CN113848313A - Method and system for calibrating sensing data of analyte sensing component - Google Patents
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Abstract
The present disclosure relates to a method and system for calibrating sensing data of an analyte sensing component, wherein the method comprises, the analyte sensing component using different barcodes to bind the analyte sensing component; performing function test on the analyte sensing assembly to obtain sensing data of the analyte sensing assembly, determining calibration information according to comparison between the sensing data of the analyte sensing assembly and a preset parameter range, and associating the calibration information with a bar code corresponding to the analyte sensor; identifying the barcode and obtaining calibration information from the barcode prior to using the analyte sensing component; and calibrating the sensing data of the analyte sensing component based on the calibration information. The system comprises a binding belt device, a testing device, an identification device and a calibration device. According to the present disclosure, a method and a system for performing effective calibration before use of a sensing assembly by using an in vitro calibration method and providing a better user experience for a user can be provided.
Description
Technical Field
The present disclosure relates generally to a calibration method and system, and more particularly to a calibration method and system for an analyte sensing assembly based on sensing data.
Background
Diabetes is a common disease of the global nature. According to the statistical data of the international diabetes union, the number of the worldwide ill people in 2017 is about 4.25 hundred million, and is predicted to reach 6.29 hundred million by 2045. China is the country with the most diabetes in the world, the number of diabetes in 2017 is 1.14 hundred million, and about 1.5 hundred million is expected in 2045 years. Monitoring blood glucose is an indispensable daily event for diabetics. Currently, a commonly used blood glucose test device is a blood glucose meter, but the blood glucose test device can only detect the blood glucose value of a patient at a single time point, cannot continuously monitor the blood glucose level, and has great limitation. In addition, fingertip blood glucose collection often causes physical and even psychological harm to the diabetic. Therefore, implantable continuous blood glucose monitors (CGM) have been developed, and the rapid development of CGM brings advantages of comfort, flexibility, convenience, etc. to the monitoring of diabetes.
If the measurement data of blood sugar is inaccurate, the risk of extremely high medication decision is brought to a patient, so that the performance required by a continuous blood sugar monitor as an implanted sensor is required to have a considerable or even higher requirement compared with the traditional sampling detection. In recent years, with the continuous progress of biosensing technology, continuous blood glucose monitors are becoming mature in terms of biocompatibility and biofilm technology, and especially, the performance of the continuous blood glucose monitors is approaching to meet the requirements of being equivalent to or even higher than that of traditional sampling detection. Due to the difference of manufacturing process and sensing data processing mode, in order to ensure the performance of the sensor of the continuous blood glucose monitor, namely, the monitored blood glucose data is accurate, most of the prior art at present adopts the mode of performing blood sampling calibration between fingers for many times before the sensor of the continuous blood glucose monitor is implanted into the body of a patient, and the patient still lacks comfort, convenience and better user experience.
Disclosure of Invention
The present invention is made in view of the above-mentioned state of the art, and an object of the present invention is to provide a method and a system for calibrating sensor data of an analyte sensing element, which are used for calibrating sensor data of an analyte sensing element by using a barcode before using the analyte sensing element, and can solve the problems of the prior art that a fingertip blood sampling calibration method lacks comfort and convenience for a patient and has better user experience.
A first aspect of the present disclosure provides a method of calibrating sensing data of an analyte sensing element, being a method for calibrating sensing data of the analyte sensing element with a barcode prior to use of the analyte sensing element, comprising: preparing a plurality of the analyte sensing assemblies and binding each of the analyte sensing assemblies using the barcodes; performing function test on each analyte sensing assembly to obtain sensing data of each analyte sensing assembly, determining calibration information according to comparison between the sensing data of the analyte sensing assembly and a preset parameter range, and associating the calibration information with a bar code corresponding to the analyte sensor; identifying the barcode and obtaining the calibration information from the barcode prior to using the analyte sensing component; and calibrating the sensing data of the analyte sensing component based on the calibration information.
Under the condition, the method can solve the problems that a fingertip blood sampling calibration mode in the prior art is lack of comfort and convenience for a patient and better user experience.
Optionally, the sensing data is a concentration profile, which is a functional test of each analyte sensing element using a plurality of different analyte concentrations and obtaining a concentration profile of each analyte sensing element. In this case, the analyte concentration data can be presented more intuitively in the form of a curve, thereby enabling analysis of the change in analyte concentration to be facilitated by analysis of the slope or curvature of the concentration change curve.
According to the method of the present disclosure, optionally, the information of the barcode is stored in a server, the analyte sensing component may be packaged, and the information of the barcode may be downloaded from the server and displayed on the package. In this case, the information of the barcode can be stored in the server after being associated with the sensing data, can be pre-processed in the server, can be downloaded and printed with the associated information or data before shipment and displayed on the packaging, thereby enabling pre-factory and post-factory information tracking of the analyte sensing assembly.
In accordance with methods contemplated by the present disclosure, optionally, the sensory data includes at least one of analyte concentration, rate of change of analyte concentration, time of analyte detection, sensor sensitivity, and rate of change of sensitivity. In this case, when the analyte sensing element needs to be calibrated, the calibration algorithm or model can determine the performance of the analyte sensing element based on the analyte concentration, the rate of change of analyte concentration, the analyte detection time, the sensor sensitivity, and the rate of change of sensitivity and perform the corresponding analysis and calibration.
According to the method of the present disclosure, the analyte sensing component may optionally be bound by using the location of the lot and tool as information for the barcode. In this case, tracking of the pre-factory information of the analyte sensing assembly can be accomplished by utilizing the barcode.
