Method and apparatus for adjusting insulin

Abstract

A method for adjusting insulin comprises the steps of: an analysis apparatus acquiring carbohydrate intake data, continuous blood glucose data, and insulin administration data; the analysis apparatus determining a meal time point on the basis of the continuous blood glucose data; the analysis apparatus setting, as a pre-meal blood glucose value, a minimum blood glucose value during a preset period before the meal time point; and the analysis apparatus determining, on the basis of the pre-meal blood glucose value, the amount of insulin to be injected.

Description

Insulin adjustment method and device

[0001] The present disclosure relates to a technology for managing blood sugar.

[0002] In cases of diabetes characterized by insulin deficiency, including Type 1 diabetes, insulin injections are necessary for blood sugar management. For effective diabetes management, the timing of meals and insulin injections is critical. Delayed insulin injection after a meal can lead to negative consequences, such as a rapid spike in blood sugar, mismatch with the insulin's action time, worsening of long-term blood sugar control, and an increased risk of hypoglycemia. Therefore, it is essential to precisely align meal times with insulin injection timing. To address this, the Bolus Calculator has been utilized; it automatically calculates the insulin dosage based on the patient's input of the planned carbohydrate intake and pre-meal blood sugar levels. The Bolus Calculator has typically been integrated into devices such as insulin pumps or Smart Insulin Pens.

[0003] [Prior Art Literature]

[0004] [Patent Literature]

[0005] Korean Published Patent Application 10-2023-0173427

[0006] Figure 1 illustrates one of the problems of the conventional technology. When a patient injects rapid-acting insulin after a meal, the bolus calculator used in conventional Smart Insulin Pens and the like had a problem in that it incorrectly recognized the blood glucose level at the time of insulin injection (blue circle), which actually corresponds to the time after the meal, as the pre-meal blood glucose level. Consequently, even though the pre-meal blood glucose level was actually at an appropriate level (red), additional insulin was injected to correct the pre-meal hyperglycemia. This additional insulin injection could lead to hypoglycemia, making it difficult to use insulin pumps or Smart Insulin Pens.

[0007] The present disclosure aims to disclose a method for automatically determining an insulin dose based on the amount of carbohydrates to be consumed and pre-meal blood glucose levels. Furthermore, the present disclosure aims to disclose a method for detecting meal times in real time and calculating an insulin dose based on actual pre-meal blood glucose values, even if the patient injects ultra-rapid-acting insulin after a meal. Additionally, the present disclosure aims to disclose a method for correcting correction factors used in devices such as a Smart Insulin Pen, inferring the amount of carbohydrates consumed, correcting the carbohydrate-to-insulin ratio, or recommending an insulin dose.

[0008] An insulin adjustment method comprises the steps of: an analysis device acquiring carbohydrate intake data, continuous glucose data, and insulin administration data; the analysis device determining a meal time based on the continuous glucose data; the analysis device setting a minimum blood glucose value as a pre-meal blood glucose value during a preset period prior to the meal time; and the analysis device determining the amount of insulin to be injected based on the pre-meal blood glucose value.

[0009] By using the present disclosure, overdose and underdose of insulin can be prevented. By using the present disclosure, blood glucose management for diabetic patients can be aided. By using the present disclosure, assistance can be provided in using an insulin pump or a smart insulin pen. By using the present disclosure, the amount of insulin to be injected can be determined. By using the present disclosure, correction factors to be used for insulin administration can be corrected. By using the present disclosure, carbohydrate intake data can be corrected. By using the present disclosure, the carbohydrate-to-insulin ratio can be corrected. By using the present disclosure, the dawn phenomenon can be determined.

[0010] Figure 1 shows one of the problems of the prior art.

[0011] FIG. 2 is one of the embodiments in which an analysis device (100) performs an insulin adjustment method.

[0012] Figure 3 is a flowchart (200) of one example of an insulin adjustment method.

[0013] FIG. 4 shows one of the embodiments (300) for correcting the correction coefficient.

[0014] FIG. 5 shows one of the embodiments (400) for correcting carbohydrate intake data.

[0015] FIG. 6 shows one of the examples (500) that corrects the Insulin-to-Carbohydrate Ratio (ICR).

[0016] FIG. 7 shows one of the embodiments (600) for determining whether the dawn phenomenon occurs.

[0017] FIG. 8 is a configuration of one of the embodiments of an analysis device (700).

[0018] The present disclosure may be subject to various modifications and may have various embodiments. Specific embodiments of the present disclosure may be described in the drawings of the specification. However, this is for the purpose of explaining the present disclosure and is not intended to limit the present disclosure to specific embodiments. Accordingly, it should be understood that all modifications, equivalents, and substitutions that fall within the spirit and scope of the present disclosure are included in the present disclosure.

[0019] Terms such as first, second, A, B, etc., may be used to describe various components. However, such terms are used merely to distinguish one component from others and are not intended to limit the components. For example, without departing from the scope of the present disclosure, the first component may be named the second component, and similarly, the second component may be named the first component. The term “and / or” includes a combination of multiple related described items or any one of the multiple related described items.

