Microfluidics-based qi and blood detection and analysis device and detection method thereof

Abstract

The detection method comprises the following steps: adding an oxygen-containing solution into a blood sample, adding the oxygen-containing solution into a micro-fluidic chip, irradiating the blood sample through light sources with different wavelengths, and detecting data of absorbed light to obtain concentration information and establish a model; the contribution of hemoglobin in the measurement concentration of the blood sample is obtained by analyzing the data of the absorbed light, and finally, the blood sample is detected through the model, and the hemoglobin concentration is obtained and output. Compared with the prior art, under the condition that a blood sample is not pretreated, the hemoglobin concentration can be accurately detected, and a result is obtained; the method comprises the following steps: adding an oxygen-containing solution into a blood sample; compared with the prior art, by changing the light absorption property of hemoglobin in the blood sample, the hemoglobin can be detected more easily, and the detection accuracy is improved.

Description

Technical Field

[0001] The present invention relates to a gas and blood detection and analysis device based on microfluidics and a detection method thereof, and in particular to a gas and blood detection and analysis device based on microfluidics and a detection method thereof. Background Art

[0002] Microfluidic detection of qi and blood is a method of detecting qi and blood using microfluidic technology. Specifically, microfluidic technology can accurately control and operate fluids through miniaturized fluid channels, valves, pumps and other components to achieve functions such as fluid mixing, separation, and detection. In qi and blood detection, microfluidic technology can accurately manipulate and mix blood samples, and measure qi and blood levels through specific biochemical reactions, such as measuring the oxygen content or hemoglobin concentration in the blood, thereby evaluating the individual's qi and blood status; this technology has the advantages of small size, high integration, simple operation, low cost, and easy integration, making the qi and blood detection process more efficient, fast, and accurate. In addition, by designing multiple parallel channels, microfluidic technology can also achieve high-throughput processing of qi and blood detection, further improving detection efficiency.

[0003] In the process of detecting the hemoglobin concentration in the blood, the blood needs to be pre-treated by centrifugation, such as centrifugation, filtration, chromatography, etc. However, in the process of removing interferences by pre-treatment, sample distortion may occur, so that the test results cannot truly reflect the actual situation in the patient's body. Summary of the invention

[0004] The present invention overcomes the deficiencies of the prior art and provides a microfluidics-based gas and blood detection and analysis device and a detection method thereof.

[0005] To achieve the above object, the technical solution adopted by the present invention is: a microfluidics-based gas and blood detection and analysis method, comprising:

[0006] S1, collecting a blood sample, mixing the blood sample with an additive, and adding the blood sample to a microfluidic chip;

[0007] S2, the optical system uses two light sources of specific wavelengths to illuminate the mixed blood sample in S1;

[0008] S3, collecting the data of light absorption by the blood sample in S2 through a detector and converting it into an electrical signal;

[0009] S4, after the electrical signal of S3 is received by the data processing unit, a relationship model between light absorption and hemoglobin concentration is established by using a multivariate linear regression algorithm method;

[0010] S5, using an algorithm based on spectral analysis to analyze the absorbance at different wavelengths in S3 to distinguish the contribution of hemoglobin and other blood components;

[0011] S6. Based on the analysis of S5, the hemoglobin concentration in the blood sample is calculated according to the model and outputted.

[0012] In a preferred embodiment of the present invention, specifically, in step S1, collecting the blood sample specifically involves collecting an appropriate amount of venous blood from the subject using a sterile blood collection tool such as a vacuum blood collection tube.

[0013] In a preferred embodiment of the present invention, specifically, in step S1, the additive is an oxygen-containing solution.

[0014] In a preferred embodiment of the present invention, specifically, in step S2, the wavelengths of the two light sources with specific wavelengths are 540 nm and 575 nm.

[0015] In a preferred embodiment of the present invention, specifically, in step S3, the detector is a spectrophotometer, which can measure the light absorption degree of the blood sample at different wavelengths.

[0016] In a preferred embodiment of the present invention, specifically, in step S3, the data of light absorption by the blood sample in S2 collected by the detector is specifically:

[0017]

[0018] Where A is the absorbance, I0 is the incident light intensity, I is the transmitted light intensity, and λ represents the wavelength (540nm or 575nm).

