Target impedance simulation circuit, element parameter determination method and impedance simulation jig

Abstract

The invention discloses a target impedance simulation circuit, an element parameter determination method and an impedance simulation jig. The target impedance analog circuit comprises a plurality of RC modules, wherein each RC module comprises a resistor unit and a capacitor unit which are connected in series; part or all of the RC modules are connected in parallel to simulate impedance data of a to-be-measured target. According to the technical scheme provided by the invention, the RC module is adopted to simulate the impedance value, so that the impedance behavior characteristics of the specified object under different frequencies can be accurately simulated, and the device can be flexibly and repeatedly used.

Description

Technical Field

[0001] The present invention relates to the field of impedance simulation technology, and in particular to a target impedance simulation circuit, a method for determining component parameters, and an impedance simulation fixture. Background Art

[0002] Currently, in scenarios requiring impedance measurement, such as bioimpedance measurement, it is often necessary to prepare standard impedance values ​​in advance to calibrate the measuring equipment. Existing calibration processes mostly employ analog circuits with fixed parameters, typically simple series-parallel pure resistive networks, which lack frequency response characteristics and are generally difficult to provide accurate standard values. Other approaches select a standard object and use its measured impedance value as the standard value; however, this approach relies heavily on experience, has poor repeatability and controllability, and struggles to guarantee calibration accuracy. Furthermore, in bioimpedance measurement, using human volunteers for comparative testing may pose ethical risks. Summary of the Invention

[0003] This invention provides a target impedance simulation circuit, a method for determining component parameters, and an impedance simulation fixture to improve the accuracy and flexibility of impedance simulation.

[0004] In a first aspect, embodiments of the present invention provide a target impedance simulation circuit, the circuit comprising: multiple sets of RC modules, each set of RC modules including a resistor unit and a capacitor unit connected in series; some or all of the RC modules are connected in parallel to simulate the impedance data of the target under test.

[0005] Optionally, the resistor unit is an adjustable resistor unit, and the capacitor unit is an adjustable capacitor unit, so as to simulate the impedance data of different targets under test or different target groups among the targets under test by adjusting the resistor unit and / or the capacitor unit.

[0006] Optionally, the circuit further includes a switching module for switching the selected RC module used to simulate impedance, so as to simulate impedance data of different targets under test or different target groups among the targets under test.

[0007] Optionally, the switching module includes one or more of a DIP switch, a jumper cap, and a programmable analog switch.

[0008] Optionally, the target to be measured includes bioimpedance and is divided into multiple target groups based on one or more of the following: location, age, sex, BMI, health status, and exercise status.

[0009] Secondly, embodiments of the present invention also provide a method for determining circuit element parameters, applied to the target impedance simulation circuit provided in any embodiment of the present invention, the method comprising:

[0010] Obtain impedance test data of the target under test;

[0011] The Cole-Cole model is fitted based on the impedance test data to determine the model parameters and obtain the target Cole-Cole model.

[0012] Multiple target RC modules are selected based on the model parameters, and the RC parameters of each target RC module are determined based on the parallel total response of each target RC module and the target Cole-Cole model.

[0013] Optionally, determining the RC parameters of each target RC module based on the parallel total response of each target RC module and the target Cole-Cole model includes:

[0014] The RC parameters are optimized by minimizing the amplitude-frequency or phase-frequency error between the total parallel response and the target Cole-Cole model.

[0015] Optionally, acquiring the impedance test data of the target under test includes:

[0016] Impedance test grouping data of multiple target groups under the target under test are obtained respectively, so as to determine the grouping RC parameters of the target grouping RC module to be selected for each target group.

[0017] Thirdly, embodiments of the present invention also provide a bioimpedance simulation fixture, which includes a target impedance simulation circuit determined by the circuit element parameter determination method provided in any embodiment of the present invention.

[0018] Optionally, the fixture may further include multiple interfaces, each of which corresponds to one of the target impedance simulation circuits, and each of the interfaces is connected to the corresponding electrode of the bioimpedance analysis device.

