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

Abstract

The present disclosure describes a correction method for sensitivity attenuation of an analyte sensor, a system and a medium. The correction method comprises applying a first input signal to at least two electrodes of an analyte sensor at least once within a correction duration, and collecting a response signal corresponding to the first input signal; obtaining a correction coefficient on the basis of at least one response parameter of the response signal and at least one reference parameter of a reference signal curve; on the basis of the correction coefficient, correcting target parameters of the analyte sensor related to sensitivity attenuation; and determining an analyte level on the basis of an analyte level-related signal collected by the analyte sensor and the corrected target parameters. Therefore, the accuracy and convenience of determining the analyte level can be improved.

Description

Method, system and medium for correcting sensitivity decay of analyte sensors Technical Field

[0001] The present disclosure relates to the field of biomedical engineering industry, and in particular to a method, system, and medium for correcting sensitivity attenuation of an analyte sensor. Background Art

[0002] Diabetes is a metabolic disorder involving proteins, fats, water, and electrolytes caused by insufficient insulin secretion and decreased insulin sensitivity in target tissue cells. Currently, continuous glucose monitoring (CGM) technology can continuously monitor glucose in a user's interstitial fluid. For example, using electrochemical analysis-based CGM technology, a glucose sensor is typically placed subcutaneously to monitor changes in glucose concentration in the subcutaneous tissue fluid.

[0003] Glucose sensors used in continuous glucose monitoring typically experience a gradual decrease in the accuracy of determining analyte levels over time. This phenomenon is known as "sensor fade," "sensor drift," or "sensor fading." Sensitivity fade can be caused by a variety of factors, including sensor aging, immune responses, or environmental factors. Currently, a common correction method for sensitivity fade is to collect blood glucose levels from the user's fingertips and use this value as the calibration value for continuous glucose monitoring.

[0004] However, multiple fingertip blood collections will reduce user comfort and convenience. How to reduce the impact of sensitivity attenuation on glucose detection without relying on additional blood collection remains to be studied. Summary of the Invention

[0005] The present disclosure is made in view of the above-mentioned state of the prior art, and its object is to provide a method, system and medium for correcting sensitivity attenuation of an analyte sensor, which can improve the accuracy and convenience of determining the analyte level.

[0006] To this end, a first aspect of the present disclosure provides a method for correcting sensitivity attenuation of an analyte sensor, comprising applying a first input signal to at least two electrodes of the analyte sensor at least once within a correction time, and collecting a response signal corresponding to the first input signal; 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; correcting a target parameter of the analyte sensor related to the sensitivity attenuation based on the correction coefficient; and determining the analyte level based on a signal related to the analyte level collected by the analyte sensor and the corrected target parameter.

[0007] In the first aspect of the present disclosure, by applying a first input signal to at least two electrodes of an analyte sensor within a calibration time and collecting corresponding response signals, the electrochemical performance can be measured in real time during the use of the analyte sensor; a correction coefficient is obtained based on at least one response parameter of the response signal and at least one reference parameter of a reference signal curve, and by using the reference signal curve as a standard, a correction coefficient that makes the response parameter close to the reference parameter can be obtained; by correcting the target parameter based on the obtained correction coefficient, and then determining the analyte level based on the corrected target parameter, the analyte sensor that has undergone sensitivity attenuation can obtain the analyte level that has not undergone sensitivity attenuation. Thus, the accuracy of determining the analyte level can be improved. In addition, unlike calibrating the analyte sensor based on fingertip blood as a standard, using the reference signal curve corresponding to the time when sensitivity attenuation has not occurred as a standard can improve the convenience of determining the analyte level.

[0008] Additionally, in the calibration 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, wherein the at least two pulse waves have different pulse amplitudes to form a step-like signal waveform. In this case, the step-like signal waveform has different pulse amplitudes, and applying signal waveforms with different pulse amplitudes to the electrodes can cause the corresponding response signals to reflect more information about the electrodes, such as specificity, response time, or linear range. This can further enable the calibration coefficient used during calibration to include more information about the electrodes, thereby further improving the accuracy of determining the analyte level.

[0009] In addition, in the correction method involved in the first aspect of the present disclosure, optionally, fitting is performed based on the response signal to obtain a response signal curve, coordinate transformation is performed on the response signal curve, and at least one response parameter of the response signal is obtained based on the response signal curve after coordinate transformation. In this case, by fitting the obtained discrete data into a continuous response signal curve, it is possible to facilitate the extraction of information related to sensitivity attenuation from the response signal; in addition, the response signal can be smoothed by fitting, thereby reducing data fluctuations caused by acquisition errors or other factors; in addition, the response signal can be interpolated by fitting to obtain a continuous response signal curve, thereby improving the accuracy of the obtained response parameters. In addition, the response signal curve can be transformed from a curve form to a straight line form by coordinate transformation, and the straight line 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 a curve form, thereby simplifying the correction method.

[0010] In addition, in the calibration method according to the first aspect of the present disclosure, optionally, before calibration, the reference signal curve is obtained based on the second input signal and saved, and during calibration, the calibration 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, wherein the second input signal has the same signal waveform as the first input signal; and / or before calibration, the reference signal curve is obtained based on the third input signal, multiple attenuation signal curves are obtained based on the third input signal at 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 multiple attenuation signal curves and saved, and during calibration, the calibration coefficient is determined based on at least one response parameter of the response signal and the target relationship, wherein the target relationship represents the relationship between the response parameter and the calibration coefficient, and the third input signal has the same signal waveform as the first input signal. In this case, when the calibration is based on the second input signal, by performing calibration based on the saved reference signal curve, the integrity of the standard used for calibration can be maintained, and compared with converting the reference signal curve into other information, information loss can be reduced, thereby improving the accuracy of determining the analyte level. In addition, when based on the third input signal, the target relationship 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 relationship during correction. It is convenient to obtain the correction coefficient through simple calculation or by searching the lookup table, which can reduce the processing steps during correction and thus improve the correction speed, thereby improving the real-time performance of the correction method.

[0011] In addition, in the correction method involved in 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, obtaining the reference signal curve through the preset formula can facilitate rapid acquisition of the reference signal curve before correction, and can obtain an ideal reference signal curve without sensitivity attenuation, that is, can obtain a value close to the theoretical value without sensitivity attenuation; in addition, obtaining the reference signal curve by actually applying the input signal and obtaining the response signal can make the reference signal curve obtained before correction close to the actual value without sensitivity attenuation.

[0012] In addition, in the correction method involved in 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 proportional coefficient, and t is time. Thus, the reference parameter can be obtained based on the proportional coefficient in the preset formula, and the calibration coefficient can be obtained based on the reference parameter.

[0013] In addition, in the calibration method involved in the first aspect of the present disclosure, optionally, the parameter type of the response parameter is consistent with the parameter type of the reference parameter, and the parameter type includes a combination of one or more of the peak value, the area under the curve, and the slope of the curve. In this case, it is convenient to directly compare the response parameter and the reference parameter, and thus the difference between the response signal and the reference signal can be obtained. In this case, when the parameter type is the peak value, it can reflect the maximum response value of the response signal to the input signal, and thus the maximum response capability of the analyte sensor to the input signal can be obtained, thereby the degree of sensitivity attenuation can be obtained. In addition, when the parameter type is the integral under the curve, it can reflect the cumulative response amount of the response signal to the input signal, and thus the charge accumulation capability of the analyte sensor can be obtained, thereby the degree of sensitivity attenuation can be obtained. In addition, when the parameter type is the slope of the curve, it can reflect the speed of the response signal falling or rising, and thus the response speed of the analyte sensor can be obtained, thereby the degree of sensitivity attenuation can be obtained.

