A multi-probe radio frequency distributed lung water monitoring system and method

Abstract

The present application relates to the technical field of data processing, and discloses a multi-probe radio frequency distributed lung water monitoring system and method, which comprises the following steps: collecting low, high and guard frequency transmission parameters and converting them into a logarithmic domain by deploying a thoracic radio frequency array; fitting a rib quasi-periodic model based on a guard frequency scan to obtain a rib arch trend and a synthetic pitch; estimating effective wavelengths in tissues corresponding to low and high frequencies; obtaining window consistency weights in combination with geometric and wavelength parameters, generating a standard complex response by weighted and normalized logarithmic parameters; performing self-spectrum analysis on the complex response to extract respiratory and heart motion angular frequencies, performing orthogonal projection based on sine and cosine and direct current of the respiratory and heart motion angular frequencies to obtain a modulated slow-varying complex response; taking an initial breath holding as a baseline to construct a complex difference of high and low frequency complex responses, and projecting real and imaginary parts of the complex difference into a two-dimensional vector to generate a lung water index.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, more particularly, it relates to a multi-probe radio frequency distributed lung water monitoring system and method. BACKGROUND

[0002] In recent years, non-invasive monitoring methods based on radio frequency electromagnetic waves have been gradually applied to the dynamic monitoring of lung liquid content. Compared with traditional imaging methods, radio frequency measurement has the advantages of real-time, wearable and no radiation, and therefore has wide application prospects in intensive care, management of cardiogenic edema and prevention and control of postoperative complications. In order to improve the spatial resolution and stability, researchers usually arrange multiple radio frequency probes around the chest, and estimate the lung water level through the amplitude and phase changes of the cross-probe signals.

[0003] However, in practical application, the measurement signal is not only related to the lung water content, but also significantly affected by the chest wall tissue structure. The bony components (ribs) of the chest wall are greatly different from soft tissues, muscles and lung parenchyma in terms of dielectric constant and conductivity. When the radio frequency signal passes through the chest wall, it will encounter a strong discontinuous boundary, resulting in scattering, reflection and attenuation effects. These effects are not uniformly distributed in space, but are limited to the periodic arrangement of ribs and intercostal spaces. Further, at certain frequencies, radio frequency waves are more likely to penetrate intercostal spaces along a specific angle, while being greatly attenuated when directly opposite the ribs. This causes the sensitivity between probe channels to have a directional difference.

[0004] When the probe array is fixed to the body surface, the relationship between its direction and the arrangement of the ribs directly determines whether the radio frequency signal can smoothly penetrate to the lung tissue. If some channels are aligned with the intercostal space, a small change in lung water can produce a significant electromagnetic response; on the contrary, if the channel is directly opposite the ribs, its perception of lung water changes will be severely weakened. More complexly, when the patient's body position is adjusted or the chest wall moves, causing a slight shift in the relative direction of the probe and the ribs, the originally sensitive channel may suddenly become insensitive, and the originally insensitive channel may suddenly become enhanced. This makes it difficult to maintain consistency in monitoring results at different time points, and weakens the reliability of the radio frequency distributed method in clinical monitoring. SUMMARY

[0005] The present application provides a multi-probe radio frequency distributed lung water monitoring system and method, which solves the technical problems raised in the background art.

[0006] In a first aspect, the present application provides a multi-probe radio frequency distributed lung water monitoring method, comprising:

[0007] Arranging a radio frequency array around the chest, acquiring transmission parameters in a low frequency working frequency band, a high frequency working frequency band and a guard frequency working frequency band, and converting the transmission parameters into a logarithmic domain to form logarithmic transmission parameters;

[0008] Based on the guard band, shallow high-frequency spatial spectrum scanning is performed, a quasi-periodic lattice model of the rib and the intercostal space is fitted, a rib arch direction unit vector and a combined pitch of the rib and the intercostal space are obtained;

[0009] The effective wavelength in the tissue corresponding to the low-frequency working frequency band and the high-frequency working frequency band is determined;

[0010] According to the rib arch direction unit vector, the combined pitch of the rib and the intercostal space, and the effective wavelength in the tissue, a window consistency weight is determined; and the logarithmic transmission parameters are weighted and summed and normalized with the window consistency weight to obtain a standard complex response;

[0011] The standard complex response is subjected to a self-spectrum analysis, and a respiratory angular frequency and a heart angular frequency are extracted; a linear orthogonal projection is performed on the respiratory angular frequency and the heart angular frequency with a direct current component as a basis vector to obtain a demodulation slow-varying complex response;

[0012] Taking an initial breath-hold time as a baseline, a complex difference of the demodulation slow-varying complex responses of the low-frequency working frequency band and the high-frequency working frequency band is constructed, the real part and the imaginary part of the complex difference are taken as a two-dimensional vector, and a lung water index is generated by projecting the two-dimensional vector.

[0013] Further, the transmission parameters are collected in the low-frequency working frequency band, the high-frequency working frequency band and the guard band, and the transmission parameters are converted into the logarithmic domain to form logarithmic transmission parameters, including:

[0014] The low-frequency working frequency band is 0.6 GHz to 0.8 GHz, the high-frequency working frequency band is 1.2 GHz to 1.5 GHz, and the guard band is 2.0 GHz to 2.5 GHz;

[0015] The transmission parameters of the time t in the frequency band are collected at a fixed time interval, the amplitude and the phase of the transmission parameters are obtained, and the frequency band represents the low-frequency working frequency band, the high-frequency working frequency band or the guard band;

[0016] The transmission parameters are converted into the logarithmic domain according to the amplitude and the phase of the transmission parameters, as follows:

[0017]

[0018] wherein, represents the logarithmic transmission parameter, represents an imaginary unit, .

[0019] Further, based on the guard band, a shallow high-frequency spatial spectrum scanning is performed, and by fitting a quasi-periodic lattice model of the ribs and intercostal spaces, a rib arch direction unit vector and a synthetic pitch of the ribs and intercostal spaces are obtained, including:

[0020] In a first preset time period, a logarithmic transmission parameter of each frequency in the guard band is determined at a fixed time interval, and a variance of the logarithmic transmission parameter of the corresponding frequency is calculated; the frequency corresponding to the maximum logarithmic transmission parameter variance is taken as a scanning frequency point;

[0021] In a second preset time period, the M scanning probes are controlled to collect the logarithmic transmission parameter according to the scanning frequency point, and an average value of each logarithmic transmission parameter is calculated ;

[0022] A one-dimensional mapping is set to determine a one-dimensional coordinate of the mth scanning probe ; wherein, ; wherein, represents the origin coordinate of the one-dimensional coordinate system, represents the coordinate of the mth scanning probe, represents an initial rib arch direction unit vector, represents an angle between the one-dimensional mapping and the horizontal direction;

[0023] Based on the average value of the logarithmic transmission parameter of each scanning probe and the one-dimensional coordinate, fitting is performed as follows:

[0024]

[0025] wherein, represents a constant term of the quasi-periodic lattice model, represents an amplitude coefficient of the quasi-periodic lattice model, represents a phase coefficient of the quasi-periodic lattice model, represents a synthetic pitch of the initial ribs and intercostal spaces;

[0026] The initial synthetic pitch of the ribs and intercostal spaces and the quasi-periodic lattice model corresponding to the initial rib arch direction unit vector are calculated, as follows:

[0027]

[0028] wherein, represents a fitting value of the quasi-periodic lattice model to the average value of the logarithmic transmission parameter of the mth scanning probe, represents the average value of the logarithmic transmission parameter of all scanning probes in the second preset time period;

[0029] Along the direction that maximizes the explained variance, the corresponding initial synthetic pitch of the ribs and intercostal spaces and the initial rib arch direction unit vector are taken as the synthetic pitch of the ribs and intercostal spaces and a rib arch direction unit vector .

