A method and system for measuring extremely weak magnetism in traditional Chinese medicine acupuncture

Abstract

This application relates to the field of signal measurement in diagnostics, and particularly to a method and system for measuring extremely weak magnetic fields in traditional Chinese medicine acupuncture. The method includes: during acupuncture treatment, collecting different signals, amplifying the extremely weak magnetic signals and displaying them on a monitor; performing low-scale analysis on the signals to construct a low-frequency electromagnetic response characteristic factor at a low scale; constructing a biological magnetic interference eigenvalue based on the chaotic characteristics, similarity, and low-frequency electromagnetic response characteristic factor between the extremely weak magnetic signals and the other signals; adjusting the Kalman gain according to the biological magnetic interference eigenvalue to complete signal denoising; and determining the effectiveness of acupuncture by observing the changes in the extremely weak magnetic signals after denoising at the acupuncture site on the monitor. This application improves the accuracy of measuring extremely weak magnetic signals in acupuncture.

Description

Technical Field

[0001] This application relates to the field of signal measurement in diagnostics, and particularly to a method and system for measuring extremely weak magnetic fields in traditional Chinese medicine acupuncture. Background Art

[0002] Acupuncture, as an important part of traditional Chinese medicine, regulates the qi and blood of the human body by stimulating specific acupoints to treat various diseases. With the development of technology, especially the application of extremely weak magnetic field measurement technology, it provides a new tool for the scientific research of acupuncture efficacy. This technology can capture the weak magnetic signals generated by the human body during acupuncture, thus providing an objective and quantifiable means for evaluating the efficacy of acupuncture. By measuring the changes in magnetoencephalogram signals after acupuncture at different acupoints, not only can the treatment plan be optimized and the treatment effect be improved, but also the in-depth understanding of the mechanism of traditional Chinese medicine acupuncture can be promoted, and the modernization process of traditional Chinese medicine can be advanced.

[0003] The prospect of extremely weak magnetic field measurement technology is broad. It can not only be used as a new type of treatment method to provide high-sensitivity medical services for patients in a passive, non-destructive, and wearable manner, but also combine multi-disciplinary knowledge such as medicine, physics, and engineering to promote the innovative development of the acupuncture discipline. In the measurement of extremely weak magnetic fields for acupuncture efficacy, biological electromagnetic noise is an interference factor that cannot be ignored. During normal physiological activities of the human body, such as heart beating, nerve impulse transmission, and muscle contraction, weak electromagnetic fields will be generated. These electromagnetic fields generated by physiological activities are called biological electromagnetic noise, and they may overlap with the magnetic signals generated by acupuncture efficacy in time and space, thus mixing with each other, increasing the complexity of magnetic signal processing, and greatly affecting the accuracy of extremely weak magnetic signal measurement. Summary of the Invention

[0004] To solve the technical problem of the accuracy of extremely weak magnetic signal measurement, this application provides a method and system for measuring extremely weak magnetic fields in traditional Chinese medicine acupuncture. The specific technical solutions adopted are as follows:

[0005] In the first aspect, this application proposes a method for measuring extremely weak magnetic fields in traditional Chinese medicine acupuncture. The method includes the following steps:

[0006] Collect different signals, amplify the extremely weak magnetic signal and display it on a display.

[0007] Denoise the extremely weak magnetic signal according to the interference characteristics of the extremely weak magnetic signal in the collected different signals.

[0008] Judge whether the acupuncture is effective by the change of the extremely weak magnetic signal after denoising at the acupuncture site on the display.

[0009] The specific steps of denoising the extremely weak magnetic signal are as follows:

[0010] (1) Perform low-scale analysis on the signal. At low scales, construct a low-frequency electromagnetic response characteristic factor based on the frequency characteristics of different signals and the signal energy corresponding to the signals.

[0011] (2) Construct a biological magnetic interference eigenvalue based on the chaos characteristic difference between the extremely weak magnetic signal and the other signals at low scales, the similarity of the signals, the correlation between the other signals, and the low-frequency electromagnetic response characteristic factor.

[0012] (3) Obtain an initial Kalman gain value, use the initial Kalman gain and the biological magnetic interference eigenvalue to obtain a real-time Kalman gain value, and complete signal denoising based on this.

