave position detection results according to the R-wave position detection results of multiple channels. For example, it can supplement the missing R-waves in the pre-analysis R-wave position detection results, or adjust the positions of some R-waves in the pre-analysis R-wave position detection results, and so on. After the analysis terminal device obtains the R-wave type detection results of multiple channels, it can adjust the pre-analysis R-wave type detection results according to the R-wave type detection results of multiple channels. For example, it can adjust the types of R-waves at some positions in the pre-analysis R-wave type detection results, and so on.

[0079] In an embodiment of the present application, the analysis terminal device adjusts the pre-analysis R-wave position detection results according to the R-wave position detection results of multiple channels, including:

[0080] For each RR time period in the pre-analysis R-wave position detection results, the analysis terminal device respectively detects whether there is an R-wave that meets the preset conditions within the RR time period of the R-wave position detection results of each channel; if the ratio of the number of target channels included in multiple channels to the number of multiple channels is greater than the first threshold, then an R-wave is supplemented within the RR time period of the pre-analysis R-wave position detection results; wherein, the RR time period is the time period between two adjacent R-wave positions in the pre-analysis R-wave position detection results, and the target channel is the channel where there is an R-wave that meets the preset conditions within the RR time period of the corresponding R-wave position detection results.

[0081] Suppose the pre-analysis R-wave position detection results include N R-wave positions, namely R1, R2, R3, R4... RN. Then the first RR time period RR1 = [R1, R2], representing the time period between R1 and R2; the second RR time period RR2 = [R2, R3], representing the time period between R2 and R3, and so on. For each RR time period, it is possible to detect whether there is an R wave satisfying a preset condition within this RR time period in the R-wave position detection results of each channel. For example, for the RR time period [R1, R2], it is respectively detected whether there is an R wave satisfying the preset condition within the [R1, R2] time period in the R-wave position detection results of channel 1, and whether there is an R wave satisfying the preset condition within the [R1, R2] time period in the R-wave position detection results of channel 2, and so on. The channel for which the corresponding R-wave position detection result has an R wave satisfying the preset condition within this RR time period is determined as the target channel, that is, the target channel is the channel that detects an R wave satisfying the preset condition within this RR time period. Then, compare the number of target channels with the number of all channels. If the ratio of the number of target channels to the number of all channels is greater than a preset first threshold, such as 2 / 3 or 1 / 2, it means that more than half of the channels have detected R waves satisfying the preset condition within this RR time period. Therefore, it can be considered that there is indeed a valid R wave within this RR time period, and this R wave is missed in the pre-analysis R-wave position detection results. Therefore, an R wave can be added within this RR time period of the pre-analysis R-wave position detection results to complete the adjustment. Traverse all RR time periods of the pre-analysis R-wave position detection results, and supplement the missed R waves in the above manner to complete the adjustment process of the pre-analysis R-wave position detection results.

[0082] As an example, the analysis terminal device respectively detects whether there is an R wave satisfying a preset condition within the RR time period of the R-wave position detection results of each channel, including:

[0083] (1) The analysis terminal device calculates the average value of the interval durations of each R-wave position in the pre-analysis R-wave position detection results to obtain the average RR interval;

[0084] (2) For each channel, if there is a target R wave with an amplitude greater than a second threshold within the RR time period of the R-wave position detection results of the channel, the number of R waves of the same type as the target R wave in the R-wave position detection results of the channel is greater than a third threshold, and the target RR interval is within the interval range constructed based on the average RR interval, then it is determined that there is an R wave satisfying the preset condition within the RR time period of the R-wave position detection results of the channel; where the target RR interval is the duration between the target R wave and the start point of the RR time period.

[0085] The R wave that meets the preset conditions can be regarded as a valid R wave. The following specifically introduces how to determine whether a valid R wave is detected in a certain channel during the RR time period. First, it is necessary to calculate the average RR interval. The average RR interval refers to the average of the interval durations of the positions of each R wave in the pre-analysis R wave position detection result, that is, the average of each RR interval. For example, assuming that the RR intervals of the pre-analysis R wave position detection result are: RR1, RR2,... RRN, then the average RR interval refers to the average of the durations of RR1, the duration of RR2,... the duration of RRN. In addition, in order to improve the accuracy of the average RR interval calculation, the maximum and minimum values in each RR interval can be removed first, and then the average of each RR interval can be calculated.

