Abnormal electrocardiogram acquisition point monitoring and processing method and system

Abstract

The invention relates to the technical field of electrocardiogram monitoring, in particular to an abnormal electrocardiogram acquisition point monitoring processing method and system, and the method comprises the steps: generating corresponding acquisition time points and reading time points in each sampling period based on an action time setting rule, and generating read-back interval time corresponding to the interval between the acquisition time points and the reading time points; acquiring electrocardio data in each sampling period, and storing the electrocardio data in a register after digital-to-analog conversion; triggering an acquisition task based on the acquisition time point so as to sample electrocardiogram data in a register and define the electrocardiogram data as an acquisition point; triggering a reading task based on the reading time point so as to read back the electrocardio data in the corresponding register, and defining the electrocardio data as a read-back point; and judging whether the data contents of the acquisition points and the read-back points in the same sampling period are the same or not, and screening and processing abnormal points based on a judgment result. The method has the effect of reducing the influence caused by abnormal electrocardiogram data recognition due to the conflict between the Bluetooth task and the collection task.

Description

Technical Field

[0001] The present application relates to the technical field of electrocardiogram (ECG) monitoring, and in particular to a method and system for monitoring and processing abnormal ECG acquisition points. Background Art

[0002] The Holter recorder has the functions of pacing detection and wireless transmission. The implementation of pacing detection requires sampling of ECG signals. The sampling frequency usually cannot be lower than a certain threshold. Wireless transmission uses the Bluetooth protocol, which has very high timing requirements. During the execution of the application in the main control, the Bluetooth protocol stack will periodically interrupt the current task, jump to execute the Bluetooth task, and then jump back after completion. Since the execution time of the Bluetooth task is very short, it has basically no impact on general application scenarios.

[0003] However, when the Bluetooth SOC collects ECG signals, it needs to perform an ECG collection task every period of time, and the collection action must be completed within the specified time. If the Bluetooth task conflicts with the collection task, the Bluetooth task will be executed first due to its higher priority. When the Bluetooth task is completed and jumps back to the collection task, the remaining time is not enough to complete a normal collection action, which will eventually lead to abnormal sampled ECG data. The abnormal data will cause the pacing detection algorithm to misidentify, posing a major safety hazard. Summary of the Invention

[0004] In order to reduce the impact of abnormal ECG data identification caused by conflicts between Bluetooth tasks and collection tasks, the present application provides a method and system for monitoring and processing abnormal ECG collection points.

[0005] In a first aspect, the present application provides a method for monitoring and processing abnormal ECG acquisition points, which adopts the following technical solutions: A method for monitoring and processing abnormal electrocardiogram (ECG) collection points, comprising the following steps: Generate corresponding acquisition time points and reading time points in each sampling period based on the action time setting rule, wherein the acquisition time points and reading time points are separated by a corresponding readback interval time; Acquire electrocardiogram data in each sampling period and store it in a register after performing digital-to-analog conversion; triggering an acquisition task based on the acquisition time point to acquire the electrocardiogram data in the register and defining the acquired data as an acquisition point; Triggering a reading task based on the reading time point to read back the ECG data in the corresponding register and defining the result as a read-back point; It is determined whether the data contents of the acquisition point and the read-back point in the same sampling period are the same, and abnormal points are screened and processed based on the determination result.

[0006] In some embodiments, generating corresponding acquisition time points and reading time points in each sampling period based on the action time setting rule includes the following steps: Obtain the number of abnormal points that occur in a preset time period and the timestamps corresponding to each abnormal point, and generate an interval setting strategy based on the number and the timestamps, wherein the interval setting strategy includes symmetric, asymmetric, and golden window strategies; If the number of the abnormal points is not greater than the first threshold, the interval setting strategy is the symmetrical strategy; If the number of the abnormal points is greater than a first threshold and the timestamps do not have repetitiveness, the interval setting strategy is asymmetric; If the number of the abnormal points is greater than the first threshold and the timestamps are repetitive, the interval setting strategy is a golden window strategy.

[0007] In some embodiments, obtaining the number of abnormal points occurring in a preset time period and the timestamp corresponding to each abnormal point, and generating an interval setting strategy based on the number and the timestamp, further includes the following steps: In the symmetrical formula, the acquisition time point and the read time point are placed on both sides symmetrical to the midpoint of the cycle, and the standard action duration is configured towards the midpoint of the cycle to obtain an acquisition segment and a readback segment. The time length between the acquisition segment and the readback segment is defined as the readback interval. In the asymmetric formula, the acquisition time point and the read time point are set on both sides of the cycle midpoint, reducing the time distance between the acquisition time point and the starting point of the sampling cycle, and reducing the time distance between the read time point and the cycle midpoint. The standard action duration is respectively configured toward the cycle midpoint to obtain an acquisition segment and a readback segment. The time length between the acquisition segment and the readback segment is defined as the readback interval. In the golden window format, the timestamps of the repeated abnormal points are defined as conflict times, a golden window excluding the conflict times is divided in the sampling period, the acquisition segment and the readback segment are set in the golden window based on the time length and continuity of the golden window, and the time length between the acquisition segment and the readback segment is defined as the readback interval time.

[0008] In some embodiments, determining whether the data contents of the acquisition points and the readback points in the same sampling period are identical, and filtering and processing abnormal points based on the determination result include the following steps: If the data content of the acquisition point and the data content of the readback point in the same sampling period are the same, the data content is retained and defined as valid acquisition; If the data contents of the acquisition point and the data contents of the read-back point in the same sampling period are different, the data content in the sampling period is defined as an abnormal point and is removed.

