Gradient magnetic field suppression method, system, storage medium and device for electrocardiosignal

Abstract

The embodiment of the present application discloses a gradient magnetic field suppression method of electrocardiosignal, and the method comprises the following steps: obtaining the electrocardiosignal of the current electrocardiosignal window and a threshold θ; performing difference on the electrocardiosignal of the current electrocardiosignal window to obtain a difference value ΔE; determining corresponding mutation point information according to the difference value ΔE; obtaining the local slope s of the electrocardiosignal of the current electrocardiosignal window according to the mutation point information; and outputting the electrocardiosignal after gradient magnetic field suppression according to the comparison relationship between the local slope s of the electrocardiosignal and the threshold θ. The signal mutation point information is obtained by performing difference on the electrocardiosignal, it is judged whether the mutation point should be reserved, and then the electrocardiosignal is continuously screened to obtain the electrocardiosignal after gradient magnetic field suppression.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electrocardiosignal processing, and particularly relates to a gradient magnetic field suppression method and system for electrocardiosignal, a storage medium and equipment. BACKGROUND

[0002] As an important means of monitoring the heart activity of patients, electrocardiogram plays a crucial role in the field of cardiovascular magnetic resonance (CMR) imaging. It is not only used for real-time monitoring of the physiological state of patients, but also used for realizing the gating control in the scanning process, so as to ensure the accuracy and effectiveness of imaging. However, the special conditions in the magnetic resonance imaging (MRI) environment bring unprecedented challenges to the acquisition and analysis of electrocardiosignal.

[0003] During the MRI scanning process, the electrocardiosignal is disturbed by multiple factors, mainly including the static magnetic field, the radio frequency pulse and the gradient magnetic field. These interference sources will cause serious distortion of the electrocardiosignal, and the artifact caused by the gradient magnetic field will produce high-frequency peaks in the electrocardiosignal, which greatly affects the detection accuracy of the QRS wave.

[0004] The traditional filtering method can reduce the high-frequency noise to a certain extent, but it has a large amount of calculation, a long processing time and is easy to introduce phase delay, which leads to the inability to meet the real-time gating requirements. SUMMARY

[0005] Therefore, it is necessary to propose a gradient magnetic field suppression method for electrocardiosignal in view of the above problems.

[0006] A gradient magnetic field suppression method for electrocardiosignal, the method comprising the following steps:

[0007] obtaining the electrocardiosignal of the current electrocardiosignal window and a threshold value θ;

[0008] differencing the electrocardiosignal of the current electrocardiosignal window to obtain a difference value ΔE;

[0009] determining the corresponding mutation point information according to the difference value ΔE;

[0010] obtaining the local slope s of the electrocardiosignal of the current electrocardiosignal window according to the mutation point information;

[0011] outputting the electrocardiosignal after gradient magnetic field suppression according to the comparison relationship between the local slope s of the electrocardiosignal and the threshold value θ.

[0012] In the above scheme, after obtaining the electrocardiosignal of the current electrocardiosignal window, the following steps are further included:

[0013] filtering and normalizing the electrocardiosignal of the current electrocardiosignal window.

[0014] In the above scheme, the corresponding mutation point information is determined according to the difference value ΔE, specifically comprising:

[0015] The point-by-point difference of the electrocardio signal is obtained to obtain the difference value ΔE of adjacent two points:

[0016] ΔE(t i )=E(t i+1 )-E(t i )

[0017] Wherein, t i and t i+1 represent the time of adjacent two sampling points respectively;

[0018] If the difference value ΔE of the adjacent two points is 0 value, record t i+1 This moment as t1, as the mutation starting point of the electrocardio signal E(t);

[0019] If the difference value ΔE of the adjacent two points is non-0 value, record t i+1 This moment as t2, as the mutation judgment point of the electrocardio signal E(t);

[0020] The time t1, t2 of the mutation point and the corresponding electrocardio signal amplitude y1, y2 are obtained, which are taken as the mutation point information and the local slope s is calculated:

[0021] S=(y2-y1) / (t2-t1)

[0022] Wherein, t1, t2 are the time of recording the mutation point respectively, and y1, y2 are the corresponding electrocardio signal amplitude respectively.