[0020] In the terms used below, singular expressions should be understood to include plural expressions unless the context clearly indicates otherwise, and terms such as "includes" should be understood to mean that the described features, number, steps, actions, components, parts, or combinations thereof exist, and not to exclude the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0021] Before providing a detailed description of the drawings, it is to clarify that the classification of components in this specification is merely based on the primary function each component is responsible for. That is, two or more components described below may be combined into a single component, or a single component may be divided into two or more components based on more subdivided functions. Furthermore, each component described below may additionally perform some or all of the functions of other components in addition to its own primary function, and it is obvious that some of the primary functions of each component may be exclusively performed by other components.

[0022] Furthermore, in performing the method or operation method, each process constituting the method may occur differently from the specified order unless a specific order is clearly indicated in the context. That is, each process may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the reverse order.

[0023]

[0024] Carb in this disclosure eaten It can be the amount of carbohydrates consumed.

[0025] G in the present disclosure target may be Target Glucose. The Target Glucose may be an individual patient target glucose value. In this disclosure, Gcurrent may be the blood glucose value at the time of insulin injection. In this disclosure, G t_pointed may be a blood glucose value after a certain period of time following insulin injection. In the present disclosure, G hypo may be a blood glucose value at the time of hypoglycemia. In the present disclosure, G low may be a hypoglycemia threshold. For example, the hypoglycemia threshold may be 70 mg / dL. In this disclosure, G start may be the blood glucose at the time of the starting bolus. In the present disclosure, G lowest This could be the lowest blood sugar value.

[0026] I in the present disclosure real may be the amount of insulin actually injected. In this disclosure, I real,i may be the amount of insulin actually injected at additional insulin infusion event i. In the present disclosure, I plan,i This could be the insulin injection amount recommended by the calculator at that time.

[0027] In the present disclosure, t bolus may be the initial insulin infusion time. In the present disclosure, tinsulin activity time may be the time of the effect of insulin after the initial insulin infusion. In the present disclosure, t hypo may be the time when hypoglycemia occurred. In the present disclosure, t bolus,i may be the time of occurrence of additional insulin infusion event i. In the present disclosure, t start may be the time of the start ballous event. In the present disclosure, t pointed may be a time at the point in time of a specific event. In this disclosure, t lowest This may be the time when the lowest blood sugar occurred.

[0028] In the present disclosure, the Insulin Injection Event List may be a list of events in which a patient injected insulin. The Insulin Injection Event List may include information regarding the time of insulin injection, the amount of insulin injected, and the type of insulin. In the present disclosure, Bolus event may be a list of insulin bolus events. In this disclosure, Bolus start may be an initiating bolus event. In this disclosure, BolusAdditional may be an additionally injected insulin event. In this disclosure, I i or I real,i It may be the amount of additional insulin injected.

[0029] In the present disclosure, Carbohydrate Insulin may be insulin injected to process carbohydrates consumed during a meal. In the present disclosure, Correction Insulin may be insulin additionally injected to correct a hyperglycemic state.

[0030] In the present disclosure, the Insulin-to-Carbohydrate Ratio (ICR) is a coefficient used to determine the amount of insulin required based on carbohydrate intake.

[0031] In the present disclosure, CF may be a Correction Factor. The Correction Factor may be a value representing insulin sensitivity. The Correction Factor may be a value representing insulin sensitivity required to correct blood glucose. The Correction Factor may be calculated as (1800 / total daily insulin dose).

[0032] In the present disclosure, Insulin On Board (IOB) may be the percentage of residual active insulin in the body after initial insulin administration. IOB represents residual active insulin remaining in the body after the injection, which can further lower blood glucose. IOB may vary depending on the time of action (TD) and the time of peak action (TP) of insulin. In the present disclosure, IOB i can be an IOB for additional insulin infusion event i.

[0033] In the present disclosure, TD (Total Duration) and TP (Time to peak) may be constants related to the duration of insulin action (Duration, Peak Time).

[0034] Ratio in this disclosure boundary represents the allowable range ratio, ensuring that the target value does not exceed a certain range.

[0035] In the present disclosure, the dawn phenomenon may be a phenomenon in which blood glucose levels rise abnormally during the early morning hours in insulin-dependent diabetes. The dawn phenomenon may be a phenomenon in which blood glucose levels gradually rise during the early morning hours despite the absence of a specific cause.

[0036] In the present disclosure It may be a type of time-of-action curve depending on the type of insulin. It can be Rapid or Ultra-Rapid.

[0037] F in the present disclosure IOB may be a function that calculates residual active insulin (IOB) according to the insulin time of action curve. F IOB It may vary depending on the type of insulin and the individual's duration of action. F IOB It can generally be modeled in the form of an exponential function considering the total duration of action and peak time of insulin. In this disclosure, F IOB It can be equal to mathematical formula 1.

[0038]

[0039] In the above mathematical formula 1, t may be the elapsed time after insulin injection.

[0040]

[0041] FIG. 2 is one of the embodiments in which an analysis device (100) performs an insulin adjustment method.

[0042] The analysis device (100) can be physically implemented in various forms. For example, the analysis device (100) can take the form of a PC, laptop, smart device, server, or a chipset dedicated to data processing.

[0043] There may be at least one analysis device (100). That is, the insulin adjustment method may be performed by a single analysis device, or divided and performed by at least one device.