[0009] In some embodiments, determining whether the data contents of the acquisition points and the readback points in the same sampling period are identical, and filtering and processing abnormal points based on the determination result further includes the following steps: Determine whether the standard action duration is less than the readback time interval; If so, rereading the ECG data in the register during the readback time interval to generate a verification point; When the data contents of the acquisition point and the readback point in the same sampling period are different, the data content corresponding to the verification point is compared with the acquisition point and the readback point respectively; If there is a match, the data content with the same match is retained and defined as valid collection; If there is no such a comparison, the data content in the sampling period is defined as an abnormal point and removed.

[0010] In some embodiments, acquiring ECG data in each sampling period and storing it in a register after digital-to-analog conversion includes the following steps: Setting a first buffer zone and a second buffer zone in the register; Get the number of leads and set an identity tag for each lead; Based on the standard lead sequence, the digital-to-analog converted electrocardiogram data is stored in the corresponding register address in the first buffer according to the identity tag mapping; Based on the reorganized lead sequence, the digital-to-analog converted ECG data is stored in the corresponding register address in the second buffer according to the identity tag mapping; In the standard lead sequence and the reorganized lead sequence, the identity labels corresponding to the leads in the first half and the second half are different.

[0011] In some embodiments, triggering a collection task and a reading task, determining whether the data contents of the collection points and the readback points in the same sampling period are the same, and filtering and processing abnormal points based on the determination results include the following steps: collecting the electrocardiogram data in the second buffer at the collection time point to obtain a recombined sequence; Reading the electrocardiogram data in the first buffer at the reading time point to obtain a standard sequence; Adjusting the order of the recombined sequence based on the standard lead sequence during the readback interval to obtain a verification sequence corresponding to the standard sequence; After the standard sequence is read, the verification sequence and the standard sequence are compared, and the abnormal points are screened based on the comparison results.

[0012] In some embodiments, screening outliers based on the judgment results and processing them includes the following steps: Determine the proportion of failed leads based on the comparison of the data content, where the proportion of failed leads is represented by the ratio of the number of leads that failed comparison to the total number of leads; If the proportion of failed leads is greater than a preset value, the abnormal points in the sampling period are removed; If the proportion of failed leads is not greater than a preset value, the ECG data segments corresponding to the failed leads in the abnormal points are reconstructed.

[0013] In some of these embodiments, In a second aspect, the present application provides an abnormal ECG acquisition point monitoring and processing system, which adopts the following technical solutions: An abnormal electrocardiogram (ECG) acquisition point monitoring and processing system is provided for implementing the above method.

[0014] The technical solutions provided in the embodiments of this application can achieve the following technical effects: The Bluetooth SOC performs two reading actions in each reading cycle and compares the ECG data contents read twice. If the two are completely consistent, the reading is considered successful. If they are inconsistent, the reading is considered abnormal. This effectively judges and eliminates the "singularity" generated in the collected data, reduces ECG data monitoring abnormalities caused by abnormal ECG data collection, and reduces safety risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 1 is a schematic diagram of the steps of the abnormal ECG acquisition point monitoring and processing method provided in this embodiment.

[0016] Figure 2 This is a simplified schematic diagram of the sampling period corresponding to different action time setting rules in the embodiment of the present application.

[0017] Figure 3 It is a simplified schematic diagram of the sampling period corresponding to the redundant verification in the embodiment of the present application.

[0018] Figure 4 This is a waveform diagram before abnormal point processing in an embodiment of the present application.

[0019] Figure 5 This is a waveform diagram after abnormal points are processed in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to more clearly understand the purpose, technical solutions and advantages of the present application, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. However, it should be understood by those skilled in the art that the present application can be implemented without these details. In some cases, in order to avoid unnecessary descriptions that make various aspects of the present application obscure, the well-known methods, processes, systems, components and / or circuits that have been described at a higher level will not be described in detail. It is obvious to those skilled in the art that various changes can be made to the embodiments disclosed in the present application, and the general principles defined in the present application can be applied to other embodiments and application scenarios without departing from the principles and scope of the present application. Therefore, the present application is not limited to the embodiments shown, but conforms to the broadest scope consistent with the scope claimed for protection in the present application.

[0021] It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0022] In the description of this application, "several" means one or more, "many" means more than two, "greater than," "less than," and "exceed" are understood to exclude the number itself, while "above," "below," and "within" are understood to include the number itself. The use of "first" and "second" in the description is solely for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance, implicitly specifying the number of the indicated technical features, or implicitly specifying the order of the indicated technical features.

[0023] In the description of this application, reference to the terms "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of this application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any combination in one or more embodiments or examples.

[0024] like Figure 1 As shown, the embodiment of the present application discloses a method for monitoring and processing abnormal ECG acquisition points, comprising the following steps: S100 , generating corresponding collection time points and reading time points in each sampling period based on an action time setting rule, with the collection time points and the reading time points separated by a corresponding readback interval time.

[0025] When used in an ECG recorder, it needs to regularly collect and subsequently analyze the user's ECG data according to a certain collection cycle. In order to avoid the Bluetooth SOC being affected by other Bluetooth tasks with higher priority when it normally needs to collect ECG data, this application uses an ECG AFE chip to change the one-time reading action in the existing technology into two readings. The first reading is used to collect ECG data, and the second reading is used to read back the ECG data. Since the ECG data read each time should be exactly the same data, the consistency of the data collected twice can be used to determine whether there is an abnormal reading point.

[0026] Therefore, it is necessary to first configure the collection time point corresponding to the corresponding collection action in each sampling cycle, and at the same time configure the reading time point corresponding to the second reading action.