[0086] Taking the RR time period RR7 = [R7, R8] and channel 1 as an example for illustration. Assuming that in the detection result of the R wave position of channel 1, there is a target R wave with an amplitude greater than the second threshold (for example, 0.2 mV) in the time period [R7, R8], denoted as Rx. According to the R wave type detection result of channel 1, it is judged whether the number of R waves of the same type as the target R wave detected by channel 1 is greater than the third threshold (for example, 10). If so, continue to the next step of judgment; if not, it is determined that channel 1 has not detected a valid R wave in the RR7 time period. The next step is to judge whether the RR interval meets the requirements. First, calculate the duration between the target R wave and the start point of the RR time period as the target RR interval, that is, the target RR interval = Rx - R7. Then, judge whether the target RR interval is within the interval range constructed according to the average RR interval. For example, it can be judged whether "average RR interval × 0.6 < target RR interval < average RR interval × 1.5" holds. If it holds, it means that channel 1 has detected a valid R wave in the RR7 time period; otherwise, it means that channel 1 has not detected a valid R wave in the RR7 time period.

[0087] In another embodiment of the present application, the analysis terminal device adjusts the pre-analysis R wave position detection result according to the R wave position detection results of multiple channels, including:

[0088] For each RR time period in the pre-analysis R wave position detection result, if the analysis terminal device detects that there is a target R wave that meets the preset conditions in this RR time period of the R wave position detection result of a certain channel, it further detects whether there is an R wave that meets the preset conditions within the preset time range near the target R wave in the R wave position detection results of other channels; if the ratio of the number of channels with R waves that meet the preset conditions within the preset time range near the target R wave in the R wave position detection results to the number of all channels exceeds the set threshold, an R wave is supplemented in this RR time period of the pre-analysis R wave position detection result.

[0089] For example, in the above example for the RR7 time period and channel 1, when channel 1 detects the target R wave Rx within the RR7 time period, it traverses all other channels (channels 2 - 8) to determine whether there is an R wave that meets the preset conditions within the preset time range [Rx - 150ms, Rx + 150ms], that is, whether a valid R wave is detected within the preset time range [Rx - 150ms, Rx + 150ms]. If the number of channels that detect a valid R wave within the preset time range [Rx - 150ms, Rx + 150ms] exceeds 2 / 3 or 1 / 2, it indicates that there is indeed a valid R wave within the RR7 time period, and this R wave is missed in the pre - analysis R wave position detection result. Therefore, an R wave can be added within the RR7 time period of the pre - analysis R wave position detection result to complete the adjustment. And so on, for each RR time period of the pre - analysis R wave position detection result, the missing R waves are supplemented in the same way as the RR7 time period.

[0090] In an embodiment of the present application, the analysis - end device adjusts the pre - analysis R wave type detection result according to the R wave type detection results of multiple channels, including:

[0091] For the R wave type at each position in the pre - analysis R wave type detection result, the analysis - end device adjusts the R wave type to the target type at the corresponding position in the R wave type detection results of multiple channels; where the target type is the type of the R wave of the same type with the largest number at the corresponding position in the R wave type detection results of multiple channels.

[0092] The above describes the adjustment of the pre - analysis R wave position detection result. Next, the adjustment of the pre - analysis R wave type detection result is described. For the adjustment of the pre - analysis R wave type detection result, a fusion operation of the R wave type detection results of multiple channels according to the R wave type with the largest count at the current position is performed. Specifically, the analysis - end device will respectively detect the target type of the R wave at each position in the R wave type detection results of multiple channels, and then correct the R wave type at each position in the pre - analysis R wave type detection result to the target type at the corresponding position, thereby completing the adjustment of the pre - analysis R wave type detection result. Among them, the target type is the type of the R wave of the same type with the largest number at the corresponding position.

[0093] For example, assume that for the R wave at the first position, the type of the R wave at this position detected in Channels 1 - 6 is ventricular premature beat, and the type of the R wave at this position detected in Channels 7 and 8 is normal heartbeat. Then, it can be statistically obtained that the number of R waves of the ventricular premature beat type is 6, and the number of R waves of the normal heartbeat type is 2. Then, it can be determined that the target type of the R wave at the first position after fusion is ventricular premature beat. And so on, the target type of the R wave at each position is determined respectively. If the type of the R wave at the first position in the pre - analysis R wave type detection result is not ventricular premature beat, it is adjusted to ventricular premature beat.

