CN120381237A

CN120381237A - Method, system and medium for correcting sensitivity decay of analyte sensors

Info

Publication number: CN120381237A
Application number: CN202410128340.6A
Authority: CN
Inventors: 李晓波
Original assignee: Shenzhen Guiji Sensing Technology Co ltd
Current assignee: Shenzhen Guiji Sensing Technology Co ltd
Priority date: 2024-01-27
Filing date: 2024-01-27
Publication date: 2025-07-29
Also published as: WO2025157150A1

Abstract

This disclosure describes a method, system, and medium for correcting sensitivity decay in an analyte sensor. The method includes applying a first input signal to at least two electrodes of the analyte sensor at least once within a calibration time and acquiring a response signal corresponding to the first input signal; obtaining a correction factor based on at least one response parameter of the response signal and at least one reference parameter of a reference signal curve; correcting a target parameter of the analyte sensor related to sensitivity decay based on the correction factor; and determining the analyte level based on the signal related to the analyte level acquired by the analyte sensor and the corrected target parameter. This method improves the accuracy and convenience of determining the analyte level.

Description

Correction method, system and medium for sensitivity decay of analyte sensor

Technical Field

The present disclosure relates to the field of biomedical engineering industry, and in particular to a method, system, and medium for correcting sensitivity decay of an analyte sensor.

Background

Diabetes is a series of metabolic disorders of proteins, fats, water, electrolytes, etc. caused by insufficient insulin secretion and reduced sensitivity of target tissue cells to insulin. Currently, continuous glucose monitoring (Continuous Glucose Monitoring, CGM) techniques can continuously monitor glucose in a user's tissue fluid, for example, continuous glucose monitoring techniques based on electrochemical analysis, and glucose sensors for monitoring glucose concentration can typically be subcutaneously placed to monitor changes in glucose concentration in subcutaneous tissue fluid.

Glucose sensors used for continuous glucose monitoring typically exhibit a gradual decrease in accuracy in determining analyte levels over time, known as "sensitivity decay," "sensor drift," or "sensor discoloration," which may be caused by a variety of factors including sensor aging, immune response, or environmental factors, among others. The current correction method for sensitivity attenuation is to collect the fingertip blood of the user to detect the blood glucose value, and then use the blood glucose value as the correction value for continuous glucose monitoring.

However, multiple collection of fingertip blood reduces user comfort and ease of use, and how to reduce the effect of sensitivity decay on glucose detection without relying on additional collection of blood remains to be studied.

Disclosure of Invention

The present disclosure has been made in view of the above-described state of the art, and an object thereof is to provide a correction method, system and medium for sensitivity decay of an analyte sensor capable of improving accuracy and convenience in determining an analyte level.

To this end, a first aspect of the present disclosure provides a correction method for sensitivity decay of an analyte sensor, comprising applying a first input signal to at least two electrodes of the analyte sensor at least once during a correction time and acquiring a response signal corresponding to the first input signal, obtaining a correction factor based on at least one response parameter of the response signal and at least one reference parameter of a reference signal curve, correcting a target parameter of the analyte sensor related to the sensitivity decay based on the correction factor, determining the analyte level based on a signal acquired by the analyte sensor related to the analyte level and the corrected target parameter.

In a first aspect of the present disclosure, electrochemical performance can be measured in real time during use of an analyte sensor by applying a first input signal to at least two electrodes of the analyte sensor over a correction time and collecting corresponding response signals, obtaining a correction coefficient based on at least one response parameter of the response signals and at least one reference parameter of a reference signal curve, the correction coefficient for approximating the response parameter to the reference parameter can be obtained by taking the reference signal curve as a standard, and the analyte sensor having sensitivity decay can be made to obtain an analyte level having no sensitivity decay by correcting a target parameter based on the obtained correction coefficient and determining the analyte level based on the corrected target parameter. Thereby, the accuracy of determining the analyte level can be improved. In addition, unlike calibration analyte sensors that use fingertip blood as a standard, the convenience of determining analyte levels can be improved by using a reference signal curve that corresponds to when no sensitivity decay occurs as a standard.

In addition, in the correction method according to the first aspect of the present disclosure, optionally, the signal waveform of the first input signal includes a combination of at least two pulse waves, and pulse amplitudes of the at least two pulse waves are different to form the signal waveform in a stepwise manner. In this case, the stepped signal waveforms have different pulse amplitudes, and applying the signal waveforms of different pulse amplitudes to the electrodes enables the corresponding response signals to reflect more information of the electrodes, such as the specificity, response time, or linear range, and further enables the correction coefficients used in the correction to include more information of the electrodes, thereby enabling further improvement in the accuracy of determining the analyte level.

In addition, in the correction method according to the first aspect of the present disclosure, optionally, fitting is performed based on the response signal to obtain a response signal curve, the response signal curve is subjected to coordinate transformation, and at least one response parameter of the response signal is obtained based on the response signal curve subjected to coordinate transformation. In this case, the obtained discrete data is fitted to a continuous response signal curve, so that the information related to the sensitivity decay can be conveniently extracted from the response signal, in addition, the response signal can be smoothed by fitting, so that the data fluctuation caused by acquisition errors or other factors can be reduced, in addition, the response signal can be interpolated by fitting to obtain a continuous response signal curve, so that the accuracy of the obtained response parameters can be improved. In addition, the response signal curve can be converted from a curve form to a linear form through coordinate conversion, and further, the linear can be directly processed without considering the problem of how to select the slope of the feature point when the response signal curve is in the curve form, so that the correction method can be simplified.

Further, in the correction method according to the first aspect of the present disclosure, optionally, the reference signal curve is obtained and stored based on a second input signal, which is identical to a signal waveform of the first input signal, and at least one response parameter of the response signal and at least one reference parameter of the reference signal curve are obtained at the time of correction, and/or the reference signal curve is obtained based on a third input signal, which is identical to a signal waveform of the first input signal, and a plurality of attenuation signal curves are obtained based on the third input signal at different periods of time, a target relationship is determined and stored based on at least one reference parameter of the reference signal curve and at least one response parameter of the plurality of attenuation signal curves, the target relationship being determined based on at least one response parameter of the response signal and the target relationship at the time of correction, the target relationship representing a relationship of the response parameter and the correction coefficient, and the third input signal being identical to a signal waveform of the first input signal. In this case, by performing the correction based on the stored reference signal profile when based on the second input signal, the standard used for the correction can be kept intact, the loss of information can be reduced compared to converting the reference signal profile into other information, and the accuracy of determining the analyte level can be improved. In addition, when the third input signal is based, the target relation is obtained based on the reference signal curve and the attenuation signal curve before correction, and the correction coefficient is obtained based on the target relation during correction, so that the correction coefficient is conveniently obtained through simple calculation or obtained through searching the lookup table, the processing steps during correction can be reduced, the correction speed can be further improved, and the instantaneity of the correction method can be improved.

In addition, in the correction method according to the first aspect of the present disclosure, optionally, the reference signal curve is obtained based on a preset formula related to the input signal, and/or the reference signal curve is obtained based on a response signal corresponding to the applied input signal. In this case, the reference signal curve is obtained by a preset formula, it is possible to facilitate rapid acquisition of the reference signal curve before correction, and to obtain an ideal reference signal curve without sensitivity attenuation, that is, to obtain a theoretical value near without sensitivity attenuation, and in addition, the reference signal curve obtained before correction can be made to approach a true value without sensitivity attenuation by actually applying an input signal to obtain a response signal to obtain the reference signal curve.

