An electromagnetic interference suppression method, device and system for an electro-superfield

Abstract

The present application relates to the technical field of ultrasonic signal filtering, and specifically relates to a method, device and system for suppressing electromagnetic interference in an electro-superfield. The method includes: determining the frequency-domain consistent eigenvalue of each modal component by analyzing the similarity in the frequency domain between all frame signals of each modal component, and combining the time-domain consistent eigenvalue to determine the periodic eigenvalue; respectively analyzing the differences in the frequency domain and time domain between each modal component in the ultrasonic signal in each probe and all modal components in its corresponding clustering cluster, constructing the time-frequency eigenvalue, and combining the periodic eigenvalue to determine the ultrasonic eigenvalue, so as to suppress the electromagnetic interference in the electro-superfield. The present application can accurately identify and eliminate the electromagnetic interference generated by electrical stimulation signals, thereby improving the stability and treatment effect of the electro-ultrasonic therapeutic instrument.

Description

Technical Field

[0001] This application relates to the technical field of ultrasonic signal filtering, and specifically relates to a method, device, and system for suppressing electromagnetic interference in an electro-superfield. Background Art

[0002] An electro-ultrasonic therapeutic instrument is an electronic medical device that combines the principles of electrotherapy and ultrasonic therapy to provide a comprehensive physical therapy solution for patients. This device utilizes the physical properties and biological effects of ultrasonic waves. Through a transducer, electrical energy is converted into mechanical energy, thereby generating high-frequency vibrations. These vibrations are transmitted to human tissues through a treatment probe, producing various biological effects at different depths, such as thermal effects, mechanical effects, and chemical effects. These effects can promote blood circulation, improve metabolism, relieve pain, reduce inflammation and swelling, and contribute to tissue repair and regeneration. The electro-ultrasonic therapeutic instrument outputs deep ultrasonic stimulation and high-frequency pulsed current through the same electrode, which is beneficial for the ultrasonic stimulation to linearly change the permeability or sensitivity of cells. Subsequently, more specific physiological effects are achieved through electrical stimulation, or the two act synergistically to stimulate new biological reactions and enhance the therapeutic effect.

[0003] However, the electromagnetic field generated by the electrical stimulation signal in the electro-ultrasonic therapeutic instrument will bring electromagnetic interference to the ultrasonic signal, thereby distorting the ultrasonic signal, and further affecting the stability and effectiveness of the electro-ultrasonic therapeutic instrument. In the prior art, a band-pass filter is used to filter the ultrasonic signal to remove noise in a specific frequency range, and can suppress electromagnetic interference in the electro-superfield. The passband frequency range in a traditional band-pass filter is usually a fixed value selected by experience. However, during the actual use of the electro-ultrasonic therapeutic instrument, the differences in users and treatment sites will cause differences in the electrical stimulation parameters used in the electro-ultrasonic therapeutic instrument. As a result, the frequency distribution in the electromagnetic interference noise generated by the electrical stimulation signal will also be different, making the fixed passband frequency range in the traditional band-pass filter unable to adapt to the changes in the electromagnetic interference generated by the electrical stimulation signal in the electro-ultrasonic therapeutic instrument. Therefore, it is difficult to effectively filter out the noise components generated by the electromagnetic interference of the electrical stimulation signal in the ultrasonic signal, reducing the stability and therapeutic effect of the electro-ultrasonic therapeutic instrument. Summary of the Invention

[0004] In a first aspect, an embodiment of the present application provides a method for suppressing electromagnetic interference in an electro-superfield. The method includes the following steps:

[0005] Obtain the ultrasonic signal in each probe during the operation of the electro-ultrasonic therapeutic instrument;

[0006] The modal decomposition algorithm is used to obtain all modal components of the ultrasonic signal in each probe, and each modal component is divided into multiple frame signals. By evaluating the correlation between all frame signals in each modal component, the time-domain consistency eigenvalue of each modal component is determined; by analyzing the similarity in the frequency domain between all frame signals of each modal component, the frequency-domain consistency eigenvalue of each modal component is determined, and in combination with the time-domain consistency eigenvalue, the periodicity eigenvalue of each modal component is determined.

[0007] Cluster all modal components of the ultrasonic signal in each probe to obtain multiple clusters, and respectively analyze the differences in the frequency domain and time domain between each modal component in the ultrasonic signal in each probe and all modal components in its corresponding cluster, construct the time-frequency eigenvalue of each modal component in the ultrasonic signal in each probe, and in combination with the periodicity eigenvalue, determine the ultrasonic eigenvalue of each modal component in the ultrasonic signal in each probe.

