CN112438704B - Calibration system of physiological parameter monitor - Google Patents

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

Calibration system for physiological parameter monitors

Technical field

The invention relates to a calibration system for a physiological parameter monitor.

Background technique

Diabetes is a syndrome of a series of metabolic disorders such as sugar, protein, fat, water and electrolytes. It is caused by various pathogenic factors such as genetic factors, immune dysfunction, microbial infections and their toxins, which act on the body to cause pancreatic islet dysfunction, insulin resistance, etc. caused. If diabetes is not well controlled, it may cause complications such as ketoacidosis, lactic acidosis, chronic renal failure, and retinopathy. As the incidence of diabetes continues to increase, diabetes has become a public health problem worldwide.

In today's society, diabetes is a high-risk disease with a prevalence rate higher than 10%. Long-term high blood sugar 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 part of diabetes management and can significantly reduce the risk of diabetes complications.

The existing blood glucose monitoring methods are mainly glycosylated hemoglobin and finger blood glucose monitoring. Glycated hemoglobin reflects the average blood sugar level for 2 to 3 months, and it is impossible to observe short-term blood sugar concentration to achieve timely control of blood sugar. Finger blood glucose monitoring can only obtain a single point of blood glucose value, but cannot obtain short-term comprehensive blood glucose values to achieve comprehensive control of blood sugar; it also requires complex operating procedures and painful user experiences such as finger blood collection, and finger blood glucose monitoring is required multiple times a day. Monitoring requires users to specify a testing plan, resulting in poor patient compliance with regular blood glucose monitoring.

Continuous blood glucose monitoring is the development direction of blood glucose monitoring for diabetic patients. It can reflect the current blood sugar concentration in real time and obtain continuous and comprehensive blood sugar values, which is convenient for guiding patients and doctors on blood sugar control. Traditional continuous blood glucose monitoring requires 1 to 2 or more frequent finger-blood glucose monitoring for calibration every day, 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 a painless insertion. It does not require finger blood glucose monitoring and frequent finger blood collection. However, the factory-set calibration algorithm still has major limitations. For example, different users’ physiques require different calibration algorithms, or when the user’s body temperature is high, or when the detection device is affected by other adverse factors, the calibration algorithm cannot be adjusted according to these special circumstances.

Contents of the invention

The present invention is completed in view of the above-mentioned state of the prior art, and its purpose is to provide a calibration system for a physiological parameter monitor that can adjust the calibration algorithm and has good adaptability.

To this end, the present disclosure provides a calibration system for a physiological parameter monitor, which is characterized in that it includes: a monitoring module, which is used to monitor and obtain the original physiological parameter information of the object to be measured, and the monitoring module is equipped with a calibration algorithm, The monitoring module calibrates the original physiological parameter information based on the calibration algorithm to generate calibrated physiological parameter information; a collection module is used to collect the blood of the subject to be tested and obtain reference physiological parameters in the blood Information; an update module that obtains the original physiological parameter information, the calibrated physiological parameter information and the reference physiological parameter information, and based on the original physiological parameter information, the calibrated physiological parameter information and the reference physiological parameter information The calibration algorithm is updated.

In the calibration system of the physiological parameter monitor involved in the present disclosure, the calibration algorithm can calibrate the original physiological parameter information obtained by the monitoring module and generate the calibrated physiological parameter information. In this case, the update module can obtain and based on The original physiological parameter information, the calibrated physiological parameter information and the reference physiological parameter information update the calibration algorithm, thereby enabling the calibration algorithm to be calibrated according to the reference physiological parameter information to improve the adaptability of the calibration system. .

In addition, in the calibration system related to the present invention, optionally, the update module is arranged in the monitoring module. As a result, the calibration algorithm in the monitoring module can be updated in a timely manner.

In addition, in the calibration system involved in the present invention, optionally, the update module compares the calibrated physiological parameter information with the reference physiological parameter information, and based on the original physiological parameter information and the calibrated physiological parameter The information obtains calibration parameters to update the calibration algorithm. Thus, the calibration parameters can be obtained through the update module and the calibration algorithm can be updated to further improve the adaptability of the calibration system.

In addition, in the calibration system of the present invention, optionally, the acquisition module and the monitoring module are separable. Thus, the blood of the subject to be tested can be collected through the collection module.

