Adaptive electromagnetic compatibility ultrashort wave physiotherapy system and interference-free operation control method

Abstract

The invention discloses a self-adaptive electromagnetic compatibility ultrashort wave physiotherapy system and a non-interference operation control method, and belongs to the technical field of ultrashort wave physiotherapy. The adaptive electromagnetic compatible ultrashort wave physiotherapy system comprises an ultrashort wave physiotherapy host, an electromagnetic environment sensing module, a positioning isolation module, an adaptive adjustment module, a physiotherapy parameter matching module and a safety monitoring module. According to the invention, the problems of lack of adaptive control of electromagnetic compatibility and incapability of solving interference in operation in the prior art are solved. Through real-time electromagnetic interference monitoring and multi-dimensional self-adaptive adjustment, various electromagnetic interferences in a complex medical environment can be effectively inhibited, electromagnetic compatibility control and dynamic balance of a treatment effect are realized, electromagnetic interferences are inhibited, physiotherapy parameters can be accurately optimized, physiotherapy energy is ensured to effectively act on a diseased region of a human body, and the treatment effect is improved. The treatment effective rate is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of ultrashort wave physiotherapy, in particular to an ultrashort wave physiotherapy system with adaptive electromagnetic compatibility and a non-interference operation control method. BACKGROUND

[0002] The ultrashort wave physiotherapy technology has been widely applied to the fields of rehabilitation medicine and clinical medicine due to its remarkable effects on inflammation subsiding, tissue repair and pain relief. The ultrashort wave physiotherapy equipment generates high-frequency electromagnetic waves with a frequency of 30-300 MHz to act on the affected part of the human body, and realizes the treatment purpose by using the thermal effect and non-thermal effect of electromagnetic energy.

[0003] A control method and system based on an ultrashort wave therapeutic instrument are disclosed in Chinese Patent No. CN120459540A. The method comprises: acquiring disease information and human body composition data of a user; the disease information comprises a treatment site, and the human body composition data comprises a body fat rate, a water content and a muscle content; inputting the human body composition data and the disease information into a trained treatment parameter recommendation model to obtain treatment parameters of the user; the treatment parameters comprise an output power and a treatment time, and the treatment parameter recommendation model is a machine learning model; and outputting the treatment parameters can make the ultrashort wave therapeutic instrument emit ultrashort waves corresponding to the treatment parameters.

[0004] The above-mentioned patent determines the physiotherapy position through a human body image and adjusts the parameters according to the blood flow velocity during actual use, thereby improving the treatment accuracy, but lacks adaptive control of electromagnetic compatibility and cannot solve the problem of interference during operation; therefore, the existing requirements are not met, and for this purpose, the ultrashort wave physiotherapy system with adaptive electromagnetic compatibility and the non-interference operation control method are proposed. SUMMARY

[0005] The application aims to provide an ultrashort wave physiotherapy system with adaptive electromagnetic compatibility and a non-interference operation control method. Through real-time electromagnetic interference monitoring and multi-dimensional adaptive adjustment, various types of electromagnetic interference in complex medical environments can be effectively suppressed, the dynamic balance between electromagnetic compatibility control and treatment effect is realized, the physiotherapy parameters can be accurately optimized while suppressing electromagnetic interference, the physiotherapy energy can be effectively applied to the affected part of the human body, the treatment efficiency is improved, and the problems in the above background technology are solved.

[0006] To achieve the above-mentioned purpose, the application provides the following technical scheme: an ultrashort wave physiotherapy system with adaptive electromagnetic compatibility, comprising: an ultrashort wave physiotherapy host, configured to generate an ultrashort wave signal with a preset frequency and power, radiate the ultrashort wave signal to an affected part of the human body, and realize ultrashort wave physiotherapy; An electromagnetic environment perception module is configured to collect initial electromagnetic environment data around the ultrashort wave therapy host in real time by using a distributed electromagnetic sensor and to preprocess the initial electromagnetic environment data, the initial electromagnetic environment data including multi-band electromagnetic signals, electric field intensity, magnetic field intensity, and characteristic parameters of interference signals, and to synchronize the collected data to an adaptive adjustment module and a positioning isolation module; The positioning isolation module is configured to perform feature extraction and type identification on the collected interference signals, to determine the spatial position of the interference source according to the phase difference and amplitude difference of multiple groups of perception data, and to generate a targeted isolated magnetic field according to the position and type of the interference source. The adaptive adjustment module is configured to dynamically adjust the signal output frequency, power, and signal modulation mode of the ultrashort wave therapy host according to the electromagnetic environment data and the therapy parameters, and to perform adaptive adjustment on the electromagnetic shielding structure. The therapy parameter matching module is configured to generate an optimal therapy parameter combination according to the physiological parameters, therapy site, and medical history information of the patient, in combination with historical therapy data and electromagnetic compatibility optimization parameters. The safety monitoring module is configured to monitor the running state of the ultrashort wave therapy host, the physiological signals of the patient, and the safety threshold of the electromagnetic environment in real time, and to immediately trigger a protection mechanism to cut off the ultrashort wave output or adjust the running parameters when an abnormal condition is detected.

[0007] Preferably, the intelligent matching module comprises: The therapy demand analysis unit is configured to collect and analyze therapy-related information of the patient to determine the patient's therapy target, suitable therapy intensity, and therapy duration. The parameter matching unit is configured to match an initial therapy parameter combination from a database according to the analysis results, the initial therapy parameter combination including ultrashort wave output frequency, power, modulation mode, therapy duration, and therapy interval parameters. The parameter optimization unit is configured to optimize and adjust the initial therapy parameter combination in combination with the output electromagnetic environment data and historical optimization data to generate an optimal therapy parameter combination.

[0008] Preferably, the adaptive adjustment module comprises: The adaptive filtering unit is configured to adjust the filtering frequency band and filtering attenuation coefficient in real time according to the frequency characteristics of the interference signals. The adjustable shielding unit is configured to control the aperture size and shielding angle of the shielding mesh. The frequency adaptive adjustment unit is configured to dynamically adjust the oscillation frequency of the high-frequency oscillation circuit within the standard working frequency band of the ultrashort wave therapy. The power adaptive compensation unit is configured to adjust the power amplification multiple in real time according to the interference intensity to compensate for the therapy energy loss caused by the interference.