[0013] In the above solution, the present application proposes a method and system for measuring extremely weak magnetic fields in traditional Chinese medicine acupuncture. Aiming at the interference problem of biological electromagnetic noise on the measurement of extremely weak magnetic fields in acupuncture efficacy, based on the method of quadratic discrete wavelet transform, information entropy, and correlation analysis, analyze the interaction correlation between the magnetic signals generated by acupuncture efficacy and biological magnetic signals, and construct a low-frequency electromagnetic response characteristic factor to characterize the electromagnetic response characteristics and synchronism between different signals; aiming at the interference characteristic problem of biological magnetic signals on the extremely weak magnetic signals of acupuncture, based on the method of correlation coefficient and least squares linear regression, analyze the correlation intensity and the similarity degree of the trend between biological magnetic signals, and construct a biological magnetic interference eigenvalue to characterize the interference degree of biological magnetic signals on acupuncture signals; further improve the Kalman filtering algorithm, and add weights to the calculation of the Kalman gain to achieve the beneficial effect of balancing noise reduction and detail retention in different individuals, thereby solving the challenge of difficult effective separation of signals and biological electromagnetic noise, and ensuring the accuracy of the measurement of extremely weak magnetic signals in acupuncture efficacy.

[0014] In one embodiment, the collected signals include extremely weak magnetic signals, heart rate signals, and blood pressure signals. All the data collected for each signal form a sequence, which are respectively denoted as the extremely weak magnetic sequence, the heart rate sequence, and the blood pressure sequence.

[0015] In one embodiment, the method for performing low-scale analysis on the signal and constructing a low-frequency electromagnetic response characteristic factor based on the frequency characteristics of different signals and the signal energy corresponding to the signals at low scales is as follows:

[0016] Transform the extremely weak magnetic sequence, the heart rate sequence, and the blood pressure sequence into frequency-domain signals through wavelet transform, and select low-frequency signals at four scales to obtain the extremely weak magnetic low-scale signal, the heart rate low-scale signal, and the blood pressure low-scale signal.

[0017] Perform coherence analysis between the low-scale signals to obtain the low-frequency coherence eigenvalue of two low-scale signals.

[0018] Calculate the signal energy of each low-scale signal, and obtain the low-frequency electromagnetic response characteristic factor according to the low-frequency coherence eigenvalues between all pairs of low-scale signals and the signal energy of the low-scale signals.

[0019] In one embodiment, the method for performing coherence analysis between low-scale signals to obtain the low-frequency coherence eigenvalues of two low-scale signals is as follows:

[0020] For any two low-scale signals, obtain the wavelet coherence power spectrum between the two low-scale signals, where each frequency corresponds to a coherence value. Set the significance level value. Among all frequencies, when the coherence value is greater than the significance level value, assign the coherence value of the frequency to 0; when the coherence value is less than the significance level value, the coherence value of the frequency remains unchanged. Calculate the mean of the reassigned coherence values corresponding to all frequencies and denote it as the low-frequency coherence eigenvalue of the two low-scale signals.

[0021] In one embodiment, the method for obtaining the low-frequency electromagnetic response characteristic factor according to the low-frequency coherence eigenvalues between all pairs of low-scale signals and the signal energy of the low-scale signals is as follows:

[0022] Denote any one low-scale signal as the target low-scale signal, take the ratio of the signal energy of the target low-scale signal to the signal energy of another low-scale signal as the signal energy ratio. Multiply the difference between the signal energy ratio and the number 1 after inverse function normalization by the corresponding low-frequency coherence eigenvalue as the electromagnetic response characteristic of the two low-scale signals. Take the mean of the electromagnetic response characteristics obtained pairwise from all low-scale signals as the low-frequency electromagnetic response characteristic factor.

[0023] In one embodiment, the method for constructing the biomagnetic interference characteristic value according to the chaos characteristic difference between the extremely weak magnetic signal and the remaining signals at low scales, the signal similarity, the correlation between the remaining signals, and the low-frequency electromagnetic response characteristic factor is as follows:

[0024] For each low-scale signal, calculate the information entropy of the low-scale signal. Denote the low-scale signals of heart rate and blood pressure as the influencing signals. For the influencing signals and the extremely weak magnetic signal, construct a window based on each data point, and obtain the correlation coefficient between the signal slope of the window and the influencing signals.

[0025] Construct the biomagnetic interference characteristic value according to the difference between the signal slope of the extremely weak magnetic low-scale signal and the signal slope of the influencing signals, the information entropy difference, the correlation coefficient between the influencing signals corresponding to each window, and the low-frequency electromagnetic response characteristic factor.