[0019] In a preferred embodiment of the present invention, specifically, in step S4,

[0020] The relationship model between light absorption and hemoglobin concentration was established using the multivariate linear regression algorithm. Specifically:

[0021] A(λ1)=∈ Hb (λ1)·c Hb ·l

[0022] A(λ2)=∈ Hb (λ2)·c Hb l,

[0023] λ1, λ2 are two wavelengths, ∈ Hb (λ1),∈ Hb (λ2) is the molar absorption coefficient at λ1 and λ2, c Hb is the concentration of hemoglobin in the blood sample, l is the optical path length (fixed in the microfluidic chip)

[0024] To eliminate the effect of the optical path length l, we divide the two equations and obtain:

[0025]

[0026] Solving for c Hb ,but:

[0027]

[0028] Among them, it is known that ∈ Hb (λ1) and l or through the calibration process to obtain ∈ Hb (λ1) and l, where k is λ1 is the reference wavelength;

[0029] The feasibility of this method was verified by using a hemoglobin analyzer to detect hemoglobin concentration.

[0030] In a preferred embodiment of the present invention, specifically, in step S5, the spectral analysis algorithm is used to distinguish the absorbance contributions of hemoglobin and other blood components at different wavelengths in S3:

[0031] Y=XB+E,

[0032] p is the absorbance measurement value at different wavelengths, expressed as X1,X2,X3,…,X P ,q is the concentration of blood components, expressed as Y1,Y2,Y3,…,Y q , n is the number of blood samples;

[0033] Y is an n×q matrix containing the concentrations of all samples and all components;

[0034] X is an n × p matrix containing the absorbance measurements of all samples at all wavelengths;

[0035] B is a p×q coefficient matrix, representing the regression coefficient of each component at each wavelength;

[0036] E is an n×q error matrix;

[0037] The process of solving the formula;

[0038] B=(X′X) -1 X′Y,

[0039] It is worth noting that here p ≤ n and there is no collinearity problem;

[0040] After obtaining B, solve the specific contribution of hemoglobin;

[0041]

[0042] Where M is the contribution of hemoglobin, is the absorbance measurement at the ith wavelength, B i is the regression coefficient of hemoglobin concentration at this wavelength.

[0043] In a preferred embodiment of the present invention, specifically, in step S6, the hemoglobin concentration of the sample detected is measured as follows:

[0044]

[0045] X new is a vector containing the absorbance measurements of the new sample at all wavelengths (note that X new is a 1×p matrix, where p is the number of wavelengths), B is the p×q coefficient matrix obtained from the training data (where q is the number of blood components), B g represents the vector related to hemoglobin concentration in the coefficient matrix B, and Y1 is the detected hemoglobin concentration.

[0046] In a preferred embodiment of the present invention, a microfluidics-based gas and blood detection and analysis device comprises:

[0047] A sampling and staking module is used to collect blood samples and stake out the blood samples;

[0048] Microfluidic chip module: The microfluidic chip is the core of the device, integrating micro-nanoscale channels, chambers and various sensors; these channels and chambers are used to precisely manipulate and distribute blood samples to react with chemically sensitive media, and to achieve sample introduction, reaction, separation and detection;

[0049] The sensor module is used to measure the concentration and other components by detecting the signal of light absorption by the sample. The sensor has the characteristics of high precision, high sensitivity and fast response, which can ensure the accuracy and reliability of the test results.

[0050] an analysis module that analyzes absorbance at different wavelengths to distinguish the contribution of hemoglobin and other blood components;

[0051] The data processing module receives the signal and calculates the result through the algorithm and outputs it.

[0052] In a preferred embodiment of the present invention,

[0053] The present invention solves the defects existing in the background technology and has the following beneficial effects:

[0054] (1) By adding an oxygen-containing solution to a blood sample and then adding it to a microfluidic chip, the blood sample is irradiated with light sources of different wavelengths, and the concentration information is obtained by detecting the data of absorbed light and establishing a model. By analyzing the data of absorbed light, the contribution of hemoglobin to the measured concentration in the blood sample is obtained, and finally the blood sample is detected through the model to obtain the hemoglobin concentration and output it; compared with the existing technology, the hemoglobin concentration can be accurately detected and the result can be obtained without pre-processing the blood sample.