[0009] Preferably, the adaptive filtering unit comprises: The multi-band electromagnetic signals in the electromagnetic environment data are preprocessed to obtain target signals; After the target signals are normalized, a plurality of preset analysis algorithms are used for signal conversion to obtain a plurality of target frequency domain signals; The signal confidence of the target frequency domain signal obtained by the preset analysis algorithm is acquired; The interference frequency characteristics of the target frequency domain signal are extracted and mean value analysis is performed to obtain a characteristic mean value; The characteristic difference ratio of the interference frequency characteristics of the target frequency domain signal and the corresponding characteristic mean value is calculated, and the characteristic performance difference of the interference frequency characteristics of the target frequency domain signal is determined in combination with the signal confidence of the corresponding preset analysis algorithm; When the characteristic performance difference is less than the set difference threshold of the corresponding interference frequency characteristics, a mark is added to the target frequency signal; The target frequency signal with the largest number of marks is determined as a reference frequency signal; The interference frequency range of the reference frequency signal is extracted, and when the interference frequency range is multiple, the maximum value and the minimum value in all interference frequency ranges are extracted to construct an important interference frequency band; When there is only a single interference frequency range, the important interference frequency band is determined based on the interference frequency range; The main interference frequency point of the reference frequency signal is taken as a target center frequency; When the important interference frequency band and the physiotherapy signal frequency band overlap, or the frequency band distance is less than the lower limit of the set distance threshold, the filtering frequency band is expanded to cover the overlapping frequency band or the important interference frequency band; The adjusted filtering frequency band is determined based on the target bandwidth and the target center frequency; When the frequency band distance between the important interference frequency band and the physiotherapy signal frequency band is greater than the upper limit of the set distance threshold, the adjusted filtering frequency band is determined based on the target center frequency and the bandwidth of the current filtering frequency band; The strength of the interference signal is evaluated based on the amplitude of each frequency component of the reference frequency signal to obtain a target signal strength; The target filtering attenuation coefficient is selected from a signal strength-filtering attenuation coefficient mapping table using the target signal strength; In the case where the important interference frequency band and the physiotherapy signal frequency band overlap, the target filtering attenuation coefficient is increased and used as the filtering attenuation coefficient of the overlapping frequency band; The target filtering attenuation coefficient is used as the filtering attenuation coefficient of the remaining frequency bands in the adjusted filtering frequency band except for the overlapping frequency band; In the case that the frequency band distance between the important interference frequency band and the physiotherapy signal frequency band is greater than the upper limit of the set distance threshold, the target filter attenuation coefficient is reduced as the filter attenuation coefficient of the adjusted filter frequency band.

[0010] Preferably, the safety monitoring module specifically comprises: The working state parameters of the ultrashort wave physiotherapy host are monitored in real time, and the heart rate, respiratory rate, skin temperature, skin resistance signal of the patient during the physiotherapy process, and the electromagnetic radiation intensity around the ultrashort wave physiotherapy host are monitored. When it is monitored that a certain parameter exceeds the preset normal range, the patient's physiological signal is abnormal, or the electromagnetic radiation intensity is abnormal, an early warning signal is immediately sent, and the power supply or signal output circuit of the ultrashort wave physiotherapy host is quickly cut off.

[0011] The interference-free operation control method is applied to an ultrashort wave physiotherapy system with adaptive electromagnetic compatibility, and comprises the following steps: S1: initial electromagnetic environment data around the ultrashort wave physiotherapy host is collected by using a distributed electromagnetic sensor, and the collected initial electromagnetic environment data is subjected to analog-to-digital conversion and pretreatment; S2: physiological parameters of the patient are collected in real time, the physiological parameters include heart rate, body temperature, skin impedance, and electromyographic signal, and an optimal physiotherapy parameter combination is generated according to the physiological parameters; S3: initial electromagnetic compatibility control parameters are determined by an adaptive electromagnetic compatibility control algorithm according to the initial electromagnetic environment data and the optimal physiotherapy parameter combination; S4: the ultrashort wave physiotherapy host is controlled to start working according to the optimal physiotherapy parameter combination and the initial electromagnetic compatibility control parameters, and ultrashort wave physiotherapy is started, while the electromagnetic environment data is monitored in real time and the interference signal parameters are updated; S5: the real-time monitored electromagnetic environment data is dynamically analyzed, and the difference between the current electromagnetic environment data and the initial electromagnetic environment data is compared to determine whether the electromagnetic interference has changed, if the interference has no obvious change, the current parameters are maintained unchanged and the treatment is continued; S6: the interference signal in the real-time monitored electromagnetic environment data is subjected to type identification and frequency band division, the spatial position coordinates of the interference source are determined, and the interference source is subjected to directional isolation; S7: if the interference has obvious change, the interference source positioning and isolation process of S6 is repeated, and the signal parameters and shielding structure are dynamically adjusted according to the changed electromagnetic environment data, while the physiotherapy parameter combination is real-time optimized and adjusted; S8: if it is monitored that the host operation parameters are abnormal or the patient's physiological signal is abnormal, an emergency protection mechanism is triggered immediately, the ultrashort wave output is cut off, the fault information is recorded, and a fault prompt is displayed; S9: when the treatment time reaches the preset time optimized, the control ultrashort wave physiotherapy host stops working, records the relevant data of this treatment, generates a treatment report and displays it to the operator.

[0012] Preferably, S5 specifically includes: The difference between the current electromagnetic environment data and the initial electromagnetic environment data is compared to obtain an electromagnetic environment difference coefficient; When the electromagnetic environment difference coefficient exceeds the set difference threshold, it is determined that the electromagnetic interference has changed significantly; Otherwise, it is determined that the electromagnetic interference has not changed significantly.

[0013] Preferably, S6 specifically includes: The interference type of the interference signal in the real-time collected electromagnetic interference data is identified, and the interference signal is divided into low-frequency interference, ultrashort wave frequency band interference and high-frequency interference; According to the phase difference and amplitude difference of the interference signal, combined with the array layout information of the distributed electromagnetic sensor, a fusion positioning algorithm based on AOA and TDOA is used to determine the spatial position coordinates of the interference source; According to the type, intensity and position of the interference source, the interference source is directionally isolated by selecting active cancellation, physical shielding or a combination of the two; The isolated electromagnetic environment data is monitored in real time, and the isolated electromagnetic environment data is compared with the electromagnetic environment data before isolation to calculate the isolation effect index. If the isolation effect index does not reach the preset threshold, adjust the isolation parameters until the requirements are met.