In addition, in the correction method according to the first aspect of the present disclosure, optionally, when the input signal is a step wave, the preset formula is expressed as: wherein I is the reference signal curve, A is the proportionality coefficient, and t is the time. Thus, the reference parameter can be obtained based on the proportionality coefficient in the preset formula, and the calibration coefficient can be obtained based on the reference parameter.

In addition, in the correction method according to the first aspect of the present disclosure, optionally, a parameter type of the response parameter and a parameter type of the reference parameter are identical, the parameter type including one or more of a peak value, an area under a curve, and a slope of the curve. In this case, it can be convenient to directly compare the response parameter and the reference parameter, and thus a difference between the response signal and the reference signal can be obtained. In this case, when the parameter type is a peak value, the maximum response value of the response signal to the input signal can be reflected, and the maximum response capability of the analyte sensor to the input signal can be obtained, so that the degree of attenuation of the sensitivity can be obtained. In addition, when the parameter type is an integral under a curve, the cumulative response of the response signal to the input signal can be reflected, and the charge accumulation capacity of the analyte sensor can be obtained, so that the degree of attenuation of the sensitivity can be obtained. In addition, when the parameter type is a curve slope, the degree of the decrease or increase of the response signal can be reflected, and the response speed of the analyte sensor can be obtained, so that the degree of the attenuation of the sensitivity can be obtained.

Further, in the correction method according to the first aspect of the present disclosure, optionally, the target parameter is a sensitivity coefficient, the sensitivity of the analyte sensor is corrected based on the sensitivity coefficient, the analyte level is determined based on the corrected sensitivity, and/or the target parameter is a current compensation coefficient, the current value of the analyte sensor is corrected based on the current compensation coefficient, and the analyte level is determined based on the corrected current value. In this case, the sensitivity or the current value can be corrected indirectly by correcting the target parameter.

A second aspect of the present disclosure provides an analyte monitoring system comprising an analyte sensor configured to acquire a signal related to an analyte level and apply an input signal to at least two electrodes of the analyte sensor for a correction time and acquire a response signal corresponding to the input signal, and a processing module configured to receive the signal and the response signal and determine the analyte level using the correction method according to the first aspect of the present disclosure. Thereby, the accuracy and convenience of the analyte monitoring system in determining the analyte level can be improved.

Additionally, in the analyte monitoring system of the second aspect of the present disclosure, optionally, the analyte sensor further comprises a mode switching module including a switching circuit to cause the analyte sensor to have an operational mode and a calibration mode. In this case, the analyte sensor can be facilitated to determine the analyte level during the on-time and to calibrate during the calibration time, which can improve the operational efficiency of the analyte monitoring system.

A third aspect of the present disclosure provides a computer readable storage medium storing at least one instruction that when executed by a processor implements the correction method of the first aspect of the present disclosure or implements the analyte monitoring system of the second aspect of the present disclosure.

In accordance with the present disclosure, a correction method, system, and medium for sensitivity decay of an analyte sensor are provided that can improve the accuracy and convenience of determining analyte levels.

Drawings

Embodiments of the present disclosure will now be explained in further detail by way of example only with reference to the accompanying drawings.

Fig. 1 is an application scenario diagram illustrating an analyte monitoring system according to an example of the present disclosure.

Fig. 2 is a system block diagram illustrating an analyte monitoring system in accordance with examples of the present disclosure.

Fig. 3 is a flow chart illustrating a correction method for sensitivity decay of an analyte sensor in accordance with examples of the present disclosure.

Fig. 4A is a schematic diagram showing embodiment 1 of a signal waveform of a first input signal according to an example of the present disclosure.

Fig. 4B is a schematic diagram showing embodiment 2 of a signal waveform of a first input signal according to an example of the present disclosure.

Fig. 4C is a schematic diagram showing embodiment 3 of a signal waveform of the first input signal according to the example of the present disclosure.

Fig. 4D is a schematic diagram showing a4 th embodiment of a signal waveform of a first input signal according to an example of the present disclosure.

Fig. 4E is a schematic diagram showing a5 th embodiment of a signal waveform of a first input signal according to an example of the present disclosure.

Fig. 5 is a schematic diagram illustrating acquisition response signals related to examples of the present disclosure.

Fig. 6 is a flow chart illustrating application of a first input signal and acquisition of a corresponding response signal in accordance with examples of the present disclosure.

Fig. 7A is a flowchart showing embodiment 1 of obtaining correction coefficients according to an example of the present disclosure.

Fig. 7B is a flowchart showing embodiment 2 of obtaining correction coefficients according to an example of the present disclosure.

Detailed Description

Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the following description, the same members are denoted by the same reference numerals, and overlapping description thereof is omitted. In addition, the drawings are schematic, and the ratio of the sizes of the components to each other, the shapes of the components, and the like may be different from actual ones.

It should be noted that the terms "comprises" and "comprising," and any variations thereof, in this disclosure, such as a process, method, system, article, or apparatus that comprises or has a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus, but may include or have other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

The present disclosure relates to a correction method for sensitivity attenuation of an analyte sensor (hereinafter may be simply referred to as a correction method, may also be referred to as an analyte sensor correction method or a calibration method, etc.), and the correction method according to the present disclosure may be applied to a case where the analyte sensor is in a state of sensitivity attenuation, where an analyte level acquired when the analyte sensor is in the state of sensitivity attenuation deviates from an analyte level acquired when the analyte sensor is not subjected to sensitivity attenuation, that is, an offset analyte level is acquired. For example, due to long service time, the sensor may be degraded due to chemical reaction, physical change, or loss, i.e., the sensitivity of the analyte sensor may be degraded. By the correction method provided by the disclosure, the accuracy and convenience of determining the analyte level can be improved.

The sensitivity to which the present disclosure relates may be a parameter related to the ability of the sensor to detect or respond to changes in analyte levels. The sensitivity coefficient to which the present disclosure relates may be a parameter for correcting the sensitivity of the analyte sensor. The sensitivity to which the present disclosure relates may be a parameter for correcting a signal of the analyte sensor related to the analyte level (hereinafter referred to simply as an analyte signal).

It is noted that the improvement in the accuracy of determining the analyte level in relation to the present disclosure may be to make the analyte level obtained after correction approach or equal to the analyte level obtained when no sensitivity decay has occurred. For example, where the analyte is glucose in a tissue fluid and the analyte level is the glucose concentration in the tissue fluid, the analyte sensor may be a sensor that includes an enzyme that undergoes a redox reaction with glucose (e.g., glucose oxidase or glucose dehydrogenase), and the improvement in accuracy of determining the analyte level in accordance with the present disclosure may be to approximate or equal the glucose concentration obtained after calibration to the glucose concentration obtained when no sensitivity decay of the analyte sensor has occurred.

The increased accuracy of determining the analyte level to which the present disclosure relates may be to have the acquired analyte level approach or equal to the reference analyte level. For example, where the analyte is glucose, the reference analyte level may be the glucose concentration in the fingertip blood.

The present disclosure also provides an analyte monitoring system that can collect an analyte signal, apply an input signal to two electrodes of an analyte sensor for a calibration time and collect a response signal corresponding to the input signal, receive the analyte signal and the response signal, and determine an analyte level using the calibration method described above. The time of use of the analyte monitoring system may be 1 week, 2 weeks, 3 weeks, or 4 weeks. The calibration methods contemplated by the present disclosure enable the analyte monitoring system to maintain good accuracy in determining analyte levels over the time of use.

In some examples, the analyte may be one or more of glucose, acetylcholine, amylase, bilirubin, cholesterol, chorionic gonadotrophin, creatine kinase, creatine, DNA, fructosamine, glutamine, growth hormone, ketone body, lactate, oxygen, peroxide, prostate specific antigen, prothrombin, RNA, thyroid stimulating hormone, or troponin. In some examples, when the analyte is glucose, the analyte level may be a glucose concentration.

