WO2023151213A1 - 分析物浓度数据生成方法和装置、监测分析物浓度的系统 - Google Patents

分析物浓度数据生成方法和装置、监测分析物浓度的系统 Download PDF

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WO2023151213A1
WO2023151213A1 PCT/CN2022/100103 CN2022100103W WO2023151213A1 WO 2023151213 A1 WO2023151213 A1 WO 2023151213A1 CN 2022100103 W CN2022100103 W CN 2022100103W WO 2023151213 A1 WO2023151213 A1 WO 2023151213A1
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moment
sensitivity
data set
analyte concentration
data
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PCT/CN2022/100103
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French (fr)
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韩洋
雷大鹏
那姣龙
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苏州百孝医疗科技有限公司
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1468—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using chemical or electrochemical methods, e.g. by polarographic means
    • A61B5/1473—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using chemical or electrochemical methods, e.g. by polarographic means invasive, e.g. introduced into the body by a catheter
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/14546—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring analytes not otherwise provided for, e.g. ions, cytochromes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1495—Calibrating or testing of in-vivo probes
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7221—Determining signal validity, reliability or quality
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/26—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating electrochemical variables; by using electrolysis or electrophoresis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/66—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving blood sugars, e.g. galactose
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2560/00—Constructional details of operational features of apparatus; Accessories for medical measuring apparatus
    • A61B2560/02—Operational features
    • A61B2560/0223—Operational features of calibration, e.g. protocols for calibrating sensors
    • A61B2560/0228—Operational features of calibration, e.g. protocols for calibrating sensors using calibration standards

Definitions

  • the present application relates to the field of continuous analyte concentration data generation, for example, a method and device for generating analyte concentration data, and a system for monitoring analyte concentration.
  • Some diseases require continuous monitoring of analyte concentrations, such as diabetes, a disease in which blood glucose concentration data are abnormal due to the inability of the pancreas to produce insulin (type 1 diabetes) or inefficient insulin secretion and action (type 2 diabetes).
  • Users affected by diabetes need to monitor blood glucose (Blood Glucose, BG) levels throughout the day to control blood sugar and take countermeasures to keep it within the normal range as much as possible.
  • BG blood glucose
  • Diabetic users are forced to take exogenous insulin infusions or medications, the schedule and dosage of which are determined based on BG measurements.
  • BG measurements can be collected in two main ways: i) finger pricking through capillaries in daily life to draw finger blood and measure with dipstick, i.e. self-monitoring blood glucose up to 4-5 times a day; ii ) in an inpatient clinical trial, as measured by a finger-blood-linked blood glucose meter. Both of these BG surveillance systems are fairly accurate. However, it is impossible to continuously and dynamically monitor the user's blood glucose concentration change level, and blood sampling can only be performed occasionally, and the rapid fluctuation of the user's glucose concentration may not be detected.
  • CGM Continuous Blood Glucose monitoring
  • CGM has a much higher temporal resolution (displayed every 1-5 minutes) than BG, but sometimes exhibits systematic under/overestimation of true blood glucose concentrations. Obviously, the lack of accuracy of CGM will affect its clinical application. At present, the research community has recognized the bottleneck of the accuracy of CGM in clinical practice.
  • the present application provides a method and device for generating analyte concentration data, and a system for monitoring analyte concentration, so as to improve the technical defects existing in related technologies.
  • the application provides a method for generating analyte concentration data, including:
  • the first data set is acquired by the first device, the first data set includes first analyte concentration data and a target measurement time corresponding to the first analyte concentration data;
  • the second data set including raw values related to the analyte concentration and a time stamp of the raw values obtained by the second device;
  • a proportional relationship is determined; the proportional relationship is the ratio of the original value at the target moment to the first analyte concentration data at the target measurement moment, and the target moment is the target measurement moment or the moment closest to said target measurement moment;
  • a first weight value and a second weight value are determined; the first sensitivity is the sensitivity at the first moment, and the first moment is located between the last measurement moment and the between the target measurement times;
  • the present application also provides a device for generating analyte concentration data, including:
  • the first data set acquisition module is configured to acquire the first data set, the first data set is acquired by the first device, the first data set includes the first analyte concentration data and the target measurement corresponding to the first analyte concentration time;
  • the second data set acquisition module is configured to acquire a second data set, and the second data set includes an original value related to the analyte concentration and a time stamp of the original value acquired by the second device;
  • the proportional relationship determination module determines the proportional relationship based on the first data set and the second data set; the proportional relationship is the ratio of the original value at the target moment to the first analyte concentration data at the target measurement moment, and the target moment is the target measurement time or the time closest to the target measurement time;
  • the weight value determination module is configured to determine a first weight value and a second weight value based on the rate of change of the proportional relationship relative to the first sensitivity; the first sensitivity is the sensitivity at the first moment, and the first moment Located between the last measurement moment and the target measurement moment;
  • a sensitivity updating module configured to determine a second sensitivity based on the proportional relationship and the first weight value corresponding to the proportional relationship, and the first sensitivity and the second weight value corresponding to the first sensitivity;
  • An analyte concentration data generation module configured to generate a second analyte concentration data set for a first time period based on the second sensitivity and the second data set, the first time period starting from the target measurement moment And continue to the second moment, the second moment is located after the target measurement moment.
  • the present application also provides a system for monitoring the concentration of an analyte, comprising: a sensor, a wireless transmitter, and a mobile computing device;
  • a sensor configured to acquire a second data set
  • the mobile computing device includes: a receiving device, a memory, a processor, and a software application;
  • a receiving device configured to receive the first data group and the second data group
  • a memory configured to store data comprising said first data set and said second data set
  • a processor configured to process said data
  • a software application includes instructions stored in the memory, which when executed by the processor implement the analyte concentration data generation method described.
  • the present application also provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and operable on the processor.
  • the processor implements the method for generating the analyte concentration data when executing the program.
  • the present application also provides a non-transitory computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the method for generating analyte concentration data as described in any one of the above-mentioned methods is realized.
  • FIG. 1 is a schematic structural diagram of an implementation environment involved in an embodiment of the present application.
  • Fig. 2 is a schematic flowchart of the method for generating analyte concentration data provided by the present application.
  • Fig. 3 is a schematic diagram of sensitivity in different time periods in the method for generating analyte concentration data provided by the present application.
  • Fig. 4 is a schematic diagram showing the comparison of the blood glucose concentration after the implementation of the analyte concentration data generation method provided by the present application and without implementation of the analyte concentration data generation method.
  • Fig. 5 is a schematic structural diagram of the analyte concentration data generating device provided in the present application.
  • FIG. 6 is a schematic structural diagram of an electronic device provided by the present application.
  • the consistency of sensitivity may generate unreasonable and mutated analyte concentration data due to poor reference samples and other reasons, causing the data output by the continuous analyte concentration data measurement equipment after calibration to be even less able to reflect the actual measurement time of each original value. Consequences of Analyte Concentration Data.
  • the data measured by the continuous analyte concentration data measurement equipment is still output in real time, resulting in inappropriate or unreasonable error data in the output data (because no reference sample is used for adjustment), and it is not It must be able to reflect the real analyte concentration level of the user, so that it cannot be practically applied in clinical practice, and even the error data will mislead experts and users, further affecting the diagnosis and treatment effect; in another case, the continuous analyte concentration data measurement worn by the user The device continues to collect raw values related to the analyte concentration, but due to the inconvenience of operation and the avoidance of error data in the above situations, the user does not have a receiving device or is not allowed to use the receiving device to view the analyte concentration data, and can only check the personal data intermittently. Analyte concentration profiles (small, sparse but accurate reference samples), and the inability to generate a continuous report that reflects the user's true analyte concentration levels.
  • the analyte in this application can be blood sugar, blood ketone, ethanol, lactic acid, creatinine (analyte related to renal function), uric acid, the analyte that causes heart failure-brain natriuretic peptide (Brain Natriuretic Peptide, BNP), various Infectious source analytes (such as C-reactive protein, procalcitonin, serum amyloid A, interleukin 6, etc.), etc.
  • Each analyte can have a device that measures the concentration continuously, as well as a more precise device that measures the concentration non-continuously.
  • blood glucose concentration is taken as an example for further description, and the method of generating and monitoring concentration data of other analytes is the same as that of blood glucose.
  • FIG. 1 shows a schematic structural diagram of an implementation environment involved in multiple embodiments of the present application.
  • the implementation environment includes: a first device 100 and a second device 200, and/or a server 300.
  • the first device 100 may be a device capable of testing blood glucose, such as a blood glucose meter, a blood glucose meter, a blood glucose monitoring device, a blood glucose testing device, etc. that test blood glucose concentration data by collecting finger blood.
  • a device capable of testing blood glucose such as a blood glucose meter, a blood glucose meter, a blood glucose monitoring device, a blood glucose testing device, etc. that test blood glucose concentration data by collecting finger blood.
  • the second device 200 may be a continuous glucose monitoring (CGM) system configured to continuously monitor a person's blood glucose.
  • CGM continuous glucose monitoring
  • a CGM system may be configured with a CGM sensor, for example, that is inserted subcutaneously into a person's skin and detects an analyte indicative of the person's blood sugar.
  • a CGM system can continuously generate glucose measurements based on detected analytes.
  • continuous is near continuous such that continuous glucose monitoring takes the resources of a CGM system (e.g.,
  • the CGM system can include receiving devices with data processing capabilities, such as mobile phones, tablet computers, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, and MP4 (Moving Picture Experts Group Audio Layer IV) players devices, laptops, desktops, and more.
  • receiving devices with data processing capabilities such as mobile phones, tablet computers, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, and MP4 (Moving Picture Experts Group Audio Layer IV) players devices, laptops, desktops, and more.
  • An application program client or a browser may be installed in the receiving device, and the web page client of the application program may be accessed through the browser.
