Non-invasive tissue fluid lactic acid dynamic monitoring method

Abstract

The invention provides a non-invasive tissue fluid lactic acid dynamic monitoring method. The method comprises the following steps: establishing a relation model of epidermal and subcutaneous lactic acid concentrations; steady-state current values under different epidermal lactic acid concentrations are obtained through in-vitro experiments, and then the function relation between the steady-state current values and the epidermal lactic acid concentrations is obtained; net current values under different subcutaneous lactic acid concentrations are obtained through human body experiments, a function relationship between the net current values and the subcutaneous lactic acid concentrations is established, and the function relationship can be used for a subsequent transdermal extraction detection process; substituting the measured epidermal lactic acid concentration into a relation model of epidermal and subcutaneous lactic acid concentrations to obtain an accurate concentration value of tissue fluid lactic acid monitoring; according to the method, in the dynamic real-time monitoring process of the lactic acid concentration of the tissue fluid, the concentration of the lactic acid extracted from the epidermis measured by the lactic acid sensor can be converted into the real-time and accurate lactic acid concentration of the subcutaneous tissue fluid, and rapid, painless, infection-free and continuous monitoring of the lactic acid level of the subcutaneous tissue fluid can be achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of continuous lactate monitoring, and particularly relates to a non-invasive tissue fluid lactate dynamic monitoring method. BACKGROUND

[0002] Lactate is an important metabolic product generated by reducing pyruvate through glycolysis in the state of anaerobic or sub-anaerobic. Lactate in tissue fluid can directly and sensitively reflect the metabolic state and microcirculation perfusion condition of local tissue. Therefore, monitoring and management of lactate in tissue fluid has important value.

[0003] At present, the main methods of tissue fluid lactate monitoring can be divided into two categories: the first category is to collect tissue fluid through invasive means such as microdialysis catheter or hollow microneedle and monitor lactate level. This kind of method needs to pierce the skin to obtain interstitial fluid, which not only easily causes pain and discomfort of the patient, but also increases the risk of bleeding and infection. In addition, these technologies usually require professional medical staff to perform complex operations and continuous maintenance, which limits their convenience and real-time application. At the same time, there is obvious time delay in the sampling and analysis process, which makes it difficult to achieve real-time monitoring. The second category is the non-invasive lactate monitoring method that has emerged in recent years, which detects lactate level in tissue fluid through non-invasive or minimally invasive methods, significantly improving patient compliance.

[0004] At present, the non-invasive lactate monitoring method mainly includes magnetic fluid dynamics method and counter-ion electroosmosis method. The magnetic fluid dynamics method has not been verified in the human body due to scientific problems such as extremely low signal-to-noise ratio and poor specificity, and is still at the experimental exploration stage at present. Compared with the magnetic fluid dynamics lactate detection method, the transdermal extraction and detection integrated equipment represented by the counter-ion electroosmosis technology shows great potential. The equipment can extract subcutaneous tissue fluid through the epidermis and detect the lactate level. The lactate content in subcutaneous tissue fluid can directly reflect the metabolic state and hypoxic degree of local tissue, and can provide a sensitive early warning signal. At the same time, this method has the advantages of painless, not easy to be infected, continuous monitoring and easy to be miniaturized, which can quickly complete the measurement of subcutaneous tissue fluid lactate, greatly saving the detection time. In addition, the biomarkers in the biological microfluid extracted by the counter-ion electroosmosis method, such as lactate, are extremely easy to detect by electrochemical method. This technology measures the extracted interstitial fluid lactate level by applying a mild current on the skin, which is a new type of non-invasive continuous lactate monitoring method. However, the lactate concentration in subcutaneous tissue fluid based on the counter-ion electroosmosis tissue fluid extraction technology cannot be directly obtained. Therefore, how to accurately calculate the lactate concentration in subcutaneous tissue fluid from the lactate concentration extracted through the epidermis is crucial for constructing a continuous tissue fluid lactate monitoring system. SUMMARY

[0005] The technical problem to be solved by the present application is to provide a non-invasive tissue fluid lactic acid dynamic monitoring method.

