Method for performing automatic detection according to change rate of difference value of actual blood glucose values and closed-loop artificial pancreas

Abstract

A method for performing automatic detection according to a change rate of a difference value of actual blood glucose values and a closed-loop artificial pancreas. The method comprises: acquiring an actual blood glucose value of a user at a current moment (201); acquiring a historical actual blood glucose level of the user at a previous time, and calculating a difference value between the actual blood glucose level at the current time and the actual blood glucose level at the previous time (202); calculating the rate of change of the difference between the actual blood glucose values at the current time (203); and comparing the change rate of the difference value of the actual blood glucose value at the current moment with a preset threshold value, and determining the event type according to a comparison result. According to the determined event type, the artificial pancreas can automatically adjust the corresponding infusion strategy, and closed-loop control over the artificial pancreas is achieved.

Description

Method for automatic detection based on the rate of change of actual blood sugar difference and closed-loop artificial pancreas Technical Field

[0001] The present invention generally relates to the field of medical devices, and more particularly to a method for automatically detecting meal and / or exercise events. Background Art

[0002] In a healthy individual, the pancreas automatically secretes insulin and glucagon based on blood glucose levels, maintaining a healthy blood sugar range. However, in diabetics, pancreatic function is abnormal, preventing the body from producing the necessary insulin. Diabetes is a metabolic disease, a lifelong condition. Current medical technology cannot cure diabetes; instead, it can control the onset and progression of diabetes and its complications by stabilizing blood sugar levels.

[0003] Diabetic patients need to test their blood sugar before injecting insulin. Current detection methods can continuously detect blood sugar and send the blood sugar value to a display device in real time for the user to view. This detection method is called continuous glucose monitoring (CGM). This method requires the detection device to be attached to the surface of the skin, and the probe it carries is inserted into the subcutaneous tissue fluid to complete the detection. According to the blood sugar value detected by CGM, the infusion device will inject the currently required insulin into the subcutaneous tissue, thereby forming a fully closed-loop or semi-closed-loop artificial pancreas.

[0004] The current artificial pancreas still requires manual input of meal and / or exercise information, including meal type and size, exercise type and intensity, etc., before the artificial pancreas can adjust the corresponding infusion strategy. Therefore, the current artificial pancreas can only be called a semi-closed-loop artificial pancreas. To achieve closed-loop control of the artificial pancreas, the artificial pancreas must first realize automatic meal detection and / or exercise detection, and then automatically adjust the corresponding infusion strategy based on the automatically detected meal and / or exercise information.

[0005] Therefore, the prior art urgently needs a method capable of automatically performing meal detection and / or exercise detection and a closed-loop artificial pancreas capable of automatically performing meal detection and / or exercise detection.

[0006] Summary of the Invention

[0007] An embodiment of the present invention discloses a method for automatically detecting an event based on the rate of change of the difference in actual blood glucose levels. The method comprises: obtaining the user's actual blood glucose level at the current moment; obtaining the user's historical actual blood glucose level at a previous moment, calculating the difference between the current and previous actual blood glucose levels; calculating the rate of change of the difference in the current actual blood glucose levels; comparing the rate of change of the current actual blood glucose level difference with a preset threshold, and determining the event type based on the comparison result. Based on the determined event type, the artificial pancreas can automatically adjust the corresponding infusion strategy, achieving closed-loop control of the artificial pancreas.

[0008] The present invention discloses a method for automatic detection based on the rate of change of the difference in actual blood glucose values, comprising: obtaining the actual blood glucose value of a user at the current moment; obtaining the historical actual blood glucose value of the user at the previous moment, and calculating the difference between the actual blood glucose values ​​at the current moment and the previous moment; calculating the rate of change of the difference in the actual blood glucose values ​​at the current moment; comparing the rate of change of the difference in the actual blood glucose values ​​at the current moment with a preset threshold value, and determining the event type based on the comparison result.

[0009] According to one aspect of the present invention, when the rate of change of the difference between the actual blood glucose levels at the current moment is positive and greater than a preset positive threshold, the event is determined to be a meal.

[0010] According to one aspect of the present invention, when the rate of change of the difference between the actual blood glucose levels at the current moment is negative and smaller than a preset negative threshold, the event is determined to be exercise.

[0011] According to one aspect of the present invention, when starting to determine the event type, the time interval between the current moment and the previous moment is gradually shortened.

[0012] According to one aspect of the present invention, the event type is further determined in combination with other judgment results.

[0013] According to one aspect of the present invention, the other judgment result is a judgment result obtained based on the change rate of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0014] According to one aspect of the present invention, the type of event is determined when the judgment result obtained from the change rate of the difference between the actual blood glucose value and the predicted blood glucose value at the current moment is consistent with the judgment result obtained based on the change rate of the difference between the actual blood glucose values.

[0015] According to one aspect of the present invention, the prediction algorithm for predicting blood glucose levels also takes into account the effects of insulin that has not yet taken effect in the body and insulin sensitivity.

[0016] According to one aspect of the present invention, the predicted blood glucose level is calculated based on at least the actual blood glucose level at the previous moment and the first-order derivative or the second-order derivative of the actual blood glucose level at the previous moment with respect to time.

[0017] According to one aspect of the present invention, other determination results further include results determined based on insulin infusion information.