In addition, in the calibration system of the present invention, optionally, the monitoring module includes a glucose sensor, and the original 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 subject to be measured.

In addition, in the calibration system of the present invention, optionally, the calibration parameters include at least one of the initial sensitivity, sensitivity drift, sensitivity attenuation coefficient and temperature coefficient of the glucose sensor. As a result, the reliability of the calibration algorithm can be improved.

In addition, in the calibration system of 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 consistent with all the parameters in the glucose sensor. The quality, volume, thickness, and activity of the glucose enzyme layer are related to the film thickness and diffusion coefficient of the semipermeable membrane. Thus, the calibration parameters can be controlled by controlling the relevant parameters of the glucose enzyme layer and the semipermeable membrane.

In addition, in the calibration system of the present invention, optionally, the collection module is a fingertip blood glucose meter, and the reference physiological parameter information is obtained from the fingertip blood glucose meter to obtain blood glucose concentration information. As a result, more accurate blood glucose concentration information can be obtained from blood.

In addition, in the calibration system of the present invention, optionally, the monitoring module monitors and obtains the original physiological parameter information in the tissue fluid of the subject to be tested. As a result, the original physiological parameter information of the subject to be measured can be obtained from the tissue fluid.

In addition, in the calibration system of the present invention, optionally, the calibration parameters also include a correlation coefficient between the blood glucose concentration information in the tissue fluid and the blood glucose concentration information in the blood. Thus, the blood sugar concentration information in the blood can be obtained from the blood sugar concentration information in the interstitial fluid.

According to the present invention, a calibration system for a physiological parameter monitor that can adjust the calibration algorithm and has good adaptability can be provided.

Description of drawings

Embodiments of the present disclosure will now be explained in further detail only by way of example with reference to the accompanying drawings, in which:

FIG. 1 is a schematic diagram showing an application scenario of a calibration system for a physiological parameter monitor according to an embodiment of the present disclosure.

FIG. 2 is a signal transmission diagram illustrating a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.

3 is a module block diagram illustrating a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.

4 is a module block diagram equipped with a calibration algorithm illustrating the calibration system of the physiological parameter monitor according to the embodiment of the present disclosure.

FIG. 5 is a schematic structural diagram of a glucose sensor showing a calibration system of a physiological parameter monitor according to an embodiment of the present disclosure.

FIG. 6 is a schematic diagram illustrating various factors that affect the calibration parameters of the calibration system of the physiological parameter monitor according to the embodiment of the present disclosure.

FIG. 7 is a schematic diagram illustrating the relationship between original physiological parameter information and original physiological parameter information in blood according to the embodiment of the present disclosure.

FIG. 8 is a schematic diagram showing the calibration flow of the calibration system of the physiological parameter monitor according to the embodiment of the present disclosure.

Explanation of reference numbers:

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 tested.

Detailed ways

Below, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. In the drawings, the same components or components with the same functions are marked with the same symbols, and repeated descriptions thereof are omitted.

The invention discloses a calibration system for a physiological parameter monitor. The calibration system of the physiological parameter monitor of the present invention can adjust the calibration algorithm and has good adaptability. In addition, the calibration system of the physiological parameter monitor related to the present invention may be referred to as a calibration system for short.

FIG. 1 is a schematic diagram showing an application scenario of a calibration system 1 for a physiological parameter monitor according to an embodiment of the present disclosure. FIG. 2 is a schematic diagram showing signal transmission of the calibration system 1 of the physiological parameter monitor according to the embodiment of the present disclosure. FIG. 3 is a module block diagram illustrating the calibration system 1 of the physiological parameter monitor according to the embodiment of the present disclosure.

In some examples, as shown in FIGS. 1 and 2 , the calibration system 1 of the physiological parameter monitor involved in the present disclosure may include a monitoring module 10 , an acquisition module 20 and an update module 30 . Among them, the monitoring module 10 can be configured on the arm of the subject 2 (see Figure 1 ), but the example of the present disclosure is not limited thereto. The monitoring module 10 can also be configured on the chest, legs, and abdomen of the subject 2 or the neck. The collection module 20 can be used to collect the blood of the subject 2 to be tested, for example, it can be used to collect the finger blood of the subject 2 to be tested.