  • the application program client and the web page client are collectively referred to as clients, which will not be specifically stated below.
  • Server 300 can be a near-end or remote server, or a server cluster composed of several servers,
  • the server 300 may be configured to interact with the second device 200 to provide services related to this application.
  • the server 300 is a server corresponding to the client, and the two can be combined to implement multiple functions provided by the client, and are usually set up by an Internet service provider.
  • the second device 200 can be connected to the first device 100 through a wireless network or a wired network to realize data transmission; the second device 200 and the first device 100 can also be connected to the server 300 through a wireless network or a wired network to realize data transmission. .
  • a method for generating analyte concentration data of the present application includes: S1, acquiring a first data set, the first data set is acquired by the first device 100, and the first data set includes the first data set An analyte concentration data and a target measurement time corresponding to the first analyte concentration data.
  • the first device 100 may have only one type of device, or may be devices of multiple different brands or different models of the same brand, and each set of first data groups corresponds to one brand or one model.
  • each first data set is data collected by the same brand or model at a specific target measurement moment, which includes the first blood glucose concentration data and its corresponding target measurement moment.
  • the user is pre-associated with the second device 200 , and the first data set used by the first device 100 for calibration corresponds to the same user as the second device 200 .
  • the first device 100 may be associated with multiple users, and correspondingly, data of each user is respectively transmitted to the second device 200 pre-associated with each user.
  • the reliability of each first data set is relatively high, and it can be defined that the first device 100 tests the first data set in a discontinuous manner by collecting finger blood.
  • the generation of the second blood glucose concentration data set is suspended, In the case that the original value related to the blood glucose concentration is in a normal state, continue to generate the second blood glucose concentration data set. That is, since the state is abnormal, it can be considered that it is meaningless to generate the second blood glucose concentration data set at this time, and the second device 200 should be in a normal working state, so the second blood glucose concentration data set is generated.
  • the proportional relationship is the ratio of the original value at the target time to the first analyte concentration data at the target measurement time, and the target time is the target measurement time or the time closest to the target measurement time.
  • the first data set includes the time value of the target measurement moment, and the first blood glucose concentration data at the target measurement moment, that is, the first blood glucose concentration data with a time stamp.
  • the original value of the second device 200 at the target measurement time may be the current value at the target measurement time.
  • the sampling period is generally several seconds to several minutes, there is a possibility that the original value does not exist at the target measurement time), this The original value at the moment closest to the target measurement time can be selected.
  • the target time can also select the original value at the closest target measurement time, for example, select the original value at a time within the preset range of the target measurement time, and the preset range can be within 15 seconds before and after the target measurement time, for example, you can select Raw value three seconds before or fifteen seconds after the measurement moment.
  • the original value located three seconds before the target measurement time can be selected, or the time difference from the target measurement time is less than one sampling period.
  • the raw value of the moment used to determine the scaling relationship. The closer the target time is to the original value at the target measurement time, the better the reference for determining the proportional relationship, so the target measurement time or the original value closest to the target measurement time is selected.
  • the target measurement time and the second sensitivity after the target measurement time can be further determined.
  • the first moment is a moment before the target measurement moment, and may be a moment with the first sensitivity in the last sampling period of the collected raw values before the target measurement moment.
  • the magnitude of the change of the proportional relationship relative to the first sensitivity may be determined, and then the first weight value and the second weight value are determined according to the rate of change.
  • the first weight value corresponds to the proportional relationship
  • the second weight value corresponds to the first sensitivity.
  • the first weight value and the second weight value are dynamically adjusted based on the rate of change.
  • the influence of the first data group at each target measurement time on the second sensitivity can be considered, and the first sensitivity between the last measurement time and the current target measurement time can also be considered.
  • the second weight value can be increased. At this time, more consideration needs to be made to maintain consistency with the first sensitivity, and no sudden change in sensitivity occurs; when the proportional relationship When the rate of change with the target measurement time is small, the first weight value can be increased. At this time, more consideration should be given to the proportional relationship obtained from the target measurement time to further optimize the second rate of change; the first weight value ,
  • the second weight values may be the same or different.
  • S5. Determine a second sensitivity based on the proportional relationship and the first weight value corresponding to the proportional relationship, and the first sensitivity and the second weight value corresponding to the first sensitivity.
  • the determined second sensitivity can consider that the proportional relationship obtained by the current target measurement time can be the one before the target measurement time A certain moment with the first sensitivity in the previous sampling period for collecting the original value, and keeping consistency with the first sensitivity can be taken into account at the same time.
  • a second blood glucose concentration for the first time period is generated based on the second sensitivity and the second data set (ie, the raw blood glucose concentration-related values for the first time period and their time stamps)
  • the data set, the second blood glucose concentration data set includes the blood glucose concentration value and its time stamp for display.
  • the second device 200 does not output the blood glucose concentration data in real time, so as to avoid inappropriate or unreasonable error data in the real-time output data, and further avoid misleading experts and users by the error data, which may affect the diagnosis and treatment effect. situation.
  • the above steps S1 to S1 can be performed for each target measurement moment.
  • S6 Based on the first data set at each target measurement moment, the second data set, and the first sensitivity before each target measurement moment, the second sensitivity of each sub-time period in the second time period is obtained, thereby generating each sub-time A second blood glucose concentration data set of a time period (for example, one of the sub-time periods may be the first time period).
  • Each previous first sensitivity relative to the second sensitivity can be continuously inherited with a certain weight, and the generation of the second blood glucose concentration data set in each time period can more or less take into account the initial sensitivity , and sensitivities at a plurality of different times preceding each first time period.
  • the second blood glucose concentration data set of each sub-time period can be combined to form a second blood glucose concentration data set of the second time period, and the second blood glucose concentration data set can form an overall report of the second time period to generate a A continuous report that can reflect the user's true blood glucose concentration level.
  • the overall report can more reasonably restore the user's real blood sugar concentration, and can achieve clinical practical application effects.
  • the subject of execution of the present application is the second device 200 or the server 300 and other devices with data processing capabilities.
  • the present application combines the user's first data set obtained by the first device and the second data set obtained by the second device to determine the proportional relationship.
  • the proportional relationship is the ratio of the original value at the target measurement moment or the closest to the target measurement moment to the first blood glucose concentration data. Based on the rate of change of the proportional relationship relative to the first sensitivity, the first weight value and the second weight value are determined, and then the second sensitivity for generating the second blood glucose concentration data set for the first time period is determined.
  • the second sensitivity can take into account the proportional relationship corresponding to the current target measurement time, and can also take into account the consistency with the first sensitivity to avoid generating an unreasonable and abrupt second sensitivity. Based on the dynamically adjusted second sensitivity, the second sensitivity of each time period can be maintained to more reasonably restore the real situation at the time when each original value is measured. The second sensitivity thus generated is very close to the real sensitivity at the actual measurement time of each original value, and can make the second device 200 generate a more accurate second blood glucose concentration data set in the first time period after the target measurement time, realizing the second The output data of the high sensitivity and high measurement accuracy of the device 200.
  • This application can eliminate the error caused by sensitivity attenuation during the continuous blood glucose monitoring process of the second device 200, which cannot reflect the real blood glucose concentration data at the actual measurement time of each original value, and can also directly output dynamically adjusted and more accurate second blood glucose
  • the concentration data set avoids misleading the user caused by the second device 200 outputting data that has not been adjusted by the first data set.
  • the raw values include data collected by the second device 200 for determining the second analyte concentration data set.
  • the raw value includes a current value used to determine the second analyte concentration data set, and the current value is between the sensor in the second device 200 and a specific solution (for example, blood in the user's body, tissue). liquid or other solutions, etc.); the specific solution is the solution where the sensor is located.
  • a specific solution for example, blood in the user's body, tissue. liquid or other solutions, etc.
  • the determining the first weight value and the second weight value based on the rate of change of the proportional relationship relative to the first sensitivity includes: using the following formula to determine the proportional relationship relative to the first sensitivity The rate of change R:
  • the first weight value and the second weight value are determined by using the following formula:
  • I represents the original value collected at the target measurement time
  • G represents the first analyte concentration data at the target measurement time
  • S old represents the first sensitivity
  • the first sensitivity is used to determine the last measurement
  • the third analyte concentration data set at time t represents the target time difference between the generation time of the first sensitivity and the target measurement time
  • f(R, t) represents a function with R and t as parameters
  • the function represents the second weight
  • the values are related to R and t
  • a represents the first weight value corresponding to the proportional relationship
  • the sensitivity change rate per minute there is a maximum value for the sensitivity change rate per minute in different time periods within the effective working time of the sensor.
  • the proportional relationship is relatively large (greater than the proportional threshold), it may be due to human operation that the measurement of the first data set of the first device 100 at the target measurement time has errors or deviations.
  • the first sensitivity has a certain usable value for the newly generated second sensitivity. You can consider the first sensitivity and give it a second weight value, which can properly reduce the gap between the second sensitivity and the first sensitivity. Smooth, so that data mutations will not occur in the first period of time. If you need to consider more proportional relationships, you can set the first weight value to be greater than the second weight value. If you need to consider referring to the first sensitivity more, you can set the first weight value to be less than or equal to the second weight value. If you consider the proportional relationship If it is equally important as the second sensitivity, the first weight value can also be set equal to the second weight value. For example, the first weight value and the second weight value may be set according to the change rate of the proportional relationship relative to the first sensitivity, the target time difference between the generation moment of the first sensitivity and the target measurement moment.
  • the second weight value is an initial preset value, zero or an empirical preset value.
  • b can be adjusted dynamically, and the initial value of b can be 0 or an initial preset value or an empirical preset value.
  • the first sensitivity is a preset sensitivity.
  • the preset sensitivity may be the initial sensitivity of the sensor, or the preset sensitivity determined based on the method of the present application and meeting certain preset conditions.
  • the first moment is the previous moment before the target measurement moment
  • the first time difference between the target measurement moment and the first moment is for the second device 200 to obtain the original value the sampling period.