[0018] According to one aspect of the present invention, a method for determining a result based on insulin infusion information includes: obtaining insulin infusion information within a recent period of time and calculating the insulin infusion amount I1; obtaining insulin infusion information within a past period of time and calculating the insulin infusion amount I2; calculating the absolute value of the difference between I1 and I2; comparing the absolute value of the difference with a preset threshold value, and if the absolute value of the difference is not greater than the preset threshold value, trusting the result determined based on the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0019] According to one aspect of the present invention, the past period of time is a period of time adjacent to the most recent period of time.

[0020] According to one aspect of the present invention, other determination results further include a result determined based on the variance between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0021] According to one aspect of the present invention, a method for determining a result based on the variance of the actual blood glucose value at the current moment and the predicted blood glucose value includes comparing the variance with a preset threshold value. If the variance is greater than the threshold value, trusting the result determined based on the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0022] According to one aspect of the present invention, other determination results further include results determined based on insulin infusion information.

[0023] According to one aspect of the present invention, when the absolute value of the difference between the amount of insulin infused in the most recent period I1 and the amount of insulin infused in the past period I2 is less than a preset threshold, the result determined based on the variance between the actual blood glucose value at the current moment and the predicted blood glucose value is trusted.

[0024] The present invention also discloses a closed-loop artificial pancreas capable of automatically performing meal detection and / or exercise detection, comprising: a detection module for continuously detecting the user's current actual blood sugar value; an infusion module for infusing the currently required insulin into the user's body according to insulin infusion instructions; an electronic module for controlling the operation of the detection module and the infusion module, comprising a memory and a processor; and characterized in that the processor automatically determines the type of event by calculating the rate of change of the difference between the actual blood sugar values ​​detected by the detection module.

[0025] According to one aspect of the present invention, a method for automatically determining the type of an event includes: obtaining the actual blood glucose value of the user at the current moment; obtaining the historical actual blood glucose value of the user at the previous moment, and calculating the difference between the actual blood glucose values ​​at the current moment and the previous moment; calculating the rate of change of the difference between the actual blood glucose values ​​at the current moment; comparing the rate of change of the difference between the actual blood glucose values ​​at the current moment with a preset threshold, and determining the event type based on the comparison result.

[0026] According to one aspect of the present invention, when the rate of change of the difference between the actual blood glucose values ​​at the current moment is positive and greater than a preset positive threshold, the event is determined to be a meal; when the rate of change of the difference between the actual blood glucose values ​​at the current moment is negative and less than a preset negative threshold, the event is determined to be exercise.

[0027] According to one aspect of the present invention, the method for automatically determining the type of an event further combines other determination results to jointly determine the event type.

[0028] According to one aspect of the present invention, the other judgment result is a judgment result obtained based on the change rate of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0029] According to one aspect of the present invention, other determination results further include results determined based on insulin infusion information.

[0030] According to one aspect of the present invention, a method for determining a result based on insulin infusion information includes: obtaining insulin infusion information over a recent period of time and calculating the insulin infusion amount I1; obtaining insulin infusion information over a past period of time and calculating the insulin infusion amount I2; calculating the absolute value of the difference between I1 and I2; comparing the absolute value of the difference with a preset threshold value, and if the absolute value of the difference is not greater than the preset threshold value, trusting the result determined based on the rate of change of the difference between the actual blood glucose values ​​and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0031] According to one aspect of the present invention, other determination results further include a result determined based on the variance between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0032] According to one aspect of the present invention, a method for determining a result based on the variance of the actual blood glucose value at the current moment and the predicted blood glucose value includes comparing the variance with a preset threshold value. If the variance is greater than the threshold value, trusting the result determined based on the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0033] According to one aspect of the present invention, the result determined based on the variance between the actual blood glucose value at the current moment and the predicted blood glucose value further includes a result determined based on insulin infusion information.

[0034] According to one aspect of the present invention, a motion sensor is further included, and the motion sensor is a combination of a three-axis acceleration sensor and a gyroscope.

[0035] According to one aspect of the present invention, at least two of the detection module, the infusion module and the electronic module are interconnected or integrated to form an integral structure.

[0036] According to one aspect of the present invention, the detection module, the infusion module and the electronic module are respectively arranged in different structures.

[0037] Compared with the prior art, the technical solution of the present invention has the following advantages:

[0038] In the method disclosed herein for automatically detecting an event based on the rate of change of the actual blood glucose level difference, the rate of change of the actual blood glucose level difference at the current moment is compared with a pre-set threshold, and the event type is determined based on the comparison result. When the rate of change of the actual blood glucose level difference at the current moment is positive and greater than the pre-set positive threshold, the event is determined to be a meal. When the rate of change of the actual blood glucose level difference at the current moment is negative and less than the pre-set negative threshold, the event is determined to be exercise. Based on the determined event type, the artificial pancreas can automatically adjust the corresponding infusion strategy, achieving closed-loop control of the artificial pancreas.

[0039] Furthermore, the method of automatic detection based on the rate of change of the difference between the actual blood glucose values ​​can be combined with other judgment results to jointly determine the event type, making the judgment result more accurate, such as combining the judgment result obtained based on the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value, combining the result determined based on the insulin infusion information, and / or combining the result determined based on the variance of the actual blood glucose value at the current moment and the predicted blood glucose value.