According to the method of the present disclosure, optionally, a compensation model is generated based on the calibration information, and the sensing data of the analyte sensing component can be calibrated by the compensation model. In this case, the calibration information is obtained from the factory-front sensing data obtained by using the barcode, and the analyte sensing assembly can be calibrated by using the preset compensation model before being used, that is, ex-vivo calibration after leaving the factory, so that discomfort or inconvenience of the conventional fingertip blood sampling calibration method is reduced, and better user experience is obtained.
According to the method of the present disclosure, optionally, a terminal device with a display function is used to match the analyte sensing component, and the calibrated sensing data can be displayed on the terminal device. In this case, when the analyte sensing component is used, the terminal device with the display function can better and more intuitively display the sensing data to a patient or other people needing to obtain accurate analyte sensing data, namely, more conveniently acquire information.
According to the method to which the present disclosure relates, optionally, the calibration information comprises at least one of a calibration behavior, a calibration factor and a calibration coefficient. In this case, the calibration behavior can determine whether the sensing data needs to be calibrated and transmit the determination result to the next calibration process, the calibration factor can make the calibration information more complete, for example, the calibration factor can be a simulation factor, a test time period, a test mode, and the like of the test equipment before the factory, and the calibration factor can make the calibration information obtain a corresponding compensation factor, that is, a degree of compensation or a mathematical mode, when the compensation model is generated.
A second aspect of the present disclosure provides a system for calibrating sensing data of an analyte sensing element using a barcode prior to using the analyte sensing element, which may include: a binding device that can bind each of the plurality of analyte sensing components using the barcode; the test device can perform function test on each analyte sensing assembly to obtain sensing data of each analyte sensing assembly, can determine calibration information according to comparison between the sensing data of the analyte sensing assembly and a preset parameter range, and can associate the calibration information with a bar code corresponding to the analyte sensor; an identification device that can identify the barcode and obtain the calibration information from the barcode prior to use of the analyte sensing component; a calibration device that can calibrate the sensing data of the analyte sensing component based on the calibration information.
Under this condition, solve among the prior art fingertip blood sampling calibration mode and lack the problem of travelling comfort, convenience and better user experience to the patient through this system.
According to the calibration system of the present disclosure, optionally, the calibration system further comprises a communication device for information transfer and a user display device for display. In this case, the binding device, the testing device, and the identification device in the system can perform data communication via the communication device, such as obtaining information of the barcode, binding information of the barcode, sensing data, information associated with the barcode and the sensing data, calibration information of the analyte sensing component based on the sensing data, and the like, and the user display device can better and more intuitively display the information to a patient or other people who need to obtain sensing data of an accurate analyte sensing component, that is, more conveniently obtain the information.
According to the calibration system related by the present disclosure, optionally, a server for data storage is further included, and the server may perform data communication with the binding device, the testing device, and the identification device through the communication device. In this case, the binding device, the testing device and the identification device in the system can mutually transmit data and be processed and stored by the server, thereby realizing data intercommunication and information tracking.
According to the calibration system of the present disclosure, optionally, the sensing data is a concentration profile, which is a function test of each of the analyte sensing elements using a plurality of different analyte concentrations, thereby obtaining a concentration profile of each of the analyte sensing elements. Under the condition, the concentration change curve can be more convenient to analyze and calibrate the sensing data, and can be more intuitively presented to a person needing to acquire the sensing data.
According to the calibration system of the present disclosure, optionally, the information of the barcode is stored in the server, and the analyte sensing component may be packaged, and the information of the barcode is downloaded from the server and may be displayed on the package. In this case, the information of the barcode can be stored in the server after being associated with the sensing data, can be pre-processed in the server, can be downloaded and printed with the associated information or data before shipment and displayed on the packaging, thereby enabling pre-factory and post-factory information tracking of the analyte sensing assembly.
According to the calibration system of the present disclosure, optionally, the sensing data includes at least one of an analyte concentration, a rate of change of analyte concentration, an analyte detection time, a sensor sensitivity, and a rate of change of sensitivity. In this case, when the analyte sensing element needs to be calibrated, the calibration algorithm or model can determine the performance of the analyte sensing element based on the analyte concentration, the rate of change of analyte concentration, the analyte detection time, the sensor sensitivity, and the rate of change of sensitivity and perform the corresponding analysis and calibration.
According to the calibration system of the present disclosure, the analyte sensing component is optionally bound by using the location of the lot and tool as information for the barcode. In this case, tracking of the pre-factory information of the analyte sensing assembly can be accomplished by utilizing the barcode.
According to the calibration system of the present disclosure, optionally, a compensation model is generated based on the calibration information, and the sensing data of the analyte sensing component can be calibrated by the compensation model. In this case, the calibration information is obtained from the factory-front sensing data obtained by using the barcode, and the analyte sensing assembly can be calibrated by using the preset compensation model before being used, that is, ex-vivo calibration after leaving the factory, so that discomfort or inconvenience of the conventional fingertip blood sampling calibration method is reduced, and better user experience is obtained.
According to the calibration system of the present disclosure, optionally, a terminal device with a display function is used to match the analyte sensing component, and the calibrated sensing data can be displayed on the terminal device. In this case, when the analyte sensing component is used, the terminal device with the display function can better and more intuitively display the sensing data to a patient or other people needing to obtain accurate analyte sensing data, namely, more conveniently acquire information.
According to the calibration system of the present disclosure, optionally, the calibration information includes at least one of a calibration behavior, a calibration factor, and a calibration coefficient. In this case, the calibration behavior can determine whether the sensing data needs to be calibrated and transmit the determination result to the next calibration process, the calibration factor can make the calibration information more complete, for example, the calibration factor can be a simulation factor, a test time period, a test mode, and the like of the test equipment before the factory, and the calibration factor can make the calibration information obtain a corresponding compensation factor, that is, a degree of compensation or a mathematical mode, when the compensation model is generated.