[0027] At the same time, the Bluetooth SOC requires a certain response time for each reading. In order to avoid reading abnormalities due to insufficient response time during the two reading actions, a certain time interval needs to be set between the two readings, that is, the read-back interval time.

[0028] Then a sampling cycle includes three time segments: the acquisition action time segment with the acquisition time point as the starting point - the readback interval time - the reading time segment with the reading time point as the starting point.

[0029] S200 , acquiring ECG data in each sampling period and storing it in a register after performing digital-to-analog conversion.

[0030] The ADC within the ECG AFE chip samples the ECG signal at an 8kHz frequency (i.e., completing an analog-to-digital conversion every 125μs). The sampled ECG data is stored in registers. The sampled ECG data is a fixed-byte-length string of numbers. Different ECG leads correspond to different byte counts. For example, 12-lead ECG data typically contains 24 bytes per sample, with a 2-byte ADC value per lead.

[0031] After the conversion is completed, the Bluetooth SOC is notified to read the data through hardware interrupt (such as DRDY pin) or SPI / I2C bus status.

[0032] After receiving the notification, the Bluetooth SOC will read the ECG data in the register at different time points.

[0033] S300 , triggering a collection task based on a collection time point to collect ECG data in a register and defining the data as a collection point.

[0034] When the collection time point arrives, the ECG AFE notifies the Bluetooth SOC to read the ECG data in the register, and after reading, the data obtained in the node during this period is used as the collection point.

[0035] S400 , triggering a reading task based on a reading time point to read back the ECG data in the corresponding register and defining it as a read-back point.

[0036] Similarly, after waiting for the readback interval time, the ECG AFE notifies the Bluetooth SOC to read the ECG data in the register again, and after reading, the data read back in the node during this period is used as the readback point.

[0037] S500 , determining whether the data contents of the acquisition points and the readback points in the same sampling period are the same, filtering outliers based on the determination result and performing processing.

[0038] In a sampling cycle, if ECG data needs to be collected every 125us, the Bluetooth SOC must complete the entire collection process within 125us. When a complete collection takes 40us, if the Bluetooth SOC is occupied by other Bluetooth tasks, resulting in only 30us left when it resumes the collection process, the collected data will be abnormal. In the prior art, data is collected only once in each sampling period. When the collected data is abnormal, it is impossible to determine whether it is caused by a conflict between the Bluetooth task and the collection task or by an abnormality in the user's health.

[0039] This application reads the ECG data twice and compares them. When it is known that data can be read twice in one sampling cycle, it is known that there is no abnormality in the sampling cycle based on the same content of the compared data. When the content of the compared data is different, it is known that there is a conflicting sampling abnormality of the Bluetooth SOC in the sampling cycle.

[0040] Through the above technical solution, the Bluetooth SOC performs two reading actions in each reading cycle, and compares the contents of the ECG data read twice. If the two are completely consistent, the reading is determined to be successful, and if they are inconsistent, the reading is determined to be abnormal. This effectively judges and eliminates the "singularity points" generated in the collected data, reduces ECG data monitoring abnormalities caused by abnormal ECG data collection, and reduces safety risks.

[0041] like Figure 2 As shown, in other embodiments, generating corresponding acquisition time points and reading time points in each sampling period based on the action time setting rule includes the following steps: S110, obtaining the number of abnormal points occurring in a preset time period and the timestamp corresponding to each abnormal point, and generating an interval setting strategy based on the number and timestamp. The interval setting strategy includes symmetric, asymmetric, and golden window strategies.

[0042] The action time setting rule is characterized by a rule for optimizing the time interval between two reading actions in a cycle according to different situations. The start time position of the reading action is adjusted according to the number of abnormal points, the occurrence time, etc. in combination with the action time setting rule to minimize the impact on ECG data collection when Bluetooth task conflicts occur in the Bluetooth SOC.

[0043] Because the abnormal points are characterized by conflicts between Bluetooth tasks and collection tasks, the frequency, duration, and cycle of Bluetooth tasks can be analyzed through the number and time of the abnormal points.

[0044] Among them, the timestamp of the abnormal point represents the time when the abnormality occurred. Specifically, since each ECG data is proportional to the number of leads of the device, such as each lead corresponds to 2 bytes, and 12 leads correspond to 24 bytes, then the position of the first appearance of different bytes after comparing the two read data can be used to generate the time when the abnormality occurred. Among them, the time analyzed above may correspond to the time when the abnormality occurred in the first reading, or it may correspond to the time when the abnormality occurred in the second reading. Therefore, it is only necessary to compare the difference between the two Bluetooth SOC readings and the ECG data initially obtained by the ECG AFE to determine which reading had the abnormality.

[0045] In order to reduce abnormal ECG data monitoring caused by Bluetooth task conflicts, it is necessary to dynamically adjust the time point of ECG data reading based on the analyzed Bluetooth task characteristics to avoid the time when the Bluetooth task is in progress.

[0046] The interval setting strategies include symmetrical, asymmetrical and golden window. Specifically, S120: If the number of abnormal points is not greater than the first threshold, the interval setting strategy is symmetrical.

[0047] In the symmetrical formula, the acquisition time point and the readback time point are placed on both sides symmetrical to the midpoint of the cycle, and the standard action duration is configured toward the midpoint of the cycle to obtain the acquisition segment and the readback segment. The time length between the acquisition segment and the readback segment is defined as the readback interval.

[0048] The standard action duration represents the time required to complete a reading task. Based on different acquisition accuracy and requirements, the size of the standard action duration will vary accordingly.