In some examples, the monitoring module 10 can be used to obtain original physiological parameter information of the subject 2 and generate calibrated physiological parameter information. The collection module 20 can be used to collect the blood of the subject 2 to obtain reference physiological parameter information in the blood. The update module 30 may update the calibration algorithm based on the original physiological parameter information, the calibrated physiological parameter information and the reference physiological parameter information. The calibration system 1 involved in the present disclosure can adjust the calibration algorithm and has good adaptability.

FIG. 4 is a module block diagram illustrating the calibration system 1 of the physiological parameter monitor according to the embodiment of the present disclosure and equipped with the calibration algorithm 11 . FIG. 5 is a schematic structural diagram of a glucose sensor showing 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 Figure 2 or Figure 3).

In some examples, as shown in FIG. 4 , the monitoring module 10 can be used to monitor and obtain original physiological parameter information of the subject 2 to be measured.

In some examples, the monitoring module 10 can monitor and obtain original physiological parameter information in the interstitial fluid of the subject 2 . As a result, the original physiological parameter information of the subject 2 can be obtained from the tissue fluid. In other examples, the monitoring module 10 can monitor and obtain original physiological parameter information in the blood of the subject 2 .

In some examples, the original physiological parameter information may be blood glucose concentration information. Thus, the monitoring module 10 can obtain the blood glucose concentration information of the subject 2 to be measured.

In some examples, monitoring module 10 may include glucose sensor 12 (see Figure 5). The original physiological parameter information may be blood glucose concentration information obtained by the glucose sensor 12 . Therefore, the monitoring module 10 can obtain the blood glucose concentration information of the subject 2 through the glucose sensor 12 . However, this embodiment is not limited to this, and the original physiological parameter information can be other body fluid component data. For example, by changing the glucose enzyme layer on the glucose sensor 12, data on other body fluid components other than glucose can also be obtained. Other body fluid components may be, for example, acetylcholine, amylase, bilirubin, cholesterol, chorionic gonadotropin, creatine kinase, creatine, creatinine, DNA, fructosamine, glucose, glutamine, growth hormone, hormones, ketones body, lactate, oxygen, peroxide, prostate-specific antigen, prothrombin, RNA, thyroid-stimulating hormone and troponin, etc.

In other examples, monitoring module 10 may monitor the concentration of a drug in body fluids. For example, antibiotics (such as gentamicin, vancomycin, etc.), digoxigenin, 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 stacked in sequence.

In some examples, the glucose enzyme layer can react with glucose. The glucose enzyme layer can 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, and activity of the glucose enzyme layer in the glucose sensor 12, as well as the film thickness and diffusion coefficient of the semipermeable membrane. Thus, the calibration parameter 111 (described later) can be controlled by controlling the relevant parameters of the glucose enzyme layer and the semipermeable membrane.

In some examples, the glucose sensor 12 may be provided with the glucose enzyme layer and the semipermeable membrane through at least one process of spin coating, dip-coating, drop coating, and spray coating.

In some examples, substrate S of glucose sensor 12 may be flexible. Therefore, the discomfort caused by the glucose sensor 12 after being implanted in the human body can be reduced.

In some examples, substrate S may be a flexible substrate. The flexible substrate can generally be made of polyethylene (PE), polypropylene (PP), polyimide (PI), polystyrene (PS), polyethylene terephthalate (PET), polyterephthalate Made from at least one of ethylene glycol esters (PEN).

In other examples, the flexible substrate S may be generally made of metal foil, ultra-thin glass, single-layer inorganic film, multi-layer organic film or multi-layer inorganic film, or the like.

In other examples, substrate S may be a non-flexible substrate. Non-flexible substrates may generally include less conductive ceramics, alumina or silica, etc. In this case, the glucose sensor 12 with a non-flexible base may also have points or sharp edges, thereby enabling the glucose sensor 12 to be implanted into the skin without the need for an auxiliary implantation device (not shown) (eg, , superficial layer of skin, etc.).

In some examples, the thickness of the glucose enzyme layer may be approximately 0.1 μm to 100 μm. Preferably, the thickness of the glucose enzyme layer may be approximately 2 μm to 10 μm, for example, 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 glucose enzyme layer may be 10 μm. In this case, the thickness of the glucose enzyme should be controlled within a certain level to avoid the decrease in adhesion caused by too much glucose enzyme, causing the material to fall off in the body, and to avoid the insufficient reaction caused by too little glucose enzyme and failure. Feedback normal glucose concentration information and other issues.

