Method and device for determining reference value of electrocardio data, and computer device

Abstract

The application relates to a reference value determination method and device of electrocardio data, a computer device, a storage medium and a computer program product. The method comprises the following steps: obtaining target electrocardio data collected in a collection time period, the target electrocardio data containing a plurality of heartbeat data units, each heartbeat data unit being composed of a plurality of heartbeat data segments. A heartbeat data segment to be detected is determined from the plurality of heartbeat data segments, and a target parameter matched with the heartbeat data segment to be detected is determined. A calculation mode of a reference value is determined, and a target test mode corresponding to the calculation mode is determined from a plurality of preset test modes; wherein the calculation mode comprises at least one of an automatic calculation mode and a manual calculation mode. The reference value of the target electrocardio data under the target parameter is calculated based on the target test mode. In this way, the accuracy of the reference value of the electrocardio data is greatly improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus, computer equipment, storage medium, and computer program product for determining the reference value of electrocardiogram (ECG) data. Background Technology

[0002] With the development of data processing technology, in order to detect ventricular abnormalities, it is often necessary to obtain the electrocardiogram (ECG) of the ventricle to be tested, and then perform data analysis on the data in the ECG to determine whether the ventricle to be tested is abnormal.

[0003] In traditional techniques, custom testing methods are often used to analyze the electrocardiogram (ECG) data of the ventricle being tested in order to determine its condition. However, the baseline data determined by a single testing method is insufficient for accurately analyzing ECG data under different conditions. In other words, this single testing method cannot adapt to different abnormal situations and is prone to misjudging the ECG condition of the ventricle being tested. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer device, computer-readable storage medium, and computer program product for determining the reference value of electrocardiogram data in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for determining the baseline values ​​of electrocardiogram (ECG) data. The method includes:

[0006] Acquire target electrocardiogram (ECG) data collected within the acquisition time period. The target ECG data includes multiple heartbeat data units, and each heartbeat data unit consists of multiple heartbeat data segments.

[0007] The heartbeat data segment to be detected is determined from multiple heartbeat data segments, and the target parameters that match the heartbeat data segment to be detected are determined.

[0008] A calculation mode for the baseline value is determined, and a target test mode corresponding to the calculation mode is determined from multiple preset test modes; wherein, the calculation mode includes at least one of an automatic calculation mode and a manual calculation mode;

[0009] Based on the target testing method, the baseline values ​​of the target parameters of the target electrocardiogram data are calculated.

[0010] Secondly, this application also provides a reference value determination device for electrocardiogram (ECG) data. The device includes:

[0011] The acquisition module is used to acquire target electrocardiogram data collected within the acquisition time period. The target electrocardiogram data includes multiple heartbeat data units, and each heartbeat data unit is composed of multiple heartbeat data segments.

[0012] The determination module is used to determine the heartbeat data segment to be detected from multiple heartbeat data segments, and to determine the target parameters that match the heartbeat data segment to be detected.

[0013] The determining module is further configured to determine the calculation mode of the benchmark value and determine the target test mode corresponding to the calculation mode from a plurality of preset test modes; wherein, the calculation mode includes at least one of an automatic calculation mode and a manual calculation mode;

[0014] The calculation module is used to calculate the baseline value of the target parameter of the target electrocardiogram data based on the target testing method.

[0015] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0016] Acquire target electrocardiogram (ECG) data collected within the acquisition time period. The target ECG data includes multiple heartbeat data units, and each heartbeat data unit consists of multiple heartbeat data segments.

[0017] The heartbeat data segment to be detected is determined from multiple heartbeat data segments, and the target parameters that match the heartbeat data segment to be detected are determined.

[0018] A calculation mode for the baseline value is determined, and a target test mode corresponding to the calculation mode is determined from multiple preset test modes; wherein, the calculation mode includes at least one of an automatic calculation mode and a manual calculation mode;

[0019] Based on the target testing method, the baseline values ​​of the target parameters of the target electrocardiogram data are calculated.

[0020] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0021] Acquire target electrocardiogram (ECG) data collected within the acquisition time period. The target ECG data includes multiple heartbeat data units, and each heartbeat data unit consists of multiple heartbeat data segments.

[0022] The heartbeat data segment to be detected is determined from multiple heartbeat data segments, and the target parameters that match the heartbeat data segment to be detected are determined.

[0023] A calculation mode for the baseline value is determined, and a target test mode corresponding to the calculation mode is determined from multiple preset test modes; wherein, the calculation mode includes at least one of an automatic calculation mode and a manual calculation mode;

[0024] Based on the target testing method, the baseline values ​​of the target parameters of the target electrocardiogram data are calculated.

[0025] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0026] Acquire target electrocardiogram (ECG) data collected within the acquisition time period. The target ECG data includes multiple heartbeat data units, and each heartbeat data unit consists of multiple heartbeat data segments.

[0027] The heartbeat data segment to be detected is determined from multiple heartbeat data segments, and the target parameters that match the heartbeat data segment to be detected are determined.

[0028] A calculation mode for the baseline value is determined, and a target test mode corresponding to the calculation mode is determined from multiple preset test modes; wherein, the calculation mode includes at least one of an automatic calculation mode and a manual calculation mode;

[0029] Based on the target testing method, the baseline values ​​of the target parameters of the target electrocardiogram data are calculated.

[0030] The aforementioned method, apparatus, computer equipment, storage medium, and computer program product for determining the baseline value of electrocardiogram (ECG) data acquires target ECG data within a specific time period and identifies the heartbeat data segment to be detected, thereby accurately locating the target parameter corresponding to the baseline value. By selecting a target test method compatible with the calculation mode from multiple preset test methods, it ensures that different calculation modes have corresponding target test methods, avoiding the inability of a single test method to adapt to the current calculation mode. This ensures the effectiveness and accuracy of the test, avoids misjudging the ECG condition reflected by the target ECG data, and greatly improves the accuracy of ECG condition assessment. Attached Figure Description

[0031] Figure 1 This is a flowchart illustrating a method for determining the baseline value of electrocardiogram (ECG) data in one embodiment;

[0032] Figure 2 This is a schematic diagram of a central camera data unit in one embodiment;

[0033] Figure 3 This is a flowchart illustrating the steps for determining the target testing method in one embodiment;

[0034] Figure 4 This is a schematic diagram illustrating the determination of a benchmark value using a first mean determination method in one embodiment;

[0035] Figure 5 This is a schematic diagram illustrating the determination of a baseline value using a second mean determination method in one embodiment;

[0036] Figure 6 This is a schematic diagram illustrating the determination of the benchmark value using the second mean determination method in another embodiment;

[0037] Figure 7 This is a schematic diagram illustrating how the probability distribution determines the baseline value in one embodiment.

[0038] Figure 8 This is a schematic diagram illustrating the determination of a baseline value when an event occurs in one embodiment.

[0039] Figure 9 This is a schematic diagram illustrating the method of determining a baseline value using a trend chart test in one embodiment.

[0040] Figure 10 This is a structural block diagram of a reference value determination device for electrocardiogram data in one embodiment;

[0041] Figure 11 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0043] In one embodiment, such as Figure 1 As shown, a method for determining the baseline value of electrocardiogram (ECG) data is provided. This embodiment illustrates the application of this method to a terminal. It is understood that this method can also be applied to a server, and further to a system including both a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0044] Step S102: Obtain the target electrocardiogram data collected during the collection period. The target electrocardiogram data includes multiple heartbeat data units, and each heartbeat data unit is composed of multiple heartbeat data segments.

