Glucose monitoring method, and device and computer-readable storage medium

Abstract

A glucose monitoring method, comprising: determining first information and second information, wherein the first information is a glucose monitoring result corresponding to a first time period, the second information is a target behavior type associated with the first time period, the target behavior type is one of user behavior types, and the user behavior types comprise one or more of an eating behavior type, an exercise behavior type or a sleep behavior type; and on the basis of the first information and the second information, generating first prompt information, wherein the first prompt information is used for prompting the glucose monitoring result associated with the target behavior type. The method can help a user achieve more precise and more effective glucose management.

Description

Methods, devices and computer-readable storage media for monitoring blood glucose

[0001] This application claims priority to Chinese Patent Application No. 202510315895.6, filed on March 17, 2025, entitled "Method, Device and Computer-Readable Storage Medium for Monitoring Blood Glucose", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of terminal technology, and in particular to methods, devices and computer-readable storage media for monitoring blood glucose. Background Technology

[0003] Long-term hyperglycemia can have many negative effects on the human body, such as inducing diabetes and cardiovascular diseases. Given the potential dangers of hyperglycemia, daily prevention of hyperglycemia is particularly important. However, current blood glucose monitoring technology can only provide users with recent blood glucose trends, such as the overall rise and fall of blood glucose and the approximate magnitude of the changes. Summary of the Invention

[0004] Therefore, this application provides a method, device, and computer-readable storage medium for monitoring blood glucose, which can help users achieve more precise and effective blood glucose management.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] Firstly, a method for monitoring blood glucose is provided, the method comprising:

[0007] First information and second information are determined. The first information is the blood glucose monitoring result corresponding to the first time period, and the second information is the target behavior type associated with the first time period. The target behavior type is one of the user behavior types, including one or more of the following: eating behavior type, exercise behavior type, or sleep behavior type. A first prompt is generated based on the first information and the second information. The first prompt is used to prompt the blood glucose monitoring result associated with the target behavior type.

[0008] The above methods can be executed by a terminal device (i.e., an example of a device), by a module applied to the terminal device (e.g., a processor, chip, or chip system), or by a logic module or software that can implement all or part of the functions of the terminal device.

[0009] In the above method, the terminal device identifies two types of key information: first information and second information. Based on these two types of information, it generates a first prompt message, which reflects the dynamic correlation between the target behavior type and the blood glucose monitoring results. This method has the following advantages: Firstly, by analyzing the correlation between the target behavior type and the blood glucose monitoring results, the terminal device can generate more detailed and personalized health guidance plans for users, enabling them to manage their blood glucose more precisely and effectively. Secondly, the first prompt message helps users understand the direct impact of their behavior on their blood glucose levels. For example, when blood glucose rises or fluctuates abnormally, users can quickly understand the cause based on the first prompt message. The specific behavioral type of the change allows users to adjust their behavior in a timely manner and take more scientific health management measures to achieve precise control of blood sugar levels. For example, when a user finds that the previous lunch (an example of the user's behavior type) is the main cause of elevated blood sugar, the user can adjust their diet at the next meal based on the first prompt (such as a reminder that blood sugar rose after the previous lunch), thereby effectively avoiding a sustained rise in blood sugar. It can be seen that by analyzing the target behavior type and blood sugar monitoring results, the terminal device generates targeted first prompts, which not only improves the personalization and precision of users' health management, but also promotes the user's initiative and effectiveness in self-health management.

[0010] In one possible implementation, determining the first information and the second information includes: acquiring first data, which is physiological data corresponding to a first time period; acquiring second data, which is user behavior data associated with the first time period, and the user behavior data is used for the target behavior type; determining the first information based on the first data; and determining the second information based on the second data.

[0011] In some application scenarios, the terminal device determines the first information (or the second information) by first acquiring the first data and the second data corresponding to this information. The first data can be physiological data, such as photoplethysmography (PPG) data, temperature data, continuous glucose monitoring (CGM) data, etc., which can be used to reflect the user's blood glucose changes. The second data is the target user behavior data associated with the first time period, such as acceleration data, which can be used to determine the target behavior type. By acquiring and analyzing the first data and the second data, the terminal device can provide the user with blood glucose monitoring results for the target behavior type.

[0012] In one possible implementation, acquiring the first data includes acquiring the first data via at least one of the following devices: an optical sensor, a temperature sensor, or a continuous glucose monitoring (CGM) system.

