Intelligent disease course management method and system based on diabetics
By acquiring plate images and blood glucose level information, and using image detection algorithms and historical databases to predict blood glucose levels, the reliability issue of post-meal health assessment for diabetic patients is resolved, enabling more accurate health assessments.
Patent Information
- Application Number
- CN202510719939.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-30
- Publication Date
- 2025-09-09
AI Technical Summary
In the existing technology, hospitals' assessment of the health status of diabetic patients after meals has the problem of low reliability, making it difficult to accurately judge the health status of patients.
By obtaining the actual image information of the target plate and the current blood sugar level information of the target user, the image detection algorithm is used to generate estimated sugar value information, and the blood sugar level information is predicted based on the historical database, and finally the health assessment result information is generated to reduce subjective judgment.
It achieves accurate assessment of the health status of diabetic patients after meals, improves the reliability of the assessment, and reduces subjective errors.
Smart Images
Figure CN120613124A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of smart medical care, and more specifically, to an intelligent disease course management method and system for diabetic patients. Background Art
[0002] Diabetic patients need to strictly control their sugar intake, and at the same time need to monitor their blood sugar levels and adjust their medications over a long period of time. For some patients with severe conditions, they usually need to be hospitalized for blood sugar adjustment and be discharged only after their condition stabilizes.
[0003] At present, hospitals usually use manual evaluation to assess patients' health status after meals, which is highly subjective and difficult to accurately judge patients' health status after meals. It has the problem of low reliability and needs further improvement. Summary of the Invention
[0004] Based on this, the embodiment of the present application provides an intelligent disease course management method and system for diabetic patients to solve the problem of low reliability in the existing technology.
[0005] In a first aspect, an embodiment of the present application provides an intelligent disease course management method for diabetic patients, the method comprising:
[0006] Obtaining real-shot image information of the target meal plate and the current blood sugar level information of the target user;
[0007] generating estimated sugar content information based on the real-shot image information and the image detection algorithm;
[0008] Generate predicted blood sugar level information based on the current blood sugar level information and the estimated blood sugar level information based on a preset historical database;
[0009] Health assessment result information is generated based on the predicted blood sugar level information and the preset warning blood sugar level information.
[0010] Compared with the existing technology, the beneficial effect is: the intelligent disease course management method based on diabetic patients provided by the embodiment of the present application, the terminal device can first obtain the real-shot image information of the target plate, and at the same time obtain the current blood sugar value information of the target user, and then quickly generate estimated sugar value information based on the real-shot image information and the image detection algorithm, and then based on the historical database, effectively generate predicted blood sugar value information based on the current blood sugar value information and the estimated blood sugar value information, and finally accurately generate health assessment result information based on the predicted blood sugar value information and the warning blood sugar value information, thereby realizing accurate assessment of the health status of diabetic patients after meals before meals, reducing subjective judgments, effectively improving reliability, and to a certain extent solving the current low reliability problem.
[0011] In a second aspect, an embodiment of the present application provides an intelligent disease course management system for diabetic patients, the system comprising:
[0012] Real-time image information acquisition module: used to obtain real-time image information of the target plate and the current blood sugar value information of the target user;
[0013] Estimated sugar value information generation module: used to generate estimated sugar value information based on the real-shot image information and image detection algorithm;
[0014] A predicted blood sugar level information generating module is configured to generate predicted blood sugar level information based on a preset historical database and the current blood sugar level information and the estimated sugar level information;
[0015] Health assessment result information generation module: used to generate health assessment result information based on the predicted blood glucose value information and the preset warning blood glucose value information.
[0016] In a third aspect, an embodiment of the present application provides a terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of the first aspect described above when executing the computer program.
[0017] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method of the first aspect described above are implemented.
[0018] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art.
