CN115171884A - Method and system for analyzing blood glucose fluctuation of NC membrane adsorption insulin leakage - Google Patents

Abstract

The method comprises the steps of collecting a leakage image, adsorbing leakage at a target position by using a nitrocellulose membrane after a patient injects insulin, and shooting the nitrocellulose membrane after adsorption of the leakage and a reference object to obtain the leakage image; analyzing the leakage image to determine a leakage area in the leakage image; determining a leakage area based on the resolution of the leakage image, the leakage area and the reference pattern; determining the leakage amount corresponding to the leakage area based on the adsorption capacity and the leakage area of the nitrocellulose membrane; and determining the influence of the leakage amount on the blood glucose fluctuation of the patient based on the injection dose, the leakage amount, and a first blood glucose level and a second blood glucose level of the patient, wherein the first blood glucose level and the second blood glucose level are respectively blood glucose indexes before and after the insulin injection of the patient. Therefore, the leakage amount can be effectively, conveniently and non-invasively acquired to analyze the influence of the leakage amount on the blood glucose fluctuation.

Description

Method and system for analyzing blood glucose fluctuation of NC membrane adsorption insulin leakage

Technical Field

The present disclosure relates generally to the medical field of health-related information systems, and in particular, to a method and a system for analyzing blood glucose fluctuations in NC membrane-adsorbed insulin leakage.

Background

Diabetes mellitus is a lifelong chronic endocrine disease mainly characterized by insulin resistance and islet function reduction, and can cause a series of metabolic disorder syndromes such as high protein and high fat. The incidence of diabetes increases year by year and presents a trend of younger age, and often induces a series of complications (e.g., diabetic foot, diabetic nephropathy, etc.), seriously affects the quality of life and the health of life of patients, increases social and household economic burdens, and has become a public health problem worldwide.

Researchers have been working on diet, medication, exercise, etc. to find ways to control the stability of blood glucose in patients. For example, in terms of medication, insulin injection has become an important hypoglycemic mode of treatment for diabetes (e.g., type 2 diabetes), and by injecting a dose of insulin, a patient can control his or her own blood glucose level.

However, relevant medical clinical studies show that during insulin injection, there are problems such as drug remaining at the outlet of the injection device or drug solution leaking out after injection, which results in a decrease in the dose of insulin injected into the patient, which tends to cause instability in blood glucose control of the patient, and thus a decrease in blood glucose control effect, and no relevant studies have been found on how to quantitatively determine leakage and whether there is a correlation between leakage amount and blood glucose fluctuation.

Disclosure of Invention

The present disclosure has been made in view of the above circumstances, and an object thereof is to provide an analysis method and an analysis system capable of efficiently, conveniently, and noninvasively acquiring a leakage amount to analyze an influence of the leakage amount on blood glucose fluctuations.

Therefore, the first aspect of the disclosure provides an analysis method for blood glucose fluctuation of insulin leakage adsorbed by a nitrocellulose membrane, which includes acquiring a leakage image, wherein after a patient injects insulin, the nitrocellulose membrane is utilized to adsorb leakage at a target position, and after adsorption is completed, the nitrocellulose membrane adsorbed with the leakage is shot with a reference object with a known size to obtain the leakage image; performing image analysis on the leaked liquid image to determine a region aiming at the leaked liquid in the leaked liquid image and serve as a leaked liquid region; determining a leakage area based on the resolution of the leakage image, the leakage area and a reference object pattern in the leakage image; determining the leakage amount corresponding to the leakage area based on the adsorption capacity of the nitrocellulose membrane for adsorbing insulin and the leakage area; and determining the influence of the leakage amount on the blood glucose fluctuation of the patient based on the injection dose, the leakage amount, a first blood glucose level of the patient before the injection of insulin, and a second blood glucose level of the patient after the injection of insulin. In this case, the amount of the leakage liquid is effectively collected by the nitrocellulose membrane, the leakage area is intelligently and conveniently determined through image analysis, the leakage area corresponding to the leakage area is conveniently determined based on the reference object, and the leakage condition is quantitatively determined based on the leakage area and the adsorption capacity of the nitrocellulose membrane. Therefore, quantitative leakage conditions can be effectively, conveniently and non-invasively acquired to analyze the influence of the leakage amount on blood glucose fluctuation.

Further, in the analysis method according to the first aspect of the present disclosure, optionally, the target site includes an insulin outlet of an injection device for injecting insulin and a skin surface around the injection site of the patient, the injection device including at least one of a needle-free injection device and a needle-containing injection device. In this case, the leakage at the target site can substantially encompass the medical fluid that is not injected into the patient, and the influence of the leakage on the blood glucose excursion of the patient and/or the effectiveness of the injection behavior can subsequently be effectively assessed.

In addition, in the analysis method related to the first aspect of the present disclosure, optionally, after the nitrocellulose membrane is continuously adsorbed for a first preset time to determine that adsorption completes the leakage, the leakage image is collected within a second preset time, where the first preset time is determined by the adsorption capacity, and the second preset time is determined by the volatilization time of insulin for the nitrocellulose membrane. Under the condition, based on stricter time control, the leakage can be effectively adsorbed, the probability of leakage volatilization is reduced, a leakage image which more accurately represents the leakage condition can be obtained, and the calculation accuracy of the leakage area is improved.

Further, in the analysis method relating to the first aspect of the present disclosure, optionally, in determining the influence of the leakage amount on the blood glucose excursion of the patient, a plurality of target data for a plurality of injections of insulin to the patient are acquired, each target data of the plurality of target data including the injection dose, the leakage amount, the first blood glucose level, and the second blood glucose level, and a correlation between a change in the leakage amount and the blood glucose excursion of the patient is determined based on the plurality of target data. In this case, the influence of the leakage amount on the blood glucose fluctuation can be determined by comparing the leakage amount corresponding to the multiple injections with the corresponding blood glucose index.

In addition, in the analysis method according to the first aspect of the present disclosure, optionally, the number of pixels in the leakage area is determined based on a resolution of the leakage image, the area of the pixels is determined based on the reference pattern in the leakage image, and the leakage area is determined based on the number of pixels and the area of the pixels. This enables the determination of the leakage area based on the reference object.