[0008] Based on the ultrasonic eigenvalue, screen out the ultrasonic modal components from all modal components of the ultrasonic signal in each probe to suppress the electromagnetic interference of the electrical superfield.

[0009] Preferably, the time-domain consistency eigenvalue of each modal component is the mean value of the correlation coefficients between all frame signals of each modal component.

[0010] Preferably, the method for determining the frequency-domain consistency eigenvalue of each modal component in the ultrasonic signal in each probe is as follows:

[0011] The time-frequency conversion algorithm is used to obtain the spectrogram of each frame signal, and the mean value of the similarities between the spectrograms of all frame signals of each modal component is taken as the frequency-domain consistency eigenvalue of each modal component.

[0012] Preferably, the periodicity eigenvalue of each modal component is the mean value of the time-domain consistency eigenvalue and the frequency-domain consistency eigenvalue of each modal component.

[0013] Preferably, the expression of the time-frequency eigenvalue of each modal component in the ultrasonic signal in each probe is: ; where represents the time-frequency eigenvalue of the j-th modal component in the ultrasonic signal in probe i; represents the mean value of the difference between the main frequency of the j-th modal component in the ultrasonic signal in probe i and the main frequencies of all modal components in its corresponding cluster in the frequency domain; represents the mean value of the difference between the j-th modal component in the ultrasonic signal in probe i and all modal components in its corresponding cluster; exp( ) represents the exponential function with the natural constant as the base.

[0014] Preferably, the ultrasonic eigenvalue of each modal component in the ultrasonic signal of each probe is the product of the periodic eigenvalue and the time-frequency eigenvalue of each modal component in the ultrasonic signal of each probe.

[0015] Preferably, the process of screening out the ultrasonic modal components from all modal components in the ultrasonic signal of each probe is as follows:

[0016] Take the ultrasonic eigenvalue of all modal components in the ultrasonic signal of each probe as the input of the threshold segmentation algorithm, output the segmentation threshold, and take all modal components with ultrasonic eigenvalue greater than the segmentation threshold as the ultrasonic modal components.

[0017] Preferably, the suppression of the electromagnetic interference of the electro-superfield includes:

[0018] Take the union of the frequency ranges of all ultrasonic modal components in the ultrasonic signal of each probe in the frequency domain as the passband frequency range of the band-pass filter in each probe, and filter out the electromagnetic interference of the electro-superfield in each probe.

[0019] In a second aspect, an embodiment of the present application further provides an electro-superfield electromagnetic interference suppression device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the electro-superfield electromagnetic interference suppression method described in any one of the above are implemented.

[0020] In a third aspect, an embodiment of the present application provides an electro-superfield electromagnetic interference suppression system, and the system includes:

[0021] An ultrasonic data acquisition module, configured to acquire ultrasonic signals in each probe during the operation of an electro-ultrasonic therapeutic instrument;

[0022] An ultrasonic weight analysis module, configured to use a modal decomposition algorithm to obtain all modal components of the ultrasonic signal in each probe, divide each modal component into multiple frame signals, and determine the time-domain consistency eigenvalue of each modal component by evaluating the correlation between all frame signals in each modal component; determine the frequency-domain consistency eigenvalue of each modal component by analyzing the similarity in the frequency domain between all frame signals of each modal component, and combine the time-domain consistency eigenvalue to determine the periodic eigenvalue of each modal component;

[0023] Cluster all modal components of the ultrasonic signal in each probe to obtain multiple clustering clusters, respectively analyze the differences in the frequency domain and time domain between each modal component in the ultrasonic signal of each probe and all modal components in its clustering cluster, construct the time-frequency eigenvalue of each modal component in the ultrasonic signal of each probe, and combine the periodic eigenvalue to determine the ultrasonic eigenvalue of each modal component in the ultrasonic signal of each probe;

[0024] An electromagnetic interference suppression module is configured to screen out ultrasonic modal components from all modal components in the ultrasonic signals within each probe based on the ultrasonic eigenvalue, and suppress the electromagnetic interference of the electro-ultrasonic field.