[0023] In the above scheme, the electrocardio signal after gradient magnetic field suppression is output according to the comparison relationship between the local slope s of the electrocardio signal and the threshold value θ, specifically comprising:

[0024] When the local slope s of the electrocardio signal ≤ threshold value θ, the amplitude of the electrocardio signal in the current electrocardio signal window is output;

[0025] When the local slope s of the electrocardio signal > threshold value θ, the mean value M of the electrocardio signal in the current electrocardio signal window is output.

[0026] In the above scheme, when the local slope s of the electrocardio signal > threshold value θ, the mean value M of the electrocardio signal in the current electrocardio signal window is output, specifically comprising:

[0027] The window length N of the electrocardio signal E(t) is set;

[0028] The electrocardio signal in the window length N is summed to obtain the signal amplitude sum S:

[0029]

[0030] wherein t i denotes the time of the i-th sample point within the window;

[0031] determine a mean value M of the current electrocardio signal window according to the window length N and the signal amplitude sum S.

[0032] In the above scheme, after obtaining the electrocardio signal of the current electrocardio signal window and the threshold θ, the method further comprises:

[0033] decomposing the electrocardio signal of the current electrocardio signal window to extract sub-signals of different frequencies;

[0034] setting a high-frequency threshold;

[0035] removing part of the signals according to the comparison relationship between the high-frequency threshold and the sub-signals of different frequencies to obtain the denoised sub-signals;

[0036] reconstructing the denoised sub-signals to determine the current electrocardio signal.

[0037] In the above scheme, after obtaining the electrocardio signal of the current electrocardio signal window and the threshold θ, the method further comprises:

[0038] filtering and normalizing the electrocardio signal of the current electrocardio signal window;

[0039] real-time detecting gradient magnetic field interference in the electrocardio signal to obtain an interference detection result;

[0040] adjusting the filtering parameter according to the interference detection result, and outputting the filtered electrocardio signal.

[0041] The application also proposes a gradient magnetic field suppression system for electrocardio signals, which comprises an original signal acquisition unit, a signal processing unit and a signal output unit.

[0042] The original signal acquisition unit is configured to obtain the electrocardio signal of the current electrocardio signal window and a threshold θ.

[0043] The signal processing unit is configured to perform difference on the electrocardio signal of the current electrocardio signal window to obtain a difference value ΔE, determine corresponding abrupt point information according to the difference value ΔE, and obtain a local slope s of the electrocardio signal of the current electrocardio signal window according to the abrupt point information.

[0044] The calculation unit is configured to output the electrocardio signal after gradient magnetic field suppression according to the comparison relationship between the local slope s of the electrocardio signal and the threshold θ.

[0045] The application further provides a readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0046] obtaining an electrocardio signal of a current electrocardio signal window and a threshold value θ;

[0047] differencing the electrocardio signal of the current electrocardio signal window to obtain a difference value ΔE;

[0048] determining corresponding mutation point information according to the difference value ΔE;

[0049] obtaining a local slope s of the electrocardio signal of the current electrocardio signal window according to the mutation point information;

[0050] outputting the electrocardio signal after gradient magnetic field suppression according to a comparison relationship between the local slope s of the electrocardio signal and the threshold value θ.

[0051] The application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the computer program causes the processor to perform the following steps:

[0052] obtaining an electrocardio signal of a current electrocardio signal window and a threshold value θ;

[0053] differencing the electrocardio signal of the current electrocardio signal window to obtain a difference value ΔE;

[0054] determining corresponding mutation point information according to the difference value ΔE;

[0055] obtaining a local slope s of the electrocardio signal of the current electrocardio signal window according to the mutation point information;

[0056] outputting the electrocardio signal after gradient magnetic field suppression according to a comparison relationship between the local slope s of the electrocardio signal and the threshold value θ.

[0057] The application has the following beneficial effects: the electrocardio signal of the current electrocardio signal window and the threshold value θ are obtained first; the electrocardio signal of the current electrocardio signal window is differentiated to obtain a difference value ΔE; corresponding mutation point information is determined according to the difference value ΔE; a local slope s of the electrocardio signal of the current electrocardio signal window is obtained according to the mutation point information; and the electrocardio signal after gradient magnetic field suppression is output according to a comparison relationship between the local slope s of the electrocardio signal and the threshold value θ. The gradient magnetic field noise can be effectively suppressed, and the signal-to-noise ratio of the electrocardio signal can be improved through the differential operation, mutation point identification and local slope calculation. BRIEF DESCRIPTION OF DRAWINGS