In addition, in the analysis method according to the first aspect of the present disclosure, optionally, the analysis method further includes determining effectiveness of the injection behavior based on the leakage amount, and then creating a first guidance message and outputting the first guidance message to a subject who implements the injection behavior to normalize the injection behavior; and/or the analysis method further comprises determining a correlation between the amount of leakage and the patient's blood glucose excursion based on the amount of leakage, thereby creating a second guidance message and outputting the second guidance message to a subject performing an injection behavior to normalize the injection behavior. Under the condition, the effectiveness of the injection behavior is determined, the risk that a patient does not inject enough insulin can be reduced, adverse reactions can be reduced, the effectiveness of subsequent injection behaviors can be improved by timely standardizing the injection behavior, economic problems caused by insufficient insulin injection are reduced, and the method has important clinical value. In addition, determining the correlation between leakage and patient blood glucose excursions can have practical guidance on blood glucose excursions in patients with poor pancreatic islet function.

In addition, in the analysis method according to the first aspect of the present disclosure, optionally, the analysis further includes analyzing leakage amounts of different injection devices or leakage amounts of different injection doses. In this case, the injection device having a relatively small leakage amount can be determined by analysis, and the injection behavior of the patient can be guided. In addition, the relationship between the injection dose and the leakage amount can be obtained, and the injection dose of the patient can be guided.

Further, in the assay method according to the first aspect of the present disclosure, optionally, the reference is a scale. In this case, the area of the pixel point can be conveniently determined through the scales on the ruler.

In addition, in the analysis method according to the first aspect of the present disclosure, optionally, the color of the nitrocellulose membrane is white, in the image analysis, the contrast of the leakage image is enhanced to obtain an enhanced image, pixel points in the enhanced image are classified to obtain a first type of pixels and a second type of pixels, a region corresponding to one type of pixels with a large gray mean value in the first type of pixels and the second type of pixels is used as a background region, and a region corresponding to the other type of pixels is used as the leakage region. In this case, the leakage area can be determined based on the color change of the nitrocellulose membrane after adsorption of insulin, and a more accurate leakage area can be obtained.

The second aspect of the present disclosure provides an analysis system for blood glucose excursion of an insulin leakage adsorbed by a nitrocellulose membrane, comprising: a processor; and a memory for storing instructions for execution by the processor to perform the analysis method of the first aspect of the present disclosure.

According to the present disclosure, an analysis method and an analysis system capable of acquiring the amount of leakage effectively, conveniently, and non-invasively to analyze the influence of the amount of leakage on the fluctuation of blood glucose can be provided.

Drawings

The 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 diagram illustrating an example of an analysis environment to which examples of the present disclosure relate.

Fig. 2 is an exemplary flowchart illustrating an analysis method of blood glucose excursion in accordance with an example of the present disclosure.

Fig. 3 is an exemplary flow chart illustrating a reference-based acquisition of weep images in accordance with examples of the present disclosure.

Fig. 4 is a schematic diagram showing a leakage image using a reference according to an example of the present disclosure.

Fig. 5 is an exemplary flowchart illustrating an image analysis method according to an example of the present disclosure.

Fig. 6A is a histogram illustrating gray values of a brightness component prior to histogram equalization according to an example of the present disclosure.

Fig. 6B is a histogram illustrating gray values of lightness components after histogram equalization according to an example of the present disclosure.

Fig. 7A is a graph showing a comparison of needle and needle-free weep areas in accordance with examples of the present disclosure.

Fig. 7B is a comparative graph showing weep areas with and without a needle for different injection doses in accordance with examples of the present disclosure.

Detailed Description

Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In the following description, the same components are denoted by the same reference numerals, and redundant description thereof is omitted. The drawings are schematic, and the proportions of the dimensions of the components and the shapes of the components may be different from the actual ones. It is noted that the terms "comprises" and "comprising," and any variations thereof, in this disclosure, such that a process, method, system, article, or apparatus that comprises or has a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include or have other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. All methods described in this disclosure can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context.

As mentioned above, during insulin injection, there are problems that the drug remains at the outlet of the injection device (i.e., the outlet of the drug solution) after injection or the drug solution leaks out. The main causes of this problem are: the outlet of the injection device is fine, and the time for injecting the liquid medicine into the body is relatively long when the liquid medicine is injected; and with the increasing of the amount of the insulin injection, the absorption speed of the liquid medicine at the injection position (also called as the injection position) is gradually reduced; when the injection part (for example, a needle of a needle-containing injection device or a nozzle of a needle-free injection device) is not removed in time after the insulin is injected, the liquid medicine leaks out from the outlet when the external temperature changes (from cold to hot).

The inventor finds that the leakage amount is closely related to the injection device and the injection dosage through research. In addition, the amount of leakage can have an effect on blood glucose fluctuations. Therefore, a method and a system for analyzing blood glucose fluctuation of NC membrane-adsorbed insulin leakage are provided. The method and the system for analyzing the blood glucose fluctuation of the leakage of the NC membrane-adsorbed insulin can effectively, conveniently and non-invasively acquire the leakage amount. In addition, the influence of the leakage amount on the blood glucose fluctuation can be analyzed. The analysis method of blood glucose excursions according to the examples of the present disclosure may be simply referred to as an analysis method, a guidance method, an evaluation method, or the like, in some cases, and may be simply referred to as an analysis method hereinafter. The blood glucose fluctuation analysis system according to the example of the present disclosure may be simply referred to as an analysis system, a guidance system, an evaluation system, or the like in some cases, and may be simply referred to as an analysis system hereinafter.

Fig. 1 is a schematic diagram illustrating an example of an analysis environment to which examples of the present disclosure relate. The scenes described in the examples of the present disclosure are for the purpose of more clearly illustrating the technical solutions of the present disclosure, and do not constitute a limitation on the technical solutions provided by the present disclosure.

As shown in fig. 1, the analysis environment may include an adsorbent material 10 for adsorbing insulin. The adsorbent material 10 may be any material capable of adsorbing proteins such as insulin. After the patient has finished injecting insulin, the absorbent material 10 may be attached to a target site (shown in fig. 1 as an illustration of the absorbent material 10 attached to the skin surface around the injection site of the patient) to collect the leakage, the absorbent material 10 with the collected leakage may be placed near the reference object 20 located on the same plane as the absorbent material 10, and an image of the absorbent material 10 and the reference object 20 may be collected by the computing device 30 as a leakage image.

