CN-122016872-A - Microwave biosensing real-time monitoring platform suitable for low concentration CEA in serum

CN122016872ACN 122016872 ACN122016872 ACN 122016872ACN-122016872-A

Abstract

The invention discloses a microwave biological sensing real-time monitoring platform suitable for CEA with low concentration in serum, and relates to the technical field of microwave biological sensing. The invention carries out quantitative analysis on serum protein characteristic parameters through an interference evaluation unit to obtain four interference coefficients, calculates interference state values in a normalized mode, carries out interference grading judgment according to the interference state values to obtain interference object information, carries out grading separation shielding through an interference separation unit to solve the problem that low-concentration CEA microwave response signals are covered because serum matrix interference cannot be accurately identified and removed, and also completes microwave sensing monitoring and real-time evaluation output on a serum sample subjected to interference optimization through a sample parameter acquisition module, a serum interference separation module, a microwave monitoring module and a microwave evaluation real-time output module to solve the problems that the existing low-concentration CEA detection sensitivity and specificity of serum are insufficient and real-time monitoring cannot be realized, and realizes real-time microwave biosensing detection.

Inventors

YAO ZHAO
LI YUANYUE
ZHANG YUE
LI XINLIN

Assignees

青岛大学

Dates

Publication Date: 20260512
Application Date: 20260317

Claims (10)