[0040] Furthermore, when a meal or exercise begins to be detected, the detection module can shorten the detection interval, for example, changing Ts from 2 minutes to 1 minute, half a minute, 20s, 10s, 5s, or even shorter, thereby increasing the sampling frequency and more accurately identifying meal or exercise events. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] FIG1 is a schematic diagram of a closed-loop artificial pancreas module according to an embodiment of the present invention;

[0042] FIG2 is a flow chart of determining a meal or exercise event based on the rate of change of the difference between actual blood glucose levels according to an embodiment of the present invention;

[0043] 3 is a flow chart illustrating a method for determining a meal or exercise event based on the rate of change of the difference between the actual blood glucose level and the predicted blood glucose level according to an embodiment of the present invention;

[0044] 4 is a flow chart of determining a meal or exercise event in combination with insulin infusion information according to an embodiment of the present invention;

[0045] FIG5 is a flow chart of determining whether to eat or exercise based on the variance between the actual blood glucose level at the current moment and the predicted blood glucose level according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] As mentioned earlier, the current artificial pancreas still requires manual input of meal and / or exercise information, including meal type and size, exercise type and intensity, etc., so that the artificial pancreas can adjust the corresponding infusion strategy, and can only achieve semi-closed-loop control of the artificial pancreas.

[0047] To address this issue, the present invention provides a method for automatic detection based on the rate of change of the difference in actual blood glucose levels. The method includes: obtaining the user's current actual blood glucose level; obtaining the user's historical actual blood glucose levels and calculating the difference between the current and previous actual blood glucose levels; calculating the rate of change of the current actual blood glucose difference; and comparing the current rate of change of the actual blood glucose difference with a pre-set threshold value, and determining the event type based on the comparison result. Based on the determined event type, the artificial pancreas can automatically adjust the corresponding infusion strategy, achieving closed-loop control of the artificial pancreas.

[0048] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments should not be construed as limiting the scope of the present invention.

[0049] In addition, it should be understood that for ease of description, the sizes of the various components shown in the drawings are not necessarily drawn according to actual proportional relationships. For example, the thickness, width, length or distance of certain units may be enlarged relative to other structures.

[0050] The following description of exemplary embodiments is merely illustrative and is not intended to limit the present invention, its application, or use in any sense. Technologies, methods, and apparatus known to those skilled in the art may not be discussed in detail herein, but to the extent applicable, such technologies, methods, and apparatuses should be considered part of this specification.

[0051] It should be noted that like reference numerals and letters denote like items in the following figures, and thus, once an item is defined or described in one figure, it will not need to be further discussed in the subsequent figure descriptions.

[0052] FIG1 is a schematic diagram of a closed-loop artificial pancreas module according to an embodiment of the present invention.

[0053] In the embodiment of the present invention, the closed-loop artificial pancreas mainly includes a detection module 100 , an infusion module 102 and an electronic module 101 .

[0054] The detection module 100 is used to continuously monitor the user's current actual blood glucose level. Typically, the detection module 100 is a continuous glucose monitoring (CGM) device that can detect the user's current actual blood glucose level in real time and monitor blood glucose fluctuations. The detection module 100 can send the current blood glucose level to the electronic module 101 and / or the infusion module 102. The detection module 100 also includes a communication interface for communicating with external devices.

[0055] The infusion module 102 includes the mechanical structures necessary for insulin infusion, such as a drug storage cartridge for storing drugs; a drug infusion line, including an infusion needle, for infusing drugs into the user's body; a driving component for transferring drugs from the drug storage cartridge through the drug infusion line into the user's body, a battery for providing electrical energy, etc. A program unit is provided in the infusion module 102, including a memory and a processor, etc., and also includes a communication interface for communicating with external devices. The infusion module 102 can infuse the currently required insulin into the user's body according to the insulin infusion instructions. At the same time, the infusion status of the infusion module 102 can also be fed back to other modules in real time, such as the electronic module 101. The infusion module 102 can be a traditional insulin pump or a catheter-free patch-type insulin pump of Yi Yu Company.

[0056] The electronic module 101 can control the operation of the detection module 100 and the infusion module 102. The electronic module 101 is a portable electronic device, such as a smartphone, PDM, smartwatch, or handheld device. The portable electronic device may include: a communication interface for communicating with the detection device, infusion device, and external remote devices; a display and display controller for presenting visual information in the form of graphics and / or text and controlling the presentation of visual information; an input device, such as a mouse, keyboard, touch screen, microphone, etc., for receiving input signals; a memory and a processor, etc. The memory is used to store data, records, instructions, or store one or more control applications for execution by the processor, and the processor is used to execute instructions in the memory, calculate the insulin infusion data currently required by the user, and control the operation of other components.

[0057] In another embodiment of the present invention, the electronic module 101 may also be a structure electrically connected to or integrated with the infusion module 102 and / or the detection module 100 , but has the same functions as the aforementioned portable electronic device.

[0058] The communication between the detection module 100, the infusion module 102, and the electronic module 101 includes, but is not limited to, any wired or wireless communication link operating according to any known communication protocol or standard, such as Bluetooth , Wi-Fi, near field communication standards, cellular standards or any other wireless protocols, etc.

[0059] The embodiments of the present invention do not limit the specific positions and connection relationships of the detection module 100, the electronic module 101 and the infusion module 102, as long as the aforementioned functional conditions are met.

