CN116429854A - Method for improving glucose monitoring accuracy in reverse iontophoresis technology - Google Patents
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Abstract
The invention provides a method for improving glucose monitoring accuracy in a reverse iontophoresis technology, which comprises the steps of establishing a prediction model of subcutaneous glucose concentration through theoretical analysis; obtaining the glucose electroosmosis speed under different pH values through in vitro experiments, and further obtaining a functional relation between the glucose electroosmosis speed and the pH value, wherein the functional relation can be used for the subsequent glucose transdermal extraction and detection process; obtaining a calibration intercept by a first blood sampling measurement; the measured pH and the extracted glucose concentration are substituted into a pH correction model to obtain a more accurate glucose test result, so that the accuracy and the reliability of transdermal glucose monitoring are improved.
Description
Technical Field
The invention relates to the technical field of continuous blood glucose monitoring, in particular to a method for improving glucose monitoring accuracy in a reverse iontophoresis technology.
Background
Diabetes is one of the most common chronic diseases worldwide, often resulting in various tissue injuries and dysfunctions, particularly with more pronounced effects on the eyes, heart and blood vessels. With the increase of living standard, the number of diabetics is continuously increased, and the number reaches 6.93 hundred million from 2021 to 2045. Therefore, management and prevention of diabetes becomes particularly important. Currently, the main blood glucose testing methods can be divided into two categories: one is a conventional fingertip blood glucose meter. While this approach may enable self-management of blood glucose levels in diabetics, there is the disadvantage of ignoring hyperglycemic or hypoglycemic information. In addition, this monitoring method also has the problem that the trend and continuous fluctuation of blood sugar cannot be tracked in real time, and frequent finger tests can cause pain and inconvenience to patients. Another emerging continuous blood glucose monitoring method detects glucose levels in biological microfluidics such as sweat, saliva, tears, and interstitial fluid in a non-invasive or minimally invasive manner. The glucose level in these biological microfluidics is highly correlated with blood glucose level, so the method can provide more real-time accurate glucose level information, thereby improving compliance of diabetics.
The current continuous blood glucose monitoring system is mainly based on a subcutaneous implanted electrode type blood glucose biosensor, and the glucose level of subcutaneous interstitial fluid is detected mainly by an electrochemical method so as to realize real-time continuous tracking of the glucose level. The continuous blood glucose monitoring system for commercial application has higher feasibility, acceptance and clinical accuracy, and shows competitive performance in terms of wearability, accuracy and specificity. However, continuous blood glucose monitoring systems with implanted electrodes are minimally invasive, and their microneedles are prone to breakage over time, potentially resulting in pain, bleeding and inflammation, causing additional risk. Thus, there is a need for further development of implantable continuous blood glucose monitoring devices to improve stability and reliability and reduce discomfort and risk to the patient.
Compared with a subcutaneous implanted continuous glucose monitoring device, the transdermal extraction and detection integrated equipment is represented by a reverse iontophoresis technology and has great potential. The device can extract subcutaneous cell interstitial fluid through epidermis and detect the glucose level of the subcutaneous cell interstitial fluid, has the advantages of painless, difficult infection, easy miniaturization and the like, and is suitable for wearable flexible epidermis physiological information detection equipment. In addition, biomarkers, such as glucose, etc., in biological microfluidics transdermally extracted by reverse iontophoresis are easily detected by electrochemical means. This technique measures the extracted interstitial fluid glucose level by applying a gentle current to the skin. In 2001, cygnus corporation introduced the first commercialized GlucoWatch glucose sensor based on the reverse iontophoresis technology, however, the product was released from the market in 2007 due to interference of skin perspiration and erythema caused by current stimulation. With the development of the technology of reverse iontophoresis, the problem is primarily solved by optimizing the methods of applying current intensity, extracting time and the like, but the accuracy of the epidermal glucose detection level based on the technology of reverse iontophoresis interstitial fluid extraction still needs to be further improved, which is of great importance for continuous blood glucose monitoring systems.