[0058] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description only represent some of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0059] Wherein:

[0060] Figure 1 It is a flow chart of the gradient magnetic field suppression method for a center electrical signal of an embodiment. DETAILED DESCRIPTION

[0061] The technical solutions in the embodiments of the present application will be described clearly and completely in the following description of the drawings in the embodiments of the present application. Obviously, the described embodiments only represent some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0062] In the following description, a large number of specific details are given in order to provide a more thorough understanding of the present application; however, it is obvious to those skilled in the art that the present application can be implemented without one or more of these details; in other examples, in order to avoid obscuring the present application, some technical features known in the art are not described, it should be understood that the present application can be implemented in different forms, and should not be interpreted as being limited to the embodiments presented here; on the contrary, the presentation of these embodiments will make the disclosure complete and complete, and will fully convey the scope of the present application to those skilled in the art.

[0063] The terms used herein are only for the purpose of describing specific embodiments and not as a limitation of the present application. As used herein, the singular forms "a", "an" and "the" are intended to include plural forms as well, unless the context clearly indicates otherwise, it should also be understood that the terms "comprise" and / or "include", when used in the specification, determine the presence of the stated features, integers, steps, operations, elements and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components and / or groups. As used herein, the term "and / or" includes any and all combinations of the associated listed items.

[0064] In order to thoroughly understand the present application, detailed structures will be presented in the following description in order to explain the technical solutions presented by the present application; the alternative embodiments of the present application are described in detail as follows, however, in addition to these detailed descriptions, the present application can also have other implementation manners.

[0065] AsFigure 1 As shown, in one embodiment, a gradient magnetic field suppression method of an electrocardiosignal is provided, which comprises steps S101 to S105, which are described in detail as follows:

[0066] S101, acquiring an electrocardiosignal of a current electrocardiosignal window and a threshold value θ;

[0067] The acquisition of the electrocardiosignal of the current electrocardiosignal window is a segmented processing of the electrocardiosignal, which helps to reduce the calculation amount and improve the efficiency. The selection of the electrocardiosignal window is based on time or sample quantity, which is used to limit the range of analysis. The setting of the threshold value θ is crucial for identifying the mutation point and judging whether the local slope needs to be suppressed in the subsequent steps, and its value will affect the effect of gradient magnetic field suppression.

[0068] S102, differentiating the electrocardiosignal of the current electrocardiosignal window to obtain a difference value ΔE;

[0069] The differentiation operation can reveal the rate of change of the electrocardiosignal over time, highlighting the high-frequency components in the electrocardiosignal, such as mutation points and noise. The difference value ΔE reflects the signal difference between adjacent sample points, which helps to identify the mutation part of the signal, which may be caused by external factors such as gradient magnetic field interference.

[0070] Preferably, after acquiring the electrocardiosignal of the current electrocardiosignal window, it further comprises:

[0071] Filtering and normalizing the electrocardiosignal of the current electrocardiosignal window.

[0072] S103, determining corresponding mutation point information according to the difference value ΔE;

[0073] By analyzing the difference value ΔE, the mutation points in the electrocardiosignal can be identified, such as the starting point and the end point of the QRS wave. These mutation points correspond to abnormal changes in the signal, which may be caused by interference sources.

[0074] In some embodiments, the determination of the corresponding mutation point information according to the difference value ΔE specifically comprises:

[0075] Point-by-point differentiation of the electrocardiosignal to obtain the difference value ΔE of adjacent two points:

[0076] ΔE(t i )=E(t i+1 )-E(t i )

[0077] Where t i and t i+1 represent the time of the adjacent two sampling points, respectively.

[0078] If the difference ΔE of the two adjacent points is a non-zero value, it is determined that the electrocardiosignal E(t) is a mutation point;

[0079] The time t1, t2 of the mutation point and the corresponding electrocardiosignal amplitude y1, y2 are obtained and used as mutation point information.

[0080] Specifically, if the difference ΔE of the two adjacent points is a 0 value, t i+1 The time is t1, which is the mutation starting point of the electrocardiosignal E(t);

[0081] If the difference ΔE of the two adjacent points is a non-zero value, t i+1 The time is t2, which is the mutation judgment point of the electrocardiosignal E(t);

[0082] The time t1, t2 of the mutation point and the corresponding electrocardiosignal amplitude y1, y2 are obtained and used as mutation point information.