[0006] To solve the above technical problems, the technical scheme of the present application is:

[0007] A non-invasive tissue fluid lactic acid dynamic monitoring method, the specific steps are as follows:

[0008] (I) Establish a relationship model of epidermal and subcutaneous lactic acid concentration, obtain the accurate concentration of subcutaneous lactic acid based on the epidermal lactic acid concentration using counterion electrophoresis technology, and the relationship model is: Wherein, c ilac is the subcutaneous tissue fluid lactic acid concentration; c lac is the epidermal extracted lactic acid concentration; k is the sensor sensitivity; b is the sensor calibration intercept; y2 is the sensor baseline current value; m is the extraction calibration slope; and n is the extraction calibration intercept.

[0009] (II) The epidermal extracted lactic acid concentration (c lac ) is detected using a lactic acid sensor, and then the accurate concentration value (subcutaneous tissue fluid lactic acid concentration c ilac ) of transdermal tissue fluid lactic acid monitoring is obtained through the relationship model.

[0010] Preferably, the non-invasive tissue fluid lactic acid dynamic monitoring method has the specific steps as follows:

[0011] (1) Establish a relationship model of epidermal and subcutaneous lactic acid concentration, obtain the accurate concentration of subcutaneous lactic acid based on the epidermal lactic acid concentration using counterion electrophoresis technology, and the relationship model is: Wherein, c ilac is the subcutaneous tissue fluid lactic acid concentration; c lac is the epidermal extracted lactic acid concentration; k is the sensor sensitivity; b is the sensor calibration intercept; y2 is the sensor baseline current value; m is the extraction calibration slope; and n is the extraction calibration intercept.

[0012] (2) In vitro experiments are performed using a lactic acid sensor, and the steady-state current under different epidermal lactic acid concentrations is obtained through the in vitro experiments, and a steady-state current value and epidermal extracted lactic acid concentration model is established: y=y1+y2=k·x+b, wherein y is the steady-state current value, y1 is the sensor net current value; y2 is the sensor baseline current value; k is the sensor sensitivity; x is the epidermal lactic acid concentration; and b is the sensor calibration intercept.

[0013] (3) Human experiments are performed using a lactic acid sensor, and the net current value under different subcutaneous lactic acid concentrations is obtained through the human experiments, and a function relationship of net current value and subcutaneous lactic acid concentration is established: f=m·c+n, wherein f is the net current value, m is the extraction calibration slope, c is the subcutaneous lactic acid concentration, and n is the extraction calibration intercept.

[0014] (4) The measured epidermis lactate concentration is substituted into the model of the relationship between epidermis and subcutaneous lactate concentration in step (1) to obtain the accurate concentration value of transdermal interstitial fluid lactate monitoring.

[0015] Preferably, in the above non-invasive interstitial fluid lactate dynamic monitoring method, the step of preparing a gradient lactate concentration PBS buffer solution (such as 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6 mM, etc.) before the in vitro experiment is performed.

[0016] Preferably, in the above non-invasive interstitial fluid lactate dynamic monitoring method, the lactate sensor is scanned by cyclic voltammetry before the in vitro experiment to stabilize the electrode, and the chronoamperometric curve is tested in the phosphate buffered saline solution. After the curve is stable, the lactate detection test is performed, and the data is recorded.

[0017] Preferably, in the above non-invasive interstitial fluid lactate dynamic monitoring method, in step (2), the epidermis lactate concentration is used as the independent variable, and the steady-state current value under different epidermis lactate concentrations is used as the dependent variable to obtain the functional relationship between the steady-state current value and the epidermis lactate concentration y = y1 + y2 = k x + b, wherein y is the steady-state current value, y1 is the net current value of the sensor; y2 is the baseline current value of the sensor; k is the sensitivity of the sensor; x is the epidermis lactate concentration; and b is the calibration intercept of the sensor.