[0030] Further, the effective wavelength in tissue corresponding to the low-frequency operating frequency band and the high-frequency operating frequency band is determined, including:

[0031] The interval distance of the transmission channel from the mth scanning probe to the transmitting probe is determined ;

[0032] The patient to be monitored is controlled to suspend breathing for at least 10 seconds, and the transmission channel corresponding phase is collected at fixed time intervals to calculate the average phase, and the average phase is phase unfolded to obtain the corresponding unfolded phase ;

[0033] The angle between the transmission channel and the rib arch direction unit vector is determined , and the angle is used to calculate the corresponding direction smoothing weight ;

[0034] The unfolded phase and the baseline length are fitted by weighted least squares, as follows:

[0035]

[0036] wherein, represents the slope to be fitted;

[0037] The corresponding slope to be fitted is taken as the target slope along the direction that minimizes the weighted least squares fitting value;

[0038] The effective wavelength in tissue is calculated according to the target slope, including:

[0039]

[0040] wherein, represents the effective wavelength in tissue, belongs to the low-frequency operating frequency band or the high-frequency operating frequency band, represents the target slope.

[0041] Further, the window consistency weight is determined according to the rib arch direction unit vector, the combined pitch of the ribs and intercostal spaces, and the effective wavelength in tissue, including:

[0042] The combined pitch of the ribs and intercostal spaces is projected to the angle between the transmission channel and the rib arch direction unit vector to calculate the equivalent pitch of the transmission channel ;

[0043] Based on the equivalent pitch and the effective wavelength in tissue, the corresponding matching residual is calculated, as follows:​

[0044]

[0045] wherein, denotes the projection factor, denotes the matching residual of the transmission channel;

[0046] extracting the matching residual of each transmission channel to determine the median of the matching residuals; taking the product of the median of the matching residuals and a normal distribution constant as the frequency corresponding robust scale ;

[0047] calculating the window consistency weight of the transmission channel at the frequency f according to the robust scale and the matching residual:

[0048]

[0049] wherein, denotes the window consistency weight of the transmission channel at the frequency f.

[0050] Further, the logarithmic transmission parameters are weighted and summed with the window consistency weight and normalized to obtain the standard complex response, including:

[0051] determining the window consistency weight of each logarithmic transmission parameter, calculating the product of the logarithmic transmission parameter and the corresponding window consistency weight as the weighted composite complex;

[0052] accumulating the window consistency weights of all transmission channels to obtain the window composite weight;

[0053] taking the ratio of the weighted composite complex and the window composite weight as the standard complex response.

[0054] Further, the standard complex response is subjected to a spectral analysis to extract the respiratory angular frequency and the cardiac angular frequency, including:

[0055] performing a discrete Fourier transform on the standard complex response to obtain an estimated spectrum;

[0056] calculating a combined composite weight of the window composite weight corresponding to the low-frequency working frequency band and the window composite weight corresponding to the high-frequency working frequency band; determining the working frequency band corresponding to the standard complex response, and taking the ratio of the window composite weight corresponding to the working frequency band and the combined composite weight as the inter-frequency combination weight coefficient;

[0057] taking the product of the inter-frequency combination weight coefficient and the estimated spectrum as the joint spectrum;

[0058] extracting the maximum value and the minimum value in the joint spectrum, and calculating the respiratory angular frequency and cardiac angular frequency .

[0059] Further, linear orthogonal projection is performed on the positive and negative sine functions and the direct current component of the respiratory angular frequency and the cardiac angular frequency to obtain a demodulated slow-varying complex response, including:

[0060] Constructing a negative response sequence from N standard complex responses at different times ;

[0061] Constructing a base matrix , as follows:

[0062]

[0063] Constructing a projection sequence from the base matrix ;

[0064] Mapping the projection sequence to a demodulated slow-varying complex response sequence ; wherein, .

[0065] Further, taking the initial breath-holding time as a baseline, a complex difference of the demodulated slow-varying complex responses in the low-frequency working frequency band and the high-frequency working frequency band is constructed, and the real part and the imaginary part of the complex difference are taken as a two-dimensional vector, and a lung water index is generated by two-dimensional vector projection, including:

[0066] Determining the demodulated slow-varying complex response sequence in the low-frequency working frequency band and the demodulated slow-varying complex response sequence in the high-frequency working frequency band, respectively, and determining the starting time of breath-holding of the patient to be monitored ;

[0067] Constructing a complex difference at the tth time , including:

[0068]

[0069] wherein, represents the demodulated slow-varying complex response in the high-frequency working frequency band at the tth time, represents the demodulated slow-varying complex response in the low-frequency working frequency band at the tth time, represents the demodulated slow-varying complex response in the high-frequency working frequency band at the starting time, represents the demodulated slow-varying complex response in the low-frequency working frequency band at the starting time,

[0070] Complexly decomposing the complex difference to obtain a two-dimensional vector ; wherein, ​​​​representing a complex difference of a real part, representing a complex difference of an imaginary part;

[0071] a mean vector of the two-dimensional vectors at N time points , the two-dimensional vectors at each time point are de-meaned to obtain a zero-mean sequence , and a two-dimensional covariance matrix is estimated from the zero-mean sequence ;

[0072] The two-dimensional covariance matrix is subjected to eigenvalue decomposition processing to obtain the maximum eigenvalue, and the unit eigenvector corresponding to the maximum eigenvalue is determined ;

[0073] The lung water index at time t is calculated .

[0074] In the second aspect, a multi-probe radio frequency distributed lung water monitoring system is applied to any one of the multi-probe radio frequency distributed lung water monitoring methods, comprising:

[0075] The logarithmic parameter acquisition module is used for arranging a radio frequency array around the thoracic cage, collecting transmission parameters in a low-frequency working frequency band, a high-frequency working frequency band and a guard frequency working frequency band, and converting the transmission parameters into a logarithmic domain to form logarithmic transmission parameters;

[0076] The rib arch scanning module is used for shallow high-frequency spatial spectrum scanning based on the guard frequency working frequency band, fitting a quasi-periodic lattice model of ribs and intercostal spaces, and obtaining a rib arch direction unit vector and a combined pitch of ribs and intercostal spaces;

[0077] The wavelength determination module is used for determining effective wavelengths in tissues corresponding to the low-frequency working frequency band and the high-frequency working frequency band;

[0078] The standard complex response module is used for determining window consistency weights according to the rib arch direction unit vector, the combined pitch of ribs and intercostal spaces and the effective wavelengths in tissues, and performing weighted summation and normalization processing on the logarithmic transmission parameters with the window consistency weights to obtain a standard complex response;

[0079] The demodulation response module is used for performing spectral analysis on the standard complex response, extracting a respiratory angular frequency and a cardiac angular frequency, and performing linear orthogonal projection with the sine and cosine functions of the respiratory angular frequency and the cardiac angular frequency and a direct current component as basis vectors to obtain a demodulation slow-varying complex response;

[0080] The lung water index module is used for taking an initial breath-holding time as a baseline, constructing a complex difference of the demodulation slow-varying complex responses of the low-frequency working frequency band and the high-frequency working frequency band, taking a real part and an imaginary part of the complex difference as a two-dimensional vector, and generating a lung water index by two-dimensional vector projection.