[0045] The target ECG data (i.e., ECG signal) is a sequence of heartbeats within the acquisition time period, which is a continuously changing waveform. This waveform is a curve showing the change of voltage over time. The heartbeat data unit is the smallest unit constituting the target ECG data, and its structure is as follows: Figure 2As shown. This heartbeat data unit can be considered as a normal waveform. This heartbeat data unit contains multiple waves, such as the P wave (reflecting the potential changes during depolarization of the left and right atria), the QRS complex (which includes the Q wave, R wave, and S wave, reflecting the electrical excitation process of the left and right ventricles), the T wave (corresponding to the potential changes during ventricular myocardial repolarization), and the U wave (possibly reflecting the changes in potential and time after myocardial excitation). Multiple heartbeat data segments are determined according to the time of initiation of each wave, such as the ST segment and QT segment.

[0046] Specifically, during the data acquisition period, the ECG data acquisition device collects target ECG data through the body surface. The terminal then acquires the target ECG data sent by the ECG data acquisition device. The ECG data acquisition device can be an electrocardiograph or a portable wearable device; there is no specific limitation.

[0047] For example, during the data collection period, the electrocardiograph collects target ECG data through lead electrodes deployed at different collection sites, or by using electrodes placed close to the smartwatch to acquire target ECG data. Collection sites include the left upper limb, right upper limb, left lower limb, right lower limb, and chest, among others, with no specific limitation.

[0048] Step S104: Determine the heartbeat data segment to be detected from multiple heartbeat data segments, and determine the target parameters that match the heartbeat data segment to be detected.

[0049] Among them, such as Figure 2 As shown, a heartbeat data unit contains multiple heartbeat data segments, such as the ST segment and the QT segment. The ST segment is the signal segment between the end of the QRS complex and the beginning of the T wave. Specifically, the ST segment is a horizontal line from the end of the QRS complex to the beginning of the T wave. Figure 2 The dashed line 2 in the diagram represents the ST segment, which reflects the slow repolarization process of the ventricle. The QT segment is the signal segment from the beginning of the QRS complex to the end of the T wave. The ECG data reflects the voltage changes over time, involving both voltage and time parameters.

[0050] Specifically, the terminal identifies the heartbeat data segment to be detected from among the multiple heartbeat data segments that constitute the heartbeat data unit. Based on the various parameters that constitute the electrocardiogram data, the terminal determines the target parameters that match the heartbeat data segment to be detected.

[0051] It's important to note that during ECG data analysis, abnormalities in different parameters can lead to anomalies in the corresponding heartbeat data segments. For example, an abnormality in the voltage parameter's baseline offset (i.e., the baseline value of the voltage parameter) will cause abnormalities such as ST segment elevation or depression (i.e., the ST segment being above or below the isoelectric line). An abnormality in the time parameter's baseline interval (i.e., the baseline value of the time parameter) will cause abnormalities such as QT segment delay or shortening. In other words, different parameters are examined for different heartbeat data segments. For example, for the ST segment, the voltage within that segment is examined, specifically the voltage value at the flat line between the end of the QRS complex and the beginning of the T wave. For the QT segment, the time interval of the QT segment is examined, i.e., the length of time from the beginning of the QRS complex to the end of the T wave.

[0052] Step S106: Determine the calculation mode of the benchmark value, and determine the target test mode corresponding to the calculation mode from multiple preset test modes; wherein, the calculation mode includes at least one of automatic calculation mode and manual calculation mode.

[0053] The calculation mode involves processing ECG data. The automatic calculation mode automatically selects the target test method and completes the calculation accordingly. The manual calculation mode involves manually selecting the target test method and automatically completing the calculation. The reference value represents the standard offset of the target parameter. If the heartbeat data segment to be tested is the ST segment, the reference value is the ST offset reference voltage; if the heartbeat data segment to be tested is the QT segment, the reference value is the reference interval.

[0054] Specifically, the terminal determines the calculation mode of the benchmark value. The terminal selects the target preset test mode corresponding to the calculation mode from multiple preset test modes, and selects the target test mode corresponding to the target parameter from multiple target preset test modes.

[0055] It should be noted that the types and number of preset test methods differ in different calculation modes. Specifically, the automatic calculation mode corresponds to a first set of preset test methods with a first number of preset test methods, while the manual calculation mode corresponds to a second set of preset test methods with a second number of preset test methods. The first set and the second set are not the same. Therefore, given a calculation mode, the set corresponding to that calculation mode can be automatically determined, and the preset test methods contained in that set can be used as the target preset test methods.

[0056] For example, if the terminal only has an automatic calculation mode, the terminal directly determines this as the automatic calculation mode. The terminal selects the preset test mode corresponding to the automatic calculation mode from multiple preset test modes and uses this preset test mode as the target preset test mode. Based on the target ECG data, the terminal determines the target test mode corresponding to the target parameters from multiple target preset test modes.

[0057] Alternatively, if the terminal only has a manual calculation mode, the terminal directly determines that the calculation mode as manual calculation mode. The terminal selects the preset test mode corresponding to the manual calculation mode from multiple preset test modes, and uses the preset test mode corresponding to the manual calculation mode as the target preset test mode. Then, it determines the target test mode corresponding to the target parameters from multiple target preset test modes.

[0058] Alternatively, if the terminal includes an automatic calculation mode and a manual calculation mode, the terminal responds to a data processing instruction, determines the calculation mode based on the data processing instruction, selects a target preset test mode corresponding to the calculation mode from multiple preset test modes, and selects a target test mode corresponding to the target parameters from multiple target preset test modes.

[0059] It should be noted that the terminal may only have an automatic calculation mode or a manual calculation mode, or it may include both automatic and manual calculation modes; there is no specific limitation.

[0060] Step S108: Based on the target testing method, calculate the baseline value of the target parameter of the target ECG data.

[0061] Specifically, the terminal tests the target ECG data according to the target testing method to obtain the baseline value of the target parameter. When an event corresponding to the target parameter is detected, the baseline value is updated to determine the validity of the event. If the event is determined to be valid, a valid determination result is given, which is used to instruct staff to implement the corresponding response measures.

[0062] The event can be either an ST event or a QT event, with no specific limitation. An ST event refers to whether the ST segment is elevated or depressed, while a QT event refers to whether the QT interval is prolonged or shortened. The QT interval is the duration of the QT segment. The response can be a therapeutic action or a drug injection.

[0063] For example, when the target parameter is voltage, the terminal tests the target ECG data according to the target testing method to obtain a baseline voltage value. Based on each heartbeat data unit in the target ECG data, the terminal determines ST events (ST segment elevation or depression). If an ST event occurs in a heartbeat data unit, the baseline voltage value is updated to obtain an updated baseline value. This updated baseline value is used to effectively determine ST events. If no ST event occurs, the baseline voltage value is used to assess the ECG status of the ventricle being tested.

[0064] In the aforementioned method for determining the baseline value of ECG data, the target ECG data within the acquisition time period is obtained, and the heartbeat data segment to be detected is determined, thereby accurately locating the target parameter corresponding to the baseline value. By selecting a target test method compatible with the calculation mode from multiple preset test methods, it is ensured that different calculation modes have corresponding target test methods, avoiding the inability of a single test method to adapt to the current calculation mode. This ensures the effectiveness and accuracy of the test, avoids misjudging the ECG condition reflected by the target ECG data, and greatly improves the accuracy of ECG condition assessment.