[0025] As can be seen from the above embodiments, an electro-ultrasonic field electromagnetic interference suppression method provided by the embodiments of the present application has at least the following beneficial effects:

[0026] By analyzing the similarity between the time-domain characteristics and the frequency-domain characteristics of each modal component in the ultrasonic signal at different time periods, the present application constructs a periodic eigenvalue, which helps to identify the useful components in the ultrasonic signal and the noise caused by electromagnetic interference, and helps to determine the periodic characteristics of the signal, so as to more accurately identify and eliminate the electromagnetic interference generated by electrical stimulation in the ultrasonic signal. Further, by analyzing the differences between different modal components in the time domain and in the frequency domain, a time-frequency eigenvalue is constructed, which helps to identify the electromagnetic interference generated by the electrical stimulation signal in the ultrasonic signal, so as to more accurately and effectively suppress the electromagnetic interference generated by the electrical stimulation signal in the ultrasonic signal, and further improve the stability and treatment effect of the electro-ultrasonic therapeutic instrument. Finally, by combining the periodic eigenvalue and the time-frequency eigenvalue, an ultrasonic eigenvalue is constructed, which can accurately identify and screen out the ultrasonic signal, and optimize the band-pass filter in the probe of the electro-ultrasonic therapeutic instrument based on the frequency range of the ultrasonic signal, so as to better suppress the electromagnetic interference generated by electrical stimulation in the ultrasonic signal. This embodiment can accurately identify and eliminate the electromagnetic interference generated by the electrical stimulation signal by analyzing the time-domain and frequency-domain characteristics of the ultrasonic signal, thereby improving the stability and treatment effect of the electro-ultrasonic therapeutic instrument. Description of the Drawings

[0027] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0028] Figure 1 It is a flowchart of the steps of an electro-ultrasonic field electromagnetic interference suppression method provided by an embodiment of the present application;

[0029] Figure 2 It is a schematic diagram of the ultrasonic eigenvalue extraction process provided by an embodiment of the present application;

[0030] Figure 3 It is a block diagram of an electro-ultrasonic field electromagnetic interference suppression system provided by an embodiment of the present application. Detailed Embodiments

[0031] To further elaborate on the technical means and effects adopted by this application to achieve the intended invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details a method, device, and system for suppressing electromagnetic interference in an electro-superfield, including its specific implementation manner, structure, features, and effects, as follows. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0033] The following specifically describes the specific solutions of a method, device, and system for suppressing electromagnetic interference in an electro-superfield provided by this application in combination with the accompanying drawings.

[0034] Please refer to Figure 1 , which shows a flowchart of the steps of a method for suppressing electromagnetic interference in an electro-superfield provided by an embodiment of this application. The method includes the following steps:

[0035] Step S1: Obtain the ultrasonic signals in each probe during the operation of the electro-ultrasonic therapeutic instrument.

[0036] An electro-ultrasonic therapeutic instrument is an electronic medical device that combines electrotherapy and ultrasonic therapy. Its principle is to output deep ultrasonic stimulation and high-frequency pulsed current through the same electrode. It first uses ultrasonic stimulation to change the permeability or sensitivity of cells, and then realizes more specific physiological effects through electrical stimulation, or the two act synergistically to stimulate new biological reactions, thereby enhancing the treatment effect.

[0037] However, the electro-ultrasonic therapeutic instrument faces the problem of the technical integration difficulty of combining the deep ultrasonic stimulation technology (DUS) and the high-frequency pulsed current technology (HFPC) on the same electrode. Therefore, in this embodiment, for the electromagnetic interference generated by the electrical stimulation signal in the ultrasonic signal, by analyzing the time-frequency characteristics of the ultrasonic signal, the electromagnetic interference generated by the electrical stimulation signal in the ultrasonic signal is suppressed.

[0038] In this embodiment, the electro-superfield electromagnetic interference suppression device includes an electro-ultrasonic therapeutic instrument, which includes an electro-ultrasonic treatment system software, and a probe shared by ultrasound and electrical stimulation. For the convenience of description, the probe shared by ultrasound and electrical stimulation is abbreviated as the probe and is used in the following content description.

[0039] The electro-ultrasonic treatment system software in the electro-ultrasonic therapeutic instrument will provide a treatment plan according to the case information uploaded by the user. When the user sets the instrument parameters according to the treatment plan and clicks to start the treatment, each probe in the electro-ultrasonic therapeutic instrument will generate ultrasonic signals in the ultrasonic generator respectively according to the parameters in the treatment plan.

[0040] Therefore, during the use of the electro-ultrasonic therapeutic apparatus by the user, ultrasonic signals in each probe during the working process of the electro-ultrasonic therapeutic apparatus are collected, and the ultrasonic signal acquisition frequency is set to 6 MHz.