[0083] Taking an actual electrocardiosignal as an example, assuming that the sampling rate is 1000Hz, at each sampling point, the electrocardiosignal difference ΔE of the two adjacent points is calculated, if ΔE is 0, it is considered that the point has no mutation; if ΔE is not 0, it is considered that the point has mutation, which may be a high-frequency peak value caused by gradient magnetic field.

[0084] S104, according to the mutation point information, obtaining the local slope s of the electrocardiosignal in the current electrocardiosignal window;

[0085] The local slope s reflects the change rate of the signal near the mutation point, which helps to more accurately quantify the influence degree of gradient magnetic field and other interference on the electrocardiosignal. By calculating the local slope, the mutation point can be more accurately identified, and the gradient magnetic field noise and the real change of the electrocardiosignal can be distinguished.

[0086] S105, according to the comparison relationship between the local slope s of the electrocardiosignal and the threshold value θ, outputting the electrocardiosignal after gradient magnetic field suppression.

[0087] Wherein, according to the time t1, t2 of the mutation point and the corresponding electrocardiosignal amplitude y1, y2, the local slope s is calculated: s=(y2-y1) / (t2-t1).

[0088] Specifically, taking an actual electrocardiosignal as an example, assuming that the information of two mutation points is recorded: t1=100ms, y1=0.5mV and t2=200ms, y2=1.5mV, according to these information, the local slope s of the electrocardiosignal can be calculated: (200-100) / (1.5-0.5)=0.01mV / ms, then judge whether the local slope s is greater than the threshold value, and output the electrocardiosignal.

[0089] By comparing the local slope s and the threshold value θ, it can be judged whether the change of the electrocardiosignal is caused by the gradient magnetic field noise or the real electrocardiac activity, and according to the judgment result, the gradient magnetic field noise can be suppressed and the real information of the electrocardiosignal can be retained.

[0090] If the local slope s exceeds the threshold value θ, it is considered that the part of the signal is significantly disturbed by the gradient magnetic field and needs to be suppressed or corrected, and the output signal is the electrocardiosignal after processing and reducing the gradient magnetic field interference, which improves the accuracy and reliability of the signal.

[0091] The threshold value θ is adjusted according to the actual application scene and the characteristics of the electrocardiosignal.

[0092] In some embodiments, according to the comparison relationship between the local slope s of the electrocardiosignal and the threshold value θ, the electrocardiosignal after gradient magnetic field suppression is output, specifically including:

[0093] When the local slope s of the electrocardiosignal is less than or equal to the threshold value θ, the amplitude of the electrocardiosignal in the current electrocardiosignal window is output;

[0094] When the local slope s of the electrocardiosignal is greater than the threshold value θ, the mean value M of the electrocardiosignal in the current electrocardiosignal window is output.

[0095] Taking an actual electrocardiosignal as an example, assuming that we set the threshold value θ = 0.02 mV / ms, and according to the calculated local slope s = 0.01 mV / ms, since s < θ, the original amplitude of the electrocardiosignal at the current time is output, and for abnormal changes caused by the gradient magnetic field, the interference is removed by outputting the mean value M; and for normal changes in the electrocardiosignal, the original amplitude is kept unchanged.

[0096] In some embodiments, when the local slope s of the electrocardiosignal is greater than the threshold value θ, the mean value M of the electrocardiosignal in the current electrocardiosignal window is output, specifically including:

[0097] The window length N of the electrocardiosignal E(t) is set;

[0098] The electrocardiosignal in the window length N is summed to obtain the signal amplitude sum S:

[0099]

[0100] Where, t i represents the time of the i-th sampling point in the window;

[0101] The mean value M of the electrocardiosignal in the current electrocardiosignal window is determined according to the window length N and the signal amplitude sum S.

[0102] In order to remove the gradient magnetic field interference in the electrocardiosignal, the electrocardiosignal in the current window length needs to be averaged, and the purpose of this step is to obtain the overall level of the electrocardiosignal in the current window, and to provide a reference for subsequent difference and slope calculation.

[0103] Taking an actual electrocardiosignal as an example, assuming that the window length N = 256 and the sampling rate is 1000 Hz. In each window, the electrocardiosignal of 256 sampling points is summed and then divided by 256 to obtain the mean M of the electrocardiosignal in the window, which will be used as a reference value in the subsequent steps.

