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

Abstract

The present disclosure describes a correction method, system and medium for sensitivity attenuation of an analyte sensor, the correction method comprising applying a first input signal to at least two electrodes of the analyte sensor at least once within a correction time, and acquiring 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 the reference signal curve; correcting a target parameter of the analyte sensor related to the sensitivity attenuation based on the correction coefficient; the analyte level is determined based on a signal associated with the analyte level acquired by the analyte sensor and the corrected target parameter. Therefore, the accuracy and convenience of determining the analyte level can be improved.

Description

Technical Field

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

[0002] Diabetes is a series of metabolic disorders of proteins, fats, water and electrolytes caused by insufficient insulin secretion and reduced sensitivity of target tissue cells to insulin. At present, continuous glucose monitoring (CGM) technology can continuously monitor glucose in the user's interstitial fluid. Taking the continuous glucose monitoring technology based on electrochemical analysis as an example, a glucose sensor for monitoring glucose concentration can generally be implanted subcutaneously to monitor the change of glucose concentration in subcutaneous interstitial fluid.

[0003] The glucose sensor used in continuous glucose monitoring usually shows a phenomenon that the accuracy of determining the analyte level gradually decreases after being used for a period of time. This phenomenon is called "sensitivity attenuation", "sensor drift" or "sensor fading". Sensitivity attenuation may be caused by various factors, including sensor aging, immune response or environmental factors, etc. The currently commonly used method for correcting sensitivity attenuation is to collect the blood glucose value by finger prick of the user and then use the blood glucose value as the correction value for continuous glucose monitoring.

[0004] However, multiple finger prick blood collections will reduce the user's comfort and the convenience of use. 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] In view of the above-mentioned state of the prior art, the present disclosure is completed. Its purpose 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, the first aspect of the present disclosure provides a method for correcting sensitivity attenuation of an analyte sensor, including 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 calibration 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. By using the reference signal curve as a standard, a calibration coefficient can be obtained to make the response parameter close to the reference parameter; by correcting the target parameter based on the obtained calibration coefficient and then determining the analyte level based on the corrected target parameter, an analyte sensor with sensitivity attenuation can obtain an analyte level without sensitivity attenuation. Thus, the accuracy of determining the analyte level can be improved. Additionally, different from calibrating the analyte sensor with fingertip blood as a standard, using the reference signal curve corresponding to the situation without sensitivity attenuation as a standard can improve the convenience of determining the analyte level.

[0008] Furthermore, in the calibration method related 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 the pulse amplitudes of the at least two pulse waves are different to form a stepped signal waveform. In this case, the stepped signal waveform has different pulse amplitudes. Applying a signal waveform with different pulse amplitudes to the electrodes can enable the corresponding response signals to reflect more information about the electrodes, such as specificity, response time, or linear range. Furthermore, the calibration coefficient used during calibration can include more information about the electrodes, thereby further improving the accuracy of determining the analyte level.

[0009] Moreover, in the calibration method related to the first aspect of the present disclosure, optionally, the response signal is fitted to obtain a response signal curve, a 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 the coordinate transformation. In this case, fitting the obtained discrete data into a continuous response signal curve can 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. Additionally, coordinate transformation can transform the response signal curve from a curve form to a straight line form, thereby enabling direct processing of the straight line without considering the problem of how to select the slope of the characteristic points when the response signal curve is in curve form, thus simplifying the calibration method.

[0010] In addition, in the calibration method according to the first aspect of the present disclosure, optionally, the reference signal curve is obtained based on the second input signal and the reference signal curve is saved before calibration, and 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 during calibration, where the second input signal has the same signal waveform as the first input signal; and / or the reference signal curve is obtained based on the third input signal before calibration, a plurality of 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 plurality of attenuation signal curves and the target relationship is saved, and the calibration coefficient is determined based on at least one response parameter of the response signal and the target relationship during calibration, where 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 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, by obtaining the target relationship based on the reference signal curve and the attenuation signal curve before calibration and obtaining the calibration coefficient based on the target relationship during calibration, it is convenient to obtain the calibration coefficient through simple calculation or by retrieving a look-up table, the processing steps during calibration can be reduced, thereby improving the calibration speed, and thus the real-time performance of the calibration method can be improved.

[0011] In addition, in the calibration 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 the response signal corresponding to the applied input signal. In this case, by obtaining the reference signal curve through the preset formula, it is convenient to quickly obtain the reference signal curve before calibration, and an ideal reference signal curve without sensitivity attenuation can be obtained, that is, a theoretical value close to the case without sensitivity attenuation can be obtained; in addition, by actually applying the input signal to obtain the response signal to obtain the reference signal curve, the reference signal curve obtained before calibration can be made close to the true value without sensitivity attenuation.

[0012] In addition, in the calibration 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: where 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 then the calibration coefficient can be obtained based on the reference parameter.

[0013] In addition, in the calibration method according to the first aspect of the present disclosure, optionally, the parameter types of the response parameter and the reference parameter are the same, and the parameter types include one or a combination of more than one of peak value, area under the curve, and curve slope. 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 ability of the analyte sensor to the input signal can be obtained, and the attenuation degree of the sensitivity 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 ability of the analyte sensor can be obtained, and the attenuation degree of the sensitivity can be obtained. In addition, when the parameter type is the curve slope, it can reflect the speed of the response signal decreasing or increasing, and thus the response speed of the analyte sensor can be obtained, and the attenuation degree of the sensitivity 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, and 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, and 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 the current value can be indirectly calibrated by calibrating the target parameter.