[0049] When the number of abnormal points is small, for example, the probability of conflict between the Bluetooth task and the acquisition task is extremely low, and such a conflict occurs on average once per second at an 8Khz sampling rate, then its impact on the overall ECG monitoring is low.

[0050] The symmetrical time interval setting method is also the conventional time interval setting method for Bluetooth readback. The configuration is relatively simple. The frequency cycle of the ECG AFE notifying the Bluetooth SOC to collect data is relatively uniform, which can be achieved directly by using a fixed-time timer.

[0051] Specifically, in a 125us sampling cycle, sampling begins at 15us and ends at 55us. It takes another 7.5us to reach the midpoint of the cycle, and after the same 7.5us, it reaches the reading time point and starts reading (70us). The sampling continues until 110us. The remaining 15us is used as response time and data comparison time.

[0052] S130: If the number of abnormal points is greater than the first threshold and the timestamps do not have repetitiveness, the interval setting strategy is asymmetric.

[0053] In the asymmetric type, the acquisition time point and the read time point are set on both sides of the cycle midpoint, reducing the time distance between the acquisition time point and the starting point of the sampling cycle, and reducing the time distance between the read time point and the cycle midpoint. The standard action duration is configured toward the cycle midpoint to obtain the acquisition segment and the readback segment. The time length between the acquisition segment and the readback segment is defined as the readback interval.

[0054] When there are a large number of outliers and the timestamps corresponding to each outlier are non-repetitive, this indicates a high frequency of random Bluetooth task conflicts. Random Bluetooth tasks include asynchronous events corresponding to data requests from external devices, such as commands sent by an app.

[0055] The occurrence of this type of conflict requires appropriate processing of the time interval between two reads to reduce the probability of conflict-affecting events.

[0056] In this application, by adjusting the conventional symmetrical dual read time setting to an asymmetrical one, both the acquisition and readback times within a sampling cycle are advanced. Although the Bluetooth task has a higher priority than ECG data acquisition, preempting the task time slices can minimize the read time within a single acquisition cycle. Triggering an interrupt requires hardware conditions (such as the Bluetooth chip sending an interrupt signal and the SOC interrupt enable being enabled). If the read action is completed before the interrupt signal arrives, conflicts can be minimized.

[0057] In other words, the difference between the asymmetric and symmetric methods lies in offsetting the times of the two reads within a completed sampling cycle to keep the non-reading time periods on the same side as much as possible, reducing the distribution of the non-reading time periods. This allows for a longer non-reading time period to match when a relatively random Bluetooth task conflict occurs, reducing the probability of affecting the reading time.

[0058] In other embodiments, the "tight at the beginning and loose at the end" method in the above asymmetric formula can be adjusted to a "loose at the beginning and tight at the end" method based on the actual improvement results of the number of abnormal point occurrences, that is, the time of the two readings are both set synchronously towards the direction of the later acquisition time.

[0059] S140: If the number of abnormal points is greater than the first threshold and the timestamps are repetitive, the interval setting strategy is the golden window strategy.

[0060] In the golden window method, the timestamp of repeated anomalies is defined as the conflict time. The sampling period is divided into golden windows that do not include the conflict time. The acquisition segment and readback segment are set in the golden window based on the time length and continuity of the golden window. The time length between the acquisition segment and the readback segment is defined as the readback interval.

[0061] If a large number of anomaly points are collected, and analysis of the timestamps of several anomaly points reveals that the occurrence periods of multiple anomaly points are repetitive, the repetitiveness is characterized by the same or similar time positions of the anomaly point occurrence periods in each sampling cycle.

[0062] When there is repetitiveness, it is believed that the Bluetooth SOC performs some periodic events based on the protocol, such as connection intervals and heartbeat packet interactions. This type of data is triggered at fixed time intervals, and after being triggered, it will affect the collection of ECG data based on high priority.

[0063] For such situations, the present application provides a golden window spacing based on the traditional symmetrical spacing and the improved asymmetrical spacing.

[0064] Because the outliers are repetitive, the location of the Bluetooth task conflict-prone time of the Bluetooth SOC in each sampling cycle can be analyzed based on the repetition frequency. The golden window is characterized by avoiding the time of two readings outside the Bluetooth task conflict-prone time. The readback interval between the two readings is used as the golden window to match the Bluetooth task conflict-prone time, thereby reducing the occurrence of conflicts by dynamically adjusting the reading time.

[0065] If, after analyzing the timestamps of anomalies, it is found that anomalies often occur between 50us and 65us of the sampling period, a golden window can be set within the range of 50us-65us, and the two reading times need to avoid the golden window. In this way, the reading time position can be dynamically adjusted according to the periodicity of the anomaly occurrence time to reduce the occurrence of conflicts.

[0066] It should be noted that the time required for each reading behavior must meet the requirements. Therefore, if the remaining time period after setting the golden window in the sampling period does not meet the time length required for two complete readings, the golden window interval setting strategy must be prohibited in the sampling period.

[0067] In other embodiments, determining whether the data contents of acquisition points and readback points in the same sampling period are identical, and filtering and processing abnormal points based on the determination result include the following steps: S510: If the data content of the acquisition point and the readback point in the same sampling period is the same, the data content is retained and defined as a valid acquisition.

[0068] If the data content of the acquisition point and the readback point in a sampling cycle are completely consistent, it is considered that the Bluetooth SOC has not read less or misread the ECG data in the register due to the conflict between the Bluetooth task and the acquisition task during this time period, and the data content is defined as valid acquisition.

[0069] S520: If the data contents of the acquisition point and the readback point in the same sampling period are different, the data content in the sampling period is defined as an abnormal point and removed.