[0104] In some embodiments, after obtaining the electrocardiosignal of the current electrocardiosignal window and the threshold θ, the method further comprises:

[0105] Downsampling the electrocardiosignal of the current electrocardiosignal window to reduce the amount of data to be processed in the time window;

[0106] After passing through the low-pass filter, remove the remaining high-frequency noise;

[0107] After passing through the high-pass filter, remove the low-frequency interference caused by respiratory movements and the like;

[0108] Obtaining the denoised signal to determine the current electrocardiosignal.

[0109] In some embodiments, after obtaining the electrocardiosignal of the current electrocardiosignal window and the threshold θ, the method further comprises:

[0110] Filtering and normalizing the electrocardiosignal of the current electrocardiosignal window;

[0111] Calculating the mean square error of the filter output signal and the expected output signal;

[0112] Adjusting the adaptive filter parameters using the least squares method and outputting the filtered electrocardiosignal.

[0113] Adjusting the filter parameters according to the interference detection result and outputting the filtered electrocardiosignal.

[0114] In summary, the present application proposes a gradient magnetic field suppression method for electrocardiosignal, which realizes real-time removal of gradient magnetic field interference in the electrocardiosignal through the steps of averaging, point-by-point difference, judging the mutation point, calculating the local slope and threshold judgment.

[0115] Take an actual ECG signal as an example, assuming the window length N = 256, the sampling rate is 1000 Hz, and the threshold value θ = 0.02 mV / ms. In each window, first sum the ECG signal of 256 sampling points, then divide by 256 to get the mean M of the ECG signal in the window. The ECG signal is differentiated point by point, and the difference ΔE between adjacent points is calculated. If ΔE is 0, record the time t1 and the ECG signal amplitude y1 of the point; if ΔE is not 0, record the time t2 and the ECG signal amplitude y2 of the point.

[0116] According to the above information, the local slope s of the ECG signal is calculated, and if s is greater than the threshold value θ, the mean M of the ECG signal is output to remove interference; if s is less than or equal to the threshold value θ, the original amplitude of the ECG signal at the current time is output. By this method, the gradient magnetic field interference in the ECG signal can be removed in real time, and the accuracy and real-time performance of ECG monitoring in MRI imaging can be improved.

[0117] The application also provides an ECG signal gradient magnetic field suppression system, which comprises an original signal acquisition unit, a signal processing unit and a signal output unit.

[0118] The original signal acquisition unit is configured to acquire the ECG signal of the current ECG signal window and the threshold value θ.

[0119] The signal processing unit is configured to differentiate the ECG signal of the current ECG signal window to obtain the difference ΔE, determine the corresponding mutation point information according to the difference ΔE, and acquire the local slope s of the ECG signal of the current ECG signal window according to the mutation point information.

[0120] The calculation unit is configured to output the ECG signal after gradient magnetic field suppression according to the comparison relationship between the local slope s of the ECG signal and the threshold value θ.

[0121] The application also provides a readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps:

[0122] Acquire the ECG signal of the current ECG signal window and the threshold value θ.

[0123] Differentiate the ECG signal of the current ECG signal window to obtain the difference ΔE.

[0124] Determine the corresponding mutation point information according to the difference ΔE.

[0125] Acquire the local slope s of the ECG signal of the current ECG signal window according to the mutation point information.

[0126] Output the ECG signal after gradient magnetic field suppression according to the comparison relationship between the local slope s of the ECG signal and the threshold value θ.

[0127] The application further provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to perform the following steps:

[0128] obtain the current ECG signal and the threshold θ;

[0129] differ the current ECG signal to obtain a difference value ΔE;

[0130] determine the corresponding mutation point information according to the difference value ΔE;

[0131] obtain the local slope s of the current ECG signal according to the mutation point information;

[0132] output the ECG signal after gradient magnetic field suppression according to the comparison relationship between the local slope s of the ECG signal and the threshold θ.

[0133] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by a computer program instructing related hardware, and the program can be stored in a non-volatile computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. Any reference to memory, storage, database or other medium used in the embodiments provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM).

[0134] Any combination of the technical features of the above embodiments can be made. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist, it should be considered as the scope of the present application.