According to the calibration system of the present disclosure, optionally, the compensation model comprises at least one of probability analysis, fuzzy logic, and decision function. In this case, the compensation model can perform corresponding calibration on the sensing data according to different requirements in the manners of probability analysis, fuzzy logic, decision function and the like.
According to the calibration system of the present disclosure, optionally, the compensation model may further include a display model, and the display model may include at least one of a parameter compensation correction, a curve curvature compensation correction, and an image compensation correction. In this case, after the sensing data of the analyte sensing component is calibrated, the display model in the compensation model can display compensation and correction information including parameter compensation and correction, curve curvature compensation and correction, image compensation and correction, and the compensation and correction information can be displayed more intuitively for the person who needs to acquire the sensing data and the calibration information. .
A third aspect of the present disclosure provides an analyte sensing assembly that can have a chemical that reacts with glucose and generate sensing data. In this case, the analyte sensing assembly can form a complete calibration system with each of the devices in the system described above.
According to the analyte sensing assembly to which the present disclosure relates, optionally, the analyte sensing assembly comprises a sensing unit for detecting an analyte concentration and generating sensing data, and a communication unit for transmitting the sensing data. In this case, the sensing unit can obtain sensing data required by the above system or method and transmit the sensing data with each device in the system or method through the communication unit.
According to the analyte sensing assembly to which the present disclosure relates, optionally, the sensing data is transmitted to a terminal device for processing and/or displaying the sensing data through the communication unit. In this case, when the analyte sensing part is used, the sensing unit can acquire real-time sensing data in the human body and the calibrated sensing data obtained from the calibration system is visually displayed in the terminal device having the display function through the communication unit.
According to the analyte sensing assembly of the present disclosure, optionally, the sensing data is processed by the terminal device to generate a concentration curve with time. In this case, the sensed data can be intuitively displayed in the terminal device having the display function.
According to the present disclosure, a method and a system for calibrating sensing data of an analyte sensing assembly can be provided, which are a method and a system for calibrating sensing data of an analyte sensing assembly by using a barcode before using the analyte sensing assembly, and which can solve the problems that a fingertip blood sampling calibration mode in the prior art lacks comfort, convenience and better user experience for a patient.
Drawings
Fig. 1 is a flow chart of a method of calibrating sensing data of an analyte sensing assembly according to the present disclosure.
Fig. 2 is a block diagram of a calibration system for calibrating sensing data of an analyte sensing assembly according to the present disclosure.
Fig. 3 is a schematic diagram of an application scenario of an analyte sensing assembly according to the present disclosure.
FIG. 4 is a schematic illustration of a calibration result of a method and/or calibration system for calibrating sensing data of an analyte sensing assembly according to the present disclosure.
FIG. 5 is a graphical illustration of a calibration result of a method of calibrating sensing data of an analyte sensing assembly and/or a calibration system using a compensation model of a probability analysis according to the present disclosure.
FIG. 6 is a graphical illustration of a calibration result of a method of calibrating sensing data of an analyte sensing assembly and/or a compensation model of a calibration system using fuzzy logic according to the present disclosure.
FIG. 7 is a graphical illustration of a calibration result of a method of calibrating sensing data of an analyte sensing assembly and/or a calibration system using a compensation model of a decision function according to the present disclosure.
Fig. 8 is a schematic diagram illustrating a calibration result of a calibration system and/or a method of calibrating sensing data of an analyte sensing component according to the present disclosure in a terminal device.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first", "second", "third" and "fourth" etc. in the description and claims of the present invention and the above-mentioned drawings are used for distinguishing different objects and are not used for describing a specific order. Furthermore, the terms "comprising" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus. In the following description, the same components are denoted by the same reference numerals, and redundant description thereof is omitted. The drawings are schematic and the ratio of the dimensions of the components and the shapes of the components may be different from the actual ones.
The utility model provides a method and system for calibrating analyte sensing assembly's sensing data is a method and system for utilizing the bar code to carry out calibration to analyte sensing assembly's sensing data before using analyte sensing assembly, and it can solve among the prior art fingertip blood sampling calibration mode lack the problem of travelling comfort, convenience and better user experience to the patient. The following detailed description is made with reference to the accompanying drawings.
Fig. 1 is a flow chart illustrating a method of calibrating sensing data of an analyte sensing assembly according to the present disclosure.
As shown in fig. 1, a first aspect of the present disclosure provides a method for calibrating sensing data of an analyte sensing element using a barcode prior to using the analyte sensing element, comprising:
step S001, preparing a plurality of analyte sensing assemblies, and binding each analyte sensing assembly by using different bar codes;
step S002, performing function test on each analyte sensing assembly to obtain sensing data of each analyte sensing assembly;
step S003, determining calibration information according to comparison of sensing data of the analyte sensing component and a preset parameter range, and associating the calibration information with a bar code corresponding to the analyte sensor;
step S004, before the analyte sensing assembly is used, the bar code is identified and calibration information is obtained according to the bar code;
step S005 calibrates the sensing data of the analyte sensing element based on the calibration information.
Under the condition, the method can solve the problems that a fingertip blood sampling calibration mode in the prior art is lack of comfort and convenience for a patient and better user experience.
In some examples, the preset parameter range may refer to preset analyte concentration data, rate of change, sensitivity or sensitivity rate of change, or the like.
In some examples, the analyte concentration may refer to a glucose concentration of interstitial fluid in a human body. In other examples, the analyte concentration may refer to a concentration of lactate, vitamin C, uric acid, urea, glutamate, or transaminase, among others.
