CN114113227A - Measuring system and measuring method - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 34
- 238000001453 impedance spectrum Methods 0.000 claims abstract description 20
- 238000004088 simulation Methods 0.000 claims abstract description 16
- 210000001161 mammalian embryo Anatomy 0.000 claims abstract description 12
- 238000013178 mathematical model Methods 0.000 claims abstract description 12
- 238000005259 measurement Methods 0.000 claims abstract description 12
- 238000000691 measurement method Methods 0.000 claims abstract description 7
- 238000012937 correction Methods 0.000 claims description 12
- 230000002068 genetic effect Effects 0.000 claims description 11
- 239000011159 matrix material Substances 0.000 claims description 11
- 230000014509 gene expression Effects 0.000 claims description 10
- 238000001228 spectrum Methods 0.000 claims description 9
- 238000009792 diffusion process Methods 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 6
- 238000005457 optimization Methods 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 5
- 230000001939 inductive effect Effects 0.000 claims description 5
- 101150030983 GEP gene Proteins 0.000 claims description 3
- 230000035772 mutation Effects 0.000 claims description 3
- 239000003814 drug Substances 0.000 abstract description 4
- 229940079593 drug Drugs 0.000 abstract description 3
- 230000011712 cell development Effects 0.000 abstract 1
- 239000004793 Polystyrene Substances 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- 229920003229 poly(methyl methacrylate) Polymers 0.000 description 4
- 239000004926 polymethyl methacrylate Substances 0.000 description 4
- 229920002223 polystyrene Polymers 0.000 description 4
- 238000004611 spectroscopical analysis Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 238000011871 bio-impedance analysis Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000013020 embryo development Effects 0.000 description 2
- 239000011859 microparticle Substances 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 239000000725 suspension Substances 0.000 description 2
- 244000309466 calf Species 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000010362 genome editing Methods 0.000 description 1
- 238000001566 impedance spectroscopy Methods 0.000 description 1
- 239000004005 microsphere Substances 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
- G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Abstract
The application relates to a measuring system and a measuring method, which are technically characterized in that: firstly, acquiring a characteristic relation between cell position change and impedance in a simulation mode, and establishing a mathematical model between the cell position change and the impedance; secondly, correcting impedance data according to the mathematical model to eliminate the influence of the position on the impedance and improve the measurement precision; and finally, extracting the electrical characteristics of the biological embryo by an impedance spectrum equivalent circuit automatic fitting algorithm. The measurement system and the measurement method provided by the application have important significance for researching drug response and cell development.
Description
Technical Field
The invention relates to a method for combining measurement and data processing, in particular to an accurate measurement method for electrical characteristics in an embryo development process.
Background
As the single cell is the minimum structure and function unit of the life tissue, the detection of the development process of the embryo has extremely important significance for revealing the secret of life and researching the drug response.
However, conventional detection methods are as follows: single cell sequencing, a gene editing technique is both complex and expensive. Bioimpedance Spectroscopy (BIS) has been widely used in industry, biology and medicine as a label-free, non-radiative, non-invasive new technology.
The bioimpedance spectroscopy method can quantitatively judge the type, size and number of cells (one-dimensional information), and is widely applied. Such as:
reference 1: JP2011050765A provides a method and apparatus for performing a bio-impedance analysis. In some embodiments, an equivalent circuit frequency response model is provided that provides improved correlation with MRI data. The frequency response model takes into account body composition, including fat composition of the body part.
Reference 2: WO2005027717a2 provides a method and apparatus for bioimpedance analysis. Data obtained by bioimpedance spectroscopy (BIS) and MRI on the calf of the subject demonstrate that the correlation can be improved compared to a single frequency analysis at 50kHz and analysis using a conventional Cole-Cole model.
However, the detection accuracy of the bio-impedance spectrum is often affected by the position variation of the object to be detected, and therefore, the electrical characteristic parameters of the cells in the development process cannot be accurately extracted by directly using the measured data of the bio-impedance spectrum.