The analyte sensor to be corrected to which the examples of the present disclosure relate may be an analyte sensor in which a sensitivity decay occurs. The analyte sensor that does not require calibration may be an analyte sensor that does not experience sensitivity decay.

Examples of the present disclosure are described below with reference to the accompanying drawings, taking the example that the analyte is glucose in interstitial fluid, and such description is not limiting the scope of the present disclosure.

Fig. 1 is a diagram illustrating an application scenario of an analyte monitoring system 1 according to an example of the present disclosure.

In some examples, analyte monitoring system 1 may include an analyte sensor 10 and a processing module 20. As shown in fig. 1, the analyte sensor 10 may be implanted subcutaneously in a target object or mounted on the skin surface, and the analyte sensor 10 may be configured to collect analyte signals. Processing module 20 may be configured to receive the analyte signal and determine the analyte level. The present disclosure is not limited to the arrangement position of the treatment module 20 shown in fig. 1, and for example, the treatment module 20 may be arranged on the skin surface of the target object.

Fig. 2 is a system block diagram illustrating an analyte monitoring system 1 in accordance with examples of the present disclosure.

In some examples, analyte sensor 10 may include at least two electrodes 100. At least two electrodes 100 may be implanted subcutaneously in a subject to react with the analyte in the subcutaneous tissue fluid and produce a continuous signal related to the level of the analyte. The at least two electrodes 100 may include a working electrode and a counter electrode. In this case, at least two electrodes 100 of the analyte sensor 10 are capable of reacting with and forming a circuit with the analyte, thereby being capable of generating a continuous signal related to the level of the analyte.

The at least two electrodes 100 to which the present disclosure relates may further include three electrodes 100. In some examples, the three electrodes 100 may be a working electrode, a reference electrode, and a counter electrode, respectively. The at least two electrodes 100 may further include four electrodes 100. In some examples, the four electrodes 100 may be a working electrode, a reference electrode, a blank electrode, and a counter electrode, respectively. In this case, the generated analyte signal can be made more accurate by providing a reference stable potential using the function of the other electrode 100, for example, the reference electrode.

In some examples, processing module 20 may determine the analyte level based on the analyte signal and the target parameter. In particular, processing module 20 may amplify, filter, analog-to-digital convert, and calculate the corresponding analyte level of the signal based on the target parameter.

The target parameter to which the present disclosure relates may be a parameter related to sensitivity decay. For example, the target parameter may be a sensitivity coefficient. The target parameter may also be other parameters for determining the analyte level.

When the analyte sensor 10 is in a sensitivity-decaying state, the analyte monitoring system 1 may determine the analyte level using the calibration methods involved in the present disclosure. Specifically, the correction time may be set at the gap of the operating time. During operation, the analyte monitoring system 1 may collect an analyte signal and determine an analyte level based on the analyte signal and a target parameter. The analyte monitoring system 1 may apply an input signal to at least two electrodes 100 of the analyte sensor 10 over a calibration time, collect a response signal corresponding to the input signal and determine an analyte level based on the analyte signal and the response signal using the calibration methods contemplated by the present disclosure. Thereby, the accuracy of determining the analyte level of the analyte sensor 10, in which the sensitivity decay occurs, can be improved.

As shown in fig. 2, the analyte monitoring system 1 may include an analyte sensor 10 and a processing module 20. The analyte sensor 10 may include at least two electrodes 100. The analyte sensor 10 may be configured to acquire an analyte signal and apply an input signal to at least two electrodes 100 of the analyte sensor 10 for a correction time and acquire a response signal corresponding to the input signal. Processing module 20 may be configured to receive the analyte signals and the response signals and determine the analyte level using the calibration methods contemplated by the present disclosure.

In some examples, analyte sensor 10 may also include a mode switching module 200. The mode switching module 200 may include switching circuitry to provide the analyte sensor 10 with an operating mode and a calibration mode. In some examples, during an operating time, mode switch module 200 may switch to an operating mode and analyte monitoring system 1 may determine an analyte level. In some examples, during the calibration time, mode switch module 200 may switch to the calibration mode and analyte monitoring system 1 may calibrate the target parameter. In this case, the analyte sensor 10 can be facilitated to determine the analyte level during the operation time and to correct during the correction time, and thus the operation efficiency of the analyte monitoring system 1 can be improved.

In some examples, analyte sensor 10 may also include a signal source 300. The signal source 300 may be configured to generate an input signal. The generated input signal may be applied to at least two electrodes 100 of the analyte sensor 10. Preferably, when analyte sensor 10 includes three electrodes 100, it can be applied to both the working electrode and the reference electrode. The input signals may include a first input signal, a second input signal, and a third input signal. The signal waveform of the input signal may include one or more combinations of pulse waves, step waves, saw tooth waves, triangular waves, sine waves, and rectangular waves. The second input signal may be the same signal waveform as the first input signal. The third input signal may be the same signal waveform as the first input signal.

In some examples, analyte monitoring system 1 may further include a first sampling module 30. The first sampling module 30 may sample the continuous signal associated with the analyte level generated by the at least two electrodes 100 during the operating time to obtain a discrete signal associated with the analyte level. Specifically, the first sampling module 30 may include an analog-to-digital converter to sample the discrete signals.

In some examples, the first sampling module 30 may also sample the response signal corresponding to the input signal during the correction time. In some examples, analyte monitoring system 1 may further include a second sampling module 40, and second sampling module 40 may be configured to sample a response signal corresponding to the input signal during the correction time. That is, the first sampling module 30 sampling during the operation time may be used when sampling the response signal corresponding to the input signal during the correction time, or the second sampling module 40 may be used.

The analyte monitoring system 1 to which the present disclosure relates may include at least two circuits. I.e. at least a working circuit formed by the working electrode and the counter electrode and a measuring circuit formed by the working electrode and the reference electrode. The collection of analyte signals in accordance with the present disclosure may be collection of current signals flowing through the working electrode during a working time. The acquisition response signal to which the present disclosure relates may be a current signal flowing through the working electrode corresponding to the acquisition input signal. For example, a voltage is applied as a first input signal to the working electrode and the reference electrode, and an enzyme disposed on the working electrode reacts with the analyte and generates a current, which is collected at the working electrode as a response signal. The current as a response signal may be related to the sensitivity decay of the analyte sensor 10. The current as a response signal may also be correlated to the analyte level. The acquisition of the analyte signal and the acquisition response signal may be performed by one sampling module or by two different sampling modules.

In some examples, analyte monitoring system 1 may also include a storage module 50. The storage module 50 may store relevant data for correcting the target parameter. In some examples, the relevant data for correcting the target parameter may be a target relationship (including a look-up table or an adjustment coefficient), a reference signal curve, at least one reference parameter of the reference signal curve, or a correction coefficient.

Fig. 3 is a flowchart illustrating a correction method for sensitivity decay of the analyte sensor 10 according to an example of the present disclosure.

The correction method according to the present disclosure may be applied to the analyte monitoring system 1 described above. Further, the correction methods according to the present disclosure may be applied to the processing module 20 described above, i.e., the processing module 20 may determine the analyte level using the correction methods according to the present disclosure.

Referring to FIG. 3, in some examples, the correction method may include applying a first input signal to at least two electrodes 100 of the analyte sensor 10 at least once during a correction time, and acquiring a response signal corresponding to the first input signal (step S100), obtaining a correction coefficient based on at least one response parameter of the response signal and at least one reference parameter of a reference signal curve (step S200), correcting a target parameter of the analyte sensor 10 related to sensitivity decay based on the correction coefficient (step S300), and determining an analyte level based on the signal related to analyte level acquired by the analyte sensor 10 and the corrected target parameter (step S400).