[0014] In addition, in the calibration 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 calibrated based on the sensitivity coefficient, and the analyte level is determined based on the calibrated sensitivity; and / or the target parameter is a current compensation coefficient, the current value of the analyte sensor is calibrated based on the current compensation coefficient, and the analyte level is determined based on the calibrated current value. In this case, the sensitivity or current value can be indirectly corrected by correcting the target parameter.

[0015] A second aspect of the present disclosure provides an analyte monitoring system comprising an analyte sensor and a processing module; the analyte sensor is configured to acquire a signal related to an analyte level, apply an input signal to at least two electrodes of the analyte sensor within a calibration 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 calibration method of the first aspect of the present disclosure. This improves the accuracy and convenience of the analyte monitoring system in determining analyte levels.

[0016] Additionally, in the analyte monitoring system according to the second aspect of the present disclosure, the analyte sensor may optionally further include a mode switching module, wherein the mode switching module includes a switching circuit to enable the analyte sensor to have an operating mode and a calibration mode. In this case, the analyte sensor can determine the analyte level during the operating time and perform calibration during the calibration time, thereby improving the operating efficiency of the analyte monitoring system.

[0017] The third aspect of the present disclosure provides a computer-readable storage medium, which stores at least one instruction. When the at least one instruction is executed by a processor, it implements the correction method involved in the first aspect of the present disclosure, or implements the analyte monitoring system involved in the second aspect of the present disclosure.

[0018] According to the present disclosure, a method, system, and medium for correcting sensitivity decay of an analyte sensor are provided that can improve the accuracy and convenience of determining analyte levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Embodiments of the present disclosure will now be explained in further detail, by way of example only, with reference to the accompanying drawings.

[0020] FIG1 is a diagram showing an application scenario of an analyte monitoring system according to an example of the present disclosure.

[0021] FIG2 is a system block diagram illustrating an analyte monitoring system according to examples of the present disclosure.

[0022] FIG3 is a flow chart illustrating a method for correcting sensitivity decay of an analyte sensor according to an example of the present disclosure.

[0023] FIG4A is a schematic diagram illustrating a first embodiment of a signal waveform of a first input signal according to an example of the present disclosure.

[0024] FIG4B is a schematic diagram illustrating a second embodiment of the signal waveform of the first input signal according to an example of the present disclosure.

[0025] FIG4C is a schematic diagram showing a third embodiment of the signal waveform of the first input signal involved in the example of the present disclosure.

[0026] FIG4D is a schematic diagram showing a fourth embodiment of the signal waveform of the first input signal involved in the examples of the present disclosure.

[0027] FIG4E is a schematic diagram showing a fifth embodiment of the signal waveform of the first input signal involved in the examples of the present disclosure.

[0028] FIG5 is a schematic diagram illustrating an acquisition response signal involved in an example of the present disclosure.

[0029] FIG6 is a flow chart illustrating applying a first input signal and collecting a corresponding response signal according to an example of the present disclosure.

[0030] FIG. 7A is a flowchart illustrating a first embodiment of obtaining a correction coefficient according to an example of the present disclosure.

[0031] FIG. 7B is a flowchart illustrating a second embodiment of obtaining a correction coefficient according to an example of the present disclosure. DETAILED DESCRIPTION

[0032] The preferred embodiments of the present disclosure are described in detail below with reference to the accompanying drawings. In the following description, identical components are assigned identical reference numerals, and duplicate descriptions are omitted. In addition, the accompanying drawings are merely schematic, and the proportions of the dimensions of the components and the shapes of the components may differ from the actual ones.

[0033] It should be noted that the terms "including" and "having" and any variations thereof in this disclosure, such as a process, method, system, product or device that includes or has a series of steps or units, are not necessarily limited to those steps or units clearly listed, but may include or have other steps or units that are not clearly listed or are inherent to these processes, methods, products or devices.

[0034] The present disclosure relates to a correction method for sensitivity attenuation of an analyte sensor (hereinafter referred to as the correction method, and may also be referred to as an analyte sensor correction method or calibration method, etc.). The correction method involved in the present disclosure can be applicable to the case where the analyte sensor is in a sensitivity attenuation state. The analyte level obtained when the analyte sensor is in the sensitivity attenuation state deviates from the analyte level obtained when the analyte sensor has not undergone sensitivity attenuation, that is, an analyte level that has been offset is obtained. For example, due to long-term use, the sensor's performance degrades due to chemical reactions, physical changes, or losses, which is sensitivity attenuation of the analyte sensor. The correction method provided by the present disclosure can improve the accuracy and convenience of determining the analyte level.

[0035] The sensitivity of the present disclosure may be a parameter related to the ability of a sensor to detect or respond to changes in analyte levels. The sensitivity coefficient of the present disclosure may be a parameter used to calibrate the sensitivity of an analyte sensor. The sensitivity of the present disclosure may be a parameter used to calibrate a signal of an analyte sensor related to an analyte level (hereinafter referred to as an analyte signal).

[0036] It should be noted that the improvement in the accuracy of determining the analyte level involved in the present disclosure may be to make the analyte level obtained after correction close to or equal to the analyte level obtained when sensitivity attenuation has not occurred. For example, in the case where the analyte is glucose in tissue fluid, the analyte level is the glucose concentration in the tissue fluid, and the analyte sensor may be a sensor that includes an enzyme that undergoes an oxidation-reduction reaction with glucose (e.g., glucose oxidase or glucose dehydrogenase). The improvement in the accuracy of determining the analyte level involved in the present disclosure may be to make the glucose concentration obtained after correction close to or equal to the glucose concentration obtained when the analyte sensor has not experienced sensitivity attenuation.

[0037] The present disclosure relates to improving the accuracy of determining the analyte level by making the obtained analyte level close to or equal to the reference analyte level. For example, when the analyte is glucose, the reference analyte level can be the glucose concentration in the fingertip blood.

[0038] 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 within a calibration time, collect a response signal corresponding to the input signal, receive the analyte signal and the response signal, and determine the analyte level using the calibration method described above. The analyte monitoring system can be used for 1 week, 2 weeks, 3 weeks, or 4 weeks. The calibration method disclosed herein enables the analyte monitoring system to maintain good accuracy in determining analyte levels during its use.

[0039] In some examples, the analyte can be one or more of glucose, acetylcholine, amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase, creatine, creatinine, DNA, fructosamine, glutamine, growth hormone, 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 can be glucose concentration.

[0040] The analyte sensor that needs to be calibrated in the examples of the present disclosure may be an analyte sensor that has experienced sensitivity degradation, while the analyte sensor that does not need to be calibrated may be an analyte sensor that has not experienced sensitivity degradation.