[0015] The second aspect of the present disclosure provides an analyte monitoring system, including 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 within a calibration time and collect the 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 by using the calibration method according to the first aspect of the present disclosure. Thereby, the accuracy and convenience of determining the analyte level by the analyte monitoring system can be improved.

[0016] In addition, in the analyte monitoring system according to the second aspect of the present disclosure, optionally, 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 calibration mode. In this case, it is convenient for the analyte sensor to determine the analyte level during the working time and perform calibration during the calibration time, and thus the operation efficiency of the analyte monitoring system can be improved.

[0017] A third aspect of the present disclosure provides a computer-readable storage medium storing at least one instruction, which when executed by a processor, implements the calibration method related to the first aspect of the present disclosure or implements the analyte monitoring system related to the second aspect of the present disclosure.

[0018] According to the present disclosure, there is provided a calibration method, system, and medium for sensitivity attenuation of an analyte sensor, which can improve the accuracy and convenience of determining the analyte level. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0020] Figure 1 FIG. is an application scenario diagram of the analyte monitoring system involved in the examples of the present disclosure.

[0021] Figure 2 FIG. is a system block diagram of the analyte monitoring system involved in the examples of the present disclosure.

[0022] Figure 3 FIG. is a flowchart of a calibration method for sensitivity attenuation of an analyte sensor involved in the examples of the present disclosure.

[0023] Figure 4A FIG. is a schematic diagram of a first embodiment of the signal waveform of the first input signal involved in the examples of the present disclosure. [[ID=2�]]

[0024] Figure 4B FIG. is a schematic diagram of a second embodiment of the signal waveform of the first input signal involved in the examples of the present disclosure.

[0025] Figure 4C FIG. is a schematic diagram of a third embodiment of the signal waveform of the first input signal involved in the examples of the present disclosure.

[0026] Figure 4D FIG. is a schematic diagram of a fourth embodiment of the signal waveform of the first input signal involved in the examples of the present disclosure.

[0027] Figure 4E FIG. is a schematic diagram of a fifth embodiment of the signal waveform of the first input signal involved in the examples of the present disclosure.

[0028] Figure 5 FIG. is a schematic diagram of collecting a response signal involved in the examples of the present disclosure.

[0029] Figure 6 FIG. is a flowchart of applying the first input signal and collecting the corresponding response signal involved in the examples of the present disclosure.

[0030] Figure 7A is a flowchart showing the first embodiment of obtaining a correction coefficient involved in the examples of the present disclosure.

[0031] Figure 7B is a flowchart showing the second embodiment of obtaining a correction coefficient involved in the examples of the present disclosure. Detailed Embodiment

[0032] Hereinafter, with reference to the drawings, the preferred embodiments of the present disclosure will be described in detail. In the following description, the same reference numerals are given to the same components, and repeated descriptions are omitted. In addition, the drawings are only schematic diagrams, and the ratio of the sizes of the components to each other or the shapes of the components may be different from the actual ones.

[0033] It should be noted that the terms "include" and "have" in the present disclosure and any variations thereof, for example, the processes, methods, systems, products or devices including or having a series of steps or units do not necessarily have to be limited to those steps or units clearly listed, but may include or have other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0034] The present disclosure relates to a method for correcting the sensitivity attenuation of an analyte sensor (hereinafter may be simply referred to as a correction method, and may also be referred to as an analyte sensor correction method or a calibration method, etc.). The correction method involved in the present disclosure can be applied to the case where the analyte sensor is in a state of sensitivity attenuation. When the analyte sensor is in a state of sensitivity attenuation, there is a deviation between the analyte level obtained and the analyte level obtained when the analyte sensor has not undergone sensitivity attenuation, that is, an offset analyte level is obtained. For example, due to long use time, the performance of the sensor decreases due to chemical reactions, physical changes or losses, etc., which is the sensitivity attenuation of the analyte sensor. Through the correction method provided by the present disclosure, the accuracy and convenience of determining the analyte level can be improved.

[0035] The sensitivity involved in the present disclosure may be a parameter related to the detection ability or response ability of the sensor to changes in the analyte level. The sensitivity coefficient involved in the present disclosure may be a parameter for correcting the sensitivity of the analyte sensor. The sensitivity involved in the present disclosure may be a parameter for correcting the analyte-related signal (hereinafter simply referred to as the analyte signal) of the analyte sensor.

[0036] It should be noted that the improvement in the accuracy of determining the analyte level involved in the present disclosure can be to make the analyte level obtained after calibration close to or equal to the analyte level obtained when no sensitivity attenuation occurs. For example, for the case where the analyte is glucose in interstitial fluid, the analyte level is the glucose concentration in interstitial fluid, and the analyte sensor can be a sensor including an enzyme (such as glucose oxidase or glucose dehydrogenase) that undergoes a redox reaction with glucose. The improvement in the accuracy of determining the analyte level involved in the present disclosure can be to make the glucose concentration obtained after calibration close to or equal to the glucose concentration obtained when the analyte sensor does not undergo sensitivity attenuation.

[0037] The improvement in the accuracy of determining the analyte level involved in the present disclosure can be to make the obtained analyte level close to or equal to the reference analyte level. For example, for the case where the analyte is glucose, the reference analyte level can be the glucose concentration in fingertip blood.