Disclosure of Invention
The invention aims to provide a method for improving glucose monitoring accuracy in a reverse iontophoresis technology.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a method for improving glucose monitoring accuracy in a reverse iontophoresis technology is characterized in that the glucose monitoring accuracy in the reverse iontophoresis technology is improved based on pH correction, the relationship between pH and glucose electroosmosis speed under fixed impressed current and duration is further obtained through the glucose electroosmosis speed under different pH values, and a pH correction model is established for monitoring subcutaneous glucose concentration.
Preferably, in the method for improving glucose monitoring accuracy in the reverse iontophoresis technology, the calibration intercept is obtained through first blood sampling measurement; substituting the measured pH and the extracted glucose concentration into a pH correction model to obtain a more accurate glucose test result.
Preferably, in the method for improving the glucose monitoring accuracy in the reverse iontophoresis technology, the glucose electroosmosis speed under different pH values is obtained through in vitro experiments, and the glucose electroosmosis speed is substituted into the epidermal glucose prediction model to obtain more accurate glucose concentration information after pH calibration.
Preferably, the method for improving glucose monitoring accuracy in the reverse iontophoresis technology comprises preparing Tris-HCl buffer solutions with pH of 6.5, 6.9, 7.3, 7.7, 8.1 and 8.5, and adding sodium chloride and glucose to simulate the concentration of sodium ions and glucose in intercellular fluid at normal level of human body.
Preferably, in the method for improving the accuracy of glucose monitoring in the reverse iontophoresis technology, before in vitro experiments, the glucose sensor is scanned by cyclic voltammetry to stabilize the electrode, the timing current curve is tested in phosphate buffer saline solution, and after the curve is stable, the glucose detection test is performed, and data are recorded.
Preferably, in the method for improving glucose monitoring accuracy in the reverse iontophoresis technology, glucose tests with different pH values are performed under the conditions of fixed intensity of externally applied current and extraction time, wherein 7 times of extraction are continuously performed at each pH value to obtain more accurate extraction results, no less than 8 times of repeated measurement is performed at each pH value, accidental errors are avoided, and the glucose extraction coefficient under the pH condition is obtained by fitting the slope between the extracted glucose electroosmosis speed and the extraction times.
Preferably, in the method for improving glucose monitoring accuracy in the reverse iontophoresis technology, the pH value is used as an independent variable, and the slope of the electroosmosis speed of glucose with the extraction times under different pH values is used as a dependent variable to perform fitting, so as to obtain a functional relationship u=k·ph+b between the electroosmosis speed of glucose and pH, wherein k is an extraction coefficient obtained through in vitro experiments; b is the calibration intercept.
Preferably, in the method for improving the accuracy of glucose monitoring in the reverse iontophoresis technology, before each glucose extraction test, the pH detection is performed, the glucose electroosmosis speed dynamically changing with the pH value is obtained according to the pH value detection result, and the glucose electroosmosis speed is substituted into the subcutaneous glucose concentration pH correction model, so that corrected more accurate glucose concentration data is obtained.
Preferably, the method for improving glucose monitoring accuracy in the reverse iontophoresis technology establishes a pH correction model of subcutaneous glucose concentration based on pH correction, wherein the pH correction model is
Preferably, the method for improving glucose monitoring accuracy in the reverse iontophoresis technology comprises the following specific steps:
(1) The glucose sensor is attached to the skin surface of the front side of the forearm of a human body, the glucose sensor comprises a reverse iontophoresis extraction electrode and an extraction auxiliary electrode, cross flow can be applied to extract interstitial fluid, and 200 mu A/cm < 2 > of cross flow is applied in the extraction process to extract the interstitial fluid for 5 minutes.