[0041] The following describes examples of the present disclosure by taking glucose in interstitial fluid as an example, with reference to the accompanying drawings. Such description does not limit the scope of the present disclosure.

[0042] FIG1 is a diagram showing an application scenario of an analyte monitoring system 1 according to an example of the present disclosure.

[0043] In some examples, the analyte monitoring system 1 may include an analyte sensor 10 and a processing module 20. As shown in FIG1 , the analyte sensor 10 may be implanted subcutaneously or mounted on the surface of the skin of a target subject, and the analyte sensor 10 may be configured to acquire an analyte signal. The processing module 20 may be configured to receive the analyte signal and determine the analyte level. The present disclosure is not limited to the location of the processing module 20 shown in FIG1 ; for example, the processing module 20 may also be located on the surface of the target subject's skin.

[0044] FIG2 is a system block diagram illustrating an analyte monitoring system 1 according to an example of the present disclosure.

[0045] In some examples, the analyte sensor 10 may include at least two electrodes 100. The at least two electrodes 100 may be implanted subcutaneously in a subject to react with an analyte in subcutaneous tissue fluid and generate a continuous signal related to the analyte level. The at least two electrodes 100 may include a working electrode and a counter electrode. In this case, the at least two electrodes 100 of the analyte sensor 10 may react with the analyte and form a circuit, thereby generating a continuous signal related to the analyte level.

[0046] The at least two electrodes 100 involved in the present disclosure may also include three electrodes 100. In some examples, the three electrodes 100 can be a working electrode, a reference electrode, and a counter electrode, respectively. The at least two electrodes 100 may also include four electrodes 100. In some examples, the four electrodes 100 can be a working electrode, a reference electrode, a blank electrode, and a counter electrode, respectively. In this case, by utilizing the functions of other electrodes 100, such as the reference electrode providing a reference stable potential, the generated analyte signal can be made more accurate.

[0047] In some examples, processing module 20 may determine the analyte level based on the analyte signal and the target parameter. Specifically, processing module 20 may amplify, filter, and perform analog-to-digital conversion on the signal, and calculate the analyte level corresponding to the signal based on the target parameter.

[0048] The target parameter involved in the present disclosure can be a parameter related to sensitivity attenuation. For example, the target parameter can be a sensitivity coefficient. The target parameter can also be other parameters used to determine the level of an analyte.

[0049] When the analyte sensor 10 is in a state of sensitivity attenuation, the analyte monitoring system 1 can determine the analyte level using the correction method involved in the present disclosure. Specifically, the correction time can be set during the working hours. During the working hours, the analyte monitoring system 1 can collect the analyte signal and determine the analyte level based on the analyte signal and the target parameter. During the correction time, the analyte monitoring system 1 can apply the input signal to at least two electrodes 100 of the analyte sensor 10, collect the response signal corresponding to the input signal, and determine the analyte level based on the analyte signal and the response signal using the correction method involved in the present disclosure. As a result, the accuracy of determining the analyte level by the analyte sensor 10 that has undergone sensitivity attenuation can be improved.

[0050] As shown in FIG2 , 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, apply an input signal to the at least two electrodes 100 of the analyte sensor 10 within a calibration time, and acquire a response signal corresponding to the input signal. The processing module 20 may be configured to receive the analyte signal and the response signal and determine the analyte level using the calibration method disclosed herein.

[0051] In some examples, the analyte sensor 10 may further include a mode switching module 200. The mode switching module 200 may include a switching circuit to enable the analyte sensor 10 to have an operating mode and a calibration mode. In some examples, during the operating time, the mode switching module 200 may switch to the operating mode, and the analyte monitoring system 1 may determine the analyte level. In some examples, during the calibration time, the mode switching module 200 may switch to the calibration mode, and the analyte monitoring system 1 may calibrate the target parameter. In this case, it is possible to facilitate the analyte sensor 10 to determine the analyte level during the operating time and perform calibration during the calibration time, thereby improving the operating efficiency of the analyte monitoring system 1.

[0052] In some examples, the analyte sensor 10 may further 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 the analyte sensor 10 includes three electrodes 100, the input signal may be applied to a working electrode and a reference electrode. The input signal may include a first input signal, a second input signal, and a third input signal. The signal waveform of the 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, and a rectangular wave. The second input signal may have the same signal waveform as the first input signal. The third input signal may have the same signal waveform as the first input signal.

[0053] In some examples, the analyte monitoring system 1 may further include a first sampling module 30. The first sampling module 30 may sample the continuous signals related to the analyte level generated by the at least two electrodes 100 during operation to obtain discrete signals related to the analyte level. Specifically, the first sampling module 30 may include an analog-to-digital converter to sample and obtain the discrete signals.

[0054] In some examples, the first sampling module 30 may also sample the response signal corresponding to the input signal during the calibration time. In some examples, the analyte monitoring system 1 may further include a second sampling module 40, which may be configured to sample the response signal corresponding to the input signal during the calibration time. That is, when sampling the response signal corresponding to the input signal during the calibration time, either the first sampling module 30, which samples during the working time, or the second sampling module 40 may be used.

[0055] The analyte monitoring system 1 involved in the present disclosure may include at least two circuits. That is, it includes at least a working circuit formed by a working electrode and a counter electrode, and a measuring circuit formed by a working electrode and a reference electrode. The collected analyte signal involved in the present disclosure may be a current signal flowing through the working electrode collected during the working time. The collected response signal involved in the present disclosure may be a current signal flowing through the working electrode corresponding to the collected input signal. For example, a voltage is applied to the working electrode and the reference electrode as a first input signal, an enzyme provided on the working electrode reacts with the analyte and generates a current, and a current is collected at the working electrode as a response signal. The current as a response signal may be related to the sensitivity attenuation of the analyte sensor 10. The current as a response signal may also be related to the analyte level. The collection of the analyte signal and the collection of the response signal may be completed by one sampling module or by two different sampling modules.

[0056] In some examples, the analyte monitoring system 1 may further 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 lookup table or adjustment coefficient), a reference signal curve, at least one reference parameter of the reference signal curve, or a correction coefficient.

[0057] FIG3 is a flow chart illustrating a method for correcting sensitivity degradation of analyte sensor 10 according to an example of the present disclosure.

[0058] The calibration method of the present disclosure can be applied to the above-mentioned analyte monitoring system 1. Furthermore, the calibration method of the present disclosure can be applied to the above-mentioned processing module 20, that is, the processing module 20 can determine the analyte level using the calibration method of the present disclosure.

[0059] 3 , in some examples, the calibration method may include: applying a first input signal to at least two electrodes 100 of the analyte sensor 10 at least once within a calibration time, and collecting a response signal corresponding to the first input signal (step S100), obtaining a calibration 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 attenuation based on the calibration coefficient (step S300), and determining the analyte level based on a signal related to the analyte level collected by the analyte sensor 10 and the corrected target parameter (step S400).