  • the first moment is the last moment before the target measurement moment, so as to ensure that the first sensitivity adopts the sensitivity at the last moment closest to the target measurement moment, which is more meaningful for reference.
  • the determining the second sensitivity based on the proportional relationship and its corresponding first weight value, and the first sensitivity and its corresponding second weight value includes: using the following formula to determine The second sensitivity:
  • S represents the second sensitivity
  • the first sensitivity acts on the original value between the generation moment of the first sensitivity and the generation moment of the next sensitivity (second sensitivity) of the first sensitivity; the second sensitivity acts on the first time period, that is, the second sensitivity The original value between the generation time and the generation time of the sensitivity next to the second sensitivity (the third sensitivity).
  • the generating the second analyte concentration data set in the first time period based on the second sensitivity and the second data set includes: displaying each display cycle corresponding to the first time period
  • the second data set is respectively divided by the second sensitivity to generate the second analyte concentration data set in the first time period
  • the display cycle is the display of the second analyte concentration data set by the second device 200 cycle.
  • the original value corresponding to each display period is divided by the second sensitivity to generate the second blood glucose concentration data set for the first time period.
  • the method includes: displaying the second analyte concentration data set according to the display period.
  • the second blood glucose concentration data set can be output and displayed according to the display cycle, and the output and displayed data are data closer to the real blood glucose level of the user.
  • the display period is greater than or equal to 1 minute.
  • the display period can be 2-3 minutes.
  • the time interval for the CGM system to display data that is, the display period is 2-3 minutes.
  • the first data group is obtained after pre-screening based on preset rules.
  • the preset rules include: when there are multiple sets of different first devices 100, a set of data of the first device 100 with the highest trustworthiness is selected as the first data group, and the trustworthiness is based on the It is determined by the model of the first device 100 or the regular quality control maintenance records.
  • a set of data of the first device 100 with the highest trustworthiness is selected as the first data set, which may be a certain brand or model of blood glucose meter with the highest trustworthiness.
  • the first device 100 may refer to multiple different brands or different models of the same brand.
  • the data obtained by the user's historically used blood glucose meters can be selected.
  • the same user may use the same first device 100 for each calibration during blood glucose monitoring; when there are multiple devices, selecting a specific device can also reduce errors.
  • Blood glucose meters generally require regular calibration and quality control maintenance, and maintenance records are kept. There may be some test accuracy and other data on the maintenance records, and the reliability can be confirmed based on the maintenance records.
  • this blood glucose meter is not used to generate analyte concentration data.
  • the reliability of the generally used blood glucose meter is greater than that of CGM.
  • the second moment is located at or before the third moment, the third moment is the next measurement moment after the target measurement moment, and between the third moment and the second moment The second time difference between them is greater than or equal to one display period.
  • the second moment is located at the third moment, that is, the first time period (that is, the application time period of the second sensitivity) lasts from the target measurement moment to the next measurement moment.
  • the second moment is before the third moment, that is, the first time period (that is, the application time period of the second sensitivity) lasts from the target measurement moment to a certain time before the next measurement moment. moment.
  • the determination of a certain moment may be based on the target time difference. For example, if the target time difference is greater than 12 hours, other updated sensitivities may be available after the above certain moment. That is to say, the validity period of the second sensitivity can be set based on the attenuation characteristics of the sensor performance.
  • the second moment is located at or before the fourth moment, and the fourth moment is the end measurement moment after the target measurement moment.
  • the second moment is located at the fourth moment, that is, the first time period (that is, the application time period of the second sensitivity) lasts from the target measurement moment to the end measurement moment (which can be the CGM to the original value End of measurement time).
  • the second moment is located before the fourth moment, that is, the first time period (that is, the application time period of the second sensitivity) lasts from the target measurement moment to some other time before the end of the measurement moment. moment.
  • the determination of another moment may also be based on the target time difference. For example, if the target time difference is greater than 12 hours, other updated sensitivities may be available after the other moment. That is to say, the validity period of the second sensitivity can be set based on the attenuation characteristics of the sensor performance.
  • the method also includes:
  • At least one collection module is used to acquire the first data group and the second data group.
  • the first sensitivity is generated at 12:00 noon on the 1st.
  • the first case two days later, at 12:01 noon on the 3rd (the target measurement time), the other first blood glucose obtained by the blood glucose meter Concentration data appear with intervals greater than 48 hours.
  • the proportional relationship between the original value at 12:01 noon on the 3rd and the first blood glucose concentration data is calculated, and the rate of change between the proportional relationship and the first sensitivity is calculated.
  • the second sensitivity is a weighted average of the first sensitivity and the current proportional relationship.
  • the degree of influence of the last sensitivity in this sensitivity calculation is affected by time and change rate, and the time is the time difference between the generation time of the last sensitivity and the generation time of this proportional relationship. If a large change greater than the threshold occurs in a short period of time, it is considered that this proportional relationship is greatly affected by noise, so the impact factor b of the previous sensitivity is relatively large; the determination of b is based on the comprehensive factors of R and t, so it can be Recorded as:
  • the second device 200 worn by the user continuously collects raw values related to blood glucose concentration.
  • the user does not have a receiving device or is not allowed to use the receiving device to view blood glucose concentration data and/or input calibration; meanwhile, use the first device 100 (glucose meter) to intermittently check personal blood glucose conditions.
  • the first device 100 sends at least one group of first data groups to the second device 200 (the receiving device or electronic device included in the second device 200) through the first network; each group of first data groups Contains the blood glucose concentration measured by the first device 100 and its corresponding measurement time.
  • the receiving device or the electronic device calculates the second value of the first time period according to the measurement time in the original value or the data at the closest to the target measurement time, the data in the first data group at the corresponding measurement time, and the first sensitivity at the previous time. Two sensitivity.
  • the last time is before the measurement time and the time difference with the measurement time is less than one display cycle; the first sensitivity calculates the blood glucose concentration data in the first time period; the start time of the first time period is the measurement time, and the end time is the following A time to receive the first data set.
  • the complete second blood glucose data set in the monitoring process can be used for generating user reports.
  • the second sensitivity (represented by the ordinate) obtained in multiple time periods in each blood glucose
  • the measurement time of the instrument is dynamically adjusted.
  • the abscissa represents time, and the ordinate represents the original value (only the curve corresponding to the original value) or blood glucose concentration (other curves).
  • the second Sensitivity (determined based on data such as the first data set) and original value, can obtain the second blood glucose concentration group of multiple time periods, and compare it with the unadjusted CGM blood glucose concentration group automatically generated by the second device 200 . It can be determined that the adjusted second blood glucose concentration data set is closer to the user's real glucose level than the unadjusted CGM blood glucose concentration set, and the second blood glucose concentration data set adjusted by the method of the present application is more medical. reference.
  • the analyte concentration data generation device includes: a first data set acquisition module 10, configured to acquire a first data set, the first data set is acquired by the first device 100, the first data set includes the first analyte concentration data and its corresponding target Measure the moment.
  • the second data set acquisition module 20 is configured to acquire a second data set, the second data set includes the original value related to the analyte concentration and its time stamp acquired by the second device 200 .
  • the proportional relationship determination module 30 is configured to determine a proportional relationship based on the first data set and the second data set; the proportional relationship is the ratio of the original value at the target moment to the first analyte concentration data at the target measurement moment, so The target time is the target measurement time or the time closest to the target measurement time.
  • the weight value determination module 40 is configured to determine a first weight value and a second weight value based on the rate of change of the proportional relationship relative to the first sensitivity; the first sensitivity is the sensitivity at the first moment, and the first The time is located between the last measurement time and the target measurement time.
  • the sensitivity updating module 50 is configured to determine a second sensitivity based on the proportional relationship and its corresponding first weight value, and the first sensitivity and its corresponding second weight value;
  • the analyte concentration data generation module 60 is configured to generate a second analyte concentration data set for a first time period based on the second sensitivity and the second data set, and the first time period starts from the target measurement moment Continuing to a second moment, the second moment is located after the target measurement moment.
  • the analyte can be used for each target measurement moment.
  • the concentration data generating device is used, the second sensitivity of each sub-time period in the second time period is obtained based on the first data set at each target measurement moment, the second data set and the first sensitivity before each target measurement moment, Thus, a second blood glucose concentration data set for each sub-time period (for example, one of the sub-time periods may be the first time period) is generated.
  • the raw values include data collected by the second device 200 for determining the second analyte concentration data set.
  • the raw value includes a current value used to determine the second analyte concentration data set, and the current value generates an electrochemical reaction between the sensor in the second device 200 and a specific solution obtained afterwards; the specific solution is the solution in which the sensor is located.
  • the weight value determining module 40 is configured to: use the following formula to determine the rate of change R of the proportional relationship relative to the first sensitivity:
  • the first weight value and the second weight value are determined by using the following formula:
  • I represents the original value collected at the target measurement time
  • G represents the first analyte concentration data at the target measurement time
  • S old represents the first sensitivity
  • the first sensitivity is used to determine the last measurement
  • the third analyte concentration data set at time t represents the target time difference between the generation time of the first sensitivity and the target measurement time
  • f(R, t) represents a function with R and t as parameters
  • the function represents the second weight
  • the values are related to R and t
  • a represents the first weight value corresponding to the proportional relationship
  • the second weight value is an initial preset value, zero or an empirical preset value.
  • the first sensitivity is a preset sensitivity.
  • the first moment is the previous moment before the target measurement moment
  • the first time difference between the target measurement moment and the first moment is for the second device 200 to obtain the original value the sampling period.
  • the sensitivity update module 50 is configured to: use the following formula to determine the second sensitivity:
  • S represents the second sensitivity
  • the analyte concentration data generation module 60 is configured to: divide the second data group corresponding to each display cycle of the first time period by the second sensitivity respectively to generate the first time period
  • the display period is a period for the second device 200 to display the second analyte concentration data set.
