Coupling detection method based on expiration detection and electrical impedance tomography, detection system and storage medium

Abstract

The invention provides a coupling detection method and system based on expiration detection and electrical impedance tomography, and belongs to the technical field of medical information software, the technical key points are that the method comprises the following steps: S100, obtaining expiration flow velocities corresponding to different moments in a single expiration period; s200, acquiring boundary voltage matrixes corresponding to different moments in a single expiration period based on the same excitation frequency; s300, obtaining average impedance change values corresponding to different moments in a single expiration period based on the data obtained in the S200; and S400, solving an expiration impedance matching index (EIMI). By the adoption of the coupling detection method and system based on expiration detection and electrical impedance tomography, bronchial relaxation tests are not needed, and the early-stage chronic obstructive pulmonary disease can be effectively found.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of intelligent medical treatment, and particularly relates to a coupling detection method based on exhalation detection and electrical impedance imaging, a detection system, and a storage medium. BACKGROUND

[0002] The gold standard for COPD (Chronic Obstructive Pulmonary Disease) is the bronchodilator test, which mainly diagnoses COPD according to FEV1 (forced expiratory volume in one second) / FVC (forced vital capacity) <0.70 after inhaling a bronchodilator. This index can objectively evaluate the irreversibility of airflow limitation and is a key basis for differentiating COPD from other respiratory diseases.

[0003] However, the bronchodilator test has the following shortcomings in the evaluation of COPD: (1) unable to locate the lesion area; (2) there is a risk of drug stimulation because the patient inhales a bronchodilator; (3) unable to dynamically monitor the lung function of the patient.

[0004] In view of the above shortcomings, many scholars have devoted themselves to applying EIT (Electrical Impedance Tomography) in the field of COPD, such as: Reference 1: XU W N, FENG H, KAI S J, et al. Research progress of electrical impedance tomography in chronic obstructive pulmonary disease [J]. Journal of Chronic Diseases, 2022(003) believes that the COV and GI indexes can be calculated through the EIT image to evaluate the ventilation status of each region of the lung.

[0005] Reference 2: CN118697320B (Guangzhou Medical University, Zhejiang University Medical College Affiliated Shaw Hospital) believes that FEV1 / FVC and GI can be calculated based on EIT images, and thus the damage to the reserve ratio lung function can be evaluated.

[0006] Reference 3: CN118121183B (Guangzhou Medical University, Beijing Union Hospital of Chinese Academy of Medical Sciences) believes that the regional time distribution graph containing time characteristics can be obtained based on the time sequence EIT image, and the regional time distribution and its coefficient of variation of different exhaled air volumes obtained from the regional time distribution graph can accurately reflect the time required for unit exhaled air volume, objectively characterize the explosive force of the human respiratory muscle, the endurance of the respiratory muscle, and whether the lung is damaged, more comprehensively evaluate the respiratory function of the human lung, and overcome the technical difficulty that the existing index cannot reflect the time required for unit exhaled air volume.

[0007] Reference 4: CN118121184B (Guangzhou Medical University, Peking Union Medical College Hospital of Chinese Academy of Medical Sciences) believes that by determining regional time distribution and its distribution characteristic parameters based on the change characteristics of different exhalation volumes, the time characteristics required for exhaling different amounts of gas in FVC are characterized; and by comparing the regional time distribution and the distribution characteristic parameters, the result of whether the human lung has regional ventilation function damage is accurately and objectively characterized.

[0008] However, due to the two shortcomings of "low imaging resolution and low robustness" of EIT, it is difficult to realize accurate screening of chronic diseases of the lung, especially early chronic obstructive pulmonary diseases, by relying only on EIT single technology. SUMMARY

[0009] The purpose of the present application is to solve the problems existing in the prior art, and to provide a coupling detection method based on exhalation detection and electrical impedance imaging, a detection system and a storage medium.