[0060] Continuing with reference to Figure 3, in some examples, in step S100, a first input signal can be applied to at least two electrodes 100 of the analyte sensor 10. In some examples, the signal waveform of the first input signal can include a combination of one or more of a pulse wave, a step wave, a sawtooth wave, a triangle wave, a sine wave, a staircase wave, and a rectangular wave. The combination involved in the present disclosure refers to the superposition of multiple signal waveforms. Specifically, multiple signal waveforms can be aligned and superimposed in period or staggered and superimposed in period. For example, when two pulse waves are aligned and superimposed in period, a signal waveform having a pulse wave with a higher pulse amplitude can be obtained, and when two pulse waves are staggered and superimposed in period, a signal waveform having two pulse waves can be obtained. In some examples, the first input signal can be generated by a signal source 300.

[0061] FIG4A is a schematic diagram illustrating a first embodiment of a signal waveform of a first input signal according to an example of the present disclosure. FIG4B is a schematic diagram illustrating a second embodiment of a signal waveform of a first input signal according to an example of the present disclosure. FIG4C is a schematic diagram illustrating a third embodiment of a signal waveform of a first input signal according to an example of the present disclosure.

[0062] Figure 4D is a schematic diagram illustrating a fourth embodiment of the signal waveform of the first input signal involved in the example of the present disclosure. Figure 4E is a schematic diagram illustrating a fifth embodiment of the signal waveform of the first input signal involved in the example of the present disclosure.

[0063] As described above, 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 staircase wave, and a rectangular wave. To this end, the present disclosure also provides some examples of the signal waveform of the first input signal.

[0064] Referring to the first embodiment shown in FIG4A , the waveform of the first input signal can be a step wave. The abscissa represents time, and the ordinate represents the amplitude of the first input signal. Furthermore, after application, the first input signal can return to a low level or other level that does not affect the operating mode of the analyte monitoring system 1.

[0065] Referring to the second embodiment shown in FIG4B , the waveform of the first input signal may be a pulse wave. As shown in FIG4B , a pulse wave having multiple cycles may be applied during the calibration time. For example, a pulse wave having 2, 3, 4, 5, 6, 7, 8, 9, or 10 cycles may be applied.

[0066] 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 waveform has different pulse amplitudes, and applying signal waveforms with different pulse amplitudes to the electrode 100 can enable the corresponding response signal to reflect more information about the electrode 100, such as specificity, response time or linear range, and thus enable the correction coefficient used in the correction to include more information about the electrode 100, thereby further improving the accuracy of determining the analyte level. To this end, the present disclosure also provides some examples of stepped signal waveforms. It should be noted that the present disclosure is not limited to the signal waveforms shown in Figures 4C, 4D and 4E, and other stepped signal waveforms with signal gradients are also within the scope of the present disclosure, such as a decreasing stepped signal waveform.

[0067] Referring to the third embodiment shown in FIG4C , the signal waveform of the first input signal may include a combination of at least two pulse waves, and form a signal waveform having multiple pulse waves with different pulse amplitudes in a time sequence, wherein the multiple pulse waves with different pulse amplitudes form a stepped signal waveform. In this case, the pulse waves with different pulse amplitudes can cause the electrode 100 to undergo charge transfer to varying degrees, thereby enabling the kinetic characteristics of the electrochemical reaction occurring at the electrode 100 under pulse waves with different pulse amplitudes to be obtained. Thus, the obtained correction coefficient can include information related to the kinetic characteristics of the electrode 100 under pulse waves with different pulse amplitudes. Calibration based on the correction coefficient including information related to the kinetic characteristics of the electrode 100 can optimize the ability of the analyte sensor 10 to determine the analyte level, thereby further improving the accuracy of determining the analyte level.

[0068] Referring to the fourth embodiment shown in FIG4D , the signal waveform of the first input signal may include a combination of at least two pulse waves, and form a signal waveform comprising a combination of a plurality of pulse waves having the same pulse amplitude and a step wave in a time sequence, wherein the combination of the pulse wave and the step wave forms a stepped signal waveform. In this case, the step wave included in the signal waveform of the first input signal has a relatively long duration, and information related to the steady-state response of the electrode 100 can be obtained; the pulse wave included in the signal waveform of the first input signal has a relatively short duration, and information related to the transient response of the electrode 100 can be obtained. Thus, the obtained correction coefficient can include information related to the steady-state response and transient response of the electrode 100. Calibration based on the correction coefficient including information related to the steady-state response and transient response of the electrode 100 can optimize the steady-state response capability and transient response capability of the analyte sensor 10, thereby further improving the accuracy of determining the analyte level.

[0069] Referring to the fifth embodiment shown in FIG4E , the signal waveform of the first input signal can include a combination of at least two pulse waves, forming a signal waveform of multiple pulse waves with different pulse amplitudes in a time sequence. At the same time, the directions of two adjacent pulse waves are different, that is, the positive and negative directions alternate, and the multiple pulse waves with different pulse amplitudes form a step-like signal waveform. In this case, the different directions of the pulse waves can obtain information related to the electrode 100 and the reverse reaction. Thus, the obtained correction coefficient can include information related to the electrode 100 and the reverse reaction. Calibration based on the correction coefficient including information related to the electrode 100 and the reverse reaction can reduce the impact of the reverse reaction on the determination of the analyte level by the analyte sensor 10, thereby further improving the accuracy of the determination of the analyte level.

[0070] FIG5 is a schematic diagram illustrating an acquisition response signal involved in an example of the present disclosure.

[0071] In some examples, a response signal corresponding to the first input signal can be collected. As shown in Figure 5, when collecting the response signal, the response signal and the corresponding collection time can be obtained. In this case, response parameters related to sensitivity degradation can be obtained during the use of the analyte sensor 10, thereby facilitating correction for sensitivity degradation during use. In some examples, the collected response signal can be discrete data. This facilitates digital processing of the response signal through an algorithm.

[0072] In some examples, fitting can be performed based on the response signal to obtain a response signal curve. The response signal can be discrete data obtained by the first sampling module 30 or the second sampling module 40 shown in FIG5 . In this case, by fitting the discrete data obtained by the first sampling module 30 or the second sampling module 40 into a continuous response signal curve, it is possible to facilitate the extraction of information related to sensitivity attenuation from the response signal. In addition, fitting can smooth the response signal, thereby reducing data fluctuations caused by acquisition errors or other factors. In addition, fitting can interpolate the response signal to obtain a continuous response signal curve, thereby improving the accuracy of the obtained response parameters.

[0073] In some examples, the response signal curve obtained by fitting may include an ascending segment and / or a descending segment. For example, the response signal obtained by acquisition shown in FIG5 may be fitted to obtain a response signal curve including a descending segment.

[0074] 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 signal can be directly fitted into a curve form.

[0075] FIG6 is a flow chart illustrating applying a first input signal and collecting a corresponding response signal according to an example of the present disclosure.

[0076] As described above, in step S100, the first input signal may be applied to the at least two electrodes 100 of the analyte sensor 10 at least once within the calibration time, and a response signal corresponding to the first input signal may be collected. The number of times the first input signal is applied to the at least two electrodes 100 of the analyte sensor 10 within the calibration time may be 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10.

[0077] 6 , in some examples, applying a first input signal and collecting a corresponding response signal may include: applying the first input signal based on a preset number of collections, and collecting a response signal corresponding to the first input signal (step S101 ); in response to the number of collections being equal to the preset number of collections, averaging the response signals obtained based on multiple collections to obtain an average response signal (step S102 ); and obtaining a response signal curve based on the average response signal (step S103 ).