With continued reference to fig. 1, the analysis environment may include a computing device 30. The computing device 30 may implement an analysis method that may acquire images of the adsorption material 10 and the reference 20 as leakage images, acquire leakage amounts based on the leakage images, and determine the effects of the leakage amounts on the blood glucose fluctuations of the patient. In some examples, computing device 30 may also receive blood glucose data transmitted by dynamic blood glucose monitoring system 40. Thereby, the influence of the amount of leakage on the blood glucose excursion of the patient can be determined in combination with the blood glucose data.

In some examples, the analysis method may be stored on computing device 30 in the form of computer program instructions and executed by computing device 30. In some examples, computing device 30 may include one or more processors and one or more memories. The processor may execute computer program instructions. The memory may be used to store computer program instructions. The processor of computing device 30 may implement the analysis method by executing computer program instructions on the memory.

In some examples, computing device 30 may include, but is not limited to, a laptop, a tablet, a cell phone, a desktop, or a virtual computer (a virtual computer may refer to a virtual machine that has complete hardware system functionality and runs in a completely isolated environment, emulated by software), or the like. In some examples, the number of computing devices 30 may be multiple. In some examples, a portion of the plurality of computing devices 30 may be used to acquire a weep image and another portion may be used to perform steps in the analysis method other than acquiring a weep image. For example, a weep image may be captured using one computing device 30, which may be a cell phone, and transmitted to another computing device 30, which may be a desktop or virtual computer, for processing.

With continued reference to fig. 1, the analysis environment may include a dynamic blood glucose monitoring system 40. The ambulatory blood glucose monitoring system 40 may collect and transmit blood glucose data of the patient to the computing device 30. In particular, the sensors in the dynamic blood glucose monitoring system 40 may be partially or fully placed under the skin of the patient to collect blood glucose data of the patient, which may be transmitted to the computing device 30 via a receiver located outside the patient's body.

The method and the system for analyzing the blood glucose fluctuation of the leakage of the insulin adsorbed by the NC membrane according to the disclosed example are characterized in that after the insulin is injected into a patient, the leakage at a target position related to the leakage amount is adsorbed by the adsorbing material 10, after the leakage is completely adsorbed, the leakage image of the adsorbing material 10 after the leakage is adsorbed is subjected to image analysis to determine a leakage area, the leakage area is determined based on the leakage area, then the leakage amount corresponding to the leakage area is determined based on the adsorption capacity of the adsorbing material 10 for adsorbing the insulin and the leakage area, and finally the influence of the leakage amount on the blood glucose fluctuation of the patient is determined. In this case, the leakage is effectively collected by the adsorbent 10, and the leakage area is intelligently and conveniently determined by image analysis, and the leakage is quantitatively determined based on the leakage area and the adsorption capacity of the adsorbent 10. Therefore, quantitative leakage conditions (namely, the leakage amount) can be effectively, conveniently and non-invasively acquired to analyze the influence of the leakage amount on the blood glucose fluctuation.

The adsorbent material 10 according to the examples of the present disclosure may be loaded with an adsorbent. The adsorbent may be any substance having the ability to adsorb insulin. Preferably, the adsorbent may be nitrocellulose. In some examples, the adsorption material 10 loaded with nitrocellulose may be a nitrocellulose membrane (also referred to as an NC membrane). Nitrocellulose membrane is a microporous filter membrane that adsorbs proteins, while insulin is a protein hormone. In this case, the nitrocellulose membrane has strong adsorbability to insulin, and can effectively adsorb insulin. In some examples, the nitrocellulose membrane may have a substantially uniform pore size. Under this condition, can adsorb the insulin uniformly, and then reduce the follow-up degree of difficulty of calculating the weeping volume based on weeping area.

In some examples, nitrocellulose membranes may be used as carriers for C/T lines in colloidal gold test paper. In this case, the adsorbing material 10 may be a colloidal gold test paper, and the leakage image may be directed to the colloidal gold test paper.

In addition, the nitrocellulose membrane is convenient to obtain, and the convenience for obtaining the leakage amount can be further improved. The inventors have studied and verified that the adsorption of insulin by applying a nitrocellulose membrane to the surface of human skin is safe and non-invasive, and can effectively adsorb leakage generated after the injection of insulin (i.e., leakage at a target site described later).

The analysis method related to the disclosed example can quantitatively evaluate the leakage situation and can analyze the influence of the leakage quantity on the blood sugar fluctuation. The following describes an example of the present disclosure by taking the adsorbing material 10 as a nitrocellulose membrane, and does not represent a limitation of the present disclosure. Fig. 2 is an exemplary flowchart illustrating an analysis method of blood glucose excursions, according to an example of the present disclosure.

As shown in fig. 2, in some examples, the analysis method may include acquiring a weeping image (step S102), performing image analysis on the weeping image to determine a region in the weeping image for weeping and as a weeping region (step S104), determining a weeping area based on the weeping region (step S106), determining a weeping amount based on the weeping area (step S108), and determining an effect of the weeping amount on blood glucose fluctuations of the patient (step S110).

Referring to fig. 2, in the present embodiment, in step S102, a leakage image may be acquired.

In some examples, the weep image may be a color image or a grayscale image. Preferably, the weep image may be a color image. A color bleed-over image allows more detail of the bleed-over condition.

In addition, the acquisition device for acquiring the leakage image may be any device having an imaging function. For example, the capture device may include, but is not limited to, a cell phone, a computer, or a camera. In some examples, the acquisition device may be the computing device 30 described above. Preferably, the acquisition device may be a mobile phone. In this case, since the mobile phone is easy to handle, it is easy to be received by the patient or the subject who performs the injection, and the convenience of acquiring the amount of leakage liquid can be further improved. In some examples, a cell phone may integrate applications for implementing the analysis methods related to examples of the present disclosure to acquire a weeping image and obtain a weeping amount based on the weeping image. In some examples, an integrated application on the cell phone may also be used to determine the effect of the amount of leakage on the blood glucose excursion of the patient.