[0019] This invention provides a target impedance simulation circuit, including multiple sets of RC modules. Each set of RC modules includes a resistor unit and a capacitor unit connected in series. Some or all of the RC modules are connected in parallel to simulate the impedance data of the target under test. The target impedance simulation circuit provided by this invention, by using RC modules to simulate impedance values, can accurately simulate the impedance behavior characteristics of a specified object at different frequencies, and can be flexibly reused. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the target impedance simulation circuit provided in Embodiment 1 of the present invention;

[0021] Figure 2This is a schematic diagram of the component parameters required for each exemplary target group provided in Embodiment 1 of the present invention;

[0022] Figure 3 This is a flowchart of the method for determining circuit element parameters provided in Embodiment 2 of the present invention;

[0023] Figure 4 The amplitude and phase frequency response target curves obtained by the exemplary model conversion provided in Embodiment 1 of the present invention are shown below.

[0024] Figure 5 This is a schematic diagram showing the comparison results of exemplary RC parameters and model fitting effects provided in Embodiment 1 of the present invention. Detailed Implementation

[0025] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0026] Example 1

[0027] Figure 1 This is a schematic diagram of the target impedance simulation circuit provided in Embodiment 1 of the present invention. This embodiment is applicable to the calibration of equipment impedance values ​​in various multi-band measurement systems, such as bioimpedance measurement and rock physics impedance measurement. The circuit includes: multiple sets of RC modules, each set of RC modules including a resistor unit and a capacitor unit connected in series; some or all of the RC modules are connected in parallel to simulate the impedance data of the target under test.

[0028] Specifically, Figure 1 The example shown is an instance of three sets of RC modules connected in parallel. Figure 1 In addition to the portion shown, the circuit may also include other unselected RC modules. Each group of RC modules includes a resistor and a capacitor connected in series, such as... Figure 1 The three sets of RC modules consist of R1 and C1, R2 and C2, and R3 and C3 connected in series. The selected RC modules are connected in parallel; specifically, the resistor and capacitor units can be connected in parallel separately to simulate the impedance data of the target under test. In particular, a single set of RC modules can be selected to simulate the impedance data of the target under test.

[0029] The component parameters of each RC module (resistance values ​​of resistor units and capacitance values ​​of capacitor units, etc.) can be designed based on the fitting results of the Cole-Cole model of the target impedance to be measured. That is, the circuit can be considered an approximation of the physical construction of the Cole-Cole model, without relying on empirical values, thereby further improving the accuracy of the simulated impedance. For example... Figure 1 As shown, after the selected RC modules are connected in parallel, they can be connected in series with the high-frequency limiting resistance R∞ of the target under test. The voltage input terminal Vin and the voltage output terminal Vout are connected to the two ends of the series connection, respectively, so as to simulate the impedance behavior under applied electrical stimulation by connecting an external power supply.

[0030] In an optional implementation, the resistor unit is an adjustable resistor unit and the capacitor unit is an adjustable capacitor unit, so as to simulate the impedance data of different targets under test or different target groups among the targets under test by adjusting the resistor unit and / or the capacitor unit.

[0031] Specifically, significant differences can exist between different test targets, such as bioimpedance and rock physical impedance, or between different individuals of the same test target, such as the impedance values ​​of the elderly and young people. Existing analog circuits typically use fixed resistance values ​​for different test targets or different individuals of the same test target, resulting in poor simulation results. In this embodiment, adjustable resistor units (such as multi-turn potentiometers) and adjustable capacitor units (such as one adjustable capacitor or multiple capacitors connected in parallel to form a combined adjustment) can be used to construct an impedance response with a certain time constant. When switching test targets or target groups (different individuals of the same test target can be divided into different target groups based on certain classification criteria to reduce impedance differences within groups), impedance matching can be achieved by adjusting the parameters of the resistor unit and / or capacitor unit without physically replacing or resoldering the circuit, thereby significantly improving efficiency. The component parameters that need to be adjusted for different test targets or target groups can be designed based on the Cole-Cole model fitting results of the impedance of the corresponding test target or target group.

[0032] In an optional implementation, the circuit further includes a switching module for switching the selected RC module for simulating impedance to simulate impedance data of different targets under test or different groups of targets under test.

