High-frequency electrocardiosignal harmonic interference filtering method, device, equipment and medium

Abstract

The invention relates to the technical field of signal processing, and discloses a high-frequency electrocardiosignal harmonic interference filtering method, device and equipment and a medium, and the method comprises the steps: obtaining object information of a target object and an initial electrocardiosignal under a target lead; determining the initial spectrum intensity of the preset frequency point; determining a target group of the target object; based on the target group reference intensity value of the target group, determining a lead reference value, corresponding to the preset frequency point, of the target object under the target lead; based on the initial spectrum intensity corresponding to the preset frequency point and the lead reference value, whether harmonic interference exists in the initial electrocardiosignal or not is judged; and the electrocardiosignals with harmonic interference are filtered out. By accurately identifying and filtering high-frequency harmonic interference, useful high-frequency details are reserved as far as possible under the condition that the harmonic interference is filtered, the authenticity and effectiveness of electrocardiogram signals are guaranteed, doctors can make more accurate diagnosis, and misjudgment of interference signals on electrocardiogram waveforms is avoided.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, specifically to a method, apparatus, device, and medium for filtering out harmonic interference in high-frequency electrocardiogram signals. Background Technology

[0002] Electrocardiography (ECG) is an important tool for recording cardiac electrical activity and is widely used in clinical diagnosis and physiological research. With the development of data acquisition technology, the application of high-frequency ECG data is becoming increasingly widespread. However, during high-frequency sampling, ECG signals are susceptible to various electromagnetic interferences, especially power supply harmonic interference. These interferences mainly manifest as fixed-frequency harmonic signals superimposed on the ECG signal, leading to signal distortion and affecting diagnostic accuracy.

[0003] Traditional electrocardiograms (ECGs) typically use a 50Hz notch filter to remove power line interference. This is effective for routine ECG signal processing. However, for high-frequency ECG data analysis, the dominant signal frequency band is between 150-250Hz. Within this band, although the signal strength is lower, it is extremely sensitive and easily affected by interference. In particular, the 3rd, 4th, and 5th harmonics in the ECG (150Hz, 200Hz, and 250Hz, respectively) fall precisely within this high-frequency range. These harmonic interferences often overlap with useful physiological signals, and traditional ECG equipment does not specifically address these frequencies, resulting in ineffective filtering of these interference signals and affecting the accurate analysis of high-frequency data. In subsequent data processing, traditional methods for filtering high-frequency ECG signals often use fixed parameters or thresholds. This approach may filter out some useful high-frequency information while removing noise. This can affect some critical details in the ECG signal, leading to misdiagnosis or missed diagnosis. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and medium for filtering harmonic interference in high-frequency electrocardiogram (ECG) signals, in order to solve the problem that critical signals are easily lost when filtering high-frequency ECG signals in the prior art.

[0005] In a first aspect, the present invention provides a method for filtering harmonic interference from high-frequency electrocardiogram signals, the method comprising: Acquire object information of the target object and the initial electrocardiogram signal under the target lead; The initial spectral intensity of a preset frequency point is determined based on the initial electrocardiogram signal; the preset frequency point is greater than or equal to 100Hz. Based on object information, the target group of the target object is determined; the target group is determined from multiple groups, and the multiple groups are grouped into different individuals according to preset conditions; Based on the baseline intensity value of the target population in the target group, determine the baseline value of the lead corresponding to the preset frequency point under the target lead; Based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value, determine whether there is harmonic interference in the initial electrocardiogram signal; The target ECG signal is obtained by filtering out ECG signals containing harmonic interference.

[0006] In one optional implementation, the preset frequency point includes at least one of 150Hz, 200Hz, and 250Hz.

[0007] In one alternative implementation, the step of determining the baseline intensity values ​​for multiple groups includes: Acquire a preprocessed set of ECG signals, which includes the baseline ECG signals of different individuals in each lead; Based on the reference electrocardiogram signal, determine the reference spectral intensity of the corresponding lead at a preset frequency point; Individuals are grouped according to preset criteria to obtain multiple groups; Based on the baseline spectral intensity, the baseline intensity value of each group at each lead is determined to correspond to the preset frequency point.

[0008] In one optional implementation, based on the target population baseline intensity value of the target group, the lead baseline value corresponding to the preset frequency point under the target lead is determined, including: Based on the baseline spectral intensity, the mean and standard deviation of the population intensity corresponding to the preset frequency point under the target lead are determined; Based on the standard deviation and mean of population intensity of the target group at the target lead and the preset frequency point, the correction coefficient of the target group at the target lead and the preset frequency point is determined. The reference value of the target group is the product of the target population baseline intensity value and the correction coefficient at the preset frequency point under the target lead.

[0009] In one optional implementation, based on the target population baseline intensity value of the target group, the lead baseline value corresponding to the preset frequency point under the target lead is determined, including: Determine the signal-to-noise ratio of the initial electrocardiogram signal; The correction coefficients are determined based on the signal-to-noise ratio. The reference value of the target group is the product of the target population baseline intensity value and the correction coefficient at the preset frequency point under the target lead.

[0010] In one optional implementation, based on the target population baseline intensity value of the target group, the lead baseline value corresponding to the preset frequency point under the target lead is determined, including: Based on the baseline electrocardiogram signal of the target subject under the target lead, determine the individual baseline intensity value of the target subject at the preset frequency point; Based on the individual baseline intensity value and the target population baseline intensity value of the target group, determine the lead baseline value corresponding to the preset frequency point under the target lead.

[0011] In one optional implementation, determining the initial spectral intensity at a preset frequency point based on the initial electrocardiogram signal includes: Perform Fourier transform on the ECG signal corresponding to each heartbeat cycle in the initial ECG signal to determine the initial spectral intensity of each heartbeat cycle at a preset frequency point; Based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value, determine whether there is harmonic interference in the initial ECG signal, including: Compare the initial spectral intensity with the lead reference value; If the first ratio of the initial spectral intensity to the lead reference value is greater than or equal to the first preset threshold, it is determined that there is interference in the ECG signal of the corresponding heartbeat cycle. Determine the second ratio of the number of heartbeat cycles with interference to the total number of heartbeat cycles in the initial electrocardiogram signal; If the second ratio is greater than or equal to the second preset threshold, it is determined that the initial electrocardiogram signal has harmonic interference.