[0010] A coupling detection method based on exhalation detection and electrical impedance imaging, comprising the following steps: S100, acquiring different time points t0, t1, t2, t3,..., t N corresponding to a single exhalation cycle; N ); t0, t N are the start time and end time of a single exhalation cycle, respectively; S200, acquiring the corresponding boundary voltage matrix V(t0), V(t1), V(t2), V(t3),..., V(t N ) at different time points t0, t1, t2, t3,..., t N based on a single exhalation cycle under the same excitation frequency; S300, acquiring the corresponding average impedance change value △Z(t0), △Z(t1), △Z(t2), △Z(t3),..., △Z(t N ) at different time points t0, t1, t2, t3,..., t N based on the data obtained by S200 in a single exhalation cycle; S400, solving the exhalation impedance matching index EIMI: EIMI= [Q(t0) ·△Z(t0) ·(t1-t0) / 2+ Q(t1) ·△Z(t1) ·(t2-t0) / 2+Q(t2)·△Z(t2) ·(t3-t2) / 2+……+ Q(t i ) ·△Z(t i ) ·(ti+1 -t i-1 ) / 2 +……+Q(t N ) ·△Z(t N ) ·(t N -t N-1 ) / 2] / [Var(Q)·Var(△Z)] 0.5 ; Var(Q) is the variance of Q(t0)~Q(t N ); Var(△Z) is the variance of△Z(t0)~△Z(t N ).

[0011] Further, S500, according to the EIMI gives the results of ventilation function damage: If EIMI≥0.75, it is healthy; If 0.75>EIMI≥0.45, it is asthma or mild COPD; If 0.45>EIMI, it is moderate to severe COPD.

[0012] Further, S300 includes the following sub-steps: S301, calculating the boundary voltage difference matrix△V(t i ) of any time t i and t0:△V(t i )=V(t i )-V(t0); S302, calculating the relative conductivity matrix△σ(t i ) of any time t i and t0; S303, solving the normalized relative conductivity matrix△σ i (t norm ) of any time t i and t0; △σ norm (t i )=△σ(t i ) / max{△σ(t i )}, max{△σ(t i )} represents the maximum value in the matrix△σ(t i ); S304, solving the average impedance change value△Z(t i ) of any time t i :△Z(t i )=mean(△σ norm (t i )), mean represents solving the average number.

[0013] Further, S302 employs the TK-Noser method to solve the relative conductivity matrix Δσ(t i ).

[0014] A coupling detection system based on exhalation detection and electrical impedance imaging, comprising: a storage module, an average impedance change value solving module, an EIMI solving module; The storage module stores the different time points t0, t1, t2, t3, …, t N , the corresponding exhalation flow rates Q(t0), Q(t1), Q(t2), Q(t3), …, Q(t N ), the average impedance change values △Z(t0), △Z(t1), △Z(t2), △Z(t3), …, △Z(t N , the corresponding boundary voltage matrices V(t0), V(t1), V(t2), V(t3), …, V(t N ); t0, t N are the start time and the end time of a single exhalation cycle, respectively; S200, the average impedance change value solving module can solve the average impedance change values △Z(t0), △Z(t1), △Z(t2), △Z(t3), …, △Z(t N ) at different time points t0, t1, t2, t3, …, t N in a single exhalation cycle according to V(t0)~ V(t N ); S300, the EIMI solving module is used to solve the EIMI value of the patient; EIMI= [Q(t0) ·△Z(t0) ·(t1-t0) / 2+ Q(t1) ·△Z(t1) ·(t2-t0) / 2+Q(t2)·△Z(t2) ·(t3-t2) / 2+……+ Q(t i ) ·△Z(t i ) ·(t i+1 -t i-1 ) / 2 +……+Q(t N ) ·△Z(t N ) ·(t N -t N-1 ) / 2] / [Var(Q)·Var(△Z)] 0.5 ; Var(Q) refers to the variance of Q(t0)~Q(t N ); Var(△Z) refers to the variance of △Z(t0)~△Z(t N ). Further, the working method of the average impedance change value solving module is: Step a, calculate any time t i The boundary voltage difference matrix ΔV(t) with t0 i ): ΔV(t) i )= V(t i )- V(t0); Step b, calculate any time t i The relative conductivity matrix Δσ(t) with t0 i ); Step c, ; Δσ norm (t i )= Δσ(t i ) / max{Δσ(t i )},max{Δσ(t i )} represents the matrix Δσ(t) i The maximum value in ); Step d: Solve for any time t i The average impedance change value ΔZ(t) i ): ΔZ(t) i )=mean(Δσ norm (t i ()), mean means to calculate the average.

[0015] Furthermore, in step b, the TK-Noser method is used to solve for the relative conductivity matrix Δσ(t). i ).

[0016] Furthermore, based on the results of ventilatory function impairment given by EIMI: if EIMI ≥ 0.75, then the patient is healthy; if 0.75 > EIMI ≥ 0.45, then the patient has asthma or mild COPD; if 0.45 > EIMI, then the patient has moderate to severe COPD.

[0017] Furthermore, the excitation frequency ranges from [80KHz to 120KHz].