[0013] In diverse application scenarios, on the one hand, terminal devices can non-invasively acquire users' physiological data (i.e., an example of primary data) through sensors such as PPG and temperature sensors. This process does not require piercing the skin, greatly reducing the user's physical burden and discomfort, and providing a painless and efficient blood glucose monitoring experience. On the other hand, terminal devices can also accurately acquire blood glucose data (i.e., an example of physiological data) through CGM systems, and based on this, provide users with more refined blood glucose monitoring results and personalized blood glucose management strategies, thereby helping users achieve more scientific and effective blood glucose management. In addition, terminal devices can also simultaneously utilize optical sensors such as PPG and temperature sensors... The use of temperature sensors and CGM systems to acquire the aforementioned physiological data offers the following advantages: 1) When multiple data types are available, the terminal device can integrate these data to generate more accurate blood glucose monitoring results; 2) These different data types play complementary roles in blood glucose monitoring. For example, in certain scenarios, when one type of data (such as temperature data) cannot be obtained for some reason, the terminal device can still rely on another type of data (such as PPG data) to generate blood glucose monitoring results. This flexible data application strategy effectively avoids the problem of blood glucose monitoring interruption caused by the lack of a single data source, ensuring that users can obtain reliable blood glucose monitoring information under any circumstances.

[0014] In one possible implementation, determining the second information based on the second data includes: performing behavior recognition on the second data through a user behavior model to obtain a user behavior recognition result, wherein the user behavior model is one or more of a dining behavior model, an exercise behavior model, or a sleep behavior model, wherein the dining behavior model is used to identify the type of dining behavior based on the user behavior data, the exercise behavior model is used to identify the type of exercise behavior based on the user behavior data, and the sleep behavior model is used to identify the type of sleep behavior based on the user behavior data; and determining the second information based on the user behavior recognition result.

[0015] In this embodiment, since the user behavior model can output high-precision behavior recognition results, the terminal device can determine more accurate second information based on the user behavior recognition results, so as to provide accurate and effective basis for subsequent user behavior analysis, blood glucose monitoring result generation and other processing processes.

[0016] In one possible implementation, when the target behavior type is a meal behavior type, the first prompt message is used to indicate the blood glucose monitoring result associated with the meal behavior type; the meal behavior type includes at least one of the following: breakfast, lunch, or dinner.

[0017] In some scenarios, terminal devices can generate initial prompts containing specific meal behavior types (such as breakfast), allowing blood glucose monitoring results to be refined to the level of a user's specific lifestyle behavior. This not only makes it easier for users to intuitively understand the direct impact of meal behavior types on blood glucose levels, but also provides users with accurate and efficient guidelines for adjusting meal behavior types when abnormal fluctuations in blood glucose are caused by specific meal behavior types, making users' blood glucose management strategies more targeted and effective.

[0018] In one possible implementation, when the target behavior type is an exercise behavior type, the first prompt information is used to indicate the blood glucose monitoring results associated with the exercise behavior type; the exercise behavior type includes at least one of the following: aerobic exercise, anaerobic exercise, flexibility exercise, balance exercise, recreational exercise, or competitive exercise.

[0019] In some scenarios, terminal devices can generate initial prompts that include specific exercise behavior types (such as aerobic exercise), allowing blood glucose monitoring results to be refined to the level of specific lifestyle behaviors of users. This not only makes it easier for users to intuitively understand the direct impact of different exercise behavior types on blood glucose levels, but also provides users with accurate and efficient guidelines for adjusting exercise behavior types when blood glucose fluctuates abnormally due to specific exercise behavior types, making users' blood glucose management strategies more targeted and effective.

[0020] In one possible implementation, when the target behavior type is a sleep behavior type, the first cue message is used to indicate the blood glucose monitoring results associated with the sleep behavior type; the sleep behavior type includes at least one of the following: before sleep, sleep onset, light sleep, deep sleep, fast sleep, REM sleep, or after sleep.

[0021] Terminal devices can generate initial prompts that include specific sleep behavior types (such as before bedtime), allowing blood glucose monitoring results to be refined to the level of a user's specific lifestyle. This not only makes it easier for users to intuitively understand the direct impact of different sleep behavior types on blood glucose levels, but also provides users with accurate and efficient guidelines for adjusting sleep behavior types when blood glucose fluctuates abnormally due to specific sleep behavior types, making users' blood glucose management strategies more targeted and effective.

[0022] In one possible implementation, the first time period is one or more of the following: a time period before the start of the target behavior type, a time period after the end of the target behavior type, or the entire time period during the duration of the target behavior type or a portion of the duration of the target behavior type.