[0070] If the data content of the acquisition point and the readback point in a sampling cycle are inconsistent, it is considered that the Bluetooth SOC did not perform the reading task one or two times during the time period due to the conflict between the Bluetooth task and the acquisition task, but was processing a higher priority Bluetooth task. Therefore, the data content is defined as an abnormal point and the abnormal point is eliminated.

[0071] Among them, the abnormal situations caused by conflicts include: Both reads were incomplete due to conflicts; One reading is completed, but the other reading is not completed due to a conflict, and only the ECG data from the time when the Bluetooth SOC finishes processing the Bluetooth task and resumes the collection task is read; One reading is completed, and another reading only reads part of the ECG data of the current sampling cycle due to a conflict. When the Bluetooth SOC continues to read, because the time reaches the next sampling cycle, the ECG AFE automatically obtains the ECG data of the next cycle and places it in the register after digital-to-analog conversion. As a result, the Bluetooth SOC reads part of the ECG data of the previous sampling cycle and part of the ECG data of the next sampling cycle in the time of one reading task.

[0072] like Figure 3 As shown, in other embodiments, determining whether the data contents of the acquisition points and the readback points in the same sampling period are the same, filtering outliers based on the determination result and processing them further includes the following steps: S530: Determine whether the standard action duration is less than the read-back time interval.

[0073] Generally speaking, the probability of conflict between Bluetooth tasks and acquisition tasks is relatively low. At a sampling rate of 8kHz, an average of one conflict occurs per second. If the abnormal points are directly eliminated, the impact on the overall sampling data and pacing detection will be negligible.

[0074] However, in some cases where sampling accuracy is high or Bluetooth traffic is heavy, conflicts can occur more frequently per second. Therefore, when ECG acquisition accuracy is high, this application further incorporates a redundant decision step. The overall logic is to optimize the double read decision to three read decisions per sampling cycle, if the sampling cycle length permits.

[0075] Based on redundancy determination, it is first necessary to determine whether the readback time interval between two readbacks or outside two readbacks allows the third read action to be completed. Therefore, it is necessary to determine whether the action standard duration is less than the readback time interval.

[0076] S531: If yes, then reread the ECG data in the register in the readback time interval to generate a verification point.

[0077] If it is less than, it means that the remaining time is sufficient to perform a read-back action, then the ECG AFE notifies the Bluetooth SOC to perform another read-back action to read the ECG data in the register and define it as a verification point.

[0078] Verification points are used to perform redundant verification on the ECG data that are routinely read twice.

[0079] S532 , when the data contents of the acquisition point and the readback point in the same sampling period are different, the data contents corresponding to the verification point are compared with the acquisition point and the readback point respectively.

[0080] When the data contents of the acquisition points and readback points in the same sampling cycle are different, the solution based on the above embodiment will directly eliminate the data in the sampling cycle. However, after adding redundant verification, the abnormal points are not eliminated first. Instead, the verification points are compared with the acquisition points and readback points respectively, and the subsequent processing method is selected based on the comparison results.

[0081] S533: If there is a comparison, the data content with the same comparison is retained and defined as valid collection.

[0082] S534: If there is no identical comparison, the data content in the sampling period is defined as an abnormal point and removed.

[0083] The above describes several situations where conflicts between Bluetooth tasks and data collection tasks can cause abnormalities in ECG data collection. When both readings are incomplete due to a conflict, the data read twice are different and will not match the data of the verification point. Therefore, the ECG data in this sampling period is directly discarded. If one reading is complete and the other reading is incomplete, there will be two corresponding situations. If the ECG data of the verification point is collected completely and without conflict, the ECG data of the verification point will be the same as the ECG data of the collection point or the read-back point, which means that at least one sampling of the ECG data is complete and correct. At this time, the ECG data that is completely consistent can be retained as a valid collection; if the ECG data of the verification point is also not read completely due to Bluetooth conflict, then even if at least one of the reading data at the collection point or the read-back point is correct, it cannot be successfully compared with the ECG data of the verification point, then the system cannot determine which reading data is valid, so the ECG data in the sampling cycle is directly eliminated as an abnormal point.

[0084] Through the above method, the probability and accuracy of correct ECG data reading and judgment can be improved by performing multiple reading comparisons of redundant verification points when Bluetooth conflicts have not occurred or have ended. To a certain extent, ECG data that could not be effectively captured due to conflicts can be retained as much as possible, the number of abnormal points can be reduced, and the ECG monitoring data can be made more complete and coherent.

[0085] In the above-mentioned solutions, the ECG data sampled by the ECG AFE is uniformly stored in a register, and the Bluetooth SOC reads the ECG data from a register in a sampling cycle. In other embodiments, a partitioned storage and partitioned reading method can be adopted to combine the two reading behaviors and result analysis. Specifically, the ECG data is obtained in each sampling cycle and stored in a register after digital-to-analog conversion, which includes the following steps: S210 , setting a first buffer and a second buffer in a register.

[0086] The buffer is characterized as an area set inside the register for temporarily storing data. The buffer includes a data buffer (DR), an address buffer (AR), an instruction buffer (IR), and an I / O buffer. The buffer mentioned in this application is the data buffer.

[0087] There are two buffers. After the ECG AFE samples ECG data, it stores the sampled ECG data in a first buffer and a second buffer based on different rules.

[0088] S220: Obtain the number of leads and set an identity tag for each lead.

[0089] Each lead has an identity label based on the number and location of the leads. For example, lead I represents the limb lead and corresponds to the lateral wall of the heart, lead II represents the limb lead and corresponds to the anterior wall of the heart, and lead V1 is located in the fourth intercostal space at the right edge of the sternum and represents the anterior septal wall of the heart.