[0044] The analyzer (100) may be a device that performs an insulin adjustment method. The analyzer (100) may acquire carbohydrate intake data, continuous glucose data, and insulin administration data. The analyzer (100) may determine the amount of insulin to be injected based on the carbohydrate intake data, continuous glucose data, and insulin administration data. The analyzer (100) may determine the timing of a meal. The analyzer (100) may control an insulin delivery device. The analyzer (100) may inject insulin into a patient by controlling the insulin delivery device.

[0045]

[0046] Figure 3 is a flowchart (200) of one example of an insulin adjustment method.

[0047] The analysis device can acquire at least one of carbohydrate intake data, continuous glucose data and insulin administration data (210).

[0048] Carbohydrate intake data may include data on the amount of carbohydrates consumed by the patient and the time at which the patient consumed carbohydrates. Continuous glucose data may be data recording changes in the patient's blood glucose over time. Insulin administration data may include data on the amount of insulin injected into the patient and the time of insulin injection.

[0049] The analysis device can determine the timing of meals based on continuous glucose data (220).

[0050] To determine the timing of a meal, the pattern of blood glucose changes caused by the meal can be identified.

[0051] A missed bolus dose (MBD) meal-based detection algorithm can be used to determine the timing of a meal. The MBD detects characteristic changes that reflect the rise in blood glucose levels following a meal. The MBD identifies a short-term blood glucose trough and then analyzes the blood glucose rise to detect a meal.

[0052] Determining the timing of a meal using a meal-based detection algorithm (MBD) may involve identifying the point at which a blood glucose rise due to a meal is likely to begin by finding a point at which blood glucose levels are lower than the values ​​immediately before and after the meal. This can be expressed as shown in Equation 2.

[0053]

[0054]

[0055] Determining the timing of a meal using a meal-based detection algorithm (MBD) may involve analyzing the magnitude of blood glucose changes to detect large blood glucose changes associated with a meal. This can be expressed as shown in Equation 3.

[0056]

[0057] A Glucose Rate Increase Detector (GRID) algorithm can be used to determine the timing of a meal. The Glucose Rate Increase Detector (GRID) algorithm can detect a surge in blood sugar caused by a meal by analyzing the rate of change in blood sugar.

[0058] Determining the timing of a meal using a blood glucose rise detection algorithm (GRID) may include low-pass filtering continuous glucose data, identifying the rate of increase in blood glucose, and determining that a meal has been eaten if the rate of increase in blood glucose is greater than or equal to a preset value. This can be expressed as Equations 4 to 7.

[0059]

[0060]

[0061]

[0062]

[0063] In Equation 4, F(t) can be a low-pass filtered blood glucose value. In Equation 4, G NS (t) can be the noise-removed blood glucose value. In Equation 4, α can be a filter coefficient. In Equation 5, τ F can be a time constant.

[0064] Determining the timing of a meal may involve utilizing both the Meal-Based Detection (MBD) algorithm and the Blood Glucose Elevation Detection (GRID) algorithm. Therefore, it can be determined that a meal has been consumed only when both the Meal-Based Detection (MBD) algorithm and the Blood Glucose Elevation Detection (GRID) algorithms detect a meal.

[0065] The analysis device can set the minimum blood glucose value during a preset period prior to the meal as the pre-meal blood glucose value (230).

[0066] The preset period may be a period prior to the time when a meal is detected. The preset period may be a period prior to the time of the meal detected based on the blood glucose rise detection algorithm (GRID). For example, the preset period may be a period up to 90 minutes prior to the time of the meal detected based on the blood glucose rise detection algorithm.

[0067] Finding the minimum blood glucose value may involve identifying the local minimum (the point where the slope reverses). The local minimum can be the blood glucose value prior to a meal, reflecting the blood glucose status before insulin injection. By using the local minimum to determine the pre-meal blood glucose value and the time of the meal, if a specific amount of time has passed, it can be determined that too much time has elapsed since the meal. In this case, it is assumed that all consumed carbohydrates have been reflected in the blood glucose; consequently, the mealtime insulin dose is calculated as zero, and the corrective insulin dose required to reach the target blood glucose level can be calculated. This allows for a more accurate reflection of the patient's blood glucose status by taking into account the absorption of carbohydrates into the body.

[0068] The analyzer can determine the amount of insulin to be injected based on the blood glucose value before the meal (240).

[0069] The analyzer may use a Bolus Calculator to determine the amount of insulin to be injected. The Bolus Calculator may be used to calculate the amount of insulin to be injected based on a correction factor, pre-meal blood glucose levels, and the amount of carbohydrate intake.

[0070] The analyzer can inject insulin into a patient by controlling the insulin delivery device based on a determined amount of insulin. The insulin delivery device may include an insulin pump or an insulin pen.

[0071] The analyzer can determine whether the administered amount of insulin has been injected at the appropriate timing. This is intended for patients who miss or delay insulin injections after meals, enabling an immediate response. For example, if insulin is not injected within 30 minutes of a meal or within 60 minutes after a meal, it can be considered a delayed or missed insulin injection. In such cases, a warning can be issued regarding the missed insulin injection.

[0072] The analyzer can correct the amount of insulin to be injected (250).

[0073] The adjustment of insulin dosage may vary depending on whether hypoglycemia occurs.

