CN112438704B - Calibration system of physiological parameter monitor - Google Patents
Calibration system of physiological parameter monitor Download PDFInfo
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- CN112438704B CN112438704B CN202010615256.9A CN202010615256A CN112438704B CN 112438704 B CN112438704 B CN 112438704B CN 202010615256 A CN202010615256 A CN 202010615256A CN 112438704 B CN112438704 B CN 112438704B
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Classifications
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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
-
- 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
- A61B5/1486—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 enzyme electrodes, e.g. with immobilised oxidase
-
- 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
Abstract
The invention provides a calibration system of a physiological parameter monitor, which is characterized by comprising the following components: the monitoring module is used for monitoring and acquiring original physiological parameter information of the object to be detected, is provided with a calibration algorithm, and calibrates the original physiological parameter information based on the calibration algorithm to generate calibrated physiological parameter information; the acquisition module is used for acquiring blood of an object to be detected and acquiring reference physiological parameter information in the blood; and the updating module is used for acquiring the original physiological parameter information, the calibration physiological parameter information and the reference physiological parameter information and updating the calibration algorithm based on the original physiological parameter information, the calibration physiological parameter information and the reference physiological parameter information. The updating module can acquire and update the calibration algorithm based on the original physiological parameter information, the calibration physiological parameter information and the reference physiological parameter information, so that the calibration algorithm can calibrate according to the reference physiological parameter information.
Description
Technical Field
The invention relates to a calibration system of a physiological parameter monitor.
Background
Diabetes is a series of metabolic disorder syndromes of sugar, protein, fat, water, electrolyte and the like, and is caused by islet hypofunction, insulin resistance and the like caused by the action of various pathogenic factors such as genetic factors, immune dysfunction, microbial infection, toxins and the like on organisms. If diabetes is not well controlled, it may cause complications such as ketoacidosis, lactic acidosis, chronic renal failure, and retinopathy. With the increasing incidence of diabetes, diabetes has become a public health problem worldwide.
Diabetes is a high-frequency condition with a prevalence of more than 10% in today's society. Long-term hyperglycemia can cause a series of diabetes-related complications, and hypoglycemia can cause coma, etc., and even be life-threatening. Blood glucose monitoring is a very important component of diabetes management and can significantly reduce the risk of diabetic complications.
The existing blood glucose monitoring mode mainly comprises glycosylated hemoglobin and blood glucose monitoring. The glycosylated hemoglobin reacts for 2-3 months at the average blood sugar level, so that the short-term blood sugar concentration can not be observed, and the timely control of blood sugar is realized. The blood glucose monitoring can only obtain single-point blood glucose values, but cannot obtain short-term comprehensive blood glucose values, so that the comprehensive control of blood glucose is realized; and complicated operation flow and painful user experience such as blood collection are required, and multiple times per day blood glucose monitoring is required to be carried out by a user to specify a detection plan, so that compliance of patients for regular blood glucose monitoring is poor.
Continuous blood glucose monitoring is the direction of development of blood glucose monitoring by diabetics. The current blood glucose concentration can be reflected in real time, and a continuous and comprehensive blood glucose value can be obtained, so that a patient and a doctor can be guided to conduct blood glucose control conveniently. The traditional continuous blood glucose monitoring requires 1-2 times or even more times per day of frequent blood glucose monitoring for calibration, which brings great inconvenience to patients.
The continuous blood glucose detection device calibrated by the calibration algorithm can monitor blood glucose concentration for a long time after being penetrated painlessly once, and does not need to monitor blood glucose frequently for blood collection, but the calibration algorithm which is set by factory is also limited greatly, for example, the physique of users is different, the required calibration algorithm is also different, or when the body temperature of the users is higher, or the detection device is influenced by other adverse factors, the calibration algorithm cannot be adjusted according to the special conditions.
Disclosure of Invention
The present invention has been made in view of the above-described conventional circumstances, and an object thereof is to provide a calibration system for a physiological parameter monitor, which is capable of adjusting a calibration algorithm and has excellent adaptability.