[0094] In an embodiment of the present application, the analysis terminal device performs re - analysis processing on the second electrocardiogram data set based on the pre - analysis result to obtain a re - analysis result, including:

[0095] (1) Determine the abnormal data time period according to the first electrocardiogram data set;

[0096] (2) Intercept the electrocardiogram data segment within the abnormal data time period from the second electrocardiogram data set;

[0097] (3) Based on the pre - analysis result, perform re - analysis processing on the electrocardiogram data segment to obtain a re - analysis result.

[0098] The data volume of the second electrocardiogram data set is very large. For 24 - hour electrocardiogram data, it may contain more than 100,000 R waves. Performing re - analysis on the positions and types of all these R waves will consume a large amount of time. To address this problem, before performing re - analysis, the abnormal data time periods in the second electrocardiogram data set can be detected first. These abnormal data time periods are the data segments most likely to have missed detection and misdetection of R waves. Therefore, only these abnormal data time periods need to be re - analyzed, rather than the entire second electrocardiogram data set, which can effectively reduce the time consumed by re - analysis.

[0099] Specifically, the analysis terminal device can analyze according to the first electrocardiogram data set to identify the abnormal data time periods most likely to have missed detection and misdetection, and then intercept the electrocardiogram data segments within the abnormal data time periods from the second electrocardiogram data set. Next, only the re - analysis processing of R wave position detection and R wave type detection needs to be performed on the intercepted electrocardiogram data segments in the manner described above. As an example, after intercepting the electrocardiogram data segments within the abnormal data time periods from the second electrocardiogram data set, the dilation - erosion algorithm can also be used to perform processing such as dilation, erosion, and removal of duplicate segments on the electrocardiogram data segments.

[0100] In an embodiment of the present application, the analysis terminal device determines the abnormal data time period according to the first electrocardiogram data set, including:

[0101] (1) The analysis terminal device generates corresponding histograms, scatter plots, and / or time scatter plots based on the first electrocardiogram data set;

[0102] (2) The analysis terminal device determines the abnormal data time period based on the generated histograms, scatter plots, and / or time scatter plots.

[0103] Specifically, the implementation method of converting the first electrocardiogram data set into corresponding histograms, scatter plots, and time scatter plots can refer to the prior art. When identifying the abnormal data time period according to the scatter plot, the core area contour of the scatter plot can be identified by the dilation and erosion algorithm, so as to find out the abnormal heartbeats as the abnormal data time period. When identifying the abnormal data time period according to the time scatter plot, the sample entropy algorithm can be used to identify the area where the signal interval changes frequently, so as to find out the abnormal heartbeats as the abnormal data time period. When identifying the abnormal data time period according to the histogram, the method of borrowing the confidence interval can be used to screen out the abnormal area, so as to find out the abnormal heartbeats as the abnormal data time period.

[0104] As Figure 5 shown, it is a schematic diagram of the overall working principle of the electrocardiogram data analysis system provided by the embodiment of the present application. In Figure 5 , the left side represents the acquisition terminal device, and the right side represents the analysis terminal device. First, the acquisition terminal device obtains the original electrocardiogram data through multi-channel electrocardiogram data acquisition and stores it locally. In addition, lead optimization operations and data compression operations are performed on the original electrocardiogram data to obtain the first electrocardiogram data set. In addition, the original electrocardiogram data is used as the second electrocardiogram data set. Then, the acquisition terminal device uploads both the first electrocardiogram data set and the second electrocardiogram data set to the analysis terminal device. The analysis terminal device performs pre-analysis processing on the first electrocardiogram data set to obtain a pre-analysis result, performs re-analysis processing such as single-channel precise analysis, multi-channel precise analysis, and interval precise analysis on the second electrocardiogram data set to obtain a re-analysis result, and uses methods such as result fusion to complete the adjustment of the pre-analysis result. Among them, single-channel precise analysis means performing precise re-analysis on the electrocardiogram data of one channel, multi-channel precise analysis means performing precise re-analysis on the electrocardiogram data of multiple channels, and interval precise analysis means performing precise re-analysis on the abnormal data segment of the intercepted second electrocardiogram data set.