In some examples, the barcode used in step S001 may be a one-dimensional barcode or a two-dimensional barcode. In some examples, the one-dimensional barcode may include an EAN-13 Code, a UPC-A Code, a Code-128 Code, a Code-39 Code, an EAN/UCC-128 Code, or an ITF-14 Code, etc., and the two-dimensional barcode may include a PDF417, a Data Matrix, a Maxi Code, a QR Code, a Code 49, a Code 16K, a Code one, a Veri Code barcode, a CP barcode, a Code block F barcode, a mattifer Code, an Ultra Code, or an Aztec barcode, etc. In some examples, the barcode used in step S001 may be other scannable barcodes. Therefore, the step S001 can be carried out by using the corresponding bar code type according to the requirements after production and delivery, and convenience is provided for binding the bar code.
In some examples, the barcode binding in step S001 may be the binding of information that may be used as an ID identification mark, such as corresponding lot and tool information that has been assigned before the analyte sensing component is produced, to the barcode, i.e., step S001 may be completed when the analyte sensing component is not produced. In other examples, step S001 may be completed before the analyte sensing component has been produced and tested. Thus, the analyte sensing element that has passed the binding step S001 can be identified and tracked in subsequent steps.
In some examples, the analyte sensing component may be functionally tested using a functional testing device in step S002, where the functional testing refers to performance testing that simulates the analyte sensing component in a usage scenario. Thus, analyte sensing component sensing data can be obtained for analysis of its performance.
In some examples, step S003 may be completed in the test equipment in step S002 described previously. In other examples, step S003 may also be performed in the server after obtaining the sensing data of the analyte sensing component tested by the testing device. Thus, the processing load of the server can be reduced by completing step S003 in the test equipment, and the arithmetic processing in the test equipment can be reduced by completing step S003 in the server.
In some examples, step S004 may be to scan the barcode using a terminal device with barcode recognition function to obtain sensing data and calibration information of the analyte sensing assembly. Thus, a user can obtain calibration information before use of the analyte sensing component by the terminal device and use the terminal device to calibrate sensing data of the analyte sensing component after use based on the calibration information.
In some examples, step S005 may be completed in the terminal device in step S004. Whereby a user can use the terminal device to calibrate the sensory data of the analyte sensing element after use based on the calibration information.
In some examples, the problems of lack of comfort, convenience and better user experience for patients in a fingertip blood sampling calibration mode in the prior art can be solved through steps S001 to S005 in the method.
In some examples, the sensing data may be a concentration profile, which may be a functional test of each analyte sensing component using a plurality of different analyte concentrations and obtaining a concentration profile for each analyte sensing component. In this case, the analyte concentration data can be presented more intuitively in the form of a curve, thereby enabling analysis of the change in analyte concentration to be facilitated by analysis of the slope or curvature of the concentration change curve.
In some examples, the sensory data may also be a polyline or graph of concentration changes.
In some examples, the plurality of different analyte concentrations may be concentrations under pure or non-pure analyte solutions. In this case, testing the analyte sensing element with a neat concentration of analyte solution can reflect the actual performance parameters of the analyte sensing element, and testing the analyte sensing element with a non-neat concentration of analyte solution can reflect the analyte sensing element approaching the performance parameters in actual use.
In some examples, the information of the barcode may be stored at a server, the analyte sensing assembly may additionally be packaged, and the information of the barcode may be downloaded from the server and displayed on the packaging. In this case, the information of the barcode can be stored in the server after being associated with the sensing data, can be pre-processed in the server, can be downloaded and printed with the associated information or data before shipment and displayed on the packaging, thereby enabling pre-factory and post-factory information tracking of the analyte sensing assembly.
In some examples, the information of the barcode may be temporarily stored in a local device, for example, the testing device mentioned in step S002, and then uploaded to the server after the testing is completed, or the barcode information may be directly read from the testing device and printed.
In some examples, the packaging may be one of a manual packaging, a packaging machine packaging. For example, the packaging task can be completed quickly and efficiently by using a packaging machine for packaging, and the packaging machine is connected with a server to conveniently and quickly download and print the bar code to complete packaging.
In some examples, the sensory data may include at least one of analyte concentration, rate of change of analyte concentration, time of analyte detection, sensor sensitivity, and rate of change of sensitivity. In this case, when the analyte sensing element needs to be calibrated, the calibration algorithm or model can determine the performance of the analyte sensing element based on the analyte concentration, the rate of change of analyte concentration, the analyte detection time, the sensor sensitivity, and the rate of change of sensitivity and perform the corresponding analysis and calibration.
In some examples, the analyte concentration may refer to data generated from the conversion of chemical energy to electrical energy of the analyte with a sensor in the analyte sensing assembly. In some examples, the analyte concentration may be a specific single analyte concentration data or may be a multi-component analyte concentration data.
In some examples, the rate of change of analyte concentration may refer to the rate or amount of change of the analyte concentration data itself, as well as the slope or rate of change of a curve generated based on the analyte concentration.
In some examples, the analyte detection time may refer to a time until a sensor of the analyte sensing assembly contacts and reacts with the analyte solution or interstitial fluid in the human body to generate an electrical signal and the analyte sensing assembly acquires the electrical signal until the sensor separates from or stops reacting with the analyte solution or interstitial fluid in the human body.
In some examples, sensor sensitivity may refer to a lower limit of the sensor of the analyte sensing assembly reacting with the analyte.
In some examples, the sensitivity change rate can refer to a rate of change of a sensor of the analyte sensing assembly from a lower limit of analyte reaction.
In some examples, the analyte sensing component may be bound by using the location of the lot and the tool as information for the barcode. In this case, tracking of the pre-factory information of the analyte sensing assembly can be accomplished by utilizing the barcode.