With continued reference to fig. 3, in some examples, in step S100, a first input signal may be applied to at least two electrodes 100 of analyte sensor 10. In some examples, the signal waveform of the first input signal may include a combination of one or more of a pulse wave, a step wave, a sawtooth wave, a triangle wave, a sine wave, a step wave, and a rectangular wave. The combination referred to in this disclosure refers to the superposition of multiple signal waveforms. In particular, it is possible that a plurality of signal waveforms are aligned and superimposed on a period or staggered and superimposed on a period. For example, a signal waveform having a pulse wave with a higher pulse amplitude can be obtained when two pulse waves are aligned and superimposed on the cycle, and a signal waveform having two pulse waves can be obtained when two pulse waves are staggered and superimposed on the cycle. In some examples, the first input signal may be generated by the signal source 300.

Fig. 4A is a schematic diagram showing embodiment 1 of a signal waveform of a first input signal according to an example of the present disclosure. Fig. 4B is a schematic diagram showing embodiment 2 of a signal waveform of a first input signal according to an example of the present disclosure. Fig. 4C is a schematic diagram showing embodiment 3 of a signal waveform of the first input signal according to the example of the present disclosure.

Fig. 4D is a schematic diagram showing a4 th embodiment of a signal waveform of a first input signal according to an example of the present disclosure. Fig. 4E is a schematic diagram showing a 5 th embodiment of a signal waveform of a first input signal according to an example of the present disclosure.

As described above, the signal waveform of the first input signal may include one or more combinations of pulse waves, step waves, saw-tooth waves, triangular waves, sine waves, step waves, and rectangular waves. To this end, the present disclosure also provides examples of signal waveforms of some of the first input signals.

Referring to embodiment 1 shown in fig. 4A, the signal waveform of the first input signal may be a step wave. The abscissa is time and the ordinate is the amplitude of the first input signal. In addition, the first input signal may return to a low level after application is complete or other level that does not affect the analyte monitoring system 1 being in an operational mode.

Referring to embodiment 2 shown in fig. 4B, the signal waveform of the first input signal may be a pulse wave. As in fig. 4B, a pulse wave of a plurality of cycles may be applied during the correction time. For example, 2,3, 4, 5, 6, 7, 8, 9 or 10 cycles of pulse waves may be applied.

In some examples, the signal waveform of the first input signal may include a combination of at least two pulse waves. Preferably, the pulse amplitudes of at least two pulse waves may be different to form a stepped signal waveform. In this case, the stepped signal waveforms have different pulse amplitudes, and applying the signal waveforms of different pulse amplitudes to the electrode 100 enables the corresponding response signal to reflect more information of the electrode 100, such as the specificity, response time, or linear range, and further enables the correction factor used in the correction to include more information of the electrode 100, thereby enabling further improvement in the accuracy of determining the analyte level. To this end, the present disclosure also provides examples of some stepped signal waveforms. It should be noted that the present disclosure is not limited to the signal waveforms shown in fig. 4C, 4D and 4E, and other stepped signal waveforms having a signal gradient are also within the scope of the present disclosure, such as a decreasing stepped signal waveform.

Referring to embodiment 3 shown in fig. 4C, the signal waveform of the first input signal may include a combination of at least two pulse waves, and form a signal waveform having a plurality of pulse waves with different pulse amplitudes in time series, the plurality of pulse waves with different pulse amplitudes forming a stepped signal waveform. In this case, the pulse waves having different pulse amplitudes can cause the electrode 100 to transfer charges to different extents, and thus the dynamic characteristics of the electrode 100 that electrochemically reacts under the pulse waves having different pulse amplitudes can be obtained. Thus, the obtained correction coefficient can be made to contain information on the dynamic characteristics of the electrode 100 at pulse waves having different pulse amplitudes, and correction based on the correction coefficient containing information on the dynamic characteristics of the electrode 100 can optimize the ability of the analyte sensor 10 to determine the analyte level, so that the accuracy of determining the analyte level can be further improved.

Referring to the 4 th embodiment shown in fig. 4D, the signal waveform of the first input signal may include a combination of at least two pulse waves, and form a signal waveform having a combination of a plurality of pulse waves having the same pulse amplitude and a step wave in time series, the combination of the pulse waves and the step wave forming a step-shaped signal waveform. In this case, the signal waveform of the first input signal includes a step wave having a relatively long duration, and information about the steady state response of the electrode 100 can be obtained, and the signal waveform of the first input signal includes a pulse wave having a relatively short duration, and information about the transient response of the electrode 100 can be obtained. Thus, the obtained correction coefficients can be made to contain information about the steady state response and the transient response of the electrode 100, and correction based on the correction coefficients containing information about the steady state response and the transient response of the electrode 100 can optimize the steady state response capability and the transient response capability of the analyte sensor 10, so that the accuracy of determining the analyte level can be further improved.

Referring to the 5 th embodiment shown in fig. 4E, the signal waveform of the first input signal may include a combination of at least two pulse waves, and form signal waveforms of a plurality of pulse waves with different pulse amplitudes in time sequence, and at the same time, directions of adjacent two pulse waves are different, that is, positive and negative directions are alternated, and the plurality of pulse waves with different pulse amplitudes form a stepped signal waveform. In this case, the difference in the direction of the pulse wave can obtain information on the inverse reaction of the electrode 100. Thus, the obtained correction coefficient can be made to contain information on the electrode 100 and the reverse reaction, and correction based on the correction coefficient containing information on the electrode 100 and the reverse reaction can reduce the influence of the reverse reaction on the determination of the analyte level by the analyte sensor 10, so that the accuracy of determining the analyte level can be further improved.

In some examples, a response signal corresponding to the first input signal may be collected. As shown in fig. 5, the response signal and the corresponding acquisition time may be obtained when the response signal is acquired. In this case, a response parameter related to the sensitivity decay can be obtained during use of the analyte sensor 10, thereby facilitating correction for the sensitivity decay during use. In some examples, the acquired response signal may be discrete data. Thus, the response signal is facilitated to be digitally processed by an algorithm.

In some examples, a fit may be made based on the response signal to obtain a response signal curve. The response signal may be discrete data obtained by the first sampling module 30 or the second sampling module 40 shown in fig. 5. In this case, it is possible to facilitate the extraction of information related to sensitivity decay from the response signal by fitting discrete data obtained by the first sampling module 30 or the second sampling module 40 to a continuous response signal curve, in addition, smoothing the response signal by fitting to reduce data fluctuations due to acquisition errors or other factors, in addition, interpolation of the response signal by fitting to obtain a continuous response signal curve, and thus, to improve the accuracy of the obtained response parameters.

In some examples, the response signal curve obtained by fitting may include a rising segment and/or a falling segment. For example, the acquired response signal shown in fig. 5 may be fitted to obtain a response signal curve including a falling segment.

In some examples, the response signal curve may not exclude the case of a straight line. That is, the response signal curve may include a curve form and a straight line form. The discrete response signals may be fitted directly to a curve form.

As described above, in step S100, the first input signal may be applied to at least two electrodes 100 of the analyte sensor 10 at least once during the correction time, and a response signal corresponding to the first input signal may be acquired. The number of times the first input signal is applied to the at least two electrodes 100 of the analyte sensor 10 during the correction time may be 1, 2, 3,4, 5, 6, 7, 8, 9, or 10.