[0014] Preferably, S2 specifically includes: Collecting physiotherapy related information of the patient, the physiotherapy related information including physiological parameters, physiotherapy site, medical history information and current body state; Analyzing the collected physiotherapy related information of the patient to determine the physiotherapy target, suitable physiotherapy intensity and physiotherapy duration of the patient; Building a physiotherapy parameter database, and matching the initial physiotherapy parameter combination from the database according to the analysis result; Combining the output electromagnetic environment data and historical optimization data, the initial physiotherapy parameter combination is optimized and adjusted to generate the optimal physiotherapy parameter combination.

[0015] Preferably, the dynamic adjustment of the signal parameters and the shielding structure further includes When the physiotherapy parameter combination is optimized and adjusted in real time, an incremental learning algorithm is used to update the optimization model of the genetic algorithm online in combination with the real-time electromagnetic environment data and patient physiological signal feedback during the current physiotherapy process; In the dynamic adjustment of signal parameters, a predictive control algorithm is adopted to predict the interference signal characteristics in the future period of time according to the variation trend of real-time electromagnetic environment data, and the signal parameters are adjusted in advance; When a new interference source is monitored, the new interference source is quickly located based on the existing distributed electromagnetic sensor collected data and historical interference source positioning data.

[0016] Compared with the prior art, the beneficial effects of the present application are: The present application realizes the adaptive optimization of electromagnetic compatibility performance by real-time sensing of the change of the surrounding electromagnetic environment data, combining with the operation parameters of the ultrashort wave, and adjusting the aperture size and shielding angle of the shielding screen, the oscillation frequency and power amplification multiple of the high-frequency oscillation circuit, effectively suppressing the influence of external electromagnetic interference on the system, reducing the interference of the system itself electromagnetic radiation on the surrounding equipment, effectively suppressing various electromagnetic interferences in the complex medical environment, realizing the dynamic balance of electromagnetic compatibility control and treatment effect, avoiding the problems of cost increase and lack of flexibility caused by overall shielding, while suppressing electromagnetic interference, accurately optimizing physiotherapy parameters, ensuring that physiotherapy energy effectively acts on the human pathological site, and improving the treatment efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0017] Fig. 1 The present application is an adaptive electromagnetic compatibility ultrashort wave physiotherapy system schematic diagram; Fig. 2 The present application is an interference-free operation control method schematic diagram. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0019] In order to solve the problem that the prior art lacks adaptive control of electromagnetic compatibility and cannot solve the interference problem in operation, please refer to Figs. 1-2 The present embodiment provides the following technical solutions: The adaptive electromagnetic compatibility ultrashort wave physiotherapy system comprises: An ultrashort wave physiotherapy host is used to generate an ultrashort wave signal of a preset frequency and power, radiate the ultrashort wave signal to a human pathological site, and realize ultrashort wave physiotherapy. The electromagnetic environment sensing module is used to collect and preprocess the initial electromagnetic environment data around the ultra-shortwave physiotherapy host in real time using distributed electromagnetic sensors. The initial electromagnetic environment data includes characteristic parameters of multi-band electromagnetic signals, electric field strength, magnetic field strength, and interference signals. The collected data is then synchronized to the adaptive adjustment module and the positioning isolation module. The positioning and isolation module is used to extract features and identify the type of the collected interference signals. It determines the spatial location of the interference source based on the phase difference and amplitude difference of multiple sets of sensing data. Based on the location and type of the interference source, it generates a targeted isolation magnetic field to achieve directional isolation of the interference source. The adaptive adjustment module is used to dynamically adjust the signal output frequency, power, and signal modulation method of the ultra-shortwave physiotherapy host according to electromagnetic environment data and physiotherapy parameters, and to adaptively adjust the electromagnetic shielding structure. The physiotherapy parameter matching module is used to generate the optimal combination of physiotherapy parameters based on the patient's physiological parameters, physiotherapy sites, and medical history information, combined with historical physiotherapy data and electromagnetic compatibility optimization parameters. The safety monitoring module is used to monitor the operating status of the ultra-shortwave therapy host, the patient's physiological signals, and the safety threshold of the electromagnetic environment in real time. When an abnormality is detected, the protection mechanism is immediately triggered to cut off the ultra-shortwave output or adjust the operating parameters.

[0020] The intelligent matching module includes: The physiotherapy needs analysis unit is used to collect and analyze patients' physiotherapy-related information to determine the patients' physiotherapy goals, appropriate physiotherapy intensity, and physiotherapy duration. The parameter matching unit is used to match the initial physiotherapy parameter combination from the database based on the analysis results. The initial physiotherapy parameter combination includes: ultra-shortwave output frequency, power, modulation mode, physiotherapy duration, and physiotherapy interval parameters. The parameter optimization unit is used to combine the output electromagnetic environment data and historical optimization data to optimize and adjust the initial combination of physiotherapy parameters, thereby generating the optimal combination of physiotherapy parameters.

[0021] The adaptive adjustment module includes: An adaptive filtering unit is used to adjust the filtering frequency band and filtering attenuation coefficient in real time according to the frequency characteristics of the interference signal. Adjustable shielding unit is used to control the aperture size and shielding angle of the shielding mesh to achieve shielding adaptation to interference of different intensities; The frequency adaptive adjustment unit is used to dynamically adjust the oscillation frequency of the high-frequency oscillation circuit within the standard operating frequency band of ultra-shortwave therapy to avoid overlap with the frequency of interference signals. The power adaptive compensation unit is used to adjust the power amplification factor in real time according to the interference intensity to compensate for the energy loss of physiotherapy caused by interference.