In other examples, the server may randomly generate a unique serial number as barcode information and bind with each analyte sensing component that needs to be bound.
In some examples, a compensation model may be generated based on the calibration information, and the sensing data of the analyte sensing component may be calibrated by the compensation model. In this case, the calibration information is obtained from the factory-front sensing data obtained by using the barcode, and the analyte sensing assembly can be calibrated by using the preset compensation model before being used, that is, ex-vivo calibration after leaving the factory, so that discomfort or inconvenience of the conventional fingertip blood sampling calibration method is reduced, and better user experience is obtained.
In some examples, the compensation model may be a plurality of compensation models that are preset in the terminal device and that can be selected for selection based on the calibration information. Specifically, for example, if the measured sensing data is larger than the preset parameter range, the compensation model may select negative compensation; conversely, the compensation model may select positive compensation. Thus, a user can be enabled to obtain more accurate analyte concentration data when using the analyte sensing assembly.
In some examples, a terminal device with display capabilities may be used to match the analyte sensing component and the calibrated sensing data may be displayed at the terminal device. In this case, during the use of the analyte sensing component, the terminal device with the display function can better and more intuitively display the sensing data to the patient or other people who need to obtain accurate analyte sensing data, i.e., more conveniently acquire information.
In some examples, the terminal device may be a particular analyte concentration analyzer having a scanning function and a display function. In other examples, the terminal device may be a cell phone, tablet, or personal computer, etc., with analyte concentration analysis functionality. Thus, a user can conveniently use the analyte sensing assembly to analyze the concentration of the analyte.
In some examples, the calibration information may include at least one of a calibration behavior, a calibration factor, and a calibration coefficient. In some examples, the calibration behavior may determine whether the sensing data needs to be calibrated and transmit the determination result to the next calibration process, and the calibration factor may improve the calibration information, for example, the calibration factor may be a simulation factor, a test time period, a test mode, and the like of the test equipment before the factory, and the calibration coefficient may enable the calibration information to obtain a corresponding compensation coefficient, that is, a degree of compensation or a mathematical mode, when the compensation model is generated by the calibration information. In this case, the calibration accuracy can be improved by setting a plurality of kinds of calibration information.
FIG. 2 is a block diagram illustrating a calibration system for calibrating sensing data of an analyte sensing assembly according to the present disclosure; FIG. 4 is a schematic diagram illustrating calibration results of a method and/or calibration system for calibrating sensing data of an analyte sensing assembly according to the present disclosure; FIG. 5 is a schematic diagram illustrating calibration results of a method of calibrating sensing data of an analyte sensing assembly and/or a calibration system using a compensation model of a probability analysis according to the present disclosure; FIG. 6 is a schematic diagram illustrating calibration results of a compensation model of a calibration system and/or a method of calibrating sensing data of an analyte sensing assembly according to the present disclosure using fuzzy logic; FIG. 7 is a schematic diagram illustrating calibration results of a method of calibrating sensing data of an analyte sensing assembly and/or a calibration system using a compensation model of a decision function according to the present disclosure.
As shown in fig. 2, a second aspect of the present disclosure provides a calibration system 10 for calibrating sensing data of an analyte sensing element, which is a calibration system 10 for calibrating sensing data of an analyte sensing element using a barcode prior to using the analyte sensing element.
In some examples, the calibration system 10 may include the binding apparatus 11, the testing apparatus 12, the identifying apparatus 131, and the calibration apparatus 132.
In some examples, binding apparatus 11 may use different barcodes to bind each of the plurality of analyte sensing components. In some examples, testing device 12 may perform a functional test on each analyte sensing element to obtain sensing data for each analyte sensing element, and may determine calibration information based on a comparison of the sensing data for the analyte sensing element to a predetermined parameter range, and may associate the calibration information with a barcode corresponding to the analyte sensor. In some examples, the identification device 131 may identify a barcode and obtain calibration information from the barcode prior to using the analyte sensing component. In some examples, calibration device 132 may calibrate the sensing data of the analyte sensing component based on the calibration information.
Under this condition, just can acquire calibration information before using analysis sensing thing subassembly, and then calibrate analyte sensing thing subassembly's sensory data based on above-mentioned calibration information, can solve among the prior art not enough that fingertip blood sampling mode exists, for example can improve the convenience that patient's blood sugar was gathered, provide better experience for the user and feel, also can overcome among the prior art patient simultaneously and lack the travelling comfort scheduling problem.
In some examples, the binding apparatus 11 may be an information binding apparatus 11 in the server 15. In other examples, the binding apparatus 11 may be separate from the server 15 and communicate with the server 15, thereby facilitating remote planning of the plant room of the plant. In other examples, the binding device 11 may be integrated with the testing device 12, thereby facilitating binding of information and barcodes before the analyte sensing component is manufactured and tested, and reducing binding steps on other manufacturing processes.
In some examples, functional testing of the analyte sensing component in testing device 12 may include, but is not limited to: performance tests based on simulated analyte concentrations, sensitivity tests of analytical sensing assemblies, tests of electrical performance of analyte sensing assemblies (including without limitation circuit on-off, resistance, capacitance, inductance, etc.), and the like.
In some examples, the identification device 131 may be a scanning identification device 131 such as a code scanning gun or a code scanning machine. In other examples, the identification device 131 may be a mobile device with a scan identification function, such as a mobile phone, a tablet, a personal computer, etc.
In some examples, the identification means 131 and the calibration means 132 may be integrated in the terminal device 13. Thus, the analyte sensing assembly can be conveniently used by a user.