[0033] Specifically, when switching between the target under test or target groups, impedance matching can be achieved by combining RC modules with different numbers and parameters. That is, the required RC modules for different targets or target groups can be pre-installed in the circuit, and the component parameters can be designed based on the Cole-Cole model fitting results of the impedance of the corresponding target or target group. During application, the parallel structure of the RC modules can be flexibly configured by switching modules according to the specified target or target group to simulate the corresponding impedance data. Furthermore, adjustable resistor units and adjustable capacitor units can be used in the RC modules simultaneously to achieve rapid combination and adjustment, effectively covering the impedance variation range between different targets or different individuals, thereby further improving the flexibility of application in different scenarios. Optionally, the switching module includes one or more of DIP switches, jumper caps, and programmable analog switches.

[0034] In an optional implementation, the target to be measured includes bioimpedance, and is divided into multiple target groups based on one or more of the following: location, age, sex, BMI, health status, and exercise status. Bioimpedance analysis technology is widely used in various medical and health management scenarios such as body composition measurement, disease screening, and tissue status monitoring, and corresponding bioelectrical impedance analysis (BIA) devices have become widely used. The target impedance simulation circuit provided in this embodiment can be used to simulate the electrical impedance characteristics of human tissue at different frequencies, such as cell membrane capacitance effect and extracellular fluid conductivity. It can also pre-divide the target to be measured into multiple target groups based on one or more of the following: location, age, sex, BMI, health status, and exercise status, and set corresponding RC modules. In practical applications, the combination and parameters of RC modules can be adjusted based on the target groups to flexibly adjust the frequency response characteristics and more realistically simulate the impedance characteristics of biological tissue at different frequencies. This solves the problem of inaccurate calibration of multi-frequency BIA devices and improves the verification and debugging efficiency of BIA devices in multi-frequency modes.

[0035] The group classification is as follows: Age groups are categorized based on significant differences in tissue water content and conductivity, such as infants, children, adults, and the elderly; gender groups are categorized based on differences in water, muscle, and fat ratios, such as males and females; BMI groups are categorized as underweight, normal weight, overweight, and obese; health status groups are categorized as healthy, those with specific diseases (such as kidney disease or edema); and different exercise states may lead to different muscle tissue impedance structures, resulting in categories such as athletes and ordinary individuals. For example, using three sets of RC modules connected in parallel, the groups are categorized as children, adult males, adult females, the elderly, and athletes. The required component parameters for each target group are as follows: Figure 2As shown, by adjusting the parameters of different RC module combinations, the typical electrical impedance spectrum characteristics of different populations can be characterized.

[0036] The target impedance simulation circuit provided in this embodiment of the invention includes multiple sets of RC modules. Each set of RC modules includes a resistor unit and a capacitor unit connected in series. Some or all of the RC modules are connected in parallel to simulate the impedance data of the target under test. By using RC modules to simulate impedance values, the impedance behavior characteristics of a specified object at different frequencies can be accurately simulated, and the circuit can be flexibly reused.

[0037] Example 2

[0038] Figure 3 This is a flowchart illustrating the method for determining circuit element parameters provided in Embodiment 2 of the present invention. This embodiment is applicable to calibrating equipment impedance values ​​in various multi-band measurement systems, such as bioimpedance measurement and rock physics impedance measurement. This method is applied to the target impedance simulation circuit provided in any embodiment of the present invention, such as... Figure 3 As shown, the specific steps include the following:

[0039] S31. Obtain the impedance test data of the target under test.

[0040] S32. Fit the Cole-Cole model based on the impedance test data to determine the model parameters and obtain the target Cole-Cole model.

[0041] S33. Select multiple groups of target RC modules based on the model parameters, and determine the RC parameters of each target RC module based on the parallel total response of each target RC module and the target Cole-Cole model.

[0042] The Cole-Cole model is widely used to describe the frequency-dependent impedance behavior of biological tissues under alternating current stimulation. Its mathematical form can well reflect the cell membrane capacitance effect and tissue conductivity. However, the Cole-Cole model is a complex impedance function, and its expression contains fractional powers (such as (jωτ)). αThe target impedance is difficult to directly implement using traditional circuit structures (such as a single RC or RL circuit). Currently, there are two approximation methods: one is mathematical modeling, which obtains model parameters through fitting, but this method is only suitable for simulation scenarios and cannot be used for hardware implementation. The other is the equivalent circuit method, which typically uses a double-debye model or two RC series / parallel structures for coarse simulation. This method lacks accuracy and has limited frequency band coverage, making it difficult to cover the electrical changes of various targets from low to high frequencies. The circuit component parameter determination method provided in this embodiment can determine more accurate component parameters for the target impedance simulation circuit based on the Cole-Cole model, thereby achieving a physical approximation of the Cole-Cole model and solving the problem that the Cole-Cole model is difficult to implement at the circuit level.