Disclosure of Invention
The invention aims to solve the problem of low detection precision of the existing biological impedance spectroscopy method and provides a measuring system and a measuring method.
A measurement system, comprising: the system comprises a sensor, a position measuring system, a numerical simulation system, a position correction system and an electrical characteristic parameter extraction system;
the sensor is used for measuring the impedance of the cell;
the position measuring system is used for measuring the position of the cell in the sensor;
the numerical simulation system is used for obtaining the characteristic relation between the cell position and the impedance;
the position correction system is used for obtaining impedance after position correction;
the electrical characteristic parameter extraction system is used for extracting the electrical characteristic parameters by utilizing a self-fitting algorithm of the equivalent circuit of the biological impedance spectrum.
Further, the position measuring system adopts an electron microscope.
A measuring method comprises the following steps:
step one, obtaining a characteristic relation between cell positions and impedance: obtaining values between a plurality of cell positions and impedance through numerical simulation; fitting and constructing a mathematical model between the impedance and the cell position by utilizing a polynomial;
measuring the impedance of the cell in a sensor, and observing the coordinate position of the cell through an electron microscope;
step three, position correction: correspondingly correcting the impedance obtained in the second step according to the mathematical model between the impedance and the cell position obtained in the first step and the coordinate position of the cell recorded in the second step;
and step four, extracting the electrical characteristic parameters by utilizing a self-fitting algorithm of the equivalent circuit of the biological impedance spectrum according to the data corrected in the step three.
Further, for the first step, obtaining a mathematical model between the position of the cell in the sensor and the impedance through numerical simulation, specifically comprising:
s1-1, performing grid division on the simulation area;
s1-2, randomly selecting any one position as the central coordinate position of the embryo, wherein the coordinate is expressed as (x)c，yc) The frequency f is an arbitrary frequency fbAnd the measured impedance value is expressed as Zbc；
Selecting j groups of central coordinates, and selecting n groups of frequencies;
then, the impedance value matrix Z is recorded:
recording position matrix X:
s1-3, solving a matrix A:
A＝ZX-1
wherein:
further, step two records the actual position of the embryo in the sensor as (x)p,yp) Recorded at a frequency fgImpedance of Zg(ii) a Then the position is converted to the reference position (x)r,yr) Has an impedance of Z'g：
Further, the fourth step specifically comprises the following substeps:
s4-1, constructing an equivalent circuit model according to a gene expression algorithm (GEP):
setting the functional symbol of GEP as { "S" } and "P" };
setting the terminal symbols of the GEP as { "R", "C", "L", "CPE", "Z _ w" }basedon common electrical elements of the equivalent circuit of the bioimpedance spectrum;
where "S" represents a series relationship, "P" represents a parallel relationship, "R" represents a resistive element, "C" represents a capacitive element, "L" represents an inductive element, "CPE" represents a constant phase element, "Z _ w" represents a diffusion impedance, and an impedance expression corresponding to a termination symbol is as follows:
ZL＝jwL
t＝h(n-1)+1
l＝t+h
in the formula:
z _ c represents: capacitive reactance in units of: omega;
ω represents: angular frequency in rad/s;
c represents: capacitance, in units of: c;
ZLrepresents: inductive reactance, in units of: omega;
Zωrepresents: diffusion impedance, in units of: omega;
y represents: the modulus of the Warburg admittance is specifically in the range of (0,1), and the unit is dimensionless;
ZCPErepresents: the constant phase impedance, unit is: omega;
Y0represents: the form factor, the magnitude or modulus after the stripping frequency of the constant phase element, generally takes the value (0,1)
n represents: power exponent, which takes value in the range of [ -1,1 ];
t represents: tail length, dimensionless;
h represents: head length, dimensionless;
l represents: the total length of the GEP gene is dimensionless;
l represents: inductance, in units of: h;
j imaginary unit;
according to the GEP individual composition principle, firstly, the head length h and the head length n are required to be set according to the requirement, and the individual length can be known at the moment;
s4-2, forming an equivalent circuit model through GEP coding and decoding modes, wherein the father node of the child node is a functional symbol, and the symbol corresponds to the combination relation of the electrical elements:
an equivalent circuit model established based on GEP is used for fitting a biological impedance spectrum through a genetic algorithm:
firstly, initializing an electrical characteristic parameter population and a maximum iteration number by a GA according to an electrical element contained in an equivalent circuit model;
next, GA selection probability P is setsFor ensuring that better individuals in each generation can have a greater probability of being handed over to the next generation, and additionally setting the crossover probability PcAnd the mutation probability PmThe method is used for generating new individuals and avoiding the solution set from falling into local optimum, thereby ensuring that the current equivalent circuit can obtain the optimum fitness by the GA algorithm each time;
thirdly, feeding back the optimal fitness obtained by the GA to the individual of the GEP for the optimization of the equivalent circuit;
and finally, obtaining the optimal equivalent circuit and the corresponding electrical parameters thereof through GEP optimization and GA calculation fitting, and further obtaining the electrical characteristic parameters contained in the biological impedance spectrum.