[0012] In one optional implementation, determining the initial spectral intensity at a preset frequency point based on the initial electrocardiogram signal includes: Perform a Fourier transform on the initial electrocardiogram signal to determine the initial spectral intensity at a preset frequency point; Alternatively, a Fourier transform can be performed on the electrocardiogram (ECG) signal to determine the initial spectral intensity at a preset frequency point; the ECG signal is derived from the segmentation of the initial ECG signal. Based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value, determine whether there is harmonic interference in the initial ECG signal, including: Compare the initial spectral intensity with the lead reference value; If the ratio of the initial spectral intensity to the third lead reference value is greater than or equal to the third preset threshold, it is determined that the initial ECG signal has harmonic interference.

[0013] In one optional implementation, filtering out harmonic interference from the electrocardiogram (ECG) signal to obtain the target ECG signal includes: If harmonic interference is determined to exist, the filter parameters are determined based on the initial spectral intensity and lead reference value corresponding to the preset frequency point, and the target filter is obtained. Filtering of ECG signals with harmonic interference based on target filters.

[0014] In a second aspect, the present invention provides a high-frequency electrocardiogram signal harmonic interference filtering device, the device comprising: The acquisition module is used to acquire object information of the target object and the initial electrocardiogram signal under the target lead; The spectrum intensity determination module is used to determine the initial spectrum intensity at a preset frequency point based on the initial electrocardiogram signal; the preset frequency point is greater than or equal to 100Hz. The group determination module is used to determine the target group of a target object based on object information; the target group is determined from multiple groups, and the multiple groups are obtained by grouping different individuals according to preset conditions; The baseline value determination module is used to determine the baseline value of the target object under the target lead and the corresponding preset frequency point based on the baseline intensity value of the target population of the target group. The judgment module is used to determine whether there is harmonic interference in the initial electrocardiogram signal based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value. The filtering module is used to filter out ECG signals with harmonic interference to obtain the target ECG signal.

[0015] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the high-frequency electrocardiogram signal harmonic interference filtering method described in the first aspect or any corresponding embodiment.

[0016] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the high-frequency electrocardiogram signal harmonic interference filtering method of the first aspect or any corresponding embodiment described above.

[0017] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the high-frequency electrocardiogram signal harmonic interference filtering method described in the first aspect or any corresponding embodiment thereof.

[0018] The beneficial effects of this invention are as follows: The high-frequency harmonic interference filtering method for electrocardiogram (ECG) signals provided by this invention accurately identifies and filters out high-frequency harmonic interference, preserving as much useful high-frequency detail as possible while filtering out harmonic interference. This ensures the authenticity and effectiveness of the ECG signal, helping doctors make more accurate diagnoses and avoiding misinterpretations of ECG waveforms by interference signals. Furthermore, this invention avoids the problems of incomplete harmonic interference filtering or loss of useful high-frequency detail information caused by traditional filtering methods using fixed parameters or thresholds, effectively improving the accuracy of high-frequency harmonic interference identification and filtering. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating a high-frequency electrocardiogram signal harmonic interference filtering method according to an embodiment of the present invention; Figure 2 This is a structural block diagram of a high-frequency electrocardiogram signal harmonic interference filtering device according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0023] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0024] Traditional filtering methods, such as low-pass filters, high-pass filters, and band-stop filters, can reduce interference to some extent, but they often lose some useful ECG signal components, especially high-frequency details. How to effectively detect and eliminate harmonic interference while preserving ECG signal characteristics has become an urgent problem to be solved.

[0025] In view of this, according to an embodiment of the present invention, a method for filtering out harmonic interference of high-frequency electrocardiogram signals is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0026] This embodiment provides a method for filtering high-frequency electrocardiogram signal harmonic interference, which can be used in servers, terminals, and mobile terminals such as mobile phones and tablets. Figure 1 This is a flowchart of a high-frequency electrocardiogram signal harmonic interference filtering method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: Obtain the object information of the target object and the initial electrocardiogram signal under the target lead.

[0027] In this embodiment, the target object can be an object whose electrocardiogram (ECG) has already been acquired. The initial ECG signal is the raw, unprocessed ECG signal from one lead acquired under mains power, which may contain high-frequency harmonic interference from the power supply or equipment. Alternatively, the initial ECG signal can also be the raw, unprocessed ECG signal from one lead acquired without mains power. This embodiment also requires acquiring object information of the target object, including information such as age, gender, and body mass index (BMI). During ECG signal acquisition, multiple ECG leads (hereinafter referred to as leads) are used to acquire ECG signals. The number of leads is not limited to 12, but can also be 18 or 24, and is not listed here. In this embodiment, the initial ECG signal under the target lead can be the ECG signal recorded in any one of the leads.

[0028] Step S102: Determine the initial spectral intensity of a preset frequency point based on the initial electrocardiogram signal; the preset frequency point is greater than or equal to 100Hz.

[0029] In this embodiment, the initial spectral intensity at a preset frequency point is determined by performing frequency domain analysis, such as Fourier transform, on the initial electrocardiogram (ECG) signal. The preset frequency point is greater than or equal to 100Hz, preferably an integer multiple of 50Hz, and this integer is greater than or equal to 3, meaning it mainly focuses on the high-frequency region of the ECG signal, such as 150Hz, 200Hz, 250Hz, 300Hz, etc., which are not listed here. If the spectral intensity of a certain frequency point is abnormally high, it may indicate the presence of harmonic interference at that frequency point (i.e., that frequency point is the main frequency component of harmonic interference). In this embodiment, at least one frequency point among 150Hz, 200Hz, 250Hz, etc., can be used as a common interference frequency point for focused analysis, wherein the preset frequency point is preferably 150Hz. It is worth noting that the spectral intensity at a certain frequency point can be the amplitude of the ECG signal at that frequency point in the frequency domain, or the sum, average, or maximum value of the ECG signal amplitudes within a frequency range centered on that frequency point and with a preset bandwidth (which can be denoted as the target amplitude). The preset bandwidth can be customized according to the actual application scenario (such as the power frequency fluctuation range or the narrowband characteristics of interference signals), and its unit is Hertz (Hz), which can be any value within the range of [1, 10] Hz.

[0030] Step S103: Based on the object information, determine the target group of the target object; the target group is determined from multiple groups, and the multiple groups are obtained by grouping different individuals according to preset conditions.