[0018] Preferably, in the above non-invasive interstitial fluid lactate dynamic monitoring method, in step (3), the lactate sensor is attached to the skin surface (preferably the skin surface of the front side of the human arm) before the human experiment, the chronoamperometric curve is tested, and the lactate extraction detection test is performed after the curve is stable. The data is recorded.

[0019] Preferably, in the above non-invasive interstitial fluid lactate dynamic monitoring method, in step (3), the human interstitial fluid is extracted by the microneedle during the human experiment, the interstitial fluid is detected by the colorimetric method in vitro, the subcutaneous lactate concentration value (i.e. the accurate interstitial fluid lactate concentration value) is obtained, and the data is recorded, which is used to establish the functional relationship between different subcutaneous lactate concentrations and net current values.

[0020] Preferably, in the above non-invasive interstitial fluid lactate dynamic monitoring method, in step (3), the subcutaneous lactate concentration is used as the independent variable, and the net current value under different subcutaneous lactate concentrations is used as the dependent variable to obtain the functional relationship between the extraction net current value and the subcutaneous lactate concentration f = m c + n, wherein f is the net current value, m is the extraction calibration slope, c is the subcutaneous lactate concentration, and n is the extraction calibration intercept.

[0021] Preferably, the above-mentioned non-invasive tissue fluid lactate dynamic monitoring method obtains the relationship model of the epidermal and subcutaneous lactate concentrations (when f is equal to y1) through the functional relationship y=y1+y2=k·x+b between the steady-state current value and the epidermal lactate concentration, and the functional relationship f=m·c+n between the extracted net current value and the subcutaneous lactate concentration: wherein c ilac is the subcutaneous tissue fluid lactate concentration; c lac is the epidermal extracted lactate concentration; k is the sensor sensitivity; b is the sensor calibration intercept; y2 is the sensor baseline current value; m is the extraction calibration slope; and n is the extraction calibration intercept. The correctness of the relationship model established in step (1) is further confirmed.

[0022] Preferably, the above-mentioned non-invasive tissue fluid lactate dynamic monitoring method has the following specific steps:

[0023] (1) The lactate sensor is attached to the skin surface on the front side of the human forearm, and the lactate sensor (a commercially available lactate sensor using electrochemical sensing technology) includes a counter-ion electro-osmotic extraction electrode and an extraction auxiliary electrode, which can apply a constant current to extract tissue fluid;

[0024] (2) The extracted tissue fluid is detected for lactate by the sensor element of the lactate sensor, which uses electrochemical sensing technology;

[0025] (3) The detection result is substituted into the functional relationship y=y1+y2=k·x+b between the steady-state current value and the epidermal lactate concentration to obtain accurate epidermal lactate concentration data; and then the relationship model of the epidermal and subcutaneous lactate concentrations is used to obtain accurate subcutaneous lactate concentration values (i.e., accurate tissue fluid lactate concentration values).

[0026] The above-mentioned non-invasive tissue fluid lactate dynamic monitoring method is designed based on the characteristics of human tissues and biochemical reaction mechanisms, and can be measured cyclically to achieve continuous real-time dynamic monitoring of the subcutaneous lactate concentration.

[0027] Technical effects:

[0028] The above-mentioned non-invasive tissue fluid lactate dynamic monitoring method can convert the epidermal extracted lactate concentration measured by the lactate sensor into real-time and accurate subcutaneous tissue fluid lactate concentration during the dynamic real-time monitoring of the tissue fluid lactate concentration, thereby providing method support for realizing rapid, painless, infection-free and continuous monitoring of the subcutaneous tissue fluid lactate level and promoting the practical application of lactate sensors in the clinic. BRIEF DESCRIPTION OF DRAWINGS

[0029] Figure 1 is the flowchart of the non-invasive tissue fluid lactate dynamic monitoring method of the present application.