[0105] As Figure 6As shown in the figure, it is a schematic diagram of the working principle of the analysis terminal device provided by the embodiment of the present application. After receiving the first electrocardiogram data set and the second electrocardiogram data set uploaded by the acquisition terminal device, the analysis terminal device performs R-wave position detection processing and R-wave type detection processing on the first electrocardiogram data set, and can output the pre-analysis R-wave position detection result and the pre-analysis R-wave type detection result in ways such as a heart rate trend graph, a scatter plot, a histogram, an electrocardiogram, a page scan graph, and an overlay graph. For the second electrocardiogram data set, after the analysis terminal device performs multi-channel R-wave position detection processing and R-wave type detection processing on the second electrocardiogram data set, it can adjust the pre-analysis R-wave position detection result and the pre-analysis R-wave type detection result respectively in the manner described above, that is, realize R-wave position adjustment and R-wave type adjustment. In addition, the images such as the heart rate trend graph, scatter plot, histogram, electrocardiogram, page scan graph, and overlay graph displayed can be updated according to the adjusted R-wave position detection result and R-wave type detection result. The analysis terminal device can also perform other types of signal analysis on the second electrocardiogram data set, such as ST analysis, QT analysis, TWA analysis, HRV / HRT / ACDC analysis, and VCG analysis. These signal analyses can be specifically started through the advanced function menu or interface of the analysis terminal device.

[0106] As Figure 7 shown in the figure, it is a schematic diagram of the operation process of the analysis terminal device provided by the embodiment of the present application for performing multi-channel global R-wave position adjustment. By pre-analyzing the first electrocardiogram data set, the analysis terminal device can obtain the pre-analysis R-wave position detection result. By globally re-analyzing the multi-channel second electrocardiogram data set, the R-wave position detection result of each channel can be obtained. Then, according to the method described above, it can be judged whether there are missing R-waves in the pre-analysis R-wave position detection result, and the corresponding R-waves can be supplemented to the pre-analysis R-wave position detection result by means of R-wave position fusion, so as to complete the adjustment of the pre-analysis R-wave position detection result.

[0107] As Figure 8 shown in the figure, it is a schematic diagram of the operation process of the analysis terminal device provided by the embodiment of the present application for performing R-wave position adjustment of abnormal data segments. By using the histogram, scatter plot, and time scatter plot corresponding to the first electrocardiogram data set, the abnormal data time period can be identified, the electrocardiogram data segment within the abnormal data time period is intercepted from the second electrocardiogram data set, and then operations such as dilation processing, duplicate segment removal processing, and erosion processing are performed on the electrocardiogram data segment. Next, only re-analysis processing is performed on this electrocardiogram data segment, and the R-wave position adjustment within the abnormal data time period of the pre-analysis R-wave position detection result is completed by using the result of the re-analysis processing.

[0108] As Figure 9As shown in the figure, it is a schematic diagram of the operation process for the analysis terminal device provided by the embodiment of the present application to perform multi-channel global R-wave type adjustment. The analysis terminal device can obtain the pre-analysis R-wave type detection result by pre-analyzing the first electrocardiogram data set. By globally re-analyzing the multi-channel second electrocardiogram data set, the R-wave type detection result of each channel can be obtained. Then, according to the method described above, the target type of the R-wave at each position can be determined, and each R-wave type in the pre-analysis R-wave type detection result can be adjusted through the R-wave type fusion method.

[0109] As Figure 10 shown in the figure, it is a schematic diagram of the operation process for the analysis terminal device provided by the embodiment of the present application to perform R-wave type adjustment for abnormal data segments. Similarly, by using the histogram, scatter plot, and time scatter plot corresponding to the first electrocardiogram data set, the abnormal data time period can be identified, the electrocardiogram data segment within the abnormal data time period can be intercepted from the second electrocardiogram data set, and then operations such as dilation processing, duplicate segment removal processing, and erosion processing are performed on the electrocardiogram data segment. Next, only the electrocardiogram data segment is re-analyzed, and using the result of the re-analysis, the R-wave type adjustment within the abnormal data time period of the pre-analysis R-wave type detection result is completed.

[0110] In summary, the embodiment of the present application proposes a method of splitting and uploading electrocardiogram data. Through the system solution of pre-analysis combined with precise re-analysis, the waiting time for medical staff to view the electrocardiogram data analysis result can be significantly reduced.