(2) Glucose and pH are detected on the extracted interstitial fluid, each detection takes 1 minute, and glucose and pH are detected through a sensor element of a glucose sensor, wherein the glucose sensor adopts an electrochemical sensing technology based on enzyme, and the pH sensor adopts a sensing technology based on potential response;
(3) And (3) bringing the detection result into a pH correction model to obtain corrected more accurate glucose concentration data. The pH correction model can eliminate errors caused by different physiological environments and is usually designed based on human tissue characteristics and biochemical reaction mechanisms. The whole extraction detection process is about 7 minutes, and then the measurement can be circularly carried out to realize continuous real-time dynamic monitoring of the subcutaneous glucose concentration.
The beneficial effects are that:
according to the method for improving the accuracy of glucose monitoring in the reverse iontophoresis technology, through dynamically correcting the pH value of the intercellular fluid in real time, the core problem that the fluctuation of the pH value in the transdermal extraction method affects the detection result is solved, the influence of the pH value of the intercellular fluid on the extraction of the reverse iontophoresis skin is eliminated, and therefore the accuracy and the reliability of the monitoring of the epidermal glucose are improved. In addition, because of personal differences and different pH values of intercellular fluids of different parts of the same individual, the method has certain personalized characteristics, can pertinently correct the pH value, improves the monitoring efficiency and portability, and provides a better solution for blood glucose monitoring.
Drawings
FIG. 1 is a flow chart of a method of improving glucose monitoring accuracy in a reverse iontophoresis technique according to the present invention.
FIG. 2 is a graph showing the relationship between the concentration of glucose extracted and the pH of the subcutaneous interstitial fluid according to the present invention.
Detailed Description
In order to solve the problem of pH interference in the process of extracting intercellular fluid from counter ion electroosmosis skin, the invention provides a method for improving glucose monitoring accuracy in a counter ion electroosmosis technology based on pH correction.
A method for improving glucose monitoring accuracy in a reverse iontophoresis technique based on pH correction according to the present invention is described in detail below with reference to the embodiments.
Example 1
In the process of reverse iontophoresis extraction, the fluctuation of the pH value of the subcutaneous intercellular fluid is a key factor affecting the accuracy of the epidermal glucose detection. This example aims at exploring the mechanism of pH effect on the reverse iontophoresis extraction of intercellular fluid, indicating that pH can significantly affect the accuracy of epidermal glucose measurement.
The extraction of interstitial fluid by reverse iontophoresis mainly involves charged ions and neutral molecules such as sodium ions and glucose. For charged species such as sodium ions, electromigration is the primary transport mechanism, i.e., the movement of charged ions under the direct influence of electric field forces. The electron flux is converted into an ion flux by the electrode reaction, and the duration of the current action and the strength of the electric field determine the total amount of charge transport. The main transport mechanism of glucose is electroosmosis, the extraction of which is based on electromigration of sodium ions. The skin is negatively charged at physiological pH, which causes sodium ions in the interstitial fluid to migrate to the skin surface and form an electric double layer comprising a surface charge layer and a diffusion layer. The diffusion layer can be further split into two parts by the sliding surface, reflecting the zeta potential contribution to the electroosmotic rate. When the electrode is placed in the vicinity of the skin, sodium ions migrate toward the cathode, causing sodium ions to flow from the anode to the cathode. Thus, glucose dissolved in the subcutaneous intercellular fluid also moves toward the cathode under the osmotic pressure gradient caused by sodium ions. Glucose is catalyzed by glucose oxidase, which provides a measurable signal. The sodium ions attracted by the negative charges of the epidermis in the electric double layer play a decisive role in the electromigration flux. The pH of the interstitial fluid in contact with the skin affects glucose ion transport. Specifically, the isoelectric point of human skin ranges from 4 to 4.5, above which the carboxylic acid groups of the skin surface proteins release protons and are negatively charged, and below which they are positively charged. The pH of the subcutaneous interstitial fluid is above this value; thus, epidermal skin is negatively charged at physiological pH. The amount of skin charge can change with changes in pH, which changes the zeta potential in the double layer, thereby affecting the rate at which RI extracts glucose.