[0038] The present disclosure also provides an analyte monitoring system. The analyte monitoring system can collect analyte signals, apply an input signal to two electrodes of the analyte sensor within a calibration time and collect the response signal corresponding to the input signal, receive the analyte signal and the response signal, and determine the analyte level using the above-mentioned calibration method. The usage time of the analyte monitoring system can be 1 week, 2 weeks, 3 weeks, or 4 weeks. Through the calibration method involved in the present disclosure, the analyte monitoring system can maintain good accuracy in determining the analyte level during the usage time.

[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 the glucose concentration.

[0040] The analyte sensor that needs to be calibrated in the examples of the present disclosure can be an analyte sensor that undergoes sensitivity attenuation. The analyte sensor that does not need to be calibrated can be an analyte sensor that does not undergo sensitivity attenuation.

[0041] Taking the analyte as glucose in interstitial fluid as an example below, the examples of the present disclosure will be described in conjunction with the accompanying drawings, and such description does not limit the scope of the present disclosure.

[0042] Figure 1 It is a diagram showing the application scenario of the analyte monitoring system 1 involved in the examples 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 Figure 1 shown, the analyte sensor 10 may be implanted subcutaneously in a target object or mounted on the skin surface. The analyte sensor 10 may be configured to collect analyte signals. The processing module 20 may be configured to receive the analyte signals and determine the analyte level. The present disclosure is not limited to Figure 1 the setting position of the processing module 20 shown. For example, the processing module 20 may also be arranged on the skin surface of the target object.

[0044] Figure 2 FIG. is a system block diagram of the analyte monitoring system 1 involved in the examples 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 target object to react with an analyte in subcutaneous tissue fluid and generate continuous signals 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 can react with the analyte and form a circuit, so as to generate continuous signals 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 may 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 may 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 signals can be made more accurate.

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

[0048] The target parameters involved in the present disclosure may be parameters related to sensitivity attenuation. For example, the target parameter may be a sensitivity coefficient. The target parameter may also be other parameters for determining the analyte level.

[0049] When the analyte sensor 10 is in a sensitivity attenuation state, the analyte monitoring system 1 can determine the analyte level by using the calibration method involved in the present disclosure. Specifically, the calibration time can be set during the gap of the working time. During the working time, 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 calibration 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 by using the calibration method involved in the present disclosure based on the analyte signal and the response signal. Thus, the accuracy of determining the analyte level by the analyte sensor 10 with sensitivity attenuation can be improved.

[0050] As Figure 2 shown, the analyte monitoring system 1 can include an analyte sensor 10 and a processing module 20. The analyte sensor 10 can include at least two electrodes 100. The analyte sensor 10 can be configured to collect the analyte signal, and apply the input signal to at least two electrodes 100 of the analyte sensor 10 and collect the response signal corresponding to the input signal during the calibration time. The processing module 20 can be configured to receive the analyte signal and the response signal and determine the analyte level by using the calibration method involved in the present disclosure.

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

[0052] In some examples, the analyte sensor 10 can further include a signal source 300. The signal source 300 can be configured to generate an input signal. The generated input signal can be applied to at least two electrodes 100 of the analyte sensor 10. Preferably, when the analyte sensor 10 includes three electrodes 100, it can be applied to the working electrode and the reference electrode. The input signal can include a first input signal, a second input signal, and a third input signal. The signal waveform of the input signal can include one or a combination of a pulse wave, a step wave, a sawtooth wave, a triangular wave, a sine wave, and a rectangular wave. The second input signal can have the same signal waveform as the first input signal. The third input signal can 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 continuous signals related to the analyte level generated by at least two electrodes 100 during the working time to obtain discrete signals related to the analyte level. Specifically, the first sampling module 30 may include an analog-to-digital converter to sample 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, and the second sampling module 40 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, the first sampling module 30 sampled during the working time may be used, or another second sampling module 40 may be used.

[0055] The analyte monitoring system 1 involved in the present disclosure may include at least two loops. That is, it includes at least a working loop formed by a working electrode and a counter electrode and a measurement loop formed by a working electrode and a reference electrode. The analyte signal acquisition involved in the present disclosure may be to acquire the current signal flowing through the working electrode during the working time. The response signal acquisition involved in the present disclosure may be to acquire the current signal flowing through the working electrode corresponding to the input signal. For example, a voltage as a first input signal is applied to the working electrode and the reference electrode, the enzyme disposed on the working electrode reacts with the analyte and generates a current, and the current is acquired as the response signal at the working electrode. The current as the response signal may be related to the sensitivity attenuation of the analyte sensor 10. The current as the response signal may also be related to the analyte level. The acquisition of the analyte signal and the acquisition 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 target parameters. In some examples, the relevant data for correcting target parameters 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.

[0057] Figure 3 is a flowchart showing a method for correcting the sensitivity attenuation of the analyte sensor 10 according to an example of the present disclosure.

[0058] The correction method involved in the present disclosure may be applied to the above-mentioned analyte monitoring system 1. Further, the correction method involved in the present disclosure may be applied to the above-mentioned processing module 20, that is, the processing module 20 may use the correction method involved in the present disclosure to determine the analyte level.

[0059] Reference Figure 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 during the 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 the reference signal curve (step S200), correcting a target parameter related to sensitivity attenuation of the analyte sensor 10 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 to refer Figure 3 , in some examples, in step S100, the first input signal may be applied to at least two electrodes 100 of the analyte sensor 10. In some examples, the signal waveform of the first input signal may include one or more combinations of a pulse wave, a step wave, a sawtooth wave, a triangular wave, a sine wave, a stepped wave, and a rectangular wave. The combinations involved in the present disclosure refer to the superposition of multiple signal waveforms. Specifically, it may be that multiple signal waveforms are aligned and superimposed in a period or staggered and superimposed in a period. For example, when two pulse waves are aligned and superimposed in a period, a signal waveform with a pulse wave having a higher pulse amplitude can be obtained, and when two pulse waves are staggered and superimposed in a period, a signal waveform with two pulse waves can be obtained. In some examples, the first input signal may be generated by a signal source 300.