[0031] Based on the target object's information, the target group to which the target object belongs can be inferred. Here, preset conditions refer to pre-defined feature filtering and classification conditions used for group division. That is, preset conditions are a series of pre-defined features or rules used to filter and classify individuals. These preset conditions include, but are not limited to, individual characteristics such as age, gender, and BMI. For example, individuals who are male, aged 18-20, and have a BMI of 20-21 are grouped into the same group. By analyzing the target object's information, the target group to which the target object may belong can be determined. The following example illustrates this: Suppose the following groups are divided according to preset conditions: Group 1: Age range 18-30 years, male, BMI between 17.9 and 23.9; The second group consists of women aged 31-50 with a BMI between 17.9 and 23.9. The third group consists of individuals aged 51-60, males, and with a BMI between 24 and 27.9.

[0032] If the target object's information is: age 28, gender male, BMI value 22.

[0033] Based on the above information, it can be inferred that the target belongs to the "first group".

[0034] Because individuals in different groups exhibit varying harmonic interference characteristics due to differences in physiological features (age, gender, BMI, etc.), there are consistent differences in these characteristics (i.e., the differences in harmonic interference characteristics are small within the same group, but large between different groups). Therefore, it is necessary to select a suitable target group from multiple groups based on the object information, thereby providing a basis for the identification and processing of harmonic interference in the target object.

[0035] Step S104: Based on the target population baseline intensity value of the target group, determine the lead baseline value of the target object under the target lead that corresponds one-to-one with the preset frequency point.

[0036] Each group includes a population baseline intensity value corresponding to a preset frequency point under each lead. In this embodiment, after determining the target group corresponding to the target population, the corresponding target population baseline intensity value can be determined. The population baseline intensity value can be obtained by averaging, maximizing, or medianing the spectral intensity of all individuals within the group under the same lead and the same preset frequency point. In this embodiment, the lead baseline value is standard reference data obtained under the condition of no harmonic interference. Specifically, it can be further calculated based on the population baseline intensity value, or the determined population baseline intensity value can be directly used as the lead baseline value.

[0037] Step S105: Based on the initial spectral intensity corresponding to the preset frequency points and the lead reference value, determine whether there is harmonic interference in the initial electrocardiogram signal.

[0038] For example, if the initial spectral intensity at a frequency of 150Hz is high and exceeds the corresponding lead reference value, it can be inferred that the signal at that frequency may have harmonic interference. In this embodiment, the length of the ECG signal used to determine the initial spectral intensity is the same as the length of the ECG signal used to determine the lead reference value. For example, both are ECG signals corresponding to a single heartbeat cycle, or both are ECG signals of a preset length, including but not limited to 10 seconds, 1 minute, 3 minutes, and 5 minutes, which can be customized according to actual needs and are not specifically limited here.

[0039] Step S106: Filter out the ECG signal with harmonic interference to obtain the target ECG signal.

[0040] Once harmonic interference is confirmed, high-frequency harmonic interference can be removed using filtering algorithms. The signal after harmonic interference filtering can be further restored to a clean electrocardiogram (ECG) signal, thus improving the diagnostic quality of the ECG signal. The final target ECG signal should accurately reflect the target subject's cardiac health status without interference.

[0041] High-frequency ECG analysis primarily analyzes data at 150Hz and above. Human ECG signals in this range have extremely low energy intensity, only about 3% of that in low-to-mid-frequency data, making them highly susceptible to harmonic interference, which can lead to analysis failure. To address the harmonic interference problem present in the full-frequency ECG data (0-300Hz) acquired by traditional ECG machines, potential harmonics must be detected and eliminated before analysis. In this embodiment, high-frequency harmonic interference is accurately identified and filtered out. While filtering out harmonic interference, useful high-frequency details are preserved as much as possible, ensuring the authenticity and validity of the ECG signal. This helps doctors make more accurate diagnoses and avoids misinterpretation of the ECG waveform by interference signals.

[0042] This embodiment also provides a method for filtering out harmonic interference from high-frequency electrocardiogram signals, which can be used in servers, terminals, and mobile terminals such as mobile phones and tablets. The process includes the following steps: Step S201: Obtain the target object's information and the initial ECG signal in the target lead. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0043] Step S202: Determine the initial spectral intensity of a preset frequency point based on the initial electrocardiogram signal; the preset frequency point is greater than or equal to 100Hz. In some optional embodiments, the preset frequency point includes at least one of 150Hz, 200Hz, and 250Hz.

[0044] In some optional implementations, step S202 includes: performing a Fourier transform on the ECG signal corresponding to each heartbeat cycle in the initial ECG signal to determine the initial spectral intensity of each heartbeat cycle at a preset frequency point.

[0045] In this embodiment, a Fourier transform is performed on the ECG signal of each heartbeat cycle in the initial ECG signal, and the initial spectral intensity of the ECG signal of each heartbeat cycle at each preset frequency point is calculated.

[0046] In some optional implementations, step S202 includes: performing a Fourier transform on the initial electrocardiogram signal to determine the initial spectral intensity at a preset frequency point.

[0047] In this embodiment, a Fourier transform is performed on the initial electrocardiogram signal as a whole to determine the initial spectral intensity of each preset frequency point.

[0048] In some optional implementations, step S202 includes: performing a Fourier transform on the electrocardiogram signal to determine the initial spectral intensity at a preset frequency point; the electrocardiogram signal is derived from the segmentation of the initial electrocardiogram signal.

[0049] In this embodiment, the initial electrocardiogram (ECG) signal is segmented, for example, into multiple ECG signals with a width of 10 seconds. Then, a Fourier transform is performed on each ECG signal, and the initial spectral intensity of each ECG signal at each preset frequency point is calculated.

[0050] It is understandable that in some application scenarios, such as when a nonlinear load operates continuously and the load is stable, or when there are no significant changes in the power grid topology, harmonic interference is usually relatively stable and will not suddenly disappear. Therefore, a Fourier transform can be performed on one or more cardiac electronic signals in the initial electrocardiogram (ECG) signal, and the initial spectral intensity of the one or more cardiac electronic signals at each preset frequency point can be calculated. If, referring to the harmonic interference identification method in one or more embodiments of this application, it is determined that the one or more cardiac electronic signals have harmonic interference, then it is determined that the initial ECG signal has harmonic interference.