It can be seen that in physiological conditions, the pH of the intercellular fluid is maintained between 7.35 and 7.45, and when the pH is changed after ingestion or exercise by the human body, the skin chargeability and permeability of the skin barrier may be affected, thereby affecting the transdermal extraction of glucose. In particular, the permselectivity of the skin is strongly dependent on the pH of the surrounding medium. The skin is negatively charged because the ampholyte amino acids in the skin are negatively charged under normal physiological conditions, while the pH of the interstitial fluid can change the ionization degree of the amino acids, thereby changing how much the skin is negatively charged and thus affecting the flux of glucose electroosmosis. The pH value of intercellular fluid is an important physiological parameter, and the variation of the pH value of the intercellular fluid can also influence the flux of transdermal glucose extraction due to the difference between individuals and different body parts of the same individual. Therefore, the dynamic correction of pH fluctuation in transdermal glucose detection can monitor the transdermal glucose more accurately.
Example 2
As shown in fig. 1, the method for improving glucose monitoring accuracy in the reverse iontophoresis technology based on pH correction comprises the following specific steps:
step S1, theoretical analysis is carried out to establish a predictive model of subcutaneous glucose concentration based on pH correction
Theoretically, the glucose transdermal extraction flux can be calculated by the following formula:
J glu ＝c glu ·V gel /T
wherein J is glu For glucose extraction flux, c glu For the concentration of glucose extracted, V gel For the volume of Nafion hydrogel, T is the time for which current is applied against iontophoresis. Further, J glu It can also be expressed as:
J glu ＝A·u·c iglu ·U/d
wherein A is the surface area of the extraction electrode, c iglu For the subcutaneous intercellular fluid glucose concentration, U is the magnitude of the applied voltage, d is the spacing between the extraction electrodes, and U is the speed of transdermal glucose extraction by reverse iontophoresis, expressed as a function of the intercellular fluid pH equation u=k·ph+b. Wherein k is an extraction coefficient which can be obtained through in vitro experiments; b is the intercept, which can be obtained by calibration using a hemostix at the time of the first measurement.The concentration of transdermally extracted glucose c according to the above formula glu And subcutaneous interstitial fluid glucose concentration c iglu There is a relationship between pH factors:
thus, by detecting information such as the transdermally extracted glucose concentration and the pH of the interstitial fluid, real-time measurements of glucose concentration can be obtained noninvasively.
S2, obtaining the functional relation between the glucose electroosmosis speed and the pH through in vitro experiments
Tris-HCl buffers with pH of 6.5, 6.9, 7.3, 7.7, 8.1 and 8.5 were first prepared, and sodium chloride and glucose were added to simulate the intercellular sodium ions and glucose concentrations at normal levels in humans. And secondly, performing cyclic voltammetry scanning on the glucose sensor to stabilize the electrode, testing a timing current curve in phosphate buffer saline solution, performing a glucose extraction test after the curve is stable, and recording data. Before each extraction experiment, a preheating process is performed to eliminate the problem of current source overload, so that the test results of each group need to be normalized to eliminate the interference of background current generated by preheating. Then, glucose extraction tests with different pH values are carried out, wherein 7 times of extraction are continuously carried out at each pH value to obtain more accurate extraction results, and repeated measurement is carried out at least 8 times at each pH value, so that accidental errors are avoided. The data on the rate of glucose electroosmosis at this pH is obtained by fitting the slope between the rate of glucose extracted by reverse iontophoresis and the number of extractions. And finally, carrying out data fitting by taking the pH value as an independent variable and taking the slope of the electroosmosis speed of glucose with the extraction times under different pH values as a dependent variable to obtain the functional relation between the glucose extraction speed and the pH value. That is, the value of the extraction coefficient k is obtained.