[0074] Adjusting the amount of insulin to be injected in the event of hypoglycemia may include the process of calculating the blood glucose difference, the process of calculating the residual insulin activity rate (IOB), the process of adjusting the insulin dose adjustment value, the process of adjusting for additional insulin events, and the process of calculating the recommended insulin dose adjustment value.

[0075] In the event that hypoglycemia occurs, the process of calculating the blood glucose difference may include calculating an initial x value by dividing the difference between the blood glucose at the time of hypoglycemia and the target blood glucose by a correction factor. Mathematical formula 8 may be used in this process.

[0076]

[0077] In the event of hypoglycemia, the process of calculating the residual insulin ratio can calculate the initial bolus IOB value based on the elapsed time until the point of hypoglycemia. Equation 9 can be used in this process.

[0078]

[0079] In the event that hypoglycemia occurs, Equation 10 can be applied to adjust the insulin dosage for each additional insulin event i.

[0080]

[0081] And the calculated x value can be adjusted through mathematical formula 11.

[0082]

[0083] In the event of hypoglycemia, the process of calculating the recommended insulin dosage adjustment value may be a process using mathematical formula 12.

[0084]

[0085] In cases where hypoglycemia does not occur, adjusting the amount of insulin to be injected may include the process of calculating the blood glucose difference, the process of calculating the required insulin dose, and the process of adjusting for additional insulin events.

[0086] In cases where hypoglycemia does not occur, the process of calculating the blood glucose difference can use mathematical formula 13.

[0087]

[0088] In cases where hypoglycemia does not occur, the process of calculating the required insulin dose may include calculating the amount of insulin needed by dividing the difference between the blood glucose after 4 hours and the target blood glucose by a correction factor. Equation 14 may be used in this process.

[0089]

[0090] In cases where hypoglycemia does not occur, the process of adjusting for additional insulin events may include calculating the residual insulin activity ratio using Equation 15 and adjusting the insulin dose adjustment value using Equation 16.

[0091]

[0092]

[0093]

[0094] The analyzer can correct the correction factor based on continuous glucose data and insulin injection data.

[0095] By adjusting the correction factor, the appropriateness of corrected insulin infusion can be evaluated. By adjusting the correction factor, the patient's blood glucose control can be optimized. By adjusting the correction factor, hypoglycemia and hyperglycemia can be prevented. By adjusting the correction factor, the efficiency of insulin administration can be improved.

[0096] FIG. 4 shows one of the embodiments (300) for correcting the correction coefficient.

[0097] Correcting the correction factor may include a process of checking whether to inject corrective insulin based on insulin administration data (310).

[0098] The analyzer checks from the user whether the bolus calculator is being used and the amount of carbohydrate input. If the amount of carbohydrate input in the bolus calculator is set to 0, the corresponding insulin injection event can be identified as corrective insulin.

[0099] Correcting the correction factor may include a process of determining the need to correct the correction factor (320).

[0100] If the first or second condition is satisfied, it may be determined that correction is required.

[0101] The first condition may include that hypoglycemia occurs within the first period, that blood glucose is lower than the target blood glucose minus a threshold value after the first period, that there is no additional carbohydrate insulin infusion within the first period, and that there is no persistent hyperglycemia.

[0102] The first period may be the period during which insulin acts after insulin injection. The first period may be the insulin activity time.

[0103] The occurrence of hypoglycemia within the first period can be expressed as in Equation 17.

[0104]

[0105] The condition that blood glucose levels after the first period are lower than the target blood glucose level minus the threshold value can be expressed as in Equation 18.

[0106]

[0107] Not being in a state of persistent hyperglycemia means that at the time of corrective insulin injection, blood glucose levels must not remain above the limit of measurement of the continuous glucose monitor for more than 10 minutes. This is because if the blood glucose level is above the limit of measurement of the continuous glucose monitor, it is difficult to accurately assess the patient's condition, which may lead to inappropriate results.

[0108] The second condition may include that hypoglycemia does not occur within the first period, that blood glucose is higher than the target blood glucose plus a threshold value after the first period, that there is no additional carbohydrate insulin injection within the first period, that there is no change in blood glucose due to meals within the first period, and that there is not a persistent hyperglycemic state.

[0109] The fact that hypoglycemia will not occur within the first period can be expressed as in mathematical formula 19.

[0110]

[0111] The condition that blood glucose levels after the first period are higher than the target blood glucose plus a threshold value can be expressed as Equation 20.

[0112]

[0113] The condition that there is no change in blood glucose due to a meal within the first period may mean that there should be no event (MBD or GRID) indicating a rise in blood glucose due to a meal within the first period after insulin injection.

[0114] Correcting the correction factor may include the process of calculating the IOB (330).

[0115] The process of calculating IOB may include calculating the residual insulin effect by taking into account the active effect of the injected insulin remaining in the body.

[0116] Correcting the correction factor may include the process of calculating an estimated correction factor (Suggested CF) based on the IOB, the blood glucose value at the time of correction insulin injection, the blood glucose value after a preset time after correction insulin injection, the target blood glucose value, and the current correction factor (340).

[0117] Equation 21 can be used to calculate the estimated correction factor.