In some examples, calibration system 10 may also include a communication device 14 for information transfer and a user display device (not shown) for display. In this case, the binding device 11, the testing device 12 and the identification device 131 in the calibration system 10 can perform data communication via the communication device 14, such as obtaining information of a barcode, binding information of the barcode, sensing data, information of the barcode related to the sensing data, calibration information of the analyte sensing component based on the sensing data, and the like, and the user display device can better and more intuitively display the information to a patient or other people needing to obtain sensing data of an accurate analyte sensing component, that is, more conveniently obtain the information.
In some examples, the communication device 14 may communicate with the binding device 11 and the testing device 12 via a fieldbus 16 connection. In some examples, the communication device 14 may communicate information with the recognition device 131 and the calibration device 132 via a cloud, a local area network, or an internet connection.
In some examples, the user display device and the identification device 131, and the calibration device 132 may be integrated in the terminal device 13. Thus, the analyte sensing assembly can be conveniently used by a user.
In some examples, the calibration system 10 may further include a server 15 for data storage, and the server 15 may be in data communication with the binding device 11, the testing device 12, the identification device 131, and the calibration device 132 through the communication device 14. In this case, the binding device 11, the testing device 12, and the identification device 131 in the system 10 can communicate data with each other and be processed and stored by the server 15, thereby achieving data communication and information tracking.
In some examples, the server 15 may not be provided, in other words, the binding device 11, the testing device 12, the identification device 131, and the calibration device 132 perform data communication and data processing through the communication device 14 in the calibration system 10.
In some examples, the sensing data may be a concentration profile, which is a functional test of each analyte sensing component using a plurality of different analyte concentrations to obtain a concentration profile for each analyte sensing component. Under the condition, the analysis and calibration of the sensing data can be more conveniently carried out by observing the concentration change curve, and in addition, the sensing data can be more intuitively presented to the personnel needing to acquire the sensing data. This makes it possible to more easily analyze the change in analyte concentration by analyzing the slope or curvature of the concentration profile.
In some examples, the sensory data may also be a polyline or graph of concentration changes.
In some examples, the plurality of different analyte concentrations may be concentrations under pure or non-pure analyte solutions. In this case, testing the analyte sensing element with a neat concentration of analyte solution can reflect the actual performance parameters of the analyte sensing element, and testing the analyte sensing element with a non-neat concentration of analyte solution can reflect the analyte sensing element approaching the performance parameters in actual use.
In some examples, the information of the barcode may be stored at the server 15, and the analyte sensing assembly may be packaged, the information of the barcode downloaded from the server 15 and the barcode may be displayed on the packaging. In this case, the information of the barcode can be stored in the server 15 in association with the sensing data, can be preprocessed in the server 15, can be downloaded and printed with the barcode with the associated information or data before shipment and displayed on the package, and can thereby form a pre-factory and post-factory information track of the analyte sensing assembly.
In some examples, the information of the barcode may be temporarily stored in a local device, such as the testing apparatus 12, and then uploaded to the server 15 after the test is completed, or the barcode information may be directly read from the testing device and printed.
In some examples, the packaging may be one of a manual packaging, a packaging machine packaging. For example, the packaging task can be completed quickly and efficiently by using a packaging machine for packaging, and the packaging machine is connected with the server 15 to conveniently and quickly download the printed bar codes to complete the packaging.
In some examples, the sensory data may include at least one of analyte concentration, rate of change of analyte concentration, time of analyte detection, sensor sensitivity, and rate of change of sensitivity. In this case, when the analyte sensing element needs to be calibrated, the calibration algorithm or model can determine the performance of the analyte sensing element based on the analyte concentration, the rate of change of analyte concentration, the analyte detection time, the sensor sensitivity, and the rate of change of sensitivity and perform the corresponding analysis and calibration.
In some examples, analyte concentration may refer to data generated from the conversion of chemical energy to electrical energy of an analyte with a sensor in an analyte sensing assembly, which may be specific single analyte concentration data or may be multi-component analyte concentration data.
In some examples, the rate of change of analyte concentration may refer to the rate or amount of change of the analyte concentration data itself, as well as the slope or rate of change of a curve generated based on the analyte concentration.
In some examples, the analyte detection time may refer to a time until a sensor of the analyte sensing assembly contacts and reacts with the analyte solution or interstitial fluid in the human body to generate an electrical signal and the analyte sensing assembly acquires the electrical signal until the sensor separates from or stops reacting with the analyte solution or interstitial fluid in the human body.
In some examples, sensor sensitivity may refer to a lower limit of the sensor of the analyte sensing assembly reacting with the analyte.
In some examples, the sensitivity change rate can refer to a rate of change of a sensor of the analyte sensing assembly from a lower limit of analyte reaction.
In some examples, the analyte sensing component may be bound by using the location of the lot and the tool as information for the barcode. In this case, tracking of the pre-factory information of the analyte sensing assembly can be accomplished by utilizing the barcode.
In other examples, the server 15 may randomly generate a unique serial number as barcode information and bind with each analyte sensing component that needs to be bound.
In some examples, a compensation model may be generated based on the calibration information, and the sensing data of the analyte sensing component may be calibrated by the compensation model. In this case, the calibration information is obtained from the factory-front sensing data obtained by using the barcode, and the analyte sensing assembly can be calibrated by using the preset compensation model before being used, that is, ex-vivo calibration after leaving the factory, so that discomfort or inconvenience of the conventional fingertip blood sampling calibration method is reduced, and better user experience is obtained.
In some examples, the compensation model may be a plurality of compensation models that are preset in the calibration device 132 and that may be selectable based on the calibration information. Specifically, for example, if the measured sensing data is larger than the preset parameter range, the compensation model may select negative compensation; conversely, the compensation model may select positive compensation. Thus, a user can be enabled to obtain more accurate analyte concentration data using the analyte sensing assembly.