[0078] Continuing with reference to Figure 6, in some examples, in step S101, the first input signal can be applied based on a preset number of acquisitions. The first input signal can be applied multiple times within the correction time, and the number of times the first input signal is applied can be a preset number of acquisitions. In addition, in the gaps between multiple applications, the first input signal can return to a low level or other level that can restore the response signal to a steady state when the first input signal is not applied. The time required for the gaps between multiple applications can be sufficient to restore the response signal to a steady state when the first input signal is not applied. In this case, the mutual interference between the multiple response signals generated by the multiple applications of the input signal can be reduced, thereby improving the accuracy of obtaining the response parameters. The number of times the first input signal is applied can be related to the preset number of acquisitions.

[0079] Continuing with FIG. 6 , in some examples, in step S102, in response to the number of acquisitions being equal to a preset number of acquisitions, an average response signal can be obtained by averaging the response signals obtained from the multiple acquisitions. Specifically, a first input signal is applied, response signals are acquired a corresponding number of times, and the response signals are averaged to obtain the average response signal. The number of times the first input signal is applied is equal to the number of times the response signals are acquired, i.e., equal to the preset number of acquisitions. In this case, acquiring the response signals multiple times and averaging the response signals to obtain the average response signal can improve the accuracy of the acquired response signal.

[0080] Continuing with FIG6 , in some examples, in step S103, a response signal curve may be obtained based on the average response signal. In this case, obtaining the response signal curve by averaging the response signal can improve the accuracy of at least one response parameter of the response signal obtained based on the response signal curve, thereby improving the accuracy of correction based on the response parameter.

[0081] Returning to reference Figure 3, in some examples, in step S200, a correction coefficient can 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 can represent the response signal curve of the response signal corresponding to the input signal when the sensitivity attenuation of the analyte sensor 10 has not occurred. In this case, by using the reference signal curve corresponding to the absence of sensitivity attenuation as a standard, a correction coefficient that brings the response parameter close to the reference parameter can be obtained. In addition, using the reference signal curve corresponding to the absence of sensitivity attenuation of the analyte sensor 10 as a standard can reduce the impact of uncertainties on the accuracy of the standard compared to using the signal curve of the analyte sensor 10 in other states. In addition, unlike calibrating the analyte sensor 10 using fingertip blood as a standard, using the reference signal curve corresponding to the absence of sensitivity attenuation as a standard can improve the convenience of determining the analyte level.

[0082] Continuing with reference to FIG. 3 , in some examples, in step S200 , at least one response parameter of the response signal can be obtained based on a response signal curve determined from the response signal. The parameter type of the response parameter can include a combination of one or more of peak value, area under the curve, and slope of the curve. In this case, when the parameter type is peak value, it can reflect the maximum response value of the response signal to the input signal, thereby obtaining the maximum responsiveness of the analyte sensor 10 to the input signal, thereby obtaining the degree of sensitivity attenuation. Furthermore, when the parameter type is integral under the curve, it can reflect the cumulative response of the response signal to the input signal, thereby obtaining the charge accumulation capability of the analyte sensor 10, thereby obtaining the degree of sensitivity attenuation. Furthermore, when the parameter type is slope of the curve, it can reflect the speed at which the response signal decreases or increases, thereby obtaining the response speed of the analyte sensor 10, thereby obtaining the degree of sensitivity attenuation.

[0083] In some examples, the response signal curve can be in the form of a curve. The peak value in the parameter type can be the peak value of the response signal curve. The area under the curve in the parameter type can be the integral of the response signal curve over time. The slope of the curve in the parameter type can be the slope of the curve in the target segment. In addition, the target segment can be a descending segment or an ascending segment. Among them, the descending segment can correspond to the response signal collected and obtained in Figure 5. In some examples, the slope of the curve in the parameter type can be the median of the slope of the target segment, the slope in the target segment at half the peak value of the response signal curve (i.e., at half the peak value), or the slope corresponding to a feature point on the target segment.

[0084] In some examples, the response signal curve may be in the form of a straight line. The curve slope in the parameter type may be the slope of the straight line. The response signal curve in the form of a straight line can be obtained by performing a coordinate transformation on the response signal curve in the form of a curve (described later). In this case, the slope can be directly obtained from the straight line without having to consider how to select the slope when the response signal curve is a curve, thereby simplifying the calibration method.

[0085] In some examples, a reference signal curve can be obtained based on a response signal corresponding to an applied input signal. Specifically, an input signal can be applied to an analyte sensor 10 that has not undergone sensitivity attenuation, the response signal can be collected, and at least one reference parameter of the response signal can be obtained. That is, the reference signal curve is the corresponding response signal obtained by applying an input signal to the analyte sensor 10 that has not undergone sensitivity attenuation. In this case, by actually applying an input signal and obtaining a response signal to obtain a reference signal curve, the reference signal curve obtained before correction can be made close to the true value without sensitivity attenuation.

[0086] In some examples, the input signal applied may be a second input signal. In some examples, a reference signal curve may be obtained and saved based on the second input signal before calibration. Specifically, the second input signal may be configured to be applied to the analyte sensor 10 that does not require calibration outside of the calibration time. The second input signal may have the same signal waveform as the first input signal. Outside of the calibration time involved in the present disclosure may be working time during the use period of the target object or factory production time or assembly time before the use period of the target object, etc.

[0087] In some examples, the second input signal can be generated by signal source 300 during use of the analyte monitoring system 1. In some examples, the second input signal can be generated by an external signal source before use of the analyte monitoring system 1. In some examples, the external signal source can be a function signal generator. In some examples, a reference signal corresponding to the second input signal can be collected. A fitting can be performed based on the reference signal to obtain a reference signal curve.

[0088] In some examples, the reference signal curve obtained based on the second input signal can be stored in the storage module 50. In this case, by applying the second input signal to obtain and store the reference signal curve, the analyte monitoring system 1 can determine the calibration coefficient based on the stored reference signal curve within the calibration time.

[0089] In some examples, the applied input signal may be a third input signal. In some examples, a reference signal curve may be obtained based on the third input signal before calibration. The third input signal may be configured to be applied to sample sensors that do not require calibration outside the calibration period and to sample sensors that require calibration at different time periods. The sample sensor may be the sensor used when obtaining the target relationship. The sample sensor may simulate conditions where the analyte sensor 10 experiences varying degrees of sensitivity attenuation and conditions where no sensitivity attenuation occurs. The third input signal may have the same signal waveform as the first input signal. The third input signal may be generated by an external signal source. In some examples, the reference signal curve obtained based on the third input signal may be stored in the storage module 50. In this case, the correction coefficient can be determined based on the stored reference signal curve of the sample sensor within the calibration period, without having to apply an input signal to the analyte sensor 10 before the calibration period. This reduces the cost of obtaining the reference signal curve and preserves the service life of the analyte sensor 10. This further improves the accuracy of the analyte sensor 10 in determining analyte levels.

[0090] In some examples, a reference signal corresponding to the third input signal may be collected, and fitting may be performed based on the reference signal to obtain a reference signal curve.