[0020] Figure 1 This is a flowchart of an intelligent disease management method provided by an embodiment of the present application;
[0021] Figure 2 This is a flowchart of step S200 in the intelligent disease course management method provided in one embodiment of the present application;
[0022] Figure 3 This is a flowchart of step S300 in the intelligent disease course management method provided in one embodiment of the present application;
[0023] Figure 4 This is a flowchart of step S400 in the intelligent disease course management method provided in one embodiment of the present application;
[0024] Figure 5 This is a first flow chart after step S400 in the intelligent disease course management method provided in one embodiment of the present application;
[0025] Figure 6 This is a second flow chart after step S400 in the intelligent disease course management method provided in one embodiment of the present application;
[0026] Figure 7 This is a module block diagram of an intelligent disease management system provided by an embodiment of the present application;
[0027] Figure 8 This is a schematic diagram of a terminal device provided in one embodiment of the present application. DETAILED DESCRIPTION
[0028] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.
[0029] In the description of this application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.
[0030] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.
[0031] In order to illustrate the technical solution described in this application, specific embodiments are provided below.
[0032] See also Figure 1 , Figure 1: This is a flow chart of an intelligent disease course management method for diabetic patients provided in an embodiment of the present application. In this embodiment, the execution subject of the intelligent disease course management method is a terminal device. It is understood that the types of terminal devices include but are not limited to tablet computers, laptops, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), etc., and this embodiment of the present application does not impose any restrictions on the specific type of terminal devices.
[0033] See also Figure 1 The intelligent disease course management method provided in the embodiment of the present application includes but is not limited to the following steps:
[0034] In S100 , the real-shot image information of the target meal plate is obtained, and the current blood sugar level information of the target user is obtained.
[0035] Specifically, the terminal device can first obtain the real-shot image information of the target plate and simultaneously obtain the current blood sugar value information of the target user, wherein the real-shot image information is used to describe the real-shot image obtained by shooting the target plate. The shooting process of the real-shot image information can be operated by medical staff. In one possible implementation method, the shooting angle of the real-shot image information is preferably vertically downward from directly above the target plate.
[0036] Without loss of generality, the target user is used to describe diabetic patients who are hospitalized for blood sugar adjustment; the current blood sugar value information is used to describe the actual blood sugar value of the target user before a meal. In one possible implementation method, the terminal device can obtain the blood sugar value of the target user through spectral imaging technology, thereby reducing the pain and potential risks caused by invasive blood sugar testing. Detecting blood sugar values through spectral imaging technology is an existing technology, so it will not be elaborated.
[0037] In S200 , estimated sugar content information is generated based on the real-shot image information and the image detection algorithm.
[0038] Specifically, after the terminal device obtains the real-shot image information and the current blood sugar value information, the terminal device can effectively generate estimated sugar value information based on the real-shot image information and the image detection algorithm, wherein the estimated sugar value information is used to describe the estimated sugar amount of food for that meal.
[0039] In some possible implementations, in order to effectively generate estimated sugar value information, please refer to Figure 2 Step S200 includes but is not limited to the following steps:
[0040] In S210 , based on the real-shot image information and the image detection algorithm, a plurality of receiving area information, a plurality of food area information and food type information corresponding to each food area information of the target plate are generated.
[0041] Specifically, the terminal device can use an image detection algorithm to detect and process the actual image information, effectively generating multiple receiving area information of the target plate, multiple food area information of the target plate, and food type information corresponding to each food area information. The image detection algorithm can be a target detection algorithm based on YOLO (You Only Look Once) V5 or a target detection algorithm based on Faster R-CNN (Region-based Convolutional Network).
[0042] Without loss of generality, the receiving area information is used to describe the area on the target plate used to receive food; the food area information is used to describe the area corresponding to the food on the target plate, that is, the area corresponding to the food located within the receiving area information; the food type information is used to describe the corresponding type of food, such as oatmeal, apple, and tofu; each receiving area information and each food area information correspond one to one.