[0061] Figure 4A is a schematic diagram showing the first embodiment of the signal waveform of the first input signal involved in the example of the present disclosure. Figure 4B is a schematic diagram showing the second embodiment of the signal waveform of the first input signal involved in the example of the present disclosure. Figure 4C is a schematic diagram showing the third embodiment of the signal waveform of the first input signal involved in the example of the present disclosure.

[0062] Figure 4D is a schematic diagram showing the 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 showing the 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 one or more combinations of a pulse wave, a step wave, a sawtooth wave, a triangular wave, a sine wave, a stepped wave, and a rectangular wave. For this reason, the present disclosure also provides some examples of the signal waveform of the first input signal.

[0064] SeeFigure 4A In the first embodiment shown, 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. Additionally, after the application of the first input signal ends, it may return to a low level or other level that does not affect the analyte monitoring system 1 being in the operating mode.

[0065] See Figure 4B In the second embodiment shown, the signal waveform of the first input signal may be a pulse wave. As Figure 4B , multiple cycles of pulse waves may be applied within the calibration time. For example, 2, 3, 4, 5, 6, 7, 8, 9, or 10 cycles of pulse waves 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 a signal waveform 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. Furthermore, it can enable the calibration coefficient used during calibration to contain more information about the electrode 100, thereby further improving the accuracy of determining the analyte level. For this purpose, the present disclosure also provides some examples of stepped signal waveforms. It should be noted that the present disclosure is not limited to Figure 4C , Figure 4D and Figure 4E the signal waveforms shown, 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] See Figure 4C In the third embodiment shown, 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. 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 different degrees of charge transfer in the electrode 100, and thus the kinetic characteristics of the electrochemical reaction occurring in the electrode 100 under pulse waves with different pulse amplitudes can be obtained. Thereby, it can enable the obtained calibration coefficient to contain information related to the kinetic characteristics of the electrode 100 under pulse waves with different pulse amplitudes. Calibrating based on the calibration coefficient containing 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] See Figure 4DIn the fourth embodiment shown, the signal waveform of the first input signal may include a combination of at least two pulse waves, and form a signal waveform that is a combination of pulse waves and a stepped wave with the same pulse amplitude in chronological order, and the combination of the pulse wave and the stepped wave forms a stepped signal waveform. In this case, the stepped 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, and correcting 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 ability and transient response ability of the analyte sensor 10, thereby further improving the accuracy of determining the analyte level.

[0069] See Figure 4E In the fifth embodiment shown, the signal waveform of the first input signal may include a combination of at least two pulse waves, and form a signal waveform of pulse waves with different pulse amplitudes in chronological order. At the same time, the directions of two adjacent pulse waves are different, that is, the positive and negative directions alternate, and the pulse waves with different pulse amplitudes form a stepped signal waveform. In this case, the different directions of the pulse waves can obtain information related to the reverse reaction of the electrode 100. Thus, the obtained correction coefficient can include information related to the reverse reaction of the electrode 100, and correcting based on the correction coefficient including information related to the reverse reaction of the electrode 100 can reduce the influence of the reverse reaction on the analyte sensor 10 to determine the analyte level, thereby further improving the accuracy of determining the analyte level.

[0070] Figure 5 is a schematic diagram showing the acquisition of the response signal involved in the example of the present disclosure.

[0071] In some examples, the response signal corresponding to the first input signal can be acquired. As Figure 5 shown, when acquiring the response signal, the response signal and the corresponding acquisition time can be obtained. In this case, response parameters related to sensitivity attenuation can be obtained during the use of the analyte sensor 10, which is convenient for correcting the sensitivity attenuation during use. In some examples, the acquired response signal can be discrete data. Thus, it is convenient to digitally process 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 Figure 5The discrete data obtained by the first sampling module 30 or the second sampling module 40 shown. 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, through fitting, the response signal can be smoothed, thereby reducing data fluctuations caused by acquisition errors or other factors; in addition, through fitting, the response signal can be interpolated 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 a rising segment and / or a falling segment. For example, Figure 5 The illustrated acquired response signal can be fitted to obtain a response signal curve including a falling segment.

[0074] In some examples, the case of a straight line may not be excluded for the response signal curve. 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] Figure 6 is a flowchart showing the application of the first input signal and the acquisition of the corresponding response signal involved in the examples of the present disclosure.

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

[0077] Refer to Figure 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), in response to the number of acquisitions being equal to the preset number of acquisitions, obtaining an average response signal by averaging the response signals obtained from multiple acquisitions (step S102), and obtaining a response signal curve based on the average response signal (step S103).

[0078] Continue to refer to Figure 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 calibration time, and the number of times the first input signal is applied may be the preset number of acquisitions. Additionally, between multiple applications, the first input signal may return to a low level or other level that can restore the response signal to the steady state when the first input signal is not applied. The time required between multiple applications may be sufficient to restore the response signal to the steady state when the first input signal is not applied. In this case, the interference between multiple response signals generated by applying the input signal multiple times can be reduced, and thus the accuracy of obtaining the response parameters can be improved. The number of times the first input signal is applied may be related to the preset number of acquisitions.