To this end, the present disclosure provides a calibration system for a physiological parameter monitor, comprising: the monitoring module is used for monitoring and acquiring original physiological parameter information of an object to be detected, is carried with a calibration algorithm and calibrates the original physiological parameter information based on the calibration algorithm to generate calibrated physiological parameter information; the acquisition module is used for acquiring blood of the object to be detected and acquiring reference physiological parameter information in the blood; and the updating module is used for acquiring the original physiological parameter information, the calibration physiological parameter information and the reference physiological parameter information and updating the calibration algorithm based on the original physiological parameter information, the calibration physiological parameter information and the reference physiological parameter information.
In the calibration system of the physiological parameter monitor, the calibration algorithm can calibrate the original physiological parameter information acquired by the monitoring module and generate the calibrated physiological parameter information, and in this case, the updating module can acquire and update the calibration algorithm based on the original physiological parameter information, the calibrated physiological parameter information and the reference physiological parameter information, so that the calibration algorithm can calibrate according to the reference physiological parameter information to improve the adaptability of the calibration system.
In addition, in the calibration system according to the present invention, optionally, the update module is disposed in the monitoring module. Therefore, the calibration algorithm in the monitoring module can be updated in time.
In addition, in the calibration system according to the present invention, optionally, the updating module compares the calibration physiological parameter information with the reference physiological parameter information, and obtains a calibration parameter based on the original physiological parameter information and the calibration physiological parameter information to update the calibration algorithm. Therefore, the calibration parameters can be obtained through the updating module, and the calibration algorithm is updated to further improve the adaptability of the calibration system.
In addition, in the calibration system according to the present invention, optionally, the acquisition module is separable from the monitoring module. Thus, the blood of the object to be tested can be collected through the collecting module.
In addition, in the calibration system according to the present invention, optionally, the monitoring module includes a glucose sensor, and the raw physiological parameter information is blood glucose concentration information obtained by the glucose sensor. Thus, the monitoring module can obtain the blood glucose concentration information of the object to be tested.
In addition, in the calibration system according to the present invention, optionally, the calibration parameter includes at least one of an initial sensitivity, a sensitivity drift, an attenuation coefficient of sensitivity, and a temperature coefficient of the glucose sensor. Thereby, the reliability of the calibration algorithm can be improved.
In addition, in the calibration system according to the present invention, optionally, the glucose sensor has a glucose enzyme layer and a semipermeable membrane disposed on the glucose enzyme layer, and the initial sensitivity is related to a mass, a volume, a thickness, an activity of the glucose enzyme layer in the glucose sensor, and a film thickness, a diffusion coefficient of the semipermeable membrane. Thus, the calibration parameters can be controlled by controlling the parameters related to the layer of the glucolase and the semipermeable membrane.
In addition, in the calibration system according to the present invention, optionally, the acquisition module is a fingertip blood glucose meter, and the reference physiological parameter information is obtained by the fingertip blood glucose meter. Thus, more accurate blood glucose concentration information can be obtained from blood.
In addition, in the calibration system according to the present invention, optionally, the monitoring module monitors and acquires the original physiological parameter information in the tissue fluid of the subject. Thus, the original physiological parameter information of the object to be measured can be obtained from the tissue fluid.
In addition, in the calibration system according to the present invention, optionally, the calibration parameter further includes a correlation coefficient between blood glucose concentration information in the tissue fluid and blood glucose concentration information in the blood. Thus, blood glucose concentration information in blood can be obtained from blood glucose concentration information in tissue fluid.
According to the invention, the calibration system of the physiological parameter monitor, which can adjust the calibration algorithm and has good adaptability, can be provided.
Drawings
Embodiments of the present disclosure will now be explained in further detail by way of example only with reference to the accompanying drawings, in which:
fig. 1 is a schematic view showing an application scenario of a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.
Fig. 2 is a signal transmission schematic diagram illustrating a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.
Fig. 3 is a block diagram illustrating a calibration system of a physiological parameter monitor in accordance with an embodiment of the present disclosure.
Fig. 4 is a block diagram showing a module of a calibration algorithm mounted on a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.
Fig. 5 is a schematic diagram showing a glucose sensor structure of a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.
Fig. 6 is a schematic diagram showing various factors affecting calibration parameters of a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.