[0065] In one embodiment, such as Figure 3 As shown, when the calculation mode is automatic, the target test method corresponding to the calculation mode is determined from multiple preset test methods, including:

[0066] Step S302: Determine the offset of the target parameter corresponding to each heartbeat data unit, and determine the probability distribution curve and standard deviation based on the offset of the target parameter corresponding to each heartbeat data unit.

[0067] Where the target parameter is voltage, this offset is the voltage difference between the baseline and the horizontal line where the ST segment is located, that is, the voltage difference between the baseline voltage and the horizontal line voltage. Figure 2 As shown, the baseline voltage is the voltage value where the dashed line 1 is located, and the horizontal line voltage is the voltage value where the dashed line 2 is located. When the target parameter is time, this offset is the QT interval, that is, the length of time from the start of the QRS band to the end of the T wave.

[0068] Specifically, the terminal determines a preset value for each heartbeat data unit, which can be the baseline voltage or the start time of the QRS band for each heartbeat data unit. The terminal determines a target value for each heartbeat data unit, which can be the baseline voltage or the end time of the T wave. The terminal calculates the difference between each target value and the preset value, using the difference as the offset of the target parameter. The terminal calculates the probability distribution of each offset to obtain a probability distribution curve. The terminal calculates the standard deviation of each offset to obtain the standard deviation.

[0069] For example, if the target parameter is voltage, the terminal determines the baseline of each heartbeat data unit and the baseline voltage corresponding to that baseline. Figure 2 The ISO point (i.e., the ISO point, which is a point on the baseline (i.e., dashed line 1) has a voltage value equal to the baseline voltage. The terminal determines the horizontal voltage corresponding to each heartbeat data unit. For example... Figure 2 The ST point (i.e., the ST point, which is a point on the horizontal line of the ST segment) has a voltage value equal to the ST point. For any heartbeat data unit, the offset (i.e., the absolute ST offset) Amp can be calculated using the following formula:

[0070] Amp=V(ST point)–V(ISO point)

[0071] Where V(ST point) is the line voltage and V(ISO point) is the baseline voltage. The terminal calculates the probability distribution of each offset to obtain the probability distribution curve. The terminal then calculates the standard deviation of each offset to obtain the standard deviation.

[0072] With time as the target parameter, the terminal determines the start time of the QRS complex and the end time of the T wave in each heartbeat data unit based on the target ECG data. For each heartbeat data unit, the terminal uses the time difference between the end time of the T wave and the start time of the QRS complex corresponding to that heartbeat data unit as the offset of that heartbeat data unit. The terminal calculates the probability distribution of each offset to obtain a probability distribution curve; the terminal also calculates the standard deviation of each offset to obtain the standard deviation.

[0073] Step S304: Based on the probability distribution curve and the standard deviation, determine the target test method corresponding to the target parameter from multiple preset test methods; wherein, the multiple preset test methods include a first mean determination method, a second mean determination method, and a probability distribution determination method.

[0074] Both the first and second mean determination methods involve mean calculation. The first mean determination method calculates the mean based on the entire data collection period, reflecting the baseline value reflected by the overall data. The second mean determination method calculates the mean for each target time period within the data collection period, reflecting the real-time nature of the baseline value. The probability distribution determination method is a calculation method for determining the baseline value based on a probability distribution curve.

[0075] Specifically, the terminal determines the frequency of each offset using a probability distribution curve, obtaining a frequency determination result. The terminal then determines the variability of each offset using the standard deviation, obtaining a variability determination result. Based on at least one of the frequency determination result and the variability determination result, the terminal determines the target test method from multiple preset test methods corresponding to the automatic calculation mode.

[0076] The offset can be voltage or time period. Specifically, the voltage can be the voltage amplitude. The frequency determination analyzes the numerical distribution of all offsets. If the frequency determination passes, it indicates that most offset values ​​are the same. If it fails, it indicates that the numerical distribution of the offsets is not concentrated. The variability determination analyzes the fluctuation of the offset values. If the variability determination passes, it reflects that the numerical changes of each offset are gradual; if it fails, it reflects that the numerical changes of each offset are drastic.

[0077] For example, the terminal determines the frequency of each offset using a probability distribution curve, obtaining a frequency determination result. If the frequency determination result is satisfactory, the terminal determines the target testing method as the probability distribution testing method. If the frequency determination result is unsatisfactory, the terminal determines the variability of each offset based on the standard deviation, obtaining a variability determination result. If the variability determination result is satisfactory, the target detection method is determined as the first mean determination method; otherwise, the target detection method is determined as the second mean determination method.

[0078] In this embodiment, frequency determination using probability distribution curves accurately reflects the distribution of each offset value and precisely determines whether the offset values ​​are concentrated. Variation determination using standard deviation effectively identifies the changes in each offset value. Thus, based on at least one of the frequency determination and variation determination results, a target testing method suitable for the ECG condition reflected by the target ECG data can be accurately determined. This effectively improves the accuracy of the baseline value determination, thereby enabling accurate judgment of the ECG condition.

[0079] In one embodiment, determining the target test method corresponding to the target parameter from multiple preset test methods based on the probability distribution curve and the standard deviation includes: determining the maximum value of the probability distribution from the probability distribution curve, and determining a first threshold corresponding to the probability distribution curve and a second threshold corresponding to the standard deviation. If the maximum value of the probability distribution is greater than or equal to the first threshold, the target test method is determined as a probability distribution determination method. If the maximum value of the probability distribution is less than the first threshold and the standard deviation is less than the second threshold, the target test method is determined as a first mean determination method. If the maximum value of the probability distribution is less than the first threshold and the standard deviation is greater than or equal to the second threshold, the target test method is determined as a second mean determination method.

[0080] The first threshold and the second threshold are different thresholds. The first threshold is the threshold for the probability distribution, and the second threshold is the threshold for the standard deviation.

[0081] Specifically, the terminal determines the maximum value of the probability distribution from the probability distribution curve, and determines a first threshold corresponding to the probability distribution curve and a second threshold corresponding to the standard deviation. The terminal compares the maximum value of the probability distribution with the first threshold to determine frequency. If the maximum value of the probability distribution is greater than or equal to the first threshold, the frequency determination result is determined to be passed, and the terminal determines the target test method as a probability distribution determination method. If the maximum value of the probability distribution is less than the first threshold, the frequency determination result is determined to be failed. The terminal compares the standard value with the second threshold to determine variability. If the standard value is less than the second threshold, the variability determination result is determined to be passed, and the terminal determines the target test method as a first mean determination method. If the maximum value of the probability distribution is less than the first threshold, the variability determination result is determined to be failed, and the target test method is determined to be a second mean determination method.

[0082] In this embodiment, frequency determination of each offset using probability distribution curves allows for a preliminary analysis of the offset distribution. If the frequency determination result is satisfactory, indicating a concentrated offset distribution, the probability distribution test method processed through the probability distribution curve is directly used as the target test method, accurately reflecting the actual ECG condition of the ventricle being tested. If the frequency determination result is unsatisfactory, indicating a dispersed offset distribution, further analysis of the offset value fluctuations is conducted using variability determination. If the variability determination result is satisfactory, the first mean determination method can effectively reflect the baseline value within each target time period. If the variability determination result is unsatisfactory, reflecting drastic offset value changes (high volatility), it is necessary to determine the baseline value for the target time period in real time. In this case, the second mean determination method can better reflect the baseline value within each target time period. It is worth noting that if the variability determination result is satisfactory, reflecting a relatively smooth offset value change, the baseline value corresponding to the entire acquisition period can be determined. Thus, the first mean determination method can accurately reflect the actual ECG condition. Therefore, based on the probability distribution curve and standard value, the offset can be determined at least once to identify the target test method that matches the actual ECG situation.

