An electrocardiosignal detection method, device, equipment and storage medium

Abstract

This disclosure provides a method, apparatus, device, and storage medium for detecting electrocardiogram (ECG) signals. The ECG signal detection method includes: in response to acquiring an ECG signal, periodically detecting a target wave in the ECG signal according to a set window; in response to the periodic detection of the target wave in the ECG signal after a first time interval, determining abnormal parameter attributes in the target wave based on a first number of parameter attributes, and determining a second number of abnormal parameter attributes; resetting the parameter attributes of all target waves based on the second number and the first number of abnormal parameter attributes; and detecting the target wave in the ECG signal after the first time interval based on the reset parameter attributes. By resetting all parameter attributes of the target wave, the method achieves the goal of real-time detection of whether the target wave in the acquired ECG signal is normal, thereby ensuring that the detected target wave is a normal signal and improving the accuracy of ECG signal detection in high-noise environments.

Description

Technical Field

[0001] This disclosure relates to the field of signal detection, and in particular to a method, apparatus, device and storage medium for detecting electrocardiogram signals. Background Technology

[0002] With an aging population and increasing life pressures, the number of people suffering from cardiovascular diseases is constantly increasing and is gradually affecting younger people. Currently, cardiovascular disease has become one of the major diseases threatening people's lives; therefore, real-time monitoring of cardiovascular status plays a crucial role in the diagnosis of cardiovascular diseases.

[0003] With the development of technology, wearable devices are becoming increasingly diverse in type and function. For example, users can wear electrocardiogram (ECG) wearable devices to monitor heart rate and cardiovascular diseases, thereby enabling early detection and timely treatment of cardiovascular diseases.

[0004] However, wearable ECG devices are easily affected by user movement and the surrounding environment, resulting in poor quality and stability of the collected ECG signals. This makes it impossible for wearable ECG devices to accurately analyze the collected ECG signals, leading to inaccurate test results and affecting the detection of cardiovascular diseases. Summary of the Invention

[0005] To overcome the problems existing in related technologies, this disclosure provides a method, apparatus, device and storage medium for detecting electrocardiogram signals.

[0006] According to a first aspect of the present disclosure, a method for detecting electrocardiogram (ECG) signals is provided, comprising:

[0007] In response to acquiring an electrocardiogram (ECG) signal, the system periodically detects target waves in the ECG signal according to a set window. The target wave is an ascending wave corresponding to a peak point with an amplitude greater than a reference threshold. In response to the periodic detection of target waves in the ECG signal after a first time interval, the system determines abnormal parameter attributes in the target wave based on a first number of parameter attributes and determines a second number of abnormal parameter attributes. Based on the second number and the first number of abnormal parameter attributes of the target wave, the system resets the parameter attributes of all target waves. Based on the reset parameter attributes, the system detects target waves in the ECG signal after the first time interval.

[0008] In one embodiment, the abnormal parameter attributes include: the number of target waves is less than a minimum threshold; the number of target waves is greater than a maximum threshold; the standard deviation of the target wave amplitude is greater than a set target wave amplitude standard deviation threshold; the variance of the target wave amplitude is greater than a set target wave amplitude variance threshold; the variability of the target wave amplitude is greater than a set target wave amplitude variability threshold; the standard deviation of the target wave amplitude is greater than a set target wave amplitude standard deviation threshold; the standard deviation of the interval between two target waves is greater than a set two target wave interval standard deviation threshold; the variance of the interval between two target waves is greater than a set two target wave interval variance threshold; and the variability of the interval between two target waves is greater than a set two target wave interval variability threshold.

[0009] In one embodiment, resetting the parameter attributes of all target waves based on the second number and the first number of abnormal parameter attributes in the target waves includes: resetting the parameter attributes of all target waves in response to the ratio between the second number and the first number of abnormal parameter attributes of the target waves being greater than a threshold.

[0010] In one embodiment, determining the abnormal parameter attributes in the target wave based on a first number of parameter attributes, and determining a second number of abnormal parameter attributes, includes: in response to a first time interval, incrementing the number of abnormal parameter attributes by 1 for each detected abnormal parameter attribute in each period to obtain a second number of abnormal parameter attributes, wherein the initial value of the number of abnormal parameter attributes is 0.

[0011] In one embodiment, the first quantity of parameter attributes is one or more preset parameter attributes; the preset parameter attributes include at least one of the following: minimum number of target waves; maximum number of target waves; standard deviation of target wave amplitude; variance of target wave amplitude; variability of target wave amplitude; standard deviation of the interval between two target waves; variance of the interval between two target waves; variability of the interval between two target waves.