[0081] The beneficial effects of the present application are that by arranging a multi-probe radio frequency array around the thoracic cavity, combining a guard frequency scan to fit a quasi-periodic model of ribs and intercostal spaces, effective wavelength estimation in tissue and window consistency weighting processing, the directional interference caused by the bony structure of the chest wall can be significantly weakened, and the unified representation of cross-band complex response is realized; on this basis, the respiratory and cardiac components are effectively separated through self-spectrum analysis and orthogonal projection, and the lung water index is constructed by the difference between low and high frequency complex responses, thereby improving the stability and comparability of the monitoring results at different body positions and different time points under the premise of non-invasiveness, real-time and non-radiation, and significantly enhancing the sensitivity and reliability of lung water monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0082] Figure 1 is a flow chart of a multi-probe radio frequency distributed lung water monitoring method of the present application;

[0083] Figure 2 is a module diagram of a multi-probe radio frequency distributed lung water monitoring system of the present application. DETAILED DESCRIPTION

[0084] The subject matter described herein will now be discussed with reference to example implementations. It should be understood that the discussion of these implementations is merely meant to provide a better understanding of the subject matter described herein and can be changed in function and arrangement without departing from the scope of the present description. Each of the various examples can omit, substitute or add various procedures or components as desired. Additionally, features described in relation to some examples can also be combined in other examples.

[0085] Example One:

[0086] As shown in Figure 1 , a multi-probe radio frequency distributed lung water monitoring method comprises:

[0087] Arranging a radio frequency array around the thoracic cavity, acquiring transmission parameters in a low frequency working frequency band, a high frequency working frequency band and a guard frequency working frequency band, and converting the transmission parameters into a logarithmic domain to form logarithmic transmission parameters;

[0088] Performing a shallow layer high frequency spatial spectrum scan based on the guard frequency working frequency band, obtaining a rib arch direction unit vector and a synthesized pitch of ribs and intercostal spaces by fitting a quasi-periodic lattice model of ribs and intercostal spaces;

[0089] Determining the effective wavelength in tissue corresponding to the low frequency working frequency band and the high frequency working frequency band;

[0090] The window consistency weight is determined according to the rib arch direction unit vector, the synthetic pitch of the rib and the intercostal space and the effective wavelength in the tissue; and the logarithmic transmission parameters are weighted and summed and normalized by the window consistency weight to obtain the standard complex response;

[0091] The standard complex response is subjected to self-spectrum analysis to extract the respiratory angular frequency and the heart beat angular frequency; the linear orthogonal projection is performed by taking the sine and cosine functions of the respiratory angular frequency and the heart beat angular frequency and the direct current component as the basis vectors to obtain the demodulation slow-varying complex response;

[0092] The complex difference of the demodulation slow-varying complex responses of the low-frequency working band and the high-frequency working band is constructed with the initial breath-holding time as the baseline; the real part and the imaginary part of the complex difference are taken as two-dimensional vectors to generate the lung water index by two-dimensional vector projection.

[0093] It should be noted that the present application aims to solve the problem of signal sensitivity fluctuation caused by the quasi-periodic structure of the chest wall ribs and the intercostal space in the traditional radio frequency monitoring, and to realize reliable lung water dynamic monitoring across time periods and body positions, as follows:

[0094] A radio frequency probe array is arranged around the thorax to collect the transmission parameters (amplitude and phase) of the radio frequency signals in the low frequency (0.6 to 0.8 GHz), high frequency (1.2 to 1.5 GHz) and guard frequency (2.0 to 2.5 GHz) bands, and convert them into complex numbers in the logarithmic domain.

[0095] The quasi-periodic lattice model of the ribs and the intercostal space is fitted by shallow layer scanning with the guard frequency to accurately obtain the rib arch direction and the synthetic pitch of the ribs and the intercostal space.

[0096] The effective wavelength of the radio frequency signal in the human tissue is calculated in situ for the low-frequency and high-frequency working bands, which together with the periodic structure of the ribs and the intercostal space determines the penetration characteristics of the signal.

[0097] Based on the rib arch direction, the synthetic pitch and the wavelength in the tissue, the window consistency weight is calculated, that is, higher weight is given to those channels that match well with the periodic structure of the thorax, the signal is aggregated by weighted normalization to obtain the standard complex response, and the channel sensitivity mutation problem caused by body position change is eliminated.

[0098] The standard complex response is subjected to frequency spectrum analysis to extract the characteristic frequencies of respiration and heartbeat, and the linear orthogonal projection is performed to remove the interference of the two high-frequency physiological motions and retain the demodulation slow-varying complex response related to the lung water slow variation.

[0099] The complex difference of the low-frequency and high-frequency demodulation complex responses is calculated with the initial breath-holding time as the baseline; the real part and the imaginary part of the difference are taken as two-dimensional vectors to extract the main change direction by projection to generate the dimensionless lung water index, which quantitatively reflects the lung water dynamic change.

[0100] In summary, the present application realizes stable and reliable monitoring of lung water changes by sensing the periodic structure of the thorax, dynamically correcting signal weights, and stripping physiological interference, thereby facilitating doctors to conduct medical inquiries.

[0101] It should be noted that the transmission parameter represents the physical quantity related to the signal propagation characteristics detected by the receiving probe after the radio frequency signal passes through the thoracic tissue, specifically including amplitude and phase.

[0102] The amplitude represents the intensity of the radio frequency signal after passing through the thorax (including ribs, intercostal spaces, lung tissue, etc.) in the transmission channel from the transmitting probe to the receiving probe at time t and frequency f, reflecting the degree of signal attenuation in the propagation process (affected by tissue water content, density, etc.).

[0103] The phase represents the phase shift of the radio frequency signal after passing through the thorax at time t and frequency f, reflecting the path length and medium property (dielectric constant) changes of the signal in the tissue.

[0104] In an embodiment of the present application, transmission parameters are collected in the low-frequency operating frequency band, the high-frequency operating frequency band, and the guard frequency operating frequency band, and the transmission parameters are converted into the logarithmic domain to form logarithmic transmission parameters, including:

[0105] The low-frequency operating frequency band is 0.6GHz to 0.8GHz, the high-frequency operating frequency band is 1.2GHz to 1.5GHz, and the guard frequency operating frequency band is 2.0GHz to 2.5GHz;

[0106] It should be noted that the low-frequency operating frequency band is 0.6GHz to 0.8GHz, the high-frequency operating frequency band is 1.2GHz to 1.5GHz, and the radio frequency signals in these two frequency bands are closely related to the changes in lung water content in human tissue, which are the core frequency bands reflecting lung water status. The guard frequency operating frequency band is 2.0GHz to 2.5GHz, and the signal penetration depth of this frequency band is shallower, and the sensitivity to the bony structure of the chest wall is higher, which is the core frequency band reflecting the thoracic structure.

[0107] The amplitude and phase of the transmission parameter at time t in the frequency band are collected at a fixed time interval, and the frequency band represents the low-frequency operating frequency band, the high-frequency operating frequency band, or the guard frequency operating frequency band.

[0108] In detail, the system continuously collects signals at fixed time intervals to obtain the transmission parameters of each transmission channel in the three frequency bands at each time t. The transmission parameters include the amplitude, which reflects the intensity of the radio frequency signal after passing through the chest tissue (including ribs, intercostal space, lung tissue, etc.), and the change is related to the attenuation degree of the signal in the tissue; and the phase, which reflects the phase shift in the signal propagation process, and the change is related to the propagation path of the signal in the tissue and the medium characteristics (dielectric constant).