  • the device further includes an output module, and the output module is configured to: display the second analyte concentration data set according to the display period.
  • the display period is greater than or equal to 1 minute.
  • the first data group is obtained after pre-screening based on preset rules.
  • the preset rule includes: in response to determining that there are multiple groups of different first devices 100 , screening out a set of data of a first device 100 with the highest trustworthiness as the first data group, the trustworthiness being based on the The model of the first device 100 or the regular quality control maintenance records are determined.
  • the second moment is located at or before the third moment, the third moment is the next measurement moment after the target measurement moment, and between the third moment and the second moment The second time difference between them is greater than or equal to one display period.
  • the second moment is located at or before the fourth moment, and the fourth moment is the end measurement moment after the target measurement moment.
  • the device also includes:
  • At least one display module configured to enable visualization of the second analyte concentration data set
  • At least one acquisition module is configured to acquire the first data set and the second data set.
  • the present application also provides a system for monitoring the concentration of an analyte, comprising:
  • a sensor configured to acquire a second data set
  • a mobile computing device comprising:
  • a receiving device configured to receive the first data group and the second data group
  • a memory for storing data comprising the first data set and the second data set
  • a processor is used to process the data, and a software application program includes instructions stored in the memory, and when executed, the instructions implement the method for generating analyte concentration data provided by the above-mentioned methods.
  • FIG. 6 illustrates a schematic diagram of the physical structure of an electronic device, which may include: a processor (processor) 610, a communication interface (Communications Interface) 620, a memory (memory) 630, and a communication bus 640, wherein the processor 610, The communication interface 620 and the memory 630 communicate with each other through the communication bus 640 .
  • Processor 610 may invoke logic instructions in memory 630 to perform the analyte concentration data generation method.
  • the logic instructions in the above-mentioned memory 630 may be implemented in the form of software functional units and when sold or used as an independent product, may be stored in a computer-readable storage medium.
  • the computer software product is stored in a storage medium, including several
  • the instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the multiple embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disk or optical disc and other media that can store program codes. .
  • the present application also provides a computer program product
  • the computer program product includes a computer program stored on a non-transitory computer-readable storage medium
  • the computer program includes program instructions, and when the program instructions are executed by a computer When executed, the computer can execute the method for generating analyte concentration data provided by the above-mentioned multiple methods.
  • the present application also provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is implemented to perform the method for generating analyte concentration data provided by the above-mentioned multiple methods .
  • the device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative effort.

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Abstract

本申请提供一种分析物浓度数据生成方法和装置、监测分析物浓度的系统，其中所述方法包括：获取第一数据组，第一数据组包括第一分析物浓度数据及第一分析物浓度数据对应的目标测量时刻；获取第二数据组；基于所述第一数据组和第二数据组，确定比例关系；基于比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值；基于比例关系及比例关系对应的第一权重值、以及第一灵敏度及第一灵敏度对应的第二权重值，确定出第二灵敏度；基于第二灵敏度及第二数据组，生成第一时间段的第二分析物浓度数据组。

Description

分析物浓度数据生成方法和装置、监测分析物浓度的系统
本申请要求在2022年2月10日提交中国专利局、申请号为202210123121.X的中国专利申请的优先权，该申请的全部内容通过引用结合在本申请中。
技术领域
本申请涉及连续分析物浓度数据生成领域，例如涉及一种分析物浓度数据生成方法和装置、监测分析物浓度的系统。
背景技术
一些疾病需要对分析物浓度进行连续监测，例如糖尿病是由于胰腺不能产生胰岛素而引起血糖浓度数据异常的疾病(1型糖尿病)或胰岛素分泌和作用效率低下(2型糖尿病)。受糖尿病影响的用户需要全天监测血糖(Blood Glucose，BG)水平，以控制血糖并采取对策，以使其尽可能保持在正常范围内。糖尿病用户被迫服用外源性胰岛素输注或药物，其时间表和剂量是根据BG测量值确定得出的。
根据当前的测量标准，可通过两种主要方式收集BG测量值：i)在日常生活中通过毛细血管扎指头、以取出指血，并用试纸测量，即每天最多4-5次自我监测血糖；ii)在住院临床试验中，通过指血关联的血糖仪进行测量。这两个BG监视系统都相当准确。但是，无法连续、动态地监测用于的血糖浓度变化水平，只能偶尔进行血液采样，用户的葡萄糖浓度快速波动可能会无法监测到。
在过去的数十年中，已经引入了连续葡萄糖监测(Continuous Blood Glucose monitoring，CGM)系统。与BG测量系统不同，这些CGM设备可测量组织间液中的血糖，从而降低了扎指头侵入人体的频率，并允许连续多天每1-5分钟可视化实时血糖浓度值。CGM系统提供了更完整的葡萄糖波动图，证明了使用BG系统无法检测到的关键事件。但是，CGM系统仍然存在不准确性。实际上，与BG测试的结果相比，CGM测试的结果有时会出现瞬时或系统的低估/高估。CGM的时间分辨率(每1-5分钟显示)比BG高得多，但有时会表现出对真实血糖浓度的系统性低估/高估。显然，CGM的准确性不足会影响其临床应用，目前，在研究界已认识到CGM的准确性对临床实际应用时存在的瓶颈。
发明内容