[0135] The above-described embodiments are merely illustrative for the present application and are described in more detail and specifically, but should not be understood as a limitation to the scope of the present application. It should be noted that for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. The above disclosure is only the preferred embodiment of the present application, and of course cannot limit the scope of the present application. Therefore, the equivalent changes made according to the claims of the present application still belong to the scope of the present application.

Claims

1. A method of gradient magnetic field suppression of an electrocardiogram signal, characterized by, The method comprises: obtaining a current electrocardio signal window and a threshold value θ; point-by-point difference is performed on the current electrocardio signal window to obtain a difference value ΔE: wherein and respectively represent the time of two adjacent sampling points; corresponding mutation point information is determined according to the difference value ΔE, specifically comprising: If the difference ΔE of the two adjacent sampling points is 0, record The time t1 is the starting point of the mutation of the electrocardio signal E(t). If the difference ΔE of the two adjacent sampling points is a non-zero value, record The time t2 is the mutation judgment point of the electrocardio signal E(t). obtaining the time t1, t2 of the mutation point and the corresponding electrocardio signal amplitude y1, y2, and taking them as the mutation point information; obtaining the local slope s of the current electrocardio signal window according to the mutation point information: wherein t1, t2 are the time of recording the mutation point respectively, and y1, y2 are the corresponding electrocardio signal amplitude respectively; comparing the local slope s of the electrocardio signal with the threshold value θ, and outputting the electrocardio signal after gradient magnetic field suppression.

2. The gradient magnetic field suppression method of electrocardiosignal according to claim 1, characterized in that, After obtaining the current electrocardio signal window, the method further comprises: filtering and normalizing the current electrocardio signal window.

3. The gradient magnetic field suppression method of electrocardiosignal according to claim 1, characterized in that, comparing the local slope s of the electrocardio signal with the threshold value θ, and outputting the electrocardio signal after gradient magnetic field suppression, specifically comprising: when the local slope s of the electrocardio signal is less than or equal to the threshold value θ, outputting the amplitude of the current electrocardio signal window; when the local slope s of the electrocardio signal is greater than the threshold value θ, outputting the mean value M of the current electrocardio signal window.

4. The gradient magnetic field suppression method of electrocardiosignal according to claim 3, characterized in that, when the local slope s of the electrocardio signal is greater than the threshold value θ, outputting the mean value M of the current electrocardio signal window, specifically comprising: setting the window length N of the electrocardio signal E(t); summing the electrocardio signal in the window length N to obtain the signal amplitude sum S: wherein, denotes the time of the i-th sample point within the window; determining the mean value M of the current electrocardio signal window according to the window length N and the signal amplitude sum S.

5. The method of gradient magnetic field suppression of electrocardiographic signals of claim 1, wherein, After obtaining the current electrocardio signal window and the threshold value θ, the method further comprises: decomposing the current electrocardio signal window to extract sub-signals of different frequencies; setting a high-frequency threshold value; comparing the high-frequency threshold value with the sub-signals of different frequencies to remove part of the signals and obtain the denoised sub-signals; reconstructing the denoised sub-signals to determine the current electrocardio signal.

6. The method of gradient magnetic field suppression of electrocardiographic signals of claim 1, wherein, After obtaining the current electrocardio signal window and the threshold value θ, the method further comprises: filtering and normalizing the current electrocardio signal window; real-time detecting the gradient magnetic field interference in the electrocardio signal to obtain an interference detection result; adjusting the filtering parameter according to the interference detection result, and outputting the filtered electrocardio signal.

7. A gradient magnetic field suppression system for electrocardiographic signals, characterized by The system is used to implement the method of claim 1, and the system comprises an original signal acquisition unit, a signal processing unit and a signal output unit. The original signal acquisition unit is used to obtain a current electrocardio signal window and a threshold value θ. The signal processing unit is used to perform difference on the current electrocardio signal window to obtain a difference value ΔE; determine corresponding mutation point information according to the difference value ΔE; and obtain the local slope s of the current electrocardio signal window according to the mutation point information. The signal output unit is used to compare the local slope s of the electrocardio signal with the threshold value θ, and output the electrocardio signal after gradient magnetic field suppression. 8.A readable storage medium, storing a computer program, wherein the computer program is executed by a processor to make the processor perform the steps of the method in any one of claims 1 to 6. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to make the processor perform the steps of the method in any one of claims 1 to 6.

Images