[0012] According to a second aspect of the present disclosure, an electrocardiogram (ECG) signal detection device is provided, comprising:

[0013] The detection unit is used to periodically detect the target wave in the ECG signal according to a set window in response to the acquisition of the ECG signal. The target wave is the rising wave corresponding to the peak point with an amplitude greater than a reference threshold. Based on the reset parameter attributes, the target wave in the ECG signal after the first time period is detected.

[0014] The determining unit is configured to, in response to the periodic detection of a target wave in an electrocardiogram signal passing through a first time, determine the presence of abnormal parameter attributes in the abnormal target wave based on a first number of parameter attributes, and determine a second number of abnormal target wave parameter attributes.

[0015] The reset unit is used to reset the parameter attributes of all target waves based on the second quantity and the first quantity of the abnormal parameter attributes of the abnormal target waves.

[0016] In one embodiment, the determining unit determines the presence of the abnormal parameter attribute in the target wave in the following ways: the number of target waves is less than a minimum threshold; the number of target waves is greater than a maximum threshold; the standard deviation of the target wave amplitude is greater than a set target wave amplitude standard deviation threshold; the variance of the target wave amplitude is greater than a set target wave amplitude variance threshold; the variability of the target wave amplitude is greater than a set target wave amplitude variability threshold; the standard deviation of the target wave amplitude is greater than a set target wave amplitude standard deviation threshold; the standard deviation of the interval between two target waves is greater than a set two target wave interval standard deviation threshold; the variance of the interval between two target waves is greater than a set two target wave interval variance threshold; and the variability of the interval between two target waves is greater than a set two target wave interval variability threshold.

[0017] In one embodiment, the reset unit resets the parameter attributes of all target waves based on the second number and the first number of abnormal target waves in the target wave: in response to the ratio between the second number and the first number of abnormal target waves being greater than a threshold, the parameter attributes of all target waves are reset.

[0018] In one embodiment, the determining unit determines abnormal target waves with abnormal parameter attributes based on a first number of parameter attributes of the detected target waves, and determines a second number of target waves with abnormal parameter attributes: in response to a first time interval, each time the abnormal parameter attribute wave is detected in each period, the number of abnormal parameter attribute waves is incremented by 1 to obtain the second number of target waves with abnormal parameter attributes, and the initial value of the number of target waves with abnormal parameter attributes is 0.

[0019] In one embodiment, the first quantity of parameter attributes is one or more preset parameter attributes; the preset parameter attributes include at least one of the following: minimum number of detected target waves; maximum number of detected target waves; standard deviation of target wave amplitude; variance of target wave amplitude; variability of target wave amplitude; standard deviation of the interval between two target waves; variance of the interval between two target waves; variability of the interval between two target waves.

[0020] According to a third aspect of the present disclosure, an electrocardiogram (ECG) signal detection device is provided, comprising:

[0021] processor;

[0022] Memory used to store processor-executable instructions;

[0023] The processor is configured to execute the method described in the first aspect or any embodiment of the first aspect.

[0024] According to a fourth aspect of the present disclosure, a storage medium is provided, the storage medium storing instructions that, when executed by a processor of a terminal, enable the terminal to perform the method described in the first aspect or any embodiment of the first aspect.

[0025] The technical solutions provided by the embodiments of this disclosure can include the following beneficial effects: by determining the target wave, obtaining a first number of parameter attributes of the target wave within a first time period, determining the presence of abnormal parameter attributes in the target wave based on the parameter attributes, and determining a second number of abnormal parameter attributes. That is, the detection result of the ECG signal is converted into monitorable parameter attributes; by comparing the abnormal parameter attributes with all parameter attributes, the detected ECG signal is determined to be abnormal; the parameter attributes in all target waves are reset; and the target wave in the ECG signal is re-detected, thereby real-time detection of whether the target wave in the ECG signal is a normal signal, ensuring the detection of a normal ECG signal, and thus improving the accuracy of ECG signal detection in high-noise scenarios.

[0026] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0027] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0028] Figure 1 This is a schematic diagram illustrating an electrocardiogram acquired by an ECG wearable device according to an exemplary embodiment.

[0029] Figure 2 This is a flowchart illustrating an electrocardiogram (ECG) signal detection method according to an exemplary embodiment.

[0030] Figure 3 This is a flowchart illustrating an electrocardiogram (ECG) signal detection method according to an exemplary embodiment.

[0031] Figure 4 This is a flowchart illustrating an electrocardiogram (ECG) signal detection method according to an exemplary embodiment.

[0032] Figure 5 This is a block diagram of an electrocardiogram signal detection device according to an exemplary embodiment.