[0026] In one embodiment, the method for constructing a window based on each data point and obtaining the correlation coefficient between the signal slope of the window and the influencing signals is as follows:

[0027] For each influencing signal, a 1*N window is constructed centered on each data point therein, and the correlation coefficient of the corresponding windows of the data points at the same position between the influencing signals is calculated through the Pearson correlation coefficient;

[0028] For each influencing signal, taking the data within each window as the input, it is fitted using the least squares linear regression to obtain the straight line fitted by the data in the window of the influencing signal, and the slope of the straight line is obtained through the fitted straight line, thereby obtaining the signal slope corresponding to each window;

[0029] For the extremely weak magnetic low-scale signal, taking the data within each window as the input, it is fitted using the least squares linear regression to obtain the straight line fitted by the data in the window of the extremely weak magnetic low-scale signal, and the slope of the straight line is obtained through the fitted straight line, thereby obtaining the signal slope corresponding to each window.

[0030] In one embodiment, the method for constructing the biomagnetic interference eigenvalue according to the difference in signal slope between the extremely weak magnetic low-scale signal and the influencing signal, the difference in information entropy, the correlation coefficient between the influencing signals, and the low-frequency electromagnetic response characteristic factor is as follows:

[0031] The absolute value of the difference in information entropy between the influencing signal and the extremely weak magnetic low-scale signal is normalized through an inverse proportional function to obtain the information difference, and the ratio of the signal slopes of the corresponding windows of the data points at the same position between the influencing signal and the extremely weak magnetic low-scale signal is denoted as the slope difference; the ratio of the information differences between the two influencing signals and the extremely weak magnetic low-scale signal and each slope difference is denoted as the information difference value, and the mean value of all the information difference values is taken and multiplied by the mean value of the correlation coefficients between the influencing signals of all windows and the low-frequency electromagnetic response characteristic factor as the biomagnetic interference eigenvalue.

[0032] In one embodiment, the method for obtaining the real-time Kalman gain value using the initial Kalman gain and the biomagnetic interference eigenvalue is as follows:

[0033] The product of the initial Kalman gain and the biomagnetic interference eigenvalue is used as the real-time Kalman gain.

[0034] In a second aspect, the embodiments of the present application further provide an extremely weak magnetic measurement system for traditional Chinese medicine acupuncture, and the system includes:

[0035] An acupuncture treatment signal filtering module: used to filter the interference characteristics of the extremely weak magnetic signal according to the collected different signals, perform low-scale analysis on the signals, and construct a low-frequency electromagnetic response characteristic factor according to the frequency characteristics of different signals and the signal energy corresponding to the signals at a low scale;

[0036] Construct a bio - magnetic interference eigenvalue based on the chaotic characteristic differences between extremely weak magnetic signals and other signals at low scales, the similarity of signals, the correlation between other signals, and the low - frequency electromagnetic response characteristic factors.

[0037] Obtain an initial Kalman gain value, use the initial Kalman gain and the bio - magnetic interference eigenvalue to obtain a real - time Kalman gain value, and filter the signal based on this.

[0038] Acupuncture treatment effect determination module: used to determine whether acupuncture is effective by the change of the extremely weak magnetic signal filtered at the acupuncture site in the display. Description of the Drawings

[0039] 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 - described drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0040] Figure 1 It is a flowchart of a method for measuring extremely weak magnetic fields for traditional Chinese medicine acupuncture provided by an embodiment of the present application.

[0041] Figure 2 It is the change situation of the extremely weak magnetic signal of the present application. Detailed Embodiments

[0042] To further elaborate on the technical means and effects adopted by the present application to achieve the intended invention purpose, the following, in combination with the drawings and preferred embodiments, details the specific embodiments, structures, features, and effects of a method and system for measuring extremely weak magnetic fields for traditional Chinese medicine acupuncture 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.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0044] An embodiment of a method and system for measuring extremely weak magnetic fields for traditional Chinese medicine acupuncture:

[0045] The following specifically describes the specific solutions of a method and system for measuring extremely weak magnetic fields for traditional Chinese medicine acupuncture provided by the present application in combination with the drawings.

[0046] Please refer to Figure 1 , which shows a flowchart of a method for measuring extremely weak magnetic fields for traditional Chinese medicine acupuncture provided by an embodiment of the present application. The method includes the following steps:

[0047] Step S001, during acupuncture treatment, acquire signals of different types at the acupuncture location, amplify the extremely weak magnetic signals and display them on a display.