[0041] Step S2: Use the modal decomposition algorithm to obtain all modal components of the ultrasonic signals in each probe, divide each modal component into multiple frame signals, and determine the time-domain consistency eigenvalue of each modal component by evaluating the correlation between all frame signals in each modal component; determine the frequency-domain consistency eigenvalue of each modal component by analyzing the differences in the frequency domain between all frame signals of each modal component, and combine the time-domain consistency eigenvalue to determine the periodicity eigenvalue of each modal component.

[0042] In order to maintain the stability of the treatment process, the electro-ultrasonic therapeutic apparatus cannot adjust parameters after the start of the treatment process. The ultrasonic signals of each probe in the electro-ultrasonic therapeutic apparatus are usually periodic signals generated at a fixed frequency, so that the useful signal components in the ultrasonic signals generated by the probe have a certain periodicity. The electromagnetic interference generated by the electrical stimulation signal has complex frequency components, so that the noise components containing electromagnetic interference in the ultrasonic signals generated by the probe usually do not have a certain periodicity. The periodicity of the signal usually manifests as the signal having consistent time-domain and frequency-domain distribution characteristics in different time periods.

[0043] Therefore, by analyzing the consistency characteristics of the ultrasonic signals in the time domain and frequency domain in different time periods, the periodicity characteristics are determined, so as to distinguish the useful components in the ultrasonic signals from the noise caused by electromagnetic interference, and to eliminate the influence of the electromagnetic interference generated by the electrical stimulation signal on the function effect of the ultrasonic signals during the working process of the ultrasonic signals. Specifically:

[0044] First, take the ultrasonic signals in each probe as the input of the variational mode decomposition algorithm. Among them, the penalty factor of the variational mode decomposition algorithm is set to 4000, the number of modes M is set to 10, and the convergence tolerance is set to to output M modal components of the ultrasonic signals in each probe.

[0045] Among them, the variational mode decomposition algorithm is a well-known technology, and its specific principle will not be elaborated here.

[0046] Secondly, frame and window each modal component of the ultrasonic signal of each probe to obtain all frame signals of each modal component of the ultrasonic signal of each probe. Among them, the values of the frame length and frame shift during the frame processing, as well as the setting of the window function, are all set artificially. In this embodiment, the value of the frame length during the frame processing is 25 ms, the value of the frame shift is 10 ms, and the Hamming window is selected as the window function. In the actual application process, as other implementation manners, regarding the setting of the values of the frame length and frame shift and the selection of the window function, the implementer can also set them according to the specific situation by himself, and this embodiment does not make special restrictions.

[0047] It should be understood that the process of frame and window the signal and the Hamming window are all well-known technologies, and the specific principle of the frame and window technology and the specific application process of the Hamming window will not be elaborated here.

[0048] Furthermore, the mean value of the correlation coefficients between all frame signals of each modal component is used as the time-domain consistency eigenvalue of each modal component to characterize the degree of consistency of the time-domain distribution characteristics of the modal component in different time periods. If the correlation coefficient of the time-domain distribution characteristics between different time periods of the modal component is larger, then the time-domain transfer eigenvalue of the modal component is larger, indicating that the periodicity of the modal component is more obvious, and the possibility that the modal component belongs to the ultrasonic signal is greater; on the contrary, if the correlation coefficient of the time-domain distribution characteristics between different time periods of the modal component is smaller, then the time-domain transfer eigenvalue of the modal component is smaller, indicating that the periodicity of the modal component is less obvious, and the possibility that the modal component belongs to the electromagnetic interference generated by the electrical stimulation signal is greater.

[0049] It should be noted that there are many methods for calculating the correlation coefficient between signals. In this embodiment, the absolute value of the Pearson correlation coefficient between all frame signals of each modal component is used as the correlation coefficient between all frame signals of each modal component. In the actual application process, as other implementation manners, the implementer can also use the Spearman correlation coefficient or the Kendall rank correlation coefficient. Regarding the selection of the calculation method of the correlation coefficient between signals, this embodiment does not make special restrictions.

[0050] Among them, the calculation method of the Pearson correlation coefficient is a well-known technology, and its specific calculation process will not be elaborated here.

