Electric superfield electromagnetic interference suppression method, device and system

Abstract

The invention relates to the technical field of ultrasonic signal filtering, in particular to an electric superfield electromagnetic interference suppression method, device and system, and the method comprises the steps: determining a frequency domain consistent characteristic value of each modal component through analyzing the similarity of all frame signals of each modal component in a frequency domain, and combining the time domain consistent characteristic value to obtain an electromagnetic interference suppression result; determining a periodic characteristic value; and respectively analyzing the difference between each modal component in the ultrasonic signal in each probe and all modal components in the cluster where the modal component is located in the frequency domain and the time domain, constructing a time-frequency characteristic value, determining an ultrasonic characteristic value in combination with the periodic characteristic value, and suppressing the electromagnetic interference of the electric superfield. The electromagnetic interference generated by the electrical stimulation signal can be accurately identified and eliminated, so that the stability and the treatment effect of the electric ultrasonic therapeutic apparatus are improved.

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 apparatus 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 apparatus 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 apparatus will cause electromagnetic interference to the ultrasonic signal, resulting in distortion of the ultrasonic signal, and further affecting the stability and effectiveness of the electro-ultrasonic therapeutic apparatus. In the prior art, a band-pass filter is used to filter the ultrasonic signal to remove noise in a specific frequency range, which can suppress the electromagnetic interference in the electro-superfield. The passband frequency range in a traditional band-pass filter is usually a fixed value selected based on experience. However, in the actual use process of the electro-ultrasonic therapeutic apparatus, the differences in users and treatment sites will cause differences in the electrical stimulation parameters used in the electro-ultrasonic therapeutic apparatus. 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 apparatus. 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 apparatus. 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 including the following steps: Obtain the ultrasonic signal in each probe during the operation of the electro-ultrasonic therapeutic apparatus; 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 combined with the time-domain consistency eigenvalue, the periodicity eigenvalue of each modal component is determined. Cluster all modal components of the ultrasonic signal 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 periodicity eigenvalue to determine the ultrasonic eigenvalue of each modal component in the ultrasonic signal of each probe. Based on the ultrasonic eigenvalue, the ultrasonic modal components are screened out from all modal components of the ultrasonic signal in each probe to suppress the electromagnetic interference of the electrical superfield.

[0005] 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.

[0006] Preferably, the method for determining the frequency-domain consistency eigenvalue of each modal component in the ultrasonic signal of each probe is as follows: 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.

[0007] 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.

[0008] Preferably, the expression of the time-frequency eigenvalue of each modal component in the ultrasonic signal of each probe is: ; where represents the time-frequency eigenvalue of the j-th modal component in the ultrasonic signal of probe i; represents the mean value of the difference between the main frequency of the j-th modal component in the ultrasonic signal of 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 of probe i and all modal components in its corresponding cluster; exp( ) represents the exponential function with the natural constant as the base.

[0009] Preferably, the ultrasonic eigenvalue of each modal component in the ultrasonic signal of each probe is the product of the periodicity eigenvalue and the time-frequency eigenvalue of each modal component in the ultrasonic signal of each probe.

[0010] Preferably, the process of screening out ultrasonic mode components from all mode components of the ultrasonic signals in each probe is as follows: Taking the ultrasonic eigenvalue of all mode components of the ultrasonic signal in each probe as the input of the threshold segmentation algorithm, outputting the segmentation threshold, and taking all mode components with ultrasonic eigenvalues greater than the segmentation threshold as ultrasonic mode components.

[0011] Preferably, suppressing the electromagnetic interference of the electro-superfield includes: Taking the union of the frequency ranges of all ultrasonic mode components of the ultrasonic signal in each probe in the frequency domain as the passband frequency range of the band-pass filter in each probe, and filtering out the electromagnetic interference of the electro-superfield in each probe.

[0012] 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.