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 semipermeable membrane. A semipermeable membrane controls the amount of glucose. The semipermeable membrane can be provided on the glucose enzyme layer.

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-interference layer stacked on the diffusion control layer. In some examples, the diffusion control layer may be disposed outside the anti-interference 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. In this way, the tissue fluid or blood components passing through the semipermeable membrane can be reduced first, and then the interference substances can be blocked outside the semipermeable membrane through the anti-interference layer. Common interfering substances can include uric acid, ascorbic acid, acetaminophen, etc. that are commonly found in the body.

In some examples, the semipermeable membrane can control the passage rate of glucose molecules, that is, the semipermeable membrane can limit the number of glucose molecules in tissue fluid or blood that reach the glucose enzyme layer. Specifically, the diffusion control layer of the semipermeable membrane can effectively reduce the amount of glucose that diffuses to the glucose enzyme layer by a certain proportion.

In some examples, the semipermeable membrane can be biocompatible.

In other examples, glucose sensor 12 may include a biocompatible membrane.

In some examples, glucose sensor 12 may include working electrode 121, reference electrode 122, and counter electrode 123 (see Figure 5).

In some examples, the glucose sensor 12 after being pierced into the skin can perform a redox reaction with glucose in tissue fluid or blood through the glucose enzyme in the working electrode 121 and form a loop with the counter electrode 123 to generate a current signal.

In other examples, the reference electrode 122 may form a known and fixed potential difference with tissue fluid or blood. In this case, the potential difference between the working electrode 121 and tissue fluid or blood can be measured through the potential difference formed between the reference electrode 122 and the working electrode 121, so as to accurately grasp the voltage generated by the working electrode 121. Therefore, the voltage at the working electrode 121 can be automatically adjusted and maintained stable according to the preset voltage value to ensure that the measured current signal can accurately reflect the glucose concentration value.

Additionally, in some examples, counter electrode 123 may be made of platinum, silver, silver chloride, palladium, titanium, or iridium. Therefore, the electrochemical reaction at the working electrode 121 can be maintained without affecting the electrical conductivity. However, this embodiment is not limited thereto. In other examples, the counter electrode 123 may be made of at least one selected from gold, glassy carbon, graphite, silver, silver chloride, palladium, titanium or iridium. Therefore, the influence on the working electrode 121 can be reduced while maintaining good conductivity.

In some examples, monitoring module 10 may include an electronic system. Electronic systems can be used to store raw physiological parameter information. In this case, the electronic system can transmit the received original physiological parameter information through wireless communication methods such as Bluetooth, wifi, etc.

In some examples, the monitoring module 10 may transmit the acquired original physiological parameter information to the update module 30 through wireless communication.

In other examples, an external reading device may receive the raw physiological parameter information emitted by the electronic system. For example, an external reading device may receive the glucose concentration signal and display the glucose concentration value. In some examples, the glucose concentration value may be represented by a numerical value. In other examples, the reading device may graphically represent a trend in glucose concentration values over a predetermined time period. Additionally, in some examples, the reading device can display information such as pictures, animations, charts, graphs, value ranges, and numeric data.

In addition, since the glucose sensor 12 in this embodiment can realize continuous monitoring, it can achieve the purpose of continuously monitoring the human body glucose concentration value for a long time (for example, 1 day to 24 days). In addition, in some examples, the reading device may be a reader or a mobile phone APP. In other examples, the reading device may also be the collection module 20 (described later).

In some examples, monitoring module 10 may include a calibration algorithm. In other words, the monitoring module 10 may be equipped with a calibration algorithm 11 (see Figure 4).

In some examples, the monitoring module 10 may calibrate the original physiological parameter information based on the calibration algorithm 11 to generate calibrated physiological parameter information.

In some examples, the calibration algorithm 11 may be installed in the monitoring module 10 from the factory. In other examples, the calibration algorithm 11 may be downloaded by the user from a server, algorithm library, cloud, etc. through the network when first using it. In this case, the downloaded calibration algorithm 11 can be matched based on the user's personal information, such as the user's height, weight, age, reason for use and other personal information. In this way, the degree of personalization of the calibration algorithm 11 can be improved, making it easier to use for various groups of people and improving adaptability. In this case, the calibration algorithm 11 of the monitoring module 10 may be different for different users.