[0051] Furthermore, the time-frequency conversion algorithm is used to obtain the spectrograms of each frame signal. The average of the similarities between the spectrograms of all frame signals of each modal component is used as the frequency-domain consistency eigenvalue of each modal component, which is used to characterize the degree of consistency of the frequency-domain distribution characteristics of the modal component in different time periods. If the correlation coefficient between the spectrograms of all frame signals of the modal component is larger, the frequency-domain consistency eigenvalue of the modal component is larger, indicating that the periodic distribution characteristics of the modal component are more obvious, and the possibility that the modal component belongs to the ultrasonic signal is greater; on the contrary, if the correlation coefficient between the spectrograms of all frame signals of the modal component is smaller, the frequency-domain consistency eigenvalue of the modal component is smaller, indicating that the periodic distribution characteristics of the modal component are less obvious, and the possibility that the modal component belongs to the ultrasonic signal is smaller.

[0052] It should be noted that there are many commonly used time-frequency conversion algorithms. In this embodiment, the fast Fourier transform is used to obtain the spectrograms of each frame signal. In the actual application process, as other implementation manners, the implementer can also use other time-frequency conversion algorithms such as wavelet transform. Regarding the selection of the time-frequency conversion algorithm, no special limitation is made in this embodiment.

[0053] In addition, it should be understood that there are also many methods for measuring the similarity between spectrograms. In this embodiment, the Bhattacharyya coefficient between the spectrograms of all frame signals is used as the similarity between the spectrograms of all frame signals. In the actual application process, the implementer can also use other methods such as cosine similarity. Regarding the selection of the method for measuring the similarity between spectrograms, no special limitation is made in this embodiment.

[0054] Among them, the process of using the fast Fourier transform to obtain the spectrogram of the signal and the calculation method of the Bhattacharyya coefficient are both well-known technologies. The specific process of using the fast Fourier transform to obtain the spectrogram of the frame signal and the calculation process of the Bhattacharyya coefficient in this embodiment will not be elaborated.

[0055] Furthermore, based on the time-domain consistency eigenvalue and the frequency-domain consistency eigenvalue, the periodicity eigenvalue of each modal component is determined. Specifically, the periodicity eigenvalue of each modal component is the average of the time-domain consistency eigenvalue and the frequency-domain consistency eigenvalue of each modal component.

[0056] From the periodicity eigenvalue of each modal component, it can be understood that if the time-domain consistency eigenvalue of the modal component is larger and the frequency-domain consistency eigenvalue is larger, the periodicity characteristic of the modal component is larger, indicating that the periodicity characteristic of the modal component is more obvious, and the possibility that the modal component belongs to the ultrasonic signal is greater; on the contrary, if the time-domain consistency eigenvalue of the modal component is smaller and the frequency-domain consistency eigenvalue is smaller, the periodicity characteristic of the modal component is smaller, indicating that the periodicity characteristic of the modal component is less obvious, and the possibility that the modal component belongs to the ultrasonic signal is smaller.

[0057] Step S3: Cluster all modal components of the ultrasonic signals in each probe to obtain multiple clusters. Analyze the differences in the frequency domain and time domain between each modal component in the ultrasonic signal of each probe and all modal components in its corresponding cluster, construct the time-frequency eigenvalue of each modal component in the ultrasonic signal of each probe, and combine the periodic eigenvalue to determine the ultrasonic eigenvalue of each modal component in the ultrasonic signal of each probe.

[0058] Since different probes in the electro-ultrasonic therapeutic instrument follow the same physical mechanism when generating ultrasonic signals, that is, using the piezoelectric effect to convert electrical signals into ultrasonic signals. This means that when the probes generate ultrasonic signals at close frequencies, the useful signal components in these generated ultrasonic signals will have similar main frequency components. Therefore, even though electromagnetic interference may introduce additional noise in the generated ultrasonic signals, because the frequency components of electromagnetic interference are complex and non-periodic, it will not change the basic periodic characteristics of the ultrasonic signals. Therefore, the useful signal components in the ultrasonic signals generated by these probes at close frequencies will have similar signal time-domain waveforms.

[0059] Based on the above analysis, by analyzing the differences in the time domain and frequency domain of different modal components in the ultrasonic signal, the ultrasonic eigenvalue is determined, the signal belonging to the ultrasonic part is screened out from the ultrasonic signal, and the electromagnetic interference generated by the electrical stimulation signal is suppressed. The specific process is as follows:

[0060] Extract the main frequency in the spectrogram of each modal component, and cluster all modal components of each ultrasonic signal. Among them, the absolute value of the difference between the main frequencies of each pair of modal components of each ultrasonic wave in the frequency domain is used as the measurement distance of the clustering algorithm to obtain multiple clusters, which are used to represent a set composed of a group of modal components with similar signal main frequencies.