[0030] Figure 2 This is a graph showing the fitting relationship between the steady-state current value and the concentration of lactic acid extracted from the epidermis, as described in this invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention will be further described in detail below with reference to specific embodiments.

[0032] Example 1

[0033] like Figure 1 As shown, the non-invasive tissue fluid lactate dynamic monitoring method first establishes a preliminary relationship model between epidermal and subcutaneous lactate concentrations through analysis. Then, through in vitro and human experiments, it obtains the functional relationships between steady-state current value and epidermal lactate concentration, as well as between net current value and subcutaneous lactate concentration. Next, it substitutes the epidermal lactate concentration into the relationship model between epidermal and subcutaneous lactate concentrations to obtain more accurate lactate concentration data. The specific steps are as follows:

[0034] Step S1: Theoretical analysis to establish a model relating epidermal and subcutaneous lactic acid concentrations

[0035] Theoretically, the steady-state current value under different epidermal lactic acid concentrations can be calculated using the following formula:

[0036] y = y1 + y2 = k·x + b

[0037] Where y is the steady-state current value, y1 is the sensor net current value, y2 is the sensor baseline current value, k is the sensor sensitivity, x is the epidermal lactic acid concentration, and b is the sensor calibration intercept.

[0038] The net current value at different subcutaneous lactic acid concentrations can be calculated using the following formula:

[0039] f = m·c + n

[0040] Where f is the net current value, m is the extraction calibration slope, c is the subcutaneous lactic acid concentration, and n is the extraction calibration intercept. According to the above formula, when f is equal to y1, the epidermal lactic acid concentration c obtained from transdermal extraction can be obtained. lac With the concentration of lactic acid in subcutaneous tissue fluid c ilac There is a linear relationship between them: Among them, c ilac c is the concentration of lactic acid in subcutaneous tissue fluid. lac y2 represents the concentration of lactic acid extracted from the epidermis; k represents the sensor sensitivity; b represents the sensor calibration intercept; y2 represents the sensor baseline current value; m represents the extraction calibration slope; and n represents the extraction calibration intercept.

[0041] Therefore, by detecting the concentration of epidermal lactic acid extracted transdermally, a real-time measurement of subcutaneous lactic acid concentration can be obtained non-invasively.

[0042] Step S2: Obtain the function relationship between the steady-state current value and the epidermal lactic acid concentration and the related parameters through in-vitro experiments

[0043] First, configure the step lactic acid concentration PBS buffer (0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6 mM). Second, perform cyclic voltammetry scanning on the lactic acid sensor to stabilize the electrode, test the chronoamperometric curve in the phosphate buffered saline solution, and perform the lactic acid detection test after the curve is stable, and record the data, wherein not less than 8 repeated measurements are performed under each epidermal lactic acid concentration to avoid accidental errors, and the results of the repeated measurements are processed to obtain the mean value data y. Before each detection test, a PBS buffer empty running process is performed to eliminate the problem of unstable current baseline, so it is necessary to perform baseline stabilization processing on the test results of each group to exclude the interference of the baseline instability on the final steady-state current value to obtain y2. Then, test different epidermal lactic acid concentrations, wherein not less than 8 repeated measurements are performed under each epidermal lactic acid concentration to avoid accidental errors. The results of the repeated measurements are processed to obtain the mean value data, and the epidermal lactic acid concentration is taken as the independent variable, and the steady-state current value under different epidermal lactic acid concentrations is taken as the dependent variable to perform data fitting to obtain k and b; the function relationship between the steady-state current value and the epidermal lactic acid concentration: y = y1 + y2 = k x + b, wherein y is the steady-state current value, y1 is the net current value of the sensor; y2 is the baseline current value of the sensor; k is the sensitivity of the sensor; x is the epidermal lactic acid concentration; b is the calibration intercept of the sensor.