[0109] The transmission parameters are converted into a logarithmic domain according to the amplitude and phase of the transmission parameters, as follows:

[0110]

[0111] wherein, represents the logarithmic transmission parameter, represents the imaginary unit, .

[0112] In detail, the conversion formula is .

[0113] wherein is the converted logarithmic transmission parameter, which is a complex number. The real part is obtained by converting the amplitude of the transmission parameter by the natural logarithm, and this processing can convert the nonlinear attenuation characteristics of the signal into a linear form, which is convenient for subsequent superposition and weighting operation; the imaginary part is directly composed of the phase of the transmission parameter , is the imaginary unit and , used to distinguish the real part and the imaginary part. Through the conversion, the originally separated amplitude and phase information are integrated into a unified complex form.

[0114] In an embodiment of the present application, shallow high-frequency spatial spectrum scanning is performed based on the guard band working frequency band, and a quasi-periodic lattice model of ribs and intercostal spaces is fitted to obtain a rib arch direction unit vector and a synthetic pitch of ribs and intercostal spaces, including:

[0115] In the first preset time period, the logarithmic transmission parameters of each frequency in the guard band working frequency band are determined at fixed time intervals, and the logarithmic transmission parameter variance of the corresponding frequency is calculated; the frequency corresponding to the maximum logarithmic transmission parameter variance is taken as the scanning frequency point;

[0116] In detail, within the first preset time period, the system collects the logarithmic transmission parameters of each frequency within the operating frequency band of the chest wall at fixed time intervals. Because the operating frequency band of the chest wall is highly sensitive to the bony structures of the chest wall, and the quasi-periodic arrangement of the ribs and intercostal spaces causes differential fluctuations in the logarithmic transmission parameters at different frequencies, the greater the fluctuation, the more the frequency reflects the periodic structural characteristics. By calculating the variance of the logarithmic transmission parameters corresponding to each frequency, the frequency with the largest variance indicates that its signal is most significantly affected by the periodicity of the ribs and intercostal spaces; therefore, this frequency is selected as the scanning frequency.

[0117] During the second preset time period, M scanning probes are controlled to collect logarithmic transmission parameters according to the scanning frequency, and the average value of each logarithmic transmission parameter is calculated. ;

[0118] In detail, within the second preset time period, the system controls M scanning probes to continuously acquire logarithmic transmission parameters at selected scanning frequencies. Since a single acquisition may be affected by noise interference, by calculating the average value of the logarithmic transmission parameters of each scanning probe, the influence of random noise can be reduced, resulting in a more stable signal basis characterizing the thoracic structure, namely the average value of the logarithmic transmission parameters of each scanning probe.

[0119] Define a one-dimensional mapping to determine the one-dimensional coordinates of the m-th scanning probe. ;in, ;in, This represents the coordinates of the origin of a one-dimensional coordinate system. This represents the coordinates of the m-th scanning probe. This represents the initial rib arch orientation unit vector. This represents the angle between the one-dimensional mapping and the horizontal direction;

[0120] In detail, to simplify the analysis of the periodicity of the ribs and intercostal spaces, it is necessary to map the two-dimensional probe coordinates to a one-dimensional space. The origin coordinates of the one-dimensional coordinate system are set as follows: The coordinates of the m-th scanning probe are The initial rib arch orientation unit vector is ( (The angle between the vector and the horizontal direction). This is achieved through vector dot product. The one-dimensional coordinates of the m-th scanning probe in the initial rib arch orientation direction are obtained. This mapping transforms the periodic distribution along the rib arch in two-dimensional space into a periodic distribution on a one-dimensional line.

[0121] The fitting is performed based on the average value of the logarithmic transmission parameters of each scanning probe and the one-dimensional coordinates, as follows:

[0122]

[0123] in, a constant term of the quasi-periodic lattice model, an amplitude coefficient of the quasi-periodic lattice model, a phase coefficient of the quasi-periodic lattice model, represents the initial rib and intercostal combined pitch;

[0124] In detail, the logarithmic transmission parameter average value A m and its corresponding one-dimensional coordinate s m is fitted by using a periodic function, and the fitting model is . Wherein is a constant term of the model, reflecting the overall baseline level of the signal; and are the coefficients of the cosine term and the sine term respectively, which together reflect the amplitude and phase of the periodic fluctuation; is the initial rib and intercostal combined pitch, that is, the periodic length of the sum of the rib width and the intercostal gap width. The model simulates the modulation effect of the quasi-periodic structure formed by the alternating arrangement of ribs and intercostal gaps on the signal by using a trigonometric function.

[0125] The explained variance of the quasi-periodic lattice model corresponding to the initial rib and intercostal combined pitch and the initial rib arch direction unit vector is calculated as follows:

[0126]

[0127] Wherein, represents the fitting value of the quasi-periodic lattice model for the average value of the logarithmic transmission parameter of the mth scanning probe, represents the average value of the logarithmic transmission parameter of all scanning probes within the second preset time period;

[0128] In detail, to evaluate the fitting effect of the model, the explained variance needs to be calculated, and the calculation formula is . Wherein the numerator is the sum of the squares of the difference between the actual logarithmic transmission parameter average value A of each scanning probe and the model fitting value , reflecting the signal fluctuation that is not explained by the model; the denominator is the sum of the squares of the difference between each and the average value of all probes , reflecting the total fluctuation of the signal. The closer the explained variance is to 1, the stronger the model's ability to explain the signal fluctuation, that is, the closer the assumed initial combined pitch p and the initial rib arch direction unit vector to the actual thoracic structure.

[0129] Along the direction that maximizes the explained variance, the corresponding initial rib and intercostal combined pitch and the initial rib arch direction unit vector are taken as the rib and intercostal combined pitch and the rib arch direction unit vector .

[0130] It should be noted that by traversing different initial synthetic pitch p and initial rib arch direction unit vector (i.e. changing value), the corresponding explained variance is calculated, and the and that make the explained variance maximum are selected as the synthetic pitch of the rib and the intercostal gap and the rib arch direction unit vector respectively. Thus, through data-driven optimization, the obtained parameters can accurately reflect the quasi-periodic arrangement characteristics of the ribs and intercostal gaps.

[0131] In an embodiment of the present application, the effective wavelength in the tissue corresponding to the low-frequency working frequency band and the high-frequency working frequency band is determined, comprising:

[0132] determining the interval distance of the transmission channel from the mth scanning probe to the transmitting probe;

[0133] controlling the patient to be monitored to suspend breathing for at least 10 seconds, and collecting the phase corresponding to the transmission channel at fixed time intervals to calculate the average phase and perform phase unwrapping processing on the average phase to obtain the unwrapped phase ;

[0134] In detail, the patient to be monitored is controlled to suspend breathing for at least 10 seconds, so as to eliminate the interference of the chest fluctuation caused by the respiratory motion on the signal propagation path and ensure the stability of the phase measurement. During this period, the phase corresponding to the transmission channel is collected at fixed time intervals, and the average phase is calculated to reduce the influence of random noise. Since the phase measurement is usually limited to the range of -π to π, the average phase needs to be unwrapped to obtain the continuous unwrapped phase, which truly reflects the cumulative phase shift in the signal propagation process.