[0018] Furthermore, at different times t0, t1, t2, t3, ..., t within a single expiratory cycle N The corresponding expiratory flow rates are Q(t0), Q(t1), Q(t2), Q(t3), ..., Q(t). N Based on the same exhalation frequency, at different times t0, t1, t2, t3, ..., t within a single expiratory cycle, N The corresponding boundary voltage matrices are V(t0), V(t1), V(t2), V(t3), ..., V(t). N All of these data were obtained under the condition that the subject completed a forceful inhalation until the lungs were full and then forcefully exhaled until all the air was exhaled (this process is similar to the characteristics of FVC).

[0019] A storage medium, characterized in that it stores a program capable of executing the coupling detection method as described above.

[0020] The advantages of the technical solution of the present application mainly include: First, the first basic idea of the present application is to propose a new specificity parameter: EIMI. The value of EIMI reflects the airflow-impedance time-domain synergy. By using EIMI, the following advantages are achieved: 1.1, bronchodilation test is not required; 1.2, early COPD can be effectively found.

[0021] Second, EIMI is defined as follows: EIMI= [Q(t0) ·△Z(t0) ·(t1-t0) / 2+ Q(t1) ·△Z(t1) ·(t2-t0) / 2+Q(t2)·△Z(t2) ·(t3-t2) / 2+……+ Q(t i ) ·△Z(t i ) ·(t i+1 -t i-1 ) / 2 +……+Q(t N ) ·△Z(t N ) ·(t N -t N-1 ) / 2] / [Var(Q)·Var(△Z)] 0.5 ; Var(Q) is the variance of Q(t0)~ Q(t N ); Var(△Z) is the variance of △Z(t0)~ △Z(t N ); In the formula, EIMI is the expiratory impedance matching index; Q(t) is the expiratory velocity signal measured by the flow rate sensor; △Z(t) is the average lung impedance change value; t0, t N are the start and end times of the expiratory period; and Var[] is the variance of the signal.

[0022] In the calculation process of EIMI, the normalized relative conductivity matrix Δσ norm (t i ) is used to avoid measurement differences caused by different excitation frequencies and amplitude differences caused by different measurement conditions. BRIEF DESCRIPTION OF DRAWINGS

[0023] The present application will be further described in detail below in combination with the embodiments in the drawings, but it does not constitute any limitation on the present application.

[0024] Figure 1 The specificity of EIMI in COPD, health, asthma is illustrated.

[0025] Figure 2 The threshold analysis result of EIMI is illustrated.

[0026] Figure 3 The physical meaning of the symbol of the present application is illustrated. DETAILED DESCRIPTION

[0027] The objects, advantages and features of the present application will be explained by the following non-limiting description of preferred embodiments. These embodiments are only typical examples of the application, and any technical solution formed by equivalent replacement or equivalent transformation falls within the scope of the present application.

[0028] <1. The research and development idea of the characteristics of early COPD> The research and development team found that early COPD has weak abnormalities in respiratory physiological parameters, especially in the form of expiratory flow fluctuation, tidal end humidity change, and respiratory impedance mode change. How to select suitable quantifiable biological characteristics from the above-mentioned performances to form specific parameters is the key to solving the diagnosis of early COPD.

[0029] The specific parameter proposed in the present application is the expiratory impedance matching index, which can be called EIMI (Expiratory Impedance Matching Index).

[0030] Specifically, EIMI is defined as follows: EIMI= [Q(t0) ·△Z(t0) ·(t1-t0) / 2+ Q(t1) ·△Z(t1) ·(t2-t0) / 2+Q(t2)·△Z(t2) ·(t3-t2) / 2+……+ Q(t i ) ·△Z(t i ) ·(t i+1 -t i-1 ) / 2 +……+Q(t N ) ·△Z(t N ) ·(t N -t N-1 ) / 2] / [Var(Q)·Var(△Z)] 0.5 ; Var(Q) is the variance of Q(t0)~ Q(t N ); Var(△Z) is the variance of △Z(t0)~ △Z(t N ); In the formula, EIMI is an expiratory impedance matching index; Q(t) is an expiratory speed signal measured by a flow rate sensor; ΔZ(t) is a mean impedance change value of the lung; t0 and t1 are start and end times of an expiratory period; and Var[] is a variance of the signal. N

[0031] [II. Specific expression of EIMI] A total of 168 subjects were preliminarily recruited from a double-center cohort of the Second Affiliated Hospital of Soochow University and the First Affiliated Hospital of Jinan University. All the subjects signed informed consent forms and completed a complete FVC (forced vital capacity) breath detection process.