1. A microwave biosensing real-time monitoring platform suitable for low concentration CEA in serum, comprising: The sample parameter acquisition module is used for acquiring data of a serum sample to obtain serum protein characteristic parameters, and then conveying the serum protein characteristic parameters to the serum interference separation module; The serum interference separation module comprises an interference evaluation unit and an interference separation unit, wherein the interference evaluation unit extracts serum protein characteristic parameters based on a sample data set, then performs interference evaluation analysis on the serum protein characteristic parameters to obtain interference information, and transmits the interference information to the interference separation unit; The microwave monitoring module is used for carrying out microwave sensing monitoring on the optimized serum sample to obtain microwave sensing parameters and transmitting the parameters to the microwave evaluation real-time output module; The microwave evaluation real-time output module is used for receiving the microwave sensing parameters, performing microwave state evaluation to obtain a serum CEA state report, and then outputting the serum CEA state report in real time.
2. The real-time microwave biosensing monitoring platform suitable for low-concentration CEA in serum, which is disclosed in claim 1, is characterized in that the serum sample is subjected to data acquisition to obtain serum protein characteristic parameters, specifically, the serum sample is subjected to data acquisition through an installed sample acquisition sensing group to obtain the serum protein characteristic parameters, the sample acquisition sensing group comprises, but is not limited to, a double-frequency interdigital transducer, a planar microwave resonance sensor, a microwave signal generator and a particle size inversion DSP module, and the serum protein characteristic parameters comprise double-frequency time sequence microwave S parameter data, microwave dielectric response data, dielectric characteristic synchronous data and multi-frequency microwave S parameter data.
3. The microwave biosensing real-time monitoring platform suitable for low concentration CEA in serum according to claim 1, wherein the interference evaluation analysis is performed on the serum protein characteristic parameter to obtain the interference information, and the specific analysis flow is as follows: identifying serum protein characteristic parameters to obtain double-frequency time sequence microwave S parameter data, microwave dielectric response data, dielectric characteristic synchronous data and multi-frequency microwave S parameter data; Performing characteristic quantitative analysis on the double-frequency time sequence microwave S parameter data to obtain a double-frequency attenuation difference coefficient, performing characteristic quantitative analysis on the microwave dielectric response data to obtain a dielectric interference duty ratio coefficient, performing characteristic quantitative analysis on the dielectric characteristic synchronous data to obtain a coupling interference coefficient, performing characteristic quantitative analysis on the multi-frequency microwave S parameter data to obtain a particle size distribution interference coefficient; The method comprises the steps of carrying out normalization processing on a dual-frequency attenuation difference coefficient, a dielectric interference duty ratio coefficient, a coupling interference coefficient and a particle size distribution interference coefficient, mapping the two-frequency attenuation difference coefficient, the dielectric interference duty ratio coefficient, the coupling interference coefficient and the particle size distribution interference coefficient into intervals [0,1], calculating and outputting an interference state value through a preset comprehensive coupling formula, dividing the interference state value into a low-interference state interval and an interference separation state interval according to a preset state value dividing value, generating interference object information to be interference-free information when the interference state value of a current serum sample is in the low-interference state interval, and generating interference object information to be an interference separation starting signal when the interference state value is in the interference separation state interval.
4. The real-time monitoring platform for microwave biosensing suitable for low concentration CEA in serum according to claim 3, wherein the characteristic quantitative analysis is performed on the double-frequency time sequence microwave S parameter data to obtain a double-frequency attenuation difference coefficient, which specifically comprises: Obtaining average values of transmission microwave S parameter signals acquired for multiple times at low frequency and high frequency based on double-frequency time sequence microwave S parameter data, respectively marking the average values corresponding to the low frequency and the high frequency as a low-frequency microwave time domain signal and a high-frequency microwave time domain signal; And then inputting the two fractional order attenuation energies into a set nonlinear difference coefficient calculation formula to calculate so as to obtain a double-frequency attenuation difference coefficient.
5. The microwave biosensing real-time monitoring platform suitable for low concentration CEA in serum of claim 4, wherein the microwave dielectric response data is subjected to characteristic quantitative analysis to obtain a dielectric interference duty ratio coefficient, and the microwave biosensing real-time monitoring platform is characterized in that a dielectric response time domain sequence is obtained based on the microwave dielectric response data and is substituted into a Gaussian radial basis function to obtain a regeneration kernel function Hilbert space, and the dielectric interference duty ratio coefficient is obtained by analyzing the dielectric response time domain sequence and the regeneration kernel function Hilbert space based on orthogonal projection of a set RKHS space algorithm.
6. The real-time microwave biosensing monitoring platform suitable for low concentration CEA in serum of claim 5, wherein the characteristic quantitative analysis of the dielectric characteristic synchronization data is performed to obtain a coupling interference coefficient, which specifically comprises: obtaining a microwave attenuation coefficient sequence and a resonant frequency offset sequence based on dielectric characteristic synchronous data, and performing empirical distribution function transformation to obtain a uniform distribution sequence, namely analyzing the empirical distribution function to obtain a microwave attenuation uniform distribution sequence and a resonant uniform distribution sequence; Inputting a microwave attenuation uniform distribution sequence and a resonance uniform distribution sequence into a Gumbel Copula function, wherein the Gumbel Copula function comprises a microwave attenuation uniform distribution value and resonance uniform distribution value combined distribution characteristic corresponding to the two uniform distribution sequences of each sample microwave S parameter sampling point and Copula dependent parameters; And inputting the optimal dependent parameters into a coupling interference quantization formula to calculate to obtain a coupling interference coefficient.
7. The real-time monitoring platform for microwave biosensing suitable for low concentration CEA in serum of claim 6, wherein the characteristic quantitative analysis of the multi-frequency microwave S parameter data is performed to obtain a particle size distribution interference coefficient, which specifically comprises: The method comprises the steps of obtaining a particle size average value and a particle size quality ratio based on multi-frequency microwave S parameter data, obtaining corresponding effective separation particle size intervals, carrying out weight giving analysis on particle size values of interference proteins and the effective separation particle size intervals to obtain weight adjustment factors of the particle size intervals, carrying out weight average calculation on the particle sizes based on the weight adjustment factors to obtain particle size weighted average values, and calculating and outputting particle size distribution interference coefficients through a non-uniformity interference calculation formula.
8. The real-time monitoring platform for microwave biosensing suitable for CEA with low concentration in serum according to claim 6, wherein the Copula dependent parameters are subjected to maximum likelihood estimation solution analysis to obtain optimal dependent parameters, specifically, a microwave attenuation uniform distribution sequence and a resonance uniform distribution sequence which are actually measured and correspond to a preset distribution sequence group number are substituted into a Gumbel Copula function in sequence, and all results are multiplied to obtain likelihood functions related to the Copula dependent parameters, and the Copula dependent parameters obtained through maximum likelihood estimation solution are optimally solved, hereinafter, the optimal dependent parameters are abbreviated as optimal dependent parameters.
9. The microwave biosensing real-time monitoring platform suitable for low concentration CEA in serum according to claim 1, wherein the interference separation unit receives the interference information and performs interference separation shielding execution to obtain an optimized serum sample, specifically, if the interference information of the current serum sample is identified as no interference information, the interference information is directly marked as the optimized serum sample, and when the interference information is identified as an interference separation start signal, the interference separation shielding execution is performed.
10. The microwave biosensing real-time monitoring platform suitable for low concentration CEA in serum of claim 2, wherein the double-frequency time sequence microwave S parameter data is S parameter time domain and frequency domain signals of serum samples at low frequency and high frequency of a set frequency; the microwave dielectric response data is broadband sweep frequency microwave excitation which emits a resonant frequency band covering a microwave sensing unit, microwave network scattering parameters are collected, and a dielectric response time domain sequence is obtained through inverse Fourier transform; the dielectric characteristic synchronous data is a microwave S parameter attenuation coefficient sequence and a resonance frequency offset sequence of a serum sample in a set sampling period at low frequency; The multi-frequency microwave S parameter data are S parameter attenuation coefficients at low frequency, medium frequency and high frequency of a set frequency, the microwave attenuation of each frequency is inverted based on a Rayleigh scattering model to obtain particle size intervals of various interference proteins, average value calculation is carried out based on the particle size intervals to obtain particle size average values, the ratio of the mass of the interference proteins in each particle size interval to the mass of the total interference proteins, namely the particle size mass ratio, the particle size average value and the particle size mass ratio are integrated to obtain the multi-frequency microwave S parameter data, and the effective separation particle size intervals are set.