[0135] determining the included angle between the transmission channel and the rib arch direction unit vector, and calculating the corresponding direction smoothing weight with the included angle ;

[0136] In detail, the included angle between the transmission channel and the rib arch direction unit vector is determined, which reflects the relative relationship between the channel direction and the rib arrangement direction. Based on the included angle, the corresponding direction smoothing weight is calculated, and the weight formula is When the channel and the rib arch direction have a large included angle, The smaller the value, the greater the weight, which means that the channel in this direction is less affected by rib shielding, and the phase data is more stable; otherwise, the weight is smaller, thereby realizing differentiated weighting of channel data in different directions.

[0137] The unwrapped phase is fitted with the baseline length by weighted least squares, as follows:

[0138]

[0139] wherein, represents the slope to be fitted;

[0140] In detail, the relationship between the unwrapped phase and the baseline length is fitted by the weighted least squares method, and the fitting target is to minimize wherein, is the unwrapped phase, is the channel spacing distance, is the slope to be fitted. The slope to be fitted reflects the phase change rate corresponding to a unit distance, and the weighted processing makes the fitting process more focused on the channel data with high weight (i.e., less affected by interference), thereby obtaining a more accurate slope.

[0141] The corresponding slope to be fitted along the direction that minimizes the weighted least squares fitting value is taken as the target slope;

[0142] The effective wavelength in the tissue is calculated according to the target slope, including:

[0143]

[0144] wherein, represents the effective wavelength in the tissue, belongs to the low-frequency working frequency band or the high-frequency working frequency band, represents the target slope.

[0145] It should be noted that the corresponding slope to be fitted along the direction that minimizes the weighted least squares fitting value is taken as the target slope. According to the physical relationship between the wave number and the wavelength, the wave number (phase change per unit length) and the wavelength are inversely related (wave number = 2π / λ), so the effective wavelength in the tissue can be calculated by wherein, belongs to the low-frequency working frequency band or the high-frequency working frequency band, is the frequency of the downlink radio frequency signal in the human tissue.

[0146] In an embodiment of the present application, the window consistency weight is determined according to the rib arch direction unit vector, the combined pitch of the ribs and the intercostal space, and the effective wavelength in the tissue, including:

[0147] The synthetic pitch of the ribs and the intercostal space is projected to the angle between the transmission channel and the unit vector of the rib arch direction to calculate the equivalent pitch of the transmission channel ;

[0148] In detail, the synthetic pitch of the ribs and the intercostal space is used to reflect the periodicity of the thoracic cavity, but the direction of the transmission channel may have an angle with the rib arch direction, so the synthetic pitch needs to be projected to the channel direction to obtain the effective periodicity length. Specifically, the equivalent pitch is calculated by the angle between the transmission channel and the unit vector of the rib arch direction, and the equivalent pitch is the product of the synthetic pitch and the cosine value of the angle, that is, the equivalent pitch reflects the actual periodic length of the ribs and the intercostal space arranged alternately in the channel direction.

[0149] Based on the equivalent pitch and the effective wavelength in the tissue, the corresponding matching residual is calculated as follows:

[0150]

[0151] wherein, n represents the projection multiple, the matching residual of the transmission channel;

[0152] In detail, the matching residual is used to measure the matching degree of the effective wavelength in the tissue and the equivalent pitch, and the calculation formula is the minimum value of the absolute value of the difference between the effective wavelength and the n times equivalent pitch when the projection multiple n is 1 and 2. This is because when the wavelength of the radio frequency signal is close to the 1st or 2nd order period (i.e. the pitch itself or twice the pitch) of the periodic structure of the thoracic cavity, a significant periodic modulation effect will be produced, and the smaller the residual is, the higher the matching degree is, and the more stable the sensitivity of the channel to lung water change is.

[0153] The matching residual of each transmission channel is extracted to determine the median of the matching residual; the product of the median of the matching residual and the normal distribution constant is taken as the frequency The corresponding robust scale ;

[0154] In detail, the robust scale is used to standardize the matching residual to eliminate the influence of individual differences or noise on the weight calculation. Specifically, by extracting the matching residual of all transmission channels, the median is calculated, and then the median is multiplied by the normal distribution constant (usually 1.4826, which is used to convert the absolute deviation of the median to a robust scale estimate), and the result obtained is the robust scale at the frequency, which reflects the overall distribution characteristics of the residual.

[0155] According to the robust scale and the matching residual, the window consistency weight of the transmission channel at the frequency f is calculated:

[0156]

[0157] wherein, the transmission channel Window consistency weight at frequency f.

[0158] It should be noted that the window consistency weight is determined by matching the relationship between the residual and the robust scale, and the formula is When the matching residual is smaller (i.e. the wavelength and the equivalent pitch match better), the weight is closer to 1, indicating that the channel is stably modulated by the periodic structure of the thorax, and the response to the change in lung water is more reliable; on the contrary, the smaller the weight, the lower the matching degree of the channel and the periodic structure, and the poorer the response stability, and the weight can be used to differentially weight the signals of different channels.

[0159] In an embodiment of the present application, the window consistency weight is used to weight and sum the logarithmic transmission parameters and normalize to obtain the standard complex response, including:

[0160] Determine the window consistency weight of each logarithmic transmission parameter, and calculate the product of the logarithmic transmission parameter and the corresponding window consistency weight as the weighted composite complex quantity;

[0161] In detail, the logarithmic transmission parameter is a complex number containing amplitude and phase information, which reflects the propagation characteristics of the radio frequency signal after passing through the thoracic tissue. The window consistency weight quantifies the matching degree of each transmission channel and the periodic structure of the thorax, and the higher the weight, the more stable the channel is affected by the periodicity of the ribs and intercostal space, and the more reliable the response to the change in lung water. By multiplying each logarithmic transmission parameter and its corresponding window consistency weight, the signal contribution of the reliable channel can be enhanced, and the signal contribution of the unreliable channel can be weakened, and the product obtained is the weighted composite complex quantity of the channel, which reflects the effective signal of the channel after reliability adjustment.

[0162] Accumulate the window consistency weights of all transmission channels to obtain the window composite weight;

[0163] In detail, the window composite weight is the sum of the window consistency weights of all transmission channels. This can thus eliminate the influence of the number of channels or the absolute value difference of a single weight by aggregating the weights of all channels, ensuring that the signals at different body positions or different times have a unified reference benchmark.

[0164] The ratio of the weighted composite complex quantity to the window composite weight is taken as the standard complex response.

[0165] It should be noted that the sum of the weighted complex quantities of all channels is divided by the window complex weight, that is, the standard complex response is obtained. The ratio operation realizes normalization, so that the result is not affected by the absolute value of the weight, and only reflects the comprehensive effect of the reliability weighted signal of each channel. As the integrated complex signal, the standard complex response not only retains the amplitude and phase information in the logarithmic transmission parameter, but also filters the interference of unstable channels through the window consistency weight. At the same time, the normalization processing ensures its comparability under different conditions, providing a stable and reliable basis signal for subsequent stripping of respiratory and heart motion interference and calculation of lung water index.

[0166] In an embodiment of the present application, the standard complex response is subjected to spectral analysis to extract the respiratory angular frequency and the heart motion angular frequency, comprising:

[0167] The standard complex response is subjected to discrete Fourier transform to obtain an estimated spectrum;

[0168] In detail, the standard complex response is a complex signal after weighted normalization, containing slow-varying information related to lung water and high-frequency interference of physiological movements such as respiration and heart motion. Discrete Fourier transform of the standard complex response can convert the time-domain signal into the estimated spectrum in the frequency domain, which can intuitively present the energy distribution of different frequency components in the signal, laying a foundation for identifying the characteristic frequencies of respiration and heart motion.