[0022] The adaptive filtering unit specifically includes: The target signal is obtained by preprocessing the multi-band electromagnetic signals in the electromagnetic environment data. After the target signal is normalized, the signal is converted using a variety of preset analysis algorithms to obtain several target frequency domain signals. Obtain the signal confidence level of the corresponding target frequency domain signal using a preset analysis algorithm; The interference frequency characteristics of the target frequency domain signal are extracted and mean analysis is performed to obtain the characteristic mean. Calculate the feature difference ratio between the interference frequency characteristics of the target frequency domain signal and the corresponding feature mean, and determine the feature performance difference of the interference frequency characteristics of the current target frequency domain signal by combining the signal confidence of the corresponding preset analysis algorithm; When the difference in characteristic performance is less than the set difference threshold of the corresponding interference frequency characteristic, a mark is added to the target frequency domain signal; The target frequency signal with the largest number of markers is determined as the reference frequency signal; Extract the interference frequency range of the reference frequency signal, and when there are multiple interference frequency ranges, extract the maximum and minimum values ​​of all interference frequency ranges to construct important interference frequency bands; When there is only a single interference frequency range, the important interference frequency bands are determined based on the interference frequency range. The main interference frequency of the reference frequency signal is taken as the target center frequency; When there is overlap between important interference frequency bands and physiotherapy signal frequency bands, or when the frequency band distance is less than the lower limit of the set distance threshold, the corresponding filtering frequency band will be extended to cover the overlapping frequency band, or extended to cover the important interference frequency band. The adjusted filter frequency band is determined based on the target bandwidth and target center frequency; When the frequency band distance between the important interference frequency band and the physiotherapy signal frequency band is greater than the upper limit of the set distance threshold, the adjusted filter frequency band is determined based on the target center frequency and the bandwidth of the current filter frequency band. The strength of the interference signal is evaluated based on the amplitude of each frequency component of the reference frequency signal, and the strength of the target signal is obtained. The target filter attenuation coefficient is obtained by filtering from the signal strength-filter attenuation coefficient mapping table using the target signal strength. When there is overlap between the important interference frequency band and the physiotherapy signal frequency band, the target filter attenuation coefficient is increased and then used as the filter attenuation coefficient for the overlapping frequency band. The target filter attenuation coefficient is used as the filter attenuation coefficient for the remaining frequency bands in the adjusted filter frequency band, excluding overlapping frequency bands. When the frequency distance between the important interference frequency band and the physiotherapy signal frequency band is greater than the upper limit of the set distance threshold, the target filter attenuation coefficient is reduced and used as the filter attenuation coefficient of the adjusted filter frequency band.

[0023] Among them, multi-band electromagnetic signals are electromagnetic radiation signals of different frequency bands (covering the physiotherapy signal frequency band and the potential interference frequency band) in the environment where the ultra-shortwave physiotherapy system is located, including interference signals.

[0024] Data preprocessing includes, but is not limited to, amplification, and filtering algorithms to remove high-frequency noise and low-frequency drift from the signal; the target signal is an electromagnetic signal that has been processed by denoising and amplification; the target frequency domain signal is a frequency domain signal obtained by converting the target signal through a preset analysis algorithm, reflecting the components and characteristics of the target signal at different frequencies.

[0025] The preset analysis algorithm is a spectrum analysis algorithm, including but not limited to FFT, wavelet transform, parametric modeling, etc.; dimensional normalization processing includes amplitude normalization, power spectral density conversion, and phase consistency correction.

[0026] Signal confidence is used to quantify the reliability of the target frequency domain signal generated by a preset analysis algorithm. Signal confidence is determined by evaluating the preset performance evaluation index of different preset analysis algorithms. For example, for the FFT algorithm, its accuracy in identifying the frequency components of the signal under different signal-to-noise ratio environments can be used as signal confidence; for wavelet transform, its stability in detecting abrupt changes in the signal can be used as signal confidence; parametric modeling methods can evaluate signal confidence through indicators such as the residuals of model fitting.

[0027] Interference frequency characteristics are parameters used to describe the frequency characteristics of interference signals, including but not limited to the main frequency points, frequency range, and amplitude of each frequency component of the interference signal.

[0028] The characteristic mean is the value obtained by averaging the characteristic values ​​of the same interference frequency characteristics of each target frequency domain signal.

[0029] The feature difference ratio is the ratio of the interference frequency feature of the target frequency domain signal to the corresponding feature mean, which is used to reflect the degree of deviation of the interference frequency feature of the current target frequency domain signal from the mean value.

[0030] The feature performance difference can be obtained by multiplying the signal confidence level of the preset analysis algorithm with the feature difference ratio. It is used to measure the difference in interference frequency characteristics and the reliability of the quantification value. The value range is (0,1).

[0031] The difference threshold is set in advance based on a large amount of experimental data, the tolerance for differences in the characteristics of interference signals in actual application scenarios, and the requirements for filtering accuracy and performance. It is used to determine whether the difference in characteristic performance meets the threshold for adding a label.

[0032] For example, assuming that the main frequency points and frequency ranges of the interference frequency characteristics of the target frequency domain signal 1 all have differences in the corresponding set difference thresholds, then the target frequency domain signal 1 is marked twice; the number of marks for the target frequency domain signal 1 is 2.

[0033] Important interference frequency bands are those constructed based on the range of interference frequencies that may have a significant impact on physiotherapy signals.

[0034] When there are multiple interference frequency ranges, the maximum and minimum values ​​within each range are extracted to construct the important interference frequency band. For example, if there are three interference frequency ranges, namely [100Hz-200Hz], [300Hz-400Hz], and [500Hz-600Hz], then the maximum and minimum values ​​within each range are extracted, i.e., the maximum value of 600Hz and the minimum value of 100Hz. The constructed important interference frequency band is [100Hz - 600Hz].

[0035] When there is only a single interference frequency range, the important interference frequency band is determined based on the interference frequency range. For example, if there is an interference frequency range of [800Hz-900Hz], then the important interference frequency band determined based on this interference frequency range is [800Hz-900Hz].

[0036] The physiotherapy signal frequency band can be the frequency band occupied in the frequency domain by the signal used by the ultra-shortwave physiotherapy system.

[0037] The frequency range between important interference frequency bands and physiotherapy signal frequency bands can be determined by calculating the difference between the center frequencies of the two frequency bands or the difference between the boundary frequencies of the frequency bands.

[0038] The lower limit of the distance threshold is set to a preset distance threshold to determine whether the distance between the important interference frequency band and the physiotherapy signal frequency band is too close. When the frequency band distance is less than the set lower limit of the distance threshold, the filter frequency band needs to be adjusted accordingly.