[0118]

[0119]

[0120] G in mathematical equation 21 pointed may be the blood glucose value at the time of hypoglycemia or the blood glucose value at the tinsulin activity time. In Equation 21, F total iob calc may be a value recalculated as the actual insulin acted as IOB, taking into account additional corrective insulin injection. In Equation 21, F total iob calc may be a value used as a ratio after summing all injected corrected insulin doses and converting them. In Equation 21, F total iob calc It may be composed of a formula that corrects the corrected insulin injection amounts for i≥2 by back-calculating them based on the first corrected insulin injection time (i=1).

[0121] Correcting the correction factor may include calculating the corrected correction factor (Revised CF) by reflecting the estimated correction factor in the current correction factor (350).

[0122] Equation 22 can be used to calculate the corrected correction factor.

[0123]

[0124]

[0125] The analysis device can correct carbohydrate intake data based on carbohydrate intake data, continuous glucose data, and insulin administration data.

[0126] The purpose of calibrating carbohydrate intake data is to support more accurate blood glucose management by supplementing the reliability of the acquired data. It aims to provide the data necessary for blood glucose management by estimating intake more precisely, even when the reliability of the acquired carbohydrate intake data is low or uncertain.

[0127] FIG. 5 shows one of the embodiments (400) for correcting carbohydrate intake data.

[0128] Correcting carbohydrate intake data may include a process of determining whether there is hypoglycemia due to insulin injection (410). Equation 23 may be used to determine whether there is hypoglycemia.

[0129]

[0130] Correcting carbohydrate intake data may include the process of calculating the expected amount of carbohydrate intake based on whether there is hypoglycemia (420).

[0131] Unless it is a case of hypoglycemia, the expected carbohydrate intake can be calculated using mathematical formula 24.

[0132]

[0133]

[0134] G in mathematical equation 24 pointed is G t_pointed It could be.

[0135] In the case of hypoglycemia, the estimated carbohydrate intake can be calculated using mathematical formula 25.

[0136]

[0137]

[0138] G in mathematical equation 25pointed is G lowest It could be.

[0139]

[0140] The analyzer can correct the Insulin-to-Carbohydrate Ratio (ICR) based on carbohydrate intake data, continuous glucose data, and insulin administration data.

[0141] FIG. 6 shows one of the examples (500) that corrects the Insulin-to-Carbohydrate Ratio (ICR).

[0142] Correcting the ICR may include the process of calculating the amount of insulin required to adjust the difference between the blood glucose value and the target blood glucose value after a preset time based on the time of insulin administration (510).

[0143] Mathematical formula 26 can be used in this process.

[0144]

[0145] In mathematical formula 26, A may be the amount of insulin needed to control the blood glucose level if there is a difference from the target blood glucose level after a period of time.

[0146] Correcting the ICR may include the process of calculating the insulin action value (520).

[0147] Calculating the insulin action value may involve calculating the insulin action value by taking into account the additionally injected insulin along with the initially injected insulin. Calculating the insulin action value may involve adjusting the actual total injection volume by taking into account the IOB at each injection event.

[0148] The process of calculating the insulin action value can be carried out through mathematical formulas 27 and 28.

[0149] Equation 27 is a formula for calculating the insulin action value when the first insulin is injected, and Equation 28 is a formula for calculating the insulin action value when additional insulin is injected.

[0150]

[0151]

[0152] In mathematical formula 27, B may be the insulin action value considering additional injected insulin.

[0153] Correcting the ICR may include a process of correcting the ICR based on the calculated amount of insulin required and the insulin action value (530).

[0154] This can be performed using mathematical formula 29.

[0155]

[0156] Correcting the ICR may involve the process of adjusting the upper and lower limits.

[0157] Mathematical formula 30 can be used to set upper and lower limits.

[0158]

[0159]

[0160] The analysis device can determine whether the dawn phenomenon occurs based on continuous glucose data and insulin administration data.

[0161] FIG. 7 shows one of the embodiments (600) for determining whether the dawn phenomenon occurs.

[0162] Determining whether the dawn phenomenon occurs may include the process of setting the time period for determining the dawn phenomenon (610).

[0163] The time period for determining the dawn phenomenon may be the time period when the dawn phenomenon is expected to occur. For example, the time period for determining the dawn phenomenon may be the time from midnight to early morning.

[0164] Determining whether the dawn phenomenon has occurred may include the process of finding the lowest blood glucose value during the dawn phenomenon determination time (620).

[0165] The lowest blood glucose value can be found among continuous glucose data from the early morning hours. Generally, the lowest blood glucose value can also be found around 3 a.m.

[0166] If the blood glucose level fluctuates below a certain level after the lowest blood glucose level is detected, this can be considered a fluctuation.

[0167] Determining whether the dawn phenomenon has occurred may include the process of finding an event corresponding to the analysis endpoint (630).

[0168] The event corresponding to the analysis endpoint may be an insulin injection event that occurs later than the time of the lowest blood glucose value. Alternatively, the event corresponding to the analysis endpoint may be the time of the first Meal-Based Detection (MBD) and Blood Glucose Elevation Detection (GRID) occurring during the morning. Alternatively, the event corresponding to the analysis endpoint may be 11:00 AM.