[0043] Specifically, firstly, impedance test data of the target under test is obtained within a specified frequency range (e.g., 1kHz-1MHz for bioimpedance simulation). Then, the Cole-Cole model is nonlinearly fitted based on the obtained impedance test data to obtain model parameters, resulting in the fitted target Cole-Cole model. The Cole-Cole model formula is:

[0044]

[0045] Where R0 represents the low-frequency limiting resistance (in Ω), R∞ represents the high-frequency limiting resistance (in Ω), τ represents the time constant, α represents the Cole relaxation coefficient, and ω = 2πf, where f represents the frequency. Specifically, the Trust Region Reflective (TRF) algorithm can be used for fitting. The fitting objective is to find the four parameters (R0, R∞, τ, α) in the Cole-Cole model based on the impedance test data (fi, |Zi|) such that the model's magnitude |Zmodel(fi; R0, R∞, τ, α)| is closest to the true value. Fitting can begin by initializing the model parameters based on the required specified frequency range and empirical values, and then iterating until convergence (e.g., when the error change is small or the maximum number of iterations is reached). In each iteration, the impedance test data is first substituted into the calculation of the current model's magnitude |Zmodel|, then the residual vector ri = |Zmodel(fi)| - |Zmeasured(fi)| between the current model's magnitude and the measured impedance value is calculated, and the Jacobian matrix is ​​constructed. That is, the partial derivative of the residual vector with respect to each model parameter, where pi is the model parameter vector. Then, within the predefined trust region, a linear subproblem is solved: min δ ||J·δ+r|| 2subjectto||δ||≤Δ, where δ is the correction to the model parameters, and Δ represents the confidence radius (i.e., the range currently allowed to be searched in the parameter space). After obtaining the optimal δ, try to use δ to correct the original model parameters, i.e., p new =p old The algorithm increments by δ and calculates the new residuals. If the residuals decrease, the revised model parameters are accepted, and the confidence radius can be appropriately increased. Otherwise, the revision is rejected, the confidence radius is reduced, and the next iteration begins. After completing the iteration process, the optimal model parameters are obtained, thus determining the desired target Cole-Cole model.

[0046] After fitting, the complex impedance expression of the target Cole-Cole model can be converted into target amplitude-frequency and phase-frequency response curves in the logarithmic frequency domain. The fitting effect can be observed by plotting the actual measured impedance test data together. The amplitude-frequency response curve shows how tissue impedance changes with frequency, while the phase-frequency response curve shows how the tissue's capacitance / sensitivity changes with frequency, such as reflecting cell membrane polarization behavior. In other words, the curves reflect the frequency response characteristics of the tissue, and can be used for tissue analysis, disease prediction, component estimation, etc. For the conversion process, the Cole-Cole model formula itself is a complex function that varies with the angular frequency ω = 2πf. For each f, the amplitude-frequency response can be calculated as: The phase response is: Then, the logarithm of the frequency axis (log-frequency domain) can be taken and plotted (impedance generally changes drastically over a wide frequency range, such as the impedance of biological tissues which changes drastically between 1kHz and 1MHz), that is, the horizontal axis is log10(f), and the vertical axes are |Z(f)| and θ(f).

[0047] For example, the measured impedance data of muscle tissue at frequencies of 1kHz, 5kHz, 50kHz, 250kHz, 500kHz, and 1000kHz were 352.0, 341.1, 293.7, 260.1, 250.8, and 246.1, respectively. The initial model parameters were R0 = 360Ω, R∞ = 240Ω, and τ = 10. -5 s, α = 0.7, set initial confidence radius, R0: 50-100Ω, R∞: 30-80Ω, τ: 1e -5 -1e -4 s, α: 0.05-0.1, the model parameters obtained by the above fitting method are R0 = 800Ω, R∞ = 200Ω, τ = 10 -4Given s and α = 0.75, the converted amplitude and phase frequency response target curves are shown below. Figure 4 As shown.