Fig. 7 is a schematic diagram showing a relationship between original physiological parameter information and original physiological parameter information in blood according to an embodiment of the present disclosure.
Fig. 8 is a calibration flow diagram illustrating a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.
Reference numerals illustrate:
1 … calibration system, 10 … monitoring module, 11 … calibration algorithm, 111 … calibration parameters, 12 … glucose sensor, 121 … working electrode, 122 … reference electrode, 123 … counter electrode, S … substrate, 20 … acquisition module, 30 … update module, 2 … object to be measured.
Detailed Description
The present invention will be described in further detail with reference to the drawings and detailed description. In the drawings, the same components or components having the same functions are denoted by the same reference numerals, and repetitive description thereof will be omitted.
The invention discloses a calibration system of a physiological parameter monitor. The calibration system of the physiological parameter monitor can adjust the calibration algorithm and has good adaptability. In addition, the calibration system of the physiological parameter monitor according to the present invention may be simply referred to as a calibration system.
Fig. 1 is a schematic view showing an application scenario of a calibration system 1 of a physiological parameter monitor according to an embodiment of the present disclosure. Fig. 2 is a signal transmission schematic diagram showing a calibration system 1 of a physiological parameter monitor according to an embodiment of the present disclosure. Fig. 3 is a block diagram illustrating a calibration system 1 of a physiological parameter monitor according to an embodiment of the present disclosure.
In some examples, as shown in fig. 1 and 2, a calibration system 1 of a physiological parameter monitor to which the present disclosure relates may include a monitoring module 10, an acquisition module 20, and an update module 30. The monitoring module 10 may be disposed on an arm of the subject 2 (see fig. 1), but the example of the present disclosure is not limited thereto, and the monitoring module 10 may be disposed at a chest, a leg, an abdomen, or a neck of the subject 2. The acquisition module 20 may be used for acquiring blood of the object 2 to be measured, for example, may be used for acquiring finger blood of the object 2 to be measured.
In some examples, the monitoring module 10 may be used to obtain raw physiological parameter information of the subject 2 to be measured and generate calibrated physiological parameter information. The acquisition module 20 may be used to acquire blood of the subject 2 to be measured to obtain reference physiological parameter information in the blood. The update module 30 may update the calibration algorithm based on the raw physiological parameter information, the calibration physiological parameter information, and the reference physiological parameter information. The calibration system 1 according to the present disclosure is capable of adjusting the calibration algorithm and has good adaptability.
Fig. 4 is a block diagram showing a module of the calibration system 1 with the calibration algorithm 11 mounted thereon of the physiological parameter monitor according to the embodiment of the present disclosure. Fig. 5 is a schematic diagram showing the structure of a glucose sensor of the calibration system 1 of the physiological parameter monitor according to the embodiment of the present disclosure.
In some examples, as described above, the calibration system 1 of the physiological parameter monitor may include a monitoring module 10 (see fig. 2 or 3).
In some examples, as shown in fig. 4, the monitoring module 10 may be used to monitor and obtain raw physiological parameter information of the subject 2 to be tested.
In some examples, the monitoring module 10 may monitor and acquire raw physiological parameter information in tissue fluid of the subject 2. Thus, the original physiological parameter information of the object to be measured 2 can be obtained from the tissue fluid. In other examples, the monitoring module 10 may monitor and acquire raw physiological parameter information in the blood of the subject 2.
In some examples, the raw physiological parameter information may be blood glucose concentration information. Thereby, the monitoring module 10 can obtain blood glucose concentration information of the subject 2 to be measured.
In some examples, the monitoring module 10 may include a glucose sensor 12 (see fig. 5). The raw physiological parameter information may be blood glucose concentration information obtained by the glucose sensor 12. Thereby, the monitoring module 10 can obtain the blood glucose concentration information of the subject 2 by the glucose sensor 12. However, the present embodiment is not limited thereto, and the original physiological parameter information may be other body fluid composition data. For example, by changing the glucose enzyme layer on the glucose sensor 12, other body fluid composition data besides glucose can be acquired. Other body fluid components may be, for example, acetylcholine, amylase, bilirubin, cholesterol, chorionic gonadotrophin, creatine kinase, creatine, DNA, fructosamine, glucose, glutamine, growth hormone, ketone bodies, lactate, oxygen, peroxide, prostate specific antigen, prothrombin, RNA, thyroid stimulating hormone, troponin, and the like.