[0169] Determining whether the dawn phenomenon has occurred may include a process of determining that the dawn phenomenon has occurred if the difference (deltaG) between the blood glucose value at the event corresponding to the analysis endpoint and the lowest blood glucose value is greater than or equal to a preset value (640).

[0170] Mathematical formula 31 can be used in this process.

[0171]

[0172] G in mathematical equation 31 event may be the blood glucose value at the event corresponding to the analysis endpoint. In Equation 31, G start This may be the lowest blood sugar value during the time period for judging the dawn phenomenon.

[0173]

[0174] FIG. 8 is a configuration of one of the embodiments of an analysis device (700).

[0175] The analysis device (700) may correspond to the analysis device (100) described above in FIG. 1. That is, the analysis device (700) may be a device that performs the aforementioned insulin adjustment method.

[0176] The analysis device (700) may include at least one input device (710), a storage device (720), a computation device (730), an output device (740), an interface device (750), and a communication device (760).

[0177] The input device (710) may receive data, information, or models necessary for performing the aforementioned insulin adjustment method. The input device (710) may receive carbohydrate intake data, continuous glucose data, and insulin administration data. The input device (710) may receive an analysis model. The input device (710) may receive training data necessary for training the analysis model. The input device (710) may include a device for inputting certain commands or data (keyboard, mouse and touchscreen, joystick, trackball, touchpad, scanner, webcam, etc.). The input device (710) may include a configuration for receiving data through a separate storage device (USB, CD, hard disk, etc.). The input device (710) may receive data through a separate measuring device or a separate database. The input device (710) may receive data via a wired or wireless connection through a communication device (760). The input device (710) may receive a control signal for controlling the analysis device (700).

[0178] The storage device (720) can store data, information, or models necessary for performing the aforementioned insulin adjustment method. The storage device (720) can store carbohydrate intake data, continuous glucose data, and insulin administration data. The storage device (720) can store an analysis model. The storage device (720) can store training data necessary for training the analysis model. The storage device (720) may be a device for storing certain data, information, or models. The storage device (720) can store data, information, and models received through the input device (710). The storage device (720) can store commands that cause the computing device (730) to perform operations necessary for the insulin adjustment method. The storage device (720) can store information generated during the process of computing by the computing device (730). That is, the storage device (720) may include memory. For example, storage devices may include HDD (Hard Disk Drive), SSD (Solid State Drive), ROM, RAM, CD-ROM, magnetic tape, or floppy disk.

[0179] The computing device (730) can perform calculations necessary to carry out the aforementioned insulin adjustment method. The computing device (730) can acquire carbohydrate intake data, continuous glucose data, and insulin administration data. The computing device (730) can determine the timing of a meal based on the continuous glucose data. The computing device (730) can set the minimum blood glucose value during a preset period prior to the timing of a meal as the pre-meal blood glucose value. The computing device (730) can determine the amount of insulin to be injected based on the pre-meal blood glucose value. The computing device (730) can correct the correction factor based on the continuous glucose data and insulin administration data. The computing device (730) can correct the carbohydrate intake data based on the carbohydrate intake data, continuous glucose data, and insulin administration data. The computing device (730) can correct the Insulin-to-Carbohydrate Ratio (ICR) based on the carbohydrate intake data, continuous glucose data, and insulin administration data. The computing device (730) can determine whether the dawn phenomenon occurs based on the continuous glucose data and insulin administration data. The computing device (730) may be a device such as a processor, an AP (Application Processor), or a chip with a program embedded therein that processes data and performs certain operations. For example, the computing device (730) may include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or an NPU (Neural Processing Unit). The computing device (730) may generate control signals to control the analysis device (700). The computing device (730) may generate control signals to control the input device (710), storage device (720), output device (740), interface device (750), and communication device (760) included in the analysis device (700).

[0180] The output device (740) may be a device that outputs certain data, information, and models. The output device (740) may be a device that outputs certain data, information, and models outside the analysis device (700). The output device (740) may output interfaces, input data, analysis results, etc., necessary for the data processing process. The output device (740) may include a device that outputs data, etc., through tactile, visual, auditory, gustatory, and olfactory methods. The output device (740) may be implemented in various physical forms, such as a display, speaker, vibration motor, or document output device. The output device (740) may output data, information, or models, etc., stored in the storage device (720). The output device (740) may output data, information, and models, etc., generated during the process of calculation by the computation device (730). The output device (740) may output the results calculated by the computation device (730).

[0181] The interface device (750) may be a device that receives certain commands and data from the outside. The interface device (750) may receive control signals for controlling the analysis device (700). The interface device (750) may output the results analyzed by the analysis device (700). The interface device (750) may receive information necessary to perform the aforementioned insulin adjustment method from a physically connected input device or an external storage device.

[0182] The communication device (760) can receive information necessary to perform the aforementioned insulin adjustment method. The communication device (760) can receive a model necessary to perform the aforementioned insulin adjustment method. The communication device (760) can transmit and receive carbohydrate intake data, continuous glucose data, and insulin administration data. The communication device (760) can transmit and receive an analysis model. The communication device (760) can receive control signals necessary to control the analysis device (700). The communication device (760) can transmit the results analyzed by the analysis device (700). The communication device (760) may refer to a configuration that receives and transmits certain data, information, and models, etc., through a wired or wireless network. The communication device (760) can perform network communication such as Wi-Fi (Wireless Fidelity), Wi-Fi Direct, Bluetooth, UWB (Ultra-Wide Band) or NFC (Near Field Communication), USB (Universal Serial Bus), or HDMI (High Definition Multimedia Interface), LAN (Local Area Network), etc.