[0055] (2) By adding an oxygen-containing solution to a blood sample; compared to the prior art, by changing the light absorption properties of hemoglobin in the blood sample, hemoglobin is easier to detect, thereby increasing the accuracy of the detection.

[0056] (3) Spectral analysis is used for absorbance; compared with the existing technology, the relationship between hemoglobin, other interferents and hemoglobin concentration is obtained by analyzing the absorbance, thereby increasing the accuracy of model detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

[0058] Figure 1 is a flow chart of a preferred embodiment of the present invention; DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0061] like Figure 1 As shown, a microfluidics-based gas and blood detection and analysis method comprises:

[0062] S1, collecting a blood sample, mixing the blood sample with an additive, and adding the blood sample to a microfluidic chip;

[0063] S2, the optical system uses two light sources of specific wavelengths to illuminate the mixed blood sample in S1;

[0064] S3, collecting the data of light absorption by the blood sample in S2 through a detector and converting it into an electrical signal;

[0065] S4, after the electrical signal of S3 is received by the data processing unit, a relationship model between light absorption and hemoglobin concentration is established by using a multivariate linear regression algorithm method;

[0066] S5, using an algorithm based on spectral analysis to analyze the absorbance at different wavelengths in S3 to distinguish the contribution of hemoglobin and other blood components;

[0067] S6, based on the analysis of S5, calculating the hemoglobin concentration in the blood sample according to the model and outputting it;

[0068] Specifically, in step S1, collecting the blood sample specifically involves collecting an appropriate amount of venous blood from the subject using a sterile blood collection tool such as a vacuum blood collection tube;

[0069] Specifically, in step S1, the additive is an oxygen-containing solution, which can change the absorbance of hemoglobin in the blood sample, making the hemoglobin easier to detect;

[0070] Specifically, in step S2, the wavelengths of the two specific wavelength light sources are 540nm and 575nm; the use of two specific wavelength light sources (such as 540nm and 575nm) for detection is based on the difference in absorption spectra of hemoglobin and its different oxygenation states. Specifically, the absorption characteristics of oxygenated hemoglobin (HbO2) and reduced hemoglobin (Hb) in the red light and infrared light regions (including around 540nm and 575nm) are different; by measuring the absorbance changes at these two wavelengths, the relative proportion of oxygenated hemoglobin and reduced hemoglobin in the blood can be calculated, and then the blood oxygen saturation can be inferred.

[0071] Specifically, in step S2, the light source of the optical path system passes through the filter and irradiates the mixed blood sample in S1; the filter is a bandpass filter with a central wavelength of 550nm (between 540nm and 575nm) and a bandwidth of 50nm. Light in the range of 500nm to 600nm will partially pass through, but light in the range of 525nm to 575nm (especially light near 550nm) will have the highest transmittance; light below 500nm and above 600nm will be significantly attenuated by the filter, thereby filtering out stray light that does not match the absorption wavelength of hemoglobin.

[0072] Specifically, in step S3, the detector uses a spectrophotometer, which can measure the light absorption degree of the blood sample at different wavelengths; data collection is specifically as follows: the light source passes through the blood sample and finally shines on the spectrophotometer, and the spectrophotometer receives the light signal and converts it into an electrical signal.

[0073] Specifically, in step S3, the data of light absorption of the blood sample in S2 collected by the detector is specifically:

[0074]

[0075] Where A is the absorbance, I0 is the incident light intensity, I is the transmitted light intensity, and λ represents the wavelength (540nm or 575nm).