[0013] In a third aspect, an embodiment of the present application provides an electro-superfield electromagnetic interference suppression system, and the system includes: An ultrasonic data acquisition module, configured to acquire ultrasonic signals in each probe during the operation of an electro-ultrasonic therapeutic apparatus; An ultrasonic weight analysis module, configured to use a mode decomposition algorithm to obtain all mode components of the ultrasonic signal in each probe, divide each mode component into multiple frame signals, evaluate the correlation between all frame signals in each mode component to determine the time-domain consistency eigenvalue of each mode component; analyze the similarity between all frame signals of each mode component in the frequency domain to determine the frequency-domain consistency eigenvalue of each mode component, and combine the time-domain consistency eigenvalue to determine the periodicity eigenvalue of each mode component; Clustering all mode components of the ultrasonic signal in each probe to obtain multiple clustering clusters, respectively analyzing the differences in the frequency domain and time domain between each mode component of the ultrasonic signal in each probe and all mode components in its clustering cluster, constructing the time-frequency eigenvalue of each mode component of the ultrasonic signal in each probe, and combining the periodicity eigenvalue to determine the ultrasonic eigenvalue of each mode component of the ultrasonic signal in each probe; An electromagnetic interference suppression module, configured to screen out ultrasonic mode components from all mode components of the ultrasonic signal in each probe based on the ultrasonic eigenvalue, and suppress the electromagnetic interference of the electro-superfield.

[0014] As can be seen from the above embodiments, an electro-superfield electromagnetic interference suppression method provided by an embodiment of the present application has at least the following beneficial effects: By analyzing the similarity between the time-domain characteristics and the similarity between the frequency-domain characteristics of each modal component in the ultrasonic signal at different time periods, this application constructs periodic eigenvalues, which helps to identify the useful components in the ultrasonic signal and the noise caused by electromagnetic interference, helps to determine the periodic characteristics of the signal, and thus more accurately identifies and eliminates the electromagnetic interference generated by electrical stimulation in the ultrasonic signal. Further, by analyzing the differences in the time domain and the frequency domain between different modal components, time-frequency eigenvalues are constructed, which helps to identify the electromagnetic interference generated by the electrical stimulation signal in the ultrasonic signal, thereby more accurately and effectively suppressing the electromagnetic interference generated by the electrical stimulation signal in the ultrasonic signal, and further improving the stability and treatment effect of the electro-ultrasonic therapeutic instrument. Finally, by combining the periodic eigenvalues and the time-frequency eigenvalues, ultrasonic eigenvalues are constructed, which can accurately identify and screen out ultrasonic signals, 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. In this embodiment, by analyzing the time-domain and frequency-domain characteristics of the ultrasonic signal, the electromagnetic interference generated by the electrical stimulation signal can be accurately identified and eliminated, thereby improving the stability and treatment effect of the electro-ultrasonic therapeutic instrument. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] 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 the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 It is a flowchart of the steps of a method for suppressing electromagnetic interference in an electro-ultrasonic field provided by an embodiment of the present application; Figure 2 It is a schematic diagram of the ultrasonic eigenvalue extraction process provided by an embodiment of the present application; Figure 3 It is a block diagram of a system for suppressing electromagnetic interference in an electro-ultrasonic field provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to further elaborate on the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following, in combination with the accompanying drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of an electro-ultrasonic field electromagnetic interference suppression method, device, and system proposed according to the present application. 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.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs.

[0019] The following specifically describes the specific solutions of an electro-superfield electromagnetic interference suppression method, device, and system provided by this application in conjunction with the accompanying drawings.

[0020] Please refer to Figure 1 , which shows a flowchart of the steps of an electro-superfield electromagnetic interference suppression method provided by an embodiment of this application. The method includes the following steps: Step S1: Obtain the ultrasonic signals in each probe during the operation of the electro-ultrasonic therapeutic apparatus.

[0021] An electro-ultrasonic therapeutic apparatus is an electronic medical device that combines electrotherapy and ultrasound therapy. Its principle is to output deep ultrasound stimulation and high-frequency pulsed current from the same electrode. By using ultrasound stimulation to first change the cell permeability or sensitivity, and then through electrical stimulation to achieve more specific physiological effects, or the two act synergistically to stimulate new biological reactions, thereby enhancing the therapeutic effect.