Description

Microwave biosensing real-time monitoring platform suitable for low concentration CEA in serum Technical Field The invention relates to the technical field of microwave biosensing, in particular to a microwave biosensing real-time monitoring platform suitable for low-concentration CEA in serum. Background Serum low-concentration CEA, namely carcinoembryonic antigen, is a broad-spectrum tumor marker of clinical cores, the serum reference threshold of healthy people is usually less than 5ng/mL, the low-concentration CEA particularly refers to trace targets at the level of pg/mL to low ng/mL, and the CEA is a key indicator for early screening and prognosis monitoring of tumors, wherein the trace targets are usually found in early stages of malignant tumors, postoperative micrometastasis recurrence and pre-cancerous lesions. By carrying out microwave biological sensing real-time monitoring on the CEA, CEA concentration change of a patient after operation and during chemotherapy can be dynamically tracked, concentration abnormal fluctuation can be found earlier, and tumor recurrence and metastasis risks can be early warned in time. At present, the microwave biological sensing real-time monitoring platform has the advantages of high sensitivity and quick response in the tumor marker detection field, and the existing low-concentration CEA concentration determination method based on the microwave biological sensor realizes quick concentration determination by designing a sensor structure and establishing a response relationship between CEA solution concentration and sensor parameters. However, serum samples have complex components, and high-frequency interferents such as albumin, globulin and the like in serum and nonspecific binding proteins can mask the microwave response signal of CEA with low concentration, so that the detection accuracy is reduced. Disclosure of Invention The present invention has been made in order to solve the technical problems set forth in the background art described above. The embodiment of the invention provides a microwave biological sensing real-time monitoring platform suitable for CEA with low concentration in serum. The aim of the invention can be achieved by the following technical scheme: the sample parameter acquisition module is used for acquiring data of a serum sample to obtain serum protein characteristic parameters, and then conveying the serum protein characteristic parameters to the serum interference separation module. As a preferred embodiment of the present invention, the serum sample is subjected to data acquisition to obtain serum protein characteristic parameters, which specifically include: The serum sample is subjected to data acquisition through an installed sample acquisition sensing group to obtain serum protein characteristic parameters, the sample acquisition sensing group comprises, but is not limited to, a double-frequency interdigital transducer, a planar microwave resonance sensor, a microwave signal generator and a particle size inversion DSP module, and the serum protein characteristic parameters comprise double-frequency time sequence microwave S parameter data, microwave dielectric response data, dielectric characteristic synchronous data and multi-frequency microwave S parameter data. The method comprises the steps of setting a microwave S parameter data of a microwave sensor unit, acquiring a microwave network scattering parameter, acquiring a dielectric response time domain sequence, dielectric characteristic synchronous data, a microwave attenuation coefficient sequence of the serum sample in a sampling period and a synchronously acquired resonance frequency offset sequence, wherein the microwave S parameter data of the microwave sensor unit are transmission microwave time domain signals of serum samples at low frequency and high frequency of a set frequency, the microwave dielectric response data are broadband sweep frequency microwave excitation which emits a resonance frequency band of the microwave sensor unit, acquiring microwave network scattering parameters, acquiring the dielectric response time domain sequence through inverse Fourier change, acquiring the microwave attenuation coefficient sequence of the serum sample in the sampling period and the synchronously acquired resonance frequency offset sequence, the microwave attenuation coefficient data of the microwave S parameter data of the frequency are the microwave attenuation coefficients of the set frequency at the low frequency, the medium frequency and the high frequency, inverting the microwave attenuation of each frequency based on a Rayleigh scattering model to obtain particle size intervals of various interference proteins, calculating average particle size values based on the particle size intervals, and collecting the ratio of the mass of the interference proteins in each particle size interval, namely the particle size mass ratio, collecting the average particle size value and