The technical scheme of the invention has the advantages that:
1) the first invention of the present application is that: the phenomenon of "the cell position differs in the sensor, and the measured impedance differs" is found. Based on this phenomenon, in order to study the impedance of different cells or cells at different stages, it is necessary to remove the influence of the position of the impedance actually measured.
Based on this problem, the inventors found through a large number of experiments that the relationship between the position of the cell in the sensor and the impedance satisfies the following equation:
accordingly, steps one and three are proposed to eliminate the above-mentioned position influence.
2) The second invention of the present application is: the present application can be used to measure electrical characteristic parameters of cells; the method has good application prospect when being used for researching drug reaction.
Drawings
The invention will be further described in detail with reference to examples of embodiments shown in the drawings to which, however, the invention is not restricted.
Fig. 1 is a flowchart of a measurement method of the present application.
Detailed Description
The objects, advantages and features of the present invention will be explained by the following non-restrictive description of preferred embodiments thereof. The embodiments are merely exemplary for applying the technical solutions of the present invention, and any technical solution formed by replacing or converting the equivalent thereof falls within the scope of the present invention claimed.
The first embodiment: integral framework design for precision measurement method]
The present invention is further described with reference to fig. 1.
An accurate measurement method for electrical characteristics in an embryo development process comprises the following steps:
step one, obtaining a characteristic relation between cell positions and impedance: obtaining a numerical value between the cell position and the impedance through numerical simulation;
fitting and constructing a mathematical model between the impedance and the cell position by utilizing a polynomial;
measuring the impedance of the cell in a sensor, and observing the coordinate position of the cell through an electron microscope;
step three, position correction: and correspondingly correcting the impedance obtained in the second step according to the mathematical model between the impedance and the cell position obtained in the first step and the coordinate position of the cell recorded in the second step, so that the influence of position factors on the impedance is avoided, and high-precision measurement is realized.
And step four, extracting the electrical characteristic parameters by utilizing a self-fitting algorithm of the equivalent circuit of the biological impedance spectrum according to the data corrected in the step three.
In view of the above-mentioned measurement method, the first embodiment also provides a measurement system, and the composition and function of the measurement system are shown in table 1.
TABLE 1
For the fourth step, extracting the electrical characteristics by using a self-fitting algorithm of the equivalent circuit of the biological impedance spectrum; the automatic fitting algorithm is a mixed algorithm combining a genetic expression algorithm and a genetic algorithm, wherein the genetic expression algorithm realizes the construction of a biological impedance spectrum equivalent circuit, and the genetic algorithm realizes the fitting of a biological impedance spectrum and the calculation of electrical parameters based on the constructed equivalent circuit model.
Example two: detailed operation of numerical simulation System]
And the specific work of the numerical simulation system is the work of the step one correspondingly.