[0061] It should be noted that there are many common clustering algorithms. In this embodiment, the DBSCAN clustering algorithm is used to cluster the modal components. In the actual application process, as other implementation manners, the implementer also uses other clustering methods such as the DPC density peak clustering algorithm for clustering. The selection of the clustering method is not specially limited in this embodiment.

[0062] Among them, the method for obtaining the main frequency and the DBSCAN clustering algorithm are both well-known technologies, and their specific principles will not be elaborated here.

[0063] Furthermore, by analyzing the differences in the frequency domain and time domain between each modal component in the ultrasonic signal of each probe and all modal components in its corresponding cluster, the time-frequency eigenvalue of each modal component in the ultrasonic signal of each probe is constructed. Specifically:

[0064] The time-frequency eigenvalue of the j-th modal component in the ultrasonic signal of probe i The expression is as follows: wherein, represents the time-frequency eigenvalue of the j-th modal component in the ultrasonic signal of probe i; represents the average value of the differences between the j-th modal component in the ultrasonic signal of probe i and the main frequencies of all modal components in its clustering cluster in the frequency domain; represents the average value of the differences between the j-th modal component in the ultrasonic signal of probe i and all modal components in its clustering cluster; exp( ) represents the exponential function with the natural constant as the base.

[0065] It should be understood that there are many methods to measure the differences between data. In this embodiment, the absolute value of the difference between the j-th modal component in the ultrasonic signal of probe i and the main frequencies of all modal components in its clustering cluster in the frequency domain is used as the difference between the main frequencies of all modal components in the clustering cluster where the j-th modal component in the ultrasonic signal of probe i is located. In the actual application process, the implementer can also adopt other methods to measure the differences between data, such as the square or ratio of the differences. Regarding the selection of the method to measure the differences between data, this embodiment does not make special restrictions.

[0066] It should be noted that there are many methods to measure the differences between signals. In this embodiment, the DTW distance between all modal components in the clustering cluster where the modal component is located is used as the difference between all modal components. In the actual application process, as other implementation manners, the implementer can also adopt other methods to measure the differences between signals, such as the Euclidean distance and the Manhattan distance. Regarding the selection of the method to measure the differences between signals, this embodiment does not make special restrictions.

[0067] Among them, the calculation method of the DTW distance is a well-known technology, and its specific calculation process will not be elaborated. Further, according to the time-frequency eigenvalues of each modal component in the ultrasonic signal of each probe, it can be understood that the smaller the difference between the current modal component and the main frequencies of all modal components in its clustering cluster in the frequency domain, and the smaller the difference between the current modal component and all modal components in its clustering cluster, that is, the greater the similarity degree between the current modal component and the modal components in its clustering cluster in the frequency domain, the greater the time-frequency eigenvalue of the current modal component, indicating that the signal waveforms between the current modal component and the modal components in its clustering cluster are more similar, and the greater the possibility that the current modal component belongs to the ultrasonic signal;

[0068] Conversely, the greater the difference in the main frequencies in the frequency domain between the current modal component and all modal components in its cluster, and the greater the difference between the current modal component and all modal components in its cluster, that is, the smaller the similarity degree in the frequency domain between the current modal component and the modal components in its cluster, the smaller the time-frequency eigenvalue of the current modal component, indicating that the difference in the signal waveforms between the current modal component and the modal components in its cluster is greater, and the greater the possibility that the current modal component belongs to the electromagnetic interference generated by the electrical stimulation signal.

[0069] Furthermore, the product of the periodicity eigenvalue and the time-frequency eigenvalue of each modal component in the ultrasonic signal within each probe is used as the ultrasonic eigenvalue of each modal component in the ultrasonic signal within each probe.

[0070] From the ultrasonic eigenvalues of each modal component in the ultrasonic signal within each probe, it can be understood that if the periodicity eigenvalue of the modal component is larger and the time-frequency eigenvalue is larger, then the ultrasonic eigenvalue of the modal component is larger, indicating that the current modal component is more likely to belong to the ultrasonic signal; conversely, if the periodicity eigenvalue of the modal component is smaller and the time-frequency eigenvalue is smaller, then the ultrasonic eigenvalue of the modal component is smaller, indicating that the current modal component is more likely to belong to the electromagnetic interference generated by the electrical stimulation signal.

[0071] Preferably, the schematic diagram of the ultrasonic eigenvalue extraction process provided in this embodiment is as Figure 2 shown.