[0169] The combination complex weight of the window complex weight corresponding to the low-frequency working frequency band and the window complex weight corresponding to the high-frequency working frequency band is calculated; the working frequency band corresponding to the standard complex response is determined, and the ratio of the window complex weight corresponding to the working frequency band to the combination complex weight is taken as the inter-frequency combination weight coefficient;

[0170] In detail, the combination complex weight is the sum of the window complex weight corresponding to the low-frequency working frequency band and the window complex weight corresponding to the high-frequency working frequency band, which is used to integrate the weight information of the two frequency bands. The inter-frequency combination weight coefficient is the ratio of the window complex weight of the working frequency band (low frequency or high frequency) to which the standard complex response belongs to the combination complex weight. This coefficient balances the signal reliability (the window complex weight reflects the overall matching degree of the channel) of different frequency bands, so that the subsequent spectrum analysis focuses more on the frequency band with higher weight and more stable signal.

[0171] The product of the inter-frequency combination weight coefficient and the estimated spectrum is taken as the joint spectrum;

[0172] In detail, the inter-frequency combination weight coefficient is multiplied by the estimated spectrum to obtain the joint spectrum. Thus, the spectrum of different frequency bands is integrated by weighting through the combination weight coefficient, the frequency characteristics of physiological interference in the reliable frequency band are strengthened, the noise influence of the unreliable frequency band is weakened, and the frequency peaks of respiration and heart motion are more prominent, which is convenient for accurate identification.

[0173] The maximum value in the joint spectrum is extracted and minimum , and calculate the respiratory angular frequency and the cardiac angular frequency .

[0174] It should be noted that the respiration and the heartbeat are periodic physiological activities, and the corresponding frequency components are manifested as obvious peaks in the joint autospectrum. Generally, the cardiac frequency is higher than the respiratory frequency, so the maximum value in the joint autospectrum corresponds to the cardiac frequency, and the minimum value corresponds to the respiratory frequency. Through the physical relationship between the angular frequency and the frequency (angular frequency = 2π x frequency), the respiratory angular frequency and the cardiac angular frequency can be calculated respectively.

[0175] In an embodiment of the present application, linear orthogonal projection is performed on the positive and negative sine functions of the respiratory angular frequency and the cardiac angular frequency and the direct current component as the basis vectors to obtain the demodulated slow-varying complex response, including:

[0176] A negative response sequence is constructed from the standard complex responses at N time points ;

[0177] In detail, the standard complex responses at N time points are selected, and they are arranged in time sequence to form a response sequence. The sequence contains slow-varying information related to lung water and is mixed with periodic interference caused by respiration and heartbeat. The purpose of constructing the sequence is to integrate the dispersed signals in the time domain into a unified processing object, laying a foundation for subsequent batch removal of interference.

[0178] A basis matrix is constructed , as follows:

[0179]

[0180] In detail, each row of the basis matrix corresponds to a time point, and each column corresponds to a basis vector, and a total of five basis vectors are included. The first column is all 1, representing the direct current component, which is used to capture the constant baseline in the signal; the second column and the third column are the cosine function value and the sine function value of the respiratory angular frequency, respectively, which are used to represent the periodic characteristics of the respiratory movement; the fourth column and the fifth column are the cosine function value and the sine function value of the cardiac angular frequency, respectively, which are used to represent the periodic characteristics of the heartbeat movement. The construction of the basis matrix is essentially to establish a subspace of the interference signals of respiration and heartbeat, which covers all possible periodic components of the two physiological activities.

[0181] A projection sequence is constructed through the basis matrix ;

[0182] In detail, the projection sequence is obtained by multiplying the response sequence by the formula . Wherein, I is the unit matrix, B is the basis matrix, is the transpose of the basis matrix. The core of the formula is to realize the orthogonal projection: subtract the projection of the response sequence on the subspace spanned by the basis matrix from the response sequence, and the remaining part is the signal component orthogonal to the respiratory and cardiac interference. This operation can effectively filter out the periodic fluctuations in the response sequence caused by breathing and heartbeat, and retain the slowly varying signal related to lung water changes.

[0183] map the projection sequence to the demodulated slowly varying complex response sequence ; wherein, .

[0184] It should be noted that each element in the projection sequence corresponds to a time point after the interference removal signal, and these elements are mapped in time sequence to the demodulated slowly varying complex response sequence. The demodulated slowly varying complex response at each time point is equal to the element at the corresponding position in the projection sequence, that is, the conversion from the projection result to the slowly varying signal with clear physical meaning is completed. The sequence has stripped off the high-frequency physiological interference and only retains the slowly fluctuating component related to lung water changes.

[0185] In an embodiment of the present application, taking the initial breath-holding time as the baseline, the complex difference of the demodulated slowly varying complex response of the low-frequency working frequency band and the high-frequency working frequency band is constructed, the real part and the imaginary part of the complex difference are taken as a two-dimensional vector, and the lung water index is generated by two-dimensional vector projection, comprising:

[0186] determining the demodulated slowly varying complex response sequence of the low-frequency working frequency band and the demodulated slowly varying complex response sequence of the high-frequency working frequency band, respectively, and determining the starting time of the patient to be monitored to suspend breathing ;

[0187] In detail, the demodulated slowly varying complex response sequence of the low-frequency working frequency band and the demodulated slowly varying complex response sequence of the high-frequency working frequency band need to be determined respectively. These two sequences have stripped off the respiratory and cardiac interference and only contain the slowly varying signal related to lung water. At the same time, the starting time of the patient to be monitored to suspend breathing is determined. At this time, the chest state is stable because the respiratory movement stops, which can be used as a reference point to eliminate the fixed signal deviation caused by individual physiological structure.

[0188] constructing the complex difference at the tth time point , comprising:

[0189]

[0190] wherein, represents the demodulated slowly varying complex response of the high-frequency working frequency band at time , represents the demodulated slowly varying complex response of the low-frequency working frequency band at time , represents the demodulated slowly varying complex response of the high-frequency working frequency band at the starting time , denotes the start time of the demodulation slow time-varying complex response of the low-frequency operating band;

[0191] In detail, the complex difference is used to highlight the difference between high and low frequency signals caused by changes in lung water, and the calculation formula is This operation eliminates the influence of individual inherent differences (such as chest wall thickness, initial lung state, etc.) through baseline calibration, and only retains the lung water-related signal component that changes over time, so that the difference result directly reflects the electromagnetic characteristic difference caused by the change of lung water.

[0192] The complex difference is decomposed into a two-dimensional vector ; wherein represents the real part of the complex difference , and represents the imaginary part of the complex difference .

[0193] In detail, the complex difference is decomposed into a two-dimensional vector, wherein the real part reflects the change of signal amplitude (attenuation), and the imaginary part reflects the change of signal phase, and the two together constitute the multi-dimensional characteristics of lung water changes. According to the mean vector of the two-dimensional vector at N time points, the two-dimensional vector at each time point is subtracted from the mean vector to obtain a zero-mean sequence. The de-meaning process can eliminate the overall offset of the data, so that the sequence fluctuates around zero, and the relative change of lung water is more accurately reflected.

[0194] According to the mean vector of the two-dimensional vector at N time points , the two-dimensional vector at each time point is de-meaned to obtain a zero-mean sequence , and the two-dimensional covariance matrix of the zero-mean sequence is estimated.