本申请提供一种分析物浓度数据生成方法和装置、监测分析物浓度的系统，用以改善相关技术中存在的技术缺陷。
本申请提供一种分析物浓度数据生成方法，包括：
获取第一数据组，所述第一数据组由第一设备获取，所述第一数据组包括第一分析物浓度数据及第一分析物浓度数据对应的目标测量时刻；
获取第二数据组，所述第二数据组包括由第二设备获取的、与分析物浓度相关的原始值及原始值的时间戳；
基于所述第一数据组和第二数据组，确定比例关系；所述比例关系为目标时刻的原始值与目标测量时刻的第一分析物浓度数据的比值，所述目标时刻为目标测量时刻或最接近所述目标测量时刻处的时刻；
基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值；所述 第一灵敏度为第一时刻的灵敏度，所述第一时刻位于上一个测量时刻与所述目标测量时刻之间；
基于所述比例关系及比例关系对应的第一权重值、以及所述第一灵敏度及第一灵敏度对应的第二权重值，确定出第二灵敏度；
基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组，所述第一时间段从所述目标测量时刻开始并延续至第二时刻，所述第二时刻位于所述目标测量时刻之后。
本申请还提供一种分析物浓度数据生成装置，包括：
第一数据组获取模块，设置为获取第一数据组，所述第一数据组由第一设备获取，所述第一数据组包括第一分析物浓度数据及第一分析物浓度对应的目标测量时刻；
第二数据组获取模块，设置为获取第二数据组，所述第二数据组包括由第二设备获取的、与分析物浓度相关的原始值及原始值的时间戳；
比例关系确定模块，基于所述第一数据组和第二数据组，确定比例关系；所述比例关系为目标时刻的原始值与目标测量时刻的第一分析物浓度数据的比值，所述目标时刻为目标测量时刻或最接近所述目标测量时刻处的时刻；
权重值确定模块，设置为基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值；所述第一灵敏度为第一时刻的灵敏度，所述第一时刻位于上一个测量时刻与所述目标测量时刻之间；
灵敏度更新模块，设置为基于所述比例关系及比例关系对应的第一权重值、以及所述第一灵敏度及第一灵敏度对应的第二权重值，确定出第二灵敏度；
分析物浓度数据生成模块，设置为基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组，所述第一时间段从所述目标测量时刻开始并延续至第二时刻，所述第二时刻位于所述目标测量时刻之后。
本申请还提供一种监测分析物浓度的系统，包括：传感器，无线发射器，以及移动计算装置；
传感器，设置为获取第二数据组；
无线发射器，其用以发射所述第二数据组；
移动计算装置包括：接收设备，存储器，处理器，以及软件应用程序；
接收设备，设置为接收第一数据组和第二数据组；
存储器，设置为存储包含所述第一数据组和第二数据组的数据；
处理器，设置为处理所述数据；
软件应用程序包含存储于所述存储器中的指令，所述指令当由所述处理器执行时实现所述的分析物浓度数据生成方法。
本申请还提供一种电子设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，所述处理器执行所述程序时实现所述的分析物浓度数据生成方法。
本申请还提供一种非暂态计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现如上述任一种所述的分析物浓度数据生成方法。
附图说明
图1是本申请实施例所涉及的一种实施环境的结构示意图。
图2是本申请提供的分析物浓度数据生成方法的流程示意图。
图3是本申请提供的分析物浓度数据生成方法中的不同时间段的灵敏度的示意图。
图4是本申请提供的分析物浓度数据生成方法实施后与未实施分析物浓度数据生成方法的血糖浓度对比示意图。
图5是本申请提供的分析物浓度数据生成装置的结构示意图。
图6是本申请提供的电子设备的结构示意图。
具体实施方式
在通过利用少量、稀疏但准确的参考样本(例如，可以是通过血糖仪获得的BG值)对频繁、连续的测量的分析物浓度数据进行优化时，未考虑到以下因素：i)持续分析物浓度监测过程中发生灵敏度衰减，但目前的优化方式均是采用参考样本对连续分析物浓度数据测量设备输出的分析物浓度数据进行校准，且校准时未考虑测量时刻之前的灵敏度，无法保持校准前后灵敏度的一致性，可能会因不良参考样本等原因，生成不合理、突变分析物浓度数据，引起经校准后，连续分析物浓度数据测量设备输出的数据更加不能够反映每个原始值实测时刻真实分析物浓度数据的后果。ii)在一种情况下，仍对连续分析物浓度数据测量设备测量的数据进行实时输出，导致输出的数据中存在不适当或不合理的误差数据(因未采用参考样本进行调整)，并不一定能够体现用户的真实分析物浓度水平，导致无法实际应用于临床，甚至误差数据会误导专家、用户，进一步影响诊断和治疗效果；在另一种情况下，用户佩戴的连续分析物浓度数据测量设备持续采集与分析物浓度相关的原始值，但由于操作不便、避免以上情况的误差数据等原因，用户没有接收设备或不被允许使用接收设备查看分析物浓度数据，只能间断的查看个人的分析物浓度情况(少量、稀疏但准确的参考样本)，且无法生成一个连续的、能够体现用户的真实分析物浓度水平的报告。
本申请中的分析物可以是血糖、血酮，乙醇，乳酸，肌酐(与肾功能相关的分析物)，尿酸，引起心衰的分析物-脑钠肽(Brain Natriuretic Peptide，BNP)，多种感染源分析物(如C反应蛋白、降钙素原、血清淀粉样蛋白A、白介素6等)，等等。每种分析物都可以具有连续测浓度的设备，以及更精准的非连续测浓度的设备。以下实施例中，以血糖浓度作为示例进一步进行说明，其他分析物的浓度数据生成、监测方式同血糖。
请参考图1，其示出了本申请多个实施例所涉及的一种实施环境的结构示意图。该实施环境包括：第一设备100和第二设备200，和/或服务器300。
第一设备100可以是一种具备血糖测试能力的设备，如通过采集指血的方式测试血糖浓度数据的血糖仪、血糖计、血糖监测设备、血糖测试设备等。
第二设备200可以是连续动态血糖监测(CGM)系统，CGM系统被配置为连续监测人的血糖。CGM系统可以配置有CGM传感器，例如，该CGM传感器，其皮下插入人的皮肤并检测指示人的血糖的分析物。CGM系统可以连续地基于检测到的分析物产生葡萄糖测量。如本文所用，术语“连续”是接近连续的，使得连续葡萄糖监测以CGM系统的资源(例如，
电池寿命，处理能力，通信能力等)支持的时间间隔产生测量，连续监测的血糖浓度数据不需要手动交互，例如扎手指并采集指血来获得。通过连续监测葡萄糖水平，CGM系统不仅允许用户对其治疗做出更好的知情决策，而且还继续监测葡萄糖水平，同时允许他们利用扎手指并采集指血的方式对CGM系统进行校准。CGM系统可以包含具备数据处理能力的接收设备，接收设备可以如手机、平板电脑、电子书阅读器、MP3(Moving Picture Experts Group Audio Layer III)播放器、MP4(Moving Picture Experts Group Audio Layer IV)播放器、膝上型便携计算机和台式计算机等等。接收设备中可以安装有应用程序客户端，或者安装有浏览器，通过浏览器访问应用程序的网页客户端。本申请实施例将应用程序客户端和网页客户端统称为客户端，下文不再特别声明。
服务器300可以是一台近端或远端服务器，或者由若干台服务器组成的服务器集群，
或者是一个云计算服务中心。当第二设备200和服务器300同时处理本申请相关业务时，服务器300可设置为与第二设备200交互提供本申请相关业务。服务器300是与客户端对应的服务器，两者可以结合实现客户端提供的多项功能，通常由互联网服务商来设立。
第二设备200与第一设备100之间可以通过无线网络或者有线网络相连实现数据传输；第二设备200与第一设备100之间也可以通过无线网络或者有线网络分别与服务器300相连实现数据传输。
下面结合图2描述本申请的一种分析物浓度数据生成方法，该方法包括：S1、获取第一数据组，所述第一数据组由第一设备100获取，所述第一数据组包括第一分析物浓度数据及第一分析物浓度数据对应的目标测量时刻。
第一设备100可能只有一种设备，也可能是多种不同的品牌或同一品牌的不同型号的设备，每一组第一数据组对应于一种品牌或一种型号。或者，每一组第一数据组是同一种品牌或一种型号在某一个特定的目标测量时刻采集的数据，其包括第一血糖浓度数据及其对应的目标测量时刻。
S2、获取第二数据组，所述第二数据组包括由第二设备200获取的、与分析物浓度相关的原始值及其时间戳。
所述用户与所述第二设备200是预先相关联的，第一设备100用于校准的第一数据组与第二设备200对应于同一个用户。第一设备100可以关联多个用户，相应的，将每个用户的数据分别传输给每一个用户所预先相关联的第二设备200。在一种情况下，每一组第一数据组的可信任度较高，可以限定第一设备100是通过采集指血、非连续的方式测试第一数据组的。一种情况下，当血糖浓度相关的原始值为异常状态时(即，目标测量时刻或最接近所述目标测量时刻处的原始值为异常状态)，此时暂停生成第二血糖浓度数据组，在血糖浓度相关的原始值为正常状态情况下，继续生成第二血糖浓度数据组。即，由于状态为异常时，可以认为此时生成第二血糖浓度数据组是没有意义的，第二设备200应处于正常工作状态，则进行生成第二血糖浓度数据组。
S3、基于所述第一数据组和第二数据组，确定比例关系；所述比例关系为目标时刻的原始值与目标测量时刻的第一分析物浓度数据的比值，所述目标时刻为目标测量时刻或最接近所述目标测量时刻处的时刻。
在一种情况下，第一数据组包含了目标测量时刻这个时间值，以及目标测量时刻的第一血糖浓度数据，也就是带有时间戳的第一血糖浓度数据。当所述目标时刻为目标测量时刻时，所述第二设备200在目标测量时刻的原始值可以是目标测量时刻的电流值。当目标测量时刻不存在原始值时(因原始值是按一定周期采集(采样周期)的连续值，采样周期一般在几秒至几分钟，存在目标测量时刻不存在原始值的可能性)，此时可以选取最接近所述目标测量时刻处的原始值。目标时刻也可以选取最接近目标测量时刻处的原始值，例如选取目标测量时刻预设范围内的时刻处的原始值，预设范围可以是目标测量时刻的前后15秒以内，例如可以选取位于目标测量时刻前三秒处或后十五秒处的原始值。当同时存在位于目标测量时刻前三秒处和后十五秒处的原始值，可以选择位于目标测量时刻前三秒处的原始值，也可以选取与目标测量时刻的时间差小于一个采样周期处的时刻的原始值，用于确定比例关系。目标时刻越是接近目标测量时刻的原始值，其确定比例关系的参考性越好，因此选取目标测量时刻或最接近所述目标测量时刻处的原始值。利用目标测量时刻或最接近所述目标测量时刻处的原始值与目标测量时刻的第一血糖浓度数据的比值，可以进一步确定出目标测量时刻及目标测量时刻以后的第二灵敏度。
S4、基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值；所述第一灵敏度为第一时刻的灵敏度，所述第一时刻位于上一个测量时刻与所述目标测量时刻之间。
在一种情况下，第一时刻为目标测量时刻之前的时刻，可以为目标测量时刻之前的采集原始值的上一个采样周期中具有第一灵敏度的某一时刻。基于比例关系相对于第一灵敏度的变化率，可以确定比例关系相对于第一灵敏度的变化大小，进而根据该变化率来确定出第一权重值、第二权重值。第一权重值是对应于比例关系的，第二权重值是对应于第一灵敏度的。每一次执行分析物浓度数据生成方法时，都基于变化率来动态调整第一权重值、第二权重值。可以既考虑到每一次目标测量时刻的第一数据组对第二灵敏度的影响，也能够兼顾到上一个测量时刻到本次目标测量时刻之间的第一灵敏度。例如，当比例关系与目标测量时刻之间的变化率较大时，可以加大第二权重值，此时需要更多的考虑与第一灵敏度保持一致性，不发生灵敏度的突变；当比例关系与目标测量时刻之间的变化率较小时，可以加大第一权重值，此时需要更多的考虑由本次目标测量时刻得到的比例关系，以进一步优化第二变化率；第一权重值、第二权重值可以相同，也可以不同。