[0079] Continue to refer to Figure 6 , in some examples, in step S102, in response to the number of acquisitions being equal to the preset number of acquisitions, the average response signal may be obtained by averaging the response signals obtained from multiple acquisitions. Specifically, the first input signal is applied and the response signals are acquired for the 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, which is also equal to the preset number of acquisitions. In this case, by acquiring the response signals multiple times and averaging them to obtain the average response signal, the accuracy of the acquired response signals can be improved.

[0080] Continue to refer to Figure 6 , in some examples, in step S103, the response signal curve may be obtained based on the average response signal. In this case, by obtaining the response signal curve from the average response signal, the accuracy of at least one response parameter of the response signal obtained based on the response signal curve can be improved, and thus the accuracy of calibration based on the response parameters can be improved.

[0081] Return to refer to Figure 3 , in some examples, in step S200, the calibration 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. Additionally, the reference signal curve may represent the response signal curve of the response signal corresponding to the input signal when the analyte sensor 10 has not undergone sensitivity attenuation. In this case, by using the reference signal curve corresponding to the non-sensitivity-attenuated state as a standard, a calibration coefficient that can make the response parameters close to the reference parameters can be obtained. Additionally, by using the reference signal curve corresponding to the state when the analyte sensor 10 has not undergone sensitivity attenuation as a standard, compared with using the signal curve of the analyte sensor 10 in other states, the influence of uncertain factors on the accuracy of the standard can be reduced. Additionally, different from calibrating the analyte sensor 10 with fingertip blood as a standard, using the reference signal curve corresponding to the non-sensitivity-attenuated state as a standard can improve the convenience of determining the analyte level.

[0082] Continue to refer to Figure 3 In some examples, in step S200, at least one response parameter of the response signal can be obtained based on the response signal curve determined by the response signal. The types of parameters of the response parameter can include one or a combination of more of a peak value, an area under the curve, and a curve slope. 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 further, the maximum response ability of the analyte sensor 10 to the input signal can be obtained, so that the attenuation degree of the sensitivity 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 further, the charge accumulation ability of the analyte sensor 10 can be obtained, so that the attenuation degree of the sensitivity can be obtained; in addition, when the parameter type is the curve slope, it can reflect the speed of decrease or increase of the response signal, and further, the response speed of the analyte sensor 10 can be obtained, so that the attenuation degree of the sensitivity can be obtained.

[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 curve slope 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 Figure 5 the response signal collected therein. In some examples, the curve slope in the parameter type can be the median of the slope of the target segment, the slope at the half of the peak value (i.e., the half-peak value) of the response signal curve in the target segment, or the slope corresponding to the characteristic point on the target segment.

[0084] In some examples, the response 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. The response signal curve in the form of a straight line can be obtained by performing coordinate transformation on the response signal curve in the form of a curve (described later). In this case, the slope can be directly obtained through the straight line, without considering the problem of how to select the slope when the response signal curve is a curve, so that the calibration method can be simplified.

[0085] In some examples, a reference signal curve can be obtained based on the response signal corresponding to the applied input signal. Specifically, an input signal can be applied to the analyte sensor 10 that has not undergone sensitivity attenuation, and the response signal is collected and at least one reference parameter of the response signal is 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 to obtain the response signal to obtain the reference signal curve, the reference signal curve obtained before calibration can be made close to the true value of the analyte sensor 10 that has not undergone sensitivity attenuation.

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

[0087] In some examples, the second input signal can be generated by the signal source 300 when the analyte monitoring system 1 is used. In some examples, the second input signal can be generated by an external signal source before the analyte monitoring system 1 is used. In some examples, the external signal source can be a function signal generator. In some examples, the reference signal corresponding to the second input signal can be collected. 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 saved in the storage module 50. In this case, by obtaining and saving the reference signal curve by applying the second input signal, the analyte monitoring system 1 can determine the calibration coefficient based on the saved reference signal curve during the calibration time.

[0089] In some examples, the applied input signal can be the third input signal. In some examples, a reference signal curve can be obtained based on the third input signal before calibration. The third input signal can be configured to be applied to the sample sensor that does not require calibration outside the calibration time and applied to the sample sensor that requires calibration at different time periods. The sample sensor can be the sensor used when obtaining the target relationship. The sample sensor can simulate the situations where the analyte sensor 10 has different degrees of sensitivity attenuation and the situation where there is no sensitivity attenuation. The signal waveform of the third input signal can be the same as that of the first input signal. The third input signal can be generated by an external signal source. In some examples, the reference signal curve obtained based on the third input signal can be saved in the storage module 50. In this case, the calibration coefficient can be determined based on the saved reference signal curve of the sample sensor during the calibration time without applying an input signal to the analyte sensor 10 before the calibration time, thereby reducing the acquisition cost of the reference signal curve and maintaining the service life of the analyte sensor 10. Thus, the accuracy of the analyte sensor 10 in determining the analyte level can be further improved.

[0090] In some examples, the reference signal corresponding to the third input signal can be collected. Fitting can 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, a plurality of attenuation signal curves can be obtained based on the third input signal at different time periods. The different time periods can be respective time periods corresponding to different degrees of sensitivity attenuation of the sample sensor.

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

[0093] Continuing to refer to Figure 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, by obtaining the reference signal curve through the preset formula, it is possible to quickly obtain the reference signal curve before calibration and obtain an ideal reference signal curve without sensitivity attenuation, that is, it is possible to 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]

[0095] where I is the reference signal curve, A is the proportionality coefficient, and t is the time. Thus, a reference parameter can be obtained based on the proportionality coefficient in the preset formula, and then a calibration coefficient can be obtained based on the reference parameter.