[0023] In some application scenarios, blood glucose monitoring can be performed before (or after), or during, a target behavior pattern. This allows for obtaining blood glucose monitoring results associated with the start (or end) or duration of the target behavior pattern. Specifically, performing blood glucose monitoring before the target behavior pattern (i.e., obtaining blood glucose monitoring results associated with the target behavior pattern before it occurs) helps users understand their blood glucose status in advance, thereby preventing hypoglycemia or hyperglycemia during or after the target behavior pattern. For example, if a user's blood glucose was found to be high before their last meal, they can adjust their diet accordingly at the next meal to avoid consuming high levels of glucose. Excessive consumption of high-sugar foods can lead to excessively high blood sugar levels after a meal. Furthermore, monitoring blood sugar during sleep helps users understand their blood sugar fluctuations and avoid abnormal changes (such as abnormally low blood sugar) during sleep. Additionally, monitoring blood sugar after a target behavior occurs (i.e., obtaining blood sugar monitoring results associated with the target user's behavior) can assess the impact of the previous target behavior on blood sugar. For example, monitoring blood sugar two hours after a meal helps users understand the impact of their current meal behavior on their blood sugar; monitoring blood sugar after exercise can assess the effectiveness of the exercise behavior in controlling blood sugar.

[0024] In one possible implementation, the method further includes: displaying a first interface, the first interface including: a first prompt message and a first control; receiving a first operation, the first operation being used to trigger the first control; and in response to the first operation, displaying a second interface, the second interface including third information and fourth information, the third information including at least one of user behavior type, the number of times the user behavior type occurs, or the time when the user behavior type occurs, the fourth information including blood glucose monitoring results associated with the user behavior type, and the preset time period including a first time period.

[0025] The first control is used to view the details of the first prompt information; the third information is used to indicate the types of user behavior that have been monitored within the preset time period; and the fourth information is used to indicate the blood glucose monitoring results corresponding to the types of user behavior that have been monitored within the preset time period.

[0026] In some application scenarios, users may need to view more detailed blood glucose information corresponding to user behavior types within a preset time period (e.g., within 24 hours of the current day). Therefore, the terminal device can display the initial prompt information on the first interface while providing a first control for displaying blood glucose details. This allows users to easily access more detailed information about the blood glucose monitoring results associated with their behavior types by triggering the first control, thereby improving user experience and blood glucose management efficiency. For example, users can trigger the first control to display a second interface on the terminal device. This second interface can show users details such as the type of user behavior and the frequency of that behavior, enabling them to clearly understand the impact of their behavior types on blood glucose levels. This, in turn, encourages users to flexibly adjust their lifestyle habits according to actual conditions to ensure that their blood glucose remains stable within a healthy range.

[0027] In one possible implementation, when the user behavior type is dining behavior, the second interface also includes a second control for viewing historical dining blood glucose levels. The method further includes: receiving a second operation to trigger the second control; and responding to the second operation by displaying a third interface, which includes a dining blood glucose risk curve. The dining blood glucose risk curve describes the trend of dining blood glucose risk over time in a second time period, which occurs before the first time period. The dining blood glucose risk is one of the following: the number of times postprandial hyperglycemia occurs, the proportion of postprandial hyperglycemia, or the average probability value of postprandial hyperglycemia.

[0028] In some application scenarios, users can also trigger a second control to display a third interface on the terminal device. This third interface can show users information such as the blood glucose risk curve during a second time period (i.e., a certain historical time period), so that users can understand the changes in blood glucose risk during historical meals. This design not only makes it easier for users to comprehensively review and analyze their own blood glucose status, but also helps users adjust their blood glucose control strategies to ensure that blood glucose levels are maintained within a healthy range, thereby achieving more refined blood glucose management.

[0029] In one possible implementation, the third interface also includes a meal history blood glucose report and / or meal guidance information. The meal history blood glucose report includes the user's eating habits and the pattern of changes in meal blood glucose risk during the second time period. The meal guidance information includes at least one of the following: the order of eating, the type of food, or dietary recommendations.

[0030] In some cases, terminal devices can intuitively display historical blood glucose reports through a third-party interface, which helps users clearly understand their blood glucose response at different times and with different eating behaviors, thereby increasing users' awareness of the importance of blood glucose management. In addition, displaying meal guidance information through a third-party interface can help users optimize their subsequent eating habits, ensure that blood glucose remains stable at a healthy level, and achieve more refined blood glucose management.