[0033] Figure 6 This is a block diagram illustrating an apparatus for detecting electrocardiogram signals according to an exemplary embodiment. Detailed Implementation

[0034] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure.

[0035] The electrocardiogram (ECG) signal detection method disclosed herein is applicable to ECG signal detection scenarios, such as ECG signal detection in wearable devices.

[0036] With the increasing aging population and rising life pressures, the number of people suffering from cardiovascular diseases is constantly increasing and becoming increasingly younger. Cardiovascular disease has become one of the major diseases threatening people's lives, and electrocardiograms (ECGs) are a reliable clinical indicator of cardiovascular disease. However, conventional ECG monitoring devices are bulky, difficult to wear, and do not meet users' needs for real-time ECG monitoring. Therefore, developing wearable ECG devices in the field of wearable health monitoring technology is an inevitable trend in technological development.

[0037] Currently, wearable ECG devices can collect and analyze ECG data through sensors to perform dynamic electrocardiogram monitoring, thereby enabling the prevention of cardiovascular diseases. Specifically, heart rate calculation requires R-wave calibration in the ECG data; therefore, analysis of the R-wave signal in the ECG signal is necessary. Figure 1 This is a schematic diagram illustrating an electrocardiogram (ECG) acquired by an ECG wearable device according to an exemplary embodiment. However, as... Figure 1 As shown, during the ECG acquisition process, the wearable ECG device may experience abnormal waveforms in the early acquisition signals due to unstable capacitance of the wearable device or the user not being in a suitable state for ECG detection. This affects the detection algorithm and leads to inaccurate detection signals in the later stages.

[0038] In related technologies, the slope-based detection algorithm can be improved by updating the amplitude screening threshold and slope comparison threshold, and by adding R-wave interval verification, thereby achieving higher accuracy in real-time R-wave detection even under significant interference. However, when updating the amplitude screening threshold, the first amplitude screening threshold is still calculated based on the abnormal waveform signal. Therefore, improving the slope-based detection algorithm cannot reliably guarantee accurate heart rate detection using ECGs with abnormal waveforms.

[0039] In related technologies, received patient physiological information can be compared with a starting threshold. If the threshold is exceeded, the system is moved to a reset threshold (different from the starting threshold); if the reset threshold is exceeded, the system is moved back to the starting threshold. However, there is no scheme for updating or resetting the threshold for ECG signals with abnormal waveforms. Therefore, related technologies cannot solve the problem of achieving accurate detection of ECG signals under high noise conditions.

[0040] Therefore, this disclosure determines the target wave, obtains a first number of parameter attributes of the target wave within a first time period, determines the presence of abnormal parameter attributes in the target wave based on the parameter attributes, and determines a second number of abnormal parameter attributes. Based on the second number and the first number, when it is determined that the current signal detection result is abnormal, the parameter attributes in all target waves can be reset, thereby ensuring that normal signals are obtained and improving the accuracy of ECG signal detection.

[0041] Figure 2 This is a flowchart illustrating an electrocardiogram (ECG) signal detection method according to an exemplary embodiment, such as... Figure 2 As shown, the ECG signal detection method used in the terminal includes the following steps.

[0042] In step S11, in response to acquiring the electrocardiogram (ECG) signal, the target wave in the ECG signal is periodically detected according to the set window.

[0043] The target wave is the rising wave corresponding to the peak point whose amplitude is greater than the reference threshold.

[0044] The rising wave can be an R wave, which is an upward wave in an electrocardiogram (ECG) signal.

[0045] In this embodiment of the disclosure, the reference threshold can be the product of a reference value and an amplitude base value. For example, the reference threshold can be the product of 0.4 and the amplitude base value. The amplitude base value can be the amplitude corresponding to the median peak value in the first window of the setting window.

[0046] In this embodiment of the disclosure, the electrocardiogram (ECG) signal can be obtained by a sensor installed on a wearable device. A bandpass filter can be used to remove baseline drift and motion noise from the acquired ECG signal, and a notch filter can be used to remove power frequency interference and its harmonics, thereby obtaining a more accurate ECG signal.

[0047] In step S12, in response to the periodic detection of the target wave in the electrocardiogram signal passing through a first time, abnormal parameter attributes in the target wave are determined based on a first number of parameter attributes, and a second number of abnormal parameter attributes is determined.

[0048] The first time can contain multiple settings windows.

[0049] The settings window can display the ECG signals detected within a set time period.

[0050] In this embodiment of the disclosure, a first number of parameter attributes are determined in the target wave, and the first number of parameter attributes can characterize whether the detected target wave is reasonable.

[0051] In this embodiment of the disclosure, based on the parameter attributes in the target wave, it can be determined whether there are abnormal parameter attributes in the target wave, and the abnormal parameter attributes are counted to obtain a second number of abnormal data parameters.