In this embodiment, the leakage image may be an image of the nitrocellulose membrane after the patient has absorbed the leakage after the patient has injected insulin. Specifically, after the patient injects insulin, the nitrocellulose membrane can be used for adsorbing the leakage at the target position related to the leakage amount, and after the leakage is adsorbed, an image corresponding to the nitrocellulose membrane after the leakage is adsorbed can be collected as a leakage image.

In some examples, after the adsorption with the nitrocellulose membrane is continued for a first preset time to determine that the adsorption is completed, a leakage image may be acquired for a second preset time. In addition, the first preset time may be determined by the adsorption capacity of the nitrocellulose membrane. The second preset time may be determined by the evaporation time of insulin to the nitrocellulose membrane. Under the condition, based on stricter time control, the leakage can be effectively adsorbed, the probability of leakage volatilization is reduced, a leakage image which more accurately represents the leakage condition can be obtained, and the calculation accuracy of the leakage area is improved.

In some examples, the first preset time may be a first fixed value (e.g., an empirical value) related to the adsorption capacity of the nitrocellulose membrane. In addition, the first fixed value may be a range. In some examples, the first predetermined time may be obtained by multiple experiments in which the nitrocellulose membrane adsorbs the leakage. In other examples, the first preset time may be estimated based on the adsorption capacity of the nitrocellulose membrane.

In some examples, the second preset time may be a second fixed value (e.g., an empirical value) related to the evaporation time of insulin for the nitrocellulose membrane. In addition, the second fixed value may be a range. In some examples, the second preset time may be obtained by a plurality of tests to verify the volatilization time of the insulin adsorbed by the nitrocellulose membrane. In some examples, the second preset time may be less than 30 seconds. In some examples, the requirement for the second predetermined time may be reduced by increasing the stability of the nitrocellulose membrane to adsorb insulin.

As described above, an image corresponding to the nitrocellulose membrane after adsorbing the leakage may be collected as a leakage image. In some examples, an image of the nitrocellulose membrane after adsorption of the leakage corresponding to the reference 20 may be collected as a leakage image. That is, the leakage image may include both a leakage pattern (i.e., a pattern of a region for leakage) and a pattern of the reference object 20 (which may also be simply referred to as a reference object pattern). In this case, it is then possible to determine the leakage area conveniently on the basis of the reference 20. In addition, due to the reference object 20, the requirement for consistency of the acquisition conditions (such as the resolution, the focal length, the shooting distance and the like of the acquisition equipment) is low, and the convenience of acquiring the leakage image can be improved.

In some examples, the dimensions of the reference 20 may be known. That is, the reference object 20 may be any item of known dimensions. For example, the reference object 20 may include, but is not limited to, a coin, a ruler, and the like. Preferably, the reference object 20 may be a ruler. In this case, the pixel area (i.e. the area of a single pixel) can be conveniently determined by the scale on the scale.

In some examples, during acquisition, the nitrocellulose membrane after leakage adsorption may be photographed with a reference 20 of known dimensions to obtain a leakage image. In some examples, the nitrocellulose membrane may be in the same plane as the reference 20 when photographed. In this case, the distance between the nitrocellulose membrane and the reference substance 20 and the collection device is substantially the same, which can reduce the difficulty in calculating the leakage area subsequently.

Fig. 3 is an exemplary flow chart illustrating the acquisition of a weep image based on a reference 20 in accordance with examples of the present disclosure. Fig. 4 is a schematic diagram showing a leakage image using the reference 20 according to the example of the present disclosure.

In particular, fig. 3 shows a process for acquiring a weep image based on the reference object 20, which may comprise the following steps:

step S202: the patient is injected with insulin.

Step S204: after completion of insulin injection, the leakage at the target site can be collected using a nitrocellulose membrane. For example, a nitrocellulose membrane may be attached to the target site to collect the leakage.

Step S206: the nitrocellulose membrane with the leaked liquid collected can be placed near a reference 20 of known size lying on the same plane as the nitrocellulose membrane. The vicinity of the reference object 20 may be, for example, above, below, left, right, or the like of the reference object 20.

Step S208: the nitrocellulose membrane after the leakage is collected may be photographed with the reference 20 to acquire a leakage image. As an example, fig. 4 is a schematic of a leakage image showing that the reference 20 is a scale, the adsorbing material 10 is a nitrocellulose membrane, and the nitrocellulose membrane is placed above the scale, wherein fig. 4 shows a nitrocellulose membrane pattern 11 representing the nitrocellulose membrane, a leakage pattern 111 in the nitrocellulose membrane pattern 11, a scale pattern 21 representing the scale, and a background cloth pattern 50 representing the background cloth. The background cloth can be used to suppress noise caused by the imaging environment, and is advantageous in distinguishing the regions corresponding to the adsorbent 10 and the reference material 20 from the leaked liquid image.

In some examples, there may be a gap between the weep pattern and the reference pattern in the weep image. In this case, the mutual influence of the leakage pattern and the reference pattern can be reduced, and it is advantageous to acquire images of the respective regions for image analysis, respectively.

However, examples of the present disclosure are not limited thereto, and in other examples, the reference object 20 may not be used (i.e., the reference object pattern may not be included in the leakage image), and is described in detail later in determining the leakage area.

As mentioned above, the leakage at the target site may be adsorbed by a nitrocellulose membrane. In some examples, the target location may be any location or locations associated with a leak. In some examples, the target location may include an insulin outlet of an injection device used to inject insulin and a skin surface around the injection location of the patient. In this case, the leakage at the target site can substantially encompass the medical fluid that is not injected into the patient, and the influence of the leakage on the blood glucose excursion of the patient and/or the effectiveness of the injection behavior can subsequently be effectively assessed.

In some examples, leaks corresponding to different locations in the target location may be distributed at different locations of the nitrocellulose membrane. In this case, the leakage situation of different positions can be distinguished in the leakage image obtained by one-time acquisition, and then the amount of leakage at each position and the total amount of leakage at a plurality of positions can be obtained simultaneously.

In other examples, the target location may also be one of the insulin outlet of the injection device and the skin surface surrounding the injection location of the patient. This makes it possible to obtain the amount of leakage at each position. Specifically, the target position may be selected according to the purpose of detecting the amount of leakage liquid.