[0044] Step S3: Obtain the function relationship between the net current value and the subcutaneous lactic acid concentration and the related parameters through human experiments

[0045] First, the lactic acid sensor is attached to the surface of the skin on the front side of the human arm, the chronoamperometric curve is tested, and after the baseline current value is obtained, 150 μA / cm 2 to 300 μA / cm 2The steady-state current value is obtained by extracting tissue fluid for 5 to 10 minutes at a constant current, detecting the lactic acid concentration of the extracted tissue fluid for 1 minute, and recording the steady-state current value. Finally, the net current value is obtained. During the extraction of tissue fluid, human tissue fluid is extracted through microneedles for the same time, and then the lactic acid concentration of the tissue fluid is detected by a laboratory kit for ex vivo colorimetric detection. The subcutaneous lactic acid concentration value (i.e., the accurate tissue fluid lactic acid concentration value) is obtained, and the data is recorded for establishing a functional relationship between different subcutaneous lactic acid concentrations and net current values. During the experiment, the lactic acid concentration of the tissue fluid of the small arm can be changed by binding an elastic band and changing the binding time to cause local hypoxia of the small arm. Each binding time is repeated for not less than 8 times to avoid accidental errors. The results of repeated measurements are processed by mean data to take the subcutaneous lactic acid concentration as the independent variable and the net current value at different subcutaneous lactic acid concentrations as the dependent variable for fitting to obtain the functional relationship between the net current value and the subcutaneous lactic acid concentration and the specific value of the corresponding parameter: f = m·c + n, wherein f is the net current value, m is the extraction calibration slope, c is the subcutaneous lactic acid concentration, and n is the extraction calibration intercept.

[0046] Step S4: The epidermal lactic acid concentration is substituted into the relationship model of epidermal and subcutaneous lactic acid concentrations to obtain the accurate concentration value of transdermal lactic acid monitoring

[0047] After obtaining the functional relationship between the epidermal and subcutaneous lactic acid concentrations and the current value, the accurate relationship model of the epidermal and subcutaneous lactic acid concentrations is obtained by fitting the functional relationship of the current value with the epidermal and subcutaneous lactic acid concentrations: wherein c ilac is the subcutaneous tissue fluid lactic acid concentration; c lac is the epidermal extraction lactic acid concentration; k is the sensor sensitivity; b is the sensor calibration intercept; y2 is the sensor baseline current value; m is the extraction calibration slope; and n is the extraction calibration intercept. The result is consistent with the theoretical analysis result in step S1.

[0048] The detection result is substituted into the functional relationship y = y1 + y2 = k·x + b between the steady-state current value and the epidermal lactic acid concentration to obtain accurate epidermal lactic acid concentration data; and then the accurate subcutaneous lactic acid concentration value (i.e., the accurate tissue fluid lactic acid concentration value) is obtained through the relationship model of the epidermal and subcutaneous lactic acid concentrations

[0049] Through the above non-invasive tissue fluid lactic acid dynamic monitoring method, accurate subcutaneous lactic acid test results can be obtained. The relationship model is based on the functional relationship of the subcutaneous lactic acid concentration with the epidermal lactic acid concentration, and uses the epidermal lactic acid concentration to predict the subcutaneous lactic acid concentration.

[0050] Example 2

[0051] The relationship model of the epidermal and subcutaneous lactic acid concentrations described in Example 1 is applied to non-invasive tissue fluid lactic acid dynamic monitoring, and the specific steps are as follows:​

[0052] First, a lactate sensor (commercially available lactate sensor) is attached to the skin surface of the human forearm, the lactate sensor contains counter-ion electro-osmotic extraction electrode and extraction auxiliary electrode, which can apply constant current to extract tissue fluid. During the extraction process, a constant current of 150 μA / cm 2 to 300 μA / cm 2 is applied, and the tissue fluid is extracted for 5 to 10 minutes.