Referring to fig. 6, in some examples, applying the first input signal and acquiring the corresponding response signal may include applying the first input signal based on a preset number of acquisitions and acquiring the response signal corresponding to the first input signal (step S101), obtaining an average response signal based on the response signals obtained from the plurality of acquisitions averaged (step S102) in response to the number of acquisitions being equal to the preset number of acquisitions, and obtaining a response signal curve based on the average response signal (step S103).

With continued reference to fig. 6, in some examples, in step S101, the first input signal may be applied based on a preset number of acquisitions. The first input signal may be applied multiple times within the correction time, and the number of times the first input signal is applied may be a preset number of acquisitions. In addition, the first input signal may return to a low level or other level that may return the response signal to a steady state when the first input signal is not applied across the gap of multiple applications. The time required for the gap to be applied multiple times may be sufficient to restore the response signal to a steady state when the first input signal is not applied. In this case, the interference between the plurality of response signals generated by applying the input signal a plurality of times can be reduced, and the accuracy of obtaining the response parameters can be improved. The number of times the first input signal is applied may be related to a preset number of acquisitions.

With continued reference to fig. 6, in some examples, in step S102, an average response signal may be obtained based on averaging response signals obtained from multiple acquisitions in response to the number of acquisitions being equal to a preset number of acquisitions. Specifically, a first input signal is applied, response signals of corresponding times are acquired, and the response signals are averaged to obtain an average response signal. The number of times the first input signal is applied is equal to the number of times the response signal is acquired, i.e. equal to the preset number of acquisitions. In this case, the response signal is acquired a plurality of times and averaged to obtain an average response signal, and the accuracy of the acquired response signal can be improved.

With continued reference to fig. 6, in some examples, in step S103, a response signal curve may be obtained based on the average response signal. In this case, by averaging the response signals to obtain the response signal curves, the accuracy of at least one response parameter of the response signals obtained based on the response signal curves can be improved, and thus the accuracy of correction based on the response parameters can be improved.

Referring back to fig. 3, in some examples, in step S200, a correction coefficient may be obtained based on at least one response parameter of the response signal and at least one reference parameter of the reference signal curve. In addition, the reference signal curve may represent a response signal curve of a response signal corresponding to the input signal when the analyte sensor 10 is not subject to sensitivity decay. In this case, by taking the reference signal curve corresponding to the occurrence of no sensitivity decay as a standard, a correction coefficient can be obtained that brings the response parameter close to the reference parameter. In addition, the reference signal curve corresponding to the case where no sensitivity decay occurs in the analyte sensor 10 is used as a standard, and the influence of the uncertainty factor on the accuracy of the standard can be reduced as compared with the signal curve using the analyte sensor 10 in other states. In addition, unlike calibration of analyte sensor 10 with fingertip blood as a standard, the convenience of determining analyte levels can be improved with reference to a reference signal curve corresponding when no sensitivity decay occurs.

With continued reference to fig. 3, in some examples, at least one response parameter of the response signal may be obtained based on a response signal curve determined from the response signal in step S200. The parameter types of the response parameters may include one or more of a peak, an area under the curve, and a slope of the curve. In this case, when the parameter type is a peak value, the maximum response value of the response signal to the input signal can be reflected, and thus the maximum response capability of the analyte sensor 10 to the input signal can be obtained, and the degree of attenuation of the sensitivity can be obtained, and when the parameter type is an integral under a curve, the cumulative response of the response signal to the input signal can be reflected, and thus the charge accumulating capability of the analyte sensor 10 can be obtained, and further, when the parameter type is a slope of a curve, the degree of attenuation of the sensitivity can be obtained, and further, the degree of decrease or increase of the response signal can be reflected, and thus the response speed of the analyte sensor 10 can be obtained, and the degree of attenuation of the sensitivity can be obtained.

In some examples, the response signal curve may be in the form of a curve. The peak in the parameter class may be the peak of the response signal curve. The area under the curve in the parameter class may be the integral of the response signal curve over time. The slope of the curve in the parameter class may be the slope of the curve at the target segment. In addition, the target segment may be a falling segment or a rising segment. The falling segment may correspond to the response signal acquired in fig. 5. In some examples, the slope of the curve in the parameter class may be the median of the slope of the target segment, the slope in the target segment corresponding to the characteristic point on the target segment, or the slope at half the peak of the response signal curve (i.e., at half the peak).

In some examples, the response signal curve may be in the form of a straight line. The slope of the curve in the parameter class may be the slope of a straight line. A response signal curve in a straight line form (described later) can be obtained by performing coordinate transformation on the response signal curve in a curve form. In this case, the slope can be directly obtained by a straight line without considering a problem of how to select the slope when the response signal curve is a curve, so that the correction method can be simplified.

In some examples, the reference signal profile may be obtained based on a response signal corresponding to the applied input signal. Specifically, an input signal may be applied to analyte sensor 10 where no sensitivity decay occurs, a response signal acquired, and at least one reference parameter of the response signal acquired. That is, the reference signal profile is a corresponding response signal obtained by applying an input signal to the analyte sensor 10 where no sensitivity decay occurs. In this case, by actually applying the input signal acquisition response signal to obtain the reference signal curve, the reference signal curve obtained before correction can be made to approach a true value where no sensitivity decay occurs.

In some examples, the applied input signal may be a second input signal. In some examples, a reference signal profile may be obtained based on the second input signal and saved prior to correction. In particular, the second input signal may be configured to be applied to analyte sensor 10 without correction outside of the correction time. The signal waveforms of the second input signal and the first input signal may be the same. The correction time to which the present disclosure relates may be, for example, a work time during the use of the target object or a factory production time or an assembly time before the use of the target object.

In some examples, the second input signal may be generated by signal source 300 when analyte monitoring system 1 is in use. In some examples, the second input signal may be generated by an external signal source prior to use of the analyte monitoring system 1. In some examples, the external signal source may be a function signal generator. In some examples, a reference signal corresponding to the second input signal may be acquired. Fitting may be performed based on the reference signal to obtain a reference signal curve.

In some examples, a reference signal profile obtained based on the second input signal may be saved to the memory module 50. In this case, by applying the second input signal to obtain and save the reference signal curve, the analyte monitoring system 1 can be caused to determine the correction coefficient based on the saved reference signal curve during the correction time.

In some examples, the applied input signal may be a third input signal. In some examples, the reference signal profile may be obtained based on the third input signal prior to correction. The third input signal may be configured to be applied to the sample sensor without correction outside of the correction time and to the sample sensor with correction in a different time period. The sample sensor may be a sensor used in obtaining a target relationship. The sample sensor may simulate the case where the analyte sensor 10 experiences varying degrees of sensitivity decay and the case where no sensitivity decay occurs. The third input signal may be the same signal waveform as the first input signal. The third input signal may be generated by an external signal source. In some examples, a reference signal profile obtained based on the third input signal may be saved to the memory module 50. In this case, the correction coefficient can be determined based on the stored reference signal curve of the sample sensor during the correction time without applying the input signal to the analyte sensor 10 before the correction time, so that the acquisition cost of the reference signal curve can be reduced and the service life of the analyte sensor 10 can be maintained. Thereby, the accuracy of the analyte sensor 10 in determining the analyte level can be further improved.

In some examples, a reference signal corresponding to the third input signal may be acquired. Fitting may be performed based on the reference signal to obtain a reference signal curve.

In some examples, the third input signal may also be used to obtain an attenuation signal curve, which may be used to determine a target relationship (described later). In particular, a plurality of decay signal curves may be obtained based on the third input signal at different time periods. The different time periods may be respective time periods for which the sample sensor experiences different degrees of sensitivity decay.

In some examples, a response signal corresponding to the third input signal may be collected. Fitting may be performed based on the response signals to obtain an attenuation signal curve.