In other examples, monitoring module 10 may monitor the concentration of a drug in a bodily fluid. For example, antibiotics (e.g., gentamicin, vancomycin, etc.), digitoxin, digoxin, theophylline, warfarin, etc.
In some examples, the glucose sensor 12 may include a substrate S (see fig. 5), a glucose enzyme layer, and a semipermeable membrane, which are laminated in order.
In some examples, the layer of glucose may react with glucose. The layer of the glucose enzyme may be provided on the substrate S.
In some examples, the initial sensitivity of the glucose sensor 12 (described later) is related to the mass, volume, thickness, activity of the glucose enzyme layer in the glucose sensor 12, as well as the membrane thickness, diffusion coefficient of the semi-permeable membrane. Thereby, the calibration parameters 111 (described later) can be controlled by controlling the relevant parameters of the dextranase layer and the semipermeable membrane.
In some examples, the glucose sensor 12 may be provided with a glucose enzyme layer and a semi-permeable membrane by at least one of spin coating, dip-pull, drip coating, and spray coating processes.
In some examples, the substrate S of the glucose sensor 12 may be flexible. Thus, the discomfort caused by the implantation of the glucose sensor 12 into the human body can be reduced.
In some examples, the substrate S may be a flexible substrate. The flexible substrate may be generally made of at least one of Polyethylene (PE), polypropylene (PP), polyimide (PI), polystyrene (PS), polyethylene terephthalate (PET), and polyethylene naphthalate (PEN).
In other examples, the flexible substrate S may be generally made of a metal foil, ultra-thin glass, a single-layer inorganic film, a multi-layer organic film, or a multi-layer inorganic film, etc.
In other examples, the substrate S may be a non-flexible substrate. The inflexible substrate may generally comprise a less conductive ceramic, alumina, silica, or the like. In this case, the glucose sensor 12 having a non-flexible substrate may also have sharp points or sharp edges, thereby enabling implantation of the glucose sensor 12 into the skin (e.g., shallow skin, etc.) without the need for an auxiliary implantation device (not shown).
In some examples, the thickness of the layer of the glucosidase enzyme may be about 0.1 μm to 100 μm. Preferably, the thickness of the layer of the glucosidase enzyme may be about 2 μm to 10 μm, for example, it may be 2 μm, 3 μm, 4 μm, 5 μm, 6 μm, 7 μm, 8 μm, 9 μm or 10 μm.
In one example, the thickness of the layer of the glucose enzyme may be 10 μm. Under the condition, the thickness of the glucose is controlled within a certain degree, so that the problems that the adhesion force is reduced due to too much glucose, materials fall off in the body, insufficient reaction is caused due to too little glucose, normal glucose concentration information cannot be fed back and the like are avoided.
In other examples, the glucose enzyme may be one or more of glucose oxidase or glucose dehydrogenase.
In some examples, as described above, glucose sensor 12 may include a semi-permeable membrane. The semipermeable membrane can control the amount of glucose. The semipermeable membrane may be provided on the layer of the dextranase.
In some examples, the semipermeable membrane may be provided by at least one of spin coating, dip-coating, drop-coating, and spray-coating processes.
In some examples, the semipermeable membrane may include a diffusion control layer and an anti-tamper layer laminated on the diffusion control layer. In some examples, the diffusion control layer may be disposed outside the tamper resistant layer. In the semipermeable membrane, the diffusion control layer can control the diffusion of glucose molecules, and the anti-interference layer can prevent the diffusion of non-glucose substances. Thus, the tissue fluid or blood component passing through the semipermeable membrane can be reduced, and then the interference object is blocked outside the semipermeable membrane through the anti-interference layer. Common interferents may include uric acid, ascorbic acid, acetaminophen, and the like, which are ubiquitous in the body.