In some examples, the injection device may include at least one of a needle-free injection device (which may also be referred to as a jet injection device) and a needle injection device. In this case, leakage amounts corresponding to different injection devices can be obtained, which is advantageous for the patient to select an appropriate injection device. The needleless injection device can utilize a specific device to generate instantaneous high pressure, and the instantaneous high pressure jets the liquid medicine to the surface of the skin through a very thin nozzle to form micropores, so that the liquid medicine is directly dispersed to subcutaneous tissues. Alternatively, for a needleless injection device, the insulin outlet may be a nozzle. For a needle injection device, the insulin outlet may be a needle tip.

The nitrocellulose membrane may have any color that can cause a difference in color between a region where leakage occurs after adsorption of insulin and a region where leakage does not occur. Preferably, the nitrocellulose membrane may be white. In this case, the white nitrocellulose membrane, after adsorbing insulin, becomes darker in appearance, which is advantageous for distinguishing a leakage area in subsequent image analysis.

In addition, for the nitrocellulose membrane capable of forming a color difference after adsorbing insulin, there may be a color difference between an area for no leakage in the leakage image (may be simply referred to as a background area) and an area for leakage (that is, a leakage area). That is, the gray values of the pixel points in the background area and the leakage area in the leakage image can respectively belong to different gray intervals. Under the condition, the leakage area is distinguished by utilizing the color change of the nitrocellulose membrane after the insulin is adsorbed, and the method is more convenient and faster compared with a scheme of generating color intensity by utilizing reagent reaction.

Referring back to fig. 2, in the present embodiment, in step S104, image analysis may be performed on the leakage image to determine a region for leakage in the leakage image and to serve as the leakage region.

In some examples, in image analysis, the weeping image may be segmented to obtain weeping regions. For example, the weep image may be segmented using an image segmentation algorithm to extract the weep region. The image segmentation algorithm may include, but is not limited to, active contours, grabcut (graph cut), or threshold segmentation methods, etc.

In addition to the image segmentation algorithms mentioned above. Examples of the present disclosure also provide an image analysis method. The image analysis method can enhance the contrast of the leakage image to obtain an enhanced image, and classify pixel points in the enhanced image to determine the leakage area. Fig. 5 is an exemplary flowchart illustrating an image analysis method according to an example of the present disclosure. Fig. 6A is a histogram illustrating gray values of brightness components prior to histogram equalization according to an example of the present disclosure. Fig. 6B is a histogram illustrating gray values of lightness components after histogram equalization according to an example of the present disclosure.

Referring to fig. 5, the image analysis method may include contrast-enhancing the weep image to obtain an enhanced image (step S302). This can improve the contrast between the leakage area and another area in the enhanced image.

In some examples, in contrast enhancement, the color space of the weep image may be converted to a target color space having a lightness component (which may also be referred to as a luminance component), the grayscale values of the lightness component in the target color space are histogram equalized, and the grayscale values of the lightness component are converted back to an RGB (Red: green, blue: blue) space via the histogram equalized target color space to obtain an enhanced image.

As an example, fig. 6A and 6B respectively show histograms of gradation values of lightness components before and after histogram equalization. It can be seen that, before histogram equalization, two peaks (which may correspond to a background region and a leakage region) are clearly seen in fig. 6A, and the gray scale is distributed in a narrower interval (i.e., the contrast of the leakage image is not high). After the histogram equalization, the gray values in fig. 6B are distributed more uniformly, and the range of gray value difference between the pixels is increased, so that the effect of enhancing the contrast in the image is achieved.

In some examples, for gray values of the brightness component, histogram equalization may correspond to a cumulative distribution function that satisfies the formula:

where k may represent the gray value of the lightness component, n _k The number of pixel points with the gray value of the lightness component being k in the leaked liquid image can be represented, N can represent the total number of the pixel points of the leaked liquid image, and S _k Lightness component, which can be represented as kThe gray value of (a) is subjected to histogram equalization. In some examples, for an 8-bit grayscale image, k ∈ [0,255 ∈ [ ]]。

In some examples, the target color space may also include a hue component and a saturation component. For example, the target color space may be an HSV (Hue, saturation, value, lightness) space or an HSI (Hue, saturation, intensity) space. Thereby, an enhanced image can be generated by either the HSV space or the HSI space.

In some examples, for a weep image in which other patterns (e.g., a reference object pattern or a background cloth pattern) are present, contrast enhancement may be performed on an image of a region for the weep in the weep image to obtain an enhanced image. For example, an image of a region of the weep image for the weep may be captured and contrast enhanced to obtain an enhanced image.

Referring back to fig. 5, the image analysis method may further include classifying pixel points in the enhanced image to determine a leakage area (step S304).

In some examples, the pixels in the enhanced image may be classified to obtain two types of pixels, a target type of pixel may be selected from the two types of pixels, and a leakage area may be determined based on an area corresponding to the target type of pixel.

As described above, the white nitrocellulose membrane becomes darker in appearance when adsorbing insulin, and is displayed at a lower gradation value on the enhanced image, so that the region of the enhanced image having a lower gradation value may be a leakage region. Specifically, the pixel points in the enhanced image may be classified to obtain a first type of pixel and a second type of pixel, a region corresponding to a type of pixel with a large gray average value in the first type of pixel and the second type of pixel is used as a background region, and a region corresponding to another type of pixel is used as a leakage region. In this case, the leakage area can be determined based on the color change of the nitrocellulose membrane after adsorption of insulin, and a more accurate leakage area can be obtained.

In some examples, the obtaining of the classification of the first type of pixels and the second type of pixels may be K-means clustering. Specifically, in K-means clustering, K may be set to be 2, a pixel point in an enhanced image may be a sample, gray values of three channels (may also be referred to as three spaces) in RGB spaces in each sample are used as features, and unsupervised clustering is performed on the sample to obtain a first type of pixels and a second type of pixels. Therefore, two types of pixel points can be obtained based on K-means clustering.