[0051] In this embodiment, when performing Fourier transform on the initial ECG signal, the length of the time-domain ECG signal before the Fourier transform should be the same as the length of the time-domain ECG signal when calculating the baseline intensity value of the population, such as 10 seconds. Then, the spectral intensity of each frequency point is calculated in the frequency domain to assess whether there is harmonic interference based on the spectral intensity.

[0052] Step S203: Based on the object information, determine the target group of the target object; the target group is determined from multiple groups, and the multiple groups are obtained by grouping different individuals according to preset conditions. For details, please refer to [link to details]. Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0053] Step S204: Based on the target population baseline intensity value of the target group, determine the lead baseline value of the target object under the target lead that corresponds one-to-one with the preset frequency point.

[0054] In this embodiment, each group includes a baseline intensity value corresponding to a preset frequency point under each lead. Specifically, the average, maximum, or median of the baseline spectral intensity of all individuals within the group at the same lead and frequency point can be calculated to obtain the baseline intensity value of that group. In this embodiment, after determining the target group corresponding to the target population, the corresponding baseline intensity value of the target population can be determined.

[0055] Specifically, the steps for determining the baseline intensity values ​​for multiple population groups include: Step a1: Obtain the preprocessed ECG signal set, which includes the baseline ECG signals of different individuals in each lead.

[0056] In this embodiment, raw electrocardiogram (ECG) signals from different individuals (e.g., different genders, ages, and BMI values) across various leads are collected without the use of mains power to ensure the richness and diversity of the data sample. Each acquisition lasts at least 10 seconds. Then, basic preprocessing is performed on the raw ECG signals to remove obviously erroneous signals, resulting in a baseline ECG signal and thus a set of ECG signals.

[0057] Step a2: Based on the reference electrocardiogram signal, determine the reference spectral intensity of the corresponding lead at the preset frequency point.

[0058] Specifically, refer to the method for determining the initial spectral intensity in step S202 above. That is, perform a Fourier transform on the ECG signal corresponding to each heartbeat cycle in the reference ECG signal to determine the spectral intensity of the ECG signal at each preset frequency point for each heartbeat cycle, and use the mean, median, or maximum value of the spectral intensity of all heartbeat cycles at a single preset frequency point as the reference spectral intensity of the corresponding individual in the corresponding lead at that preset frequency point. Alternatively, perform a Fourier transform on the reference ECG signal to determine the reference spectral intensity at each preset frequency point. Or, perform a Fourier transform on the electrocardiogram (ECG) signal to determine the reference spectral intensity at each preset frequency point; the ECG signal is derived from the segmentation of the reference ECG signal. The spectral intensity of a single ECG signal at a preset frequency point in the reference ECG signal can be used as the reference spectral intensity of the corresponding individual in the corresponding lead at that preset frequency point; alternatively, the mean, median, or maximum value of the spectral intensities of multiple ECG signals at preset frequency points in the reference ECG signal can be used as the reference spectral intensity of the corresponding individual in the corresponding lead at that preset frequency point.

[0059] Step a3: Group different individuals according to preset conditions to obtain multiple groups. For example, group individuals who are male, aged 18-20, and have a BMI of 20-21 into the same group to obtain multiple groups.

[0060] Step a4: Based on the baseline spectral intensity, determine the population baseline intensity value corresponding to a preset frequency point for each group in each lead. The population baseline intensity value is used to determine the lead baseline value corresponding to the preset frequency point for the target group in the target lead. Specifically, the average, maximum, or median of the baseline spectral intensity of all individuals in the group at the same lead and frequency point can be calculated to obtain the population baseline intensity value for that group.

[0061] In some optional implementations, step S204 above includes: Step b1: Based on the reference spectral intensity, determine the mean and standard deviation of the population intensity of the target group at the preset frequency point under the target lead.

[0062] In this embodiment, the mean population intensity is obtained by averaging the baseline spectral intensity of all individuals within the target group at the same lead and frequency. If the baseline population intensity is the average of the baseline spectral intensity of all individuals within the target group at the same lead and frequency, then the baseline population intensity value of the target group at the target lead and corresponding to the preset frequency can be used as the mean population intensity. The standard deviation of the population intensity can be calculated using the following formula: ; Where N is the number of individuals in the target group. Let i be the baseline spectral intensity of the i-th individual. This represents the average intensity of the population.

[0063] Step b2: Based on the standard deviation and mean of population intensity of the target group at the target lead and the preset frequency point, determine the correction coefficient of the target group at the target lead and the preset frequency point.

[0064] Specifically, the correction coefficient can be dynamically determined based on the standard deviation and mean of the population intensity at the preset frequency point. For example, the correction coefficient = C + D × standard deviation of population intensity / mean of population intensity, where C ranges from [1, 1.6] and D ranges from [0.1, 0.2]. Thus, the larger the standard deviation (i.e., the dispersion of the reference spectrum intensity within the group), the larger the correction coefficient and the higher the reference value, thereby reducing the risk of misjudgment.

[0065] Step b3: The product of the target population baseline intensity value and the correction coefficient corresponding to the preset frequency point under the target lead is used as the lead baseline value.

[0066] In some optional implementations, step S204 above includes: Step c1: Determine the signal-to-noise ratio of the initial ECG signal.

[0067] Step c2: Determine the correction coefficients based on the signal-to-noise ratio.

[0068] Step c3: The product of the target population baseline intensity value and the correction coefficient corresponding to the preset frequency point under the target lead is used as the lead baseline value.

[0069] In this embodiment, the correction coefficient can also be determined based on the signal-to-noise ratio (SNR) of the initial ECG signal to be filtered. A higher SNR results in a larger correction coefficient, which is greater than 1. For example, if the SNR is greater than or equal to 20 dB, the correction coefficient is 1.5; if the SNR is less than 20 dB, the correction coefficient is 1.3, to improve the detection rate of weak signals. In other words, the SNR reflects signal reliability. A higher SNR indicates a higher proportion of useful signals and clearer interference characteristics, allowing for a reduction in "normal signals being misjudged as interference" through strict thresholding. Conversely, a lower SNR allows noise to mix with useful information, requiring a more relaxed threshold to avoid "missed interference detection."