In some examples, the semipermeable membrane may control the rate of passage of glucose molecules, i.e., the semipermeable membrane may limit the number of glucose molecules in interstitial fluid or blood that reach the glucose layer. Specifically, the diffusion-controlling layer of the semipermeable membrane is effective to reduce the amount of glucose diffused into the glucose layer by a certain proportion.
In some examples, the semipermeable membrane may be biocompatible.
In other examples, glucose sensor 12 may include a biocompatible membrane.
In some examples, glucose sensor 12 may include a working electrode 121, a reference electrode 122, and a counter electrode 123 (see fig. 5).
In some examples, glucose sensor 12 after lancing the skin may generate a current signal by redox reaction of glucose in working electrode 121 with glucose in interstitial fluid or blood and forming a circuit with counter electrode 123.
In other examples, the reference electrode 122 may form a known and fixed potential difference with interstitial fluid or blood. In this case, the potential difference between the working electrode 121 and the tissue fluid or blood can be measured by the potential difference formed by the reference electrode 122 and the working electrode 121, so that the voltage generated by the working electrode 121 can be accurately grasped. Thus, the voltage at the working electrode 121 can be automatically adjusted and maintained stable according to the preset voltage value, so as to ensure that the measured current signal can accurately reflect the glucose concentration value.
In addition, in some examples, the counter electrode 123 may be made of platinum, silver chloride, palladium, titanium, or iridium. Thus, the electrochemical reaction at the working electrode 121 can be unaffected with good conductivity. However, the present embodiment is not limited thereto, and in other examples, the counter electrode 123 may be made of at least one selected from gold, glassy carbon, graphite, silver chloride, palladium, titanium, or iridium. Thereby, the influence on the working electrode 121 can be reduced with good conductivity.
In some examples, the monitoring module 10 may include an electronic system. The electronic system may be used to store raw physiological parameter information. In this case, the electronic system may transmit the received original physiological parameter information through a wireless communication manner, such as bluetooth, wifi, etc.
In some examples, the monitoring module 10 may transmit the acquired raw physiological parameter information to the updating module 30 via wireless communication.
In other examples, an external reading device may receive raw physiological parameter information sent by the electronic system. For example, an external reading device may receive the glucose concentration signal and display a glucose concentration value. In some examples, the glucose concentration value may be represented by a digital value. In other examples, the reading device may graphically represent glucose concentration value trends over a predetermined period of time. Additionally, in some examples, the reading device may display information such as pictures, animations, charts, graphs, value ranges, and digital data.
Further, since the glucose sensor 12 according to the present embodiment can realize continuous monitoring, the glucose concentration value of the human body can be continuously monitored for a long period of time (for example, 1 to 24 days). Additionally, in some examples, the reading device may be a reader or a cell phone APP. In other examples, the reading device may also be an acquisition module 20 (described later).
In some examples, the monitoring module 10 may include a calibration algorithm. In other words, the monitoring module 10 may be equipped with a calibration algorithm 11 (see fig. 4).
In some examples, the monitoring module 10 may calibrate the raw physiological parameter information based on the calibration algorithm 11 to generate calibrated physiological parameter information.
In some examples, the calibration algorithm 11 may be factory-installed, i.e., onboard, the monitoring module 10. In other examples, the calibration algorithm 11 may be downloaded by the user from a server, algorithm library or cloud, etc. location via a network at the time of initial use. In this case, the downloaded calibration algorithm 11 may be matched according to personal information of the user, for example, according to personal information of the height, weight, age, use reason, etc. of the user. Thus, the individualization degree of the calibration algorithm 11 can be improved, and various people can use the calibration algorithm conveniently to improve adaptability. In this case, the calibration algorithm 11 of the monitoring module 10 may be different for different users.
In some examples, the calibration algorithm 11 has calibration parameters 111. The calibration parameters 111 may be updated. The update method is described later. In this case, after the calibration parameters 111 are updated, the monitoring module 10 may recalibrate the original physiological parameter information based on the calibration algorithm 11 to regenerate the calibrated physiological parameter information.
In some examples, the calibration parameters 111 of the calibration algorithm 11 of the monitoring module 10 may be different for different users.