[0060] For example, in one embodiment of the present invention, the three are electrically connected or integrated to form an integral structure. Therefore, the three are pasted on the same position of the user's skin. The three modules are connected as a whole and pasted on the same position, and the number of devices pasted on the user's skin will be reduced, thereby reducing the interference of more devices pasted on the user's activities; at the same time, it also effectively solves the problem of wireless communication reliability between separate devices, further enhancing the user experience. Generally, the service life of the detection module 100, the electronic module 101 and the infusion module 102 are different. Therefore, when the three are electrically connected to each other to form the same device, the three can also be separated from each other in pairs. If one module reaches the end of its life first, the user can only replace the module and keep the other two modules for continued use.

[0061] In another embodiment of the present invention, the electronic module 101 and the infusion module 102 are interconnected or integrated to form a single structure, while the detection module 100 is separately located in another structure. In this case, the detection module 100 and the electronic module 101 transmit wireless signals to each other to achieve mutual connection. Thus, the electronic module 101 and the infusion module 102 are attached to a certain location on the user's skin, while the detection module 100 is attached to another location on the user's skin.

[0062] In another embodiment of the present invention, the electronic module 101 and the detection module 100 are interconnected or integrated to form a single device, while the infusion module 102 is separately provided in a separate structure. The infusion module 102 and the electronic module 101 transmit wireless signals to each other to achieve mutual connection. Thus, the electronic module 101 and the detection module 100 can be attached to a certain location on the user's skin, while the infusion module 102 can be attached to another location on the user's skin.

[0063] In another embodiment of the present invention, the infusion module 102 and the detection module 100 are interconnected or integrated to form a single device, while the electronic module 101 is separately located in a separate structure. The infusion module 102, the detection module 100, and the electronic module 101 mutually transmit wireless signals to achieve interconnection. Thus, the infusion module 102 and the detection module 100 can be attached to a specific location on the user's skin, while the electronic module 101 can be attached to another location on the user's skin or carried around as a portable electronic device.

[0064] In another embodiment of the present invention, the three modules are disposed in separate structures. Thus, the three modules are attached to different locations on the user's skin, or the detection module 100 and the infusion module 102 are attached to different locations on the user's skin, and the electronic module 101 is carried around as a portable electronic device. In this case, the electronic module 101 transmits wireless signals to the detection module 100 and the infusion module 102 to establish connections.

[0065] FIG2 is a flow chart of determining a meal or exercise event based on the rate of change of the difference between actual blood glucose levels according to an embodiment of the present invention.

[0066] The detection module 100 detects the user's current actual blood glucose level and periodically sends the blood glucose level to the electronic module 101, for example, every 5 minutes, every 2 minutes, every 1 minute, or even every 30 seconds, or other time intervals. The electronic module 101 receives and stores the blood glucose level detected by the detection module 100. Step 201: Obtain the user's current actual blood glucose level; Step 202: Obtain the user's previous historical actual blood glucose level and calculate the difference between the current and previous actual blood glucose levels. dev (N) = G(N) - G(N-1)

[0067] Here:

[0068] G(N) represents the actual blood glucose value at the current moment;

[0069] G(N-1) represents the actual blood glucose value at the previous moment;

[0070] G dev (N) represents the difference in actual blood sugar level at the current moment.

[0071] Before calculating the difference between the actual blood glucose value at the current moment and the previous moment, the raw continuous glucose data may be filtered or smoothed.

[0072] Step 203, calculate the rate of change of the difference between the actual blood glucose levels at the current moment:

[0073] Here:

[0074] G dev (N) represents the difference between the actual blood glucose value at the current moment;

[0075] G dev (N-1) represents the difference between the actual blood glucose value at the previous moment;

[0076] T S Indicates the time interval between the previous moment and the current moment;

[0077] G accel(N) represents the rate of change of the difference in actual blood sugar levels at the current moment.

[0078] Here, the difference between the actual blood glucose level at the previous moment can be calculated by referring to step 202. The time interval T between the previous moment and the current moment S It can be the minimum period detected and sent by the detection module 100 or an integer multiple of the minimum period, or it can be less than the minimum period detected and sent by the detection module 100, but in steps 202 and 203, the time interval between the current moment and the previous moment is consistent.

[0079] Step 204 determines whether the rate of change of the difference in actual blood glucose levels is positive. If so, step 205 compares the rate of change of the difference in actual blood glucose levels with a pre-set positive threshold. If not, step 206 compares the rate of change of the difference in actual blood glucose levels with a pre-set negative threshold. Since the user's blood glucose level will fluctuate to a certain extent even when not eating or exercising, setting corresponding thresholds can better determine whether the rate of change of the difference in blood glucose levels is caused by eating or exercising. The positive and negative thresholds can be based on empirical values ​​or customized by the user. If the rate of change of the difference in actual blood glucose levels is higher than the pre-set positive threshold, step 207 determines the event as a meal event; otherwise, it is not determined to be a meal event. If the rate of change of the difference in actual blood glucose levels is lower than the pre-set negative threshold, step 208 determines the event as an exercise event; otherwise, it is not determined to be an exercise event.

[0080] At the beginning of a meal or exercise, generally within 20 minutes, blood glucose levels will change at an accelerated rate. In order to more accurately identify the rate of change of the difference between the actual blood glucose levels at the current moment, when a meal or exercise is detected, the detection module 100 can shorten the detection interval, for example, changing Ts from 2 minutes to 1 minute, half a minute, 20s, 10s, 5s, or even shorter, thereby increasing the sampling frequency to more accurately identify meal or exercise events.