[0070] In some optional implementations, step S204 above includes: Step d1: Determine the individual baseline intensity value of the target object at a preset frequency point based on the baseline ECG signal of the target object under the target lead.

[0071] Step d2: Based on the individual baseline intensity value and the target population baseline intensity value of the target group, determine the lead baseline value corresponding to the preset frequency point under the target lead for the target object.

[0072] That is, if the ECG signal set contains the reference ECG signal of the target object, the reference spectral intensity calculated according to the corresponding embodiment of this application will be used as the individual reference intensity value of the target object. If the ECG signal set does not contain the reference ECG signal of the target object, the reference ECG signal of the user (individual) in each lead will be collected without the use of mains power. The reference spectral intensity of the collected reference ECG signal at the corresponding lead and the corresponding preset frequency point will be determined according to the method of determining the reference spectral intensity based on the reference ECG signal described in one or more embodiments of this application. The reference spectral intensity will then be used as the individual reference intensity value of the target object, thereby obtaining the individual reference intensity value of the target object at the target lead and the preset frequency point.

[0073] Then, following the method for determining the population baseline intensity value described in one or more embodiments of this application, the target population baseline intensity value corresponding to the target group to which the target object belongs and the preset frequency point under the target lead is determined. Further, for a single preset frequency point, the target population baseline intensity value of the target group under the target lead and the individual baseline intensity value of the target object under the target lead are weighted and summed to obtain the comprehensive baseline intensity value of the target object under the target lead and the preset frequency point. The individual baseline intensity value can be calculated based on a 10-second ECG signal or based on multiple 10-second ECG signals. The weight of the individual baseline intensity value can be dynamically determined based on the signal-to-noise ratio of the initial ECG signal to be filtered, and the two are positively correlated. The sum of the weights of the target population baseline intensity value and the individual baseline intensity value is 1.

[0074] In this embodiment, the comprehensive reference strength value can be directly used as the lead reference value. Alternatively, the product of the comprehensive reference strength value and the correction coefficient can be used as the lead reference value. The correction coefficient can be determined by referring to steps b1 and b2, or steps c1 and c2, as described above.

[0075] Alternatively, based on the baseline spectral intensity, first determine the mean and standard deviation of the population intensity at the target lead corresponding to the preset frequency point for the target group; then, based on the standard deviation and mean of the population intensity at the target lead corresponding to the preset frequency point for the target group, determine the correction coefficient for the target group at the target lead corresponding to the preset frequency point. Further, calculate the product of the target population baseline intensity value at the target lead corresponding to the preset frequency point and the correction coefficient to obtain the initial baseline value; finally, sum this initial baseline value with the individual baseline intensity value at the preset frequency point to obtain the final lead baseline value.

[0076] By comprehensively considering the baseline intensity value of the target population to which the target object belongs, as well as the individual baseline intensity value of the target object, the lead baseline value is obtained. This fully takes into account individual characteristics, effectively improves individual adaptability, achieves a balance between commonality and individuality, and can further improve the accuracy of interference identification.

[0077] Step S205: Based on the initial spectral intensity corresponding to the preset frequency points and the lead reference value, determine whether there is harmonic interference in the initial electrocardiogram signal.

[0078] In some optional implementations, step S205 above includes: Step S2051: Compare the initial spectral intensity with the lead reference value.

[0079] Step S2052: If the first ratio of the initial spectral intensity to the lead reference value is greater than or equal to the first preset threshold, it is determined that there is interference in the ECG signal of the corresponding heartbeat cycle.

[0080] Step S2053: Determine the second ratio of the number of heartbeat cycles with interference to the total number of heartbeat cycles in the initial electrocardiogram signal.

[0081] Step S2055: If the second ratio is greater than or equal to the second preset threshold, it is determined that the initial electrocardiogram signal has harmonic interference.

[0082] This embodiment describes a method for determining harmonic interference when performing a Fourier transform on an electrocardiogram signal for a single heartbeat cycle.

[0083] Specifically, the initial spectral intensity at a preset frequency point is calculated for each heartbeat cycle of the initial ECG signal, and compared with the lead reference value at that preset frequency point in the target lead. For example, it is determined whether the ratio of the initial spectral intensity to the lead reference value is greater than or equal to a first preset threshold to determine if interference exists in the ECG signal of that heartbeat cycle. Then, the proportion of heartbeat cycles with interference in the ECG signal is calculated among all heartbeat cycles. If the proportion is greater than or equal to a second preset threshold, it is determined to be "real interference" (mains interference is persistent and has a high proportion), i.e., the initial ECG signal has harmonic interference; if the proportion is less than the second preset threshold, it is determined to be "normal signal fluctuation." The first and second preset thresholds can be customized according to actual conditions. For example, the first preset threshold can be any value in [2, 5], and the second preset threshold can be any value in [60%, 80%]. If harmonic interference is determined to exist, it is filtered out using a filter. Specifically, if harmonic interference is determined to exist in the initial ECG signal based on the ECG signals of each heartbeat cycle, the target ECG signal can be obtained either by filtering out harmonic interference from the entire initial ECG signal, or by filtering out harmonic interference from the ECG signals of the heartbeat cycles with interference, and then obtaining the target ECG signal based on the ECG signals of each heartbeat cycle in sequence (including the ECG signals of the heartbeat cycles where harmonic interference is determined to be absent and the ECG signals of each heartbeat cycle after harmonic interference filtering). The filter can specifically be a notch filter.

[0084] In one optional implementation, step S205 includes: If the ratio of the initial spectral intensity to the lead reference value is greater than or equal to a third preset threshold, it is determined that harmonic interference exists in the initial ECG signal. The third preset threshold is greater than or equal to a first preset threshold.

[0085] In this embodiment, the initial electrocardiogram (ECG) signal is subjected to a Fourier transform, and the determined initial spectral intensity is directly compared with the corresponding lead reference value to determine whether the initial ECG signal has harmonic interference, so as to filter the initial ECG signal with harmonic interference.

[0086] Alternatively, the initial ECG signal can be divided into multiple ECG signals of preset duration. A Fourier transform is performed on each ECG signal to obtain its initial spectral intensity at a preset frequency point. This initial spectral intensity is then compared with the baseline value of the target object in the target lead at the preset frequency point to determine if harmonic interference exists in each ECG signal. In other words, harmonic interference is assessed for each ECG signal individually. ECG signals with harmonic interference are filtered, and the filtered ECG signal, i.e., the target ECG signal, is reconstructed based on the timing of each ECG signal. The preset duration can be customized according to actual needs, such as 10 seconds.