[0022] However, the electro-ultrasonic therapeutic apparatus faces the problem of the technical integration difficulty of combining the deep ultrasound 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.

[0023] In this embodiment, the electro-superfield electromagnetic interference suppression device includes an electro-ultrasonic therapeutic apparatus. The electro-ultrasonic therapeutic apparatus includes an electro-ultrasonic therapy system software, and the ultrasound and electrical stimulation share a probe. For the convenience of description, the probe shared by the ultrasound and electrical stimulation is briefly recorded as the probe and is used in the following content description.

[0024] The electro-ultrasonic therapy system software in the electro-ultrasonic therapeutic apparatus 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 apparatus will respectively generate ultrasonic signals in the ultrasonic generator according to the parameters in the treatment plan.

[0025] Therefore, during the user's use of the electro-ultrasonic therapeutic apparatus, the ultrasonic signals in each probe during the operation of the electro-ultrasonic therapeutic apparatus are collected, and the ultrasonic signal acquisition frequency is set to 6 MHz.

[0026] Step S2: Use the 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 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.

[0027] To maintain the stability of the treatment process, the parameters of the electro-ultrasonic therapeutic apparatus cannot be adjusted after the treatment process starts. The ultrasonic signal of each probe in the electro-ultrasonic therapeutic apparatus is usually a periodic signal generated at a fixed frequency, so that the useful signal components in the ultrasonic signal 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 signal 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.

[0028] Therefore, by analyzing the consistency characteristics of the ultrasonic signal 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 signal 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 signal during the working process of the ultrasonic signal. Specifically: First, take the ultrasonic signal 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 , and output M modal components of the ultrasonic signal in each probe.

[0029] Among them, the variational mode decomposition algorithm is a well-known technology, and its specific principle will not be elaborated here.

[0030] Secondly, perform frame-by-frame windowing processing on 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 in the frame-by-frame processing process, as well as the setting of the window function, are all artificially set. In this embodiment, the value of the frame length in the frame-by-frame processing process 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 methods, the setting of the values of the frame length and frame shift and the selection of the window function can also be set by the implementer according to the specific situation, and this embodiment does not make special restrictions.

[0031] It should be understood that the process of performing frame-by-frame windowing processing on the signal and the Hamming window are both well-known technologies, and the specific principle of the frame-by-frame windowing technology and the specific application process of the Hamming window will not be elaborated here.

[0032] Furthermore, the mean 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, 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, 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.

[0033] 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 actual application, as other implementation manners, the implementer can also use the Spearman correlation coefficient or the Kendall rank correlation coefficient. This embodiment does not make special restrictions on the selection of the calculation method of the correlation coefficient between signals.

[0034] 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.

[0035] Furthermore, the time-frequency conversion algorithm is used to obtain the spectrogram of each frame signal, and the mean 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 to characterize the degree of consistency of the frequency-domain distribution characteristics of the modal component between 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.

[0036] 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 spectrogram of each frame signal. In actual application, as other implementation manners, the implementer can also use other time-frequency conversion algorithms such as wavelet transform. This embodiment does not make special restrictions on the selection of the time-frequency conversion algorithm.

[0037] 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 adopt other methods such as cosine similarity. Regarding the selection of the method for measuring the similarity between spectrograms, this embodiment does not make special restrictions.

[0038] Among them, the process of obtaining the spectrogram of the signal by using the fast Fourier transform and the calculation method of the Bhattacharyya coefficient are both well-known technologies. In this embodiment, the specific process of obtaining the spectrogram of the frame signal by using the fast Fourier transform and the calculation process of the Bhattacharyya coefficient will not be described in detail.

[0039] 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 mean of the time-domain consistency eigenvalue and the frequency-domain consistency eigenvalue of each modal component.

[0040] 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, then the periodicity 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, then the periodicity 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.