[0096] Continuing to refer to Figure 3 , 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 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 the preset formula can be subjected to a coordinate transformation to transform the reference signal curve from a curve form to a straight line form, and the curve slope in at least one reference parameter can be A.

[0097] In some examples, the parameter types of the reference parameters and the parameter types of the response parameters can be the same. For example, if the parameter types of the response parameters include peaks, the parameter types of the reference parameters can also include peaks. In this case, it is possible to facilitate a direct comparison of the response parameters and the reference parameters, and then obtain the difference between the response signal and the reference signal.

[0098] Continuing to refer to 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 the stored reference signal curve during calibration. Specifically, the difference between the response signal and the reference signal curve can 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 the correction coefficient can be obtained based on the difference. Additionally, the stored reference signal curve can be a reference signal curve obtained based on the above-mentioned second input signal, third input signal, or preset formula.

[0099] In some examples, a correction coefficient can be obtained based on the difference between the response signal and the reference signal curve. In some examples, the difference between the response signal and the reference signal curve can be the difference between the response parameter and the reference parameter. For example, the difference or ratio between the response parameter and the reference parameter, etc. In some examples, a correction coefficient can be obtained based on the difference or ratio between the response parameter and the reference parameter, etc. For example, the ratio between the response parameter and the reference parameter can be used as the correction coefficient.

[0100] In some other examples, different correction coefficients can be used to correct 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 corrected 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 target parameter is corrected by multiplying the different correction coefficients by the target parameter. After the target parameter of the analyte sensor 10 is corrected, the corresponding analyte level is also corrected. Taking the analyte level corresponding to the stored reference signal curve as the standard, the closeness between the corrected analyte level and the analyte level corresponding to the stored reference signal curve is compared. The correction coefficient corresponding to the corrected analyte level that is closest is obtained.

[0101] In some examples, the response signal and the stored reference signal curve can be aligned in time before analyzing to obtain the difference. For example, aligning at the start time point of the pulse wave. In this case, the accuracy of analyzing the difference between the response signal and the stored reference signal curve can be improved.

[0102] Continue to refer to 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 the target relationship during calibration. Additionally, the target relationship can represent the 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.

[0103] In some examples, the target relationship can be a functional relationship. Further, the target relationship can be a linear relationship. When the target relationship is a linear relationship, the target relationship can be represented by an adjustment coefficient. The adjustment coefficient can 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 usage amount in the storage module 50 when storing the target relationship can be reduced.

[0104] Specifically, the response parameter can be multiplied by the adjustment coefficient to obtain the correction coefficient. For example, when the response parameter is the curve slope, the curve slope can be multiplied by the adjustment coefficient to obtain the correction coefficient.

[0105] In some examples, the target relationship can be represented by a look-up table. The response parameter and the correction coefficient can be stored in the look-up table. The look-up table can represent the corresponding relationship between the response parameter and the correction coefficient. In this case, it is convenient to retrieve the response parameter to quickly obtain the corresponding correction coefficient.

[0106] As described above, the reference signal curve and multiple attenuation signal curves can be obtained based on the third input signal. In some examples, the 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.

[0107] 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 through the straight line without considering 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 different degrees of sensitivity attenuation of the sample sensor can be obtained.

[0108] In some examples, different adjustment parameters can be used to multiply the response parameter to obtain different correction coefficients to obtain the target relationship. The target parameter of the sample sensor is corrected using different correction coefficients. After the target parameter of the sample sensor is corrected, the corresponding analyte level is also corrected. Taking the analyte level corresponding to the reference signal curve as a standard, the proximity between the corrected analyte level and the analyte level corresponding to the reference signal curve is compared. The adjustment parameter corresponding to the corrected analyte level that is closest is used as the target relationship.

[0109] In some examples, different correction factors can also be used to correct the sample sensor to obtain the target relationship. The target parameters of the sample sensor are corrected using different correction factors. After the target parameters of the sample sensor are corrected, the corresponding analyte levels are also corrected. For example, when the target parameter is the sensitivity coefficient, after the sensitivity coefficient is corrected, the corresponding analyte levels calculated based on the target parameter are also corrected. Taking the analyte level corresponding to the reference signal curve as the standard, the proximity between the corrected analyte level and the analyte level corresponding to the reference signal curve is compared. The correction factor corresponding to the corrected analyte level that is closest and the initial response parameters are stored in a look-up table. The look-up table is taken as the target relationship.

[0110] In other examples, the target relationship can be obtained through machine learning. In some examples, 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 factor.

[0111] In some examples, the target relationship can be obtained through at least one of in vitro experiments and human wear experiments. The in vitro experiment can be to measure the relevant data of the analyte sensor 10 in a glucose solution simulating interstitial fluid. The human wear experiment can be to measure the relevant data of the analyte sensor 10 when implanted in the interstitial fluid of the human body.

[0112] In some examples, the target relationship can be saved. In some examples, the target relationship can be saved in the storage module 50.

[0113] Continuing to refer to Figure 3 , in some examples, in step S200, correction can be performed in response to the analyte sensor 10 being in a sensitivity attenuation state. Specifically, it can be determined that the analyte sensor 10 is in a sensitivity attenuation state based on the difference between at least one response parameter of the response signal and at least one reference parameter of the reference signal curve. Further, correction can be performed in response to the analyte sensor 10 being in a sensitivity attenuation state. In this case, it is possible to detect that the analyte sensor 10 is in a sensitivity attenuation state and perform correction, which can enable the analyte monitoring system 1 to maintain the accuracy of determining the analyte level during the use of the target object.