[0048] Place an ultra-high sensitive atomic magnetometer in a stable measurement environment (such as a magnetic shielding chamber that shields external magnetic field interference). Before starting the measurement, accurately find and mark the acupuncture points for the subject, and place the atomic magnetometer near all the acupuncture points to facilitate capturing the extremely weak magnetic signals generated by acupuncture stimulation, so as to achieve continuous real-time acquisition of magnetic signal data. Use PhotoPlethysmoGraphy (PPG) to acquire the patient's real-time heart rate and blood pressure data. Amplify the acquired signals through a signal amplifier, and display the extremely weak magnetic signals on a display through the amplified signal display.

[0049] During the acupuncture process, the signal data will change. The efficacy of acupuncture can be determined by detecting the change of the extremely weak magnetic signals at the index part, and the change of the signals on the display provides necessary feedback information for the doctor to adjust the acupuncture time and depth.

[0050] Uniformly acquire the extremely weak magnetic signals, heart rate and blood pressure data at intervals of time t. In this embodiment, t takes an empirical value of 0.05 s, and using the three types of acquired data as input, perform real-time normalization processing on them using the Z-Score algorithm to form an extremely weak magnetic sequence, a heart rate sequence and a blood pressure sequence.

[0051] So far, the acquisition of signals is completed.

[0052] Step S002, perform low-scale analysis on the signals. At a low scale, construct a low-frequency electromagnetic response characteristic factor according to the frequency characteristics of different signals and the signal energy corresponding to the signals.

[0053] In the measurement of extremely weak magnetic fields for acupuncture efficacy, the magnetic field at acupoints is usually related to acupuncture stimulation, with a weak intensity and limited to a specific area. It may have specific frequency characteristics and obvious time dependence, while the magnetic fields generated by the heart and brain are stronger, have a wider frequency range, and are relatively stable. When measuring the extremely weak magnetic fields for acupuncture efficacy, the physiological state of the subject, including heart rate, blood pressure, etc., may have a significant impact on the measurement results. These physiological parameters are closely related to the electrophysiological activities in the body, and their changes will be reflected in the measurement of bioelectromagnetic fields. The beating of the heart and blood circulation generate electromagnetic fields, and the current generated by each beat propagates in the body, forming an electromagnetic field that can be detected by external sensors. Changes in blood pressure may also affect the electromagnetic field by influencing blood circulation, thus affecting the display of extremely weak magnetic signals. After being displayed on the monitor, errors may occur when the physician adjusts according to the monitor content. Therefore, it is necessary to suppress the heart rate signal and blood pressure signal.

[0054] Taking the extremely weak magnetic sequence, heart rate sequence, and blood pressure sequence as inputs, the three sequences are transformed from the time domain to frequency domain signals using the second-order discrete wavelet transform. After the discrete wavelet transform, frequency domain signals at four scales of LL, HL, LH, and HH are obtained. Since the electromagnetic field signals generated by the heart and brain are mainly located in the low-frequency region, and these signals may have similar frequency characteristics to the weak magnetic field signals generated by acupuncture stimulation, in the measurement of bioelectromagnetic fields for acupuncture efficacy, the LL low-frequency signal after the second-order discrete wavelet transform is selected for analysis.

[0055] Extract the signals at the LL scale after wavelet transform of the extremely weak magnetic sequence, heart rate sequence, and blood pressure sequence, denoted as the extremely weak magnetic low-scale signal, heart rate low-scale signal, and blood pressure low-scale signal. Calculate the signal energy of all low-scale signals. The calculation method of signal energy is a well-known technique and will not be elaborated in this embodiment.

[0056] Let the maximum frequency range in the extremely weak magnetic low-scale signal, heart rate low-scale signal, and blood pressure low-scale signal be , perform wavelet coherence analysis on any two of the three signals. That is, for any two low-scale signals, obtain the wavelet coherence power spectrum between the two low-scale signals, where each frequency corresponds to a coherence value. Set the significance level value. Among all frequencies, when the coherence value is greater than the significance level value, assign the coherence value of the frequency to 0; when the coherence value is less than the significance level value, keep the coherence value of the frequency unchanged. Calculate the mean of the re-assigned coherence values corresponding to all frequencies and denote it as the low-frequency coherence eigenvalue of the two low-scale signals.

[0057] Preferably, in an embodiment of the present application, the maximum frequency range is, and the value of the significance level is 0.5.