[0031] In one possible implementation, when the user behavior type is exercise, the second interface also includes a second control for viewing historical exercise blood glucose levels. The method further includes: receiving a second operation to trigger the second control; and responding to the second operation by displaying a third interface, which includes an exercise blood glucose risk curve. The exercise blood glucose risk curve describes the trend of exercise blood glucose risk over time in a second time period, which occurs before the first time period. The exercise blood glucose risk is one of the following: the number of times the change in blood glucose before and after exercise exceeds a first threshold, the percentage of the change in blood glucose before and after exercise exceeding the first threshold, or the average probability value of the change in blood glucose before and after exercise exceeding the first threshold.

[0032] In some application scenarios, users can also trigger a second control to display a third interface on the terminal device. This third interface can show users information such as the exercise blood glucose risk curve within a second time period (i.e., a certain historical time period), so that users can understand the changes in historical exercise blood glucose risk. This design not only makes it easier for users to comprehensively review and analyze their own blood glucose status, but also helps users adjust their blood glucose control strategies to ensure that blood glucose levels are maintained within a healthy range, thereby achieving more refined blood glucose management.

[0033] In one possible implementation, the third interface also includes exercise history blood glucose reports and / or exercise guidance information. The exercise history blood glucose reports include the user's exercise habits and the pattern of changes in exercise blood glucose risk during the second time period. The exercise guidance information includes at least one of the following: single exercise volume, exercise frequency, or exercise type.

[0034] In some cases, terminal devices can intuitively display exercise history blood glucose reports through a third-party interface, which helps users clearly understand their blood glucose response at different times and under different exercise behaviors, thereby increasing users' attention to blood glucose management. In addition, displaying exercise guidance information through a third-party interface can help users optimize their current exercise habits, ensure that blood glucose is stable at a healthy level, and achieve more refined blood glucose management.

[0035] In one possible implementation, when the user behavior type is sleep behavior, the second interface also includes a second control for viewing historical sleep blood glucose levels. The method further includes: receiving a second operation to trigger the second control; and responding to the second operation by displaying a third interface, which includes a sleep blood glucose risk curve. The sleep blood glucose risk curve describes the trend of sleep blood glucose risk over time in a second time period, which occurs before the first time period. The sleep blood glucose risk is one of the following: the number of times the sleep blood glucose change exceeds a second threshold, the percentage of sleep blood glucose changes exceeding the second threshold, or the average probability value of sleep blood glucose changes exceeding the second threshold.

[0036] In some application scenarios, users can also trigger a second control to display a third interface on the terminal device. This third interface displays information such as the sleep blood glucose risk curve within a second time period (i.e., a certain historical time period) to help users understand the changes in historical sleep blood glucose risk. This design not only makes it easier for users to comprehensively review and analyze their own blood glucose status, but also helps users adjust their blood glucose control strategies to ensure that blood glucose levels are maintained within a healthy range, thereby achieving more refined blood glucose management.

[0037] In one possible implementation, the third interface also includes a sleep history blood glucose report and / or sleep guidance information. The sleep history blood glucose report includes the user's sleep habits and the pattern of changes in sleep blood glucose risk during the second time period, and the sleep guidance information includes methods for adjusting sleep schedule and / or dietary adjustments.

[0038] The terminal device intuitively displays the sleep history blood glucose report through a third interface, which helps users clearly understand their blood glucose response at different times and under different sleep behaviors, thereby increasing users' awareness of the importance of blood glucose management. In addition, displaying sleep guidance information through the third interface can help users optimize their subsequent sleep habits and ensure that blood glucose remains stable at a healthy level, thereby achieving more refined blood glucose management.

[0039] In one possible implementation, the method further includes: receiving a third operation on the first interface and displaying a fourth interface, the fourth interface including fifth information and / or sixth information, the fifth information being used to reflect the overall situation of abnormal blood glucose changes within a preset period, the sixth information being used to reflect blood glucose monitoring results associated with user behavior types within the preset period, the preset period including a first time period, and the sixth information including at least one of the following: blood glucose monitoring results associated with eating behavior types, blood glucose monitoring results associated with exercise behavior types, or blood glucose monitoring results associated with sleep behavior types.

[0040] In some application scenarios, the terminal device receives a third operation on the first interface and displays a fourth interface. This fourth interface can not only present a comprehensive picture of abnormal blood glucose changes within a preset period, but also present blood glucose monitoring results associated with the user's behavior type, so that the user can intuitively and clearly grasp the blood glucose status within the entire preset period.