[0072] Step S4: Based on the ultrasonic eigenvalues, filter out the ultrasonic modal components from all modal components in the ultrasonic signal within each probe to suppress the electromagnetic interference of the electro-ultrasonic field.

[0073] The ultrasonic eigenvalues of all modal components in the ultrasonic signal of each probe are used as the input of the threshold segmentation algorithm to output the segmentation threshold. All modal components with ultrasonic eigenvalues greater than the segmentation threshold are denoted as ultrasonic modal components, and the union of the frequency ranges of all ultrasonic modal components in the frequency domain in the ultrasonic signal within each probe is used as the passband frequency range of the band-pass filter in each probe. The ultrasonic signal generated by the ultrasonic generator in the probe is filtered using the band-pass filter.

[0074] It should be noted that there are many commonly used threshold segmentation algorithms. In this embodiment, the method of obtaining the segmentation threshold using the maximum inter-class variance algorithm is adopted. In other embodiments, the implementer can also adopt other threshold segmentation algorithms. Regarding the selection of the threshold segmentation algorithm, no special limitation is made in this embodiment.

[0075] Among them, the maximum inter-class variance algorithm is a well-known technology, and its specific principle will not be elaborated here.

[0076] So far, in this embodiment, by obtaining the signal frequency range of the useful signal component in the ultrasonic signal generated by each probe in the electro-ultrasonic therapeutic instrument, and using the signal frequency range as the passband frequency range in the band-pass filter of each probe respectively, compared with the existing method of filtering the ultrasonic signal using a fixed passband frequency range, it can adapt to the change of electromagnetic interference generated by the electrical stimulation signal in the electro-ultrasonic therapeutic instrument, and thus can more effectively filter out the noise components generated by the electromagnetic interference of the electrical stimulation signal in the ultrasonic signals generated by different probes in the electro-ultrasonic therapeutic instrument, improving the stability and therapeutic effect of the electro-ultrasonic therapeutic instrument in the subsequent treatment process.

[0077] Based on the same inventive concept as the above method, an embodiment of the present application also provides an electro-ultrasonic field electromagnetic interference suppression device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above electro-ultrasonic field electromagnetic interference suppression methods.

[0078] Based on the same inventive concept as the above method, an embodiment of the present application also provides an electro-ultrasonic field electromagnetic interference suppression system, including:

[0079] An ultrasonic data acquisition module, configured to acquire ultrasonic signals in each probe during the operation of the electro-ultrasonic therapeutic instrument;

[0080] An ultrasonic weight analysis module, configured to use a modal decomposition algorithm to obtain all modal components of the ultrasonic signal in each probe, divide each modal component into multiple frame signals, evaluate the correlation between all frame signals in each modal component to determine the time-domain consistency eigenvalue of each modal component; determine the frequency-domain consistency eigenvalue of each modal component by analyzing the similarity in the frequency domain between all frame signals of each modal component, and combine the time-domain consistency eigenvalue to determine the periodicity eigenvalue of each modal component;

[0081] Cluster all modal components of the ultrasonic signal in each probe to obtain multiple clustering clusters, respectively analyze the differences in the frequency domain and time domain between each modal component in the ultrasonic signal in each probe and all modal components in its clustering cluster, construct the time-frequency eigenvalue of each modal component in the ultrasonic signal in each probe, and combine the periodicity eigenvalue to determine the ultrasonic eigenvalue of each modal component in the ultrasonic signal in each probe;

[0082] An electromagnetic interference suppression module, configured to screen out ultrasonic modal components from all modal components in the ultrasonic signal in each probe based on the ultrasonic eigenvalue, and suppress the electro-ultrasonic field electromagnetic interference.

[0083] A block diagram of an electro-ultrasonic field electromagnetic interference suppression system provided by an embodiment of the present application, as shown in Figure 3as shown

[0084] It should be noted that: the above order of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of this specification have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0085] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments.

[0086] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principle of the present application shall be included in the protection scope of the present application.