In some examples, the electronic system of the monitoring module 10 may be used to store calibrated physiological parameter information. In this case, the electronic system may transmit the received calibrated physiological parameter information through wireless communication means, such as bluetooth, wifi, etc.
In some examples, the monitoring module 10 may transmit the calibrated physiology so parameter information to the updating module 30 by way of wireless communication.
In some examples, as described above, the calibration system 1 of the physiological parameter monitor may include an acquisition module 20 (see fig. 2 or 3).
In some examples, the collection module 20 may be used to collect blood of the subject 2 to be measured and to obtain reference physiological parameter information in the blood.
In some examples, the user or subject can acquire reference physiological parameter information through acquisition module 20 as needed. In other examples, the user or subject may periodically acquire reference physiological parameter information via acquisition module 20. Thereby, the calibration algorithm 11 can be updated with the reference physiological parameter information (described later). Specifically, the user may use the acquisition module 20 to acquire the reference physiological parameter information 1 time a day, 1 time two days, 1 time three days, and 1 time a week.
Examples of the present disclosure are not limited thereto, however, for example, the calibration system 1 may not use the acquisition module 20. I.e. the calibration system 1 may not update the calibration algorithm 11. In this case, for example, a type II diabetes, pre-diabetes or even non-diabetic patient, etc., such a user who does not need to have a high requirement for measurement accuracy can obtain a good measurement value without having to update the calibration algorithm 11. Thereby, the user of the above type can use it conveniently.
In some examples, the acquisition module 20 may be separate from the monitoring module 10. Thereby, the blood of the object 2 to be tested can be collected by the collection module 20.
In other examples, the acquisition module 20 may be disposed in the monitoring module 10. This allows the acquisition module 20 to acquire data at any time.
In some examples, the reference physiological parameter information may be blood glucose concentration information. Thus, the acquisition module 20 can obtain blood glucose concentration information. The present disclosure is not limited thereto and the reference physiological parameter information may be other blood component data.
In some examples, the collection module 20 may be a fingertip blood glucose meter. The reference physiological parameter information may be blood glucose concentration information obtained by a fingertip blood glucose meter. Thus, more accurate blood glucose concentration information can be obtained from blood (see fig. 1).
In some examples, the usage flow of the acquisition module 20 is as follows: the blood sample of the fingertip blood is obtained by puncturing the finger tip with the disposable needle, using the test paper or the pipette, and then is put into the detecting device of the collecting module 20, and finally, the blood glucose concentration information (for example, the blood glucose concentration value) in the blood sample can be obtained.
In some examples, acquisition module 20 may have a wireless communication unit, such as bluetooth, WIFI, or the like. Thus, a signal can be transmitted or received by wireless communication. In this case, the acquisition module 20 may transmit the acquired reference physiological parameter information to the update module 30 by means of wireless communication.
Fig. 6 is a schematic diagram showing various factors affecting a calibration parameter 111 of the calibration system 1 of the physiological parameter monitor according to the embodiment of the present disclosure. Fig. 7 is a schematic diagram showing a relationship between original physiological parameter information and original physiological parameter information in blood according to an embodiment of the present disclosure. Fig. 8 is a schematic diagram showing a calibration flow of the calibration system 1 of the physiological parameter monitor according to the embodiment of the present disclosure.
In some examples, as described above, the calibration system 1 of the physiological parameter monitor may include an update module 30 (see fig. 2 or 3).
In some examples, the update module 30 may obtain raw physiological parameter information, calibrated physiological parameter information, and reference physiological parameter information. Specifically, the update module 30 may receive the raw physiological parameter information and the calibrated physiological parameter information output by the monitoring module 10. The update module 30 may receive the reference physiological parameter information output by the acquisition module 20.
In some examples, the update module 30 may update the calibration algorithm 11 based on the raw physiological parameter information, the calibration physiological parameter information, and the reference physiological parameter information.
In some examples, the update module 30 may be disposed in the monitoring module 10. Thus, the calibration algorithm 11 in the monitoring module 10 can be updated in time.