For step one, obtaining a mathematical model between the position of the cell in the sensor and the impedance through numerical simulation, specifically comprising:
s1-1, performing grid division on the simulation area;
s1-2, randomly selecting any one position as the central coordinate position of the embryo, wherein the coordinate is expressed as (x)c，yc) The frequency f is an arbitrary frequency fbAnd the measured impedance value is expressed as Zbc；
Selecting j groups of central coordinates, and selecting n groups of frequencies;
then, the impedance value matrix Z is recorded:
recording position matrix X:
s1-3, solving a matrix A:
the above matrix is expressed by the following formula: z is A. X
Therefore, the following steps are carried out: a ═ ZX-1(i.e., the individual values in matrix A can be solved for)
Wherein the content of the first and second substances,
s1-4, establishing impedance and fitting the cell position to establish a corresponding mathematical model:
example three: detailed operation of the position correction system]
One of the problems with the method of embodiment one is "how to perform position correction", which is, in particular, that the embryo may be shifted during the actual measurement process, so that the embryo may be located at different positions of the sensor; however, when the embryo is located at different positions of the sensor, the measured impedance is different, and therefore, the effect is difficult to evaluate.
That is, the actual coordinate position (x) of the embryo in the sensor at each measurementp,yp) Are necessarily different, and therefore, the impedance values measured at different coordinate positions need to be converted into the same coordinate positionPosition (reference position (x)r,yr) Carry out comparative analysis, and further avoid the influence of position factors on impedance to obtain a high-precision measurement result.
For this problem, the following processing is performed:
the correction process comprises the following steps:
step two records the actual position of the embryo in the sensor as (x)p,yp) Recorded at a frequency fgImpedance of Zg；
Then the position is converted to the reference position (x)r,yr) Has an impedance of Z'g：
Example four: extraction of electrical characteristics by using self-fitting algorithm of equivalent circuit of bioimpedance spectrum]
For the method of the first embodiment, one of the problems is how to extract the electrical characteristics by using the bioimpedance spectrum equivalent circuit self-fitting algorithm, and for the third step, the electrical characteristic parameters are extracted by using the bioimpedance spectrum equivalent circuit self-fitting algorithm; the automatic fitting algorithm is a mixed algorithm combining a genetic expression algorithm and a genetic algorithm, wherein the genetic expression algorithm realizes the construction of a biological impedance spectrum equivalent circuit, and the genetic algorithm realizes the fitting of a biological impedance spectrum and the extraction of electrical characteristic parameters based on the constructed equivalent circuit. Specifically, the method comprises the following steps:
s4-1, constructing an equivalent circuit model according to a gene expression algorithm (GEP):
setting the functional symbol of GEP as { "S" } and "P" };
setting the terminal symbols of the GEP as { "R", "C", "L", "CPE", "Z _ w" }basedon common electrical elements of the equivalent circuit of the bioimpedance spectrum;
where "S" represents a series relationship, "P" represents a parallel relationship, "R" represents a resistance element, "C" represents a capacitance element, "L" represents an inductance element, "CPE" represents a constant phase element, "Z _ w" represents a diffusion impedance, and impedance expressions corresponding to terminal symbols are shown in (2) to (6).
ZL＝jwL
t＝h(n-1)+1
l＝t+h
Z _ c represents: capacitive reactance in units of: omega;
ω represents: angular frequency in rad/s;
c represents: capacitance, in units of: c;
ZLrepresents: inductive reactance, in units of: omega;
Zωrepresents: diffusion impedance, in units of: omega;
y represents: the modulus of the Warburg admittance is specifically in the range of (0,1), and the unit is dimensionless;
ZCPErepresents: the constant phase impedance, unit is: omega;
Y0represents: the form factor, the magnitude or modulus after the stripping frequency of the constant phase element, generally takes the value (0,1)
n represents: power exponent, which takes value in the range of [ -1,1 ];
t represents: tail length, dimensionless;
h represents: head length, dimensionless;
l represents: the total length of the GEP gene is dimensionless;
l represents: inductance, in units of: h;
j imaginary unit;
according to the GEP individual composition principle, the head lengths h and n are firstly set according to the needs of researchers, and the individual length can be obtained by a formula (8).