[0111] It should be understood that the magnitudes of the sequence numbers of the steps in the above respective embodiments do not mean the order of execution is prior or subsequent. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0112] The electrocardiogram data analysis method has been mainly described above. Next, the electrocardiogram data analysis device will be described.

[0113] Please refer to Figure 11 , an embodiment of an electrocardiogram data analysis device applied to a collection terminal device in the embodiment of the present application includes:

[0114] An electrocardiogram data acquisition module 301, configured to acquire a first electrocardiogram data set and a second electrocardiogram data set; wherein, the first electrocardiogram data set is disassembled from the collected original electrocardiogram data by the collection terminal device, and is the electrocardiogram data including the first signal feature of the original electrocardiogram data, and the second electrocardiogram data set is the electrocardiogram data including the second signal feature of the original electrocardiogram data; the first signal feature is a key signal feature, and the feature information amount of the second signal feature is more than that of the first signal feature;

[0115] The electrocardiogram (ECG) data sending module 302 is configured to send the first ECG data set and the second ECG data set to the analysis terminal device, so as to instruct the analysis terminal device to perform pre-analysis processing on the first ECG data set to obtain a pre-analysis result, and based on the pre-analysis result, perform re-analysis processing on the second ECG data set to obtain a re-analysis result.

[0116] In an implementation manner of the embodiment of the present application, the original ECG data includes ECG data of multiple channels; the ECG data acquisition module includes:

[0117] The peak average value calculation unit is configured to detect the average value of all signal peaks of the ECG data within a specified time period for the ECG data of each channel;

[0118] The lead optimization unit is configured to select, from the ECG data of multiple channels, the ECG data of one channel whose corresponding average value has the smallest difference from the set peak value as the first ECG data set.

[0119] Please refer to Figure 12 , an embodiment of an ECG data analysis device applied to an analysis terminal device in the embodiment of the present application includes:

[0120] The ECG data receiving module 401 is configured to receive the first ECG data set and the second ECG data set sent by the acquisition terminal device; wherein, the first ECG data set is disassembled from the acquired original ECG data by the acquisition terminal device and contains the ECG data of the first signal feature of the original ECG data, and the second ECG data set is the ECG data containing the second signal feature of the original ECG data; the first signal feature is a key signal feature, and the feature information amount of the second signal feature is more than that of the first signal feature;

[0121] The pre-analysis module 402 is configured to perform pre-analysis processing on the first ECG data set to obtain a pre-analysis result;

[0122] The re-analysis module 403 is configured to perform re-analysis processing on the second ECG data set based on the pre-analysis result to obtain a re-analysis result.

[0123] In an implementation manner of the embodiment of the present application, the pre-analysis result includes a pre-analysis R-wave position detection result and a pre-analysis R-wave type detection result, and the re-analysis result includes R-wave position detection results of multiple channels included in the second ECG data set and R-wave type detection results of multiple channels; the ECG data analysis device further includes:

[0124] The R-wave position adjustment module is configured to adjust the pre-analysis R-wave position detection result according to the R-wave position detection results of multiple channels;

[0125] The R-wave type adjustment module is used to adjust the pre-analyzed R-wave type detection result according to the R-wave type detection results of multiple channels.

[0126] In an implementation manner of the embodiment of the present application, the R-wave position adjustment module includes:

[0127] The R-wave supplement unit is used to respectively detect whether there is an R wave that meets the preset conditions within the RR time period of the R-wave position detection result of each channel for each RR time period in the pre-analyzed R-wave position detection result; if the ratio of the number of target channels included in multiple channels to the number of multiple channels is greater than the first threshold, an R wave is supplemented within the RR time period of the pre-analyzed R-wave position detection result; wherein, the RR time period is the time period between two adjacent R-wave positions in the pre-analyzed R-wave position detection result, and the target channel is the channel where there is an R wave that meets the preset conditions within the RR time period of the corresponding R-wave position detection result.

[0128] In an implementation manner of the embodiment of the present application, the R-wave supplement unit includes:

[0129] The average RR interval calculation sub-unit is used to calculate the average value of the interval durations of each R-wave position in the pre-analyzed R-wave position detection result to obtain the average RR interval;

[0130] The valid R-wave judgment sub-unit is used for each channel. If there is a target R wave with an amplitude greater than the second threshold within the RR time period of the R-wave position detection result of the channel, the number of R waves of the same type as the target R wave in the R-wave position detection result of the channel is greater than the third threshold, and the target RR interval is within the interval range constructed according to the average RR interval, it is determined that there is an R wave that meets the preset conditions within the RR time period of the R-wave position detection result of the channel; wherein, the target RR interval is the duration between the target R wave and the start point of the RR time period.