[0043] In S220 , based on a preset contour extraction algorithm, the receiving area contour line information corresponding to each receiving area information and the food area contour line information corresponding to each food area information are determined.
[0044] Specifically, the terminal device can quickly determine the containing area contour line information corresponding to each containing area information, and the food area contour line information corresponding to each food area information based on a preset contour extraction algorithm, wherein the contour extraction algorithm can be an edge detection algorithm based on the Canny operator or an edge detection algorithm based on the Sobel operator; the containing area contour line information is used to describe the outer contour line corresponding to the containing area information; the food area contour line information is used to describe the outer contour line corresponding to the food area information.
[0045] In S230 , for each set of receiving area information and food area information: food area information is generated according to the food area outline information, and receiving area area information is generated according to the receiving area outline information.
[0046] Without loss of generality, the terminal device may determine that the receiving area information and the corresponding food area information are the same group, that is, the receiving area information and the food area information located therein are the same group.
[0047] Specifically, after the terminal device determines the containing area contour line information and the food area contour line information, the terminal device can perform this processing for each group of containing area information and food area information: divide the area enclosed by the food area contour line information into multiple regular shapes, such as rectangles, and then calculate the area of each regular shape separately, and finally generate the food area area information according to the sum of the areas of all regular shapes; at the same time, generate the containing area area information according to the containing area contour line information, wherein the calculation process of the containing area area information can refer to the calculation process of the food area area information, so it will not be repeated; the food area area information is used to describe the area of the food area information; the containing area area information is used to describe the area of the containing area information.
[0048] In S240 , phase difference ratio information is generated based on the area information of the receiving area and the area information of the food area.
[0049] Specifically, after the terminal device generates food area area information and receiving area area information, the terminal device can generate phase difference ratio information based on the quotient of the food area area information divided by the receiving area area information, wherein the value of the phase difference ratio information is the quotient of the food area area information divided by the receiving area area information.
[0050] In S250 , the storage area volume information corresponding to the storage area information is obtained.
[0051] Specifically, after the terminal device generates the phase difference ratio information, the terminal device can obtain the storing area volume information corresponding to the storing area information, wherein the storing area volume information is used to describe the volume of the storing area information, and the storing area volume information can be a preset value set in advance based on the product size of the target plate.
[0052] In S260 , food area volume information is generated based on the phase difference ratio information and the storage area volume information.
[0053] Specifically, after the terminal device obtains the storage area volume information, the terminal device can generate food area volume information based on the phase difference ratio information multiplied by the storage area volume information, wherein the food area volume information is used to describe the estimated volume corresponding to the food area information.
[0054] In S270, the average food density information and the average food sugar content information corresponding to the food type information are obtained.
[0055] Specifically, after the terminal device generates food area volume information, the terminal device can obtain the food average density information corresponding to the food type information and the food average sugar content information corresponding to the food type information, wherein the food average density information is used to describe the average density of the food; the food average sugar content information is used to describe the sugar content per 100 grams of food; the food average density information and the food average sugar content information can both be preset values.
[0056] For example, the average food density information corresponding to food of the type of oatmeal can be preset to 0.5 grams per cubic centimeter; the average food density information corresponding to food of the type of apple can be preset to 0.7 grams per cubic centimeter; the average food density information corresponding to food of the type of tofu can be preset to 1 gram per cubic centimeter; the average food sugar content information corresponding to food of the type of apple can be preset to 10g / 100g, that is, 10 grams per 100 grams.
[0057] In S280 , estimated sugar value information is generated based on the food region volume information, the food average density information, and the food average sugar content information.
[0058] Specifically, after the terminal device obtains the average food density information and the average food sugar content information, the terminal device can effectively generate estimated sugar value information based on the product of the food area volume information multiplied by the average food density information and then multiplied by the average food sugar content information.
[0059] In S300 , based on a preset historical database, predicted blood sugar level information is generated according to the current blood sugar level information and the estimated sugar level information.