Step S3, obtaining a calibration intercept by first blood sampling measurement
The effect of individual differences should be taken into account before the first epidermal glucose extraction test is performed. In order to obtain more accurate direct information of the relationship between the subcutaneous interstitial fluid glucose concentration and the transdermally extracted glucose concentration, the subject needs to be lancing with a fingertip hemostix to calibrate the intercept b before the sample is collected. This step is critical to the establishment of an epidermal glucose predictive model. The epidermal glucose predictive model contains key information for extracting glucose concentration and subcutaneous actual glucose concentration. This model also takes into account measurement disturbances caused by pH fluctuations, providing more accurate glucose concentration information.
S4, substituting the pH measurement result and the extracted glucose concentration into a calibration model to obtain an accurate value of the glucose concentration after pH calibration
After the extraction coefficient k and the calibration intercept b required by the epidermis glucose prediction model are obtained, a more accurate relation model between the subcutaneous interstitial fluid glucose concentration and the transdermal extracted glucose concentration is obtained by fitting the functional relation of the glucose electroosmosis speed along with the pH change. At each glucose extraction test, the measured pH and the extracted glucose concentration are substituted into the calibration formula to achieve a more accurate epidermal glucose test result based on pH calibration. During the epidermal glucose test, changes in pH may interfere with the measurement. In order to eliminate measurement interference caused by pH fluctuation, the invention provides a pH calibration epidermal glucose detection method for realizing more accurate epidermal glucose test results. The calibration formula is based on the glucose electroosmotic rate as a function of pH, uses pH to calibrate the data, and calculates the epidermal glucose concentration from the extraction coefficient k and the calibration intercept b. This will help to more accurately assess the effectiveness of a patient's diabetes management and treatment regimen and to prevent the occurrence of diabetes and complications.
Example 3
The glucose monitoring method using the technique described in example 2 above comprises the following specific steps:
first, a glucose sensor is attached to the skin surface of the front side of the forearm of a human body. The glucose sensor comprises a counter iontophoresis extraction electrode and an extraction auxiliary electrode, capable of applying a lateral flow in order to extract interstitial fluid. During the extraction, a lateral flow of 200. Mu.A/cm 2 was applied, and the interstitial fluid was extracted for 5 minutes.
Subsequently, the extracted interstitial fluid was subjected to glucose and pH tests, each of which took 1 minute. The glucose sensor comprises a sensor element that can detect glucose and pH. Wherein, the glucose sensor adopts an electrochemical sensing technology based on enzyme, and the pH sensor adopts a sensing technology based on potential response.
And finally, the detection result is brought into a pH correction model, so that more accurate corrected glucose concentration data can be obtained. The pH correction model can eliminate errors caused by different physiological environments and is usually designed based on human tissue characteristics and biochemical reaction mechanisms. The whole extraction detection process is about 7 minutes, and then the measurement can be circularly carried out to realize continuous real-time dynamic monitoring of the subcutaneous glucose concentration.
As shown in fig. 2, the preliminary results of the step S2 show that the extraction results of glucose have a good linear fit with the pH change, and the slope and the linear correlation coefficient are 0.88617 and 0.93014, respectively. Specifically, the extraction amount of glucose shows a linear relationship with pH at different pH values, and when the pH value is higher, the reverse iontophoresis speed of glucose is higher under the same condition, so that the extracted glucose flux is also higher, which leads to an error in glucose detection. Since the extracted glucose concentration and the rate of glucose electroosmosis are linearly related, this result demonstrates that the rate of glucose electroosmosis and the subcutaneous interstitial fluid are linearly related, further demonstrating the effectiveness of the calibration model. It is stated that in continuous real-time dynamic monitoring of subcutaneous glucose concentration, pH calibration is required to eliminate its interference with glucose detection. The pH correction model based on human tissue characteristics and biochemical reaction mechanisms can effectively eliminate errors and improve the detection accuracy of subcutaneous glucose concentration.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (10)
1. A method for improving glucose monitoring accuracy in a reverse iontophoresis technology, which is characterized in that: the accuracy of glucose monitoring in the anti-iontophoresis technology is improved based on pH correction, the relation between pH and glucose electroosmosis speed under fixed impressed current and duration is further obtained through the glucose electroosmosis speed under different pH values, and a pH correction model is established for monitoring subcutaneous glucose concentration.