[0195] In detail, the two-dimensional covariance matrix of the zero-mean sequence is obtained by accumulating the product of each zero-mean vector and its transpose and taking the average, and the matrix reflects the correlation and fluctuation intensity of the real part and the imaginary part.

[0196] The eigenvalue decomposition process is performed on the two-dimensional covariance matrix to obtain the maximum eigenvalue and determine the unit eigenvector corresponding to the maximum eigenvalue .

[0197] In detail, the eigenvalue decomposition is performed on the covariance matrix, and the unit eigenvector corresponding to the maximum eigenvalue represents the most significant direction in the two-dimensional vector, which concentrates the main signal fluctuation information caused by the change of lung water.

[0198] The lung water index at time t is calculated as .

[0199] It should be noted that the lung water index at time t is obtained by taking the inner product of the zero-mean two-dimensional vector at the time and the unit eigenvector corresponding to the maximum eigenvalue. Thus, the two-dimensional feature is condensed into a one-dimensional index, which not only retains the main information of the lung water change, but also realizes quantitative representation. When the lung water increases or decreases, the index will present a corresponding monotonic change, thereby directly reflecting the dynamic change trend of the lung water.

[0200] It should be noted that the lung water index is only used to assist the doctor in judging the patient's condition, and is not directly used to directly diagnose the patient's condition.

[0201] Embodiment two:

[0202] As shown in Figure 2 A multi-probe radio frequency distributed lung water monitoring system applied to any one of the multi-probe radio frequency distributed lung water monitoring methods, comprising:

[0203] A logarithmic parameter acquisition module for arranging a radio frequency array around the thoracic cage, collecting transmission parameters in a low-frequency operating frequency band, a high-frequency operating frequency band and a guard frequency operating frequency band, and converting the transmission parameters into a logarithmic domain to form logarithmic transmission parameters;

[0204] A rib arch scanning module for shallow high-frequency spatial spectrum scanning based on the guard frequency operating frequency band, obtaining a rib arch direction unit vector and a synthesized pitch of the ribs and intercostal spaces by fitting a quasi-periodic lattice model of the ribs and intercostal spaces;

[0205] A wavelength determination module for determining effective wavelengths of tissues corresponding to the low-frequency operating frequency band and the high-frequency operating frequency band;

[0206] A standard complex response module for determining window consistency weights according to the rib arch direction unit vector, the synthesized pitch of the ribs and intercostal spaces and the effective wavelengths of tissues; and performing weighted summation and normalization processing on the logarithmic transmission parameters with the window consistency weights to obtain a standard complex response;

[0207] A demodulation response module for performing spectral analysis on the standard complex response to extract a respiratory angular frequency and a cardiac angular frequency, and performing linear orthogonal projection with the sine and cosine functions of the respiratory angular frequency and the cardiac angular frequency and a direct current component as basis vectors to obtain a demodulated slow-varying complex response;

[0208] A lung water index module for taking an initial breath-hold time as a baseline to construct a complex difference of the demodulated slow-varying complex responses of the low-frequency operating frequency band and the high-frequency operating frequency band, taking the real part and the imaginary part of the complex difference as a two-dimensional vector, and generating a lung water index by projecting the two-dimensional vector.

[0209] The above describes the embodiments of the present embodiment, but the present embodiment is not limited to the above-described specific embodiments, and the above-described specific embodiments are only illustrative but not restrictive, and those skilled in the art can make many forms under the inspiration of the present embodiment, which all belong to the protection of the present embodiment.

Claims

1. A multi-probe radio frequency distributed lung water monitoring method, characterized in that, The method comprises the following steps: An RF array is arranged around the thoracic cage, transmission parameters are collected in a low-frequency operating frequency band, a high-frequency operating frequency band and a guard operating frequency band, and the transmission parameters are converted into a logarithmic domain to form logarithmic transmission parameters; A shallow high-frequency spatial spectrum scan is performed based on the guard operating frequency band, a quasi-periodic lattice model of the ribs and intercostal spaces is fitted, a rib arch direction unit vector and a combined pitch of the ribs and intercostal spaces are obtained; Effective wavelengths in tissues corresponding to the low-frequency operating frequency band and the high-frequency operating frequency band are determined; A window consistency weight is determined according to the rib arch direction unit vector, the combined pitch of the ribs and intercostal spaces and the effective wavelengths in tissues, and the logarithmic transmission parameters are weighted and summed and normalized with the window consistency weight to obtain a standard complex response; Self-spectrum analysis is performed on the standard complex response, a respiratory angular frequency and a heart motion angular frequency are extracted, and a demodulation slow-varying complex response is obtained by linear orthogonal projection with the sine and cosine functions of the respiratory angular frequency and the heart motion angular frequency and a direct current component as base vectors; A complex difference of the demodulation slow-varying complex responses of the low-frequency operating frequency band and the high-frequency operating frequency band is constructed with an initial breath-holding time as a baseline, the real part and the imaginary part of the complex difference are taken as a two-dimensional vector, and a lung water index is generated by two-dimensional vector projection.

2. A multi-probe RF distributed lung water monitoring method according to claim 1, wherein, Transmission parameters are collected in a low-frequency operating frequency band, a high-frequency operating frequency band and a guard operating frequency band, and the transmission parameters are converted into a logarithmic domain to form logarithmic transmission parameters, which comprises the following steps: The low-frequency operating frequency band is 0.6 GHz to 0.8 GHz, the high-frequency operating frequency band is 1.2 GHz to 1.5 GHz, and the guard operating frequency band is 2.0 GHz to 2.5 GHz; The amplitude and phase of the transmission parameter at time t are collected at fixed time intervals The frequency band represents a low-frequency operating frequency band, a high-frequency operating frequency band, or a guard-band operating frequency band.​​​ The transmission parameters are converted into a logarithmic domain according to the amplitudes and phases of the transmission parameters, as follows: wherein represents a logarithmic transmission parameter, represents the imaginary unit, .

3. A multi-probe RF distributed lung water monitoring method according to claim 2, wherein, A shallow high-frequency spatial spectrum scan is performed based on the guard operating frequency band, a quasi-periodic lattice model of the ribs and intercostal spaces is fitted, a rib arch direction unit vector and a combined pitch of the ribs and intercostal spaces are obtained, which comprises the following steps: In a first preset time period, logarithmic transmission parameters of each frequency in the guard operating frequency band are determined at a fixed time interval, and logarithmic transmission parameter variances of the corresponding frequencies are calculated; a frequency corresponding to the maximum logarithmic transmission parameter variance is taken as a scanning frequency point; In the second preset time period, the M scanning probes are controlled to collect the logarithmic transmission parameters according to the scanning frequency points, and the average value of each logarithmic transmission parameter is calculated ; A one-dimensional mapping is set to determine a one-dimensional coordinate of the mth scanning probe ; wherein, ; wherein, represents an origin coordinate of a one-dimensional coordinate system, represents a coordinate of the mth scanning probe, represents an initial rib arch direction unit vector, represents an included angle of the one-dimensional mapping with a horizontal direction; The logarithmic transmission parameters of each scanning probe are fitted based on the average values and one-dimensional coordinates, as follows: wherein, represents a constant term of the quasi-periodic lattice model, represents an amplitude coefficient of the quasi-periodic lattice model, represents a phase coefficient of the quasi-periodic lattice model, represents a combined pitch of the initial rib and intercostal. The explained variance of the quasi-periodic lattice model corresponding to the initial rib arch direction unit vector and the combined pitch of the ribs and intercostal spaces is calculated, as follows: wherein, represents a fitting value of the quasi-periodic lattice model to the average of the logarithmic transmission parameters of the mth scanning probe, represents the average of the logarithmic transmission parameters of all scanning probes in the second preset time period; corresponding initial rib and intercostal composite pitch and initial rib arch orientation unit vectors as the rib and intercostal composite pitch and rib arch orientation unit vectors along which to maximize explained variance.