In some examples, in the image analysis method, the leakage area may also be adjusted by convex hull fitting. Under the condition, the influence of isolated pixel points can be reduced, and the accuracy of calculating the liquid leakage area is further improved. In addition, the liquid leakage area can be regulated as much as possible, and the liquid leakage condition can be observed conveniently. Specifically, connectivity analysis may be performed on the liquid leakage region to determine at least one connection component, obtain a convex hull of each connection component in the at least one connection component, and adjust the liquid leakage region to a convex hull corresponding to the at least one connection component. In some examples, the convex hull may be the smallest convex polygon of the respective connected components.

In addition, each connected component may include a plurality of pixel points that are connected to each other, and in some examples, the connectivity analysis may be an eight neighborhood connectivity analysis. Specifically, among the pixels in the region corresponding to the pixel in the target category, the connectivity between the pixel and the pixels in the surrounding eight neighborhoods may be analyzed to determine a plurality of pixels that are connected to each other. In other examples, the connectivity analysis may also be a four neighborhood connectivity analysis.

In some examples, the leaky region may also be laplacian filtered to adjust the edges of the leaky region prior to convex hull fitting. Thus, the calculation amount of the subsequent convex hull fitting can be reduced.

Referring back to fig. 2, in the present embodiment, in step S106, the leakage area (i.e., the actual area of insulin adsorbed by the nitrocellulose membrane) may be determined based on the leakage area.

In some examples, the weep area may be determined based on a resolution of the weep image and the weep region. The resolution of the leakage image can be used to determine the number of pixels in the corresponding region in the leakage image.

As described above, the images of the nitrocellulose membrane after adsorbing the leakage and the reference 20 can be collected as leakage images. In some examples, the weep area may be determined based on a resolution of the weep image, a weep area, and a reference pattern in the weep image.

Specifically, for the reference 20 with a known size, the number of pixels in the leakage area may be determined based on the resolution of the leakage image, the area of the pixels (that is, the area of a single pixel) may be determined based on the reference pattern in the leakage image, and the leakage area may be determined based on the number of pixels and the area of the pixels in the leakage area. This allows the determination of the leakage area based on the reference material 20.

Taking reference 20 as an example, because the scale is provided with the scale, the part of the leakage image including the scale pattern can be subjected to edge detection based on an image processing algorithm to obtain a region with clear scale on the scale pattern, and then a scale range corresponding to the region can be obtained. In some examples, the scale range may be divided by the number of pixels between the scale range to obtain the side length of the pixels.

As mentioned above, in other examples, the reference 20 may not be used. For example, the acquisition conditions can be fixed so that the pixel point areas of the pixel points in all the leakage images are substantially fixed, and then the leakage area can be converted into the leakage area based on the known pixel point areas and the known pixel point number. For another example, the pixel interval (the actual size represented by the distance between two pixels in the leakage image) may be obtained based on the leakage image in the DICOM (Digital Imaging and Communications in Medicine) format, the pixel interval may be used as the side length of the pixel, the pixel area may be obtained based on the side length of the pixel, and the leakage area may be determined based on the number of pixels in the leakage area and the pixel area.

With continued reference to fig. 2, in the present embodiment, in step S108, the amount of leakage may be determined based on the leakage area.

In some examples, the amount of leakage corresponding to the leakage area may be determined based on the adsorption capacity of the nitrocellulose membrane to adsorb insulin (hereinafter may be simply referred to as adsorption capacity) and the leakage area. In general, the particle size, pore size, porosity, and the like of the nitrocellulose membrane may have an effect on the adsorption capacity. In some examples, the adsorption capacity may be a fixed value. In some examples, the adsorption capacity may be obtained by experimentation. In some examples, the adsorption capacity may be a known parameter of the nitrocellulose membrane. In some examples, the adsorption capacity may be expressed in terms of the dose of insulin adsorbed per unit area of the nitrocellulose membrane.

In some examples, the adsorption capacity may be adjusted according to pixel values of pixel points in the leakage area. For example, a weight may be determined based on the gray value of the saturation component, which may be used to adjust the adsorption capacity. Under the condition, the adsorption capacity is adjusted by combining the pixel values of the pixel points, and the possible slight difference of insulin dosage in the leakage area is considered, so that more accurate leakage amount can be obtained.

In some examples, a formula for converting the weep area to the weep amount may be established based on the adsorption capacity to automatically convert the weep area to the weep amount. Therefore, the liquid leakage area can be conveniently converted into the liquid leakage amount. In some examples, a formula for converting the leakage area to the leakage amount may be established based on the adsorption capacity and the pixel values of the pixel points in the leakage region to automatically convert the leakage area to the leakage amount.

With continued reference to fig. 2, in the present embodiment, in step S110, the effect of the amount of leakage on the blood glucose excursion of the patient may be determined. In other examples, the effect of a weeping condition on the blood glucose excursion of the patient may also be determined based on a weep area or a weep area.

In the present embodiment, the blood glucose excursion may also be referred to as blood glucose variability. Due to the low ability of diabetics to control blood glucose themselves, blood glucose excursions often exceed the correct blood glucose range. During the insulin injection process, if the dosage of insulin injected into the body of a patient is insufficient, the blood sugar control of the patient is unstable, and the blood sugar fluctuation is easily caused.

In some examples, in step S110, the change in the blood glucose indicator before and after the patient injects insulin may be analyzed to determine the effect of the leakage on the patient' S blood glucose excursions. Further, the inventors considered that the absorption rate of the drug solution at the injection site gradually decreases with the increase of the injection dose of insulin, and the leakage amount is affected. In other words, the amount of leakage may be related to the dose of insulin that the patient injects per injection. In some examples, the impact of an injected dose on a patient's blood glucose excursions may be analyzed in combination. This enables more comprehensive analysis of the influence of blood glucose fluctuations.

Specifically, the effect of the amount of leakage on the blood glucose excursion of the patient may be determined based on the injected dose, the amount of leakage, and the blood glucose level of the patient before and after the injection of insulin. In this case, the influence of the leakage of the liquid to the fluctuations in blood glucose can be obtained for the patient at the respective injection dose (i.e. the insulin dose), so that timely interventions can be made (e.g. dose adjustment or by guiding the normative injection behaviour).

In addition, the blood glucose levels of the patient before and after the insulin injection may include a first blood glucose level and a second blood glucose level of the patient, the first blood glucose level may be the blood glucose level of the patient before the insulin injection, and the second blood glucose level may be the blood glucose level of the patient after the insulin injection. In addition, blood glucose levels may also be referred to as blood glucose concentrations.