[0183]

[0184] The aforementioned insulin adjustment method can be implemented as a program (or application) including an executable algorithm that can be executed on a computer.

[0185] The above program may be provided by storing it on a transitory or non-transitory computer-readable medium.

[0186] The above-mentioned temporary readable medium refers to various types of RAM such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synclink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).

[0187] The above-mentioned non-transient readable medium refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short moment, such as a register, cache, or memory. Specifically, the various applications or programs described above may be stored and provided on a non-transient readable medium such as a CD, DVD, hard disk, Blu-ray disc, USB, memory card, ROM (read-only memory), PROM (programmable read-only memory), EPROM (Erasable PROM, EPROM), EEPROM (Electrically EPROM), or flash memory.

[0188]

[0189] The embodiments and drawings attached to this specification merely clearly illustrate a part of the technical ideas included in the aforementioned technology, and it is self-evident that variations and specific embodiments that can be easily inferred by a person skilled in the art within the scope of the technical ideas included in the specification and drawings of the aforementioned technology are all included within the scope of the rights of the aforementioned technology.

Claims

1. A step in which an analysis device acquires carbohydrate intake data, continuous glucose data, and insulin administration data; A step in which the analysis device determines the timing of a meal based on the continuous glucose data; The step of the analysis device setting the minimum blood glucose value as the pre-meal blood glucose value during a preset period prior to the meal time; and The above analysis device includes the step of determining the amount of insulin to be injected based on the above pre-meal blood glucose value; Insulin adjustment method.

2. In Paragraph 1, Determining the above meal timing includes using a meal-based detection algorithm and a blood sugar rise detection algorithm, and The above meal-based detection algorithm identifies a point in time when blood glucose levels are lower than the blood glucose values ​​immediately before and after the meal to determine a point where a rise in blood glucose due to the meal is likely to begin, and determines that point as the time of the meal if the magnitude of the change in blood glucose at that point is greater than a preset value. The above blood glucose rise detection algorithm is an algorithm that performs low-pass filtering on the continuous blood glucose data, identifies the blood glucose increase rate from the low-pass filtered result, and determines that a meal has been consumed if the blood glucose increase rate is greater than or equal to a preset value. Insulin adjustment method.

3. In Paragraph 2, Determining the above meal time is to determine the point at which a meal is determined to have been eaten by both the above meal-based detection algorithm and the blood sugar rise detection algorithm as the meal time. Insulin adjustment method.

4. In Paragraph 1, Finding the above minimum blood glucose value includes finding the local minimum, which is the point where the slope reverses. Insulin adjustment method.

5. In Paragraph 1, Determining the amount of insulin to be injected includes using a Bolus Calculator, and The above Bolus Calculator is used to calculate the amount of insulin to be injected based on a correction factor, pre-meal blood glucose levels, and the amount of carbohydrate intake. Insulin adjustment method.

6. In Paragraph 1, The above analysis device further includes the step of correcting a correction factor based on the continuous glucose data and insulin administration data; Correcting the above correction factor comprises: a process of confirming whether to inject corrective insulin based on the above insulin administration data; a process of determining the necessity of correcting the correction factor; a process of calculating IOB (Insulin On Board); a process of calculating an estimated correction factor (Suggested CF) based on the IOB, the blood glucose value at the time of corrective insulin injection, the blood glucose value after a preset time following corrective insulin injection, and the current correction factor; and a process of calculating a corrected correction factor (Revised CF) by reflecting the estimated correction factor in the current correction factor. Insulin adjustment method.

7. In Paragraph 6, Calculating the above estimated correction coefficients includes using the following mathematical formula 21, Insulin adjustment method. [Mathematical Formula 21] 8. In Paragraph 6, The process of determining the necessity of correction of the above correction coefficient includes determining that correction is necessary when the first condition is satisfied, and The above first condition includes that hypoglycemia occurs within the first period, that blood glucose is lower than or equal to the target blood glucose minus a threshold value after the first period, that there is no additional carbohydrate insulin injection within the first period, and that there is no persistent hyperglycemia, and The above first period is the period during which insulin acts after insulin injection, Insulin adjustment method.

9. In Paragraph 6, The process of determining the necessity of correction of the above correction coefficient includes determining that correction is necessary when the second condition is satisfied, and The above second condition includes that hypoglycemia does not occur within the first period, that blood glucose is higher than the target blood glucose plus a threshold value after the first period, that there is no additional carbohydrate insulin injection within the first period, that there is no change in blood glucose due to meals within the first period, and that there is not a persistent hyperglycemic state. The above first period is the period during which insulin acts after insulin injection, Insulin adjustment method.