[0083] In one embodiment, when the target testing method is a first mean determination method, calculating the reference value of the target parameter of the target ECG data based on the target testing method includes: performing noise detection on the target ECG data to determine the target start time corresponding to the target ECG data; wherein the target start time characterizes the start time when the target ECG data is a normal waveform; determining a preset time period after the target start time, the preset time period including at least one heartbeat data unit; determining a first offset of the target parameter corresponding to the heartbeat data unit, and using the average of each first offset as the reference value of the target parameter of the target ECG data.

[0084] Specifically, the terminal sequentially performs noise detection on the heartbeat data units in the target ECG data according to time sequence, obtaining noise detection results corresponding to each time point. Based on each noise detection result, the terminal determines the target start time corresponding to the target ECG data. Based on the target start time, the terminal determines a preset time period from the acquisition time period corresponding to the target ECG data. The initial time of this preset time period can be any time after the target start time. The terminal determines the first offset of the target parameter in each heartbeat data unit within the preset time period, and calculates the average of each first offset to obtain the baseline value of the target parameter of the target ECG data.

[0085] Among them, noise detection is the detection method that compares the noise of the signal with a noise threshold.

[0086] For example, the terminal compares the noise of the target ECG data at each time point with a noise threshold to obtain the noise detection result corresponding to each time point. When there are multiple consecutive detection times with noise less than the noise threshold, and the detection time period formed by the multiple consecutive detection times exceeds the threshold time period, the starting time of the multiple consecutive detection times is taken as the target starting time. Based on the target starting time, the terminal filters a preset time period from the acquisition time period corresponding to the target ECG data. The initial time of the preset time period is after the target starting time, for example, the 10th second after the target starting time is taken as the initial time. The preset time period can be the time period between the 10th second and the 30th second after the target starting time. The terminal determines the detection value corresponding to each heartbeat data unit within the preset time period. The detection value is the flat voltage corresponding to the heartbeat data unit or the T wave end time corresponding to the heartbeat data unit. The terminal calculates the difference between each detection value and the preset value to obtain the first offset of the target parameter of each heartbeat data unit, and calculates the average of each first offset to obtain the reference value of the target parameter of the target ECG data. For example, Figure 4 As shown, the portion within the box represents the electrocardiogram (ECG) data for a preset time period.

[0087] It should be noted that the terminal uses the baseline value obtained by averaging the first offsets as the baseline value for the entire acquisition period.

[0088] In this embodiment, noise detection of the target ECG data allows for preliminary screening, preventing noise from affecting the effective information of the target ECG data. This noise detection identifies time periods with high signal-to-noise ratios (SNR), thereby determining each high SNR heartbeat data unit and ensuring the validity of the baseline value determination. When the target test method is the first mean determination method, i.e., the offset value changes relatively smoothly, the baseline value within the preset time period with high SNR can be directly used as the baseline value corresponding to the entire acquisition time period, ensuring the validity and accuracy of the baseline value, and thus enabling accurate judgment of the ECG condition.

[0089] In one embodiment, when the target testing method is a second mean determination method, calculating the baseline value of the target parameter of the target ECG data based on the target testing method includes: determining a first target time period, wherein the target ECG data within the first target time period represents a normal waveform; determining a first sub-time period within the first target time period, wherein the first sub-time period is shorter than the first target time period and the start time of the first sub-time period is the same as the start time of the first target time period; acquiring each heartbeat data unit within the first sub-time period, and based on a second offset of the target parameter corresponding to each heartbeat data unit; and using the average of the second offsets as the baseline value of the target parameter of the target ECG data within the first target time period.

[0090] Specifically, the terminal divides the data collection period into multiple first target time periods, each with a duration greater than a time threshold. The terminal determines a first sub-time period within each first target time period, where the sub-time period is shorter than the first target time period and its start time is the same as the start time of the first target time period. The terminal determines the cardiac beat data units within each first sub-time period. The terminal determines the detection value corresponding to each cardiac beat data unit. The terminal calculates the difference between each detection value and a first preset value to obtain a second offset of the target parameter corresponding to each cardiac beat data unit. The terminal calculates the average of each second offset to obtain the baseline value of the target parameter for the target ECG data within the first target time period.

[0091] The detected value is either the baseline voltage corresponding to the heartbeat data unit or the end time of the T wave corresponding to the heartbeat data unit. The first preset value is either the baseline voltage within each heartbeat data unit or the start time of the QRS band within each heartbeat data unit.

[0092] For example, such as Figure 5As shown, the terminal determines a first time length and divides the acquisition time period into intervals based on this first time length to obtain various first target time periods. The interval division can be a uniform interval or an arbitrary interval division; no specific limitation is imposed. The length of each first target time period is the first time length, and this first time length is greater than a time threshold length (e.g., 20 seconds). The terminal uses the first time threshold length within each first target time period as the first sub-time period, such as using the first 20 seconds of each first target time period as the first sub-time period. The terminal determines each heartbeat data unit within each first sub-time period. The terminal determines the detection value corresponding to each heartbeat data unit; this detection value is either the flat voltage corresponding to the heartbeat data unit or the T-wave end time corresponding to the heartbeat data unit. If the target parameter is voltage, the difference between the flat voltage corresponding to each heartbeat data unit and the baseline voltage is calculated to obtain the second offset. If the target parameter is time, the difference between the T-wave end time corresponding to each heartbeat data unit and the QRS band start time is calculated to obtain the second offset. The terminal calculates the average of each second offset to obtain the baseline value of the target parameter of the target ECG data within the first target time period.

[0093] In this embodiment, when the target test method is the second mean determination method, the numerical change reflecting the offset is fluctuating. Therefore, by determining the first target time period at regular intervals, timely updates to the benchmark value are achieved, ensuring the accuracy and real-time nature of the benchmark value, thereby enabling an accurate and reasonable judgment of the electrocardiogram status.

[0094] In one embodiment, when the target test method is a second mean determination method, calculating the reference value of the target parameter of the target ECG data based on the target test method includes: determining the start time of a second target time period, wherein the target ECG data within the second target time period represents a normal waveform; determining a preset time interval, and based on the second target time period and the time interval, determining a second heartbeat data unit at the preset time interval before or after the second target time period; determining a third offset of the target parameter of the second heartbeat data unit, and using the third offset as the reference value of the target parameter of the target ECG data within the second target time period.

[0095] Specifically, the terminal divides the data collection period into multiple second target time periods, with an interval between adjacent second target time periods. The terminal determines the start time of each second target time period and the preset time interval corresponding to each second target time period. For each second target time period, the terminal uses the heartbeat data unit located before the second start time of the corresponding second target time period and at a preset time interval from the corresponding second target time period as the second heartbeat data unit corresponding to the corresponding second target time period. The terminal determines the third offset of each second heartbeat data unit. For each second target time period, the terminal uses the third offset of the second heartbeat data unit corresponding to the corresponding second target time period as the reference value of the corresponding second target time period.