[0052] In step S13, the parameter attributes of all target waves are reset based on the second quantity and the first quantity of the target wave anomaly parameter attributes.

[0053] In this embodiment of the disclosure, resetting the target wave parameter attribute can be done by setting the target wave parameter attribute to zero.

[0054] In this embodiment of the present disclosure, upon receiving a filtered electrocardiogram (ECG) signal, the target wave is periodically detected within a set window. After a first time interval, a first number of target wave parameter attributes are acquired. Based on the target wave parameter attributes, abnormal target waves within the target wave are identified, and a second number of abnormal target waves is determined. Based on the ratio between the second number and the first number, the target wave parameter attributes are reset.

[0055] In step S14, the target wave in the electrocardiogram signal after the first time interval is detected based on the reset parameter attributes.

[0056] In this embodiment of the disclosure, after resetting the target wave parameter attributes, the target wave in the ECG signal after the first time interval is re-detected to obtain the first number of parameter attributes in the target wave after the second first time interval, and to determine the abnormal parameter attributes and their number in the target wave, and to determine whether the parameter attributes need to be reset.

[0057] In this embodiment of the disclosure, by determining the target wave, a first number of parameter attributes of the target wave within a first time period are obtained. Based on the parameter attributes, it is determined that there are abnormal parameter attributes in the target wave, and a second number of abnormal parameter attributes are determined. That is, the detection result of the ECG signal is converted into monitorable parameter attributes. The abnormality of the detected ECG signal is determined by the proportion of abnormal parameter attributes in all parameter attributes. The parameter attributes in all target waves are reset, and the target wave in the ECG signal is re-detected. This allows for real-time detection and monitoring of whether the ECG signal is normal, and the detection of normal ECG signals, thereby improving the accuracy of ECG signal detection.

[0058] In this embodiment of the disclosure, the target wave can be determined as an abnormal target wave by comparing the parameter attributes of the detected target wave with a preset attribute threshold.

[0059] In this embodiment of the disclosure, an abnormal parameter attribute in the target wave can be determined when at least one of the following is detected: the number of detected target waves is less than a minimum threshold; the number of detected target waves is greater than a maximum threshold; the standard deviation of the detected target wave amplitude is greater than a set target wave amplitude standard deviation threshold; the variance of the detected target wave amplitude is greater than a set target wave amplitude variance threshold; the variability rate of the detected target wave amplitude is greater than a set target wave amplitude variability rate threshold; the standard deviation of the detected target wave amplitude is greater than a set target wave amplitude standard deviation threshold; the standard deviation of the detected interval between two target waves is greater than a set two target wave interval standard deviation threshold; the variance of the detected interval between two target waves is greater than a set two target wave interval variance threshold; and the variability rate of the detected interval between two target waves is greater than a set two target wave interval variability rate threshold.

[0060] In this embodiment of the disclosure, the parameter attributes of all target waves can be reset based on the ratio between the second number of abnormal parameter attributes of the target wave and the first number of parameter attributes in the target wave.

[0061] Figure 3 This is a flowchart illustrating an electrocardiogram (ECG) signal detection method according to an exemplary embodiment, such as... Figure 3 As shown, the ECG signal detection method used in the terminal includes the following steps.

[0062] In step S21, in response to acquiring the electrocardiogram (ECG) signal, the target wave in the ECG signal is periodically detected according to the set window.

[0063] In step S22, in response to the periodic detection of the target wave in the electrocardiogram signal passing through a first time, abnormal parameter attributes in the target wave are determined based on a first number of parameter attributes, and a second number of abnormal parameter attributes is determined.

[0064] In step S23, in response to the ratio between the second quantity and the first quantity of the target wave abnormal parameter attributes being greater than a threshold, the parameter attributes of all target waves are reset.

[0065] The threshold can be preset by the user, and different thresholds can represent different levels of accuracy in detecting electrocardiogram signals.

[0066] In step S24, the target wave in the ECG signal after the first time interval is detected based on the reset parameter attributes.

[0067] Steps S21, S22, and S24 are the same as steps S11, S12, and S14, and will not be elaborated further here.

[0068] In this embodiment of the disclosure, a first number of parameter attributes of the target wave are obtained within a first time period. Based on the parameter attributes of the target wave, it is determined that there are abnormal parameter attributes in the target wave, and the abnormal parameter attributes are determined to be a second number. When the ratio between the second number and the first number is greater than a threshold, it is determined to reset the parameter attributes of all target waves and set the parameter attributes to zero.