[0058] Among them, the low-frequency coherence eigenvalue quantifies the interaction between the acupuncture stimulation and the physiological state of the subject by calculating the average coherence of two low-scale signals within a specific frequency range. The larger the value, the greater the coherence between the two signals, that is, the stronger the synchronization and correlation between the two signals at this frequency.

[0059] Obtain the low-frequency electromagnetic response characteristic factor according to the low-frequency coherence eigenvalues between all pairs of low-scale signals and the signal energy of the low-scale signals.

[0060] Denote any one low-scale signal as the target low-scale signal, take the ratio of the signal energy of the target low-scale signal to the signal energy of another low-scale signal as the signal energy ratio, multiply the difference between the signal energy ratio and the number 1 after inverse function normalization by the corresponding low-frequency coherence eigenvalue as the electromagnetic response characteristic of the two low-scale signals, and take the average of the electromagnetic response characteristics obtained pairwise from all low-scale signals as the low-frequency electromagnetic response characteristic factor.

[0061] The electromagnetic response characteristic factor is used to quantify the electromagnetic response characteristics between three different low-scale signals, reflecting the interaction and correlation between the extremely weak magnetic signal and the biomagnetic signal. If the signal energies of two low-scale signals are close, that is, they have similar intensities in the low-frequency electromagnetic response, the larger the low-frequency electromagnetic response characteristic factor, and the low-frequency coherence eigenvalue can reflect the synchronization between the electromagnetic field signal generated by acupuncture stimulation and the electromagnetic field signal generated by the heart or brain. The larger its value, the larger the low-frequency electromagnetic response characteristic factor.

[0062] Thus, the low-frequency electromagnetic response characteristic factor is obtained.

[0063] Step S003, construct the biomagnetic interference eigenvalue according to the chaos characteristic difference between the extremely weak magnetic signal and the remaining signals at the low scale, the signal similarity, the correlation between the remaining signals, and the low-frequency electromagnetic response characteristic factor.

[0064] For all signals, all the data collected from the start of collection to the current moment is the signal corresponding to the current moment.

[0065] For each low-scale signal, calculate the information entropy of the low-scale signal. Denote the heart rate low-scale signal and the blood pressure low-scale signal as the influencing signals. For each influencing signal, construct a 1*N window centered on each data point. In this embodiment, N is 11, and calculate the correlation coefficient of the corresponding windows of the data points at the same position between the influencing signals through the Pearson correlation coefficient.

[0066] It should be noted that in this embodiment, the Pearson correlation coefficient is used to calculate the correlation coefficient of the corresponding two windows. The implementer can use other methods to calculate the correlation coefficient, such as the Spearman rank correlation coefficient.

[0067] For each influencing signal, using the data within each window as input, perform linear regression fitting on it using the least squares method to obtain the straight line fitted to the data in the influencing signal window, and obtain the slope of the straight line through the fitted straight line, thereby obtaining the signal slope corresponding to each window.

[0068] For extremely weak magnetic low-scale signals, similarly use the data within each window as input, perform linear regression fitting on it using the least squares method to obtain the straight line fitted to the data in the extremely weak magnetic low-scale signal window, and obtain the slope of the straight line through the fitted straight line, thereby obtaining the signal slope corresponding to each window.

[0069] Thereby obtain the signal slope of the window corresponding to each data point of the extremely weak magnetic low-scale signal.

[0070] Construct a biomagnetic interference eigenvalue based on the differences in signal slope, information entropy difference, correlation coefficient between influencing signals corresponding to each window, and low-frequency electromagnetic response characteristic factors between the extremely weak magnetic low-scale signal and the influencing signal.

[0071] Normalize the absolute value of the difference in information entropy between the influencing signal and the extremely weak magnetic low-scale signal through an inverse proportional function to obtain the information difference, and denote the ratio of the signal slopes of the data points corresponding to the same position of the influencing signal and the extremely weak magnetic low-scale signal as the slope difference; denote the ratio of the information differences between the two influencing signals and the extremely weak magnetic low-scale signal and each slope difference as the information difference value, and take the mean of all information difference values and multiply it by the mean of the correlation coefficients between the influencing signals of all windows and the low-frequency electromagnetic response characteristic factors as the biomagnetic interference eigenvalue.