[0048] After determining the target Cole-Cole model, the equivalent physical network can be constructed. First, N groups of target RC modules are selected and connected in parallel. The component parameters (Ri, Ci) of each target RC module correspond to a time constant τi = RiCi. Then, the total parallel response of all target RC modules is:

[0049]

[0050] R∞ can be directly adopted from the R∞ of the fitted target Cole-Cole model. Then, based on the parallel total response of each target RC module and the fitted target Cole-Cole model, the RC parameters (Ri, Ci) of each target RC module can be determined by combining multiple time constants to ensure that the impedance error between the finally constructed target impedance simulation circuit and the target Cole-Cole model is less than a certain range (e.g., 1%).

[0051] Optionally, determining the RC parameters of each target RC module based on the parallel total response of each target RC module and the target Cole-Cole model includes optimizing the RC parameters by minimizing the amplitude-frequency or phase-frequency error between the parallel total response and the target Cole-Cole model. Specifically, TRF, genetic algorithms, etc., can be used for the optimization process, which is similar to the fitting process described above, ultimately achieving an amplitude-frequency / phase-frequency relative error of <0.5%. Simultaneously, the fitted model parameters provide important reference value for fitting (Ri, Ci). In the Cole-Cole model, the dispersion of the frequency response is controlled by τ, and τi = RiCi is the time characteristic of each target RC module, determining its response frequency. If the fitted result is τ ≈ 1ms, it proves that each τi = RiCi should also be distributed around this order of magnitude, for example, in the range of [0.1ms, 10ms]. The number N of target RC modules can then be adjusted according to accuracy requirements and hardware limitations to achieve a balance between computational efficiency and practical feasibility, significantly improving the quality of the initial value while preventing the optimization algorithm from getting stuck in non-target regions. In the Cole-Cole model, α controls the diffusion width. When α approaches 0, it approaches a single time constant, at which point 1-2 RC modules are sufficient. When α approaches 1, the response spreads more widely, requiring more RC modules distributed across a wide frequency range. For example, when α = 0.2, only a few groups of τi concentrated in a specific frequency band are selected; when α = 0.8, 6-10 groups of τi are selected to cover from low to high frequencies (e.g., 1kHz-1MHz). In the model fitting example above, N = 6 target RC modules can be selected, with the initial time constant τi set at 10. -6 Up to 10-2 The logarithms are distributed at equal intervals to optimize the RC parameters. An example comparison of fitting results is shown below. Figure 5 As shown.

[0052] After determining the RC parameters of each target RC module, high-precision resistors and capacitors can be selected accordingly to realize the true impedance spectrum output of the physical circuit, rather than just fitting a mathematical model. At the same time, it is strictly based on the physical background of the Cole-Cole model, which is non-empirical modeling, making the impedance simulation more accurate.

[0053] In an optional implementation, acquiring the impedance test data of the target under test includes: acquiring impedance test grouping data for multiple target groups under the target under test, so as to determine the grouping RC parameters of the target grouping RC modules required for each target group. Specifically, based on the impedance test grouping data of each target group, the grouping RC parameters of the corresponding target grouping RC modules can be determined according to the above process to achieve the adjustability of the target impedance simulation circuit and support matching modeling and personalized configuration for different target groups. Alternatively, impedance test data of different targets under test can be acquired to determine the RC parameters of the target RC modules required for various targets under test, to support matching modeling and personalized configuration for different targets under test. Furthermore, a corresponding standardized RC module library can be established for each target group and / or each target under test, and standardized encapsulation can be performed to realize a plug-and-play impedance modeling system. The modular structure design also facilitates combination and expansion.

[0054] The circuit component parameter determination method provided in this invention first acquires the impedance test data of the target under test. Then, it fits the Cole-Cole model based on the impedance test data to determine the model parameters, obtaining the target Cole-Cole model. Next, based on the fitted model parameters, multiple sets of target RC modules are selected, and the RC parameters of each target RC module are determined based on the parallel total response of each target RC module and the target Cole-Cole model. By implementing the Cole-Cole model with high precision at the circuit level, a more accurate theoretical basis is provided for the target impedance simulation circuit, thereby improving the accuracy of impedance simulation.