[0053] Subsequently, the lactate concentration of the transdermally extracted epidermal tissue fluid is detected, which takes 1 minute. The sensor element contained in the lactate sensor can detect the lactate concentration value. Among them, the lactate sensor adopts an enzyme-based electrochemical sensing technology.

[0054] Finally, the detection results are substituted into the function relationship y=y1+y2=k·x+b between the steady-state current value and the epidermal lactate concentration to obtain accurate epidermal lactate concentration data; and through the relationship model between the epidermal and subcutaneous lactate concentrations , the accurate subcutaneous lactate concentration value (i.e. accurate tissue fluid lactate concentration value) is obtained. After that, the measurement can be cycled to realize continuous real-time dynamic monitoring of the subcutaneous lactate concentration.

[0055] As shown in Figure 2 , the preliminary results show that the steady-state current value of lactate detection changes linearly with the epidermal lactate concentration, and the slope and linear correlation coefficient are 6.343×10 -7 and 2.807×10 -7 , respectively. Specifically, under different epidermal lactate concentrations, the steady-state current value of lactate detection has a linear relationship with the epidermal lactate concentration, and when the epidermal lactate concentration increases at the same gradient, the steady-state current value of epidermal lactate detection also increases at the same gradient, and the net current also has a linear relationship with the subcutaneous lactate concentration. This result proves that the epidermal lactate concentration has a linear relationship with the subcutaneous lactate concentration, and further illustrates the effectiveness of the relationship model between the epidermal and subcutaneous lactate concentrations. It is necessary to substitute the epidermal lactate concentration into the relationship model between the epidermal and subcutaneous lactate concentrations to obtain accurate subcutaneous lactate concentration when continuously monitoring the subcutaneous lactate concentration in real time.

[0056] During the counter-ion electro-osmotic extraction process, the extraction mechanism of lactate is a key factor affecting the accuracy of subcutaneous lactate detection. The following analysis example aims to explore the process of tissue fluid lactate extraction to the surface of the sensor electrode, which shows that the accurate subcutaneous lactate concentration can be obtained through the epidermal lactate concentration.

[0057] Reverse iontophoresis mainly involves the extraction of charged ions and neutral molecules such as lactate and glucose. For charged species such as lactate, which exists as lactate ions at physiological pH, the main transport mechanism is electro-migration, i.e. the movement of charged ions under the direct action of the electric field force. Reverse iontophoresis technology drives the migration of dissociated lactate ions in the dermal interstitial fluid towards the epidermal anode along the electrochemical gradient by applying a directed electric field across the skin. This process couples both ion electro-migration and electro-osmotic flow mass transfer mechanisms. Under the action of the direct current electric field, lactate ions penetrate the epidermal layers and reach the stratum corneum; at the same time, the proton flow generated by the anode electrolysis protonates the keratin of the stratum corneum, enhancing its permeability and forming an electro-osmotic flow from the inside out, which synergistically promotes the transport of lactate ions across the barrier. The electric field-induced reorganization of the stratum corneum lipid further reduces the diffusion resistance, ultimately allowing lactate to be extracted to the epidermal interface. After the lactate in the interstitial fluid is enriched to the epidermal interface by reverse iontophoresis technology, the lactate ions first diffuse through the hydrogel protective layer, which has a pH buffering function, and are protonated into electrically neutral lactate molecules in the near-neutral environment. Lactate molecules further diffuse to the surface of the working electrode and are specifically catalyzed by the immobilized lactate oxidase to generate pyruvic acid and hydrogen peroxide. Hydrogen peroxide releases electrons at the electrode surface at the oxidation potential, generating a Faraday current proportional to the lactate concentration. Since the lactate in the interstitial fluid is diluted by the hydrogel when it is extracted to the electrode surface, the electrode detects the diluted lactate concentration. However, this process strictly follows the mass conservation law and steady-state mass transfer conditions. The total amount of lactate transported by electro-osmotic flow is constrained by Faraday's law, and its value is proportional to the product of the applied current and the action time. This total amount is uniformly distributed in the fixed volume of the hydrogel cavity, making the lactate concentration in the gel equal to the total amount of migration divided by the volume of the hydrogel. By pre-calibrating the sensitivity of the electrochemical sensor, the gel concentration can be linearly converted to the current signal. Finally, combined with the electro-migration efficiency, the skin mass transfer coefficient, and the system geometry parameters such as the electrode area and the hydrogel cavity volume, the original concentration of the interstitial fluid can be accurately inverted.