[0060] Specifically, after the terminal device generates the estimated blood sugar value information, the terminal device can search a preset historical database based on the current blood sugar value information and the estimated blood sugar value information to effectively generate the predicted blood sugar value information.
[0061] Without loss of generality, the historical database can store multiple sets of user blood glucose data set information, and each set of user blood glucose data set information can be collected from each dining process of a diabetic patient; each set of user blood glucose data set information includes historical initial blood glucose value information, historical estimated sugar value information, historical final blood glucose value information and historical medication interval time information.
[0062] Specifically, the historical initial blood glucose value information is used to describe the blood glucose value of a diabetic patient before a meal during a historical meal; the historical estimated sugar value information is used to describe the estimated sugar amount of food in a historical meal during a historical meal; the historical final blood glucose value information is used to describe the blood glucose value of a diabetic patient after a meal during a historical meal. The historical final blood glucose value information can be the blood glucose peak value within a specified time period after the diabetic patient's meal; the historical medication interval time information is used to describe the time interval between the time a diabetic patient takes insulin before a meal and the time of the meal.
[0063] In some possible implementations, in order to retrieve the historical dining situation that is most similar to the current dining situation and improve the accuracy of the estimation result, before step S300, the method further includes but is not limited to the following steps:
[0064] In S301, the current medication interval information of the target user is obtained.
[0065] Specifically, the terminal device may first obtain the target user's current medication interval information, wherein the current medication interval information is used to describe the time interval between the target user's insulin taking time and the meal time during the meal.
[0066] Accordingly, see Figure 3 Step S300 includes but is not limited to the following steps:
[0067] In S310, for each group of user blood glucose data set information in the historical database: determine whether the difference between the historical initial blood glucose value information and the current blood glucose value information is less than a preset first difference threshold, whether the difference between the historical estimated sugar value information and the estimated sugar value information is less than the first difference threshold, and whether the difference between the historical medication interval time information and the current medication interval time information is less than a preset second difference threshold.
[0068] Specifically, the terminal device can perform this processing on the blood glucose data set information of each group of users in the historical database: determine whether the difference between the historical initial blood glucose value information and the current blood glucose value information is less than the preset first phase difference threshold, and at the same time determine whether the difference between the historical estimated sugar value information and the estimated sugar value information is less than the first phase difference threshold, and determine whether the difference between the historical medication interval time information and the current medication interval time information is less than the preset second phase difference threshold, wherein the first phase difference threshold and the second phase difference threshold can both be preset values set in advance based on the specific situation of the target user.
[0069] In S320, if the difference between the historical initial blood glucose value information and the current blood glucose value information is less than a preset difference threshold, and the difference between the historical predicted blood glucose value information and the estimated blood glucose value information is less than the difference threshold, and the difference between the historical medication interval information and the current medication interval information is less than a preset second difference threshold, then the historical final blood glucose value information is determined to be the predicted blood glucose value information.
[0070] Specifically, if the difference between the historical initial blood glucose value information and the current blood glucose value information is less than a preset difference threshold, the difference between the historical predicted sugar value information and the estimated sugar value information is less than the difference threshold, and the difference between the historical medication interval information and the current medication interval information is less than a preset second difference threshold, the terminal device can determine the historical dining situation that is most similar to the current dining situation, so the terminal device can determine the historical final blood glucose value information as the predicted blood glucose value information.
[0071] In S400 , health assessment result information is generated based on the predicted blood glucose level information and the preset warning blood glucose level information.
[0072] Specifically, after the terminal device generates the predicted blood glucose value information, the terminal device can accurately generate health assessment result information based on the predicted blood glucose value information and the preset warning blood glucose value information, wherein the health assessment result information includes safety result information or danger result information; the safety result information is used to describe the target user's physical health condition after the meal as safe; the danger result information is used to describe the target user's physical health condition after the meal as dangerous.