S5、基于所述比例关系及所述比例关系对应的第一权重值、以及所述第一灵敏度及所述第一灵敏度对应的第二权重值，确定出第二灵敏度。
通过赋予比例关系、第一灵敏度以动态调整后的第一权重值、第二权重值，所确定出的第二灵敏度，能够考虑由本次目标测量时刻得到的比例关系可以为目标测量时刻之前的采集原始值的上一个采样周期中具有第一灵敏度的某一时刻，且能够同时兼顾与第一灵敏度保持一致性。
S6、基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组，所述第一时间段从所述目标测量时刻开始并延续至第二时刻，所述第二时刻位于所述目标测量时刻之后。
在一种情况下，基于所述第二灵敏度及所述第二数据组(即，第一时间段的与血糖浓度相关的原始值及其时间戳)，生成第一时间段的第二血糖浓度数据组，第二血糖浓度数据组包括用于显示的血糖浓度值及其时间戳。采用以上方式，可以消除由于第二设备200持续血糖监测过程中发生灵敏度衰减、引起不能够反映每个原始值实测时刻真实血糖浓度数据导致的误差。
在一种情况下，第二设备200不实时输出血糖浓度数据，避免实时输出的数据中存在不适当或不合理的误差数据，进一步避免误差数据误导专家、用户而导致的影响诊断和治疗效果的情形。
在一种情况下，当一个更长的第二时间段(可以包含所述第一时间段)中，具有多个位于不同时间的目标测量时刻，则可以对每一个目标测量时刻执行以上S1至S6。基于每一个目标测量时刻的第一数据组、第二数据组以及每一个目标测量时刻之前的第一灵敏度，得到第二时间段中每一个子时间段的第二灵敏度，从而生成每一个子时间段(例如，其中一个子时间段可以是所述第一时间段)的第二血糖浓度数据组。每一个相对于第二灵敏度的上一个第一灵敏度可以不断以一定的权重被继承下去，每一个时间段的第二血糖浓度数据组的生成，都能够或多或少的考虑到最初始的灵敏度、以及位于每一个第一时间段之前、位于多个不同时刻的灵敏度。每一个子时间段的第二血糖浓度数据组结合在一起，可以形成第二时间段的第二血糖浓度数据集，该第二血糖浓度数据集可以形成第二时间段的整体报告，以生成一个连续的、能够体现用户的真实血糖浓度水平的报告。该整体报告可以更合理地还原用户的真实血糖浓度情况，可以达到临床实际应用效果。
在一种情况下，本申请的执行主体是第二设备200或服务器300等其他具有数据处理能力的设备。本申请结合了用户的由第一设备获取的第一数据组和由第二设备获取的第二数据组，以确定比例关系。其中，比例关系为所述目标测量时刻或最接近所述目标测量时刻处的原始值与第一血糖浓度数据的比值。基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值，进而确定出用于生成第一时间段的第二血糖浓度数据组的第二灵敏度。该第二灵敏度能够考虑由本次目标测量时刻对应的比例关系，且能够同时兼顾与第一灵敏度保持一致性，避免生成不合理、突变的第二灵敏度。基于动态调整后的第二灵敏度，可以保持每个时间段的第二灵敏度更合理地还原每个原始值实测时刻的真实情况。由此生成的第二灵敏度非常贴近每个原始值实测时刻的真实灵敏度，可以在目标测量时刻之后的第一时间段使得第二设备200生成更精准的第二血糖浓度数据组，实现了第二设备200的高灵敏度、高测量精准度的输出数据。本申请可以消除由于第二设备200持续血糖监测过程中发生灵敏度衰减、引起不能够反映每个原始值实测时刻真实血糖浓度数据导致的误差，还可以直接输出经动态调整、更精准的第二血糖浓度数据组，避免因第二设备200输出未经第一数据组调整的数据带来的对用户的误导。
在一个实施例中，所述原始值包括所述第二设备200采集的用于确定所述第二分析物浓度数据组的数据。例如，所述原始值包括用于确定所述第二分析物浓度数据组的电流值，所述电流值为所述第二设备200中的传感器与特定溶液(比如，用户体内的血液、组织间液或其他的溶液等)之间产生电化学反应后所获得的；所述特定溶液为所述传感器所处的溶液。
在一个实施例中，所述基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值，包括：利用以下公式，确定所述比例关系相对于第一灵敏度的变化率R：
Figure PCTCN2022100103-appb-000001
利用以下公式，确定出所述第一权重值、第二权重值：
b＝f(R，t)
a＝1-b
其中，I表示所述目标测量时刻所采集的原始值，G表示所述目标测量时刻的第一分析物浓度数据，S old表示第一灵敏度，所述第一灵敏度用于确定所述上一个测量时刻的第三分析物浓度数据组，t表示第一灵敏度的生成时刻和所述目标测量时刻的目标时间差，f(R，t)表示以R和t为参数的函数，该函数表示第二权重值与R、t是相关的，a表示所述比例关系对应的第一权重值，b表示所述第一灵敏度对应的第二权重值，其中，a、b满足：a+b＝100％。
在一种情况下，根据第二设备200所包含的传感器的性质，在传感器的有效工作时间内的不同时间段内的每分钟灵敏度变化率存在最大值。所述比例关系较大(大于比例阈值)时，可能是由于人为操作导致的第一设备100的第一数据组在目标测量时刻的测量出现错误或者偏差，此时可以加大b，减小a，或者可以置a＝0，b＝100％，以消除这种错误或误差。
第一灵敏度对于新生成的第二灵敏度存在一定的可利用价值，可以考虑第一灵敏度并给予其第二权重值，可以适当减小第二灵敏度与第一灵敏度之间的差距，转换灵敏度时更平滑，不至于在第一时间段产生数据突变。如果需要考虑比例关系更多的话，可以设置第一权重值大于第二权重值，如果需要考虑参照第一灵敏度更多的话，可以设置第一权重值小于或等于第二权重值，如果考虑比例关系和第二灵敏度同样重要的话，也可以设置第一权重值等于第二权重值。例如，第一权重值、第二权重值可以根据比例关系相对于第一灵敏度的变化率、 第一灵敏度的生成时刻和所述目标测量时刻的目标时间差来设置。
在一个实施例中，所述第二权重值为初始预设值、零或经验预设值。
即，在一种情况下，b是可动态调整的，b的初始值可以为0或者初始预设值、经验预设值。
在一个实施例中，所述第一灵敏度为预设灵敏度。
在一种情况下，预设灵敏度可以是传感器的初始灵敏度，或是基于本申请的方法所确定出、满足一定预设条件的预设灵敏度。
在一个实施例中，所述第一时刻为所述目标测量时刻之前的上一个时刻，所述目标测量时刻与第一时刻之间的第一时间差为所述第二设备200获取所述原始值的采样周期。
在一种情况下，第一时刻为所述目标测量时刻之前的上一个时刻，以确保第一灵敏度采用的是最接近目标测量时刻的上一个时刻的灵敏度，更具有参考意义。
在一个实施例中，所述基于所述比例关系及其对应的第一权重值、以及所述第一灵敏度及其对应的第二权重值，确定出第二灵敏度，包括：利用以下公式确定出所述第二灵敏度：
Figure PCTCN2022100103-appb-000002
其中，S表示第二灵敏度。
一种情况下，第一灵敏度作用于第一灵敏度生成时刻到第一灵敏度的下一个灵敏度(第二灵敏度)生成时刻之间的原始值；第二灵敏度作用于第一时间段，即第二灵敏度生成时刻到第二灵敏度的下一个灵敏度(第三灵敏度)生成时刻之间的原始值。
在一个实施例中，所述基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组，包括：将第一时间段的每个显示周期对应的第二数据组分别与所述第二灵敏度相除，生成第一时间段的第二分析物浓度数据组，所述显示周期为第二设备200对所述第二分析物浓度数据组的进行显示的周期。
每个显示周期对应的原始值除以第二灵敏度，可以生成第一时间段的第二血糖浓度数据组。
在一个实施例中，所述基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组生成第一时间段的第二分析物浓度数据组之后，包括：按所述显示周期，对第二分析物浓度数据组进行显示。
在一种情况下，在生成第二血糖浓度数据组之后，可以将第二血糖浓度数据组输出并按照显示周期进行显示，该输出和显示的数据均是更接近用户真实的血糖水平的数据。所述显示周期大于或等于1分钟。显示周期可以为2-3分钟，一般地，CGM系统对数据显示的时间间隔，也就是显示周期是2-3分钟。
在一个实施例中，所述第一数据组是基于预设规则进行预先筛选后得到的。所述预设规则包括：当存在多组不同的第一设备100时，筛选出可信任度最高的一种第一设备100的一组数据作为第一数据组，所述可信任度是基于所述第一设备100的型号或定期质控维护记录确定的。
在一种情况下，筛选出可信任度最高的一种第一设备100的一组数据作为第一数据组，可能是筛选出某一种可信任最高的品牌或型号的血糖仪。第一设备100可以指多种不同的品牌或同一品牌的不同型号的设备。当使用的是不同品牌的血糖仪，可以选择该用户历史使用的血糖仪所获取的数据。例如，同一个用户在血糖监测过程中，每一次校准用的可以是同一种第一设备100；在多种设备时，选一种特定的设备，也可以减小误差。血糖仪一般是需要定期校准质控维护的，且保留有维护记录，维护记录上可以有一些测试精准度等 数据，可以基于维护记录来确认可信任度。如果长时间未做校准质控维护，未查到校准质控维护记录的设备的可信任度较低，则不采用此血糖仪进行分析物浓度数据生成，一般采用的血糖仪的可信任度是大于CGM的。
在一个实施例中，所述第二时刻位于第三时刻或第三时刻之前，所述第三时刻为所述目标测量时刻之后的下一个测量时刻，且所述第三时刻和第二时刻之间的第二时间差大于或等于一个所述显示周期。
在一种情况下，所述第二时刻位于第三时刻，即，第一时间段(也就是第二灵敏度的应用时间段)从所述目标测量时刻持续到下一个测量时刻。在另一种情况下，所述第二时刻位于第三时刻之前，即，第一时间段(也就是第二灵敏度的应用时间段)从所述目标测量时刻持续到下一个测量时刻之前的某一时刻。某一时刻的确定可以基于目标时间差，例如目标时间差大于12小时，则从上述某一时刻之后，可能有其他更新的灵敏度可以使用等情况。也就是说，可以基于传感器性能的衰减特性，来设定第二灵敏度的有效期。
在一个实施例中，所述第二时刻位于第四时刻或第四时刻之前，所述第四时刻为所述目标测量时刻之后的结束测量时刻。
在一种情况下，第二时刻位于第四时刻，即，第一时间段(也就是第二灵敏度的应用时间段)从所述目标测量时刻持续到结束测量时刻(可以为CGM对原始值的结束测量时刻)。在另一种情况下，所述第二时刻位于第四时刻之前，即，第一时间段(也就是第二灵敏度的应用时间段)从所述目标测量时刻持续到结束测量时刻之前的某另一时刻。某另一时刻的确定也可以基于目标时间差，例如目标时间差大于12小时，则从上述某另一时刻之后，可能有其他更新的灵敏度可以使用等情况。也就是说，可以基于传感器性能的衰减特性，来设定第二灵敏度的有效期。
在一个实施例中，所述方法还包括：
利用至少一显示模块实现所述第二分析物浓度数据组的可视化；
和/或，利用至少一采集模块获取所述第一数据组和第二数据组。
为了进一步说明本申请的分析物浓度数据生成方法，结合不同的实施场景，提供以下示例实施例。
在一种场景下，第一灵敏度生成于1号中午12:00，在第一种情况中，两天后的3号中午12:01(目标测量时刻)，另一个由血糖仪获取的第一血糖浓度数据出现，中间相隔大于48小时。此时计算3号中午12：01的原始值与第一血糖浓度数据的比例关系，并计算比例关系与第一灵敏度之间的变化率。