[0041] Step S3: Cluster all modal components of the ultrasonic signals in each probe to obtain a plurality of clustering clusters. Analyze the differences in the frequency domain and the time domain between each modal component in the ultrasonic signals in each probe and all modal components in its corresponding clustering cluster respectively, construct the time-frequency eigenvalues of each modal component in the ultrasonic signals in each probe, and combine the periodicity eigenvalue to determine the ultrasonic eigenvalues of each modal component in the ultrasonic signals in each probe.

[0042] Since different probes in the electro-ultrasonic therapeutic apparatus 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, due to the complex frequency components of electromagnetic interference and the lack of periodicity, 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.

[0043] Based on the above analysis, by analyzing the differences of different modal components in the ultrasonic signal in the time domain and frequency domain, ultrasonic eigenvalues are determined, the signals belonging to the ultrasonic part are screened out from the ultrasonic signal, and the electromagnetic interference generated by the electrical stimulation signal is suppressed. The specific process is as follows: Extract the main frequencies in the spectrograms of each modal component, and cluster all the 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, and multiple clustering clusters are obtained, which are used to characterize a set composed of a group of modal components with similar signal main frequencies.

[0044] It should be noted that there are many commonly used 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, implementers can also use other clustering methods such as the DPC density peak clustering algorithm for clustering. This embodiment does not make special restrictions on the selection of clustering methods.

[0045] 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.

[0046] Furthermore, by analyzing the differences between each modal component in the ultrasonic signal in each probe and all the modal components in its corresponding clustering cluster in the frequency domain and time domain, the time-frequency eigenvalues of each modal component in the ultrasonic signal in each probe are constructed. Specifically: The time-frequency eigenvalue of the j-th modal component in the ultrasonic signal in probe i The expression is: ; In the formula, 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 the modal components in its corresponding clustering 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 the modal components in its corresponding clustering cluster; exp( ) represents the exponential function with the natural constant as the base.

[0047] It should be understood that there are many methods for measuring the differences between data. In this embodiment, the absolute 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 the modal components in its corresponding clustering cluster in the frequency domain is used as the difference between the main frequencies of all the modal components in the corresponding clustering cluster of the j-th modal component in the ultrasonic signal in probe i in the frequency domain. In the actual application process, implementers can also use other methods for measuring the differences between data such as the square or ratio of the differences. This embodiment does not make special restrictions on the selection of methods for measuring the differences between data.

[0048] It should be noted that there are many methods to measure the difference 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 difference between signals, such as Euclidean distance and Manhattan distance. Regarding the selection of the method to measure the difference between signals, this embodiment does not make special restrictions.

[0049] 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 eigenvalue of each modal component in the ultrasonic signal in each probe, it can be understood that the smaller the difference between the main frequency of 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; On the contrary, the greater the difference between the main frequency of the current modal component and the main frequencies of all modal components in its clustering cluster in the frequency domain, and the greater the difference between the current modal component and all modal components in its clustering cluster, that is, the smaller the similarity degree between the current modal component and the modal components in its clustering cluster in the frequency domain, the smaller 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 different, and the greater the possibility that the current modal component belongs to the electromagnetic interference generated by the electrical stimulation signal.

[0050] Further, the product of the periodic eigenvalue and the time-frequency eigenvalue of each modal component in the ultrasonic signal in each probe is used as the ultrasonic eigenvalue of each modal component in the ultrasonic signal in each probe.

[0051] According to the ultrasonic eigenvalue of each modal component in the ultrasonic signal in each probe, it can be understood that if the periodic 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 possibility that the current modal component belongs to the ultrasonic signal is greater; on the contrary, if the periodic 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 possibility that the current modal component belongs to the electromagnetic interference generated by the electrical stimulation signal is greater.

[0052] Preferably, the schematic diagram of the ultrasonic eigenvalue extraction process provided in this embodiment is as Figure 2 shown.