[0032] The following two types of data were synchronously collected for each subject: (1) an expiratory flow rate signal Q(t): collected by a mask flow rate sensor, with a sampling frequency of ≥50 Hz; (2) a chest boundary voltage signal V(t): obtained by a 16-channel EIT device in an adjacent excitation-adjacent measurement mode, with a total of 208 groups of voltages. In the data quality control link, 18 subjects were excluded according to the following standards: (1) there is a loss or saturation of ≥1.5 s in the flow rate signal; (2) there are continuous ≥5 frames of artifacts, reconstruction failure, or obvious electrode contact abnormalities in the EIT reconstructed image; (3) there are non-standard FVC operations (such as early interruption, repeated inhalation, etc.) in the expiratory process.

[0033] The total number of samples included in the analysis was 150, of which: normal control group (Normal): 50 cases, asthma group (Asthma): 50 cases, and chronic obstructive pulmonary disease group (COPD): 50 cases.

[0034] As shown in Figure 1 , the EIMI index is taken as a continuous respiratory coupling measurement value, and based on statistical analysis of the training samples, it is found that EIMI has significant differences in health, asthma or mild COPD, and moderate to severe COPD, and the threshold distribution of the three can be determined as shown in Figure 2 .

[0035] Therefore, in actual application, the lung function state of a subject can be determined by comparing EIMI with the preset grading threshold value.

[0036] [III. Coupling detection method based on expiratory detection and electrical impedance imaging] The coupling detection method based on expiratory detection and electrical impedance imaging comprises the following steps: ​S100, obtaining the corresponding expiratory flow rate Q(t0), Q(t1), Q(t2), Q(t3),..., Q(tn) at different time t0, t1, t2, t3,..., tn in a single expiratory cycle. N S100, obtaining the corresponding expiratory flow rate Q(t0), Q(t1), Q(t2), Q(t3),..., Q(tn) at different time t0, t1, t2, t3,..., tn in a single expiratory cycle. N ); t0, t N are the start time and end time of a single expiratory cycle, respectively. S200, obtaining the corresponding boundary voltage matrix V(t0), V(t1), V(t2), V(t3),..., V(tn) at different time t0, t1, t2, t3,..., tn in a single expiratory cycle based on the same excitation frequency. N S200, obtaining the corresponding boundary voltage matrix V(t0), V(t1), V(t2), V(t3),..., V(tn) at different time t0, t1, t2, t3,..., tn in a single expiratory cycle based on the same excitation frequency. N ); S300, obtaining the corresponding average impedance change value ΔZ(t0), ΔZ(t1), ΔZ(t2), ΔZ(t3),..., ΔZ(tn) at different time t0, t1, t2, t3,..., tn in a single expiratory cycle based on the data obtained in S200. N S300, obtaining the corresponding average impedance change value ΔZ(t0), ΔZ(t1), ΔZ(t2), ΔZ(t3),..., ΔZ(tn) at different time t0, t1, t2, t3,..., tn in a single expiratory cycle based on the data obtained in S200. N ); S300 includes the following sub-steps: S301, calculating the boundary voltage difference matrix ΔV(t i ) between any time t i and t0: i = V(t i )- V(t0). S302, calculating the relative conductivity matrix Δσ(t i ) between any time t i and t0: Δσ(t i )=(J T ·J+k t ·I+k n W) -1 ·J T ·ΔV(t i ). S303, in order to eliminate the influence of signal amplitude difference under different individuals and measurement conditions on the calculation result, the Δσ(t i ) is normalized, for example, normalized according to the maximum absolute value: Δσ norm (t i )= Δσ(t i ) / max{Δσ(t i )}, that is, each data in the matrix Δσ(t i ) is divided by the maximum value of the matrix; max{Δσ(t i )} represents the maximum value of the matrix Δσ(t ithe maximum value in the equation (1) ; Δσ norm (t i ) is the normalized conductivity matrix; S304, in order to simplify the subsequent analysis, the conductivity change in the whole image is regionally averaged to obtain the global or lung area representative impedance change index: ΔZ(t i )=mean(Δσ norm (t i )),mean represents the mean value; S400, solving the expiration impedance matching index EIMI: EIMI= [Q(t0) ·△Z(t0) ·(t1-t0) / 2+ Q(t1) ·△Z(t1) ·(t2-t0) / 2+Q(t2)·△Z(t2) ·(t3-t2) / 2+……+ Q(t i ) ·△Z(t i ) ·(t i+1 -t i-1 ) / 2 +……+Q(t N ) ·△Z(t N ) ·(t N -t N-1 ) / 2] / [Var(Q)·Var(△Z)] 0.5 ; Var(Q) is the variance of Q(t0)~Q(t N ); Var(△Z) is the variance of △Z(t0)~△Z(t N ); S500, according to EIMI to give the result of ventilation function damage.