Figure PCTCN2022100103-appb-000003
R会影响到本次比例关系和上一次的第一灵敏度的加权值，R越大，表示本次比例关系与上一个灵敏度的差距越大。但是由于传感器的性质中，灵敏度的变化不会存在突变或一定时间内的大幅度变化，因此需要考虑本次的比例是否受噪声影响。为了限制第二血糖浓度数据组的突变和考虑传感器灵敏度的相互影响性，第二灵敏度为第一灵敏度和当前比例关系的加权平均。
上一次灵敏度在本次灵敏度计算中的影响程度受时间和变化率影响，时间为上一次灵敏度的生成时间和本次比例关系生成时间的时间差。如果短时间内发生大于阈值的较大的变化，则认为本次比例关系受噪声的影响较大，因此上一个灵敏度的影响因子b较大；b的确定基于R与t的综合因素，因此可以记为：
b＝f(R，t)
a＝1-b
一种得到b的预设方式可以如下表1所示。
表1：得到b的预设方式
Figure PCTCN2022100103-appb-000004
由表1可知，由于中间相隔大于48小时，且R处于0-10％时，可以设置b＝0，此时a＝1。
在另一种场景下，用户佩戴的第二设备200持续的采集与血糖浓度相关的原始值。但是由于操作不便的原因，用户没有接收设备或不被允许使用接收设备查看血糖浓度数据和/或输入校准；同时，使用第一设备100(血糖仪)间断的查看个人的血糖情况。
当监测结束后，第一设备100将至少一组第一数据组通过第一网络发送到第二设备200(第二设备200所包含的接收设备或电子设备)中；每一组第一数据组包含第一设备100测量的血糖浓度和其对应的测量时刻。接收设备或电子设备根据原始值中的测量时刻或最接近所述目标测量时刻处的数据、第一数据组中对应的测量时刻的数据和上一个时刻的第一灵敏度计算第一时间段的第二灵敏度。
其中，上一个时刻在测量时刻之前且与测量时刻的时间差值小于一个显示周期；第一灵敏度计算第一时间段的血糖浓度数据；第一时间段的开始时刻为测量时刻，结束时刻为下一个接收第一数据组的时间。当所有的可用的第一数据组均使用完毕后，得到监测过程中的完整的第二血糖数据组可用于用户报告的生成。
参见图3，在一种场景下，基于本申请实施例提供的分析物浓度数据生成方法，基于第一数据组，多个时间段所得到的第二灵敏度(由纵坐标表示)在每一次血糖仪的测量时刻是经过动态调整后得到的。
参见图4，横坐标表示时间，纵坐标表示原始值(仅原始值对应的曲线)或血糖浓度(其他曲线)，在一种场景下，利用图3中的多个时间段所得到的第二灵敏度(基于第一数据组等数据所确定的)和原始值，可以得到多个时间段的第二血糖浓度组，通过与未经过调整、第二设备200自动生成的CGM血糖浓度组进行对比。可以确定的是，调整后的第二血糖浓度数据组相较于未调整的CGM血糖浓度组更能接近用户的真实葡萄糖水平，经过本申请的方法调整后的第二血糖浓度数据组更具备医学参考性。
参见图5，下面对本申请提供的分析物浓度数据生成装置进行描述，下文描述的分析物浓度数据生成装置与上文描述的分析物浓度数据生成方法可相互对应参照，所述分析物浓度数据生成装置包括：第一数据组获取模块10，设置为获取第一数据组，所述第一数据组由第一设备100获取，所述第一数据组包括第一分析物浓度数据及其对应的目标测量时刻。
第二数据组获取模块20，设置为获取第二数据组，所述第二数据组包括由第二设备200获取的、与分析物浓度相关的原始值及其时间戳。
比例关系确定模块30，设置为基于所述第一数据组和第二数据组，确定比例关系；所述比例关系为目标时刻的原始值与目标测量时刻的第一分析物浓度数据的比值，所述目标时刻 为目标测量时刻或最接近所述目标测量时刻处的时刻。
权重值确定模块40，设置为基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值；所述第一灵敏度为第一时刻的灵敏度，所述第一时刻位于上一个测量时刻与所述目标测量时刻之间。
灵敏度更新模块50，设置为基于所述比例关系及其对应的第一权重值、以及所述第一灵敏度及其对应的第二权重值，确定出第二灵敏度；
分析物浓度数据生成模块60，设置为基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组，所述第一时间段从所述目标测量时刻延续至第二时刻，所述第二时刻位于所述目标测量时刻之后。
在一种情况下，当一个更长的第二时间段(可以包含所述第一时间段)中，具有多个位于不同时间的目标测量时刻，则可以对每一个目标测量时刻进行使用分析物浓度数据生成装置时，基于每一个目标测量时刻的第一数据组、第二数据组以及每一个目标测量时刻之前的第一灵敏度，得到第二时间段中每一个子时间段的第二灵敏度，从而生成每一个子时间段(例如，其中一个子时间段可以是所述第一时间段)的第二血糖浓度数据组。
在一个实施例中，所述原始值包括所述第二设备200采集的用于确定所述第二分析物浓度数据组的数据。在一个实施例中，所述原始值包括用于确定所述第二分析物浓度数据组的电流值，所述电流值为所述第二设备200中的传感器与特定溶液之间产生电化学反应后所获得的；所述特定溶液为所述传感器所处于的溶液。
在一个实施例中，所述权重值确定模块40设置为：利用以下公式，确定所述比例关系相对于第一灵敏度的变化率R：
Figure PCTCN2022100103-appb-000005
利用以下公式，确定出所述第一权重值、第二权重值：
b＝f(R，t)
a＝1-b
其中，I表示所述目标测量时刻所采集的原始值，G表示所述目标测量时刻的第一分析物浓度数据，S old表示第一灵敏度，所述第一灵敏度用于确定所述上一个测量时刻的第三分析物浓度数据组，t表示第一灵敏度的生成时刻和所述目标测量时刻的目标时间差，f(R，t)表示以R和t为参数的函数，该函数表示第二权重值与R、t是相关的，a表示所述比例关系对应的第一权重值，b表示所述第一灵敏度对应的第二权重值，其中，a、b满足：a+b＝100％。
在一个实施例中，所述第二权重值为初始预设值、零或经验预设值。
在一个实施例中，所述第一灵敏度为预设灵敏度。
在一个实施例中，所述第一时刻为所述目标测量时刻之前的上一个时刻，所述目标测量时刻与第一时刻之间的第一时间差为所述第二设备200获取所述原始值的采样周期。
在一个实施例中，所述灵敏度更新模块50设置为：利用以下公式确定出所述第二灵敏度：
Figure PCTCN2022100103-appb-000006
其中，S表示第二灵敏度。
在一个实施例中，所述分析物浓度数据生成模块60设置为：将第一时间段的每个显示周期对应的第二数据组分别与所述第二灵敏度相除，生成第一时间段的第二分析物浓度数据组， 所述显示周期为第二设备200对所述第二分析物浓度数据组的进行显示的周期。
在一个实施例中，所述装置还包括输出模块，所述输出模块设置为：按所述显示周期，对第二分析物浓度数据组进行显示。
在一个实施例中，所述显示周期大于或等于1分钟。在一个实施例中，所述第一数据组基于预设规则进行预先筛选后得到。所述预设规则包括：响应于确定存在多组不同的第一设备100，筛选出可信任度最高的一种第一设备100的一组数据作为第一数据组，所述可信任度基于所述第一设备100的型号或定期质控维护记录确定。
在一个实施例中，所述第二时刻位于第三时刻或第三时刻之前，所述第三时刻为所述目标测量时刻之后的下一个测量时刻，且所述第三时刻和第二时刻之间的第二时间差大于或等于一个所述显示周期。
在一个优选实施例中，所述第二时刻位于第四时刻或第四时刻之前，所述第四时刻为所述目标测量时刻之后的结束测量时刻。
在一个实施例中，所述装置还包括：
至少一显示模块，被配置为实现所述第二分析物浓度数据组的可视化；
和/或，至少一采集模块，被配置为获取所述第一数据组和第二数据组。
本申请还提供一种监测分析物浓度的系统，包括：
传感器，设置为获取第二数据组；
无线发射器，其用以发射所述第二数据组；
以及
移动计算装置，其包括：
接收设备，设置为接收第一数据组和第二数据组；
存储器，其用以存储包含所述第一数据组和第二数据组的数据；
处理器，其用以处理所述数据，以及软件应用程序，其包含存储于所述存储器中的指令，所述指令执行时实现上述多个方法所提供的分析物浓度数据生成方法。
图6示例了一种电子设备的实体结构示意图，该电子设备可以包括：处理器(processor)610、通信接口(Communications Interface)620、存储器(memory)630和通信总线640，其中，处理器610，通信接口620，存储器630通过通信总线640完成相互间的通信。处理器610可以调用存储器630中的逻辑指令，以执行分析物浓度数据生成方法。
此外，上述的存储器630中的逻辑指令可以通过软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对相关技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请多个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等多种可以存储程序代码的介质。
另一方面，本申请还提供一种计算机程序产品，所述计算机程序产品包括存储在非暂态计算机可读存储介质上的计算机程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，计算机能够执行上述多个方法所提供的分析物浓度数据生成方法。
又一方面，本申请还提供一种非暂态计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现以执行上述多个方法所提供的分析物浓度数据生成方法。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是 或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到多个实施方式可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件。基于这样的理解，上述技术方案本质上或者说对相关技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如ROM/RAM、磁碟、光盘等，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行多个实施例或者实施例的某些部分所述的方法。

Claims (20)

  1. 一种分析物浓度数据生成方法，包括：
    获取第一数据组，所述第一数据组由第一设备获取，所述第一数据组包括第一分析物浓度数据及所述第一分析物浓度数据对应的目标测量时刻；
    获取第二数据组，所述第二数据组包括由第二设备获取的、与分析物浓度相关的原始值及所述原始值的时间戳；
    基于所述第一数据组和所述第二数据组，确定比例关系；所述比例关系为目标时刻的原始值与所述目标测量时刻的所述第一分析物浓度数据的比值，所述目标时刻为目标测量时刻或最接近所述目标测量时刻处的时刻；
    基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值；所述第一灵敏度为第一时刻的灵敏度，所述第一时刻位于上一个测量时刻与所述目标测量时刻之间；
    基于所述比例关系及所述比例关系对应的第一权重值、以及所述第一灵敏度及所述第一灵敏度对应的第二权重值，确定出第二灵敏度；
    基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组，所述第一时间段从所述目标测量时刻开始并延续至第二时刻，所述第二时刻位于所述目标测量时刻之后。