[0091] In some examples, the third input signal can also be used to obtain an attenuation signal curve, which can be used to determine a target relationship (described later). Specifically, multiple attenuation signal curves can be obtained based on the third input signal at different time periods. The different time periods can be time periods corresponding to different degrees of sensitivity attenuation in the sample sensor.

[0092] In some examples, a response signal corresponding to the third input signal may be collected, and a fitting may be performed based on the response signal to obtain an attenuation signal curve.

[0093] Continuing with FIG. 3 , in some examples, in step S200, a reference signal curve can be obtained based on a preset formula related to the input signal. In this case, obtaining the reference signal curve using the preset formula can facilitate rapid acquisition of the reference signal curve before calibration, and can also obtain an ideal reference signal curve without sensitivity attenuation, that is, can obtain a value close to the theoretical value without sensitivity attenuation. In some examples, when the input signal is a step wave or a pulse wave, the preset formula is expressed as:

[0094] Where I is the reference signal curve, A is the 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.

[0095] Continuing to refer to FIG3 , in some examples, in step S200 , at least one reference parameter of the reference signal curve can be obtained. When the input signal is a step wave or a pulse wave, the preset formula is In 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 with a preset formula can be coordinate transformed, and the reference signal curve can be transformed from a curve form to a straight line form, and the slope of the curve in at least one reference parameter can be A.

[0096] In some examples, the parameter type of the reference parameter and the parameter type of the response parameter can be the same. For example, if the parameter type of the response parameter includes a peak value, the parameter type of the reference parameter can also include a peak value. In this case, it is convenient to directly compare the response parameter and the reference parameter, thereby obtaining the difference between the response signal and the reference signal.

[0097] Continuing with FIG. 3 , in some examples, in step S200, a correction coefficient can be obtained based on at least one response parameter of the response signal and a stored reference signal curve during calibration. Specifically, the at least one response parameter of the response signal and at least one reference parameter of a stored reference signal curve can be analyzed to obtain a difference between the response signal and the reference signal curve, and the correction coefficient can be obtained based on the difference. Alternatively, the stored reference signal curve can be a reference signal curve obtained based on the second input signal, the third input signal, or a preset formula.

[0098] In some examples, a correction coefficient can be obtained based on a difference between a response signal and a reference signal curve. In some examples, the difference between the response signal and the reference signal curve can be a difference between a response parameter and a reference parameter. For example, the difference or ratio between the response parameter and the reference parameter can be used. In some examples, a correction coefficient can be obtained based on a difference or ratio between the response parameter and the reference parameter. For example, the ratio between the response parameter and the reference parameter can be used as the correction coefficient.

[0099] In other examples, different correction coefficients can be used to calibrate the target parameter of the analyte sensor 10 and the correction results can be compared to obtain the correction coefficient. The target parameter of the analyte sensor 10 is calibrated using different correction coefficients. For example, the different correction coefficients can 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 calibrate the target parameter. After the target parameter of the analyte sensor 10 is calibrated, the corresponding analyte level is also calibrated. Using the analyte level corresponding to the stored reference signal curve as a standard, the corrected analyte level is compared with the analyte level corresponding to the stored reference signal curve. The correction coefficient corresponding to the closest corrected analyte level is obtained.

[0100] In some examples, the response signal can be time-aligned with a stored reference signal curve before analyzing the difference. For example, the time at which the pulse wave starts can be aligned. In this case, the accuracy of analyzing the difference between the response signal and the stored reference signal curve can be improved.

[0101] Continuing with FIG. 3 , in some examples, in step S200, a correction coefficient can be obtained based on at least one response parameter of the response signal and a target relationship during calibration. Furthermore, the target relationship can represent a relationship between the response parameter and the correction coefficient. Specifically, the correction coefficient corresponding to the response parameter can be determined based on the target relationship to obtain the correction coefficient. The response parameter can be at least one response parameter of the response signal corresponding to the first input signal.

[0102] 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 that satisfies a linear relationship between the response parameter and the correction coefficient. In this case, by directly using an adjustment coefficient to represent the linear relationship between the response parameter and the correction coefficient, the amount of memory used in the storage module 50 when storing the target relationship can be reduced.

[0103] 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 the adjustment coefficient to obtain the correction coefficient.

[0104] In some examples, the target relationship can be represented by a lookup table. The response parameters and correction coefficients can be stored in the lookup table. The lookup table can represent the corresponding relationship between the response parameters and the correction coefficients. In this case, it is easy to retrieve the response parameters to quickly obtain the corresponding correction coefficients.

[0105] As described above, a reference signal curve and multiple attenuation signal curves can be obtained based on the third input signal. In some examples, a target relationship can be determined based on at least one reference parameter of the reference signal curve determined by the third input signal and at least one response parameter of the multiple attenuation signal curves.

[0106] In some examples, the attenuation signal curve can be in the form of a straight line. The curve slope in the parameter type can be the slope of the straight line. In this case, the slope can be directly obtained from the straight line, without having to consider how to select the slope when the attenuation signal curve is a curve. This allows for obtaining parameters related to the severity of sensitivity attenuation in various time periods corresponding to varying degrees of sensitivity attenuation in the sample sensor.

[0107] In some examples, different calibration coefficients can be obtained by multiplying different adjustment parameters by the response parameter to obtain a target relationship. The target parameter of the sample sensor is calibrated using the different calibration coefficients. After the target parameter of the sample sensor is calibrated, the corresponding analyte level is also calibrated. The analyte level corresponding to the reference signal curve is used as a standard, and the corrected analyte level is compared to the analyte level corresponding to the reference signal curve. The adjustment parameter corresponding to the closest corrected analyte level is used as the target relationship.

[0108] In some examples, different correction coefficients can be used to calibrate the sample sensor to obtain a target relationship. The target parameters of the sample sensor are calibrated using different correction coefficients. After the target parameter of the sample sensor is calibrated, the corresponding analyte level is also calibrated. For example, when the target parameter is a sensitivity coefficient, after the sensitivity coefficient is calibrated, the corresponding analyte level calculated based on the target parameter is also calibrated. Using the analyte level corresponding to the reference signal curve as a standard, the corrected analyte level is compared with the analyte level corresponding to the reference signal curve for closeness. The correction coefficient corresponding to the closest corrected analyte level and the initial response parameter are stored in a lookup table. The lookup table is used as the target relationship.

[0109] In other examples, the target relationship can be obtained through machine learning. In some examples, the machine learning can be to learn at least one response parameter of the response signal and at least one reference parameter of the reference signal curve to obtain the target relationship between the response parameter and the correction coefficient.

[0110] In some examples, the target relationship can be obtained through at least one of an in vitro experiment and a human-worn experiment. The in vitro experiment can be performed by measuring relevant data of the analyte sensor 10 in a glucose solution simulating interstitial fluid. The human-worn experiment can be performed by measuring relevant data of the analyte sensor 10 while implanted in the interstitial fluid of a human body.

[0111] In some examples, the target relationship may be stored. In some examples, the target relationship may be stored in the storage module 50 .

[0112] Continuing with reference to FIG. 3 , in some examples, in step S200, a calibration may be performed in response to the analyte sensor 10 being in a state of reduced sensitivity. Specifically, it may be determined that the analyte sensor 10 is in a state of reduced sensitivity 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, the calibration may be performed in response to the analyte sensor 10 being in a state of reduced sensitivity. In this case, the ability to detect that the analyte sensor 10 is in a state of reduced sensitivity and perform the calibration enables the analyte monitoring system 1 to maintain accuracy in determining analyte levels during use by a subject.