[0073] In some possible implementations, in order to intuitively judge the target user's health status after dining, please refer to Figure 4 Step S400 includes but is not limited to the following steps:
[0074] In S410 , the predicted blood glucose level information is compared with the preset warning blood glucose level information.
[0075] Specifically, the terminal device can compare the predicted blood glucose value information with the preset warning blood glucose value information.
[0076] In S420, if the predicted blood glucose level information is lower than the warning blood glucose level information, safe result information is generated; otherwise, dangerous result information is generated.
[0077] Specifically, if the predicted blood glucose value information is less than the warning blood glucose value information, the terminal device can generate a safe result information; if the predicted blood glucose value information is greater than or equal to the warning blood glucose value information, the terminal device can generate a dangerous result information.
[0078] Accordingly, see Figure 5After step S400, the method further includes but is not limited to the following steps:
[0079] In S500 , after a specified waiting time, the current blood glucose level information of the target user is obtained again.
[0080] Specifically, the terminal device can obtain the current blood glucose value information of the target user again after a specified waiting time.
[0081] In S510, the current blood sugar level information and the warning blood sugar level information are compared.
[0082] Specifically, after the terminal device obtains the current blood glucose level information again, the terminal device may compare the current blood glucose level information with the warning blood glucose level information.
[0083] In S520, if the current blood glucose level is greater than or equal to the warning blood glucose level, a danger alarm message is sent to a designated terminal.
[0084] Specifically, if the current blood sugar value information is greater than or equal to the warning blood sugar value information, it indicates that the target user is in a state of high blood sugar, so the terminal device can send a danger alarm message to the designated terminal, where the designated terminal can be the terminal device corresponding to the doctor, nurse or family member.
[0085] In some possible implementations, in order to facilitate timely rescue of target users with high blood sugar, please refer to Figure 6 After step S520, the method further includes but is not limited to the following steps:
[0086] In S600, a plurality of continuous current blood glucose level information is obtained according to a preset sampling time period.
[0087] Specifically, the terminal device can obtain multiple consecutive current blood glucose value information within a preset sampling time period.
[0088] In S610 , blood glucose peak information is determined based on a plurality of current blood glucose level information.
[0089] Specifically, after the terminal device obtains multiple consecutive current blood glucose level information, the terminal device can quickly determine the blood glucose peak information based on the multiple current blood glucose level information, wherein the blood glucose peak information is used to describe the maximum value among the multiple current blood glucose level information.
[0090] In S620, blood glucose reduction rate information is generated based on the multiple pieces of current blood glucose level information and sampling time periods.
[0091] Specifically, after the terminal device determines the blood glucose peak information, the terminal device can subtract the difference between the first current blood glucose value information in the sampling time period and the last current blood glucose value in the sampling time period, and then divide the difference by the quotient of the sampling time period to generate blood glucose reduction rate information.
[0092] In S630, the blood glucose peak information and the blood glucose reduction rate information are sent to a designated terminal.
[0093] Specifically, after the terminal device determines the blood sugar peak information and blood sugar reduction rate information, the terminal device can send the blood sugar peak information and blood sugar reduction rate information to the designated terminal, so that doctors, nurses or family members can efficiently and accurately understand the blood sugar changes of the target user, greatly shortening the rescue time.
[0094] The implementation principle of the intelligent disease course management method for diabetic patients in the embodiment of the present application is as follows: the terminal device can first obtain the actual image information of the target plate and the current blood sugar value information of the target user at the same time, and then quickly generate estimated sugar value information based on the actual image information and the image detection algorithm. Then, based on the historical database, according to the current blood sugar value information and the estimated blood sugar value information, the predicted blood sugar value information is effectively generated. Finally, according to the predicted blood sugar value information and the warning blood sugar value information, the health assessment result information is accurately generated, thereby achieving a more accurate assessment of the patient's health condition after the meal and effectively improving reliability.