[0041] In one possible implementation, the method further includes: receiving a fourth operation on the fourth interface and displaying a fifth interface, the fifth interface including the total number of blood glucose monitoring and / or the total number of abnormal blood glucose changes.

[0042] In some application scenarios, the terminal device receives a fourth operation on the fourth interface and displays a fifth interface; the fifth interface displays the total number of blood glucose monitoring and / or the total number of abnormal blood glucose changes, so that users can quickly understand the blood glucose status throughout the preset period.

[0043] In one possible implementation, the method further includes: receiving a fifth operation on the fifth interface and displaying a sixth interface, the sixth interface including seventh information and / or eighth information, the seventh information describing the trend of total blood glucose risk over time in a second time period, the second time period occurring before the first time period, the total blood glucose risk being one of the following: the number of abnormal changes in total blood glucose, the proportion of abnormal changes in total blood glucose, or the average probability value of abnormal changes in total blood glucose, the eighth information including at least one of the following: a meal blood glucose risk curve, an exercise blood glucose risk curve, or a sleep blood glucose risk curve, the meal blood glucose risk curve describing the trend of sleep blood glucose risk over time in the second time period, the exercise blood glucose risk curve describing the trend of exercise blood glucose risk over time in the second time period, and the sleep blood glucose risk curve describing the trend of sleep blood glucose risk over time in the second time period.

[0044] In some application scenarios, terminal devices can intuitively display the seventh information in a graphical way (such as a curve graph) through the sixth interface, providing users with a global overview of blood glucose management in the second time period. At the same time, the sixth interface displays the eighth information, including meal blood glucose risk curves, exercise blood glucose risk curves, and sleep blood glucose risk curves. This allows users to not only further understand the specific situation of blood glucose management under different lifestyle behaviors, but also to formulate more scientific and reasonable blood glucose management strategies based on historical risk trends, thereby effectively reducing the risk of abnormal blood glucose and improving quality of life.

[0045] In one possible implementation, the sixth interface also includes general health guidance information.

[0046] In some application scenarios, terminal devices can display comprehensive health guidance information through a sixth interface to provide users with a full range of blood glucose management strategies to help them better manage their blood glucose levels.

[0047] In one possible implementation, the method further includes: receiving a sixth operation on the fourth interface to display a seventh interface, the seventh interface including behavior identification controls and / or detailed content of blood glucose monitoring results associated with user behavior types, the behavior identification controls being used to identify blood glucose monitoring information associated with user behavior types, including at least one of meal identification controls, exercise identification controls, or sleep identification controls, the meal identification controls being used to identify blood glucose monitoring information associated with meal behavior types, the exercise identification controls being used to identify blood glucose monitoring information associated with exercise behavior types, and the sleep identification controls being used to identify blood glucose monitoring information associated with sleep behavior types.

[0048] In some application scenarios, terminal devices can display blood glucose monitoring results for user behavior types through a seventh interface. By displaying behavior identification controls, such as those corresponding to eating, exercising, and sleeping behaviors, users can quickly view the information they need without frequently switching between multiple interfaces. This simplifies the operation process, improves information acquisition efficiency, and effectively reduces the energy consumption of the device.

[0049] In a second aspect, embodiments of this application provide an apparatus that may include a processor and a memory, the memory for storing a computer program, and the processor for calling and running the computer program from the memory, such that the apparatus performs the methods described in the first aspect and various possible implementations of the first aspect.

[0050] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to perform the methods described in the first aspect and various possible implementations of the first aspect.

[0051] Fourthly, embodiments of this application provide a computer program product, which includes: computer program code, which, when executed by a processor, causes the processor to perform the methods described in the first aspect and various possible implementations of the first aspect.

[0052] Fifthly, embodiments of this application provide a chip system including a processing circuit and a storage medium storing computer program instructions; when the computer program instructions are executed by the processing circuit, they implement the methods described in the first aspect and various possible implementations of the first aspect.

[0053] Optionally, the processing circuitry in the chip system described in the fifth aspect can be replaced by a processor, and the storage medium can be replaced by a memory. Optionally, the chip system may also include a communication interface for enabling communication between the chip system and a receiving device.