[0039] The upper limit of the distance threshold is set to a preset distance threshold to determine whether the distance between the important interference frequency band and the physiotherapy signal frequency band is too far. When the frequency band distance is greater than the upper limit of the set distance threshold, the filter frequency band needs to be adjusted accordingly.

[0040] Overlapping frequency bands are the frequency bands that overlap with important interference frequency bands and physiotherapy signal frequency bands.

[0041] The target signal strength is used to reflect the strength of the interference signal. The target signal strength can be calculated using a weighted average method, which assigns different weights to different frequency components based on their importance to the interference signal (for example, the frequency components closer to the main frequency point are given higher weights). The weighted average of the amplitude values ​​of each frequency component is then used as the target signal strength.

[0042] The signal strength-filter attenuation coefficient mapping table is established by first acquiring a large amount of actual filtering effect data recorded under different signal strengths in different electromagnetic environments, and then obtaining the theoretically appropriate range of filter attenuation coefficients under different signal strengths through theoretical analysis and simulation. Next, the signal quality after filtering (such as the degree of improvement in signal-to-noise ratio, interference suppression effect, etc.) under different filter attenuation coefficients is analyzed to determine the filter attenuation coefficient that can achieve the best filtering effect in each signal strength range, and the corresponding mapping table is established.

[0043] The filter attenuation coefficient of the overlapping frequency band can be obtained by multiplying the power ratio of the interference signal in the overlapping frequency band by a preset adjustment step size, and then adding this adjustment amount to the target filter attenuation coefficient. The preset adjustment step size is an adjustment range determined based on a large amount of experimental data (such as the filtering effect after adjusting the filter attenuation coefficient with different adjustment step sizes under different electromagnetic environments and multiple different interference signal scenarios, different interference signal intensities, different degrees of overlap).

[0044] When the frequency band distance between the important interference frequency band and the physiotherapy signal frequency band is greater than the upper limit of the set distance threshold, the coupling attenuation can be determined based on the spatial propagation loss formula and the frequency band distance. Then, based on the coupling attenuation and the system's requirement to suppress potential leakage interference, the reduction range can be determined. Finally, the target filter attenuation coefficient is subtracted from the reduction range to obtain the adjusted filter attenuation coefficient.

[0045] The working principle of the above technical solution is as follows: First, the target signal obtained by amplifying and denoising the multi-band electromagnetic signals in the electromagnetic environment data using filtering algorithms is normalized. Then, it is converted into a target frequency domain signal using various preset spectrum analysis algorithms, and the signal confidence of the target frequency domain signal corresponding to each algorithm is obtained. Next, the interference frequency characteristics of the target frequency domain signal are extracted and mean analysis is performed to obtain the feature mean. The feature difference ratio is calculated and combined with the signal confidence to determine the feature performance difference. When the feature performance difference is less than the set difference threshold, the target frequency domain signal is marked, and the signal with the most marks is determined as the reference frequency signal. Then, important interference frequency bands are constructed based on the interference frequency range of the reference frequency signal, and the main interference frequency point is used as the target center frequency. According to the positional relationship between the important interference frequency band and the physiotherapy signal frequency band (overlap, distance less than the lower limit of the set threshold or greater than the upper limit of the set threshold), the filtering frequency band is expanded or adjusted accordingly. Finally, the interference signal strength is evaluated based on the amplitude of each frequency component of the reference frequency signal to obtain the target signal strength. The signal strength is then calculated using the signal strength- The target filtering attenuation coefficient is selected from the filtering attenuation coefficient mapping table. Finally, the target filtering attenuation coefficient is adjusted according to the positional relationship between the important interference frequency band and the physiotherapy signal frequency band (overlap, distance greater than the set threshold upper limit) to achieve effective filtering of the physiotherapy signal frequency band.

[0046] The beneficial effects of the above technical solution are as follows: by accurately identifying interference signals in the electromagnetic environment and intelligently expanding or adjusting the filter frequency band according to the relationship between the interference signal and the physiotherapy signal frequency band, the interference signal can be avoided from affecting the physiotherapy signal. At the same time, the filter attenuation coefficient is dynamically determined according to the intensity of the interference signal, and the corresponding attenuation coefficient is increased when there are overlapping frequency bands and decreased when the interference signal is far away. This minimizes the interference of interference signals on ultra-shortwave physiotherapy, ensures the purity and stability of the physiotherapy signal, and thus helps to improve the accuracy and effectiveness of ultra-shortwave physiotherapy.

[0047] The security monitoring module specifically includes: The system monitors the working status parameters of the ultra-shortwave physiotherapy host in real time, including output frequency, power, current, voltage, temperature, etc. It adopts a combination of sensor acquisition and circuit detection to collect and monitor the patient's heart rate, respiratory rate, skin temperature and skin resistance signals during the physiotherapy process. The sensors are made of flexible materials and fit the patient's skin surface to avoid causing pressure and discomfort to the patient. It also monitors the electromagnetic radiation intensity around the ultra-shortwave physiotherapy host. When a parameter is detected to be outside the preset normal range, or when the patient’s physiological signals are abnormal (such as excessively fast heart rate, rapid breathing, or excessively high skin temperature) or when the intensity of electromagnetic radiation is abnormal, an early warning signal is immediately sent, and the power supply or signal output circuit of the ultra-shortwave therapy host is quickly cut off to achieve hardware-level rapid protection.