In other examples, the update module 30 may be disposed at the cloud. The updating module 30 disposed at the cloud end can store the calibration parameters (to be described later) of the calibration algorithm 11 of each user in a database, classify the users, and update the calibration parameters of the calibration algorithm 11 of the same class of users iteratively to generate the calibration algorithm 11 more suitable for the class of people. Thereby, the reliability of the calibration algorithm 11 is further improved.
In some examples, the update module 30 may compare the calibrated physiological parameter information to the reference physiological parameter information. In some examples, it is determined whether the calibrated physiological parameter information and the reference physiological parameter information converge by comparing the calibrated physiological parameter information to the reference physiological parameter information.
In some examples, the update module 30 may obtain the calibration parameters 111 based on the raw physiological parameter information and the calibration physiological parameter information to update the calibration algorithm 11. Thus, the calibration parameters 111 can be obtained by the update module 30 and the calibration algorithm 11 updated to further improve the adaptability of the calibration system 1.
In some examples, the calibration parameter 111 is updated if the calibration physiological parameter information does not converge with the reference physiological parameter information. Thus, the updating of the calibration algorithm 11 can be achieved by updating the calibration parameters 111.
In some examples, as shown in fig. 6, the calibration parameters 111 may include at least one of an initial sensitivity, a sensitivity drift, an attenuation coefficient of the sensitivity, and a temperature coefficient of the glucose sensor 12. Thereby, the reliability of the calibration algorithm 11 can be improved.
In other examples, the calibration parameters 111 may include specific relationships between the sensor and sensitivity, baseline, drift, impedance/temperature relationships, and specific relationships between the site (abdomen, arm, etc.) where the sensor is implanted. In this case, the relation between the calibration parameters 111 and the respective factors can be considered more comprehensively, so that different calibration algorithms 11 can be set for different users. Therefore, the application range of the physiological parameter monitor can be improved. In particular, the site of implantation of the sensor may be affected by different vascular densities.
In some examples, the calibration algorithm 11 may calibrate based on the distribution information of the calibration parameters 111. Specifically, the distribution information includes: a range, a distribution function, a distribution parameter (mean, standard deviation, skewness, etc.), a generalized function, a statistical distribution, a distribution, or the like, which represents a plurality of possible values of the calibration information. The a priori calibration distribution information together comprise a range or distribution of values (e.g., describing their associated probabilities, probability density functions, likelihoods, or frequencies of occurrence) provided prior to a particular calibration process useful for calibration of the sensor (e.g., sensor data).
In some examples, as shown in fig. 7, the calibration parameter 111 may include a correlation coefficient of blood glucose concentration information in tissue fluid and blood glucose concentration information in blood. Thus, blood glucose concentration information in blood can be obtained from blood glucose concentration information in tissue fluid. In some examples, there is a delay in blood glucose concentration information in the interstitial fluid from blood glucose concentration information in the blood. In other examples, blood glucose concentration information in tissue fluid may be obtained by a dynamic compensation method.
The following describes the calibration flow of the calibration system 1 in detail with reference to fig. 8:
in some examples, as shown in fig. 8, the user may use the monitoring module 10 to continuously monitor the object 2 to be measured (or the user himself), after starting monitoring, the monitoring module 10 can measure the original physiological parameter information, and the monitoring module 10 calibrates the original physiological parameter information through the calibration algorithm 11 carried therein, so as to obtain the calibrated physiological parameter information and output the calibrated physiological parameter information.
In some examples, as shown in fig. 8, the collection of blood of the subject 2 by the collection module 20 and the generation of the reference physiological parameter information may be selected based on the needs of the user or when the user is ambiguous in terms of the calibrated physiological parameter information.
In some examples, if the acquisition module 20 generates or acquires the reference physiological parameter information, the calibration physiological parameter information and the reference physiological parameter information will be matched by the update module 30. Specifically, the update module 30 is utilized to obtain the original physiological parameter information, the calibrated physiological parameter information, and the reference physiological parameter information by matching the calibrated physiological parameter information with the reference physiological parameter information. Wherein matching may refer to comparing the calibrated physiological parameter information with the reference physiological parameter information.