[0069] In this embodiment of the disclosure, resetting the parameter attributes of all target waves can be done by setting the parameter attributes of the target waveform to zero, and then re-acquiring the parameter attributes when monitoring the target waveform in real time.

[0070] In this embodiment of the disclosure, if it is determined that the ratio between the second quantity and the first quantity is greater than a threshold, then the parameter attributes of all target waves are reset; if it is determined that the ratio between the second quantity and the first quantity is greater than a threshold, then it is not necessary to reset the parameter attributes of the target waves.

[0071] In this embodiment of the disclosure, when the ratio between the second quantity and the first quantity is greater than a threshold, that is, when the ratio between the abnormal parameter attribute and all parameter attributes in the target wave is greater than the threshold, it can be determined that the current signal detection result is abnormal. By resetting the parameter attributes, new parameter attributes can be obtained when performing ECG signal detection, and the new parameter attributes can be detected, thereby ensuring the rationality of the ECG signal and improving the accuracy of ECG signal detection.

[0072] In this embodiment of the disclosure, in response to determining abnormal parameter attributes from a first number of parameter attributes, the abnormal parameter attributes are counted to determine a second number of abnormal parameter attributes.

[0073] Figure 4 This is a flowchart illustrating an electrocardiogram (ECG) signal detection method according to an exemplary embodiment, such as... Figure 4 As shown, the ECG signal detection method used in the terminal includes the following steps.

[0074] In step S31, based on the first number of parameter attributes, abnormal parameter attributes in the target wave are determined, and a second number of abnormal parameter attributes is determined.

[0075] In step S32, in response to the first time interval, for each abnormal parameter attribute detected in each period, the number of abnormal parameter attributes is incremented by 1 to obtain the second number of abnormal parameter attributes.

[0076] The initial value for the number of target waves in the abnormal parameter attribute is 0.

[0077] In this embodiment of the disclosure, after determining that there are abnormal parameter attributes in the target wave based on the parameter attributes in the target wave, the abnormal attributes in each cycle of the target wave detection in the first time time are counted from zero, and the count result is the second number of abnormal parameter attributes.

[0078] In this embodiment of the disclosure, the number of abnormal attributes in the target waveform within a first time period is determined by counting the abnormal parameter attributes in the target waveform. The number of abnormal attributes can be compared with the total number of data attributes of the target waveform to determine whether the target waveform is abnormal, thereby enabling the acquisition of normal and accurate ECG signals during ECG testing.

[0079] In this embodiment of the disclosure, the first number of parameter attributes is one or more of preset parameter attributes, wherein the preset parameter attributes include at least one of the following:

[0080] Minimum number of target waves detected; maximum number of target waves detected; standard deviation of target wave amplitude; variance of target wave amplitude; variability of target wave amplitude; standard deviation of the interval between two target waves; variance of the interval between two target waves; variability of the interval between two target waves.

[0081] In this disclosure, the electrocardiogram signal detection method is described with reference to the following examples.

[0082] In this embodiment of the disclosure, a method for detecting electrocardiogram signals by using an ECG wearable device to detect the R wave in an ECG signal is described.

[0083] In this embodiment of the disclosure, ECG signals are acquired using sensors in an ECG wearable device. A bandpass filter in the ECG wearable device is used to remove baseline offset and motion noise, and a notch filter is used to remove power frequency interference and harmonics from the ECG signal. For example, a notch filter is used to remove 50Hz or 60Hz power frequency interference and its harmonics from the ECG signal.

[0084] In this embodiment of the disclosure, the filtered ECG signal is periodically detected according to a set window to determine the R wave.

[0085] In this embodiment of the disclosure, after determining that the current waveform is an R-wave, the position and amplitude of the R-wave are recorded.

[0086] In this embodiment of the disclosure, the R-wave is a waveform with an amplitude greater than a reference threshold at its peak point.

[0087] The data threshold can be multiplied by the amplitude baseline of the R-wave as a reference threshold. The data threshold can be an empirical value obtained by the user from the database.

[0088] In this embodiment of the disclosure, all peak points are determined in the first window of the setting window. A peak point includes at least one of the following: if the amplitude of the point is greater than the amplitude of points adjacent to the signal when the point is located at the beginning or end of the ECG signal; or if the amplitude of the point is greater than the amplitude of its two adjacent points when the point is not located at the beginning or end of the ECG signal. The median of all peak points is used as the baseline value for the R-wave amplitude.

[0089] In this embodiment, the ECG signal is detected in real time, and the amplitude baseline is updated in real time. The updated amplitude threshold can be calculated using the following formula:

[0090]

[0091] Among them, R t For amplitude base value, L n The position of the R wave, R n The amplitude of the R-wave. is the updated amplitude base value, where n represents the (n+1)th target wave.