[0048] The interference-free operation control method applied to an adaptive electromagnetic compatibility ultra-shortwave physiotherapy system includes the following steps: S1: Use distributed electromagnetic sensors to collect initial electromagnetic environment data around the ultra-shortwave physiotherapy host, and perform analog-to-digital conversion and preprocessing on the collected initial electromagnetic environment data; S2: Real-time acquisition of the patient's physiological parameters, including heart rate, body temperature, skin impedance and electromyography signals, and generation of the optimal combination of physiotherapy parameters based on the physiological parameters, including initial working frequency, initial output power, initial treatment time and initial radiation angle. S3: Based on the initial electromagnetic environment data and the optimal combination of physiotherapy parameters, the initial electromagnetic compatibility control parameters are determined by the adaptive electromagnetic compatibility control algorithm, including the initial filtering frequency band and attenuation coefficient of the adaptive filtering unit, the initial shielding aperture and radiation angle of the adjustable shielding unit, the initial operating frequency of the frequency adaptive adjustment unit, and the initial power compensation coefficient of the power adaptive compensation unit. S4: Based on the optimal combination of physiotherapy parameters and the initial electromagnetic compatibility control parameters, control the ultra-shortwave physiotherapy host to start working and begin ultra-shortwave physiotherapy, while monitoring electromagnetic environment data in real time and updating interference signal parameters; S5: Perform dynamic analysis on the real-time monitored electromagnetic environment data, compare the difference between the current electromagnetic environment data and the initial electromagnetic environment data, and determine whether the electromagnetic interference has changed. If the interference has not changed significantly, maintain the current parameters and continue the treatment. S6: Identify the type and divide the frequency band of interference signals in the real-time monitored electromagnetic environment data, determine the spatial location coordinates of the interference source, and isolate the interference source in a directional manner. S7: If the interference changes significantly, repeat the interference source location and isolation process of S6, and dynamically adjust the signal parameters and shielding structure according to the changed electromagnetic environment data, while optimizing and adjusting the combination of physiotherapy parameters in real time. S8: If abnormal host operating parameters or abnormal patient physiological signals are detected, the emergency protection mechanism will be triggered immediately to cut off the ultra-shortwave output, record the fault information, and display the fault prompt. S9: When the treatment time reaches the optimized preset time, control the ultra-shortwave therapy host to stop working, record the relevant data of this treatment, generate a treatment report and display it to the operator.

[0049] S5 specifically includes: By comparing the current electromagnetic environment data with the initial electromagnetic environment data, the electromagnetic environment difference coefficient is obtained. When the electromagnetic environment difference coefficient exceeds the set difference threshold, it is determined that the electromagnetic interference has changed significantly. Otherwise, it is determined that the electromagnetic interference has not changed significantly.

[0050] The formula for calculating the electromagnetic environment difference coefficient is as follows:

[0051] In the formula, This is represented by the electromagnetic environment difference coefficient; n represents the total amount of electromagnetic environment data. This represents the impact weight of the data class to which the i-th electromagnetic environment data belongs for interference analysis; This represents the current electromagnetic environment data value for the i-th electromagnetic environment data. This represents the initial electromagnetic environment data value for the i-th electromagnetic environment data.

[0052] Among them, the data categories to which electromagnetic environment data belongs include, but are not limited to, characteristic parameters of multi-band electromagnetic signals, electric field strength, magnetic field strength, and interference signals.

[0053] The impact weight of the electromagnetic environment data category for interference analysis is obtained by solving the matrix established by pairwise comparison and scoring using the analytic hierarchy process, and the values ​​are all (0, 1).

[0054] The difference threshold is set in advance based on a large amount of experimental data and analysis of actual application scenarios. For example, the threshold is set by statistical analysis of electromagnetic environment data of the normal operation and abnormality of the ultra-shortwave physiotherapy system under different levels of electromagnetic interference. For example, 0.5.

[0055] The beneficial effects of the above technical solution are as follows: by utilizing the electromagnetic environment data monitored in real time during operation, the electromagnetic interference changes can be dynamically analyzed, which can provide data basis for maintaining the stable operation of the current parameters or for locating and isolating repeated interference sources. This helps to ensure the continuity and stability of the treatment process, while enabling the ultra-shortwave physiotherapy system to quickly adapt to the changing electromagnetic environment and continuously provide effective and safe physiotherapy services.

[0056] S6 specifically includes: The interference signals in the real-time acquired electromagnetic interference data are identified by interference type and classified into low-frequency interference (<30MHz), ultra-shortwave band interference (30MHz-300MHz), and high-frequency interference (>300MHz). Based on the phase difference and amplitude difference of the interference signal, combined with the array layout information of the distributed electromagnetic sensors, a fusion positioning algorithm based on AOA and TDOA is adopted to determine the spatial coordinates of the interference source. The angle of arrival of the interference signal is calculated by the phase difference of the signals collected by each distributed electromagnetic sensor, and the time difference of arrival is calculated by the time difference of the signals collected by each sensor. Then, the Kalman filter algorithm is used to fuse the positioning results of the angle of arrival and the time difference of arrival to eliminate positioning errors and improve positioning accuracy. The positioning error does not exceed 5cm. Depending on the type, intensity, and location of the interference signal, the method of active cancellation, physical shielding, or a combination of both can be selected to isolate the interference source in a targeted manner. The system monitors the electromagnetic environment data after isolation in real time, compares the data with the data before isolation, calculates the isolation effect index, and adjusts the isolation parameters until the requirements are met if the isolation effect index does not reach the preset threshold.

[0057] By employing a spatial positioning unit and a fusion positioning algorithm based on AOA and TDOA, combined with a Kalman filter algorithm, high-precision spatial positioning of the interference source was achieved, with a positioning error of no more than 5cm. This precise determination of the spatial coordinates of the interference source provides a foundation for directional isolation. A directional isolation method combining active cancellation and physical shielding is adopted. Depending on the type and intensity of the interference signal, it can choose to generate a canceling magnetic field for active cancellation, adjust a flexible shielding barrier for physical shielding, or use a combination of both to achieve directional isolation of the interference source, avoiding the increased cost and lack of flexibility associated with monolithic shielding. For example, active cancellation can be used for high-frequency radio frequency interference; physical shielding can be used for low-frequency power frequency interference; and a combination of both can be used for strong interference, significantly improving the isolation effect while avoiding the increased cost and lack of flexibility associated with monolithic shielding.

[0058] S2 specifically includes: Collect the patient's physiotherapy-related information, including physiological parameters, treatment sites, medical history, and current physical condition. Physiological parameters include height, weight, age, heart rate, blood pressure, and skin resistance. Treatment sites include specific areas such as the neck, shoulders, waist, and joints. Medical history includes previous physiotherapy history, disease type, and allergy history. The collected patient physiotherapy-related information was analyzed to determine the patient's physiotherapy goals, appropriate physiotherapy intensity, and physiotherapy duration. The analysis process used a fuzzy comprehensive evaluation algorithm, combined with medical physiotherapy guidelines and clinical experience data, to quantitatively assess the patient's physiotherapy needs. A physiotherapy parameter database is constructed, which contains standard physiotherapy parameters corresponding to different patient types, different physiotherapy sites, and different physiotherapy goals. Based on the analysis results, an initial physiotherapy parameter combination is matched from the database. The initial physiotherapy parameter combination includes parameters such as ultra-shortwave output frequency, power, modulation mode, physiotherapy duration, and physiotherapy interval. By combining the output electromagnetic environment data and historical optimization data, the initial combination of physiotherapy parameters is optimized and adjusted. The optimization adopts a genetic algorithm with the dual optimization objectives of optimal physiotherapy effect and optimal electromagnetic compatibility. The constraints include patient tolerance threshold, electromagnetic radiation safety threshold, and equipment operating parameter threshold. The optimal combination of physiotherapy parameters is generated through selection, crossover, and mutation operations of the genetic algorithm.