[0113] 3 , in some examples, in step S200, a difference between at least one response parameter and at least one reference parameter may be determined. Furthermore, it may be determined that the analyte sensor 10 is in a desensitized 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 desensitized state.

[0114] As described above, the response signal curve, the reference signal curve, or the attenuation signal curve may be in the form of a straight line. To this end, the present disclosure further provides an example of determining a response parameter or a reference parameter in the form of a straight line.

[0115] In some examples, a coordinate transformation can be performed on the response signal curve, the reference signal curve, or the attenuation signal curve. The coordinate transformation can be a time transformation of the above-mentioned curve to transform the above-mentioned curve from a curve form to a straight line form. For example, when the input signal is a step wave or a pulse wave, the above-mentioned curve satisfies the relationship that the signal is directly proportional to the inverse of the arithmetic square root of time. The time of the above-mentioned curve can be transformed from t to 1 / sqrt(t), that is, from t to the inverse of the arithmetic square root of t. When the above-mentioned curve satisfies the relationship that the signal is directly proportional to the logarithm of time, the time of the above-mentioned curve can be transformed from t to ln(t). In this case, the above-mentioned curve can be transformed from a curve form to a straight line form through coordinate transformation, and then the straight line can be directly processed, such as calculating the slope, without considering the problem of how to select the slope of the feature point when the above-mentioned curve is in a curve form, thereby simplifying the correction method. It should be noted that the present disclosure is not limited to the above-mentioned examples. Other coordinate transformations that can transform the above-mentioned curve from a curve form to a straight line form are also within the scope of the present disclosure, such as a combination of the above-mentioned two coordinate transformations.

[0116] In some examples, at least one response parameter of the response signal or at least one reference parameter of the reference signal can be obtained based on the response signal curve, reference signal curve, or attenuation signal curve that has undergone coordinate transformation. The slope of the curve can be used as the response parameter or reference parameter of the response signal curve, reference signal curve, or attenuation signal curve. For example, when the third input signal is a step wave or a pulse wave, the time of the attenuation signal curve can be transformed from t to 1 / sqrt(t), and the attenuation signal curve after coordinate transformation is transformed from a straight line to a curve. The slope of the attenuation signal curve after coordinate transformation can be used as the curve slope of the attenuation signal curve. The curve slope of the attenuation signal curve can be used as the response parameter of the attenuation signal curve.

[0117] FIG. 7A is a flowchart illustrating a first embodiment of obtaining a correction coefficient according to an example of the present disclosure.

[0118] As described above, 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.

[0119] Referring to Figure 7A, in some examples, the first implementation method of obtaining the correction coefficient may include: performing 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).

[0120] Continuing with FIG. 7A , in some examples, in step S201, a coordinate transformation may be performed on the response signal curve. The coordinate transformation may transform the response signal curve from a curved form to a straight line form. In this case, for input signals having certain specific waveforms, such as step waves or pulse waves, the coordinate transformation may transform the response signal curve into a straight line. This allows for direct processing of the straight line, such as calculating its slope, without having to consider how to select the slopes of characteristic points when the response signal curve is a curve, thereby simplifying the calibration method.

[0121] Continuing with FIG. 7A , in some examples, in step S202, at least one response parameter of the response signal can be obtained based on the coordinate-transformed response signal curve. For example, when the input signal has a pulse wave or step wave waveform, the slope of the coordinate-transformed response signal curve can be used as the at least one response parameter of the response signal.

[0122] 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 from the lookup table.

[0123] Continuing with FIG. 7A , in some examples, in step S203, a target relationship can be determined and stored based on the reference signal curve and the attenuation signal curve corresponding to the third input signal before calibration. That is, a reference signal curve can be obtained based on the third input signal before calibration. Multiple attenuation signal curves can be obtained based on the third input signal at different time periods. 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 multiple attenuation signal curves. During calibration, a correction coefficient is determined based on at least one response parameter of the response signal and the target relationship. The target relationship represents the relationship between the response parameter and the correction coefficient. In this case, by obtaining the target relationship based on the reference signal curve and the attenuation signal curve and performing calibration based on the stored target relationship, compared to storing the reference signal curve, the memory usage of the storage module 50 can be reduced. Furthermore, during calibration, the correction coefficient is obtained based on the target relationship. The correction coefficient is obtained by simple calculation (e.g., multiplying the response parameter by the adjustment coefficient) or by searching a lookup table. This reduces the number of processing steps during calibration, thereby increasing calibration speed and thus improving the real-time performance of the calibration method.

[0124] FIG. 7B is a flowchart illustrating a second embodiment of obtaining a correction coefficient according to an example of the present disclosure.

[0125] 7B , in some examples, a second implementation of obtaining a correction coefficient may include: acquiring at least one response parameter of a response signal based on a response signal curve (step S211 ), and obtaining a correction coefficient based on at least one response parameter of the response signal and a stored reference signal curve (step S212 ).

[0126] Continuing with FIG. 7B , in some examples, in step S211, the parameter type of the response parameter may include a combination of one or more of a peak value, an area under the curve, and a curve slope. When the response signal curve is in the form of a curve, the curve slope of the response signal may be the median of the slope of the curve in a descending or ascending segment, the slope corresponding to half the peak value, or the slope corresponding to another characteristic point on the curve (e.g., the point with the maximum slope on the curve).

[0127] Continuing with FIG. 7B , in some examples, in step S212 , the response signal can be aligned with a stored reference signal curve in time. For example, alignment can be performed based on the pulse wave start time. At least one response parameter of the response signal and at least one reference parameter of the stored reference signal curve are then analyzed to obtain a difference between the response signal and the reference signal curve, and a correction coefficient is obtained based on the difference. For example, machine learning methods can be used to analyze the difference.

[0128] Continuing to refer to Figure 7B, in some examples, in step S212, the reference signal curve can be obtained and saved based on the second input signal before correction. That is, the reference signal curve can be obtained and saved based on the second input signal before correction. During 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. In this case, by performing correction based on the saved reference signal curve, the standard used for correction can be kept intact, which can reduce the loss of information compared to converting the reference signal curve into other information, thereby improving the accuracy of determining the analyte level. In addition, saving the reference signal curve before correction can simplify the preparatory steps before correction without the need for additional processing. In addition, when the reference signal curve is more complex, it is difficult to find the mathematical relationship between the reference signal curve and the response signal curve. Directly using the reference signal curve for correction can improve the applicability of the correction method.

[0129] Continuing with reference to FIG3 , in some examples, in step S300, the target parameter of the analyte sensor 10 related to sensitivity attenuation can be corrected based on the correction coefficient. The target parameter can be related to the 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 to the reference parameter, the correction coefficient can be multiplied or divided by the target parameter for correction. In some examples, when the correction coefficient is related to the difference between the response parameter and the reference parameter, the correction coefficient can be a relative error, and the target parameter can be increased or decreased by the amount of change corresponding to the relative error for correction. The amount of change corresponding to the relative error can be equal to the relative error multiplied by the target parameter. In addition, the relative error can be in the form of a percentage of the difference.