[0092] In this embodiment of the disclosure, the acquired ECG signal is analyzed after T seconds to obtain the parameter attributes corresponding to the R-wave signal, wherein the number of parameter attributes is a first quantity. The parameter attributes can be one or more of the following pre-set parameter attributes: minimum number of detected target waves; maximum number of detected target waves; standard deviation of target wave amplitude; variance of target wave amplitude; variability of target wave amplitude; standard deviation of the interval between two target waves; variance of the interval between two target waves; or variability of the interval between two target waves. The number of abnormal R-waves is determined based on parameter attributes as the second quantity. Abnormal R-waves include at least one of the following: the number of R-waves is less than the minimum threshold; the number of R-waves is greater than the maximum threshold; the standard deviation of the R-wave amplitude is greater than the set standard deviation threshold; the variance of the R-wave amplitude is greater than the set variance threshold; the variability of the R-wave amplitude is greater than the set variability threshold; the standard deviation of the R-wave amplitude is greater than the set standard deviation threshold; the standard deviation of the RR interval is greater than the set standard deviation threshold; the variance of the RR interval is greater than the set variance threshold; and the variability of the RR interval is greater than the set variability threshold.

[0093] In this embodiment of the disclosure, when the ratio of the second quantity to the first quantity is greater than a proportional threshold, all parameters of the R-wave are reset. The parameters of the R-wave include the position and amplitude of the R-wave, as well as the parameter attributes corresponding to the R-wave signal. For example, if the proportional threshold is preset to 30%, the obtained R-wave parameter attributes (first quantity) are 8 items, and the number of abnormal R-waves (second quantity) is 4, then the ratio between the second quantity and the first quantity is 50%, which is greater than the preset proportional threshold. Therefore, the currently obtained ECG signal is not processed, and all parameters of the R-wave need to be reset.

[0094] In this embodiment of the disclosure, the ECG signal after T seconds is used as the first window of the setting window, and the above operation is repeated. This allows for a reasonable judgment of the ECG signal. When the ECG signal is unreasonable, the signal is reset, thereby obtaining a higher quality ECG signal and increasing the accuracy of ECG signal detection.

[0095] Based on the same concept, embodiments of this disclosure also provide an electrocardiogram signal detection device.

[0096] It is understood that the electrocardiogram signal detection device provided in this disclosure includes hardware structures and / or software modules corresponding to each function in order to achieve the above-mentioned functions. In conjunction with the units and algorithm steps of the various examples disclosed in this disclosure, this disclosure can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solution of this disclosure.

[0097] Figure 5 This is a block diagram illustrating an electrocardiogram (ECG) signal detection device according to an exemplary embodiment. (Refer to...) Figure 5 The device includes a detection unit 101, a determination unit 102, and a reset unit 103.

[0098] The detection unit is used to periodically detect the target wave in the ECG signal according to the set window in response to the acquisition of the ECG signal. The target wave is the rising wave corresponding to the peak point with an amplitude greater than the reference threshold. Based on the reset parameter attributes, the target wave in the ECG signal after the first time period is detected.

[0099] The determining unit is configured to, in response to the periodic detection of a target wave in an electrocardiogram signal passing through a first time interval, determine the presence of abnormal parameter attributes in the abnormal target wave based on a first number of parameter attributes, and determine a second number of abnormal target wave parameter attributes.

[0100] The reset unit is used to reset the parameter attributes of all target waves based on the second and first quantities of abnormal parameter attributes of the abnormal target waves.

[0101] In one implementation, the determining unit determines the presence of abnormal parameter attributes in the target wave using the following methods: the number of target waves is less than a minimum threshold; the number of target waves is greater than a maximum threshold; the standard deviation of the target wave amplitude is greater than a set target wave amplitude standard deviation threshold; the variance of the target wave amplitude is greater than a set target wave amplitude variance threshold; the variability of the target wave amplitude is greater than a set target wave amplitude variability threshold; the standard deviation of the target wave amplitude is greater than a set target wave amplitude standard deviation threshold; the standard deviation of the interval between two target waves is greater than a set two target wave interval standard deviation threshold; the variance of the interval between two target waves is greater than a set two target wave interval variance threshold; and the variability of the interval between two target waves is greater than a set two target wave interval variability threshold.

[0102] In one embodiment, the reset unit resets the parameter attributes of all target waves based on the second number and the first number of abnormal target waves in the target wave: in response to the ratio between the second number and the first number of abnormal target waves being greater than a threshold, the parameter attributes of all target waves are reset.