[0131] In an implementation manner of the embodiment of the present application, the R-wave type adjustment module includes:

[0132] The R-wave type adjustment unit is used to adjust the R-wave type at each position in the pre-analyzed R-wave type detection result to the target type at the corresponding position in the R-wave type detection results of multiple channels; wherein, the target type is the type of the R wave of the same type with the largest number at the corresponding position in the R-wave type detection results of multiple channels.

[0133] The embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the electrocardiogram data analysis method as shown in any of the above embodiments.

[0134] The embodiment of the present application also provides a computer program product. When the computer program product runs on a terminal device, the terminal device is enabled to execute the electrocardiogram data analysis method described in any of the above embodiments.

[0135] Figure 13 FIG. 4 is a schematic diagram of a terminal device provided by an embodiment of the present application. The terminal device may be Figure 1 the acquisition terminal device or the analysis terminal device shown in FIG. 5. As Figure 13 shown in FIG. 6, the terminal device 13 of this embodiment includes: a processor 130, a memory 131, and a computer program 132 stored in the memory 131 and executable on the processor 130. When the processor 130 executes the computer program 132, the steps in the embodiments of the above various methods are implemented. Alternatively, when the processor 130 executes the computer program 132, the functions of each module / unit in the above device embodiments are implemented.

[0136] The computer program 132 may be divided into one or more modules / units. The one or more modules / units are stored in the memory 131 and executed by the processor 130 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 132 in the terminal device 13.

[0137] The so-called processor 130 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0138] The memory 131 may be an internal storage unit of the terminal device 13, such as a hard disk or memory of the terminal device 13. The memory 131 may also be an external storage device of the terminal device 13, such as a plug-in hard disk equipped on the terminal device 13, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. Further, the memory 131 may also include both the internal storage unit and the external storage device of the terminal device 13. The memory 131 is used to store the computer program and other programs and data required by the terminal device. The memory 131 may also be used to temporarily store the data that has been output or will be output.

[0139] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment and will not be elaborated herein.

[0140] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system, device, and unit described above can refer to the corresponding process in the foregoing method embodiment and will not be elaborated herein.

[0141] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0142] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0143] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0144] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments of this application.

[0145] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0146] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above method embodiments of this application, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0147] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An electrocardiogram data analysis method, applied to an analysis terminal device, characterized in that, the method includes: Receiving a first electrocardiogram data set and a second electrocardiogram data set sent by an acquisition terminal device; wherein, the first electrocardiogram data set is disassembled from the collected original electrocardiogram data by the acquisition terminal device, and contains electrocardiogram data of the first signal feature of the original electrocardiogram data, and the second electrocardiogram data set is electrocardiogram data containing the second signal feature of the original electrocardiogram data; the first signal feature is a key signal feature, and the feature information amount of the second signal feature is more than that of the first signal feature; Performing pre-analysis processing on the first electrocardiogram data set to obtain a pre-analysis result; Based on the pre-analysis result, performing re-analysis processing on the second electrocardiogram data set to obtain a re-analysis result.

2. The method according to claim 1, characterized in that, the performing re-analysis processing on the second electrocardiogram data set based on the pre-analysis result to obtain a re-analysis result includes: Determining an abnormal data time period according to the first electrocardiogram data set; Intercepting an electrocardiogram data segment within the abnormal data time period from the second electrocardiogram data set; Based on the pre-analysis result, performing re-analysis processing on the electrocardiogram data segment to obtain the re-analysis result.

3. The method according to claim 2, characterized in that, the pre-analysis result includes a pre-analysis R wave position detection result and a pre-analysis R wave type detection result, and the re-analysis result includes R wave position detection results of multiple channels included in the second electrocardiogram data set and R wave type detection results of the multiple channels; After obtaining the re-analysis result, the method further includes: Adjusting the pre-analysis R wave position detection result according to the R wave position detection results of the multiple channels; Adjusting the pre-analysis R wave type detection result according to the R wave type detection results of the multiple channels.