[0096] For example, such as Figure 6 As shown, the terminal divides the data collection period into three target time periods: second target time period A, second target time period B, and second target time period C. The interval between any two adjacent second target time periods is equal. Taking second target time period A as an example, the terminal determines the start time t1 (not shown in the figure) of second target time period A and, based on t1, determines the second beat data unit a corresponding to second target time period A. The time difference between the end time of the second beat data unit and the start time of the second target time period A is a preset time interval. The terminal determines the detection value of the second beat data unit a, which is either the flat voltage corresponding to the second beat data unit a or the T-wave end time corresponding to the second beat data unit. If the target parameter is voltage, the difference between the flat voltage corresponding to the second beat data unit a and the baseline voltage is calculated to obtain the third offset. If the target parameter is time, the difference between the T-wave end time and the QRS band start time corresponding to each second beat data unit is calculated to obtain the third offset. The terminal directly uses the third offset as the reference value for the target parameter within the second target time period A.

[0097] It should be noted that the target time period in step S304 above can be either the first target time period or the second target time period.

[0098] In this embodiment, when the target test method is the second mean determination method, the numerical change reflecting the offset is fluctuating. Therefore, by determining the second target time period at regular intervals, the baseline value is updated in a timely manner, ensuring the accuracy and real-time nature of the baseline value, thereby reflecting the actual electrocardiogram situation in real time and accurately.

[0099] In one embodiment, when the target test method is a probability distribution method, calculating the baseline value of the target parameter of the target ECG data based on the target test method includes: determining the offset of the target parameter corresponding to the maximum value of the probability distribution in the probability distribution curve, and using the offset of the target parameter corresponding to the maximum value of the probability distribution as the baseline value of the target parameter of the target ECG data.

[0100] Specifically, when the target test method is a probability distribution, the offset corresponding to the maximum value of the probability distribution curve is directly determined as the benchmark value of the target parameter of the target ECG data.

[0101] It should be noted that when the target testing method is a probability distribution, it reflects the concentrated distribution of the offset values ​​corresponding to the overall target ECG data, indicating that most offset values ​​are the same. Therefore, the offset value corresponding to the maximum value of the probability distribution appears most frequently.

[0102] For example, such as Figure 7 As shown, when the target parameter is voltage, the terminal determines each heartbeat data unit in the target ECG data (i.e., the heartbeat sequence in the figure), determines the baseline of each heartbeat data unit, and determines the baseline voltage corresponding to the baseline. The terminal determines the horizontal voltage corresponding to each heartbeat data unit. For each heartbeat data unit, the difference between the baseline voltage and the horizontal voltage corresponding to the corresponding heartbeat data unit is used as the offset, i.e., the ST absolute offset. Based on each offset, the terminal determines a probability distribution curve (i.e., the ST offset probability distribution curve in the figure). The terminal takes the offset corresponding to the maximum probability distribution value in the probability distribution curve as the ST offset reference voltage for the target ECG data.

[0103] Accordingly, with time as the target parameter, the start time of the QRS complex and the end time of the T wave in each heartbeat data unit are determined. For each heartbeat data unit, the terminal uses the time difference between the end time of the T wave and the start time of the QRS complex corresponding to the heartbeat data unit as the offset of the corresponding heartbeat data unit, i.e., the QT interval. Based on each offset, the terminal determines the probability distribution curve of the QT interval, and uses the offset corresponding to the maximum probability value in the probability distribution curve as the QT baseline interval for that target ECG data.

[0104] In this embodiment, when the target test method is a probability distribution, the numerical distribution of the offset is determined to be concentrated. In this way, the offset corresponding to the maximum value of the probability distribution is directly determined as the benchmark value of the target ECG data under the target parameters, which can truly and accurately reflect the actual ECG situation.

[0105] In one embodiment, the method further includes: upon detecting the occurrence of an event corresponding to the target parameter, determining the event heartbeat data unit corresponding to the time of the event occurrence; determining adjacent heartbeat data units that are either preceding or following the event heartbeat data unit, and determining a fourth offset of the target parameter for the adjacent heartbeat data units; and using the fourth offset as an update reference value for the target parameter within the event occurrence time period.

[0106] The event can be either a ST event or a QT event, with no specific limitation. An ST event refers to whether the ST segment rises or falls, while a QT event refers to whether the QT interval of the QT segment lengthens or shortens. The QT interval is the time period of the QT segment.

[0107] Specifically, the terminal acquires pre-set event determination conditions and, based on these conditions, performs event determination on each heartbeat data unit in the target ECG data, obtaining the event determination result corresponding to each heartbeat data unit. If the event determination result indicates that an event has occurred, the terminal determines the heartbeat data unit corresponding to the time of the event occurrence. The terminal determines the adjacent heartbeat data units preceding or following the event heartbeat data unit and determines the fourth offset of the target parameter for that adjacent heartbeat data unit. The terminal updates this fourth offset to an update reference value, which represents the reference value of the target parameter within the event occurrence time period.

[0108] Among them, the event determination conditions can be determined by numerical values ​​based on the baseline value, by event duration based on the event time, or by a combination of numerical and event time determination; there is no specific limitation.

[0109] For example, the terminal acquires a baseline value and an event time period threshold. The terminal determines the detection offset in each heartbeat data unit within the target ECG data, compares each detection offset with the baseline value, and obtains a numerical judgment result for each heartbeat data unit. The terminal adds the heartbeat data units whose detection offsets exceed the baseline value to a statistical list. Based on each heartbeat data unit in this statistical list, the terminal determines the event duration. If the event duration is greater than the event time period threshold, an event corresponding to the target parameter is determined to have occurred.

[0110] For example, when the target parameter is voltage, such as Figure 8As shown, if an ST rise event or ST fall event occurs, the event heartbeat data unit M corresponding to the time of the event is determined. The terminal determines the adjacent heartbeat data unit N adjacent to the event heartbeat data unit M, and determines the adjacent baseline voltage and adjacent flat line voltage in the adjacent heartbeat data unit. The terminal updates the difference between the adjacent baseline voltage and the adjacent flat line voltage as an update reference value, which represents the reference value of the target parameter during the event occurrence time period.

[0111] Alternatively, if the target parameter is time, and a QT interval delay event or a QT interval shortening event occurs, the terminal determines the event heartbeat data unit X corresponding to the time of the event occurrence, and determines the adjacent heartbeat data unit Y adjacent to the event heartbeat data unit X. The difference between the start time of the adjacent QRS band and the end time of the adjacent T wave in the adjacent heartbeat data unit Y is updated as the update reference value. The update reference value represents the reference value of the target parameter within the time period of the event occurrence.

[0112] In this embodiment, when an event corresponding to the target parameter is detected, the adjacent heartbeat data units prior to the event occurrence time are used as the evaluation standard, and the baseline value can be updated in real time according to this evaluation standard. This avoids misjudging the actual ECG condition based on the baseline value of the target parameter, ensuring an effective and accurate assessment of the actual ECG condition.

[0113] In one embodiment, after updating the baseline value of the target parameter based on the offset of the target parameter of the adjacent heartbeat data unit to obtain the updated baseline value, the method further includes: determining the event determination condition corresponding to the event, and performing a valid verification on the event based on the updated baseline value and the event determination condition. When the valid verification determines that an event has occurred, the event is determined to be a valid event.