[0058] As can be seen, the steady-state current value generated by the extraction of epidermal lactate can be detected by the lactate sensor, and each steady-state current value corresponds to a specific epidermal lactate concentration. Therefore, the real-time epidermal lactate concentration can be obtained according to the steady-state current value measured by the lactate sensor. Since the extraction process of interstitial fluid lactate and the dilution process of the hydrogel both follow the mass conservation law and steady-state mass transfer conditions, there is a clear linear relationship between the epidermal lactate concentration and the subcutaneous lactate concentration, so the accurate subcutaneous lactate concentration can be calculated from the epidermal lactate concentration.

[0059] The above only describes the preferred embodiments of the present application, and it should be noted that those skilled in the art can make several improvements and refinements without departing from the principles of the present application, which are all considered within the scope of protection of the present application.

Claims

1. A non-invasive method for monitoring lactate dynamics in tissue fluid, characterized in that: The specific steps are as follows: (I) a relationship model between epidermis and subcutaneous lactic acid concentration is established, and the accurate concentration of subcutaneous lactic acid is obtained based on the epidermis lactic acid concentration by using counter-ion electrophoresis technology, and the relationship model is: Wherein, c ilac is the subcutaneous tissue fluid lactic acid concentration; c lac is the epidermis extracted lactic acid concentration; k is the sensor sensitivity; b is the sensor calibration intercept; y2 is the sensor baseline current value; m is the extraction calibration slope; n is the extraction calibration intercept; (II) The epidermal extracted lactic acid concentration is detected by using the lactic acid sensor, and then the accurate concentration value of the transdermal interstitial fluid lactic acid monitoring is obtained through the relationship model.

2. The non-invasive method for monitoring tissue fluid lactate dynamics according to claim 1, wherein: The specific steps are as follows: (1) Establish a relationship model between the epidermis and subcutaneous lactic acid concentration, and obtain the accurate concentration of subcutaneous lactic acid based on the epidermis lactic acid concentration using counter-ion electrophoresis technology, and the relationship model is: Wherein, c ilac is the subcutaneous tissue fluid lactic acid concentration; c lac is the epidermis extracted lactic acid concentration; k is the sensor sensitivity; b is the sensor calibration intercept; y2 is the sensor baseline current value; m is the extraction calibration slope; n is the extraction calibration intercept; (2) The in vitro experiment is carried out by using the lactic acid sensor, and the steady-state current under different epidermal lactic acid concentrations is obtained through the in vitro experiment, and the steady-state current value and the epidermal extracted lactic acid concentration model are established: y=y1+y2=kx+b, wherein y is the steady-state current value, y1 is the net current value of the sensor; y2 is the baseline current value of the sensor; k is the sensitivity of the sensor; x is the epidermal lactic acid concentration; and b is the calibration intercept of the sensor; (3) The human experiment is carried out by using the lactic acid sensor, and the net current value under different subcutaneous lactic acid concentrations is obtained through the human experiment, and the function relationship between the net current value and the subcutaneous lactic acid concentration is established: f=m c+n, wherein f is the net current value, m is the extraction calibration slope, c is the subcutaneous lactic acid concentration, and n is the extraction calibration intercept; (4) The measured epidermal lactic acid concentration is substituted into the relationship model of the epidermal and subcutaneous lactic acid concentrations in step (1) to obtain the accurate concentration value of the transdermal interstitial fluid lactic acid monitoring.