[0087] Alternatively, the initial ECG signal can be divided into multiple ECG signals of preset duration. A Fourier transform is performed on one or more of these ECG signals to obtain their initial spectral intensity at a preset frequency point. This initial spectral intensity is then compared with the reference values ​​of the target lead at the preset frequency point to determine if harmonic interference exists. If harmonic interference is present, the initial ECG signal is determined to have harmonic interference, and harmonic interference filtering is then performed. In other words, for cases where harmonic interference is relatively continuous and stable, the presence of harmonic interference in the initial ECG signal is determined based on one or more ECG signals within the initial ECG signal.

[0088] Step S206: Filter out the ECG signal with harmonic interference to obtain the target ECG signal.

[0089] Specifically, step S206 includes: Step S2061: If it is determined that there is harmonic interference, the filter parameters are determined based on the initial spectral intensity corresponding to the preset frequency point and the corresponding lead reference value, and the target filter is obtained. Step S2062: Filter the ECG signal with harmonic interference based on the target filter.

[0090] In this embodiment, the parameters (bandwidth and quality factor) and order (e.g., second-order, fourth-order) of the notch filter are determined based on the initial spectral intensity of the initial ECG signal and the lead reference value. For example, if the initial spectral intensity is less than or equal to three times the lead reference value, a two-stage notch filter is used, with a bandwidth of 3Hz and a quality factor of 30. If the initial spectral intensity is greater than three times the lead reference value, a four-stage notch filter (two cascaded second-order notch filters) is used, with a bandwidth of 2Hz and a quality factor of 40.

[0091] Alternatively, this formula can be directly used to filter ECG signals that contain harmonic interference: ; in, , ω is the digital angular frequency, representing the digital angular frequency corresponding to the center frequency of the notch filter, and is used to determine the frequency suppression position of the notch filter. To simulate the center frequency of the notch filter, we represent the frequency of the analog signal to be suppressed, i.e., the target frequency of the notch filter, such as 150Hz; z is the frequency response variable on the complex plane, i.e., the complex plane variable or the Z-transform complex variable, used to represent the frequency domain behavior of the signal; r is the pole radius, used to control the notch filter bandwidth, which is related to the bandwidth and quality factor of the notch filter. The closer r is to 1, the narrower the bandwidth and the higher the quality factor. The approximate relationship between bandwidth and r is: BW≈2(1-r). When r approaches 1, the bandwidth approaches 0, and the notch filter is extremely narrow.

[0092] In one embodiment, after acquiring the initial ECG signals of the target object in each lead, any one lead can be used as the target lead. Following the method described in one or more embodiments of this application, it is determined whether the initial ECG signal corresponding to the target lead has harmonic interference. If it is determined that the initial ECG signal of the target lead has harmonic interference, then it is determined that the initial ECG signals of the target object in all leads have harmonic interference, and harmonic interference filtering is then performed on each lead. Alternatively, each lead can be used as a target lead, and following the method described in one or more embodiments of this application, it is determined whether the initial ECG signal corresponding to each target lead has harmonic interference. Harmonic interference filtering is then performed on the initial ECG signals with harmonic interference. This allows for a more accurate determination of whether harmonic interference exists in the ECG signals of each lead and enables targeted processing.

[0093] Similarly, if there are multiple preset frequency points, the presence of harmonic interference at any one of the preset frequency points of the initial electrocardiogram (ECG) signal can be determined according to the method described in one or more embodiments of this application. If harmonic interference is found at that preset frequency point, it is determined that harmonic interference exists at all preset frequency points, and the harmonic interference at all preset frequency points is filtered out. Alternatively, the presence of harmonic interference at each preset frequency point of the initial ECG signal can be determined according to the method described in one or more embodiments of this application, and harmonic interference filtering is performed on the signal at the preset frequency points where harmonic interference exists. In this way, the identification and filtering of harmonic interference at each preset frequency point can further improve the accuracy of high-frequency harmonic interference identification and filtering.

[0094] In one embodiment, the erroneously deleted useful ECG signal is repaired through fidelity compensation. Specifically, the erroneously deleted high-frequency components can be reconstructed through linear fitting or polynomial fitting. The erroneously deleted high-frequency components refer to the high-frequency components (i.e., high-frequency details) of the ECG signal at the preset frequency point that are simultaneously filtered out when the target filter removes harmonic interference at the preset frequency point.

[0095] In one embodiment, if it is determined whether there is harmonic interference in the corresponding initial ECG signal based on the ECG signal of each heartbeat cycle, after performing harmonic interference filtering on the ECG signal of the heartbeat cycle with harmonic interference, the high-frequency components of the ECG signal of each heartbeat cycle that were filtered out at the corresponding preset frequency point are reconstructed based on the average or median of the spectral intensity of the ECG signal of all heartbeat cycles without harmonic interference at each preset frequency point. Then, based on the ECG signal of each heartbeat cycle in time sequence, the target ECG signal with harmonic interference filtered out and high-frequency details retained is obtained.

[0096] In one embodiment, the high-frequency feature retention rate within a preset frequency range is calculated based on the power spectrum of the reference ECG signal and the power spectrum of the filtered ECG signal (i.e., the target ECG signal). The interference residual at each preset frequency point is calculated based on the amplitude of the reference and target ECG signals at those preset frequency points. The largest interference residual is taken as the target interference residual. The signal quality of the target ECG signal is then evaluated based on the high-frequency feature retention rate and the target interference residual, allowing for dynamic adjustment of the lead reference values ​​and / or filter parameters based on the evaluated signal quality. The preset frequency range can be customized, specifically 100-300Hz.

[0097] For the retention rate of high-frequency features in the 100-300Hz range, the following formula can be used for evaluation: ; Where FR is the high-frequency feature retention rate, and P(f) is the power spectrum (calculated via Fourier transform). The power spectrum of the reference electrocardiogram signal, This is the power spectrum of the filtered ECG signal (i.e., the target ECG signal).

[0098] In this embodiment, FR≥92% can be set as the target to ensure that features such as late ventricular potentials are not lost.