[0037] For the expiration flow rate Q(t0)~Q(t N ), the expiration flow rate signal can be collected by the flow sensor in the user's face mask, and the sampling frequency is ≥50Hz, which is used to reflect the airway patency and lung recoil capacity.

[0038] It should be noted that for electrical impedance, the EIT detection device such as CN215738930U, CN219557274U is worn on the patient (generally, 16 electrodes are used for chest and lung detection). The 16 electrodes on the wearable vest on the patient can collect the boundary voltage signal, and the lung EIT image sequence is obtained by combining the finite element model inversion reconstruction two-dimensional conductivity image sequence obtained by the 16 electrodes attached to the chest. 16 electrodes, distributed around the chest in turn, using adjacent excitation and adjacent acquisition method, collecting 208 groups of voltage.

[0039] It should be noted that for the relative conductivity matrix Δσ, it can be obtained in various ways. The most common TK-Noser method is used to solve (reference: CN115177234A), first, the sensitivity matrix J is solved according to the shape of the patient's lung; then, the relative conductivity matrix Δσ is obtained by using the following formula: Δσ(t i )=(J T ·J+k t ·I+k n W) -1 ·J T ·ΔV(t i );J is the sensitivity matrix, J T is the transpose matrix of J, k t , k n are regularization parameters, respectively, W represents a diagonal matrix with the same order and diagonal elements as J; I represents a unit matrix with the same number of columns as J.

[0040] It should be noted that the methods in embodiments 2-4 are not directly aimed at disease diagnosis and treatment.

[0041] It should be noted that the method of the present application does not require all the data of the FVC action period (a single FVC action contains inhalation + exhalation), and the present application only needs to take the data corresponding to the exhalation process in the FVC action period when applied.

[0042] It should be noted that the method of the present application does not require strict compliance with the FVC action of the lung function instrument determination standard (i.e. it does not need to be limited to the use of a lung function instrument when obtaining data), but must ensure that the subject completes a forced inhalation to fill the lungs and then a forced exhalation to exhaust the breath (a breath similar to the characteristics of the FVC action) to ensure the effectiveness of the EIMI calculation.

[0043] The above embodiments are the preferred embodiments of the present application, which are only used to facilitate the description of the present application and do not limit the present application in any form. Any person with ordinary knowledge in the art can make partial changes or modifications to the equivalent embodiments within the scope of the technical features disclosed by the present application without departing from the technical features of the present application, and the equivalent embodiments still belong to the scope of the technical features of the present application.

Claims

1. A method of detection based on the coupling of breath detection and electrical impedance imaging, characterized in that, Comprising the following steps: S100, acquiring exhalation flow rate Q(t0), Q(t1), Q(t2), Q(t3), …, Q(t N corresponding to different time t0, t1, t2, t3, …, t N ) at different time t0, t1, t2, t3, …, t t0, t N are the start time and end time of a single exhalation cycle, respectively S200, obtaining boundary voltage matrices V(t0), V(t1), V(t2), V(t3), …, V(tn) corresponding to the different time points t0, t1, t2, t3, …, tn in the single exhalation cycle under the same excitation frequency. N Corresponding boundary voltage matrices V(t0), V(t1), V(t2), V(t3), …, V(tn) N ) S300, based on the data obtained in S200, acquiring the average impedance change values △Z(t0), △Z(t1), △Z(t2), △Z(t3), …, △Z(tn) at different time points t0, t1, t2, t3, …, tn in a single exhalation cycle. N The corresponding average impedance change values △Z(t0), △Z(t1), △Z(t2), △Z(t3), …, △Z(tn) at different time points t0, t1, t2, t3, …, tn in a single exhalation cycle. N ) S400, solving the expiratory impedance matching index EIMI: EIMI = [Q(t0) ·△Z(t0) ·(t1-t0) / 2+ Q(t1) ·△Z(t1) ·(t2-t0) / 2+Q(t2) ·△Z(t2) ·(t3-t2) / 2+……+ Q(t i ) ·△Z(t i ) ·(t i+1 -t i-1 ) / 2 +……+Q(t N ) ·△Z(t N ) ·(t N -t N-1 ) / 2] / [Var(Q)·Var(△Z)] 0.5 ; Var(Q) refers to the variance of Q(t0)~Q(t N ). Var(△Z) is the variance of △Z(t0)~△Z(t N ).