In some examples, calibration algorithm 11 has calibration parameters 111 . Calibration parameters 111 can be updated. The update method is described later. In this case, after the calibration parameters 111 are updated, the monitoring module 10 can 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 systems of monitoring module 10 may be used to store calibrated physiological parameter information. In this case, the electronic system can transmit the received calibrated physiological parameter information through wireless communication methods such as Bluetooth, wifi, etc.

In some examples, the monitoring module 10 may transmit the calibration physiology parameter information to the update module 30 through wireless communication.

In some examples, as described above, the calibration system 1 of the physiological parameter monitor may include an acquisition module 20 (see Figure 2 or Figure 3).

In some examples, the collection module 20 can be used to collect the blood of the subject 2 and obtain reference physiological parameter information in the blood.

In some examples, the user or the subject to be measured can collect reference physiological parameter information through the collection module 20 as needed. In other examples, the user or the subject to be measured can regularly collect reference physiological parameter information through the collection module 20 . Thus, the calibration algorithm 11 can be updated using the reference physiological parameter information (described later). Specifically, the user can use the collection module 20 to collect reference physiological parameter information once a day, once every two days, once every three days, or once a week.

However, examples of the present disclosure are not limited thereto. For example, the calibration system 1 may not use the acquisition module 20 . That is, the calibration system 1 may not update the calibration algorithm 11 . In this case, users such as Type II diabetics, pre-diabetics or even non-diabetics who do not require high measurement accuracy can obtain better measurements without having to update the calibration algorithm 11 value. This makes it easier for the above-mentioned types of users to use.

In some examples, the collection module 20 and the monitoring module 10 are separable. Thus, the blood of the subject 2 can be collected through the collection module 20 .

In other examples, the collection module 20 may be provided in the monitoring module 10 . Therefore, collection can be performed at any time through the collection module 20 .

In some examples, the reference physiological parameter information may be blood glucose concentration information. Thus, the collection module 20 can obtain blood glucose concentration information. However, 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 fingerstick blood glucose meter. The reference physiological parameter information may be blood glucose concentration information obtained by a fingertip blood glucose meter. As a result, more accurate blood glucose concentration information can be obtained from blood (see Figure 1).

In some examples, the usage process of the collection module 20 is as follows: prick the fingertip with a disposable needle, use a test paper or a straw to obtain a blood sample of the fingertip blood, and then place the blood sample into the detection device of the collection module 20 , and finally , the blood glucose concentration information (such as blood glucose concentration value) in the blood sample can be obtained.

In some examples, the collection module 20 may have a wireless communication unit, such as Bluetooth, WIFI, etc. As a result, signals can be transmitted or received wirelessly. In this case, the acquisition module 20 may transmit the acquired reference physiological parameter information to the update module 30 through wireless communication.

FIG. 6 is a schematic diagram showing various factors that affect the calibration parameters 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 illustrating the relationship between original physiological parameter information and original physiological parameter information in blood according to the embodiment of the present disclosure. FIG. 8 is a schematic diagram showing the 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 Figure 2 or Figure 3).

In some examples, the update module 30 may obtain original physiological parameter information, calibrated physiological parameter information, and reference physiological parameter information. Specifically, the update module 30 may receive the original 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 collection module 20 .

In some examples, the update module 30 may update the calibration algorithm 11 based on the original physiological parameter information, the calibrated physiological parameter information, and the reference physiological parameter information.

In some examples, update module 30 may be disposed in monitoring module 10 . Therefore, the calibration algorithm 11 in the monitoring module 10 can be updated in a timely manner.

In other examples, the update module 30 may be deployed in the cloud. The update module 30 arranged in the cloud can store the calibration parameters (described later) of each user's calibration algorithm 11 in a database, classify the users, and iteratively update the calibration parameters of the calibration algorithm 11 of similar users to generate a more suitable Calibration algorithm for this type of population11. As a result, the reliability of the calibration algorithm 11 is further improved.

In some examples, 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 with the reference physiological parameter information.

In some examples, the update module 30 may obtain the calibration parameters 111 based on the original physiological parameter information and the calibrated physiological parameter information to update the calibration algorithm 11 . Therefore, the calibration parameters 111 can be obtained through the update module 30 and the calibration algorithm 11 can be updated to further improve the adaptability of the calibration system 1 .

In some examples, if the calibrated physiological parameter information and the reference physiological parameter information do not converge, the calibration parameter 111 is updated. Thus, the calibration algorithm 11 can be updated by updating the calibration parameters 111 .