[0099] For the three frequency points of 150, 200, and 250 Hz, the residual interference The calculation can be performed using this formula: ; Where A(f) is the amplitude at frequency f (extracted through Fourier transform), and the maximum value at the three frequency points is taken as the final amplitude. (≤0.3uV is considered compliant).

[0100] This invention acquires baseline ECG signals from various population groups in each lead under conditions without mains power, performs Fourier transform to determine baseline spectral intensities at preset frequency points such as 150Hz, 200Hz, and 250Hz, and analyzes the population baseline intensity values ​​for each group in each lead at each preset frequency point. This yields the lead baseline values ​​for each group in each lead at each preset frequency point. After acquiring the initial ECG signal of the target object for harmonic interference identification and filtering, the initial spectral intensity at the preset frequency point is determined based on the initial ECG signal of a single lead. This initial spectral intensity is then compared with the lead baseline value at that preset frequency point to determine whether harmonic interference exists in the corresponding ECG signal, allowing for targeted harmonic interference filtering and improving the accuracy of harmonic interference identification and filtering. Furthermore, by combining at least one of the correction coefficient and individual baseline intensity values ​​with the population baseline intensity value to determine the lead baseline value, the accuracy of harmonic interference identification and filtering can be further improved. Furthermore, if harmonic interference is determined to exist, the notch filter parameters are determined based on the initial spectral intensity of a single lead at a preset frequency point and the lead reference value. The notch filter is then used to filter the ECG signal with harmonic interference, avoiding the problems of incomplete harmonic interference removal or loss of useful high-frequency details caused by traditional filtering methods using fixed parameters or thresholds. This further effectively improves the accuracy of high-frequency harmonic interference identification and filtering.

[0101] In one or more embodiments of this application, the reference electrocardiogram (ECG) signal in the ECG signal set can be dynamically updated to adapt to changes in individual state, thereby improving the accuracy of interference identification and filtering.

[0102] This embodiment also provides a high-frequency electrocardiogram signal harmonic interference filtering device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0103] This embodiment provides a high-frequency electrocardiogram signal harmonic interference filtering device, such as... Figure 2 As shown, it includes: The acquisition module 201 is used to acquire object information of the target object and the initial electrocardiogram signal under the target lead; The spectrum intensity determination module 202 is used to determine the initial spectrum intensity of a preset frequency point based on the initial electrocardiogram signal; the preset frequency point is greater than or equal to 100Hz; the preset frequency point includes at least one of 150Hz, 200Hz, and 250Hz. The group determination module 203 is used to determine the target group of the target object based on the object information; the target group is determined from multiple groups, and the multiple groups are obtained by grouping different individuals according to preset conditions; The baseline value determination module 204 is used to determine the baseline value of the target object under the target lead and the corresponding preset frequency point based on the baseline intensity value of the target population of the target group. The judgment module 205 is used to determine whether there is harmonic interference in the initial electrocardiogram signal based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value. The filtering module 206 is used to filter out electrocardiogram signals with harmonic interference to obtain the target electrocardiogram signal.

[0104] In some optional implementations, the reference value determination module 204 is specifically used for: The process involves acquiring a preprocessed set of electrocardiogram (ECG) signals, which includes the baseline ECG signals of different individuals in each lead; determining the baseline spectral intensity of the corresponding lead at a preset frequency point based on the baseline ECG signals; grouping different individuals according to preset conditions to obtain multiple groups; and determining the population baseline intensity value corresponding to the preset frequency point for each group in each lead based on the baseline spectral intensity.

[0105] Specifically, it is used to: determine the mean and standard deviation of the population intensity of the target group at the target lead and corresponding to the preset frequency point based on the reference spectral intensity; determine the correction coefficient of the target group at the target lead and corresponding to the preset frequency point based on the standard deviation and mean of the population intensity of the target group at the target lead and corresponding to the preset frequency point; and use the product of the target population reference intensity value and the correction coefficient at the target lead and corresponding to the preset frequency point as the lead reference value.

[0106] It is also specifically used for: determining the signal-to-noise ratio of the initial electrocardiogram signal; determining the correction coefficient based on the signal-to-noise ratio; and using the product of the target population baseline intensity value and the correction coefficient corresponding to the preset frequency point under the target lead as the lead baseline value.

[0107] It is also specifically used for: determining the individual baseline intensity value of the target subject at a preset frequency point based on the baseline ECG signal of the target subject under the target lead; and determining the lead baseline value of the target subject under the target lead and the preset frequency point based on the individual baseline intensity value and the baseline intensity value of the target population of the target group.

[0108] In some optional implementations, the spectral intensity determination module is specifically used for: Perform Fourier transform on the ECG signal corresponding to each heartbeat cycle in the initial ECG signal to determine the initial spectral intensity of each heartbeat cycle at a preset frequency point; It is also specifically used for: performing a Fourier transform on an initial electrocardiogram (ECG) signal to determine the initial spectral intensity at a preset frequency point; or, performing a Fourier transform on an electronic heart signal to determine the initial spectral intensity at a preset frequency point; the electronic heart signal is derived from segmenting the initial ECG signal; In some optional implementations, the determination module 205 is specifically used for: The initial spectral intensity is compared with the lead reference value; if the first ratio of the initial spectral intensity to the lead reference value is greater than or equal to the first preset threshold, it is determined that the ECG signal of the corresponding heartbeat cycle is interfered with; the second ratio of the number of heartbeat cycles with interference to the total number of heartbeat cycles in the initial ECG signal is determined; if the second ratio is greater than or equal to the second preset threshold, it is determined that the initial ECG signal is affected by harmonic interference.

[0109] It is also specifically used to: compare the initial spectral intensity with the lead reference value; if the third ratio of the initial spectral intensity to the lead reference value is greater than or equal to the third preset threshold, it is determined that there is harmonic interference in the initial ECG signal.

[0110] In some alternative implementations, the filtering module 206 is specifically used for: If harmonic interference is detected, filter parameters are determined based on the initial spectral intensity and lead reference value corresponding to the preset frequency point to obtain the target filter; the ECG signal with harmonic interference is filtered based on the target filter.

[0111] The high-frequency electrocardiogram (ECG) signal harmonic interference filtering device provided in this embodiment of the invention can execute the high-frequency ECG signal harmonic interference filtering method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0112] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0113] The following is a detailed reference. Figure 3The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 301, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 302 or a program loaded from memory 308 into random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device. The processor 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0114] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0115] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 309, or installed from a memory 308, or installed from a ROM 302. When the computer program is executed by the processor 301, it performs the functions defined in the high-frequency electrocardiogram signal harmonic interference filtering method of the embodiments of the present invention.