[0076] Specifically, in step S4,

[0077] The relationship model between light absorption and hemoglobin concentration was established using the multivariate linear regression algorithm. Specifically:

[0078] A(λ1)=∈ Hb (λ1)·c Hb ·l

[0079] A(λ2)=∈ Hb (λ2)·c Hb l,

[0080] λ1, λ2 are two wavelengths, ∈ Hb (λ1),∈ Hb (λ2) is the molar absorption coefficient at λ1 and λ2, c Hb is the concentration of hemoglobin in the blood sample, l is the optical path length (fixed in the microfluidic chip)

[0081] To eliminate the effect of the optical path length l, we divide the two equations and obtain:

[0082]

[0083] Solving for c Hb ,but:

[0084]

[0085] Among them, it is known that ∈ Hb (λ1) and l or through the calibration process to obtain ∈ Hb (λ1) and l, where k is λ1 is the reference wavelength.

[0086] The feasibility of this method was verified by using a hemoglobin analyzer to detect hemoglobin concentration.

[0087] Specifically, in step S5, a spectral analysis algorithm is used to distinguish the absorbance contributions of hemoglobin and other blood components at different wavelengths in S3. Specifically, the absorbance contributions of hemoglobin and other blood components at different wavelengths in S3 are:

[0088] Y=XB+E,

[0089] p is the absorbance measurement value at different wavelengths, expressed as X1,X2,X3,…,X P ,q is the concentration of blood components, expressed as Y1,Y2,Y3,…,Y q , n is the number of blood samples,

[0090] Y is an n×q matrix containing the concentrations of all samples and all components.

[0091] X is an n-by-p matrix containing the absorbance measurements for all samples at all wavelengths.

[0092] B is a p×q coefficient matrix, representing the regression coefficients of each component at each wavelength.

[0093] E is an n×q error matrix;

[0094] The process of solving the formula;

[0095] B=(X′X) -1 X′Y,

[0096] It is worth noting that here p ≤ n and there is no collinearity problem;

[0097] After obtaining B, solve the specific contribution of hemoglobin;

[0098]

[0099] Where M is the contribution of hemoglobin, is the absorbance measurement at the ith wavelength, B i is the regression coefficient of hemoglobin concentration at this wavelength.

[0100] Specifically, in step S6, the hemoglobin concentration of the sample detected is measured as follows:

[0101]

[0102] X new is a vector containing the absorbance measurements of the new sample at all wavelengths (note that X new is a 1×p matrix, where p is the number of wavelengths), B is the p×q coefficient matrix obtained from the training data (where q is the number of blood components), B g represents the vector related to hemoglobin concentration in the coefficient matrix B, is the hemoglobin concentration detected.

[0103] A microfluidics-based gas and blood detection and analysis device, comprising:

[0104] Sampling and staking module; used for collecting blood samples and staking the blood samples;

[0105] Microfluidic chip module: The microfluidic chip is the core of the device, integrating micro-nanoscale channels, chambers and various sensors. These channels and chambers are used to precisely manipulate and distribute blood samples to react with chemically sensitive media, and to achieve sample introduction, reaction, separation and detection;

[0106] Sensor module; it is used to measure the concentration and other components by detecting the signal of light absorbed by the sample; the sensor has the characteristics of high precision, high sensitivity and fast response, which can ensure the accuracy and reliability of the test results;

[0107] Analysis module: analyzes absorbance at different wavelengths to distinguish the contribution of hemoglobin and other blood components;

[0108] Data processing module: receives signals and calculates and outputs the results through algorithms.

[0109] The above is based on the ideal embodiment of the present invention. Through the above description, relevant personnel can make various changes and modifications without departing from the technical concept of the present invention. The technical scope of the present invention is not limited to the content in the specification, and the technical scope must be determined according to the scope of the claims.

Claims

1. A microfluidics-based gas and blood detection and analysis method, characterized in that: The following steps are involved: S1, collecting a blood sample, mixing the blood sample with an additive, and adding the blood sample to a microfluidic chip; S2, the optical system uses two light sources of specific wavelengths to illuminate the mixed blood sample in S1; S3, collecting the data of light absorption by the blood sample in S2 through a detector and converting it into an electrical signal; S4, after the electrical signal of S3 is received by the data processing unit, a relationship model between light absorption and hemoglobin concentration is established by using a multivariate linear regression algorithm method; S5, using an algorithm based on spectral analysis to analyze the absorbance at different wavelengths in S3 to distinguish the contribution of hemoglobin and other blood components; S6. Based on the analysis of S5, the hemoglobin concentration in the blood sample is calculated according to the model and output.