[0059] Dynamically adjusting signal parameters and shielding structure, also includes When optimizing and adjusting the combination of physiotherapy parameters in real time, an incremental learning algorithm is used. By combining real-time electromagnetic environment data and patient physiological signal feedback during the physiotherapy process, the optimization model of the genetic algorithm is updated online to improve the real-time performance and accuracy of parameter optimization. When dynamically adjusting signal parameters, a predictive control algorithm is used to predict the characteristics of interference signals in the future based on the changing trends of real-time electromagnetic environment data, and adjust the signal parameters in advance to achieve the prediction and active avoidance of interference. When a new interference source is detected, the new interference source can be quickly located based on existing data collected by distributed electromagnetic sensors and historical interference source location data, shortening the location time of the new interference source to no more than 1 second.

[0060] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0061] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. An adaptive electromagnetically compatible ultra-shortwave physiotherapy system, characterized in that, include: The ultra-shortwave therapy host is used to generate ultra-shortwave signals with preset frequency and power, and radiate the ultra-shortwave signals to the diseased parts of the human body to achieve ultra-shortwave therapy; The electromagnetic environment sensing module is used to collect and preprocess the initial electromagnetic environment data around the ultra-shortwave physiotherapy host in real time using distributed electromagnetic sensors. The initial electromagnetic environment data includes characteristic parameters of multi-band electromagnetic signals, electric field strength, magnetic field strength, and interference signals. The collected data is then synchronized to the adaptive adjustment module and the positioning isolation module. The positioning and isolation module is used to extract features and identify the type of the collected interference signals. It determines the spatial location of the interference source based on the phase difference and amplitude difference of multiple sets of sensing data, and generates a targeted isolation magnetic field based on the location and type of the interference source. The adaptive adjustment module is used to dynamically adjust the signal output frequency, power, and signal modulation method of the ultra-shortwave physiotherapy host according to electromagnetic environment data and physiotherapy parameters, and to adaptively adjust the electromagnetic shielding structure. The physiotherapy parameter matching module is used to generate the optimal combination of physiotherapy parameters based on the patient's physiological parameters, physiotherapy sites, and medical history information, combined with historical physiotherapy data and electromagnetic compatibility optimization parameters. The safety monitoring module is used to monitor the operating status of the ultra-shortwave therapy host, the patient's physiological signals, and the safety threshold of the electromagnetic environment in real time. When an abnormality is detected, the protection mechanism is immediately triggered to cut off the ultra-shortwave output or adjust the operating parameters.

2. The adaptive electromagnetic compatibility ultra-shortwave physiotherapy system according to claim 1, characterized in that, The intelligent matching module includes: The physiotherapy needs analysis unit is used to collect and analyze patients' physiotherapy-related information to determine the patients' physiotherapy goals, appropriate physiotherapy intensity, and physiotherapy duration. The parameter matching unit is used to match the initial physiotherapy parameter combination from the database based on the analysis results. The initial physiotherapy parameter combination includes: ultra-shortwave output frequency, power, modulation mode, physiotherapy duration, and physiotherapy interval parameters. The parameter optimization unit is used to combine the output electromagnetic environment data and historical optimization data to optimize and adjust the initial combination of physiotherapy parameters, thereby generating the optimal combination of physiotherapy parameters.

3. The adaptive electromagnetic compatibility ultra-shortwave physiotherapy system according to claim 1, characterized in that, The adaptive adjustment module includes: An adaptive filtering unit is used to adjust the filtering frequency band and filtering attenuation coefficient in real time according to the frequency characteristics of the interference signal. Adjustable shielding unit, used to control the aperture size and shielding angle of the shielding mesh cover; The frequency adaptive adjustment unit is used to dynamically adjust the oscillation frequency of the high-frequency oscillation circuit within the standard operating frequency band of ultra-shortwave therapy. The power adaptive compensation unit is used to adjust the power amplification factor in real time according to the interference intensity to compensate for the energy loss of physiotherapy caused by interference.

4. The adaptive electromagnetic compatibility ultra-shortwave physiotherapy system according to claim 3, characterized in that, The adaptive filtering unit specifically includes: The multi-band electromagnetic signals in the electromagnetic environment data are preprocessed to obtain the target signal; After the target signal is normalized, it is converted using a variety of preset analysis algorithms to obtain several target frequency domain signals. The signal confidence level of the corresponding target frequency domain signal is obtained by the preset analysis algorithm; The interference frequency features of the target frequency domain signal are extracted and mean analysis is performed to obtain the feature mean. Calculate the feature difference ratio between the interference frequency characteristics of the target frequency domain signal and the corresponding feature mean, and determine the feature performance difference of the interference frequency characteristics of the current target frequency domain signal by combining the signal confidence of the corresponding preset analysis algorithm; When the difference in the characteristic performance is less than the set difference threshold of the corresponding interference frequency characteristic, a mark is added to the target frequency domain signal; The target frequency signal with the largest number of markers is determined as the reference frequency signal; Extract the interference frequency range of the reference frequency signal, and when there are multiple interference frequency ranges, extract the maximum and minimum values ​​of all interference frequency ranges to construct important interference frequency bands; When only one of the interference frequency ranges exists, the important interference frequency bands are determined based on the interference frequency range. The main interference frequency point of the reference frequency signal is taken as the target center frequency; When the important interference frequency band overlaps with the physiotherapy signal frequency band, or when the frequency band distance is less than the lower limit of the set distance threshold, the filtering frequency band is extended to cover the overlapping frequency band, or extended to cover the important interference frequency band. The adjusted filter frequency band is determined based on the target bandwidth and the target center frequency; When the frequency band distance between the important interference frequency band and the physiotherapy signal frequency band is greater than the upper limit of the set distance threshold, the adjusted filter frequency band is determined based on the target center frequency and the bandwidth of the current filter frequency band. Based on the amplitude of each frequency component of the reference frequency signal, the strength of the interference signal is evaluated to obtain the target signal strength; The target filter attenuation coefficient is obtained by filtering from the signal strength-filter attenuation coefficient mapping table using the target signal strength; When the important interference frequency band overlaps with the physiotherapy signal frequency band, the target filter attenuation coefficient is increased and then used as the filter attenuation coefficient for the overlapping frequency band. The target filter attenuation coefficient is used as the filter attenuation coefficient for the remaining frequency bands in the adjusted filter frequency band, excluding the overlapping frequency band. If the frequency band distance between the important interference frequency band and the physiotherapy signal frequency band is greater than the upper limit of the set distance threshold, the target filter attenuation coefficient is reduced as the filter attenuation coefficient of the adjusted filter frequency band.