  2. 根据权利要求1所述的方法，其中，所述原始值包括所述第二设备采集的用于确定所述第二分析物浓度数据组的数据。
  3. 根据权利要求2所述的方法，其中，所述原始值包括用于确定所述第二分析物浓度数据组的电流值，所述电流值为所述第二设备中的传感器与特定溶液之间产生电化学反应后所获得的；所述特定溶液为所述传感器所处的溶液。
  4. 根据权利要求1所述的方法，其中，所述基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值，包括：
    利用以下公式，确定所述比例关系相对于第一灵敏度的变化率R：
    Figure PCTCN2022100103-appb-100001
    利用以下公式，确定出所述第一权重值、第二权重值：
    b＝f(R，t)
    a＝1-b
    其中，I表示所述目标测量时刻所采集的原始值，G表示所述目标测量时刻的所述第一分析物浓度数据，S old表示所述第一灵敏度，所述第一灵敏度用于确定所述上一个测量时刻的第三分析物浓度数据组，t表示所述第一灵敏度的生成时刻和所述目标测量时刻的目标时间差，f(R，t)表示以R和t为参数的函数，a表示所述比例关系对应的所述第一权重值，b表示所述第一灵敏度对应的所述第二权重值，其中，a、b满足：a+b＝100％。
  5. 根据权利要求4所述的方法，其中，所述第二权重值为初始预设值、零或经验预设值。
  6. 根据权利要求1所述的方法，其中，所述第一灵敏度为预设灵敏度。
  7. 根据权利要求1所述的方法，其中，所述第一时刻为所述目标测量时刻之前的上一个时刻，所述目标测量时刻与所述第一时刻之间的第一时间差为所述第二设备获取所述原始值的采样周期。
  8. 根据权利要求4所述的方法，其中，所述基于所述比例关系及所述比例关系对应的第 一权重值、以及所述第一灵敏度及所述第一灵敏度对应的第二权重值，确定出第二灵敏度，包括：利用以下公式确定出所述第二灵敏度：
    Figure PCTCN2022100103-appb-100002
    其中，S表示第二灵敏度。
  9. 根据权利要求1所述的方法，其中，所述第一时间段包括至少一个显示周期，所述基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组，包括：
    将所述第一时间段的每个显示周期对应的第二数据组分别与所述第二灵敏度相除，生成所述第一时间段的第二分析物浓度数据组，所述显示周期为所述第二设备对所述第二分析物浓度数据组的进行显示的周期。
  10. 根据权利要求9所述的方法，所述基于所述第二灵敏度及所述第二数据组，生成第一时间段的第二分析物浓度数据组之后，包括：
    按照所述显示周期，对所述第二分析物浓度数据组进行显示。
  11. 根据权利要求10所述的分析物浓度数据生成方法，其中，所述显示周期大于或等于1分钟。
  12. 根据权利要求9所述的方法，其中，所述第一数据组基于预设规则进行预先筛选后得到。
  13. 根据权利要求12所述的方法，其中，所述预设规则包括：响应于确定存在多组不同的第一设备，筛选出可信任度最高的一种第一设备的一组数据作为第一数据组，所述可信任度基于所述第一设备的型号或定期质控维护记录确定。
  14. 根据权利要求9所述的方法，其中，所述第二时刻位于第三时刻或第三时刻之前，所述第三时刻为所述目标测量时刻之后的下一个测量时刻，且所述第三时刻和所述第二时刻之间的第二时间差大于或等于一个显示周期。
  15. 根据权利要求1所述的方法，其中，所述第二时刻位于第四时刻或第四时刻之前，所述第四时刻为所述目标测量时刻之后的结束测量时刻。
  16. 根据权利要求1所述的方法，还包括以下至少之一：
    利用至少一个显示模块实现所述第二分析物浓度数据组的可视化；以及
    利用至少一个采集模块获取所述第一数据组和所述第二数据组。
  17. 一种分析物浓度数据生成装置，包括：
    第一数据组获取模块，设置为获取第一数据组，所述第一数据组由第一设备获取，所述第一数据组包括第一分析物浓度数据及所述第一分析物浓度数据对应的目标测量时刻；
    第二数据组获取模块，设置为获取第二数据组，所述第二数据组包括由第二设备获取的、与分析物浓度相关的原始值及所述原始值的时间戳；
    比例关系确定模块，设置为基于所述第一数据组和所述第二数据组，确定比例关系；所述比例关系为目标时刻的原始值与所述目标测量时刻的所述第一分析物浓度数据的比值，所述目标时刻为目标测量时刻或最接近所述目标测量时刻处的时刻；
    权重值确定模块，设置为基于所述比例关系相对于第一灵敏度的变化率，确定出第一权重值、第二权重值；所述第一灵敏度为第一时刻的灵敏度，所述第一时刻位于上一个测量时刻与所述目标测量时刻之间；
    灵敏度更新模块，设置为基于所述比例关系及所述比例关系对应的第一权重值、以及所述第一灵敏度及所述第一灵敏度对应的第二权重值，确定出第二灵敏度；
    分析物浓度数据生成模块，设置为基于所述第二灵敏度及所述第二数据组，生成第一时 间段的第二分析物浓度数据组，所述第一时间段从所述目标测量时刻开始并延续至第二时刻，所述第二时刻位于所述目标测量时刻之后。
  18. 一种监测分析物浓度的系统，包括：传感器，无线发射器，以及移动计算装置；
    所述传感器，设置为获取第二数据组；
    所述无线发射器，其用以发射所述第二数据组；
    所述移动计算装置包括：接收设备，存储器，处理器，以及软件应用程序；
    所述接收设备，设置为接收第一数据组和第二数据组；
    所述存储器，设置为存储包含所述第一数据组和第二数据组的数据；
    所述处理器，设置为处理所述数据；
    所述软件应用程序包含存储于所述存储器中的指令，所述指令当由所述处理器执行时实现如权利要求1至16任一项所述的分析物浓度数据生成方法。
  19. 一种电子设备，包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述处理器执行所述程序时实现如权利要求1至16任一项所述的分析物浓度数据生成方法。
  20. 一种非暂态计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现如权利要求1至16任一项所述的分析物浓度数据生成方法。
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Publication number Priority date Publication date Assignee Title
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009055736A1 (en) * 2007-10-25 2009-04-30 Dexcom, Inc. Systems and methods for processing sensor data
US20100234710A1 (en) * 2008-03-28 2010-09-16 Abbott Diabetes Care Inc. Analyte Sensor Calibration Management
US20120265035A1 (en) * 2011-04-15 2012-10-18 Dexcom, Inc Advanced analyte sensor calibration and error detection
CN110868928A (zh) * 2017-05-03 2020-03-06 雅培糖尿病护理公司 具有传感器数据的基于持续期的调整的系统、装置以及方法
CN113380411A (zh) * 2021-07-19 2021-09-10 苏州百孝医疗科技有限公司 一种提高动物体分析物浓度连续监测过程中浓度变化实时趋势准确率的方法
CN114145738A (zh) * 2022-02-10 2022-03-08 苏州百孝医疗科技有限公司 分析物浓度数据生成方法和装置、监测分析物水平的系统

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101189512A (zh) * 2005-06-02 2008-05-28 爱森斯有限公司 在分析物传感器中使用多个数据点并进行滤波
US9675290B2 (en) * 2012-10-30 2017-06-13 Abbott Diabetes Care Inc. Sensitivity calibration of in vivo sensors used to measure analyte concentration
US8560251B2 (en) * 2011-08-16 2013-10-15 Instrumentation Laboratory Company System and method of increasing sample throughput by estimation of a sensor endpoint
EP3482319B1 (en) * 2016-07-08 2020-12-09 Novo Nordisk A/S Systems and methods for the determination of insulin sensitivity
MA51798B1 (fr) * 2018-12-10 2022-01-31 Hoffmann La Roche Procédé et système permettant de déterminer la concentration d'un analyte dans un échantillon d'un fluide corporel et procédé et système pour générer un module mis en uvre par logiciel
CN113951879B (zh) * 2021-12-21 2022-04-05 苏州百孝医疗科技有限公司 血糖预测方法和装置、监测血糖水平的系统

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009055736A1 (en) * 2007-10-25 2009-04-30 Dexcom, Inc. Systems and methods for processing sensor data
US20100234710A1 (en) * 2008-03-28 2010-09-16 Abbott Diabetes Care Inc. Analyte Sensor Calibration Management
US20120265035A1 (en) * 2011-04-15 2012-10-18 Dexcom, Inc Advanced analyte sensor calibration and error detection
CN110868928A (zh) * 2017-05-03 2020-03-06 雅培糖尿病护理公司 具有传感器数据的基于持续期的调整的系统、装置以及方法
CN113380411A (zh) * 2021-07-19 2021-09-10 苏州百孝医疗科技有限公司 一种提高动物体分析物浓度连续监测过程中浓度变化实时趋势准确率的方法
CN114145738A (zh) * 2022-02-10 2022-03-08 苏州百孝医疗科技有限公司 分析物浓度数据生成方法和装置、监测分析物水平的系统

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