2. The method according to claim 1, wherein, S500, giving the result of the ventilation function damage according to the EIMI: If EIMI≥0.75, it is healthy; If 0.75>EIMI≥0.45, it is asthma or mild COPD; If 0.45>EIMI, it is moderate to severe COPD.

3. The method of claim 1, wherein, S300 comprises the following sub-steps: S301, calculate any time t i The boundary voltage difference matrix AV(t i ) of t0: AV(t i )= V(t i )-V(t0); S302, calculating the relative permittivity matrix Δε(t i and the relative conductivity matrix Δσ(t i ) at any time t S303, solving the normalized arbitrary time t i Relative conductivity matrix of t0 norm (t i ); Δσ norm (t i )= Δσ(t i ) / max{Δσ(t i )}, max{Δσ(t i )} represents the maximum value in the matrix Δσ(t i ). S304, solving the average impedance change value ΔZ(t i ) at any time t i ): ΔZ(t i )=mean(Δσ norm (t i )), mean represents solving the average number.

4. The method of claim 3, wherein, S302 employs the TK-Noser method to solve the relative permittivity matrix Δσ(t i ).

5. A coupled detection system based on breath detection and electrical impedance imaging, characterized in that, Comprising: A storage module, an average impedance change value solving module, and an EIMI solving module; The storage module stores different time points t0, t1, t2, t3, …, t N The corresponding expiratory flow rates Q(t0), Q(t1), Q(t2), Q(t3), …, Q(t N ), based on the same excitation frequency at different time points t0, t1, t2, t3, …, t N The corresponding boundary voltage matrix V(t0), V(t1), V(t2), V(t3), …, V(t N ) t0, t N are the start time and end time of a single expiratory cycle, respectively S200, the average impedance change calculation module can calculate the value of V(t0) ~ V(t) N Find the values ​​t0, t1, t2, t3, ..., t4 at different times within a single expiratory cycle. N The corresponding average impedance changes are ΔZ(t0), ΔZ(t1), ΔZ(t2), ΔZ(t3), ..., ΔZ(t... N ); S300, the EIMI solving module is used to solve the EIMI value of the patient; EIMI= [Q(t0) ·△Z(t0) ·(t1-t0) / 2+ Q(t1) ·△Z(t1) ·(t2-t0) / 2+Q(t2) ·△Z(t2) ·(t3-t2) / 2+……+ Q(t i ) ·△Z(t i ) ·(t i+1 -t i-1 ) / 2 +……+Q(t N ) ·△Z(t N ) ·(t N -t N-1 ) / 2] / [Var(Q)·Var(△Z)] 0.5 Var(Q) refers to Q(t0) ~ Q(t). N The variance of ΔZ; Var(ΔZ) refers to the range of ΔZ(t0) to ΔZ(t). N The variance of ).

6. The system according to claim 5, wherein, The working method of the average impedance change value solving module is: Step a, calculate any time t i The boundary voltage difference matrix ΔV(t) with t0 i ): ΔV(t) i )= V(t i )- V(t0); Step b, calculating the relative conductivity matrix AS(t i at time t relative to t0 i ) Step c, solving the normalized arbitrary time t i Relative conductivity matrix Δσ with respect to t0 norm (t i ); Δσ norm (t i )= Δσ(t i ) / max{Δσ(t i )}, max{Δσ(t i )} indicates the maximum value in the matrix Δσ(t i ) Step d, solving the average impedance change value ΔZ(t i ) at any time t i : ΔZ(t i )=mean(Δσ norm (t i )), mean represents solving the average number.

7. The system of claim 5, wherein, The TK-Noser method is used in step b to solve the relative permittivity matrix Δσ(t i ).

8. The system of claim 5, wherein, According to the EIMI, the result of the ventilation function damage is given: if EIMI≥0.75, it is healthy; if 0.75>EIMI≥0.45, it is asthma or mild COPD; if 0.45>EIMI, it is moderate to severe COPD.

9. The system of claim 5, wherein, The excitation frequency ranges from [80 KHz, 120 KHz].

10. A storage medium, characterized by It stores a program capable of executing the coupling detection method according to any one of claims 1 to 4.

Images