[0114] Specifically, the terminal updates the baseline value in the event determination conditions to an updated baseline value, resulting in updated event determination conditions. The updated event determination conditions involve numerical determination based on the updated baseline value and temporal determination based on the event duration. The terminal then performs valid verification on each heartbeat data unit in the statistical list based on these updated event determination conditions. If the valid verification determines that an event has occurred, the event corresponding to the target parameter is determined to be a valid event. If the valid verification determines that no event has occurred, the event corresponding to the target parameter is determined to be an invalid event.

[0115] For example, the terminal determines the offset corresponding to each heartbeat data unit in the statistical list. The terminal compares this offset with the update baseline value to obtain the comparison result. Based on the comparison result, the terminal updates the heartbeat data units in the statistical list to obtain the updated heartbeat data units. Based on each updated heartbeat data unit, the terminal updates the event duration to obtain the updated event duration. If the updated duration is greater than or equal to the event time period threshold, the event corresponding to the target parameter is determined to be a valid event. If the updated duration is less than the event time period threshold, the event corresponding to the target parameter is determined to be an invalid event.

[0116] In this embodiment, the event is validated based on the updated baseline value and event determination conditions to determine whether a false positive has occurred, i.e., whether the event is a valid event. If the validation determines that an event has occurred, the event is valid, allowing for timely corresponding measures. If the validation determines that no event has occurred, the event is invalid, avoiding the need to process invalid events. This ensures that the actual electrocardiographic condition of the ventricle being tested can be handled reasonably and promptly.

[0117] In one embodiment, when the calculation mode is a manual calculation mode, determining the target test mode corresponding to the calculation mode from a plurality of preset test modes includes: determining at least one test mode from a first mean determination mode, a second mean determination mode, a probability distribution determination mode, an event determination mode, and a trend chart test mode as the target test mode.

[0118] The event determination method involves determining a reference value based on the adjacent heartbeat data units adjacent to the event heartbeat data unit when an event is detected (e.g., ...). Figure 8 and Figure 8 (The method described in the related content). This trend chart testing method is a way to customize the baseline value by using a trend chart composed of all offsets.

[0119] Specifically, in manual calculation mode, the terminal receives a method determination instruction generated by a staff member's trigger operation. Based on the identifier carried in the method determination instruction, it determines at least one test method from among the first mean determination method, the second mean determination method, the probability distribution determination method, the event determination method, and the trend chart test method as the target test method. Each test method has a corresponding identifier.

[0120] In manual calculation mode, any test method can be selected as the target test method, or any test method can be selected as the first test method from the first mean determination method, the second mean determination method, the probability distribution determination method, and the trend chart test method. The combination method is determined based on the first test method and the event determination method to determine the target test method.

[0121] It should be noted that if this combination method is used as the target test method, the baseline value of the target parameter is determined based on the first test method, and then the baseline value is updated based on the event determination method to obtain the updated baseline value.

[0122] For example, the terminal receives a first mode determination instruction generated by an operation triggered by a staff member, and based on the identifier carried by the first mode determination instruction, selects the trend chart test mode as the target test mode. The terminal calculates the offset of all heartbeat data units within the acquisition period, and obtains a trend chart based on each offset, such as... Figure 9 As shown in the diagram, the terminal displays the trend graph to instruct staff to set a baseline value based on it. For example, staff might use 0.05mV as the baseline value based on the trend graph.

[0123] Alternatively, the terminal receives a first mode determination instruction generated by an operation triggered by a staff member, and determines a first mean determination mode and an event determination mode as the target test mode based on the identifier carried by the first mode determination instruction. The terminal first determines a baseline value according to the first mean determination mode. Based on this baseline value, it determines whether an event has occurred. If an event has occurred, the terminal updates the baseline value according to the event determination mode. Specifically, updating the baseline value according to the event determination mode involves: determining the event heartbeat data unit corresponding to the time the event occurred; determining the adjacent heartbeat data units adjacent to the event heartbeat data unit, and determining the offset of the target parameter of the adjacent heartbeat data units; and updating the baseline value of the target parameter based on the offset of the target parameter of the adjacent heartbeat data units to obtain an updated baseline value, which represents the baseline value of the target parameter within the time period of the event.

[0124] In this embodiment, when the calculation mode is manual, an instruction is determined by receiving a trigger operation from the staff, and at least one test method is selected as the target test method from among the first mean determination method, the second mean determination method, the probability distribution determination method, the event determination method, and the trend chart test method. In this way, during actual use, staff can manually select the target test method corresponding to their needs, allowing for flexible and timely adjustment of the target test method, greatly improving the user experience.

[0125] To better understand the technical solution of this application, a more detailed embodiment is provided for description. The terminal in this embodiment can be an intelligent device for determining electrocardiogram (ECG) data baseline values. The terminal includes an automatic calculation mode and a method calculation mode. The specific process for determining the target parameter baseline value is as follows:

[0126] Step 1: During the acquisition period, the ECG data acquisition device collects target ECG data through the body surface. The terminal acquires the target ECG data sent by the ECG data acquisition device. The terminal determines the heartbeat data segment to be detected from the multiple heartbeat data segments that constitute the heartbeat data unit. Based on the various parameters constituting the ECG data, the terminal determines the target parameters that match the heartbeat data segment to be detected.

[0127] Step 2.1: In automatic calculation mode, the terminal determines a preset value for each heartbeat data unit. This preset value can be the baseline voltage or the start time of the QRS band for each heartbeat data unit. The terminal determines the target value for each heartbeat data unit. This target value can be the baseline voltage or the end time of the T wave. The terminal calculates the difference between each target value and the preset value, using the difference as the offset of the target parameter. The terminal calculates the probability distribution of each offset to obtain a probability distribution curve. The terminal calculates the standard deviation of each offset to obtain the standard deviation. The terminal determines the maximum value of the probability distribution from the probability distribution curve and determines the first threshold corresponding to the probability distribution curve and the second threshold corresponding to the standard deviation. The terminal compares the maximum value of the probability distribution with the first threshold to determine the frequency. If the maximum value of the probability distribution is greater than or equal to the first threshold, the frequency determination result is determined to be passed, and the terminal determines that the target test method is the probability distribution determination method. If the maximum value of the probability distribution is less than the first threshold, the frequency determination result is determined to be failed. The terminal compares the standard value with the second threshold to determine variability. If the standard value is less than the second threshold, the variability determination result is deemed successful, and the terminal determines the target test method as the first mean determination method. If the maximum value of the probability distribution is less than the first threshold, the variability determination result is deemed unsuccessful, and the target test method is determined as the second mean determination method.

[0128] Step 2.2: When the target test method is the first mean determination method, the terminal sequentially performs noise detection on the heartbeat data units in the target ECG data according to the time sequence, obtaining the noise detection results corresponding to each time point. Based on each noise detection result, the terminal determines the target start time corresponding to the target ECG data. Based on the target start time, the terminal determines a preset time period from the acquisition time period corresponding to the target ECG data. The initial time of this preset time period can be any time after the target start time. The terminal determines the first offset of the target parameter in each heartbeat data unit and calculates the mean of each first offset to obtain the baseline value of the target parameter of the target ECG data.