[0114] Continuing to refer to Figure 3 , in some examples, in step S200, the difference between at least one response parameter and at least one reference parameter can be determined. Further, it can be determined that the analyte sensor 10 is in a sensitivity attenuation state in response to the difference being greater than a first threshold. The first threshold can indicate that the analyte sensor 10 is in a sensitivity attenuation state.

[0115] 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. For this purpose, the present disclosure also provides an example of determining a response parameter or a reference parameter in the form of a straight line.

[0116] In some examples, a coordinate transformation may be performed on the response signal curve, the reference signal curve, or the attenuation signal curve. The coordinate transformation may be to transform the time of the above curve so that the above curve is transformed 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 curve satisfies the relationship that the signal is proportional to the reciprocal of the arithmetic square root of time. The time of the above curve can be transformed from t to 1 / sqrt(t), that is, from t to the reciprocal of the arithmetic square root of t. When the above curve satisfies the relationship that the signal is proportional to the logarithm of time, the time of the above curve can be transformed from t to ln(t). In this case, through the coordinate transformation, the above curve can be transformed from a curve form to a straight line form, and then the straight line can be directly processed, such as finding the slope, without considering the problem of how to select the slope of the characteristic points when the above curve is in the curve form, thereby simplifying the calibration method. It should be noted that the present disclosure is not limited to the above examples, and other coordinate transformations that can transform the above 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 two coordinate transformations.

[0117] 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 response signal curve, the reference signal curve, or the attenuation signal curve that has undergone coordinate transformation. The curve slope may be used as the response parameter or the reference parameter of the response signal curve, the reference signal curve, or the 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 attenuated signal curve after coordinate transformation is transformed from a straight line form to a curve form. The slope of the attenuated signal curve after coordinate transformation can be used as the curve slope of the attenuated signal curve. The curve slope of the attenuated signal curve can be used as the response parameter of the attenuated signal curve.

[0118] Figure 7A It is a flowchart showing the first implementation manner of obtaining a calibration coefficient involved in the example of the present disclosure.

[0119] As described above, in step S200, a calibration 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.

[0120] Reference Figure 7A, in some examples, the first implementation 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 response signal curve after coordinate transformation (step S202), and obtaining the correction coefficient based on at least one response parameter of the response signal and the target relationship (step S203).

[0121] Continue to refer to Figure 7A , in some examples, in step S201, coordinate transformation can be performed on the response signal curve. The response signal curve can be transformed from a curve form to a straight line form through coordinate transformation. In this case, for the situation where the input signal has certain specific signal waveforms, such as when the input signal includes a step wave or a pulse wave, through this coordinate transformation, the response signal curve can be transformed into a straight line, 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 characteristic points when the response signal curve is a curve, thereby simplifying the correction method.

[0122] Continue to refer to Figure 7A , in some examples, in step S202, at least one response parameter of the response signal can be obtained based on the response signal curve after coordinate transformation. For example, when the input signal has the characteristics of a pulse wave or a step wave signal waveform, the curve slope corresponding to the response signal curve after coordinate transformation can be used as at least one response parameter of the response signal.

[0123] Continue to refer to Figure 7A , in some examples, in step S203, the correction coefficient can 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 look-up table, the correction coefficient corresponding to the response parameter can be retrieved in the look-up table.

[0124] Continue to refer to Figure 7A, in some examples, in step S203, the target relationship can be determined and saved based on the reference signal curve and the attenuation signal curve corresponding to the third input signal before calibration. That is, the reference signal curve can be obtained based on the third input signal before calibration. Multiple attenuation signal curves are obtained based on the third input signal in different time periods. The 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 the target relationship is saved. The calibration coefficient is determined based on at least one response parameter of the response signal and the target relationship during calibration. The target relationship represents the relationship between the response parameter and the calibration 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 saved target relationship, compared with saving the reference signal curve, the usage amount in the storage module 50 can be reduced; in addition, the calibration coefficient is obtained based on the target relationship during calibration, and the calibration coefficient is obtained through simple calculation (such as multiplying the response parameter by an adjustment coefficient) or by retrieving a look-up table, which can simplify the processing steps during calibration, and thus can improve the calibration speed, and thereby can improve the real-time performance of the calibration method.

[0125] Figure 7B FIG. is a flowchart showing a second embodiment of obtaining a calibration coefficient according to an example of the present disclosure.

[0126] Reference Figure 7B , in some examples, the second embodiment of obtaining a calibration coefficient may include: obtaining at least one response parameter of the response signal based on the response signal curve (step S211), and obtaining a calibration coefficient based on at least one response parameter of the response signal and the stored reference signal curve (step S212).

[0127] Continue to refer to Figure 7B , in some examples, in step S211, the types of parameters of the response parameter may include one or a combination of peak value, area under the curve, and curve slope. When the response signal curve is in a curve form, obtaining the curve slope of the response signal may be the median of the slope in the descending or ascending section of the curve, the slope corresponding to half of the peak value, or the slope corresponding to other characteristic points on the curve (such as the point with the largest slope on the curve).

[0128] Continue to refer to Figure 7B , in some examples, in step S212, the response signal can be aligned with the stored reference signal curve in time. For example, aligning at the start time point of the pulse wave, and then analyzing at least one response parameter of the response signal and at least one reference parameter of the stored reference signal curve to obtain the difference between the response signal and the reference signal curve, and obtaining the calibration coefficient based on the difference. For example, the method of machine learning can be used to analyze the difference.