With continued reference to fig. 3, in some examples, in step S200, a reference signal curve may be obtained based on a preset formula associated with the input signal. In this case, the reference signal curve is obtained by a preset formula, it is possible to facilitate rapid acquisition of the reference signal curve before correction, and it is possible to obtain an ideal reference signal curve in which no sensitivity attenuation occurs, that is, it is possible to obtain a theoretical value close to the occurrence of no sensitivity attenuation. In some examples, when the input signal is a step wave or a pulse wave, the preset formula is expressed as:

wherein I is a reference signal curve, A is a proportionality coefficient, and t is time. Thus, the reference parameter can be obtained based on the proportionality coefficient in the preset formula, and the calibration coefficient can be obtained based on the reference parameter.

With continued reference to fig. 3, in some examples, at least one reference parameter of a reference signal curve may be acquired in step S200. When the input signal is a step wave or a pulse wave, the preset formula isIn order to make at least one response parameter of the response signal and at least one reference parameter of the reference signal curve consistent for comparison, the reference signal curve having a preset formula may be subjected to coordinate transformation, the reference signal curve is transformed from a curve form to a straight form, and a slope of the curve in the at least one reference parameter may be a.

In some examples, the parameter type of the reference parameter and the parameter type of the response parameter may be identical. For example, if the parameter type of the response parameter includes a peak value, the parameter type of the reference parameter may also include a peak value. In this case, it can be convenient to directly compare the response parameter and the reference parameter, and thus a difference between the response signal and the reference signal can be obtained.

With continued reference to fig. 3, in some examples, in step S200, correction coefficients may be obtained at the time of correction based on at least one response parameter of the response signal and the stored reference signal profile. Specifically, a difference between the response signal and the reference signal curve may be obtained by analyzing at least one response parameter of the response signal and at least one reference parameter of the stored reference signal curve, and a correction coefficient is obtained based on the difference. In addition, the stored reference signal profile may be a reference signal profile obtained based on the second input signal, the third input signal, or a preset formula as described above.

In some examples, the correction coefficient may be obtained based on a difference between the response signal and the reference signal curve. In some examples, the difference between the response signal and the reference signal curve may be a difference between the response parameter and the reference parameter. Such as the difference or ratio between the response parameter and the reference parameter, etc. In some examples, the correction coefficient may be obtained based on a difference or ratio of the response parameter to the reference parameter, or the like. For example, a ratio between the response parameter and the reference parameter may be used as the correction coefficient.

In other examples, different correction factors may be used to correct the target parameters of analyte sensor 10 and the correction results compared to obtain the correction factors. The target parameters of the analyte sensor 10 are corrected using different correction factors. For example, the different correction coefficients may be 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, and 1.3. The different correction coefficients are multiplied by the target parameter to correct the target parameter. After the target parameters of the analyte sensor 10 are corrected, the corresponding analyte levels are corrected. And comparing the corrected analyte level with the proximity of the analyte level corresponding to the stored reference signal curve, using the analyte level corresponding to the stored reference signal curve as a standard. The closest corrected analyte level corresponding correction factor is obtained.

In some examples, the response signal may also be aligned in time with the stored reference signal profile before the analysis obtains the difference. For example with the pulse wave start time point. In this case, the accuracy of analyzing the difference of the response signal from the stored reference signal curve can be improved.

With continued reference to fig. 3, in some examples, in step S200, a correction coefficient may be obtained at the time of correction based on at least one response parameter of the response signal and the target relationship. In addition, the target relationship may represent a relationship of the response parameter and the correction coefficient. Specifically, the correction coefficient corresponding to the response parameter may be determined based on the target relationship to obtain the correction coefficient. The response parameter may be at least one response parameter of a response signal corresponding to the first input signal.

In some examples, the target relationship may be a functional relationship. Further, the target relationship may be a linear relationship. When the target relationship is a linear relationship, the target relationship may be represented by an adjustment coefficient. The adjustment coefficient may be a linear coefficient satisfying a linear relationship between the response parameter and the correction coefficient. In this case, by directly using one adjustment coefficient to represent the linear relationship between the response parameter and the correction coefficient, the amount of use in the storage module 50 when storing the target relationship can be reduced.

Specifically, the response parameter may be multiplied by the adjustment coefficient to obtain the correction coefficient. For example, when the response parameter is a curve slope, the curve slope may be multiplied by an adjustment coefficient to obtain a correction coefficient.

In some examples, the target relationship may be represented by a lookup table. The response parameters and correction coefficients may be stored in a look-up table. The lookup table may represent a correspondence between the response parameters and the correction coefficients. In this case, it can be convenient to retrieve the response parameters to quickly obtain the corresponding correction coefficients.

As described above, the reference signal profile and the plurality of attenuation signal profiles may be obtained based on the third input signal. In some examples, the target relationship may be determined based on at least one reference parameter of a reference signal curve determined from the third input signal and at least one response parameter of the plurality of decay signal curves.

In some examples, the decay signal curve may be in the form of a straight line. The slope of the curve in the parameter class may be the slope of a straight line. In this case, the slope can be directly obtained by a straight line without considering the problem of how to select the slope when the attenuation signal curve is a curve, so that the parameters related to the severity of the sensitivity attenuation in each time period corresponding to the occurrence of sensitivity attenuation of different degrees of the sample sensor can be obtained.

In some examples, different correction coefficients may be obtained using different adjustment parameters multiplied by response parameters to obtain the target relationship. The target parameters of the sample sensor are corrected using different correction coefficients. After the target parameters of the sample sensor are corrected, the corresponding analyte levels are corrected. And comparing the corrected analyte level with the analyte level corresponding to the reference signal curve by taking the analyte level corresponding to the reference signal curve as a standard. The closest adjusted parameter corresponding to the corrected analyte level is taken as the target relationship.

In some examples, the sample sensor may also be corrected using different correction coefficients to obtain the target relationship. The target parameters of the sample sensor are corrected using different correction coefficients. After the target parameters of the sample sensor are corrected, the corresponding analyte levels are corrected. For example, when the target parameter is a sensitivity coefficient, after the sensitivity coefficient is corrected, the corresponding analyte level calculated based on the target parameter is corrected. And comparing the corrected analyte level with the analyte level corresponding to the reference signal curve by taking the analyte level corresponding to the reference signal curve as a standard. The closest corrected analyte level corresponding correction factor and the initial response parameter are stored in a look-up table. The look-up table is taken as the target relation.

In other examples, the target relationship may be obtained through machine learning. In some examples, machine learning may be learning at least one response parameter of the response signal and at least one reference parameter of the reference signal curve to obtain a target relationship of the response parameter to the correction coefficient.

In some examples, the target relationship may be obtained by at least one of an in vitro experiment and a body worn experiment. The in vitro experiments may be measurements of data relating to the analyte sensor 10 in a glucose solution that mimics interstitial fluid. The body wear test may be data related to measuring the analyte sensor 10 when implanted in interstitial fluid of a human body.

In some examples, the target relationship may be saved. In some examples, the target relationship may be saved to the storage module 50.

With continued reference to fig. 3, in some examples, in step S200, a correction may be made in response to analyte sensor 10 being in a sensitivity-decaying state. In particular, it may be determined that the analyte sensor 10 is in a sensitivity decay state based on a difference between at least one response parameter of the response signal and at least one reference parameter of the reference signal curve. Further, a correction may be made in response to analyte sensor 10 being in a sensitivity decay state. In this case, the detection of the analyte sensor 10 in a sensitivity-decaying state can be corrected, enabling the analyte monitoring system 1 to maintain the accuracy of determining the analyte level during use of the target object.