2. The microfluidics-based gas and blood detection and analysis method according to claim 1, characterized in that: Specifically, in step S1, the blood sample is collected by collecting an appropriate amount of venous blood from the subject using a sterile blood collection tool such as a vacuum blood collection tube.

3. The microfluidics-based gas and blood detection and analysis method according to claim 1, characterized in that: Specifically, in step S1, the additive is an oxygen-containing solution.

4. The microfluidics-based gas and blood detection and analysis method according to claim 1, characterized in that: Specifically, in step S2, the wavelengths of the two specific wavelength light sources are 540 nm and 575 nm.

5. The microfluidics-based gas and blood detection and analysis method according to claim 1, characterized in that: Specifically, in step S3, the detector uses a spectrophotometer to measure the light absorption degree of the blood sample at different wavelengths.

6. The microfluidics-based gas and blood detection and analysis method according to claim 1, characterized in that: Specifically, in step S3, the data of light absorption of the blood sample in S2 collected by the detector is specifically: Among them, A is the absorbance, I0 is the incident light intensity, I is the transmitted light intensity, and λ represents the wavelength.

7. The microfluidics-based gas and blood detection and analysis method according to claim 1, characterized in that: Specifically, in step S4, The relationship model between light absorption and hemoglobin concentration was established using the multivariate linear regression algorithm. Specifically: A(λ1)=∈ Hb (λ1)·c Hb ·l A(λ2)=∈ Hb (λ2)·c Hb ·l, λ1, λ2 are two wavelengths, ∈ Hb (λ1),∈ Hb (λ2) is the molar absorption coefficient at λ1 and λ2, c Hb is the concentration of hemoglobin in the blood sample, l is the optical path length; To eliminate the effect of the optical path length l, we divide the two equations and obtain: Solving for c Hb ,but: Among them, it is known that ∈ Hb (λ1) and l or through the calibration process to obtain ∈ Hb (λ1) and l, where k is λ1 is the reference wavelength.

8. The microfluidics-based gas and blood detection and analysis method according to claim 1, characterized in that: Specifically, in step S5, a spectral analysis algorithm is used to distinguish the absorbance contributions of hemoglobin and other blood components at different wavelengths in S3. Specifically, the absorbance contributions of hemoglobin and other blood components at different wavelengths in S3 are: Y=XB+E, p is the absorbance measurement value at different wavelengths, expressed as X1,X2,X3,…,X P ,q is the concentration of blood components, expressed as Y1,Y2,Y3,…,Y q , n is the number of blood samples; Y is an n×q matrix containing the concentrations of all samples and all components; X is an n × p matrix containing the absorbance measurements of all samples at all wavelengths; B is a p×q coefficient matrix, representing the regression coefficient of each component at each wavelength; E is an n×q error matrix; The process of solving the formula; B=(X′X) -1 X′Y, Here p≤n and there is no collinearity problem; After obtaining B, solve for the hemoglobin contribution: Where M is the contribution of hemoglobin, is the absorbance measurement at the ith wavelength, B i is the regression coefficient of hemoglobin concentration at this wavelength.

9. The microfluidics-based gas and blood detection and analysis method according to claim 1, characterized in that: Specifically, in step S6, the hemoglobin concentration of the sample is detected: X new is a vector containing the absorbance measurements of the new sample at all wavelengths, and B is the p×q coefficient matrix obtained from the training data. g represents the vector related to hemoglobin concentration in the coefficient matrix B, is the measured hemoglobin concentration.

10. A microfluidics-based gas and blood detection and analysis device, based on a microfluidics-based gas and blood detection and analysis method according to any one of claims 1 to 9, characterized in that: include: A sampling and staking module is used to collect blood samples and stake out the blood samples; Microfluidic chip module, used to introduce samples, react and detect; A sensor module is used to measure the concentration component by detecting the signal of light absorbed by the sample; an analysis module for analyzing absorbance at different wavelengths to distinguish the contribution of hemoglobin and other blood components; The data processing module is used to receive signals and calculate and output the results through algorithms.

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