[0130] Alternatively, 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 calculated by dividing the analyte signal by the sensitivity of the analyte sensor 10), and a calibrated target parameter may be used to calibrate the analyte signal or sensitivity. Specifically, the target parameter may be a sensitivity coefficient or a current compensation coefficient.

[0131] 3 , in some examples, in step S400, the sensitivity of the analyte sensor 10 may be calibrated based on the sensitivity coefficient or the current value of the analyte sensor 10 may be calibrated based on the current compensation coefficient. In some examples, the analyte level may be determined based on the analyte signal collected by the analyte sensor 10 and the calibrated target parameter.

[0132] Continuing with reference to FIG. 3 , in some examples, in step S400, the analyte level can be determined based on the analyte signal acquired by the analyte sensor 10 and the calibrated target parameter. In this case, by calibrating the target parameter based on the obtained calibration coefficient and then determining the analyte level based on the calibrated target parameter, the analyte sensor 10 experiencing sensitivity reduction can obtain the analyte level that would be obtained without sensitivity reduction. This can improve the accuracy of analyte level determination by the analyte sensor 10 experiencing sensitivity reduction.

[0133] 3 , in some examples, in step S400, when the target parameter is a sensitivity coefficient, the sensitivity of the analyte sensor 10 can 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.

[0134] In some examples, when the target parameter is a current compensation coefficient, the current value of analyte sensor 10 can be corrected based on the current compensation coefficient. In some examples, the analyte level is determined based on the analyte signal collected by analyte sensor 10 and the corrected current value. In this case, the current value can be indirectly corrected by correcting the current compensation coefficient.

[0135] One or more steps of the calibration method of the present disclosure may be performed within the calibration time, such as the application of the first input signal in step S100. Some parameters required for one or more steps of the calibration method of the present disclosure may be obtained outside the calibration time, such as during the operating time of the target object during its use, or during factory production or assembly time before the target object is used. For example, at least one reference parameter, lookup table, or adjustment coefficient of the reference signal curve in step S200 may be obtained outside the calibration time.

[0136] At least one reference parameter of the reference signal curve involved in the present disclosure can be obtained by an analyte sensor 10 that has not experienced sensitivity attenuation. In addition, the at least one reference parameter of the reference signal curve can be obtained by calibrating the analyte sensor 10 when the target subject is in a stable state, such as when the target subject is fasting or at night when the target subject is in a static state.

[0137] The analyte sensor 10 involved in the present disclosure that has not experienced sensitivity attenuation can be an analyte sensor 10 that is not in a sensitivity attenuation state, such as an analyte sensor 10 during factory production or assembly time before the target object uses the analyte monitoring system 1, an analyte sensor 10 whose difference between a response parameter and a reference parameter is less than a first threshold, an analyte sensor 10 before the target object uses it or after using it for a period of time, and an analyte sensor 10 that has been calibrated.

[0138] The calibration frequency of the calibration method of the present disclosure may be once a day, twice a day, once every two days, once a week, or may be performed in response to the analyte sensor 10 being in a sensitivity attenuation state.

[0139] The kinetic properties referred to in this disclosure include information related to sensitivity.

[0140] The present disclosure also relates to a computer-readable storage medium, which may store at least one instruction. When the at least one instruction is executed by a processor, it implements one or more steps in the above-mentioned calibration method, or implements the above-mentioned analyte monitoring system 1.

[0141] The present disclosure also relates to an electronic device, which may include a processor and a memory. The processor executes a program stored in the memory to implement one or more steps in the above-mentioned calibration method, or implement the above-mentioned analyte monitoring system 1.

[0142] Although the present disclosure has been described in detail above with reference to the accompanying drawings and embodiments, it will be understood that the above description does not limit the present disclosure in any form. Those skilled in the art may modify and change the present disclosure as needed without departing from the spirit and scope of the present disclosure, and such modifications and variations all fall within the scope of the present disclosure.

Claims

1. A calibration method for sensitivity attenuation of an analyte sensor, characterized in that, Comprising: Applying the first input signal to at least two electrodes of the analyte sensor at least once within the calibration time, and collecting the response signal corresponding to the first input signal; Obtaining a calibration coefficient based on at least one response parameter of the response signal and at least one reference parameter of the reference signal curve; Correcting the target parameter related to the sensitivity attenuation of the analyte sensor based on the calibration coefficient; Determining the analyte level based on the signal related to the analyte level collected by the analyte sensor and the corrected target parameter.

2. The method for correcting sensitivity attenuation according to claim 1, wherein The signal waveform of the first input signal includes a combination of at least two pulse waves, and the pulse amplitudes of the at least two pulse waves are different to form the stepped signal waveform.

3. The method for correcting sensitivity attenuation according to claim 1, wherein Performing fitting on the response signal to obtain a response signal curve, performing coordinate transformation on the response signal curve, and obtaining at least one response parameter of the response signal based on the response signal curve after coordinate transformation.

4. The method for correcting sensitivity attenuation according to claim 1, wherein Obtaining the reference signal curve based on the second input signal before calibration and saving the reference signal curve, and obtaining the calibration coefficient based on at least one response parameter of the response signal and at least one reference parameter of the reference signal curve during calibration, wherein the signal waveform of the second input signal is the same as that of the first input signal; and / or Obtaining the reference signal curve based on the third input signal before calibration, obtaining a plurality of attenuation signal curves based on the third input signal at different time periods, determining a target relationship 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 saving the target relationship, and determining the calibration coefficient based on at least one response parameter of the response signal and the target relationship during calibration, wherein the target relationship represents the relationship between the response parameter and the calibration coefficient, and the signal waveform of the third input signal is the same as that of the first input signal.

5. The method for correcting sensitivity attenuation according to claim 1, wherein Obtaining the reference signal curve based on a preset formula related to the input signal; and / or Obtaining the reference signal curve based on the response signal corresponding to the applied input signal.

6. The method for correcting sensitivity attenuation according to 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 a proportionality coefficient, and t is time.

7. The method for correcting sensitivity attenuation according to claim 1, wherein The types of parameters of the response parameter are the same as those of the reference parameter, and the types of parameters include one or a combination of more of peak value, area under the curve, and curve slope.

8. The method for correcting sensitivity attenuation according to claim 1, wherein The target parameter is a sensitivity coefficient, the sensitivity of the analyte sensor is corrected based on the sensitivity coefficient, and 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.

9. An analyte monitoring system, characterized in that, It includes an analyte sensor and a processing module; The analyte sensor is configured to collect signals related to the analyte level, and apply an input signal to at least two electrodes of the analyte sensor and collect the response signal corresponding to the input signal within a correction time; The processing module is configured to receive the signal and the response signal and determine the analyte level by using the correction method according to any one of claims 1 to 8.

10. The analyte monitoring system according to claim 9, wherein the analyte sensor further includes a mode switching module, and the mode switching module includes a switching circuit to enable the analyte sensor to have a working mode and a correction mode.

11. A computer-readable storage medium, wherein the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, it implements the correction method according to any one of claims 1 to 8, or implements the analyte monitoring system according to any one of claims 9 to 10.

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