In some examples, the blood glucose level (i.e., the first blood glucose level and/or the second blood glucose level) of the patient may be determined by the finger blood collection device and/or the dynamic blood glucose monitoring system 40. For example, the patient may acquire the patient's blood glucose level over time by wearing the dynamic blood glucose monitoring system 40. Under the condition, the blood glucose data of the patient can be conveniently and timely acquired, so that the influence of the leakage amount on the blood glucose fluctuation can be better analyzed.

In some examples, in determining the effect of the amount of leakage on the blood glucose excursion of the patient, a plurality of target data for a plurality of injections of insulin by the patient (i.e., a plurality of target data corresponding to a plurality of injections of insulin by the patient) may be obtained, and a correlation between a change in the amount of leakage and the blood glucose excursion of the patient may be determined based on the plurality of target data. The target data (i.e., the respective target data) for each injection of insulin may include an injection dose, an amount of leakage, a first blood glucose level, and a second blood glucose level. In this case, the influence of the leakage amount on the blood glucose fluctuation can be determined by comparing the leakage amount corresponding to the multiple injections with the corresponding blood glucose index.

In some examples, in determining the effect of the amount of leakage on the blood glucose excursion of the patient, a plurality of target data corresponding to a plurality of days of insulin injection by the patient may also be obtained, a blood glucose indicator for the plurality of days may be obtained based on the plurality of target data, and the effect of the amount of leakage on the blood glucose excursion of the patient may be analyzed based on the daily injection dose, the amount of leakage, and the blood glucose indicator. In this case, the influence of the amount of leakage on the fluctuation of blood glucose for a plurality of days in the corresponding injection dose of the patient can be obtained. I.e. the continuous effect of leakage on blood glucose fluctuations. In some examples, a preset number of days (e.g., 7 days) may be continuously monitored to obtain a blood glucose indicator for multiple days.

In some examples, the multi-day blood glucose indicators may include, but are not limited to, blood glucose Standard Deviation (SD), mean of Daily Differences (MODD), mean Amplitude of blood glucose fluctuation (MAGE), time within a blood glucose target range (TIR), and the like.

In some examples, adverse events occurring to the patient may also be recorded. Therefore, the influence of the leakage amount on the fluctuation of blood sugar can be analyzed by integrating adverse reaction conditions. In some examples, adverse reaction conditions may include, but are not limited to, injection site pain, injection site allergies or hypoglycemia, and the like.

As mentioned above, the target site may comprise the insulin outlet of the injection device for injecting insulin and the skin surface around the injection site of the patient. In this case, the leakage at the target site can substantially contain the medical fluid that is not injected into the patient, and the effectiveness of the injection behavior can be subsequently evaluated effectively.

In some examples, the analysis method may further include normalizing injection behavior based on the amount of leakage. In some examples, the effectiveness of the injection behavior may be determined based on the amount of leakage, and a corresponding guidance message may be created to normalize the injection behavior. Specifically, the effectiveness of the injection behavior may be determined based on the amount of leakage, thereby creating a first guidance message and outputting the first guidance message to a subject performing the injection behavior to normalize the injection behavior. Under the condition, the risk of insufficient insulin injection of a patient can be reduced, adverse reactions can be reduced, the effectiveness of subsequent injection behaviors can be improved by standardizing the injection behaviors in time, the economic problem caused by insufficient insulin injection is reduced, and the clinical value is important.

For example, after obtaining the amount of leakage from the insulin outlet of the injection device and the skin surface around the injection site, it may be determined whether the present injection by the patient is an effective injection based on the amount of leakage, and upon determining that it is an ineffective injection, a first guidance message may be created and a subject performing the injection may be notified, who may receive the first guidance message and specify the injection operation behavior based on the first guidance message.

In some examples, a correlation of the amount of leakage to fluctuations in blood glucose of the patient may be determined based on the amount of leakage, and a corresponding guidance message may be created to normalize the injection behavior. Specifically, a correlation between the amount of leakage and the blood glucose excursion of the patient may be determined based on the amount of leakage, thereby creating and outputting a second guidance message to the subject administering the injection behavior (i.e., administering the injected insulin) to normalize the injection behavior. In this case, it can have practical guiding significance for blood glucose excursions in patients with poor islet function (e.g., type 1 diabetic patients).

For example, it may be determined whether the amount of leakage exceeds a threshold value that has an impact on the patient's blood glucose fluctuations, and if so, a second guidance message may be created and notified to the subject that administered the injection, which may receive the second guidance message and normalize the injection behavior based on the second guidance message (e.g., the subject may determine whether to supplement the injection of insulin to stably control the patient's blood glucose based on the second guidance message).

Fig. 7A is a comparative graph showing fluid leakage areas with and without needles according to examples of the present disclosure. Fig. 7B is a comparative graph showing weep areas with and without a needle for different injection doses in accordance with examples of the present disclosure.

In some examples, the analysis method may further include analyzing leakage amounts of different injection devices. In this case, the injection device having a relatively small leakage amount can be determined by analysis, and the injection behavior of the patient can be guided. Specifically, in the analysis, the leakage amounts corresponding to different injection devices can be obtained, and the leakage amounts corresponding to the different injection devices are compared. In some examples, the amount of leakage from different injection devices may be analyzed based on the same injection dose. As an example, the size of the leakage is expressed in terms of leakage area, and fig. 7A shows a comparison of leakage areas of a needle (i.e., a needle-containing injection device) and a needle-free (i.e., a needle-free injection device) at the same injection dose, wherein a P less than 0.05 may indicate a difference between the needle-containing and the needle-free.

In some examples, the analysis method may further include analyzing leakage amounts for different injected doses. In this case, the relationship between the injection dose and the leakage amount can be obtained, and the injection dose of the patient can be guided. Therefore, the curative effect of the injected insulin can be improved. Specifically, in the analysis, the leakage amounts corresponding to different injection doses of insulin can be obtained, and the leakage amounts corresponding to different injection doses are compared. In some examples, the amount of leakage may be analyzed for different injection doses based on the same injection device. By way of example, the amount of leakage is expressed in terms of leakage area, and fig. 7B shows a comparison of leakage areas for needle and needle-free injections at different dosages (e.g., 10 units, 20 units, and 30 units as shown in fig. 7B), where P less than 0.05 may indicate a difference between needle and needle-free, and u represents a unit of insulin dosage.