S4-2, forming an equivalent circuit model through GEP coding (binary tree hierarchical traversal) and decoding (binary tree post-order traversal), wherein the father node of the child node is a functional symbol, and the symbol corresponds to the combination relationship of the electrical elements.
Based on the equivalent circuit model established by the GEP, fitting a bioimpedance spectrum by a Genetic Algorithm (GA):
firstly, initializing an electrical characteristic parameter population and a maximum iteration number by a GA according to an electrical element contained in an equivalent circuit model;
next, GA selection probability P is setsFor ensuring that better individuals in each generation can have a greater probability of being handed over to the next generation, and additionally setting the crossover probability PcAnd the mutation probability PmIs used for generating new individuals and avoiding the solution set from falling into local optimum, thereby ensuring that the GA algorithm can ensure that the current equivalent circuit can obtain the best fitness (best fit with the biological impedance spectrum)
And thirdly, feeding back the optimal fitness obtained by the GA to the individual of the GEP for the optimization of the equivalent circuit.
And finally, obtaining the optimal equivalent circuit and the corresponding electrical parameters thereof through GEP optimization and GA calculation fitting, and further obtaining the electrical characteristic parameters contained in the biological impedance spectrum.
In fig. 1: and thirdly, the fitting of the equivalent circuit is the process of constructing the equivalent circuit by the GEP, and the calculation of the electrical parameters can be completed by fitting the bio-impedance spectrum through a GA algorithm.
This method has been successfully used by the applicant for equivalent circuit self-fitting of microparticle suspensions;
applicants first measured the impedance data for 10 μm polymethyl Methacrylate (10 PMMA), 10 μm Polystyrene Magnetic microspheres (10 μm Polystyrene Magnetic,10PSM), 10 μm,20 μm 30 μm Polystyrene (10 μm,20 μm 30 μm Polystyrene,10PS,20PS,30 PS).
And secondly, fitting of the PMMA bioimpedance spectrum is achieved by using an equivalent circuit self-fitting algorithm (the fitting accuracy is higher than 99%), and the bioimpedance spectra of the rest four types of microparticle suspensions are fitted based on the PMMA equivalent circuit model.
And finally, displaying the particle diameter and the identification of the particle type according to the electrical characteristic parameters reflected by the equivalent circuit self-fitting algorithm.
The above-mentioned embodiments are only for convenience of description, and are not intended to limit the present invention in any way, and those skilled in the art will understand that the technical features of the present invention can be modified or changed by other equivalent embodiments without departing from the scope of the present invention.
Claims (7)
1. A measurement system, comprising: the system comprises a sensor, a position measuring system, a numerical simulation system, a position correction system and an electrical characteristic parameter extraction system;
the sensor is used for measuring the impedance of the cell;
the position measuring system is used for measuring the position of the cell in the sensor;
the numerical simulation system is used for obtaining the characteristic relation between the cell position and the impedance;
the position correction system is used for obtaining impedance after position correction;
the electrical characteristic parameter extraction system is used for extracting the electrical characteristic parameters by utilizing a self-fitting algorithm of the equivalent circuit of the biological impedance spectrum.
2. A measuring system according to claim 1, wherein the position measuring system employs an electron microscope.
3. A measuring method is characterized by comprising the following steps:
step one, obtaining a characteristic relation between cell positions and impedance: obtaining values between a plurality of cell positions and impedance through numerical simulation; fitting and constructing a mathematical model between the impedance and the cell position by utilizing a polynomial;
measuring the impedance of the cell in a sensor, and observing the coordinate position of the cell through an electron microscope;
step three, position correction: correspondingly correcting the impedance obtained in the second step according to the mathematical model between the impedance and the cell position obtained in the first step and the coordinate position of the cell recorded in the second step;
and step four, extracting the electrical characteristic parameters by utilizing a self-fitting algorithm of the equivalent circuit of the biological impedance spectrum according to the data corrected in the step three.