[0129] Continue 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 calibration. That is, the reference signal curve can be obtained based on the second input signal before calibration and the reference signal curve can be saved. 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 during calibration. In this case, by performing calibration based on the saved reference signal curve, the integrity of the standard used for calibration can be maintained. Compared with converting the reference signal curve into other information, information loss can be reduced, and thus the accuracy of determining the analyte level can be improved. In addition, saving the reference signal curve before calibration can simplify the preparation steps before calibration without the need for additional processing. In addition, when the reference signal curve is relatively 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 calibration can improve the applicability of the calibration method.

[0130] Continue to refer to Figure 3 , in some examples, in step S300, the target parameter related to the sensitivity attenuation of the analyte sensor 10 can be calibrated based on the calibration coefficient. The target parameter can be related to the conversion relationship between the analyte signal and the analyte level. In some examples, when the calibration coefficient is related to the ratio of the response parameter to the reference parameter, the calibration coefficient can be multiplied or divided by the target parameter for calibration. In some examples, when the calibration coefficient is related to the difference between the response parameter and the reference parameter, the calibration coefficient can be a relative error, and the target parameter can be increased or decreased by the change amount corresponding to the relative error for calibration. The change amount 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.

[0131] In addition, the conversion relationship can be determined by the analyte sensor 10 itself. In some examples, the conversion relationship can be related to the analyte signal and the sensitivity (for example, the analyte level can be obtained by dividing the analyte signal by the sensitivity of the analyte sensor 10). The calibrated target parameter can be used to calibrate the analyte signal or the sensitivity. Specifically, the target parameter can be a sensitivity coefficient or a current compensation coefficient.

[0132] Continue to refer to Figure 3 , in some examples, in step S400, the sensitivity of the analyte sensor 10 can be calibrated based on the sensitivity coefficient or the current value of the analyte sensor 10 can be calibrated based on the current compensation coefficient. In some examples, the analyte level can be determined based on the analyte signal collected by the analyte sensor 10 and the calibrated target parameter.

[0133] Continue to refer to Figure 3, in some examples, in step S400, the analyte level can be determined based on the analyte signal collected 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 then determining the analyte level based on the corrected target parameter, the analyte sensor 10 with sensitivity attenuation can obtain the analyte level without sensitivity attenuation. Thus, the accuracy of determining the analyte level by the analyte sensor 10 with sensitivity attenuation can be improved.

[0134] Continue to refer to Figure 3 , in some examples, in step S400, in some examples, when the target parameter is the 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 collected by the analyte sensor 10 and the corrected sensitivity. In this case, the sensitivity can be indirectly corrected by correcting the sensitivity coefficient.

[0135] In some examples, when the target parameter is the current compensation coefficient, the current value of the 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 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.

[0136] One or more steps of the calibration method involved in the present disclosure can be performed during the calibration time, such as applying the first input signal involved in step S100. Some parameters required for one or more steps of the calibration method involved in the present disclosure can be obtained outside the calibration time, such as the working time during the use of the target object or the factory production time or assembly time before the use of the target object, etc. For example, at least one reference parameter, look-up table or adjustment coefficient of the reference signal curve involved in step S200 can be obtained outside the calibration time.

[0137] At least one reference parameter of the reference signal curve involved in the present disclosure can be obtained by the analyte sensor 10 without sensitivity attenuation. In addition, it can also be obtained after calibrating the analyte sensor 10 when the state of the target object is stable, such as when the target object is fasting or when the body of the target object is static at night.

[0138] The analyte sensor 10 without sensitivity attenuation involved in the present disclosure may be an analyte sensor 10 not in a state of sensitivity attenuation, such as the analyte sensor 10 during the factory production time or assembly time before the target object uses the analyte monitoring system 1, the analyte sensor 10 with the difference between the response parameter and the reference parameter less than the first threshold, the analyte sensor 10 before or after a period of use by the target object, and the calibrated analyte sensor 10.

[0139] The calibration frequency of the calibration method involved in the present disclosure may be once a day, twice a day, once every two days, once a week, or calibration is performed in response to the analyte sensor 10 being in a state of sensitivity attenuation.

[0140] The kinetic characteristics involved in the present disclosure include information related to sensitivity.

[0141] The present disclosure also relates to a computer-readable storage medium that may store at least one instruction, and when the at least one instruction is executed by a processor, one or more steps in the above-mentioned calibration method are implemented, or the above-mentioned analyte monitoring system 1 is implemented.

[0142] The present disclosure also relates to an electronic device, which may include a processor and a memory, and 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.

[0143] Although the present disclosure has been specifically described above in combination with the drawings and embodiments, it can be understood that the above description does not limit the present disclosure in any form. Those skilled in the art can make deformations and changes to the present disclosure as needed without departing from the essence and scope of the present disclosure, and these deformations and changes 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 a first input signal to at least two electrodes of the analyte sensor at least once during a calibration time, and collecting a 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 a reference signal curve; Correcting a target parameter of the analyte sensor related to the sensitivity attenuation based on the calibration coefficient; Determining the analyte level based on a 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 a 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, the second input signal having the same signal waveform as the first input signal; and / or Obtaining the reference signal curve based on a 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, the target relationship representing the relationship between the response parameter and the calibration coefficient, the third input signal having the same signal waveform as 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 a 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: where 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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