The present disclosure also relates to a system for analyzing blood glucose excursions, comprising: a processor and a memory. The memory is used for storing instructions, and the processor executes the instructions to execute one or more steps of the analysis method.

The present disclosure also relates to an electronic device, which may comprise at least one processing circuit. The at least one processing circuit is configured to perform one or more steps of the analysis method or the image analysis method described above.

The present disclosure also relates to a computer-readable storage medium, which may store at least one instruction, which when executed by a processor, implements one or more steps of the analysis method or the image analysis method described above.

The analysis method, the analysis system, the equipment and the medium for blood glucose fluctuation of insulin leakage adsorbed by a nitrocellulose membrane in the disclosed examples are characterized in that after insulin is injected into a patient, the nitrocellulose membrane is used for adsorbing leakage at a target position related to the leakage amount, after the leakage is adsorbed, image analysis is carried out on a leakage image, corresponding to a reference object 20 with a known size, of the nitrocellulose membrane after the leakage is adsorbed so as to determine a leakage area, the leakage area is determined based on the leakage area and the reference object pattern, then the leakage area corresponding to the leakage area is determined based on the adsorption capacity of the nitrocellulose membrane for adsorbing the insulin and the leakage area, and finally the influence of the leakage amount on the blood glucose fluctuation of the patient is determined based on the injection amount, the leakage amount and the change of blood glucose indexes of the patient before and after the insulin is injected. In this case, the amount of leakage is effectively collected by the nitrocellulose membrane, the leakage area is intelligently and conveniently determined through image analysis, the leakage area corresponding to the leakage area is conveniently determined based on the reference 20, and the leakage condition is quantitatively determined based on the leakage area and the adsorption capacity of the nitrocellulose membrane. Therefore, quantitative leakage conditions can be effectively, conveniently and non-invasively acquired to analyze the influence of the leakage amount on blood glucose fluctuation.

In addition, according to the scheme, the nitrocellulose membrane is used as a tool for measuring the leakage amount of the insulin injected by the injection device, so that a standard insulin leakage evaluation flow is formed, a solid foundation is laid for clinical application, and benefits are brought to patients due to good blood sugar management.

While the present invention has been described in detail in connection with the drawings and the embodiments, it should be understood that the above description is not intended to limit the present invention in any way. Those skilled in the art can make modifications and variations to the present invention as needed without departing from the true spirit and scope of the invention, and such modifications and variations are within the scope of the invention.

Claims (10)

1. An analysis method for blood glucose fluctuation of a nitrocellulose membrane adsorbed insulin leakage is characterized by comprising the following steps: collecting a leakage image, wherein after a patient injects insulin, a nitrocellulose membrane is used for adsorbing leakage at a target position, and after the absorption is finished, the nitrocellulose membrane after the absorption of the leakage and a reference object with a known size are shot to obtain the leakage image; performing image analysis on the leakage image to determine a region aiming at the leakage in the leakage image and taking the region as a leakage region; determining a leakage area based on the resolution of the leakage image, the leakage area and a reference object pattern in the leakage image; determining a leakage amount corresponding to the leakage area based on the adsorption capacity of the nitrocellulose membrane for adsorbing the insulin and the leakage area; and determining the influence of the leakage amount on the blood glucose fluctuation of the patient based on the injection dose, the leakage amount, a first blood glucose level of the patient before the injection of insulin, and a second blood glucose level of the patient after the injection of insulin.

2. The analytical method of claim 1, wherein:

the target site includes an insulin outlet of an injection device for injecting insulin and a skin surface surrounding an injection site of the patient, the injection device including at least one of a needle-free injection device and a needle-containing injection device.

3. The analytical method of claim 1, wherein:

after the nitrocellulose membrane is continuously adsorbed for a first preset time to determine that adsorption is completed and leakage is detected, the leakage image is collected within a second preset time, the first preset time is determined by adsorption capacity, and the second preset time is determined by the volatilization time of the nitrocellulose membrane, wherein insulin is used for the nitrocellulose membrane.

4. The analytical method according to claim 2, wherein:

in determining an influence of the leakage amount on blood glucose fluctuations of the patient, acquiring a plurality of target data for a plurality of injections of insulin to the patient, each target data of the plurality of target data including the injection dose, the leakage amount, the first blood glucose level and the second blood glucose level, and determining a correlation between a change in the leakage amount and the blood glucose fluctuations of the patient based on the plurality of target data.

5. The analytical method of claim 1, wherein:

determining the number of pixels in the leakage area based on the resolution of the leakage image, determining the area of the pixels based on the reference pattern in the leakage image, and determining the leakage area based on the number of the pixels and the area of the pixels.

6. The analytical method of claim 2, wherein:

the analysis method further comprises the steps of determining the effectiveness of the injection behavior based on the leakage amount, further creating a first guidance message and outputting the first guidance message to a subject implementing the injection behavior to standardize the injection behavior; and/or

The analysis method further includes determining a correlation between the amount of leakage and glucose excursion of the patient based on the amount of leakage, thereby creating a second guidance message and outputting the second guidance message to a subject implementing an injection behavior to normalize the injection behavior.

7. The analytical method of claim 2, wherein:

and analyzing the leakage amount of different injection devices or different injection quantities.

8. The analytical method of claim 1, wherein:

the reference object is a scale.

9. The analytical method of claim 1, wherein:

the color of the nitrocellulose membrane is white, in the image analysis, contrast enhancement is carried out on the leakage image to obtain an enhanced image, pixel points in the enhanced image are classified to obtain a first type of pixels and a second type of pixels, the area corresponding to the first type of pixels and the second type of pixels with large gray mean values is used as a background area, and the area corresponding to the other type of pixels is used as the leakage area.

10. An analysis system for blood glucose excursions of a nitrocellulose membrane adsorbed insulin leakage, comprising: a processor; and a memory for storing instructions that are executed by the processor to perform the analysis method of any one of claims 1 to 9.

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