[0055] Example 3

[0056] This invention also provides a bioimpedance simulation fixture, which includes a target impedance simulation circuit determined by the circuit element parameter determination method provided in any embodiment of this invention, and possesses the beneficial effects of the aforementioned target impedance simulation circuit and circuit element parameter determination method. Specifically, the fixture may include a printed circuit board (PCB), on which the target impedance simulation circuit can be arranged. The fixture can be designed to cover impedance moduli between 10Ω and 1500Ω, and the frequency response curve can be adjusted to simulate typical cell membrane and body fluid characteristics. Users can select RC module combination paths according to testing needs through DIP switches, jumper caps, or programmable analog switches in the circuit, and can also adjust the resistance and capacitance values ​​to achieve loading of different tissue characteristics, simulating human impedance characteristic curves of different body types, ages, and body parts.

[0057] Optionally, the fixture also includes multiple interfaces, each corresponding to a target impedance simulation circuit, and each interface is connected to the corresponding electrode of the bioimpedance analysis device. Specifically, wires can be led out from each interface and connected to the electrode plates of existing bioimpedance analysis (BIA) devices using clamps and conductive adhesive. This supports four-electrode or eight-electrode measurement methods, is compatible with various mainstream BIA analyzers, and allows for frequency scanning and error assessment. After calibration, it can be used for simulated human body modeling, algorithm verification, etc. Compared with calibration using human volunteers, this fixture avoids the influence of regional fluctuations, improves experimental consistency, and can be implemented using conventional electronic components, making it easy to manufacture and promote. It can also be used as a universal testing tool in the production and quality inspection of BIA devices by adapting to standard interfaces.

[0058] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A target impedance simulation circuit, characterized in that, include: Multiple sets of RC modules, each set of RC modules including a resistor unit and a capacitor unit connected in series; some or all of the RC modules are connected in parallel to simulate the impedance data of the target under test.

2. The target impedance simulation circuit according to claim 1, characterized in that, The resistor unit is an adjustable resistor unit, and the capacitor unit is an adjustable capacitor unit, so as to simulate the impedance data of different targets under test or different target groups among the targets under test by adjusting the resistor unit and / or the capacitor unit.

3. The target impedance simulation circuit according to claim 1, characterized in that, The circuit also includes a switching module for switching the selected RC module used to simulate impedance, so as to simulate impedance data of different targets under test or different target groups among the targets under test.

4. The target impedance simulation circuit according to claim 3, characterized in that, The switching module includes one or more of a DIP switch, a jumper cap, and a programmable analog switch.

5. The target impedance simulation circuit according to claim 2 or 3, characterized in that, The targets to be measured include bioimpedance, and are divided into multiple target groups based on one or more of the following: location, age, sex, BMI, health status, and exercise status.

6. A method for determining circuit element parameters, characterized in that, The method, applied to a target impedance simulation circuit as described in any one of claims 1-5, comprises: Obtain impedance test data of the target under test; The Cole-Cole model is fitted based on the impedance test data to determine the model parameters and obtain the target Cole-Cole model. Multiple target RC modules are selected based on the model parameters, and the RC parameters of each target RC module are determined based on the parallel total response of each target RC module and the target Cole-Cole model.

7. The method for determining circuit element parameters according to claim 6, characterized in that, The determination of the RC parameters of each target RC module based on the parallel total response of each target RC module and the target Cole-Cole model includes: The RC parameters are optimized by minimizing the amplitude-frequency or phase-frequency error between the total parallel response and the target Cole-Cole model.

8. The method for determining circuit element parameters according to claim 6, characterized in that, The acquisition of impedance test data of the target under test includes: Impedance test grouping data of multiple target groups under the target under test are obtained respectively, so as to determine the grouping RC parameters of the target grouping RC module to be selected for each target group.

9. A bioimpedance simulation fixture, characterized in that, This includes a target impedance simulation circuit determined by applying the circuit element parameter determination method as described in any one of claims 6-8.

10. The bioimpedance simulation fixture according to claim 9, characterized in that, The fixture also includes multiple interfaces, each of which corresponds to a target impedance simulation circuit, and each interface is connected to the corresponding electrode of the bioimpedance analysis device.

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