[0103] In one embodiment, the determining unit determines abnormal target waves with abnormal parameter attributes based on a first number of parameter attributes of the detected target waves, and determines a second number of target waves with abnormal parameter attributes: in response to a first time interval, the number of abnormal parameter attribute waves is incremented by 1 for each detected abnormal parameter attribute wave in each period to obtain a second number of target waves with abnormal parameter attributes, and the initial value of the number of target waves with abnormal parameter attributes is 0.

[0104] In one implementation, the first number of parameter attributes is one or more of preset parameter attributes. The preset parameter attributes include at least one of the following: minimum number of detected target waves; maximum number of detected target waves; standard deviation of target wave amplitude; variance of target wave amplitude; variability of target wave amplitude; standard deviation of the interval between two target waves; variance of the interval between two target waves; variability of the interval between two target waves.

[0105] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0106] Figure 6This is a block diagram illustrating a device 200 for detecting electrocardiogram (ECG) signals according to an exemplary embodiment. For example, device 200 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0107] Reference Figure 6 The device 200 may include one or more of the following components: processing component 202, memory 204, power component 206, multimedia component 208, audio component 210, input / output (I / O) interface 212, sensor component 214, and communication component 216.

[0108] Processing component 202 typically controls the overall operation of device 200, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 202 may include one or more processors 220 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 202 may include one or more modules to facilitate interaction between processing component 202 and other components. For example, processing component 202 may include a multimedia module to facilitate interaction between multimedia component 208 and processing component 202.

[0109] Memory 204 is configured to store various types of data to support the operation of device 200. Examples of this data include instructions for any application or method operating on device 200, contact data, phonebook data, messages, pictures, videos, etc. Memory 204 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0110] The power supply component 206 provides power to the various components of the device 200. The power supply component 206 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to the device 200.

[0111] Multimedia component 208 includes a screen that provides an output interface between the device 200 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 208 includes a front-facing camera and / or a rear-facing camera. When the device 200 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0112] Audio component 210 is configured to output and / or input audio signals. For example, audio component 210 includes a microphone (MIC) configured to receive external audio signals when device 200 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 204 or transmitted via communication component 216. In some embodiments, audio component 210 also includes a speaker for outputting audio signals.

[0113] I / O interface 212 provides an interface between processing component 202 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0114] Sensor assembly 214 includes one or more sensors for providing status assessments of various aspects of device 200. For example, sensor assembly 214 may detect the on / off state of device 200, the relative positioning of components such as the display and keypad of device 200, changes in the position of device 200 or a component of device 200, the presence or absence of user contact with device 200, the orientation or acceleration / deceleration of device 200, and temperature changes of device 200. Sensor assembly 214 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 214 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 214 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0115] Communication component 216 is configured to facilitate wired or wireless communication between device 200 and other devices. Device 200 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 216 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 216 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0116] In an exemplary embodiment, device 200 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0117] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 204 including instructions, which can be executed by a processor 220 of device 200 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0118] It is understood that in this disclosure, "multiple" refers to two or more, and other quantifiers are similar. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. The singular forms "a," "the," and "the" are also intended to include the plural forms unless the context clearly indicates otherwise.

[0119] It is further understood that the terms "first," "second," etc., are used to describe various types of information, but this information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another, and do not indicate a specific order or degree of importance. In fact, the expressions "first," "second," etc., are completely interchangeable. For example, without departing from the scope of this disclosure, first information can also be referred to as second information, and similarly, second information can also be referred to as first information.

[0120] It is further understood that the terms “center,” “longitudinal,” “lateral,” “front,” “rear,” “up,” “down,” “left,” “right,” “vertical,” “horizontal,” “top,” “bottom,” “inner,” and “outer,” etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this embodiment and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation.

[0121] It can be further understood that, unless otherwise specified, "connection" includes both direct connections where no other components exist between the two parties and indirect connections where other components exist between them.

[0122] It is further understood that although operations are described in a specific order in the accompanying drawings in the embodiments of this disclosure, this should not be construed as requiring these operations to be performed in the specific order or serial order shown, or requiring all of the shown operations to be performed to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0123] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein.

[0124] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for detecting electrocardiogram (ECG) signals, characterized in that, The method includes: In response to the acquisition of an electrocardiogram (ECG) signal, the target wave in the ECG signal is periodically detected according to a set window. The target wave is the rising wave corresponding to the peak point with an amplitude greater than a reference threshold. In response to the periodic detection of the target wave in the electrocardiogram signal passing through a first time, abnormal parameter attributes in the target wave are determined based on a first number of parameter attributes, and the number of abnormal parameter attributes is cumulatively increased for each detection of the abnormal parameter attributes in each cycle to obtain a second number of the abnormal parameter attributes; Based on the ratio of the second quantity to the first quantity of the target wave anomaly parameter attributes, reset the parameter attributes of all target waves; Based on the reset parameter attributes, the target wave in the electrocardiogram signal after the first time interval is detected.