[0053] Step S4: Based on the ultrasonic eigenvalue, screen out the ultrasonic mode components from all mode components in the ultrasonic signal within each probe to suppress the electromagnetic interference of the electro-ultrasonic field.

[0054] Take the ultrasonic eigenvalues of all mode components in the ultrasonic signal of each probe as the input of the threshold segmentation algorithm, output the segmentation threshold, record all mode components with ultrasonic eigenvalues greater than the segmentation threshold as ultrasonic mode components, and take the union of the frequency ranges of all ultrasonic mode components in the frequency domain in the ultrasonic signal within each probe as the passband frequency range of the band-pass filter in each probe. Use the band-pass filter to filter the ultrasonic signal generated by the ultrasonic generator in the probe.

[0055] It should be noted that there are many commonly used threshold segmentation algorithms. In this embodiment, the method of obtaining the segmentation threshold by 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, this embodiment does not make special restrictions.

[0056] Among them, the maximum inter-class variance algorithm is a well-known technology, and its specific principle will not be elaborated here.

[0057] So far, in this embodiment, by obtaining the signal frequency range of the useful signal components in the ultrasonic signal generated by each probe in the electro-ultrasonic therapeutic apparatus, 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 the electromagnetic interference generated by the electrical stimulation signal in the electro-ultrasonic therapeutic apparatus, 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 apparatus, improving the stability and therapeutic effect of the electro-ultrasonic therapeutic apparatus in the subsequent treatment process.

[0058] Based on the same inventive concept as the above method, the 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.

[0059] Based on the same inventive concept as the above method, the embodiment of the present application also provides an electro-ultrasonic field electromagnetic interference suppression system, including: An ultrasonic data acquisition module, configured to acquire the ultrasonic signal within each probe during the operation of the electro-ultrasonic therapeutic apparatus; An ultrasonic weight analysis module, which is used to obtain all modal components of the ultrasonic signal in each probe by using a modal decomposition algorithm, 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 determine the periodic eigenvalue of each modal component in combination with the time-domain consistency eigenvalue; 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 cluster, construct the time-frequency eigenvalue of each modal component in the ultrasonic signal in each probe, and determine the ultrasonic eigenvalue of each modal component in the ultrasonic signal in each probe in combination with the periodic eigenvalue; An electromagnetic interference suppression module, which is used to screen out ultrasonic modal components from all modal components of the ultrasonic signal in each probe based on the ultrasonic eigenvalue, and suppress the electromagnetic interference of the electric superfield.

[0060] A block diagram of an electric superfield electromagnetic interference suppression system provided by an embodiment of the present application is as Figure 3 shown.

[0061] It should be noted that: the above-mentioned sequence of embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above describes specific embodiments of this specification. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0062] Each embodiment in this specification is described in a progressive manner. The same and similar parts between each embodiment can be referred to each other. The key point of each embodiment is to illustrate the differences from other embodiments.

[0063] 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. A method for suppressing electromagnetic interference of electric field, characterized in that: The method comprises the following steps: Acquire the ultrasonic signal in each probe during the operation of the electro-ultrasonic therapeutic apparatus; A 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. The time domain consistent eigenvalue of each modal component is determined by evaluating the correlation between all frame signals in each modal component; the frequency domain consistent eigenvalue of each modal component is determined by analyzing the similarity between all frame signals of each modal component in the frequency domain, and the periodic eigenvalue of each modal component is determined in combination with the time domain consistent eigenvalue; Clustering all modal components of the ultrasonic signal in each probe to obtain multiple clusters, 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 the cluster to which it belongs, constructing the time-frequency eigenvalue of each modal component in the ultrasonic signal in each probe, and determining the ultrasonic eigenvalue of each modal component in the ultrasonic signal in each probe in combination with the periodic eigenvalue; Based on the ultrasonic characteristic value, the ultrasonic modal component is screened out from all modal components in the ultrasonic signal in each probe, and the electromagnetic interference of the electric super field is suppressed.