[0095] It should be noted that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0096] The embodiment of the present application also provides an intelligent disease course management system based on diabetic patients. For the sake of convenience, only the parts related to the present application are shown, such as Figure 7 As shown, the system 70 includes:
[0097] The real-shot image information acquisition module 71 is used to acquire the real-shot image information of the target plate and the current blood glucose level information of the target user;
[0098] Estimated sugar value information generation module 72: used to generate estimated sugar value information based on the real-shot image information and the image detection algorithm;
[0099] Predicted blood glucose level information generating module 73: used to generate predicted blood glucose level information based on the preset historical database, the current blood glucose level information and the estimated sugar level information;
[0100] The health assessment result information generating module 74 is used to generate health assessment result information based on the predicted blood glucose level information and the preset warning blood glucose level information.
[0101] Optionally, the estimated sugar content value information generating module 72 includes:
[0102] The receiving area information generation submodule is used to generate multiple receiving area information, multiple food area information, and food type information corresponding to each food area information of the target plate based on the real-shot image information and the image detection algorithm, wherein each receiving area information and each food area information have a one-to-one correspondence;
[0103] The region contour line information determination submodule is used to determine the receiving region contour line information corresponding to each receiving region information and the food region contour line information corresponding to each food region information based on a preset contour extraction algorithm;
[0104] The area information generating submodule is used for generating food area information based on the food area outline information and the area information of the receiving area based on the receiving area outline information for each set of receiving area information and food area information;
[0105] Phase difference ratio information generation submodule: used to generate phase difference ratio information based on the area information of the storage area and the area information of the food area;
[0106] The receiving area volume information acquisition submodule is used to obtain the receiving area volume information corresponding to the receiving area information;
[0107] Food area volume information generation submodule: used to generate food area volume information based on the phase difference ratio information and the volume information of the containing area;
[0108] Food average density information acquisition submodule: used to obtain food average density information and food average sugar content information corresponding to food type information;
[0109] Estimated sugar value information generation submodule: used to generate estimated sugar value information based on food area volume information, food average density information and food average sugar content information.
[0110] Optionally, the system 70 further includes:
[0111] Current medication interval information acquisition module: used to obtain the current medication interval information of the target user;
[0112] Accordingly, the historical database stores multiple sets of user blood glucose data sets, each set of user blood glucose data sets including historical initial blood glucose value information, historical estimated blood glucose value information, historical final blood glucose value information, and historical medication interval information. The above-mentioned predicted blood glucose value information generation module 73 includes:
[0113] The historical initial blood glucose value information judgment submodule is used to judge, for each group of user blood glucose data set information in the historical database, whether the difference between the historical initial blood glucose value information and the current blood glucose value information is less than a preset first difference threshold, whether the difference between the historical estimated blood glucose value information and the estimated blood glucose value information is less than the first difference threshold, and whether the difference between the historical medication interval time information and the current medication interval time information is less than a preset second difference threshold;
[0114] Predicted blood glucose value information determination submodule: used to determine that the historical final blood glucose value information is the predicted blood glucose value information if the difference between the historical initial blood glucose value information and the current blood glucose value information is less than a preset difference threshold, and the difference between the historical predicted sugar value information and the estimated sugar value information is less than the difference threshold, and the difference between the historical medication interval time information and the current medication interval time information is less than a preset second difference threshold.
[0115] Optionally, the health assessment result information includes safety result information or danger result information. The health assessment result information generating module 74 includes:
[0116] Predicted blood glucose value information comparison submodule: used to compare the predicted blood glucose value information with the preset warning blood glucose value information;
[0117] Safety result information generation submodule: used to generate safety result information if the predicted blood glucose value information is lower than the warning blood glucose value information, otherwise generate danger result information;
[0118] Accordingly, the system 70 further includes:
[0119] Current blood glucose level information re-acquisition module: used to re-acquire the current blood glucose level information of the target user after a specified waiting time;
[0120] Current blood glucose value information comparison module: used to compare current blood glucose value information and warning blood glucose value information;
[0121] Danger alarm information sending module: used to send danger alarm information to the designated terminal if the current blood sugar value information is greater than or equal to the warning blood sugar value information.