2. The electrocardiogram signal detection method according to claim 1, characterized in that, The abnormal parameter attributes include: the number of target waves is less than the minimum number threshold; The number of target waves is greater than the maximum number threshold; The standard deviation of the target wave amplitude is greater than the set target wave amplitude standard deviation threshold. The variance of the target wave amplitude is greater than the set target wave amplitude variance threshold; The target wave amplitude variation rate is greater than the set target wave amplitude variation rate threshold; The standard deviation of the two target interwave periods is greater than the set threshold for the standard deviation of the two target interwave periods; The variance between the two target interwave periods is greater than the set variance threshold between the two target interwave periods; The variation rate of the two target interwave periods is greater than the set threshold for the variation rate of the two target interwave periods.

3. The ECG signal detection method according to claim 1, wherein resetting the parameter attributes of all target waves based on the ratio of the second number to the first number of abnormal parameter attributes in the target wave includes: In response to the ratio between the second number and the first number of the abnormal parameter attributes of the target wave being greater than a threshold, the parameter attributes of all target waves are reset.

4. The electrocardiogram signal detection method according to claim 1, characterized in that, The initial value for the number of abnormal parameter attributes is 0.

5. The method according to claim 1 or 2, characterized in that, The first number of parameter attributes are one or more of the preset parameter attributes; The preset parameter attributes include at least one of the following: Minimum number of target waves; Maximum number of target waves; The standard deviation of the target wave amplitude; The variance of the target wave amplitude; The rate of variation of the target wave amplitude; The standard deviation of the interwave intervals between the two target waves; The variance of the two target interwave periods; Variation rate between two target wave periods.

6. An electrocardiogram (ECG) signal detection device, characterized in that, The device includes: The detection unit is used to periodically detect the target wave in the ECG signal according to a set window in response to the acquisition of the ECG signal. The target wave is the rising wave corresponding to the peak point with an amplitude greater than a reference threshold. Based on the reset parameter attributes, the target wave in the ECG signal after the first time period is detected. The determining unit is configured to respond to the periodic detection of the target wave in the electrocardiogram signal passing through the first time, determine the presence of abnormal parameter attributes in the abnormal target wave based on a first number of parameter attributes, and cumulatively increase the number of abnormal parameter attributes for each detection of the presence of the abnormal parameter attributes in each cycle to obtain a second number of the abnormal parameter attributes. The reset unit is used to reset the parameter attributes of all target waves based on the ratio of the second quantity of the abnormal parameter attributes of the abnormal target waves to the first quantity.

7. The electrocardiogram signal detection device according to claim 6, characterized in that, The determining unit determines the presence of the anomalous parameter attribute in the target wave using the following method: The number of target waves is less than the minimum number threshold; The number of target waves is greater than the maximum number threshold; The standard deviation of the target wave amplitude is greater than the set target wave amplitude standard deviation threshold. The variance of the target wave amplitude is greater than the set target wave amplitude variance threshold; The target wave amplitude variation rate is greater than the set target wave amplitude variation rate threshold; The standard deviation of the two target interwave periods is greater than the set threshold for the standard deviation of the two target interwave periods; The variance between the two target interwave periods is greater than the set variance threshold between the two target interwave periods; The variation rate of the two target interwave periods is greater than the set threshold for the variation rate of the two target interwave periods.

8. The ECG signal detection device according to claim 6, wherein the reset unit resets the parameter attributes of all target waves based on the ratio of the second number to the first number of abnormal parameter attributes in the target waves: In response to the ratio between the second number and the first number of abnormal target waves being greater than a threshold, the parameter attributes of all target waves are reset.

9. The electrocardiogram signal detection device according to claim 6, characterized in that, The initial value of the number of target waves in the abnormal parameter attribute is 0.

10. The apparatus according to claim 6 or 7, characterized in that, The first number of parameter attributes is one or more of the preset parameter attributes; The preset parameter attributes include at least one of the following: Minimum number of target waves detected; The maximum number of target waves detected; The standard deviation of the target wave amplitude; The variance of the target wave amplitude; The rate of variation of the target wave amplitude; The standard deviation of the interwave intervals between the two target waves; The variance of the two target interwave periods; Variation rate between two target wave periods.

11. An electrocardiogram (ECG) signal detection device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to execute the electrocardiogram signal detection method according to any one of claims 1-5.

12. A storage medium, characterized in that, The storage medium stores instructions that, when executed by the terminal's processor, enable the terminal to perform the method described in any one of claims 1-5.

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