[0072] Among the bio-magnetic interference eigenvalues, it reflects the interference characteristics of bio-magnetic signals on the extremely weak magnetic signals of acupuncture. The larger the value, the more significant the interference of bio-magnetic signals on acupuncture signals, indicating that the acupuncture effect is more affected by the electromagnetic fields of the heart and brain. The correlation coefficient between the influencing signals is used as a weight to characterize the correlation strength between the influencing signals considering the electromagnetic response characteristics. The low-frequency electromagnetic response characteristic factor quantifies the electromagnetic response characteristics among three different signals, reflecting the interaction correlation between the extremely weak magnetic signal and the bio-magnetic signal. The larger it is, the stronger the correlation between the signals, and the larger the bio-magnetic interference eigenvalue. Information difference gives higher weights to signal combinations with smaller information entropy differences. If the information entropy of the influencing signal is close to that of the extremely weak magnetic signal, it indicates that the uncertainties of the influencing signal and the extremely weak magnetic signal are similar, and its value will be close to 1, contributing more to the bio-magnetic interference eigenvalue. Conversely, if the information entropy difference is large, this value will be close to 0, reducing the contribution to the bio-magnetic interference eigenvalue. The signal slope measures the similarity degree of the trends of two signals. When its value is larger, the trends of the two signals are not similar, and the bio-magnetic interference eigenvalue is smaller.

[0073] So far, the bio-magnetic interference eigenvalue has been obtained.

[0074] Step S004: Obtain the initial Kalman gain value, use the initial Kalman gain and the bio-magnetic interference eigenvalue to obtain the real-time Kalman gain value, and filter the signal based on this.

[0075] In order to eliminate the influence of the electromagnetic fields of the heart and brain on the extremely weak magnetic signals of acupuncture, the Kalman filtering algorithm is used to denoise the obtained extremely weak magnetic sequence. The Kalman gain K in the Kalman filtering algorithm controls the balance between noise reduction and detail retention. A larger K value can more effectively remove noise but may cause the loss of useful signals; a smaller K value helps to retain signal details, but the denoising effect may be weakened. Since the extremely weak magnetic signals are often interfered by strong electromagnetic fields generated by organs such as the heart and brain, in order to improve the signal-to-noise ratio of the signal and accurately extract the acupuncture signal, the method of adjusting the K value is adopted to adapt to the noise level and signal characteristics of different individuals, ensuring that while removing the electromagnetic interference of the heart and brain, the weak magnetic signals generated by acupuncture are retained to the greatest extent.

[0076] The initial Kalman gain empirical value of the algorithm is calculated by a fixed formula, obtained through the ratio of the predicted error covariance and the observation noise covariance. At this time, the extremely weak magnetic sequence is used as the state input of the Kalman filtering, which is the object of Kalman filtering denoising. The extremely weak magnetic sequence, heart rate sequence, and blood pressure sequence are used as the reference inputs of the Kalman filtering to improve the calculation of the Kalman gain, calibrate and adjust the performance of the filter. The real-time bio-magnetic interference eigenvalue is calculated through the reference input, and the calculation of the K value is adjusted in real time.

[0077] The product of the normalized bio-magnetic interference eigenvalue and the initial Kalman gain is used as the real-time Kalman gain.

[0078] The extremely weak magnetic signal is denoised by the Kalman filtering algorithm.

[0079] By improving the Kalman gain in real time, the algorithm can adaptively adjust the Kalman gain according to the interference strength of the bio-magnetic signal on the extremely weak magnetic signal of acupuncture. When the interference of the bio-magnetic signal on the extremely weak magnetic signal of acupuncture is stronger, the real-time Kalman gain of the algorithm is larger, making the denoising ability of the algorithm for the state input stronger to ensure the elimination of the noise influence brought by the bio-magnetic signal. When the interference of the bio-magnetic signal on the extremely weak magnetic signal of acupuncture is weaker, the real-time Kalman gain of the algorithm is smaller, enabling the algorithm to retain more details when denoising the state input to ensure the accuracy of the extremely weak magnetic signal.

[0080] Thus, the real-time Kalman gain is obtained, and the denoising of the extremely weak magnetic signal is completed.

[0081] Step S005: Determine whether the acupuncture is effective by the change of the extremely weak magnetic signal after denoising at the acupuncture site in the display.

[0082] Through the above steps, the denoised extremely weak magnetic signal is displayed in the display. When the doctor performs acupuncture, the depth of acupuncture is adjusted, and the curative effect of acupuncture is judged by observing the peak value change of the peak of the extremely weak magnetic signal. As the acupuncture progresses, the extremely weak magnetic signal changes. The higher the peak value, the stronger the magnetic field and the better the curative effect. The change of the extremely weak magnetic signal is as Figure 2 shown. The depth with the highest peak value is stored in the memory for reference in the next acupuncture.