In some examples, determining whether the calibrated physiological parameter information and the reference physiological parameter information converge, if so, outputting the calibrated physiological parameter information and ending the calibration procedure; if not, the calibration parameters in the calibration algorithm 11 are updated. Specifically, the updating module 30 updates the calibration parameters 111 in the calibration algorithm 11 based on the original physiological parameter information, the calibration physiological parameter information, and the reference physiological parameter information, so as to obtain the calibration algorithm 11 more suitable for the object 2 to be measured.
In some examples, the original physiological parameter information is again calibrated by the updated calibration algorithm 11 and the calibrated physiological parameter information is generated. Specifically, in the monitoring module 10, the updated calibration algorithm 11 calibrates the original physiological parameter information to regenerate calibrated physiological parameter information.
In some examples, the regenerated calibration physiological parameter information is matched with the reference physiological parameter information until the calibration physiological parameter information is output after convergence and the calibration procedure is ended.
In the calibration system 1 of the physiological parameter monitor according to the present disclosure, the calibration algorithm 11 can calibrate the original physiological parameter information acquired by the monitoring module 10 and generate the calibrated physiological parameter information, in which case the update module 30 can acquire and update the calibration algorithm 11 based on the original physiological parameter information, the calibrated physiological parameter information, and the reference physiological parameter information, thereby enabling the calibration algorithm 11 to calibrate according to the reference physiological parameter information to improve the adaptability of the calibration system.
While the invention has been described in detail in connection with the drawings and embodiments, it should be understood that the foregoing description is not intended to limit the invention in any way. Modifications and variations of the invention may be made as desired by those skilled in the art without departing from the true spirit and scope of the invention, and such modifications and variations fall within the scope of the invention.
Claims (7)
1. A calibration system for a physiological parameter monitor is characterized in that,
comprising the following steps:
the monitoring module is used for monitoring and acquiring original physiological parameter information of an object to be detected, and is carried with a calibration algorithm in a factory, and the monitoring module calibrates the original physiological parameter information based on the calibration algorithm to generate calibrated physiological parameter information;
the acquisition module is used for acquiring blood of the object to be detected and acquiring reference physiological parameter information in the blood;
an updating module that obtains the original physiological parameter information from the monitoring module, the calibration physiological parameter information, and the reference physiological parameter information from the acquisition module, obtains a calibration parameter based on the original physiological parameter information and the calibration physiological parameter information, compares the calibration physiological parameter information with the reference physiological parameter information, confirms whether the calibration physiological parameter information and the reference physiological parameter information converge, and if not, updates the calibration algorithm by the calibration parameter,
the monitoring module is used for storing the calibration physiological parameter information and transmitting the calibration physiological parameter information to the updating module in a wireless communication mode, the monitoring module comprises a glucose sensor, the original physiological parameter information is blood glucose concentration information obtained by the glucose sensor, and the calibration parameter comprises at least one of initial sensitivity, sensitivity drift, attenuation coefficient of sensitivity and temperature coefficient of the glucose sensor.
2. The calibration system of claim 1, wherein:
the update module is disposed in the monitoring module.
3. The calibration system of claim 1, wherein:
the acquisition module is separable from the monitoring module.
4. The calibration system of claim 1, wherein:
the glucose sensor has a glucose enzyme layer and a semipermeable membrane disposed on the glucose enzyme layer, the initial sensitivity being related to the mass, volume, thickness, activity of the glucose enzyme layer in the glucose sensor, and the membrane thickness, diffusion coefficient of the semipermeable membrane.
5. The calibration system of claim 1, wherein:
the acquisition module is a fingertip blood glucose meter, and the reference physiological parameter information is used for obtaining blood glucose concentration information by the fingertip blood glucose meter.
6. The calibration system of claim 1, wherein:
the monitoring module monitors and acquires the original physiological parameter information in the tissue fluid of the object to be detected.
7. The calibration system of claim 6, wherein:
the calibration parameters also include a correlation coefficient of blood glucose concentration information in the tissue fluid and blood glucose concentration information in the blood.
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| CN113095389B (en) * | 2021-04-02 | 2023-04-07 | 河北先河环保科技股份有限公司 | Method and system for calibrating monitoring network of gridding sensor |
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