[0090] Different numbers of leads correspond to different identity tags, which can be modified and formulated based on actual conditions and domestic and international requirements.

[0091] S230 , based on the standard lead sequence, the ECG data after digital-to-analog conversion is stored in corresponding register addresses in the first buffer according to identity tag mapping.

[0092] The standard lead sequence is characterized by the standard order in which ECG AFE samples multi-lead ECG data and stores them in registers after performing digital-to-analog processing. For example, the typical output sequence of 12 leads is: Lead 1 (I) - Lead 2 (II) - Lead 3 (III) - Lead 4 (avR) - Lead 5 (aVL) - Lead 6 (aVF) - Lead 7 (V1) - ... - Lead 12 (V6).

[0093] The ECG data sampled from several leads are sequentially stored in the register addresses of the first buffer through the above sequence. At this time, the storage structure of the first buffer is: EG_ADDR[0x00] = Lead 1 low byte; REG_ADDR[0x01] = Lead 1 high byte; REG_ADDR[0x02] = Lead 2 low byte; REG_ADDR[0x03] = Lead 2 high byte; ... REG_ADDR[0x16] = Lead 12 high byte.

[0094] S240 , based on the reorganized lead sequence, the ECG data after digital-to-analog conversion is stored in corresponding register addresses in the second buffer according to identity tag mapping.

[0095] The reorganized lead sequence is characterized as a new sorting rule generated by adjusting the position of the standard lead sequence. At the same time, the standard lead sequence and the reorganized lead sequence need to meet the following conditions: in the standard lead sequence and the reorganized lead sequence, the identity labels corresponding to the leads in the first half and the second half are different.

[0096] That is, the partitions of the leads in the standard lead sequence and the reorganized lead sequence are different. In one case, the reorganized lead sequence of 12 leads can be: Lead 7 (V1) - ... - Lead 12 (V6) - Lead 1 (I) - Lead 2 (II) - Lead 3 (III) - Lead 4 (avR) - Lead 5 (aVL) - Lead 6 (aVF).

[0097] In this way, the leads at each position in the two sequential rules can be placed in different positions without completely disrupting the lead positions.

[0098] The way to reorder the leads can be remapped via array indices.

[0099] In other embodiments, triggering a collection task and a reading task, determining whether the data content of a collection point and a readback point in the same sampling period is the same, and filtering and processing abnormal points based on the determination result include the following steps: S540 , sampling the ECG data in the second buffer at the acquisition time point to obtain a recombined sequence.

[0100] When setting the buffer, the objects corresponding to the first reading action and the second reading action are different. In the first reading, the ECG AFE first notifies the Bluetooth SOC to read the ECG data in the second buffer at the acquisition time point to obtain a reconstructed sequence based on the sequential reading of the reconstructed leads.

[0101] S541 , reading the ECG data in the first buffer at a reading time point to obtain a standard sequence.

[0102] In the second reading, the ECG AFE notifies the Bluetooth SOC to read the ECG data in the first buffer at the reading time point to obtain a standard sequence based on the standard lead sequence reading.

[0103] S542 , adjusting the order of the recombined sequence based on the standard lead sequence during the readback interval to obtain a verification sequence corresponding to the standard sequence.

[0104] The only difference between the recombinant sequence and the standard sequence is the lead order, while the number of bytes and byte content corresponding to each lead should remain consistent when no conflict anomaly occurs.

[0105] Reordering multi-lead data may cause confusion between the physical position and electrical characteristics of the leads, resulting in waveform distortion. The purpose of adjusting the lead order in this application is to make the reading order of each lead different during each reading process, reducing the probability of Bluetooth conflicts frequently affecting a certain part of the ECG data. Therefore, in order to avoid morphological distortion, when reading and comparing twice, the order of the recombined sequence needs to be adjusted to restore it to an order consistent with the standard sequence.

[0106] After the first reading is completed and before the second reading begins, the Bluetooth SOC rearranges the lead sequence in the memory so that the recombined sequence is adjusted to be consistent with the standard sequence and is redefined as the verification sequence.

[0107] S543: After the standard sequence is read, the verification sequence and the standard sequence are compared, and outliers are screened based on the comparison results.

[0108] The verification sequence is compared with the standard sequence, and if there is inconsistent byte content during the comparison, the ECG data in the sampling period is regarded as an abnormal point.

[0109] By setting up a buffer, multiple read tasks of a single storage location are converted into multiple read tasks of multiple storage locations under different time sequences, making the outlier analysis process more accurate.

[0110] In other embodiments, screening outliers based on the judgment results and processing them includes the following steps: S550: Determine the ratio of failed leads based on the comparison of the data content. The ratio of failed leads is represented by the ratio between the number of leads that failed to be compared and the total number of leads.

[0111] Furthermore, after the abnormal points are screened out, in addition to being retained or eliminated through redundant determination, the ECG data corresponding to the abnormal points can also be reconstructed through the existing lead reconstruction method.

[0112] However, on the one hand, the reconstructed lead data has a certain degree of predictability, and on the other hand, the confidence of the reconstructed data in different scenarios is different. Therefore, in order to further improve the accuracy and suitability of outlier data processing, this application further determines the final outlier processing method based on the proportion of failed leads.

[0113] First, the number of mismatched leads is determined by comparing the consistency of the data content, and the proportion of failed leads is calculated based on the total number of leads.

[0114] S551: If the proportion of failed leads is greater than a preset value, the abnormal points in the sampling period are removed.