2. The method for improving glucose monitoring accuracy in a reverse iontophoresis technique of claim 1, wherein: obtaining a calibration intercept by a first blood sampling measurement; substituting the measured pH and the extracted glucose concentration into a pH correction model to obtain a more accurate glucose test result.
3. The method for improving glucose monitoring accuracy in a reverse iontophoresis technique of claim 1, wherein: and obtaining glucose electroosmosis speeds under different pH values through in vitro experiments, and substituting the glucose electroosmosis speeds into an epidermal glucose prediction model to obtain more accurate glucose concentration information after pH calibration.
4. A method for improving glucose monitoring accuracy in a reverse iontophoresis technique as claimed in claim 3, wherein: in vitro experiments included the preparation of Tris-HCl buffers at pH 6.5, 6.9, 7.3, 7.7, 8.1, 8.5, with the addition of sodium chloride and glucose to mimic the normal levels of intercellular sodium ions and glucose concentrations in humans.
5. A method for improving glucose monitoring accuracy in a reverse iontophoresis technique as claimed in claim 3, wherein: the glucose sensor is scanned by cyclic voltammetry to stabilize the electrode before in vitro experiments are carried out, the timing current curve is tested in phosphate buffer saline, the glucose detection test is carried out after the curve is stable, and data are recorded.
6. The method for improving glucose monitoring accuracy in a reverse iontophoresis technique of claim 1, wherein: glucose tests of different pH values are carried out under the condition of fixing the intensity of the externally applied current and the extraction time, and the glucose extraction coefficient under the pH condition is obtained by fitting the slope between the extraction glucose electroosmosis speed and the extraction times.
7. The method for improving glucose monitoring accuracy in a reverse iontophoresis technique of claim 6, wherein: fitting by taking the pH value as an independent variable and taking the slope of the glucose electroosmosis speed with the extraction times under different pH values as a dependent variable to obtain a functional relation u=k.pH+b between the glucose electroosmosis speed and the pH, wherein k is an extraction coefficient obtained through in vitro experiments; b is the calibration intercept.
8. The method for improving glucose monitoring accuracy in a reverse iontophoresis technique of claim 7, wherein: before each glucose extraction test, pH detection is carried out, the glucose electroosmosis speed which dynamically changes along with the pH value is obtained according to the pH value detection result, and the glucose electroosmosis speed is substituted into a subcutaneous glucose concentration pH correction model, so that corrected more accurate glucose concentration data are obtained.
9. The method for improving glucose monitoring accuracy in a reverse iontophoresis technique of claim 1, wherein: establishing a pH correction model of subcutaneous glucose concentration based on pH correction, wherein the pH correction model is that
10. The method for improving glucose monitoring accuracy in a reverse iontophoresis technique of claim 9, wherein: the method comprises the following specific steps:
(1) The glucose sensor is attached to the skin surface of the front side of the forearm of a human body, the glucose sensor comprises a reverse iontophoresis extraction electrode and an extraction auxiliary electrode, cross flow can be applied to extract interstitial fluid, and 200 mu A/cm < 2 > of cross flow is applied in the extraction process to extract the interstitial fluid for 5 minutes.
(2) Glucose and pH are detected on the extracted interstitial fluid, each detection takes 1 minute, and glucose and pH are detected through a sensor element of a glucose sensor, wherein the glucose sensor adopts an electrochemical sensing technology based on enzyme, and the pH sensor adopts a sensing technology based on potential response;
(3) And (3) bringing the detection result into a pH correction model to obtain corrected more accurate glucose concentration data.
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