4. A measurement method according to claim 3, wherein for step one, a mathematical model between the position of the cell in the sensor and the impedance is obtained by numerical simulation, and the method specifically comprises:
s1-1, performing grid division on the simulation area;
s1-2, randomly selecting any one position as the central coordinate position of the embryo, wherein the coordinate is expressed as (x)c，yc) The frequency f is an arbitrary frequency fbAnd the measured impedance value is expressed as Zbc；
Selecting j groups of central coordinates, and selecting n groups of frequencies;
then, the impedance value matrix Z is recorded:
recording position matrix X:
s1-3, solving a matrix A:
A＝ZX-1
wherein:
5. a method of measurement according to claim 3, wherein step two records the actual position of the embryo in the sensor as (x)p,yp) Recorded at a frequency fgImpedance of Zg(ii) a Then the position is converted to the reference position (x)r,yr) Has an impedance of Z'g：
6. A measuring method according to claim 3, characterized in that step four specifically comprises the following substeps:
s4-1, constructing an equivalent circuit model according to a gene expression algorithm (GEP):
setting the functional symbol of GEP as { "S" } and "P" };
setting the terminal symbols of the GEP as { "R", "C", "L", "CPE", "Z _ w" }basedon common electrical elements of the equivalent circuit of the bioimpedance spectrum;
where "S" represents a series relationship, "P" represents a parallel relationship, "R" represents a resistive element, "C" represents a capacitive element, "L" represents an inductive element, "CPE" represents a constant phase element, "Z _ w" represents a diffusion impedance, and an impedance expression corresponding to a termination symbol is as follows:
ZL＝jwL
t＝h(n-1)+1
l＝t+h
in the formula:
z _ c represents: capacitive reactance in units of: omega;
ω represents: angular frequency in rad/s;
c represents: capacitance, in units of: c;
ZLrepresents: inductive reactance, in units of: omega;
Zωrepresents: diffusion impedance, in units of: omega;
y represents: the modulus of the Warburg admittance is specifically in the range of (0,1), and the unit is dimensionless;
ZCPErepresents: the constant phase impedance, unit is: omega;
Y0represents: the form factor, the magnitude or modulus after the stripping frequency of the constant phase element, generally takes the value (0,1)
n represents: power exponent, which takes value in the range of [ -1,1 ];
t represents: tail length, dimensionless;
h represents: head length, dimensionless;
l represents: the total length of the GEP gene is dimensionless;
l represents: inductance, in units of: h;
j imaginary unit;
according to the GEP individual composition principle, the head length h and the head length n are required to be set according to the requirement, and the individual length can be known at the moment.
7. A measuring method according to claim 6, further comprising the further sub-steps of: s4-2, forming an equivalent circuit model through GEP coding and decoding modes, wherein the father node of the child node is a functional symbol, and the symbol corresponds to the combination relation of the electrical elements:
an equivalent circuit model established based on GEP is used for fitting a biological impedance spectrum through a genetic algorithm:
firstly, initializing an electrical characteristic parameter population and a maximum iteration number by a GA according to an electrical element contained in an equivalent circuit model;
next, GA selection probability P is setsFor ensuring that better individuals in each generation can have a greater probability of being handed over to the next generation, and additionally setting the crossover probability PcAnd the mutation probability PmThe method is used for generating new individuals and avoiding the solution set from falling into local optimum, thereby ensuring that the current equivalent circuit can obtain the optimum fitness by the GA algorithm each time;
thirdly, feeding back the optimal fitness obtained by the GA to the individual of the GEP for the optimization of the equivalent circuit;
and finally, obtaining the optimal equivalent circuit and the corresponding electrical parameters thereof through GEP optimization and GA calculation fitting, and further obtaining the electrical characteristic parameters contained in the biological impedance spectrum.
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