4. The method according to claim 3, characterized in that, the adjusting the pre-analysis R wave position detection result according to the R wave position detection results of the multiple channels includes: For each RR time period in the pre-analysis R wave position detection result, respectively detecting whether there is an R wave satisfying a preset condition within the RR time period of the R wave position detection result of each channel; if the ratio of the number of target channels included in the multiple channels to the number of the multiple channels is greater than a first threshold, then supplementing an R wave within the RR time period of the pre-analysis R wave position detection result; wherein, the RR time period is the time period between two adjacent R wave positions in the pre-analysis R wave position detection result, and the target channel is the channel where there is an R wave satisfying the preset condition within the RR time period of the corresponding R wave position detection result.

5. The method according to claim 4, characterized in that, the respectively detecting whether there is an R wave satisfying a preset condition within the RR time period of the R wave position detection result of each channel includes: Calculating the average value of the interval durations of each R wave position in the pre-analysis R wave position detection result to obtain an average RR interval; For each of the channels, if there is a target R wave with an amplitude greater than a second threshold within the RR time period of the R wave position detection result of the channel, the number of R waves of the same type as the target R wave in the R wave position detection result of the channel is greater than a third threshold, and the target RR interval is within the interval range constructed based on the average RR interval, it is determined that there is an R wave satisfying the preset condition within the RR time period of the R wave position detection result of the channel; wherein, the target RR interval is the duration between the target R wave and the start point of the RR time period.

6. The method according to any one of claims 3 to 5, characterized in that the adjusting of the pre-analysis R wave type detection result according to the R wave type detection results of the multiple channels includes: for the R wave type at each position in the pre-analysis R wave type detection result, adjusting the R wave type to the target type at the corresponding position in the R wave type detection results of the multiple channels; wherein, the target type is the type of the R waves of the same type with the largest number at the corresponding position in the R wave type detection results of the multiple channels.

7. An electrocardiogram data analysis method, applied to a collection end device, characterized in that the method includes: obtaining a first electrocardiogram data set and a second electrocardiogram data set; wherein, the first electrocardiogram data set is disassembled from the collected original electrocardiogram data by the collection end device and includes the electrocardiogram data with the first signal feature of the original electrocardiogram data, and the second electrocardiogram data set is the electrocardiogram data including the second signal feature of the original electrocardiogram data; the first signal feature is a key signal feature, and the feature information amount of the second signal feature is more than that of the first signal feature; sending the first electrocardiogram data set and the second electrocardiogram data set to an analysis end device to instruct the analysis end device to perform pre-analysis processing on the first electrocardiogram data set to obtain a pre-analysis result, and based on the pre-analysis result, perform re-analysis processing on the second electrocardiogram data set to obtain a re-analysis result.

8. The method according to claim 7, characterized in that the original electrocardiogram data includes electrocardiogram data of multiple channels; the first electrocardiogram data set is obtained by the following method: for the electrocardiogram data of each of the channels, detecting the average value of all signal peaks of the electrocardiogram data within a specified time period; selecting the electrocardiogram data of one channel corresponding to the smallest difference between the average value and the set peak value from the electrocardiogram data of the multiple channels as the first electrocardiogram data set.

9. An analysis end device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program, it implements the electrocardiogram data analysis method according to any one of claims 1 to 6.

10. A collection end device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program, it implements the electrocardiogram data analysis method according to claim 7 or 8.

11. An electrocardiogram data analysis system, characterized in that, it includes a collection end device and an analysis end device; The collection end device is used to obtain a first electrocardiogram data set and a second electrocardiogram data set, and send the first electrocardiogram data set and the second electrocardiogram data set to the analysis end device; wherein, the first electrocardiogram data set is disassembled from the collected original electrocardiogram data by the collection end device, and is an electrocardiogram data containing the first signal feature of the original electrocardiogram data, and the second electrocardiogram data set is an electrocardiogram data containing the second signal feature of the original electrocardiogram data; the first signal feature is a key signal feature, and the feature information amount of the second signal feature is more than that of the first signal feature; The analysis end device is used to receive the first electrocardiogram data set and the second electrocardiogram data set, perform pre-analysis processing on the first electrocardiogram data set to obtain a pre-analysis result; based on the pre-analysis result, perform re-analysis processing on the second electrocardiogram data set to obtain a re-analysis result.

12. A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, it implements the electrocardiogram data analysis method described in any one of claims 1 to 6, or implements the electrocardiogram data analysis method described in claim 7 or 8.

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