Claims

1. An electromagnetic interference suppression method for an electro-superfield, characterized in that The method includes the following steps: Obtain the ultrasonic signals in each probe during the operation of the electro-ultrasonic therapeutic apparatus; Adopt a modal decomposition algorithm to obtain all modal components of the ultrasonic signals in each probe, divide each modal component into multiple frame signals, evaluate the correlation between all frame signals in each modal component, and denote the mean value of the correlation coefficients between all frame signals in each modal component as the time-domain consistency eigenvalue of each modal component; adopt a time-frequency conversion algorithm to obtain the spectrogram of each frame signal, take the mean value of the similarity between the spectrograms of all frame signals in each modal component as the frequency-domain consistency eigenvalue of each modal component, and combine the time-domain consistency eigenvalue to determine the periodicity eigenvalue of each modal component; Cluster all modal components of the ultrasonic signals in each probe to obtain multiple clustering clusters, respectively analyze the differences in the frequency domain and time domain between each modal component in the ultrasonic signals in each probe and all modal components in its corresponding clustering cluster, construct the time-frequency eigenvalue of each modal component in the ultrasonic signals in each probe, and combine the periodicity eigenvalue to determine the ultrasonic eigenvalue of each modal component in the ultrasonic signals in each probe; Based on the ultrasonic eigenvalue, screen out the ultrasonic modal components from all modal components in the ultrasonic signals in each probe to suppress the electromagnetic interference of the electro-ultrasonic field.

2. The electromagnetic interference suppression method of an electro-superfield according to claim 1, characterized in that The periodicity eigenvalue of each modal component is the mean value of the time-domain consistency eigenvalue and the frequency-domain consistency eigenvalue of each modal component.

3. A method for suppressing electromagnetic interference of an electro-superfield, as described in claim 1, characterized in that, The expression for the time-frequency eigenvalue of each modal component in the ultrasonic signal within each probe is as follows: ; where represents the time-frequency eigenvalue of the j-th modal component in the ultrasonic signal within probe i; represents the mean of the differences between the main frequency of the j-th modal component in the ultrasonic signal within probe i and the main frequencies of all modal components in its corresponding clustering cluster in the frequency domain; represents the mean of the differences between the j-th modal component in the ultrasonic signal within probe i and all modal components in its corresponding clustering cluster; exp( ) represents the exponential function with the natural constant as the base.

4. The electromagnetic interference suppression method for an electro-superfield according to claim 1, characterized in that, The ultrasonic eigenvalue of each modal component in the ultrasonic signals in each probe is the product of the periodicity eigenvalue and the time-frequency eigenvalue of each modal component in the ultrasonic signals in each probe.

5. The electromagnetic interference suppression method of an electric superfield according to claim 1, characterized in that The process of screening out the ultrasonic modal components from all modal components in the ultrasonic signals in each probe is as follows: Take the ultrasonic eigenvalues of all modal components in the ultrasonic signals in each probe as the input of the threshold segmentation algorithm, output the segmentation threshold, and take all modal components with ultrasonic eigenvalues greater than the segmentation threshold as the ultrasonic modal components.

6. The electro-superfield electromagnetic interference suppression method according to claim 1, characterized in that, The suppression of the electromagnetic interference of the electro-ultrasonic field includes: Take the union of the frequency ranges of all ultrasonic modal components in the ultrasonic signals in each probe in the frequency domain as the passband frequency range of the band-pass filter in each probe to filter out the electromagnetic interference of the electro-ultrasonic field in each probe.

7. An electromagnetic interference suppression device for an electro-superfield, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it realizes the steps of an electro-ultrasonic field electromagnetic interference suppression method as described in any one of claims 1-6.

8. An electro-superfield electromagnetic interference suppression system that implements an electro-superfield electromagnetic interference suppression method as described in claim 1, characterized in that, The system includes: An ultrasonic data acquisition module for obtaining the ultrasonic signals in each probe during the operation of the electro-ultrasonic therapeutic apparatus; An ultrasonic weight analysis module for adopting a modal decomposition algorithm to obtain all modal components of the ultrasonic signals in each probe, dividing each modal component into multiple frame signals, evaluating the correlation between all frame signals in each modal component to determine the time-domain consistency eigenvalue of each modal component; determining the frequency-domain consistency eigenvalue of each modal component by analyzing the similarity in the frequency domain between all frame signals in each modal component, and combining the time-domain consistency eigenvalue to determine the periodicity eigenvalue of each modal component; Cluster all modal components of the ultrasonic signal in each probe to obtain multiple clusters, respectively analyze the differences in the frequency domain and time domain between each modal component in the ultrasonic signal of each probe and all modal components in its corresponding cluster, construct the time-frequency eigenvalues of each modal component in the ultrasonic signal of each probe, and combine the periodic eigenvalues to determine the ultrasonic eigenvalues of each modal component in the ultrasonic signal of each probe; The electromagnetic interference suppression module is used to screen out the ultrasonic modal components from all modal components in the ultrasonic signal of each probe based on the ultrasonic eigenvalues to suppress the electromagnetic interference of the electro-ultrasonic field.

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