With continued reference to fig. 3, in some examples, in step S200, a difference between the at least one response parameter and the at least one reference parameter may be determined. Further, it may be determined that analyte sensor 10 is in a sensitivity decay state in response to the difference being greater than a first threshold. The first threshold may indicate that the analyte sensor 10 is in a sensitivity decay state.

As described above, the form of the response signal curve, the reference signal curve, or the decay signal curve may be a straight line form. To this end, the present disclosure also provides an example of determining a response parameter or reference parameter in the form of a straight line.

In some examples, the response signal curve, the reference signal curve, or the decay signal curve may be coordinate transformed. The coordinate transformation may be transforming the time of the curve so that the curve is transformed from a curve form to a linear form. For example, when the input signal is a step wave or a pulse wave, the curve satisfies a relationship in which the signal is directly proportional to the inverse of the arithmetic square root of time, and 1/sqrt (t) may be converted from t to the inverse of the arithmetic square root of t for the time of the curve. When the curve satisfies a log proportional relationship of signal to time, ln (t) can be transformed from t to time of the curve. In this case, the curve can be converted from a curve form to a straight form by coordinate conversion, and the straight line can be directly processed, for example, the slope can be obtained, and the problem of how to select the slope of the feature point when the curve is in the curve form does not need to be considered, so that the correction method can be simplified. It should be noted that the present disclosure is not limited to the above examples, and other coordinate transformations that can transform the curve from a curve form to a linear form are also within the scope of the present disclosure, such as a combination of the two coordinate transformations.

In some examples, at least one response parameter of the response signal or at least one reference parameter of the reference signal may be obtained based on the coordinate transformed response signal curve, the reference signal curve, or the decay signal curve. The curve slope may be used as a response parameter or reference parameter for a response signal curve, a reference signal curve or an attenuation signal curve. For example, when the third input signal is a step wave or a pulse wave, the time of the decay signal curve may be converted from t to 1/sqrt (t), and the coordinate-converted decay signal curve may be converted from a straight line form to a curve form. The slope of the attenuation signal curve after coordinate transformation may be used as the curve slope of the attenuation signal curve. The curve slope of the decay signal curve may be taken as a response parameter of the decay signal curve.

As described above, in step S200, the correction coefficient may be obtained based on at least one response parameter of the response signal and at least one reference parameter of the reference signal curve.

Referring to fig. 7A, in some examples, obtaining the 1 st embodiment of the correction coefficient may include performing a coordinate transformation on the response signal curve (step S201), obtaining at least one response parameter of the response signal based on the coordinate transformed response signal curve (step S202), and obtaining the correction coefficient based on the at least one response parameter of the response signal and the target relationship (step S203).

With continued reference to fig. 7A, in some examples, in step S201, the response signal curve may be subjected to a coordinate transformation. The response signal curve can be transformed from a curve form to a straight form by means of a coordinate transformation. In this case, for the case where the input signal has some specific signal waveform, for example, when the input signal includes a step wave or a pulse wave, the response signal curve can be converted into a straight line by such coordinate conversion, and further the straight line can be directly processed, for example, a slope can be found, without considering a problem of how to select the slope of the feature point when the response signal curve is a curve, so that the correction method can be simplified.

With continued reference to fig. 7A, in some examples, at least one response parameter of the response signal may be obtained based on the coordinate transformed response signal curve in step S202. For example, when the input signal has the characteristics of a signal waveform of a pulse wave or a step wave, a curve slope corresponding to a response signal curve subjected to coordinate transformation may be taken as at least one response parameter of the response signal.

With continued reference to fig. 7A, in some examples, in step S203, a correction coefficient may be obtained based on at least one response parameter of the response signal and the target relationship. For example, when the target relationship is a lookup table, the correction coefficient corresponding to the response parameter may be retrieved in the lookup table.

With continued reference to fig. 7A, in some examples, in step S203, a target relationship may be determined and saved prior to correction based on the reference signal curve and the decay signal curve corresponding to the third input signal. That is, the reference signal profile may be obtained based on the third input signal prior to correction. A plurality of decay signal curves are obtained based on the third input signal over different time periods. A target relationship is determined based on at least one reference parameter of the reference signal curve and at least one response parameter of the plurality of decay signal curves and the target relationship is saved. A correction coefficient is determined based on at least one response parameter of the response signal and the target relationship at the time of correction. The target relationship represents a relationship of the response parameter and the correction coefficient. In this case, the amount of use in the storage module 50 can be reduced as compared with storing the reference signal curve by obtaining the target relation based on the reference signal curve and the attenuation signal curve, and correcting the target relation based on the stored target relation, and in addition, the correction coefficient is obtained based on the target relation at the time of correction, obtained by simple calculation (for example, the response parameter is multiplied by the adjustment coefficient) or obtained by searching the lookup table, the processing step at the time of correction can be obtained, and further the correction speed can be improved, and the instantaneity of the correction method can be improved.

Referring to fig. 7B, in some examples, the 2 nd embodiment of obtaining the correction coefficient may include obtaining at least one response parameter of the response signal based on the response signal profile (step S211), and obtaining the correction coefficient based on the at least one response parameter of the response signal and the stored reference signal profile (step S212).

With continued reference to fig. 7B, in some examples, in step S211, the parameter variety of the response parameter may include a combination of one or more of a peak value, an area under the curve, and a slope of the curve. When the response signal curve is in the form of a curve, the slope of the curve from which the response signal is obtained may be the median of the slope of the curve at the falling or rising segment, the slope corresponding to half of the peak, or the slope corresponding to other characteristic points on the curve (e.g., the point on the curve where the slope is greatest).

With continued reference to fig. 7B, in some examples, in step S212, the response signal may be aligned in time with the stored reference signal profile. For example, aligned with the pulse wave start time point, the difference between the response signal and the reference signal curve is obtained by analyzing at least one response parameter of the response signal and at least one reference parameter of the stored reference signal curve, and a correction coefficient is obtained based on the difference. The differences may be analyzed, for example, using a machine learning approach.

With continued reference to fig. 7B, in some examples, in step S212, a reference signal profile may be obtained and saved based on the second input signal prior to correction. That is, the reference signal profile may be obtained based on the second input signal and saved prior to correction. A correction coefficient is obtained based on at least one response parameter of the response signal and at least one reference parameter of the reference signal curve at the time of correction. In this case, by performing the correction based on the stored reference signal profile, the standard used for the correction can be kept intact, the loss of information can be reduced compared to converting the reference signal profile into other information, and the accuracy of determining the analyte level can be improved. In addition, the reference signal curve is saved before correction, and the preparation step before correction can be simplified without performing additional processing. In addition, when the reference signal curve is complex, the mathematical relationship between the reference signal curve and the response signal curve is difficult to find, and the applicability of the correction method can be improved by directly using the reference signal curve for correction.

With continued reference to fig. 3, in some examples, in step S300, a target parameter of analyte sensor 10 related to sensitivity decay may be corrected based on the correction factor. The target parameter may be related to a conversion relationship between the analyte signal and the analyte level. In some examples, when the correction coefficient is related to the ratio of the response parameter and the reference parameter, the correction coefficient may be multiplied or divided by the target parameter to make the correction. In some examples, when the correction coefficient is related to the difference between the response parameter and the reference parameter, the correction coefficient may be a relative error, and the target parameter may be increased or decreased by a change amount corresponding to the relative error to perform correction. The amount of change corresponding to the relative error may be equal to the relative error multiplied by the target parameter. In addition, the relative error may be in the form of a percentage of the difference.