5. The adaptive electromagnetic compatibility ultra-shortwave physiotherapy system according to claim 1, characterized in that, The security monitoring module specifically includes: Real-time monitoring of the working status parameters of the ultra-shortwave physiotherapy host, monitoring the patient's heart rate, respiratory rate, skin temperature and skin resistance signal during the physiotherapy process, as well as the electromagnetic radiation intensity around the ultra-shortwave physiotherapy host; When a parameter is detected to be outside the preset normal range, or when the patient's physiological signals are abnormal or the electromagnetic radiation intensity is abnormal, an early warning signal is immediately sent, and the power supply or signal output circuit of the ultra-shortwave therapy host is quickly cut off.

6. An interference-free operation control method, applied in the adaptive electromagnetic compatibility ultra-shortwave physiotherapy system as described in claim 4, characterized in that, Includes the following steps: S1: Use distributed electromagnetic sensors to collect initial electromagnetic environment data around the ultra-shortwave physiotherapy host, and perform analog-to-digital conversion and preprocessing on the collected initial electromagnetic environment data; S2: Real-time acquisition of the patient's physiological parameters, including heart rate, body temperature, skin impedance, and electromyography signals, and generation of the optimal combination of physical therapy parameters based on the physiological parameters; S3: Based on the initial electromagnetic environment data and the optimal combination of physiotherapy parameters, the initial electromagnetic compatibility control parameters are determined through an adaptive electromagnetic compatibility control algorithm; S4: Based on the optimal combination of physiotherapy parameters and the initial electromagnetic compatibility control parameters, control the ultra-shortwave physiotherapy host to start working and begin ultra-shortwave physiotherapy, while monitoring electromagnetic environment data in real time and updating interference signal parameters; S5: Perform dynamic analysis on the real-time monitored electromagnetic environment data, compare the difference between the current electromagnetic environment data and the initial electromagnetic environment data, and determine whether the electromagnetic interference has changed. If the interference has not changed significantly, maintain the current parameters and continue the treatment. S6: Identify the type and divide the frequency band of interference signals in the real-time monitored electromagnetic environment data, determine the spatial location coordinates of the interference source, and isolate the interference source in a directional manner. S7: If the interference changes significantly, repeat the interference source location and isolation process of S6, and dynamically adjust the signal parameters and shielding structure according to the changed electromagnetic environment data, while optimizing and adjusting the combination of physiotherapy parameters in real time. S8: If abnormal host operating parameters or abnormal patient physiological signals are detected, the emergency protection mechanism will be triggered immediately to cut off the ultra-shortwave output, record the fault information, and display the fault prompt. S9: When the treatment time reaches the optimized preset time, control the ultra-shortwave therapy host to stop working, record the relevant data of this treatment, generate a treatment report and display it to the operator.

7. The interference-free operation control method according to claim 5, characterized in that, S5 specifically includes: By comparing the current electromagnetic environment data with the initial electromagnetic environment data, the electromagnetic environment difference coefficient is obtained. When the electromagnetic environment difference coefficient exceeds the set difference threshold, it is determined that the electromagnetic interference has changed significantly. Otherwise, it is determined that the electromagnetic interference has not changed significantly.

8. The interference-free operation control method according to claim 5, characterized in that, S6 specifically includes: The interference signals in the real-time acquired electromagnetic interference data are identified by interference type and classified into low-frequency interference, ultra-shortwave band interference and high-frequency interference. Based on the phase difference and amplitude difference of the interference signal, combined with the array layout information of the distributed electromagnetic sensors, a fusion localization algorithm based on AOA and TDOA is used to determine the spatial coordinates of the interference source. Depending on the type, intensity, and location of the interference signal, the method of active cancellation, physical shielding, or a combination of both can be selected to isolate the interference source in a targeted manner. The system monitors the electromagnetic environment data after isolation in real time, compares the data with the data before isolation, calculates the isolation effect index, and adjusts the isolation parameters until the requirements are met if the isolation effect index does not reach the preset threshold.

9. The interference-free operation control method according to claim 5, characterized in that, S2 specifically includes: Collect patients' physiotherapy-related information, including physiological parameters, physiotherapy sites, medical history, and current physical condition; The collected patient physiotherapy-related information is analyzed to determine the patient's physiotherapy goals, appropriate physiotherapy intensity, and physiotherapy duration; Construct a physiotherapy parameter database, and match the initial physiotherapy parameter combination from the database based on the analysis results; By combining the output electromagnetic environment data and historical optimization data, the initial combination of physiotherapy parameters is optimized and adjusted to generate the optimal combination of physiotherapy parameters.

10. The interference-free operation control method according to claim 5, characterized in that, The dynamically adjusted signal parameters and shielding structure also include When optimizing and adjusting the combination of physiotherapy parameters in real time, an incremental learning algorithm is used to update the optimization model of the genetic algorithm online by combining real-time electromagnetic environment data and patient physiological signal feedback during the physiotherapy process. When dynamically adjusting signal parameters, a predictive control algorithm is used to predict the characteristics of interference signals in the future based on the changing trends of real-time electromagnetic environment data, and adjust the signal parameters in advance. When a new source of interference is detected, the new source of interference can be quickly located based on existing data collected by distributed electromagnetic sensors and historical interference source location data.

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