In some examples, a terminal device 13 with display capabilities may be used to match the analyte sensing component and calibrated sensing data may be displayed at terminal device 13. In this case, the terminal device 13 with a display function can better and more intuitively display, i.e., more conveniently acquire information, the patient or other person who needs to obtain accurate sensing data of the analyte sensing element when the analyte sensing element is in use.
In some examples, the identification device 131 and the calibration device 132 may be a specific analyte concentration analyzer having a scanning function and a display function. In other examples, the identification device 131 and the calibration device 132 may be a mobile phone, a tablet, a personal computer, etc. with an analyte concentration analysis function. Thus, a user can conveniently use the analyte sensing assembly to analyze the concentration of the analyte.
In some examples, the calibration information may include at least one of a calibration behavior, a calibration factor, and a calibration coefficient. In this case, the calibration behavior can determine whether the sensing data needs to be calibrated and transmit the determination result to the next calibration process, the calibration factor can make the calibration information more complete, for example, the calibration factor can be a simulation factor, a test time period, a test mode, and the like of the test equipment before the factory, and the calibration factor can make the calibration information obtain a corresponding compensation factor, that is, a degree of compensation or a mathematical mode, when the compensation model is generated. For example: as shown in fig. 4, if the pre-calibration sensing data is generally smaller than the preset parameter range, that is, the pre-calibration curve 1 shows, it can be determined that the calibration behavior needs to be compensated by adding positive compensation, and the calibrated result can be shown as the post-calibration curve 3; otherwise, the curve before calibration 2 may be referred to, and it may be determined that negative compensation needs to be added according to the calibration behavior, and the result after calibration may be shown as the curve after calibration 3.
In some examples, the compensation model may include at least one of a probability analysis, fuzzy logic, decision function. In this case, the compensation model can perform corresponding calibration on the sensing data according to different requirements in the manners of probability analysis, fuzzy logic, decision function and the like.
As shown in fig. 5, in the compensation model for probability analysis, for the sensing data of the same analyte sensing component: the curve c is a curve of normal sensing data or a curve of the sensing data after calibration, and the curves a and b are sensing data curves to be calibrated, wherein in the test, the sensing data of the curves a and b are randomly distributed on two sides of the curve c by taking the curve c as a center, so that the curves a and b need to be fitted close to the curve c through a mathematical algorithm, namely after the analyte sensor is used, although the actual sensing data may be a or b, the curve c is still displayed after compensation calibration.
As shown in fig. 6, in the compensation model of fuzzy logic, for the sensing data of the same analyte sensing component: the curve f is a curve of normal sensing data or a curve of the sensing data after calibration, and the curves d and e are sensing data curves needing calibration, wherein in the test, the sensing data of the curves d and e are completely matched or overlapped with the sensing data of the partial detection time period of the curve f, the rest time periods are not matched, a compensation model of fuzzy logic is selected to perform compensation calibration on the curves d and e, namely, the part matched with the curve f in the curves d and e is reserved through a fuzzy algorithm, and the rest of the curves are correspondingly compensated.
As shown in fig. 7, in the compensation model of the decision function, for the sensing data of the same analyte sensing component: the curve k is a curve of normal sensing data or a curve of calibrated sensing data, and the curves h and g are sensing data curves requiring calibration, wherein in a test, if the sensing data of the curves h and g can correspond to but not completely match the curve k only in a certain detection time period x (x is x2-x1), a decision function model is selected to perform compensation calibration on the curves h and g, that is, abnormal data outside the detection time period x is not calculated, and only the sensing data of the detection time period x is compensated.
In some examples, the compensation model may further include a display model, and the display model may include at least one of a parametric compensation correction, a curve curvature compensation correction, and an image compensation correction. In this case, after the sensing data of the analyte sensing component is calibrated, the display model in the compensation model can display compensation and correction information including parameter compensation and correction, curve curvature compensation and correction, image compensation and correction, and the compensation and correction information can be displayed more intuitively for the person who needs to acquire the sensing data and the calibration information.
FIG. 3 is a schematic diagram illustrating an application scenario of an analyte sensing assembly according to the present disclosure; fig. 8 is a schematic diagram illustrating a method of calibrating sensing data of an analyte sensing component and/or a calibration result of a calibration system presented in a terminal device according to the present disclosure.
As shown in fig. 3, a third aspect of the present disclosure provides an analyte sensing component 02, where the analyte sensing component 02 may have a chemical that reacts with glucose, and is an analyte sensing component 02 for use in the above-described method or calibration system. In this case, the analyte sensing assembly 02 can form a complete calibration system with each of the devices in the system described above.
In some examples, the analyte sensing assembly 02 may include a sensing unit for detecting analyte concentration and generating sensing data, a communication unit for transmitting the sensing data. In this case, the sensing unit can obtain sensing data required by the calibration system or method and transmit the sensing data with each device in the calibration system or method through the communication unit.
In some examples, the analyte sensing assembly may preferably be used for detection analysis of glucose concentration in a human body.
In some examples, the sensory data may be transmitted by the communication unit to the terminal device 13 for processing and/or displaying the sensory data. In this case, when the analyte sensing module 02 is used, the sensing unit can obtain real-time sensing data in the human body and the calibrated sensing data obtained from the calibration system is visually displayed in the terminal device 13 having a display function through the communication unit.
In some examples, the sensed data may be processed by terminal device 13 to generate a concentration profile over time. In this case, the sensed data can be intuitively displayed in the terminal device 13 having the display function.