4. A multi-probe RF distributed lung water monitoring method according to claim 3, wherein, Effective wavelengths in tissues corresponding to the low-frequency operating frequency band and the high-frequency operating frequency band are determined, which comprises the following steps: determining a separation distance of the transmission channel of the mth scan probe to the transmission probe ;​ controlling the patient to be monitored to suspend breathing for at least 10 seconds, collecting and transmitting the channel at fixed time intervals corresponding phase, to calculate the average phase, and to perform phase unwrapping processing on the average phase to obtain the corresponding unwrapped phase ; Determining transmission channel The angle between the rib arch direction unit vector And the angle Calculate the corresponding direction smoothing weight ; The unwrapped phase and the baseline length are fitted by weighted least squares, as follows: wherein, represents the slope to be fitted; The corresponding to-be-fitted slope is taken as a target slope by minimizing the weighted least squares fitting value; The effective wavelengths in tissues are calculated according to the target slope, which comprises the following steps: wherein, represents an effective wavelength within the tissue, belongs to a low-frequency operating band or a high-frequency operating band, represents a target slope.

5. A multi-probe RF distributed lung water monitoring method according to claim 4, wherein, A window consistency weight is determined according to the rib arch direction unit vector, the combined pitch of the ribs and intercostal spaces and the effective wavelengths in tissues, which comprises the following steps: The rib and the intercostal synthetic pitch are projected to the angle between the transmission channel and the rib arch unit vector, and the equivalent pitch of the transmission channel is calculated ; Based on the equivalent pitch and the effective wavelengths in tissues, a matching residual corresponding to the window consistency weight is calculated, as follows: wherein denotes the projection magnification, denotes the matching residual of the transmission channel; extracting the matching residual of each transmission channel to determine a matching residual median; multiplying the matching residual median by a normal distribution constant to obtain a frequency corresponding robust scale ; The window consistency weight of the transmission channel at a frequency f is calculated according to the robust scale and the matching residual: wherein, represents a transmission channel window consistency weight at frequency f.

6. A multi-probe RF distributed lung water monitoring method according to claim 5, wherein, The logarithmic transmission parameters are weighted and summed and normalized with the window consistency weight to obtain a standard complex response, which comprises the following steps: determining a window consistency weight of each logarithmic transmission parameter, calculating a product of the logarithmic transmission parameter and the corresponding window consistency weight as a weighted complex composite variable; accumulating the window consistency weights of all transmission channels to obtain a window composite weight; taking a ratio of the weighted complex composite variable and the window composite weight as a standard complex response.

7. A multi-probe RF distributed lung water monitoring method according to claim 6, wherein, performing a spectral analysis on the standard complex response to extract a respiratory angular frequency and a cardiac angular frequency, including: performing a discrete Fourier transform on the standard complex response to obtain an estimated spectrum; calculating a combined composite weight of the window composite weight corresponding to the low-frequency working frequency band and the window composite weight corresponding to the high-frequency working frequency band; determining a working frequency band corresponding to the standard complex response, and taking a ratio of the window composite weight corresponding to the working frequency band and the combined composite weight as an inter-frequency combination weight coefficient; taking a product of the inter-frequency combination weight coefficient and the estimated spectrum as a joint spectrum; Extracting the maximum value from the joint autospectrum and minimum value And calculate the respiratory angular frequency. and cardiac angular frequency .

8. A multi-probe RF distributed lung water monitoring method according to claim 7, wherein, performing a linear orthogonal projection on the respiratory angular frequency and the cardiac angular frequency and a direct current component as a basis vector to obtain a demodulated slow-varying complex response, including: Constructing a negative response sequence from N standard complex responses ; Constructing a base matrix As follows: Constructing a projection sequence by a basis matrix ; The projection sequence is mapped to a sequence of de-modulated slowly varying complex impulse responses ; wherein, .

9. A multi-probe RF distributed lung water monitoring method according to claim 8, wherein, taking an initial breath-holding time as a baseline to construct a complex difference of the demodulated slow-varying complex responses of the low-frequency working frequency band and the high-frequency working frequency band, taking a real part and an imaginary part of the complex difference as a two-dimensional vector, and generating a lung water index by projecting the two-dimensional vector, including: determining a demodulated slow varying complex response sequence for a low frequency operating band and a demodulated slow varying complex response sequence for a high frequency operating band, respectively, and a start time instant at which the patient to be monitored suspends breathing ; constructing the complex difference at the tth time instant , comprising: in, Indicates time The demodulation of the slow-varying complex response in the high-frequency operating band. Indicates time The demodulation of the slow-varying complex response in the low-frequency operating band. Indicates the start time The demodulation of the slow-varying complex response in the high-frequency operating band. Indicates the start time The demodulation of the slow-varying complex response in the low-frequency operating band; complex difference performing complex resolution to obtain a two-dimensional vector ; wherein denotes the real part of the complex difference denotes the imaginary part of the complex difference denotes the imaginary part of the complex difference denotes the imaginary part of the complex difference According to the mean vector of the two-dimensional vectors at N time instants The two-dimensional vectors at each time instant are de-meaned to obtain a zero-mean sequence And a two-dimensional covariance matrix is estimated from the zero-mean sequence ; Eigenvalue decomposition is performed on the two-dimensional covariance matrix to obtain a maximum eigenvalue and determine a unit eigenvector corresponding to the maximum eigenvalue ; The lung water index at time t is calculated .

10. A multi-probe RF distributed lung water monitoring system, applied to the multi-probe RF distributed lung water monitoring method of any one of claims 1-9, characterized in that, including: a logarithmic parameter sampling module, configured to arrange a radio frequency array around a thorax, collect transmission parameters in a low-frequency working frequency band, a high-frequency working frequency band and a guard frequency working frequency band, and convert the transmission parameters into a logarithmic domain to form logarithmic transmission parameters; a rib arch scanning module, configured to perform a shallow high-frequency spatial spectrum scan based on the guard frequency working frequency band, fit a quasi-periodic lattice model of ribs and intercostal spaces, and obtain a rib arch trend unit vector and a combined pitch of the ribs and the intercostal spaces; a wavelength determination module, configured to determine effective wavelengths in tissues corresponding to the low-frequency working frequency band and the high-frequency working frequency band; a standard complex response module, configured to determine window consistency weights according to the rib arch trend unit vector, the combined pitch of the ribs and the intercostal spaces and the effective wavelengths in tissues, and perform weighted summation and normalization processing on the logarithmic transmission parameters with the window consistency weights to obtain a standard complex response; a demodulated response module, configured to perform a spectral analysis on the standard complex response to extract a respiratory angular frequency and a cardiac angular frequency, and perform a linear orthogonal projection on the respiratory angular frequency and the cardiac angular frequency and a direct current component as a basis vector to obtain a demodulated slow-varying complex response; a lung water index module, configured to take an initial breath-holding time as a baseline to construct a complex difference of the demodulated slow-varying complex responses of the low-frequency working frequency band and the high-frequency working frequency band, take a real part and an imaginary part of the complex difference as a two-dimensional vector, and generate a lung water index by projecting the two-dimensional vector.

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