[0081] FIG3 is a flow chart of determining whether to eat or exercise based on the rate of change of the difference between the actual blood glucose level and the predicted blood glucose level according to an embodiment of the present invention.

[0082] Since blood sugar levels increase or decrease rapidly during meals or exercise, blood sugar predictions are continuously performed during the process, and the predicted blood sugar values ​​are compared with the actual blood sugar values. It can be found that the difference between the predicted blood sugar values ​​and the actual blood sugar values ​​tends to become larger and larger.

[0083] Step 301, predicting the current blood sugar level;

[0084] In this embodiment of the present invention, the blood glucose prediction algorithm is as follows:

[0085] Gp (N) represents the predicted blood glucose value at the current moment;

[0086] G(Nk) represents the actual blood glucose value at the previous k moments;

[0087] a k Represents the coefficient related to time;

[0088] b k represents the time decay coefficient associated with the insulin consumption curve;

[0089] CF indicates insulin sensitivity;

[0090] I(Nk) represents the value of the amount of insulin infused in a unit time period at time k;

[0091] I basal Indicates the body's basal insulin consumption in each time period.

[0092] In the embodiment of the present invention, T s Indicates a cycle of blood glucose measurement and insulin infusion. The value of m*Ts should be greater than or equal to IOB time, otherwise b k *CF(I(Nk)-I basal )=0, that is, when predicting blood glucose level, only the influence of IOB in the body is considered. When IOB is no longer in the body, IOB and I basal The influence of insulin sensitivity is not taken into account, and the predicted blood glucose value is more accurate.

[0093] In another embodiment of the present invention, the predicted blood glucose level is calculated based on at least the actual blood glucose level at a previous moment and its first-order derivative and second-order derivative with respect to time.

[0094] Blood glucose change rate E v It can be calculated from two moments before and after, or obtained by linear regression of multiple moments within a period of time. Specifically, when the rate of change between the two moments before and after is used for calculation, the calculation formula is: E v =dG t / dt=(G t -G t-1 ) / Ts

[0095] in:

[0096] E v Indicates the blood sugar change rate at the current moment;

[0097] G t Indicates the current blood sugar value;

[0098] G t-1 Indicates the blood sugar value at the last moment;

[0099] Ts represents the time interval between the current moment and the previous moment.

[0100] When the blood glucose values ​​at three points are used to calculate the rate of change, the formula is: E v =dG t / dt=(3G t -4G t-1 +G t-2 ) / 2Ts

[0101] in:

[0102] G t Indicates the current blood sugar value;

[0103] G t-1 Indicates the blood sugar value at the last moment;

[0104] G t-2 Indicates the blood sugar value at the last moment;

[0105] Ts represents the time interval between the current moment and the previous moment.

[0106] In calculating the blood glucose change rate E v Before starting, you can filter or smooth the raw continuous glucose data. The threshold can be set between 1.8mg / mL and 3mg / mL, or you can customize it.

[0107] In other embodiments of the present invention, the blood glucose change rate E v The weighted average method can also be used to obtain:

[0108] in:

[0109] E vi Indicates the blood sugar change rate of each test point in the period before the current moment.

[0110] Blood glucose change rate E obtained by weighted average method v It is smoother, eliminates the interference of some singular points, and improves the accuracy of the algorithm.

[0111] The blood glucose change rate is the first-order derivative of the blood glucose value with respect to time, which can be calculated based on the blood glucose change rate E v Calculate predicted blood glucose value: G pt =E t-1 *Ts+G t-1

[0112] in:

[0113] G pt is the predicted blood sugar value at the current moment;

[0114] Ts represents the time interval between the current moment and the previous moment;

[0115] G t-1 The actual blood sugar value at the last moment;

[0116] E v-1 is the blood sugar change rate at the previous moment.

[0117] The time interval Ts can be set to an intermittent time mode of the detection module 100, such as an intermittent time mode like a CGM device, such as calculating once every 2 minutes, or it can be set to a higher frequency intermittent time mode, such as calculating once every 1 minute, once every 30 seconds, or it can be set to a continuous time mode.

[0118] Although the blood glucose change rate E can be used v To predict blood glucose levels, the above algorithm may be inaccurate when the actual blood glucose curve is at a turning point. Therefore, a higher-order derivative of the blood glucose value with respect to time can be introduced to predict the blood glucose value, which can improve the accuracy of the algorithm.

[0119] In a preferred embodiment of the present invention, the second-order derivative of blood glucose value with respect to time, namely the blood glucose change acceleration E, is introduced. a To predict blood sugar levels, it can accurately estimate blood sugar levels even when the actual blood sugar level is at a turning point.

[0120] In some embodiments of the present invention, the blood glucose change acceleration E a The calculation formula is:

[0121] in:

[0122] E v0 is the blood sugar change rate at the current moment;

[0123] E v1 The blood sugar change rate at the previous moment;

[0124] Ts represents the time interval between the current moment and the previous moment;

[0125] E a Indicates the acceleration of blood sugar changes.

[0126] Based on the blood sugar change acceleration E a The calculation formula to estimate blood sugar level is:

[0127] G pt is the predicted blood sugar value at the current moment;

[0128] Ts represents the time interval between the current moment and the previous moment;

[0129] G t-1The actual blood sugar value at the last moment;

[0130] E v is the blood sugar change rate at the previous moment.

[0131] In other embodiments of the present invention, a weighted average method may be used to obtain:

[0132] in:

[0133] Indicates the average value of the acceleration of blood sugar changes.