[0122] Optionally, the system 70 further includes:
[0123] Current blood glucose level information acquisition module: used to obtain multiple continuous current blood glucose level information according to a preset sampling time period;
[0124] A blood glucose peak information determination module is configured to determine blood glucose peak information based on a plurality of current blood glucose value information, wherein the blood glucose peak information is used to describe the maximum value among the plurality of current blood glucose value information;
[0125] Blood glucose reduction rate information generation module: used to generate blood glucose reduction rate information based on multiple current blood glucose value information and sampling time periods;
[0126] Blood glucose peak information sending module: used to send blood glucose peak information and blood glucose reduction rate information to the designated terminal.
[0127] It should be noted that the information interaction, execution process and other contents between the above modules are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.
[0128] The present application also provides a terminal device, such as Figure 8 As shown, the terminal device 80 of this embodiment includes: a processor 81, a memory 82, and a computer program 83 stored in the memory 82 and executable on the processor 81. When the processor 81 executes the computer program 83, the steps in the above-mentioned intelligent disease course management method embodiment are implemented, such as Figure 1 Steps S100 to S400 shown; or, when the processor 81 executes the computer program 83, the functions of each module in the above device are realized, for example Figure 7 The functions of modules 71 to 74 are shown.
[0129] The terminal device 80 can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal device 80 includes but is not limited to a processor 81 and a memory 82. It will be understood by those skilled in the art that Figure 8 It is merely an example of the terminal device 80 and does not constitute a limitation of the terminal device 80. The terminal device 80 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal device 80 may also include input and output devices, network access devices, buses, etc.
[0130] Among them, the processor 81 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.
[0131] The memory 82 can be an internal storage unit of the terminal device 80, such as a hard disk or memory of the terminal device 80, or the memory 82 can be an external storage device of the terminal device 80, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the terminal device 80; further, the memory 82 can also include both an internal storage unit of the terminal device 80 and an external storage device, and the memory 82 can also store the computer program 83 and other programs and data required by the terminal device 80, and the memory 82 can also be used to temporarily store data that has been output or is to be output.
[0132] One embodiment of the present application further provides a computer-readable storage medium, which stores a computer program, which, when executed by a processor, can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form; the computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium.
[0133] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the methods, principles, and structures of the present application should be included in the scope of protection of the present application.
Claims
1. An intelligent disease course management method for diabetic patients, characterized in that: The method comprises: Obtaining real-shot image information of the target meal plate and the current blood sugar level information of the target user; generating estimated sugar content information based on the real-shot image information and the image detection algorithm; Generate predicted blood sugar level information based on the current blood sugar level information and the estimated blood sugar level information based on a preset historical database; Health assessment result information is generated based on the predicted blood sugar level information and the preset warning blood sugar level information.
2. The method according to claim 1, characterized in that The generating of estimated sugar content information based on the real-shot image information and the image detection algorithm includes: Generate, based on the real-shot image information and the image detection algorithm, a plurality of receiving area information, a plurality of food area information, and food type information corresponding to each of the food area information of the target plate, wherein each of the receiving area information and each of the food area information has a one-to-one correspondence; Determining, based on a preset contour extraction algorithm, the receiving area contour line information corresponding to each of the receiving area information and the food area contour line information corresponding to each of the food area information; For each set of the receiving area information and the food area information: generating food area information according to the food area outline information, and generating receiving area area information according to the receiving area outline information; generating phase difference ratio information according to the area information of the receiving area and the area information of the food area; Obtaining volume information of a storage area corresponding to the storage area information; generating food area volume information according to the phase difference ratio information and the containing area volume information; Obtaining food average density information and food average sugar content information corresponding to the food type information; Estimated sugar value information is generated based on the food region volume information, the food average density information, and the food average sugar content information.