10. In Paragraph 1, The above analysis device further includes the step of correcting the carbohydrate intake data based on the carbohydrate intake data, continuous glucose data, and insulin administration data. Correcting the above carbohydrate intake data includes a process of determining whether there is hypoglycemia; and a process of calculating the amount of expected carbohydrate intake based on whether there is hypoglycemia. The process of calculating the above-mentioned amount of estimated carbohydrate intake includes using the following mathematical formula 24 if there is no hypoglycemia, and using the following mathematical formula 25 if there is hypoglycemia, Insulin adjustment method. [Mathematical Formula 24] [Mathematical Formula 25] 11. In Paragraph 1, The above analysis device further includes the step of correcting the Insulin-to-Carbohydrate Ratio (ICR) based on carbohydrate intake data, continuous glucose data, and insulin administration data. Correcting the above ICR includes: a process of calculating the required amount of insulin to control the difference between the blood glucose value after a preset time based on the insulin administration time and the target blood glucose value; a process of calculating the insulin action value; and a process of correcting the ICR based on the calculated required amount of insulin and the insulin action value. Insulin adjustment method.

12. In Paragraph 1, The above analysis device further includes the step of determining whether the dawn phenomenon occurs based on the continuous glucose data and insulin administration data. Insulin adjustment method.

13. In Paragraph 12, Determining whether the above-mentioned dawn phenomenon has occurred includes: a process of setting a time period for determining the dawn phenomenon; a process of finding the lowest blood glucose value within the time period for determining the dawn phenomenon; a process of finding an event corresponding to the analysis endpoint; and a process of determining that the dawn phenomenon has occurred if the difference between the blood glucose value at the event corresponding to the analysis endpoint and the lowest blood glucose value is greater than or equal to a preset value. Insulin adjustment method.

14. In Paragraph 13, The event corresponding to the above analysis endpoint is an insulin injection event occurring later than the time of the lowest blood glucose value, the time of the first meal occurring in the morning, or 11:00 AM. Insulin adjustment method.

15. Input device for receiving carbohydrate intake data, continuous glucose data, and insulin administration data; A computing device comprising: determining a meal time based on the above continuous glucose data, setting a minimum glucose value during a preset period prior to the meal time as a pre-meal glucose value, and determining the amount of insulin to be injected based on the pre-meal glucose value by an analysis device; Analysis device.

16. In Paragraph 15, Determining the above meal timing includes using a meal-based detection algorithm and a blood sugar rise detection algorithm, and The above meal-based detection algorithm identifies a point in time when blood glucose levels are lower than the blood glucose values ​​immediately before and after the meal to determine a point where a rise in blood glucose due to the meal is likely to begin, and determines that point as the time of the meal if the magnitude of the change in blood glucose at that point is greater than a preset value. The above blood glucose rise detection algorithm is an algorithm that performs low-pass filtering on the continuous blood glucose data, identifies the blood glucose increase rate from the low-pass filtered result, and determines that a meal has been consumed if the blood glucose increase rate is greater than or equal to a preset value. Analysis device.

17. In Paragraph 15, Determining the amount of insulin to be injected includes using a Bolus Calculator, and The above Bolus Calculator is used to calculate the amount of insulin to be injected based on a correction factor, pre-meal blood glucose levels, and the amount of carbohydrate intake. Analysis device.

18. In Paragraph 15, The above computing device corrects the correction coefficient based on the continuous glucose data and insulin administration data, and Correcting the above correction factor comprises: a process of confirming whether to inject corrective insulin based on the above insulin administration data; a process of determining the necessity of correcting the correction factor; a process of calculating IOB (Insulin On Board); a process of calculating an estimated correction factor (Suggested CF) based on the IOB, the blood glucose value at the time of corrective insulin injection, the blood glucose value after a preset time following corrective insulin injection, and the current correction factor; and a process of calculating a corrected correction factor (Revised CF) by reflecting the estimated correction factor in the current correction factor. Analysis device.

19. In Paragraph 15, The above computing device corrects the carbohydrate intake data based on the carbohydrate intake data, continuous glucose data, and insulin administration data, and Correcting the above carbohydrate intake data includes a process of determining whether there is hypoglycemia; and a process of calculating the amount of expected carbohydrate intake based on whether there is hypoglycemia. The process of calculating the above-mentioned amount of estimated carbohydrate intake includes using the following mathematical formula 24 if there is no hypoglycemia, and using the following mathematical formula 25 if there is hypoglycemia, Analysis device. [Mathematical Formula 24] [Mathematical Formula 25] 20. In Paragraph 15, The above computing device corrects the Insulin-to-Carbohydrate Ratio (ICR) based on carbohydrate intake data, continuous glucose data, and insulin administration data, and Correcting the above ICR includes: a process of calculating the required amount of insulin to control the difference between the blood glucose value after a preset time based on the insulin administration time and the target blood glucose value; a process of calculating the insulin action value; and a process of correcting the ICR based on the calculated required amount of insulin and the insulin action value. Analysis device.

21. In Paragraph 15, The above computing device determines whether the dawn phenomenon occurs based on the above continuous glucose data and insulin administration data, and Determining whether the above-mentioned dawn phenomenon has occurred includes: a process of setting a time period for determining the dawn phenomenon; a process of finding the lowest blood glucose value within the time period for determining the dawn phenomenon; a process of finding an event corresponding to the analysis endpoint; and a process of determining that the dawn phenomenon has occurred if the difference between the blood glucose value at the event corresponding to the analysis endpoint and the lowest blood glucose value is greater than or equal to a preset value. Analysis device.

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