In some examples, as shown in FIG. 6 , the calibration parameter 111 may include at least one of an initial sensitivity, a sensitivity drift, an attenuation coefficient of sensitivity, and a temperature coefficient of the glucose sensor 12 . As a result, the reliability of the calibration algorithm 11 can be improved.

In other examples, the calibration parameters 111 may include a specific relationship between the sensor and sensitivity, baseline, drift, impedance, impedance/temperature relationship, and the specific relationship of the site where the sensor is implanted (abdomen, arm, etc.). In this case, the relationship between the calibration parameters 111 and various factors can be considered more comprehensively, so that different calibration algorithms 11 can be set for different users. Thus, the applicable range of the physiological parameter monitor can be increased. Specifically, the site where the sensor is implanted will be affected by different blood vessel densities.

In some examples, the calibration algorithm 11 may perform calibration based on 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 multiple possible values of the calibration information. A priori calibration distribution information together contains a range or distribution of values (e.g., describing their associated probabilities, probability density functions, likelihoods, or frequencies of occurrence) provided prior to a specific calibration procedure 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 between the blood glucose concentration information in the tissue fluid and the blood glucose concentration information in the blood. Thus, the blood sugar concentration information in the blood can be obtained from the blood sugar concentration information in the interstitial fluid. In some examples, there is a delay between the blood glucose concentration information in the interstitial fluid and the blood glucose concentration information in the blood. In other examples, the blood glucose concentration information in the interstitial fluid can be obtained by using a kinetic compensation method to obtain the blood glucose concentration information in the blood.

Below, the calibration process of the calibration system 1 is described in detail with reference to Figure 8:

In some examples, as shown in Figure 8, the user can use the monitoring module 10 to continuously monitor the subject 2 (which can also be the user himself). After starting the monitoring, the monitoring module 10 can measure the original physiological parameter information, and monitor The module 10 calibrates the original physiological parameter information through the calibration algorithm 11 installed therein, so that the calibrated physiological parameter information can be obtained and the calibrated physiological parameter information can be output.

In some examples, as shown in FIG. 8 , based on the user's needs or when the user has doubts about the calibrated physiological parameter information, the blood of the subject 2 can be collected through the collection module 20 and the reference physiological parameter information can be generated.

In some examples, if the acquisition module 20 generates or obtains reference physiological parameter information, the calibration physiological parameter information and the reference physiological parameter information will be matched through the update module 30 . Specifically, the update module 30 is used to obtain original physiological parameter information, calibrated physiological parameter information, and reference physiological parameter information, and match the calibrated physiological parameter information and the reference physiological parameter information. Wherein, matching may refer to comparing calibrated physiological parameter information and reference physiological parameter information.

In some examples, it is determined whether the calibrated physiological parameter information and the reference physiological parameter information converge. If they converge, the calibrated physiological parameter information is output and the calibration process ends; if they do not converge, the calibration parameters in the calibration algorithm 11 are updated. Specifically, the update module 30 updates the calibration parameters 111 in the calibration algorithm 11 based on the original physiological parameter information, the calibrated physiological parameter information and the reference physiological parameter information, thereby obtaining the calibration algorithm 11 that is more suitable for the subject 2 to be measured.

In some examples, the original physiological parameter information is calibrated again through the updated calibration algorithm 11, and calibrated physiological parameter information is generated. Specifically, in the monitoring module 10, the updated calibration algorithm 11 calibrates the original physiological parameter information to the regenerated calibrated physiological parameter information.

In some examples, the regenerated calibrated physiological parameter information is matched with the reference physiological parameter information until the calibrated physiological parameter information is converged and the calibration process is ended.

In the calibration system 1 of the physiological parameter monitor involved in the present disclosure, the calibration algorithm 11 can calibrate the original physiological parameter information obtained by the monitoring module 10 and generate the calibrated physiological parameter information. In this case, the update module 30 The calibration algorithm 11 can be obtained and updated 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 be calibrated based on the reference physiological parameter information to improve the adaptability of the calibration system.

Although the present invention has been specifically described above in conjunction with the drawings and embodiments, it can be understood that the above description does not limit the present invention in any form. Those skilled in the art can deform and change the present invention as necessary without departing from the essential spirit and scope of the present invention, and these deformations and changes all fall within the scope of the present 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.