[0115] If the proportion of failed leads is large, it means that a large number of leads in all leads have not been read correctly due to conflicts. Therefore, lead reconstruction also needs to be based on the analysis and reconstruction of other related lead data in the same sampling cycle and the data of the lead in other sampling cycles. When the wrong lead data occupies a large proportion, the confidence of the reconstructed data is low and may not meet medical clinical needs. Therefore, the abnormal point can be directly eliminated at this time.

[0116] S552: If the proportion of failed leads is not greater than a preset value, reconstruct the ECG data segments corresponding to the failed leads in the abnormal points.

[0117] If the proportion of failed leads is small, the confidence of the reconstructed lead data will be higher because there are more correct lead data associated with the same time. At this time, the missing lead data in the abnormal point can be reconstructed based on the existing ECG data reconstruction method.

[0118] Reconstruction methods include: In the same sampling period, the spatial electrical conduction correlation between multiple leads is used to predict the missing lead through linear or nonlinear combination of known leads. Specifically: Linear transformation method: Calculate the missing lead directly through the linear combination of other leads (e.g. III=II-I); Graph Neural Network (GNN): This treats leads as nodes in a graph structure and uses graph convolution to learn the spatial dependencies between leads (such as the proximity between V1 and V2). It is suitable for scenarios where multiple chest leads are missing. Autoencoder: It uses a neural network to learn the overall features of the 12 leads. When the input contains missing leads, the model uses the feature associations of other leads to reconstruct the missing values.

[0119] Based on the historical data of the missing lead, the temporal continuity of the ECG signal (P wave, QRS wave, T wave) is used to analyze the historical waveform of the missing lead to predict the missing segment. Specifically: Time domain interpolation method: cubic spline interpolation and piecewise linear interpolation, which are suitable for short time gaps and directly fill in the intermediate values ​​based on the waveform shape of the previous and next moments; Kalman filtering: It treats ECG signals as a dynamic system and uses historical states and current observations to predict the temporal changes of missing leads. It is suitable for processing short-term missing leads with noise. Recurrent Neural Network (RNN / LSTM): By learning the historical temporal features of the missing leads (such as QRS frequency and ST segment morphology), it predicts the waveform of the missing segments in the future.

[0120] In this application, after analyzing and processing the abnormal points, the improvement effect on the ECG data is as follows: Figure 4 、 Figure 5 As shown in the figure, the abnormal points in the final ECG waveform are processed and the ECG data tends to be normal.

[0121] The following steps are also included: S600, judges health scenarios based on effectively collected ECG data.

[0122] Based on the effectively collected ECG data, the corresponding ECG monitoring waveform is generated, and the waveform is used to analyze whether there are health abnormalities. For example, if the ECG data is stable and regular, it corresponds to a daily healthy scene; if the ECG data is unstable and there are many high and low points, it corresponds to an unhealthy scene.

[0123] S610: Generate corresponding risk ratings based on the health scenario.

[0124] For different ECG monitoring scenarios, the sensitivity of risk considerations for ECG data monitoring is different, and the emergence of abnormal points will lead to the loss of some ECG data. The loss of ECG data corresponds to different risk ratings in different scenarios.

[0125] A higher risk rating indicates a greater impact of data loss in this scenario, and a lower risk rating indicates a smaller impact of data loss in this scenario.

[0126] S620: Mark the abnormal points based on the risk rating and generate alarm information based on the timestamp corresponding to the abnormal points.

[0127] Different risk ratings correspond to different anomaly alert strategies. In low-risk and high-risk situations, when anomalies appear and are processed through elimination, reconstruction, and redundant determination, the anomaly must be marked, regardless of whether it is retained or not, to inform the user that the data point is not collected normally, but rather the result of the anomaly processing, which requires the user to review and confirm. At the same time, when the risk is low, because the user's health data is relatively stable, the alarm threshold of abnormal points can be set. For example, an alarm will be issued only when the frequency of abnormal points within a period of time is greater than the preset value, or when abnormal points appear several times in a fixed time. When the risk is high, because the user's health data presents an overall pessimistic risk, an alarm can be issued every time an abnormal point occurs to prompt the user or management personnel to check and confirm.

[0128] Under different risks, the sound reminder and light reminder of the abnormal point alarm can be different. The abnormal point alarm under low risk is mainly used to prompt the frequency and number of abnormal points, reminding managers to make corresponding task adjustments and optimizations to the Bluetooth SOC. The abnormal point alarm under high risk is mainly used to remind that when abnormal points occur, some risk ECG data may be ignored or processed incorrectly, which may lead to safety hazards. Therefore, different photoelectric alarm methods are used to classify and distinguish them.

[0129] The implementation principle is: The Bluetooth SOC performs two reading actions in each reading cycle and compares the ECG data contents read twice. If the two are completely consistent, the reading is considered successful. If they are inconsistent, the reading is considered abnormal. This effectively judges and eliminates the "singularity" generated in the collected data, reduces ECG data monitoring abnormalities caused by abnormal ECG data collection, and reduces safety risks.

[0130] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps and they may be performed in other orders.

[0131] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A method for monitoring and processing abnormal ECG collection points, characterized in that: The following steps are involved: Generate corresponding acquisition time points and reading time points in each sampling period based on the action time setting rule, wherein the acquisition time points and reading time points are separated by a corresponding readback interval time; Acquire electrocardiogram data in each sampling period and store it in a register after performing digital-to-analog conversion; triggering an acquisition task based on the acquisition time point to acquire the electrocardiogram data in the register and defining the acquired data as an acquisition point; Triggering a reading task based on the reading time point to read back the ECG data in the corresponding register and defining the result as a read-back point; It is determined whether the data contents of the acquisition point and the read-back point in the same sampling period are the same, and abnormal points are screened and processed based on the determination result.