[0116] Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0117] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the high-frequency electrocardiogram signal harmonic interference filtering method shown in the above embodiments is implemented.

[0118] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0119] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for filtering harmonic interference in high-frequency electrocardiogram signals, characterized in that, The method includes: Acquire object information of the target object and the initial electrocardiogram signal under the target lead; The initial spectral intensity of a preset frequency point is determined based on the initial electrocardiogram signal; the preset frequency point is greater than or equal to 100Hz. Based on the object information, the target group of the target object is determined; the target group is determined from multiple groups, and the multiple groups are obtained by grouping different individuals according to preset conditions; Based on the target population baseline intensity value of the target group, determine the lead baseline value of the target object under the target lead, corresponding to the preset frequency point; Based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value, determine whether the initial electrocardiogram signal has harmonic interference; The target ECG signal is obtained by filtering out ECG signals containing harmonic interference.

2. The method according to claim 1, characterized in that, The preset frequency point includes at least one of 150Hz, 200Hz and 250Hz.

3. The method according to claim 1, characterized in that, The steps for determining the baseline intensity values ​​of the multiple groups include: Acquire a preprocessed set of electrocardiogram (ECG) signals, which includes baseline ECG signals of different individuals in each lead; Based on the reference electrocardiogram signal, determine the reference spectral intensity of the corresponding lead at the preset frequency point; The different individuals are grouped according to preset conditions to obtain multiple groups; Based on the reference spectral intensity, determine the population reference intensity value corresponding to the preset frequency point for each group under each lead.

4. The method according to claim 3, characterized in that, The step of determining the lead reference value of the target object corresponding to the preset frequency point under the target lead based on the target population reference intensity value of the target group includes: Based on the reference spectral intensity, determine the mean and standard deviation of the population intensity of the target group at the preset frequency point under the target lead; Based on the standard deviation of the population intensity and the mean of the population intensity corresponding to the preset frequency point under the target lead, the correction coefficient of the target group corresponding to the preset frequency point under the target lead is determined; The product of the target population baseline intensity value corresponding to the preset frequency point and the correction coefficient under the target lead is used as the lead baseline value.

5. The method according to claim 3, characterized in that, The step of determining the lead reference value of the target object corresponding to the preset frequency point under the target lead based on the target population reference intensity value of the target group includes: Determine the signal-to-noise ratio of the initial electrocardiogram signal; Based on the signal-to-noise ratio, determine the correction coefficients; The product of the target population baseline intensity value corresponding to the preset frequency point and the correction coefficient under the target lead is used as the lead baseline value.

6. The method according to claim 3, characterized in that, The step of determining the lead reference value of the target object corresponding to the preset frequency point under the target lead based on the target population reference intensity value of the target group includes: Based on the reference electrocardiogram signal of the target object under the target lead, determine the individual reference intensity value of the target object at the preset frequency point; Based on the individual baseline intensity value and the target population baseline intensity value of the target group, the lead baseline value corresponding to the preset frequency point under the target lead is determined for the target object.

7. The method according to claim 1, characterized in that, The determination of the initial spectral intensity at a preset frequency point based on the initial electrocardiogram signal includes: Perform Fourier transform on the electrocardiogram signal corresponding to each heartbeat cycle in the initial electrocardiogram signal to determine the initial spectral intensity of each heartbeat cycle at the preset frequency point; The step of determining whether the initial electrocardiogram signal has harmonic interference based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value includes: The initial spectral intensity is compared with the lead reference value; If the first ratio of the initial spectral intensity to the lead reference value is greater than or equal to a first preset threshold, it is determined that there is interference in the electrocardiogram signal of the corresponding heartbeat cycle. Determine the second ratio of the number of heartbeat cycles with interference to the total number of heartbeat cycles in the initial electrocardiogram signal; If the second ratio is greater than or equal to the second preset threshold, it is determined that the initial electrocardiogram signal has harmonic interference.

8. The method according to claim 1, characterized in that, The determination of the initial spectral intensity at a preset frequency point based on the initial electrocardiogram signal includes: Perform a Fourier transform on the initial electrocardiogram signal to determine the initial spectral intensity at the preset frequency point; or, The initial spectral intensity at the preset frequency point is determined by performing a Fourier transform on the electrocardiogram (ECG) signal; the ECG signal is derived from segmenting the initial ECG signal. The step of determining whether the initial electrocardiogram signal has harmonic interference based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value includes: The initial spectral intensity is compared with the lead reference value; If the third ratio of the initial spectral intensity to the lead reference value is greater than or equal to the third preset threshold, it is determined that the initial electrocardiogram signal has harmonic interference.

9. The method according to any one of claims 1 to 8, characterized in that, The process of filtering out harmonic interference from the electrocardiogram (ECG) signal to obtain the target ECG signal includes: If harmonic interference is determined to exist, the filter parameters are determined based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value to obtain the target filter; The target filter is used to filter electrocardiogram signals that are subject to harmonic interference.

10. A high-frequency electrocardiogram signal harmonic interference filtering device, characterized in that, The device includes: The acquisition module is used to acquire object information of the target object and the initial electrocardiogram signal under the target lead; A spectrum intensity determination module is used to determine the initial spectrum intensity at a preset frequency point based on the initial electrocardiogram signal; the preset frequency point is greater than or equal to 100Hz. The group determination module is used to determine the target group of the target object based on the object information; the target group is determined from multiple groups, and the multiple groups are obtained by grouping different individuals according to preset conditions; The reference value determination module is used to determine, based on the target population reference intensity value of the target group, the lead reference value of the target object under the target lead, corresponding to the preset frequency point; The judgment module is used to determine whether there is harmonic interference in the initial electrocardiogram signal based on the initial spectral intensity corresponding to the preset frequency point and the lead reference value; The filtering module is used to filter out ECG signals with harmonic interference to obtain the target ECG signal.

11. An electronic device, characterized in that, include: The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the high-frequency electrocardiogram signal harmonic interference filtering method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the high-frequency electrocardiogram signal harmonic interference filtering method according to any one of claims 1 to 9.

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