3. The method according to claim 1, characterized in that Before generating predicted blood glucose level information based on the current blood glucose level information and the estimated glucose level information based on the preset historical database, the method further includes: Obtaining the current medication interval information of the target user; Accordingly, the historical database stores multiple sets of user blood glucose data set information, each set of user blood glucose data set information including historical initial blood glucose value information, historical estimated blood glucose value information, historical final blood glucose value information, and historical medication interval information. The generated predicted blood glucose value information based on the preset historical database and the current blood glucose value information and the estimated blood glucose value information includes: For each group of user blood glucose data set information in the historical database: determining whether the difference between the historical initial blood glucose value information and the current blood glucose value information is less than a preset first difference threshold, whether the difference between the historical estimated blood glucose value information and the estimated blood glucose value information is less than the first difference threshold, and whether the difference between the historical medication interval information and the current medication interval information is less than a preset second difference threshold; If the difference between the historical initial blood glucose value information and the current blood glucose value information is less than a preset difference threshold, and the difference between the historical predicted sugar value information and the estimated sugar value information is less than the difference threshold, and the difference between the historical medication interval information and the current medication interval information is less than a preset second difference threshold, then the historical final blood glucose value information is determined to be predicted blood glucose value information.
4. The method according to claim 1, wherein The health assessment result information includes safety result information or danger result information. The health assessment result information is generated based on the predicted blood glucose level information and the preset warning blood glucose level information, including: comparing the predicted blood glucose level information with the preset warning blood glucose level information; If the predicted blood glucose level is lower than the warning blood glucose level, the safe result is generated; otherwise, the dangerous result is generated. Accordingly, if risk result information is generated, after generating health assessment result information based on the predicted blood glucose level information and the preset warning blood glucose level information, the method further includes: After a specified waiting time, obtaining the current blood glucose level information of the target user again; comparing the current blood glucose level information with the warning blood glucose level information; If the current blood glucose level is greater than or equal to the warning blood glucose level, a danger alarm message is sent to a designated terminal.
5. The method according to claim 4, characterized in that After sending danger alarm information to a designated terminal if the current blood glucose level information is greater than or equal to the warning blood glucose level information, the method further includes: Acquiring a plurality of continuous pieces of current blood glucose level information according to a preset sampling time period; determining blood glucose peak information based on the multiple pieces of current blood glucose level information, wherein the blood glucose peak information is used to describe the maximum value among the multiple pieces of current blood glucose level information; generating blood glucose reduction rate information according to the plurality of current blood glucose level information and sampling time periods; The blood sugar peak information and blood sugar drop rate information are sent to a designated terminal.
6. An intelligent disease management system for diabetic patients, characterized in that: The system comprises: Real-time image information acquisition module: used to obtain real-time image information of the target plate and the current blood sugar value information of the target user; Estimated sugar value information generation module: used to generate estimated sugar value information based on the real-shot image information and image detection algorithm; A predicted blood sugar level information generating module is configured to generate predicted blood sugar level information based on a preset historical database and the current blood sugar level information and the estimated sugar level information; Health assessment result information generation module: used to generate health assessment result information based on the predicted blood glucose value information and the preset warning blood glucose value information.
7. The system according to claim 6, characterized in that The system further comprises: Current blood glucose level information acquisition module: used to acquire a plurality of continuous current blood glucose level information according to a preset sampling time period; A blood glucose peak information determining module is configured to determine blood glucose peak information based on the plurality of current blood glucose level information, wherein the blood glucose peak information is used to describe the maximum value among the plurality of current blood glucose level information; A blood glucose reduction rate information generating module is configured to generate blood glucose reduction rate information based on the current blood glucose value information and sampling time periods; Blood glucose peak information sending module: used to send the blood glucose peak information and blood glucose reduction rate information to the designated terminal.
8. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.
9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.