[0083] Based on the same inventive concept as the above method, an extremely weak magnetic measurement system for traditional Chinese medicine acupuncture provided by an embodiment of the present invention includes the following modules:

[0084] Acupuncture treatment signal induction module: used to obtain different types of signals at the acupuncture position during acupuncture treatment, and amplify and display the extremely weak magnetic signal in the display;

[0085] Acupuncture treatment signal filtering module: used to filter the interference characteristics of the extremely weak magnetic signal according to the collected different signals, perform low-scale analysis on the signals, and construct a low-frequency electromagnetic response characteristic factor according to the frequency characteristics of different signals and the signal energy corresponding to the signals at a low scale;

[0086] Construct a bio-magnetic interference eigenvalue according to the chaos characteristic difference between the extremely weak magnetic signal and the remaining signals at a low scale, the signal similarity, the correlation between the remaining signals, and the low-frequency electromagnetic response characteristic factor;

[0087] Obtain the initial Kalman gain value, use the initial Kalman gain and the bio-magnetic interference eigenvalue to obtain the real-time Kalman gain value, and filter the signal based on this;

[0088] Acupuncture treatment effect determination module: used to determine whether acupuncture is effective by observing the change of the extremely weak magnetic signal filtered at the acupuncture site on the display.

[0089] It should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

[0090] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other, and the key points of each embodiment are the differences from other embodiments.

Claims

1. An extremely weak magnetic measurement system for traditional Chinese medicine acupuncture, characterized in that: The system comprises: Acupuncture treatment signal sensing module: used to obtain different types of signals at acupuncture positions, amplify extremely weak magnetic signals and display them on the display; Acupuncture treatment signal filtering module: used to filter the interference characteristics of extremely weak magnetic signals according to the different signals collected, perform low-scale analysis on the signals, and construct low-frequency electromagnetic response characteristic factors according to the frequency characteristics of different signals and the signal energy corresponding to the signals at low scale; The biomagnetic interference characteristic value is constructed according to the difference in chaotic characteristics between the extremely weak magnetic signal and the rest of the signals at low scale, the similarity of the signals, the correlation between the rest of the signals and the low-frequency electromagnetic response characteristic factor; Obtaining an initial Kalman gain value, using the initial Kalman gain and the biomagnetic interference characteristic value to obtain a real-time Kalman gain value, and filtering the signal based on the real-time Kalman gain value; Acupuncture treatment effect judgment module: used to judge whether acupuncture is effective through the changes in the extremely weak magnetic signal after filtering at the acupuncture site in the display.

2. The extremely weak magnetic measurement system for traditional Chinese medicine acupuncture as claimed in claim 1, characterized in that: The collected signals include extremely weak magnetic signals, heart rate signals and blood pressure signals. All data collected from each signal constitute a sequence, which are recorded as extremely weak magnetic sequence, heart rate sequence and blood pressure sequence respectively.

3. The extremely weak magnetic measurement system for traditional Chinese medicine acupuncture as claimed in claim 2, characterized in that: The method of performing low-scale analysis on the signal and constructing a low-frequency electromagnetic response characteristic factor according to the frequency characteristics of different signals and the signal energy corresponding to the signal at a low scale is: The extremely weak magnetic sequence, heart rate sequence and blood pressure sequence are converted into frequency domain signals through wavelet transform, and low-frequency signals are selected at four scales to obtain extremely weak magnetic low-scale signals, heart rate low-scale signals and blood pressure low-scale signals; Perform coherence analysis between low-scale signals to obtain low-frequency coherence eigenvalues ​​of two low-scale signals; The signal energy of each low-scale signal is calculated, and the low-frequency electromagnetic response characteristic factor is obtained according to the low-frequency coherence eigenvalues ​​between all low-scale signals and the signal energy of the low-scale signal.

4. The extremely weak magnetic measurement system for traditional Chinese medicine acupuncture as claimed in claim 3, characterized in that: The method for performing coherence analysis between low-scale signals to obtain low-frequency coherence eigenvalues ​​of two low-scale signals is: For any two low-scale signals, obtain the wavelet coherence power spectrum between the two low-scale signals, where each frequency corresponds to a coherence value, set the significance level value, and among all frequencies, when the coherence value is greater than the significance level value, assign the coherence value of the frequency to 0, and when the coherence value is less than the significance level value, the coherence value of the frequency remains unchanged; The average of the re-assigned coherence values ​​corresponding to all frequencies is calculated and recorded as the low-frequency coherence eigenvalue of the two low-scale signals.