[0134] E ai Indicates the acceleration of blood sugar changes at each test point in the period before the current moment.

[0135] Blood glucose change acceleration E obtained by weighted average method a It is smoother, eliminates the interference of some singular points, and improves the accuracy of the algorithm.

[0136] In other embodiments of the present invention, a smoothing algorithm such as a quadratic curve fitting method may be used to calculate the blood glucose change rate and / or blood glucose change acceleration:

[0137] in:

[0138] T i is the sampling point time;

[0139] G Ti is the blood glucose value at the sampling point;

[0140] c is the curve constant;

[0141] E v is the rate of change of blood glucose;

[0142] E a The acceleration of blood sugar changes.

[0143] Before using quadratic curve fitting, it is necessary to sample the blood glucose values ​​over a period of time to obtain a series of combinations of blood glucose values ​​and sampling time (G Ti , T i ), in embodiments of the present invention, at least three groups of samples should be taken to complete quadratic curve fitting. In a preferred embodiment of the present invention, three blood glucose values ​​within a certain period of time are used as sampling points. In other embodiments of the present invention, outliers at the sampling points can be statistically eliminated before performing quadratic curve fitting. This can minimize the influence of singular points, making the simulated curve smoother and thus improving the accuracy of the algorithm.

[0144] In other embodiments of the present invention, other curve fitting algorithms can also be used to calculate the blood glucose change rate E v and / or blood sugar change acceleration E a , such as higher-order curve fitting, will not be described here.

[0145] Step 302, obtaining the actual blood glucose value at the current moment; Step 303, calculating the difference between the actual blood glucose value at the current moment and the predicted blood glucose value; G pdev (N) = G(N) - G p (N)

[0146] G pdev (N) represents the difference between the actual blood glucose value at the current moment and the predicted blood glucose value;

[0147] G(N) represents the actual blood glucose value at the current moment;

[0148] G p (N) represents the predicted blood sugar level at the current moment.

[0149] When eating, you will find that G pdev The value of (N) will be greater than zero and will become larger and larger. When moving, G pdev (N) will be less than zero and will become smaller and smaller. Therefore, in step 303, it can be preliminarily determined whether the user has eaten or exercised.

[0150] Furthermore, the method further includes step 304 of calculating the rate of change of the difference between the actual blood glucose level at the current moment and the predicted blood glucose level;

[0151] Here:

[0152] G pdev (N) represents the difference between the actual blood glucose value at the current moment and the predicted blood glucose value;

[0153] G pdev (N-1) represents the difference between the actual blood glucose value at the previous moment and the predicted blood glucose value;

[0154] T S Indicates the time interval between the previous moment and the current moment;

[0155] G paccel (N) represents the rate of change of the difference between the actual blood sugar level at the current moment and the predicted blood sugar level.

[0156] Here, the time interval T between the previous moment and the current moment S It can be the minimum period or an integer multiple of the minimum period detected and sent by the detection module 100, or it can be less than the minimum period detected and sent by the detection module 100. The calculation method of the difference between the actual blood glucose value and the predicted blood glucose value at the previous moment is the same as step 303.

[0157] Step 305 determines whether the rate of change of the difference between the current actual blood glucose level and the predicted blood glucose level is positive. If so, step 306 compares the rate of change of the difference between the current actual blood glucose level and the predicted blood glucose level with a pre-set positive threshold. If not, step 307 compares the rate of change of the difference between the current actual blood glucose level and the predicted blood glucose level with a pre-set negative threshold. Since the user's blood glucose level can fluctuate to a certain extent even when not eating or exercising, setting appropriate thresholds can better determine whether the rate of change of the blood glucose level difference is caused by eating or exercising. The positive and negative thresholds can be based on empirical values ​​or user-defined. If the rate of change of the difference between the current actual blood glucose level and the predicted blood glucose level is higher than the pre-set positive threshold, step 308 determines the event as a meal event; otherwise, it is not determined to be a meal event. If the rate of change of the difference between the current actual blood glucose level and the predicted blood glucose level is lower than the pre-set negative threshold, step 309 determines the event as an exercise event; otherwise, it is not determined to be an exercise event.

[0158] In other embodiments of the present invention, exercise or meal events can also be determined in combination with the judgment result based on the rate of change of the difference between the actual blood glucose values ​​and the judgment result based on the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value. For example, if the judgment result based on the rate of change of the difference between the actual blood glucose value and the judgment result based on the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value are both determined to be a meal or exercise event, then it is determined to be a meal or exercise event; otherwise, it is not determined to be a meal or exercise event.

[0159] FIG4 is a flow chart showing a method of determining a meal or exercise event by combining insulin infusion information according to an embodiment of the present invention.

[0160] Since changes in blood sugar may be caused by abnormal insulin infusion, the most recent insulin infusion can be used as a reference when determining meal or exercise events.

[0161] Step 401: Obtain insulin infusion information for a recent period of time. Step 402: Calculate the amount of insulin infused I1 for the recent period of time. Step 403: Obtain insulin infusion information for a past period of time. Step 404: Calculate the amount of insulin infused I2 for the past period of time. Here, the recent period of time is m*Ts time. As previously mentioned, the value of m*Ts should be greater than or equal to 10B time, and the past period of time can be m*Ts time adjacent to the recent period of time. Step 405: Compare the amount of insulin infused I1 for the recent period of time with the amount of insulin infused I2 for the past period of time. If the absolute value of the difference between the two is not greater than a preset threshold value T, then step 406: Trust the result determined based on the rate of change of the difference between the actual blood glucose levels and / or the rate of change of the difference between the current actual blood glucose level and the predicted blood glucose level. Otherwise, step 407: Distrust the result determined based on the rate of change of the difference between the actual blood glucose levels and / or the rate of change of the difference between the current actual blood glucose level and the predicted blood glucose level, and the change in blood glucose may be caused by abnormal insulin infusion. The threshold T can be set based on experience or can be user-defined.