2. The abnormal ECG acquisition point monitoring and processing method according to claim 1, characterized in that: Generate corresponding collection time points and reading time points in each sampling period based on the action time setting rules, including the following steps: Obtain the number of abnormal points that occur in a preset time period and the timestamps corresponding to each abnormal point, and generate an interval setting strategy based on the number and the timestamps, wherein the interval setting strategy includes symmetric, asymmetric, and golden window strategies; If the number of the abnormal points is not greater than the first threshold, the interval setting strategy is the symmetrical strategy; If the number of the abnormal points is greater than a first threshold and the timestamps do not have repetitiveness, the interval setting strategy is asymmetric; If the number of the abnormal points is greater than the first threshold and the timestamps are repetitive, the interval setting strategy is a golden window strategy.

3. The abnormal ECG acquisition point monitoring and processing method according to claim 2, characterized in that: Obtaining the number of abnormal points occurring in a preset time period and the timestamps corresponding to each abnormal point, and generating an interval setting strategy based on the number and the timestamps, further comprising the following steps: In the symmetrical formula, the acquisition time point and the read time point are placed on both sides symmetrical to the midpoint of the cycle, and the standard action duration is configured towards the midpoint of the cycle to obtain an acquisition segment and a readback segment. The time length between the acquisition segment and the readback segment is defined as the readback interval. In the asymmetric formula, the acquisition time point and the read time point are set on both sides of the cycle midpoint, reducing the time distance between the acquisition time point and the starting point of the sampling cycle, and reducing the time distance between the read time point and the cycle midpoint. The standard action duration is respectively configured toward the cycle midpoint to obtain an acquisition segment and a readback segment. The time length between the acquisition segment and the readback segment is defined as the readback interval. In the golden window format, the timestamps of the repeated abnormal points are defined as conflict times, a golden window excluding the conflict times is divided in the sampling period, the acquisition segment and the readback segment are set in the golden window based on the time length and continuity of the golden window, and the time length between the acquisition segment and the readback segment is defined as the readback interval time.

4. The abnormal ECG acquisition point monitoring and processing method according to claim 1, characterized in that: Determining whether the data contents of the acquisition point and the readback point in the same sampling period are the same, and filtering and processing abnormal points based on the determination result, including the following steps: If the data content of the acquisition point and the data content of the readback point in the same sampling period are the same, the data content is retained and defined as valid acquisition; If the data contents of the acquisition point and the data contents of the read-back point in the same sampling period are different, the data content in the sampling period is defined as an abnormal point and is removed.

5. The abnormal ECG acquisition point monitoring and processing method according to claim 3 is characterized in that: Determining whether the data contents of the acquisition point and the readback point in the same sampling period are the same, filtering outliers based on the determination result and processing them, further comprising the following steps: Determine whether the standard action duration is less than the readback time interval; If so, rereading the ECG data in the register during the readback time interval to generate a verification point; When the data contents of the acquisition point and the readback point in the same sampling period are different, the data content corresponding to the verification point is compared with the acquisition point and the readback point respectively; If there is a match, the data content with the same match is retained and defined as valid collection; If there is no such a comparison, the data content in the sampling period is defined as an abnormal point and removed.

6. The abnormal ECG acquisition point monitoring and processing method according to claim 1, characterized in that: Acquiring electrocardiogram data in each sampling period and storing it in a register after digital-to-analog conversion includes the following steps: Setting a first buffer zone and a second buffer zone in the register; Get the number of leads and set an identity tag for each lead; Based on the standard lead sequence, the digital-to-analog converted electrocardiogram data is stored in the corresponding register address in the first buffer according to the identity tag mapping; Based on the reorganized lead sequence, the digital-to-analog converted ECG data is stored in the corresponding register address in the second buffer according to the identity tag mapping; In the standard lead sequence and the reorganized lead sequence, the identity labels corresponding to the leads in the first half and the second half are different.

7. The abnormal ECG acquisition point monitoring and processing method according to claim 6, characterized in that: Triggering a collection task and a reading task, determining whether the data contents of the collection point and the readback point in the same sampling period are the same, filtering outliers based on the determination results and processing them, including the following steps: collecting the electrocardiogram data in the second buffer at the collection time point to obtain a recombined sequence; Reading the electrocardiogram data in the first buffer at the reading time point to obtain a standard sequence; Adjusting the order of the recombined sequence based on the standard lead sequence during the readback interval to obtain a verification sequence corresponding to the standard sequence; After the standard sequence is read, the verification sequence and the standard sequence are compared, and the abnormal points are screened based on the comparison results.

8. The abnormal ECG acquisition point monitoring and processing method according to claim 1, characterized in that: Based on the judgment results, outliers are screened and processed, including the following steps: Determine the proportion of failed leads based on the comparison of the data content, where the proportion of failed leads is represented by the ratio of the number of leads that failed comparison to the total number of leads; If the proportion of failed leads is greater than a preset value, the abnormal points in the sampling period are removed; If the proportion of failed leads is not greater than a preset value, the ECG data segments corresponding to the failed leads in the abnormal points are reconstructed.

9. The abnormal ECG acquisition point monitoring and processing method according to claim 1, characterized in that: The following steps are also included: Determining a health scenario based on the effectively collected ECG data; generating a corresponding risk rating based on the health scenario; The abnormal point is marked based on the risk rating and an alarm message is generated based on a timestamp corresponding to the abnormal point.

10. An abnormal ECG collection point monitoring and processing system, characterized in that: Used to implement the method according to any one of claims 1 to 9.

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