[0129] Step 2.2: When the target test method is the second mean determination method, the terminal divides the collection time period into multiple first target time periods, each with a duration greater than a time threshold. The terminal determines a first sub-time period within each first target time period, where the first sub-time period is shorter than the first target time period and its start time is the same as the start time of the first target time period. The terminal determines the heartbeat data units within each first sub-time period. The terminal determines the detection value corresponding to each heartbeat data unit. The terminal calculates the difference between each detection value and a first preset value to obtain the second offset of the target parameter corresponding to each heartbeat data unit. The terminal calculates the average of each second offset to obtain the baseline value of the target parameter of the target ECG data within the first target time period.

[0130] Alternatively, if the target test method is the second mean determination method, the terminal divides the collection time period into multiple second target time periods, where there is an interval between two adjacent second target time periods. The terminal determines the start time of each second target time period and determines the preset time interval corresponding to each second target time period. For each second target time period, the terminal takes the heartbeat data unit located before the second start time of the corresponding second target time period and at a preset time interval from the corresponding second target time period as the second heartbeat data unit corresponding to the corresponding second target time period. The terminal determines the third offset of each second heartbeat data unit. For each second target time period, the terminal takes the third offset of the second heartbeat data unit corresponding to the corresponding second target time period as the reference value of the corresponding second target time period.

[0131] Step 2.3: When the target test method is a probability distribution method, directly determine the offset corresponding to the maximum value of the probability distribution curve as the benchmark value of the target parameter of the target ECG data.

[0132] Step 2.4: The terminal acquires pre-set event determination conditions and, based on these conditions, performs event determination on each heartbeat data unit in the target ECG data, obtaining the event determination result corresponding to each heartbeat data unit. If the event determination result indicates that an event has occurred, the terminal determines the heartbeat data unit corresponding to the time of the event occurrence. The terminal determines the adjacent heartbeat data units preceding or following the event heartbeat data unit and determines the fourth offset of the target parameter for that adjacent heartbeat data unit. The terminal updates this fourth offset to an update reference value, which represents the reference value of the target parameter within the event occurrence time period. The terminal updates the reference value in the event determination conditions to the updated reference value, obtaining the updated event determination conditions. The terminal performs valid verification on each heartbeat data unit in the statistical list according to the updated event determination conditions. If the valid verification determines that an event has occurred, the event corresponding to the target parameter is determined to be a valid event. If the valid verification determines that no event has occurred, the event corresponding to the target parameter is determined to be an invalid event.

[0133] Step 3: In manual calculation mode, the terminal receives a method determination instruction generated by the operator's trigger operation. Based on the identifier carried in the method determination instruction, it determines at least one test method from among the first mean determination method, the second mean determination method, the probability distribution determination method, the event determination method, and the trend graph test method as the target test method. The terminal then calculates the baseline value of the target parameter for the target ECG data according to the target test method.

[0134] In this embodiment, by acquiring target ECG data within the acquisition time period and determining the heartbeat data segment to be detected, the target parameter corresponding to the benchmark value can be accurately located. By selecting a target test method compatible with the calculation mode from multiple preset test methods, it is ensured that different calculation modes have corresponding target test methods. This avoids the situation where a single test method cannot adapt to the current calculation mode, ensuring the effectiveness and accuracy of the test, preventing misjudgments of the ECG status reflected by the target ECG data, and greatly improving the accuracy of ECG status assessment. Furthermore, in the process of determining the benchmark value according to the automatic calculation mode, the amount of manual work is reduced, improving the ease of operation.

[0135] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0136] Based on the same inventive concept, this application also provides a reference value determination device for electrocardiogram (ECG) data to implement the aforementioned method for determining reference values ​​of ECG data. The solution provided by this device is similar to the implementation described in the above method. Therefore, the specific limitations in one or more ECG data reference value determination device embodiments provided below can be found in the limitations of the ECG data reference value determination method described above, and will not be repeated here.

[0137] In one embodiment, such as Figure 10 As shown, a device for determining the reference value of electrocardiogram (ECG) data is provided, comprising: an acquisition module 1002, a determination module 1004, and a calculation module 1006, wherein:

[0138] The acquisition module 1002 is used to acquire target electrocardiogram data collected during the acquisition time period. The target electrocardiogram data includes multiple heartbeat data units, and each heartbeat data unit is composed of multiple heartbeat data segments.

[0139] The determination module 1004 is used to determine the heartbeat data segment to be detected from multiple heartbeat data segments, and to determine the target parameters that match the heartbeat data segment to be detected.

[0140] The determining module 1004 is also used to determine the calculation mode of the benchmark value and to determine the target test mode corresponding to the calculation mode from a plurality of preset test modes; wherein, the calculation mode includes at least one of automatic calculation mode and manual calculation mode.

[0141] The calculation module 1006 is used to calculate the baseline value of the target parameter of the target electrocardiogram data based on the target test method.

[0142] In one embodiment, when the calculation mode is automatic calculation mode, the determining module 1004 is used to determine the offset of the target parameter corresponding to each heartbeat data unit, and based on the offset of the target parameter corresponding to each heartbeat data unit, determine the probability distribution curve and standard deviation. Based on the probability distribution curve and the standard deviation, a target test method corresponding to the target parameter is determined from multiple preset test methods; wherein, the multiple preset test methods include a first mean determination method, a second mean determination method, and a probability distribution determination method.

[0143] In one embodiment, the determining module 1004 is configured to determine the maximum value of the probability distribution from the probability distribution curve, and to determine a first threshold corresponding to the probability distribution curve and a second threshold corresponding to the standard deviation. If the maximum value of the probability distribution is greater than or equal to the first threshold, the target testing method is determined to be a probability distribution determination method. If the maximum value of the probability distribution is less than the first threshold and the standard deviation is less than the second threshold, the target testing method is determined to be a first mean determination method. If the maximum value of the probability distribution is less than the first threshold and the standard deviation is greater than or equal to the second threshold, the target testing method is determined to be a second mean determination method.

[0144] In one embodiment, when the target test method is a first mean determination method, the calculation module 1006 is used to perform noise detection on the target ECG data and determine the target start time corresponding to the target ECG data; wherein, the target start time represents the start time when the target ECG data is a normal waveform. A preset time period after the target start time is determined, the preset time period including at least one heartbeat data unit. A first offset of the target parameter corresponding to the heartbeat data unit is determined, and the average of the first offsets is used as the reference value of the target parameter of the target ECG data.

[0145] In one embodiment, when the target test method is a second mean determination method, the calculation module 1006 is used to determine a first target time period, within which the target electrocardiogram (ECG) data represents a normal waveform. A first sub-time period is determined within the first target time period, wherein the first sub-time period is shorter than the first target time period and its start time is the same as the start time of the first target time period. Each heartbeat data unit within the first sub-time period is acquired, and a second offset of the target parameter corresponding to each heartbeat data unit is calculated. The mean value calculated from each of the second offsets is used as the reference value of the target parameter of the target ECG data within the first target time period.

[0146] In one embodiment, when the target test method is a second mean determination method, the calculation module 1006 is used to determine the start time of the second target time period, wherein the target electrocardiogram data within the second target time period represents a normal waveform. A preset time interval is determined, and a second heartbeat data unit is determined at the preset time interval before or after the second target time period. A third offset of the target parameter of the second heartbeat data unit is determined, and the third offset is used as a reference value for the target parameter of the target electrocardiogram data within the second target time period.

[0147] In one embodiment, when the target test method is a probability distribution method, the calculation module 1006 is used to determine the offset of the target parameter corresponding to the maximum value of the probability distribution in the probability distribution curve, and use the offset of the target parameter corresponding to the maximum value of the probability distribution as the reference value of the target parameter of the target electrocardiogram data.