2. The method for suppressing electric field electromagnetic interference according to claim 1, characterized in that: The time-domain consistent eigenvalue of each modal component is the mean value of the correlation coefficients between all frame signals of each modal component.

3. The method for suppressing electromagnetic interference of electric field according to claim 1, characterized in that: The method for determining the frequency domain consistent eigenvalues ​​of each modal component in the ultrasonic signal in each probe is as follows: The time-frequency conversion algorithm is used to obtain the spectrum of each frame signal, and the similarity between the spectrums of all frame signals of each modal component is averaged as the frequency domain consistent eigenvalue of each modal component.

4. The method for suppressing electromagnetic interference of electric field according to claim 1, characterized in that: The periodic eigenvalue of each modal component is the average of the time domain consistent eigenvalue and the frequency domain consistent eigenvalue of each modal component.

5. The method for suppressing electric field electromagnetic interference according to claim 1, characterized in that: The expression of the time-frequency characteristic value of each modal component in the ultrasonic signal in each probe is: ; In the formula, represents the time-frequency eigenvalue of the jth modal component in the ultrasonic signal in probe i; It represents the mean value of the difference between the main frequency of the jth modal component in the ultrasonic signal in probe i and all the modal components in the cluster where it is located in the frequency domain; represents the mean of the difference between the jth modal component in the ultrasonic signal in probe i and all the modal components in its cluster; exp( ) represents an exponential function with a natural constant as the base.

6. The method for suppressing electric field electromagnetic interference according to claim 1, characterized in that: The ultrasonic eigenvalue of each modal component in each intra-probe ultrasonic signal is the product of the periodic eigenvalue and the time-frequency eigenvalue of each modal component in each intra-probe ultrasonic signal.

7. The method for suppressing electric field electromagnetic interference according to claim 1, characterized in that: The process of screening out ultrasonic modal components from all modal components in the ultrasonic signal in each probe is as follows: The ultrasonic eigenvalues ​​of all modal components in the ultrasonic signal in each probe are used as input of the threshold segmentation algorithm, and the segmentation threshold is output. All modal components with ultrasonic eigenvalues ​​greater than the segmentation threshold are regarded as ultrasonic modal components.

8. The method for suppressing electric field electromagnetic interference according to claim 1, characterized in that: The method of suppressing the electric superfield electromagnetic interference comprises: The frequency ranges of all ultrasonic modal components in the ultrasonic signal in each probe in the frequency domain are taken as the passband frequency range of the bandpass filter in each probe to filter out the electromagnetic interference of the electric field in each probe.

9. An electric field electromagnetic interference suppression device, 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, the steps of the method for suppressing electric field electromagnetic interference as described in any one of claims 1-8 are implemented.

10. An electric super-field electromagnetic interference suppression system, implementing an electric super-field electromagnetic interference suppression method as claimed in claim 1, characterized in that: The system comprises: Ultrasonic data acquisition module, used to obtain ultrasonic signals in each probe during the operation of the electro-ultrasonic therapeutic device; The ultrasonic weight analysis module is used to obtain all modal components of the ultrasonic signal in each probe by using a modal decomposition algorithm, and divide each modal component into multiple frame signals, and determine the time domain consistent eigenvalue of each modal component by evaluating the correlation between all frame signals in each modal component; determine the frequency domain consistent eigenvalue of each modal component by analyzing the similarity between all frame signals of each modal component in the frequency domain, and determine the periodic eigenvalue of each modal component in combination with the time domain consistent eigenvalue; Clustering all modal components of the ultrasonic signal in each probe to obtain multiple clusters, 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 the cluster to which it belongs, constructing the time-frequency eigenvalue of each modal component in the ultrasonic signal in each probe, and determining the ultrasonic eigenvalue of each modal component in the ultrasonic signal in each probe in combination with the periodic eigenvalue; The electromagnetic interference suppression module is used to screen out ultrasonic modal components from all modal components in the ultrasonic signal in each probe based on the ultrasonic characteristic value, and suppress the electromagnetic interference of the electric ultra-field.

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