3. The non-invasive interstitial fluid lactate dynamics monitoring method according to claim 1 or 2, characterized in that: The step (2) is configured with a ladder lactic acid concentration PBS buffer before the in vitro experiment.

4. The non-invasive method for monitoring tissue fluid lactate dynamics according to claim 1 or 2, characterized in that: The lactic acid sensor is scanned by cyclic voltammetry before the in vitro experiment to stabilize the electrode, and the chronoamperometric curve is tested in the phosphate buffered saline solution, and the lactic acid detection test is carried out after the curve is stable, and the data is recorded.

5. The non-invasive method for monitoring tissue fluid lactate dynamics according to claim 2, wherein: In the step (2), the epidermal lactic acid concentration is taken as the independent variable, and the steady-state current value under different epidermal lactic acid concentrations is taken as the dependent variable to obtain the function relationship between the steady-state current value and the epidermal lactic acid concentration y=y1+y2=kx+b, wherein y is the steady-state current value, y1 is the net current value of the sensor; y2 is the baseline current value of the sensor; k is the sensitivity of the sensor; x is the epidermal lactic acid concentration; and b is the calibration intercept of the sensor.

6. The non-invasive method for monitoring tissue fluid lactate dynamics according to claim 2, wherein: In the step (3), the lactic acid sensor is attached to the skin surface before the human experiment, and the chronoamperometric curve is tested, and the lactic acid extraction detection test is carried out after the curve is stable, and the data is recorded.

7. The non-invasive method for tissue fluid lactate dynamics monitoring according to claim 2, wherein: In the step (3), the human tissue fluid is extracted by the microneedle during the human experiment, and the subcutaneous lactic acid concentration value is obtained by the in vitro colorimetric detection of the tissue fluid, and the data is recorded.

8. The non-invasive method of tissue fluid lactate dynamics monitoring according to claim 2, wherein: In the step (3), the subcutaneous lactic acid concentration is taken as the independent variable, and the net current value under different subcutaneous lactic acid concentrations is taken as the dependent variable to obtain the function relationship between the extraction net current value and the subcutaneous lactic acid concentration f=m c+n, wherein f is the net current value, m is the extraction calibration slope, c is the subcutaneous lactic acid concentration, and n is the extraction calibration intercept.

9. The non-invasive method of tissue fluid lactate dynamics monitoring according to claim 2, wherein: A relationship model of epidermis and subcutaneous lactic acid concentration is obtained through a function relationship y=y1+y2=k·x+b between steady-state current value and epidermis lactic acid concentration, and a function relationship f=m·c+n between extracted net current value and subcutaneous lactic acid concentration: Wherein, c ilac is subcutaneous tissue fluid lactic acid concentration; c lac is epidermis extracted lactic acid concentration; k is sensor sensitivity; b is sensor calibration intercept; y2 is sensor baseline current value; m is extraction calibration slope; and n is extraction calibration intercept.

10. The non-invasive method for monitoring tissue fluid lactate dynamics according to claim 1 or 2, wherein: The specific steps are as follows: (1) The lactic acid sensor is attached to the skin surface of the human forearm, and the lactic acid sensor includes a counter-ion electro-osmotic extraction electrode and an extraction auxiliary electrode, which can apply a constant current to extract the epidermal tissue fluid; (2) The extracted epidermal tissue fluid is detected by the sensor element of the lactic acid sensor, and the lactic acid sensor adopts electrochemical sensing technology; (3) The detection result is substituted into the function relationship between the steady-state current value and the skin lactate concentration y=y1+y2=k·x+b to obtain accurate skin lactate concentration data; and the accurate subcutaneous lactate concentration value is obtained through the relationship model between the skin and subcutaneous lactate concentrations is obtained.

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