[0148] In one embodiment, the calculation module 1006 is further configured to, upon detecting the occurrence of an event corresponding to the target parameter, determine the event heartbeat data unit corresponding to the time of the event occurrence; determine the adjacent heartbeat data units that are before or after the event heartbeat data unit; and determine a fourth offset of the target parameter for the adjacent heartbeat data units. The fourth offset is used as the update reference value of the target parameter within the event occurrence time period.

[0149] In one embodiment, the calculation module 1006 is further configured to determine the event determination condition corresponding to the event, and perform a valid verification on the event based on the updated baseline value and the event determination condition. When the valid verification determines that an event has occurred, the event is determined to be a valid event.

[0150] In one embodiment, the determining module 1004 is further configured to determine at least one test method from the first mean determination method, the second mean determination method, the probability distribution determination method, the event determination method, and the trend chart test method as the target test method.

[0151] The modules in the aforementioned ECG data baseline determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0152] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 11As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores baseline data for determining electrocardiogram (ECG) data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for determining baseline values ​​of ECG data.

[0153] Those skilled in the art will understand that Figure 11 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0154] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0155] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0156] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0157] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0158] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0159] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0160] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining the reference value of electrocardiogram (ECG) data, characterized in that, The method includes: Acquire target electrocardiogram (ECG) data collected within the acquisition time period. The target ECG data includes multiple heartbeat data units, and each heartbeat data unit consists of multiple heartbeat data segments. The heartbeat data segment to be detected is determined from multiple heartbeat data segments, and the target parameters that match the heartbeat data segment to be detected are determined. A calculation mode for the baseline value is determined, and a target test mode corresponding to the calculation mode is determined from multiple preset test modes; wherein, the calculation mode includes at least one of an automatic calculation mode and a manual calculation mode; Based on the target testing method, the baseline values ​​of the target parameters of the target electrocardiogram data are calculated; wherein, the plurality of preset testing methods include a first mean determination method, a second mean determination method, and a probability distribution determination method; If an event corresponding to the target parameter is detected, the event heartbeat data unit corresponding to the time of the event occurrence is determined; Determine the adjacent heartbeat data unit that is adjacent to the front or back of the event heartbeat data unit, and determine the fourth offset of the target parameter of the adjacent heartbeat data unit; The fourth offset is used as the update reference value for the target parameter during the event occurrence period.

2. The method according to claim 1, characterized in that, When the calculation mode is automatic calculation mode, determining the target test mode corresponding to the calculation mode from multiple preset test modes includes: Determine the offset of the target parameter corresponding to each heartbeat data unit, and based on the offset of the target parameter corresponding to each heartbeat data unit, determine the probability distribution curve and standard deviation; Based on the probability distribution curve and the standard deviation, the target test method corresponding to the target parameter is determined from multiple preset test methods.

3. The method according to claim 2, characterized in that, The step of determining the target test method corresponding to the target parameter from multiple preset test methods based on the probability distribution curve and the standard deviation includes: Determine the maximum value of the probability distribution from the probability distribution curve, and determine the first threshold corresponding to the probability distribution curve and the second threshold corresponding to the standard deviation; If the maximum value of the probability distribution is greater than or equal to the first threshold, the target testing method is determined to be a probability distribution determination method; If the maximum value of the probability distribution is less than the first threshold and the standard deviation is less than the second threshold, the target testing method is determined to be the first mean determination method. If the maximum value of the probability distribution is less than the first threshold and the standard deviation is greater than or equal to the second threshold, the target testing method is determined to be the second mean determination method.

4. The method according to claim 1, characterized in that, When the target testing method is the first mean determination method, calculating the baseline value of the target parameter of the target ECG data based on the target testing method includes: Noise detection is performed on the target ECG data to determine the target start time corresponding to the target ECG data; wherein, the target start time represents the start time when the target ECG data is a normal waveform; A preset time period is determined after the target start time, and the preset time period includes at least one heartbeat data unit; A first offset of the target parameter corresponding to the heartbeat data unit is determined, and the average of each first offset is used as the reference value of the target parameter of the target ECG data.

5. The method according to claim 1, characterized in that, When the target testing method is the second mean determination method, the step of calculating the baseline value of the target parameter of the target ECG data based on the target testing method includes: A first target time period is determined, and the target electrocardiogram data within the first target time period represents a normal waveform. Determine a first sub-time period within a first target time period, wherein the first sub-time period is shorter than the first target time period and the start time of the first sub-time period is the same as the start time of the first target time period; Obtain each heartbeat data unit within the first sub-time period, and based on the second offset of the target parameter corresponding to each heartbeat data unit; The average value calculated from each of the second offsets is used as the benchmark value of the target parameter of the target electrocardiogram data within the first target time period.

6. The method according to claim 1, characterized in that, When the target testing method is the second mean determination method, the step of calculating the baseline value of the target parameter of the target ECG data based on the target testing method includes: Determine the start time of the second target time period, and the target electrocardiogram data within the second target time period represent normal waveforms; Determine a preset time interval, and determine the second heartbeat data unit at the preset time interval before or after the second target time period; A third offset of the target parameter of the second heartbeat data unit is determined, and the third offset is used as the reference value of the target parameter of the target ECG data within the second target time period.

7. The method according to claim 2, characterized in that, When the target testing method is the probability distribution method, calculating the baseline value of the target parameter of the target ECG data based on the target testing method includes: Determine the offset of the target parameter corresponding to the maximum value of the probability distribution in the probability distribution curve, and use the offset of the target parameter corresponding to the maximum value of the probability distribution as the reference value of the target parameter of the target electrocardiogram data.

8. The method according to any one of claims 1 to 7, characterized in that, After using the fourth offset as the update reference value of the target parameter within the event occurrence time period, the method further includes: Determine the event determination conditions corresponding to the event, and perform effective verification of the event based on the updated baseline value and the event determination conditions; When the valid verification determines that an event has occurred, the event is determined to be a valid event.

9. The method according to claim 1, characterized in that, When the calculation mode is the manual calculation mode, determining the target test mode corresponding to the calculation mode from multiple preset test modes includes: Choose at least one testing method from the following: first mean determination method, second mean determination method, probability distribution determination method, event determination method, and trend chart testing method, as the target testing method.

10. A device for determining the reference value of electrocardiogram (ECG) data, characterized in that, The device includes: The acquisition module is used to acquire target electrocardiogram data collected within the acquisition time period. The target electrocardiogram data includes multiple heartbeat data units, and each heartbeat data unit is composed of multiple heartbeat data segments. The determination module is used to determine the heartbeat data segment to be detected from multiple heartbeat data segments, and to determine the target parameters that match the heartbeat data segment to be detected. The determining module is further configured to determine the calculation mode of the benchmark value and determine the target test mode corresponding to the calculation mode from a plurality of preset test modes; wherein, the calculation mode includes at least one of an automatic calculation mode and a manual calculation mode; The calculation module is used to calculate the baseline value of the target parameter of the target electrocardiogram data based on the target testing method; when an event corresponding to the target parameter is detected, determine the event heartbeat data unit corresponding to the time of the event occurrence; determine the adjacent heartbeat data unit that is adjacent to the event heartbeat data unit before or after it, and determine the fourth offset of the target parameter of the adjacent heartbeat data unit; and use the fourth offset as the update baseline value of the target parameter within the time period of the event occurrence.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.

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

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

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