5. The extremely weak magnetic measurement system for traditional Chinese medicine acupuncture as claimed in claim 3, characterized in that: The method for obtaining the low-frequency electromagnetic response characteristic factor according to the low-frequency coherent eigenvalues ​​between all low-scale signals and the signal energy of the low-scale signals is: Any low-scale signal is recorded as the target low-scale signal, the ratio of the signal energy of the target low-scale signal to the signal energy of another low-scale signal is taken as the signal energy ratio, the difference between the signal energy ratio and the number 1 is normalized by an inverse proportional function and the product of the corresponding low-frequency coherent eigenvalue is taken as the electromagnetic response feature of the two low-scale signals, and the average of the electromagnetic response features obtained pairwise from all low-scale signals is taken as the low-frequency electromagnetic response characteristic factor.

6. The extremely weak magnetic measurement system for traditional Chinese medicine acupuncture as claimed in claim 3, characterized in that: The method for constructing the biomagnetic interference characteristic value according to the difference in chaotic characteristics between the extremely weak magnetic signal and the other signals at a low scale, the similarity of the signals, the correlation between the other signals and the low-frequency electromagnetic response characteristic factor is: For each low-scale signal, the information entropy of the low-scale signal is calculated, and the low-scale signal of heart rate and the low-scale signal of blood pressure are recorded as the influence signal. For the influence signal and the very weak magnetic signal, a window is constructed based on each data point to obtain the correlation coefficient between the signal slope of the window and the influence signal; The biomagnetic interference characteristic value is constructed based on the difference in signal slope corresponding to the extremely weak magnetic low-scale signal and the signal slope of the influencing signal, the difference in information entropy, the correlation coefficient between the influencing signals corresponding to each window, and the low-frequency electromagnetic response characteristic factor.

7. The extremely weak magnetic measurement system for traditional Chinese medicine acupuncture as claimed in claim 6, characterized in that: The method of constructing a window based on each data point and obtaining the signal slope of the window and the correlation coefficient between the influencing signals is: For each impact signal, a 1*N window is constructed with each data point as the center, and the correlation coefficient of the windows corresponding to the data points at the same position between the impact signals is calculated by the Pearson correlation coefficient; For each influencing signal, the data in each window is taken as input, and the least squares linear regression is used to fit it, so as to obtain the straight line fitted by the data in the influencing signal window, and the slope of the straight line is obtained through the fitted straight line, thereby obtaining the signal slope corresponding to each window; For extremely weak magnetic low-scale signals, the data in each window is taken as input and fitted using least squares linear regression to obtain the straight line fitted to the data in the extremely weak magnetic low-scale signal window, and the slope of the straight line is obtained through the fitted straight line, thereby obtaining the signal slope corresponding to each window.

8. The extremely weak magnetic measurement system for traditional Chinese medicine acupuncture as claimed in claim 4, characterized in that: The method for constructing the biomagnetic interference characteristic value according to the difference between the signal slope corresponding to the extremely weak magnetic low-scale signal and the signal slope of the influencing signal, the information entropy difference, the correlation coefficient between the influencing signals and the low-frequency electromagnetic response characteristic factor is: The absolute value of the difference in information entropy between the influencing signal and the extremely weak magnetic low-scale signal is normalized by an inverse proportional function to obtain the information difference, and the ratio of the signal slopes of the windows corresponding to the data points at the same position of the influencing signal and the extremely weak magnetic low-scale signal is recorded as the slope difference; the information difference between the two influencing signals and the extremely weak magnetic low-scale signal and the ratio of each slope difference are recorded as information difference values, and the product of the average of all information difference values, the average of the correlation coefficients between the influencing signals in all windows, and the low-frequency electromagnetic response characteristic factor is taken as the biomagnetic interference characteristic value.

9. The extremely weak magnetic measurement system for traditional Chinese medicine acupuncture as claimed in claim 1, characterized in that: The method for obtaining the real-time Kalman gain value by using the initial Kalman gain and the biomagnetic interference characteristic value is: The product of the initial Kalman gain and the biomagnetic interference characteristic value is used as the real-time Kalman gain.

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