In addition, the conversion relationship may be determined by the analyte sensor 10 itself. In some examples, the conversion relationship may be related to the analyte signal and sensitivity (e.g., the analyte level may be divided by the analyte signal by the sensitivity of the analyte sensor 10), and the corrected target parameter may be used to correct for the analyte signal or sensitivity. In particular, the target parameter may be a sensitivity coefficient or a current compensation coefficient.

With continued reference to fig. 3, in some examples, in step S400, the sensitivity of analyte sensor 10 may be corrected based on the sensitivity coefficient or the current value of analyte sensor 10 may be corrected based on the current compensation coefficient. In some examples, the analyte level may be determined based on the analyte signal acquired by the analyte sensor 10 and the corrected target parameter.

With continued reference to fig. 3, in some examples, in step S400, an analyte level may be determined based on the analyte signal acquired by the analyte sensor 10 and the corrected target parameter. In this case, by correcting the target parameter based on the obtained correction coefficient and determining the analyte level based on the corrected target parameter, the analyte sensor 10 having sensitivity attenuation can be made to acquire the analyte level having no sensitivity attenuation. Thereby, the accuracy of determining the analyte level of the analyte sensor 10, in which the sensitivity decay occurs, can be improved.

With continued reference to fig. 3, in some examples, in step S400, in some examples, when the target parameter is a sensitivity coefficient, the sensitivity of analyte sensor 10 may be corrected based on the sensitivity coefficient. In some examples, the analyte level is determined based on the analyte signal acquired by the analyte sensor 10 and the corrected sensitivity. In this case, the sensitivity can be indirectly corrected by correcting the sensitivity coefficient.

In some examples, when the target parameter is a current compensation coefficient, the current value of analyte sensor 10 may be corrected based on the current compensation coefficient. In some examples, the analyte level is determined based on the analyte signal acquired by the analyte sensor 10 and the corrected current value. In this case, the current value can be indirectly corrected by correcting the current compensation coefficient.

One or more steps of the correction method according to the present disclosure may be performed within a correction time, such as the application of the first input signal according to step S100. Part of the parameters required for one or more steps of the correction method according to the present disclosure may be obtained outside the correction time, such as working time during the use of the target object or factory production time or assembly time before the use of the target object, etc., and at least one reference parameter, look-up table or adjustment coefficient of the reference signal curve according to step S200 may be obtained outside the correction time.

At least one reference parameter of the reference signal profile to which the present disclosure relates may be obtained by the analyte sensor 10 without sensitivity decay. Alternatively, the analyte sensor 10 may be calibrated when the target object state is stationary, such as when the target object is on an empty stomach or when the target object is physically stationary during the night.

The analyte sensor 10 to which the present disclosure relates that is not subject to sensitivity decay may be an analyte sensor 10 that is not in a state of sensitivity decay, such as an analyte sensor 10 within a factory production time or an assembly time before a target object uses the analyte monitoring system 1, an analyte sensor 10 having a difference between a response parameter and a reference parameter less than a first threshold, an analyte sensor 10 before or after a period of use of the target object, and a corrected analyte sensor 10.

The correction frequency of the correction method to which the present disclosure relates may be 1 time/day, 2 times/day, 1 time/2 days, 1 time/week, or correction in response to the analyte sensor 10 being in a sensitivity decay state.

The dynamics referred to in this disclosure include information related to sensitivity.

The present disclosure also relates to a computer readable storage medium having stored thereon at least one instruction which when executed by a processor performs one or more steps of the correction method described above, or implements the analyte monitoring system 1 described above.

The present disclosure also relates to an electronic device, which may comprise a processor and a memory, the processor executing a program stored in the memory to implement one or more steps of the correction method described above, or to implement the analyte monitoring system 1 described above.

While the disclosure has been described in detail in connection with the drawings and embodiments, it should be understood that the foregoing description is not intended to limit the disclosure in any way. Modifications and variations of the present disclosure may be made as desired by those skilled in the art without departing from the true spirit and scope of the disclosure, and such modifications and variations fall within the scope of the disclosure.

Claims

1. A method for correcting for sensitivity decay of an analyte sensor, comprising:

Applying a first input signal to at least two electrodes of the analyte sensor at least once during a correction time and collecting a response signal corresponding to the first input signal;

Obtaining a correction factor based on at least one response parameter of the response signal and at least one reference parameter of a reference signal curve;

Correcting a target parameter of the analyte sensor related to the sensitivity decay based on the correction factor;

determining the analyte level based on the signal related to the analyte level acquired by the analyte sensor and the corrected target parameter.

2. A method for correcting sensitivity decay as defined in claim 1, wherein,

The signal waveform of the first input signal comprises a combination of at least two pulse waves, the pulse amplitudes of the at least two pulse waves being different to form the signal waveform in steps.

3. A method for correcting sensitivity decay as defined in claim 1, wherein,

Fitting is performed on the response signals to obtain response signal curves, coordinate transformation is performed on the response signal curves, and at least one response parameter of the response signals is obtained on the basis of the response signal curves subjected to the coordinate transformation.

4. A method for correcting sensitivity decay as defined in claim 1, wherein,

Obtaining said reference signal profile and storing said reference signal profile based on a second input signal prior to correction, obtaining said correction factor based on at least one response parameter of said response signal and at least one reference parameter of said reference signal profile at correction time, said second input signal being identical to a signal waveform of said first input signal, and/or

The reference signal curve is obtained based on a third input signal before correction, a plurality of attenuation signal curves are obtained based on the third input signal in different time periods, a target relation is determined based on at least one reference parameter of the reference signal curve and at least one response parameter of the plurality of attenuation signal curves, and the target relation is stored, the correction coefficient is determined based on at least one response parameter of the response signal and the target relation in correction, the target relation represents the relation between the response parameter and the correction coefficient, and the third input signal has the same signal waveform as the first input signal.

5. A method for correcting sensitivity decay as defined in claim 1, wherein,

Obtaining the reference signal curve based on a preset formula related to the input signal, and/or

The reference signal profile is obtained based on a response signal corresponding to the applied input signal.

6. The method for correcting sensitivity decay as claimed in claim 5, wherein,

When the input signal is a step wave, the preset formula is expressed as:

wherein I is the reference signal curve, A is the proportionality coefficient, and t is the time.

7. A method for correcting sensitivity decay as defined in claim 1, wherein,

The parameter type of the response parameter is consistent with the parameter type of the reference parameter, the parameter type including one or more of a peak value, an area under a curve, and a slope of the curve.

8. A method for correcting sensitivity decay as defined in claim 1, wherein,

The target parameter is a sensitivity coefficient, the sensitivity of the analyte sensor is corrected based on the sensitivity coefficient, the analyte level is determined based on the corrected sensitivity, and/or

The target parameter is a current compensation coefficient, a current value of the analyte sensor is corrected based on the current compensation coefficient, and the analyte level is determined based on the corrected current value.

9. An analyte monitoring system comprising an analyte sensor and a processing module;

The analyte sensor is configured to acquire a signal related to the analyte level and apply an input signal to at least two electrodes of the analyte sensor for a correction time and acquire a response signal corresponding to the input signal;

The processing module is configured to receive the signal and the response signal and determine the analyte level using the correction method of any one of claims 1 to 8.

10. The analyte monitoring system of claim 9, wherein the analyte monitoring system comprises,

The analyte sensor further includes a mode switching module including a switching circuit to cause the analyte sensor to have an operational mode and a calibration mode.

11. A computer-readable storage medium comprising,

The computer readable storage medium stores at least one instruction that when executed by a processor implements the correction method of any one of claims 1 to 8, or implements the analyte monitoring system of any one of claims 9 to 10.