According to the present disclosure, a method and a system for calibrating sensing data of an analyte sensing assembly can be provided, which are a method and a calibration system for calibrating sensing data of an analyte sensing assembly by using a barcode before using the analyte sensing assembly, and can solve the problems of lack of comfort, convenience and better user experience for a patient in a fingertip blood calibration mode in the prior art.
While the invention has been described in detail in connection with the drawings and examples, it is to be understood that the above description is not intended to limit the invention in any way. Those skilled in the art can make modifications and variations to the present invention as needed without departing from the true spirit and scope of the invention, which falls within the scope of the invention.
Claims (24)
1. A method of calibrating sensor data of an analyte sensing element using a barcode prior to use of the analyte sensing element, comprising:
preparing a plurality of the analyte sensing assemblies and binding each of the analyte sensing assemblies using the barcodes;
performing function test on each analyte sensing assembly to obtain sensing data of each analyte sensing assembly, determining calibration information according to comparison between the sensing data of the analyte sensing assembly and a preset parameter range, and associating the calibration information with a bar code corresponding to the analyte sensor;
identifying the barcode and obtaining the calibration information from the barcode prior to using the analyte sensing component; and is
Calibrating the sensing data of the analyte sensing component based on the calibration information.
2. The method of claim 1,
the sensing data is a concentration profile, which is a function test of each analyte sensing element using a plurality of different analyte concentrations and a concentration profile of each analyte sensing element.
3. The method of claim 1,
the information of the barcode is stored in a server, the analyte sensing assembly is packaged, the information of the barcode is downloaded from the server, and the barcode is displayed on the package.
4. The method of claim 1,
the sensory data includes at least one of an analyte concentration, a rate of change of analyte concentration, an analyte detection time, a sensor sensitivity, and a rate of change of sensitivity.
5. The method of claim 1,
binding the analyte sensing component by using the position of the lot and the tooling as information of the barcode.
6. The method of claim 1,
a compensation model is generated based on the calibration information, and the sensing data of the analyte sensing assembly is calibrated by the compensation model.
7. The method of claim 1,
and matching the analyte sensing assembly by using a terminal device with a display function, and displaying the calibrated sensing data on the terminal device.
8. The method of claim 1,
the calibration information includes at least one of a calibration behavior, a calibration factor, and a calibration coefficient.
9. A calibration system for calibrating sensor data of an analyte sensing element using a barcode prior to use of the analyte sensing element, comprising:
a binding device that binds each of the plurality of analyte sensing components using the barcode;
the testing device is used for carrying out function testing on each analyte sensing assembly to obtain sensing data of each analyte sensing assembly, determining calibration information according to comparison between the sensing data of the analyte sensing assembly and a preset parameter range, and associating the calibration information with a bar code corresponding to the analyte sensor;
an identification device that identifies the barcode and obtains the calibration information from the barcode prior to use of the analyte sensing component;
a calibration device that calibrates the sensing data of the analyte sensing component based on the calibration information.
10. The calibration system of claim 9,
the calibration system further comprises communication means for information transfer, user display means for display.
11. The calibration system of claim 9,
the server is used for data storage and is in data communication with the binding device, the testing device and the identification device through the communication device.
12. The calibration system of claim 9,
the sensing data is a concentration variation curve, and a plurality of different analyte concentrations are used for carrying out function tests on each analyte sensing assembly to obtain the concentration variation curve of each analyte sensing assembly.
13. The calibration system of claim 11,
the information of the barcode is stored in the server, the analyte sensing assembly is packaged, the information of the barcode is downloaded from the server, and the barcode is displayed on the package.
14. The calibration system of claim 9,
the sensory data includes at least one of an analyte concentration, a rate of change of analyte concentration, an analyte detection time, a sensor sensitivity, and a rate of change of sensitivity.
15. The calibration system of claim 9,
binding the analyte sensing component by using the position of the lot and the tooling as information of the barcode.
16. The calibration system of claim 9,
a compensation model is generated based on the calibration information, and the sensing data of the analyte sensing assembly is calibrated by the compensation model.
17. The calibration system of claim 9,
and matching the analyte sensing assembly by using a terminal device with a display function, and displaying the calibrated sensing data on the terminal device.
18. The calibration system of claim 9,
the calibration information includes at least one of a calibration behavior, a calibration factor, and a calibration coefficient.
19. The calibration system of claim 16,
the compensation model includes at least one of probability analysis, fuzzy logic, and decision function.
20. The calibration system of claim 16,
the compensation model further includes a display model including at least one of a parametric compensation correction, a curve curvature compensation correction, and an image compensation correction.
21. An analyte sensing assembly having a chemical that reacts with glucose and generates sensing data.
22. The analyte sensing assembly of claim 21,
the analyte sensing assembly comprises a sensing unit and a communication unit, wherein the sensing unit is used for detecting the concentration of an analyte and generating the sensing data, and the communication unit is used for transmitting the sensing data.
23. The analyte sensing assembly of claim 21,
the sensing data is sent to the terminal equipment for processing and/or displaying the sensing data through the communication unit.
24. The analyte sensing assembly of claim 21,
and the sensing data is processed by the terminal equipment to generate the concentration change curve changing along with time.
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| CN202211633814.XA CN115856272A (en) | 2021-09-24 | 2021-09-24 | Method and system for calibrating concentration profile of analyte sensing component |
| CN202111123331.0A CN113848313B (en) | 2021-09-24 | 2021-09-24 | Method and system for calibrating sensing data of analyte sensing component |
| PCT/CN2022/095711 WO2023045383A1 (en) | 2021-09-24 | 2022-05-27 | Method and system for calibrating sensing data of analyte sensing assemblies |
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| CN115856272A (en) | 2023-03-28 |
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