[0162] FIG5 is a flow chart of determining whether to eat or exercise based on the variance between the actual blood glucose level at the current moment and the predicted blood glucose level according to an embodiment of the present invention.

[0163] In the embodiment of the present invention, eating or exercise events can also be determined by calculating the variance between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0164] Step 501: Calculate the variance between the actual blood glucose level at the current moment and the predicted blood glucose level. The calculation formula is as follows:

[0165] G ssr (N) represents the variance between the actual blood glucose value at the current moment and the predicted blood glucose value;

[0166] G(N) represents the actual blood glucose value at the previous moment;

[0167] G p (N) represents the predicted blood sugar level at the previous moment.

[0168] G p The calculation formula of (N) is the same as that in step 301.

[0169] Step 502 determines whether the variance between the actual blood glucose value at the current moment and the predicted blood glucose value is greater than a preset threshold. If the variance is greater than the threshold, step 503 trusts the result determined based on the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value. Otherwise, step 504 distrusts the result determined based on the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

[0170] In other embodiments of the present invention, before determining whether to eat or exercise by calculating the variance between the current actual blood glucose level and the predicted blood glucose level, the amount of insulin infused in the most recent period, I1, and the amount of insulin infused in the past period, I2, can be determined. If the absolute value of the difference between I1 and I2 is less than a preset threshold value, T, the result determined by the variance between the current actual blood glucose level and the predicted blood glucose level is trusted. Otherwise, the result determined by the variance between the current actual blood glucose level and the predicted blood glucose level is not trusted. Threshold T can be set based on experience or can be user-defined.

[0171] To more quickly determine the occurrence of exercise, the closed-loop artificial pancreas also includes a motion sensor (not shown). The motion sensor is used to automatically detect the user's physical activity, and the electronic module 101 can receive physical activity status information. The motion sensor can automatically and accurately sense the user's physical activity status and send activity status parameters to the electronic module 101. Combined with various methods for determining whether a meal or exercise has occurred, such as judging based on the rate of change of the difference between the actual blood glucose value, judging based on the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value, and judging based on the variance of the actual blood glucose value at the current moment and the predicted blood glucose value, it can quickly determine whether a meal event has occurred.

[0172] The motion sensor may be provided in the detection module 100, the electronic module 101 or the infusion module 102. Preferably, in the embodiment of the present invention, the motion sensor is provided in the electronic module 101.

[0173] It should be noted that the embodiment of the present invention does not limit the number of motion sensors and the locations where the multiple motion sensors are installed, as long as the conditions for the motion sensors to sense user activity conditions are met.

[0174] The motion sensor includes a three-axis acceleration sensor or a gyroscope. A three-axis acceleration sensor or a gyroscope can more accurately sense the intensity, movement pattern, or body posture of the body. Preferably, in an embodiment of the present invention, the motion sensor is a combination of a three-axis acceleration sensor and a gyroscope.

[0175] In summary, the present invention discloses a method for automatically detecting an event based on the rate of change of the difference in actual blood glucose levels. The method comprises: obtaining the user's current actual blood glucose level; obtaining the user's historical actual blood glucose levels and calculating the difference between the current and previous actual blood glucose levels; calculating the rate of change of the current actual blood glucose difference; and comparing the current rate of change of the actual blood glucose difference with a pre-set threshold value, and determining the event type based on the comparison result. Based on the determined event type, the artificial pancreas can automatically adjust the corresponding infusion strategy, achieving closed-loop control of the artificial pancreas.

[0176] Although some specific embodiments of the present invention have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It should be understood by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A method for automatically detecting the change rate of the difference between actual blood sugar levels, characterized in that: include: Get the user's actual blood sugar value at the current moment; Obtain the user's previous historical actual blood sugar value, and calculate the difference between the actual blood sugar value at the current moment and the previous moment; Calculate the rate of change of the difference between the actual blood sugar values ​​at the current moment; and The change rate of the difference between the actual blood sugar levels at the current moment is compared with a preset threshold, and the event type is determined according to the comparison result.

2. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 1, characterized in that: When the change rate of the difference between the actual blood sugar levels at the current moment is positive and greater than the preset positive threshold, the event is determined to be a meal.

3. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 1, characterized in that: When the change rate of the difference between the actual blood sugar levels at the current moment is negative and is less than the preset negative threshold, the event is determined to be exercise.

4. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 1, characterized in that: When the event type starts to be determined, the time interval between the current moment and the previous moment gradually shortens.

5. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 1, characterized in that: The event type is further determined in combination with other judgment results.

6. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 5, characterized in that: The other judgment results are judgment results obtained based on the change rate of the difference between the actual blood sugar value at the current moment and the predicted blood sugar value.

7. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 6, characterized in that: The type of event is determined when the judgment result obtained from the change rate of the difference between the actual blood sugar value and the predicted blood sugar value at the current moment is consistent with the judgment result obtained based on the change rate of the difference between the actual blood sugar values.

8. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 7, characterized in that: The prediction algorithm for predicting blood sugar levels also takes into account the effects of insulin that has not yet taken effect in the body and insulin sensitivity.

9. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 7, characterized in that: The predicted blood glucose value is calculated based on at least the actual blood glucose value at a previous moment and the first-order derivative or the second-order derivative of the actual blood glucose value at the previous moment with respect to time.

10. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to any one of claims 1 to 9, characterized in that: The other determination results further include results determined according to insulin infusion information.

11. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 10, characterized in that: The method for determining a result according to the insulin infusion information comprises: Obtain the insulin infusion information in the recent period and calculate the insulin infusion amount I1; Obtain the insulin infusion information in the past period of time and calculate the insulin infusion amount I2; Calculate the absolute value of the difference between I1 and I2; Compare the absolute value of the difference with a preset threshold value. If the absolute value of the difference is not greater than the preset threshold value, trust the result determined by the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

12. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 11, characterized in that: The past period of time is a time period adjacent to the most recent period of time.

13. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to any one of claims 1 to 9, characterized in that: The other determination results further include results determined based on the variance between the actual blood sugar value at the current moment and the predicted blood sugar value.

14. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 13, characterized in that: The method for determining a result based on the variance between the actual blood glucose value at the current moment and the predicted blood glucose value includes comparing the variance with a preset threshold value. If the variance is greater than the threshold value, the result determined based on the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value is trusted.

15. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 13, characterized in that: Other judgment results further include results determined based on insulin infusion information.

16. The method for automatically detecting the rate of change of the difference between actual blood sugar levels according to claim 15, characterized in that: When the absolute value of the difference between the amount of insulin infused in the most recent period I1 and the amount of insulin infused in the past period I2 is less than a preset threshold, the result determined based on the variance between the actual blood sugar value at the current moment and the predicted blood sugar value is trusted.

17. A closed-loop artificial pancreas, comprising: A detection module, used to continuously detect the user's current actual blood sugar value; An infusion module, used for infusing currently required insulin into the user's body according to the insulin infusion instruction; and The electronic module is used to control the operation of the detection module and the infusion module, and includes a memory and a processor; the characteristic is that the processor automatically determines the type of event by calculating the rate of change of the difference between the actual blood glucose values ​​detected by the detection module.

18. The closed-loop artificial pancreas according to claim 17, characterized in that: The method for automatically determining the type of an event includes: Get the user's actual blood sugar value at the current moment; Obtain the user's previous historical actual blood sugar value, and calculate the difference between the actual blood sugar value at the current moment and the previous moment; Calculate the rate of change of the difference between the actual blood sugar values ​​at the current moment; The change rate of the difference between the actual blood sugar levels at the current moment is compared with a preset threshold, and the event type is determined according to the comparison result.

19. The closed-loop artificial pancreas according to claim 18, characterized in that: When the change rate of the difference between the actual blood glucose values ​​at the current moment is positive and greater than a preset positive threshold, the event is determined to be a meal; when the change rate of the difference between the actual blood glucose values ​​at the current moment is negative and less than a preset negative threshold, the event is determined to be exercise.

20. The closed-loop artificial pancreas according to claim 19, characterized in that The method for automatically determining the type of an event further combines other determination results to jointly determine the type of event.

21. The closed-loop artificial pancreas according to claim 20, characterized in that The other judgment results are judgment results obtained based on the change rate of the difference between the actual blood sugar value at the current moment and the predicted blood sugar value.

22. The closed-loop artificial pancreas according to claim 21, characterized in that The other determination results further include results determined according to insulin infusion information.

23. The closed-loop artificial pancreas according to claim 22, characterized in that The method for determining a result according to the insulin infusion information comprises: Obtain the insulin infusion information in the recent period and calculate the insulin infusion amount I1; Obtain the insulin infusion information in the past period of time and calculate the insulin infusion amount I2; Calculate the absolute value of the difference between I1 and I2; Compare the absolute value of the difference with a preset threshold value. If the absolute value of the difference is not greater than the preset threshold value, trust the result determined by the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value.

24. The closed-loop artificial pancreas according to claim 21, characterized in that The other determination results further include results determined based on the variance between the actual blood sugar value at the current moment and the predicted blood sugar value.

25. The closed-loop artificial pancreas according to claim 24, characterized in that The method for determining a result based on the variance between the actual blood glucose value at the current moment and the predicted blood glucose value includes comparing the variance with a preset threshold value. If the variance is greater than the threshold value, the result determined based on the rate of change of the difference between the actual blood glucose value and / or the rate of change of the difference between the actual blood glucose value at the current moment and the predicted blood glucose value is trusted.

26. The closed-loop artificial pancreas according to claim 24, characterized in that The result determined based on the variance between the actual blood sugar value at the current moment and the predicted blood sugar value further includes a result determined based on insulin infusion information.

27. The closed-loop artificial pancreas according to claim 17, characterized in that The device also includes a motion sensor, which is a combination of a three-axis acceleration sensor and a gyroscope.

28. The closed-loop artificial pancreas according to claim 27, characterized in that At least two of the detection module, the infusion module and the electronic module are interconnected or integrated to form an integral structure.

29. The closed-loop artificial pancreas according to claim 27, characterized in that The detection module, the infusion module and the electronic module are respectively arranged in different structures.

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