[0054] The beneficial effects of the technical solutions in the second to fifth aspects of this application can be the same as the beneficial effects of the technical solutions in the first aspect, and will not be repeated here. Attached Figure Description

[0055] Figures 1A and 1B are schematic diagrams of a blood glucose monitoring scenario provided in an embodiment of this application;

[0056] Figure 2 is a schematic diagram of the hardware architecture of a terminal device 100 provided in an embodiment of this application;

[0057] Figure 3 is a schematic diagram of the software architecture of a terminal device 100 provided in an embodiment of this application;

[0058] Figure 4 is a schematic diagram of another software architecture of a terminal device 100 provided in an embodiment of this application;

[0059] Figures 5A and 5B are schematic diagrams of the software architecture of another terminal device provided in the embodiments of this application;

[0060] Figure 6 is a flowchart illustrating a method for monitoring blood glucose provided in an embodiment of this application;

[0061] Figure 7 is a schematic flowchart of a blood glucose monitoring method 700 provided in an embodiment of this application;

[0062] Figure 8A is a structural schematic diagram of a watch 800 provided in an embodiment of this application;

[0063] Figure 8B is a distribution diagram of blood glucose data within 24 hours provided in an embodiment of this application;

[0064] Figures 8C to 8D are schematic diagrams of an application scenario provided by an embodiment of this application;

[0065] Figures 9A to 9J are schematic diagrams of another application scenario provided by the embodiments of this application;

[0066] Figures 10A to 10E are schematic diagrams of another application scenario provided by the embodiments of this application;

[0067] Figures 11A to 11E are schematic diagrams of another application scenario provided by the embodiments of this application;

[0068] Figures 12A to 12J are schematic diagrams of another application scenario provided by the embodiments of this application;

[0069] Figures 13A to 13E are schematic diagrams of another application scenario provided by the embodiments of this application;

[0070] Figure 14 is a schematic diagram of the structure of a device provided in an embodiment of this application. Detailed Implementation

[0071] In the description of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. In the description of this application, "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. "At least one" means one or more, and "more" means two or more. The terms "first" and "second," etc., in the specification and claims of this application are used to distinguish different objects or to distinguish different treatments of the same object, not to describe a specific order of objects. For example, "first device" and "second device," etc., are used to distinguish different terminal devices, not to describe a specific order of terminal devices. Those skilled in the art will understand that the words "first," "second," etc., do not limit the quantity or execution order, and that "first," "second," etc., do not necessarily imply difference.

[0072] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0073] In blood glucose management scenarios, while blood glucose monitoring devices (such as smartwatches) can provide users with real-time trends in blood glucose changes, they cannot provide specific factors causing blood glucose fluctuations, such as dietary habits and exercise. Taking the blood glucose monitoring scenario shown in Figure 1A as an example, a user can monitor their blood glucose level one hour after a meal using a smartwatch 100. For example, the display 101 of the watch 100 will prompt the user to remain still to ensure measurement accuracy, and after a period of time, the display 101 will show the blood glucose monitoring results (also known as blood glucose assessment results). If the blood glucose is high, the watch 100 will prompt the user to continue monitoring and seek medical attention if necessary. However, the blood glucose monitoring results provided by the watch 100 are only a prompt indicating the trend of blood glucose levels. Users cannot determine the specific cause of blood glucose fluctuations based solely on this prompt information, thus making it impossible to conduct precise and effective blood glucose management.

[0074] Therefore, this application proposes a method for monitoring blood glucose, which can help users achieve more precise and effective blood glucose management.

[0075] In this method for monitoring blood glucose, the terminal device (i.e., an example of the device) can generate a first prompt message by obtaining the target behavior type (such as breakfast) associated with a first time period (e.g., 8:00 to 9:00 in the morning) and the corresponding blood glucose monitoring result (e.g., elevated blood glucose) for the first time period, so as to prompt the user about the association between the target behavior type and the blood glucose monitoring result.

[0076] For example, as shown in Figure 1B, when the blood glucose health research function of the smartwatch 102 is turned on, it can monitor the dynamic changes in postprandial blood glucose. The user can see the first prompt information on the display screen 103 of the watch 102: a high blood glucose event was detected after your most recent meal. The user can click the "Meal Blood Glucose Details 104" button to open the display interface 105 of meal blood glucose details. This display interface 105 shows the two meal situations and provides feedback on the abnormal increase in blood glucose after lunch (i.e., an example of the target behavior type). This feedback information allows the user to understand the key factors that cause blood glucose fluctuations in a timely manner, and then adjust the amount, frequency and dietary structure of meals to ensure that blood glucose is maintained at a healthy level and prevent continuous rise. This process shows that by acquiring and analyzing the correspondence between user behavior type and blood glucose monitoring results, the terminal device can generate targeted first prompt information, which not only improves the personalization and precision of user health management, but also promotes the user's initiative and effectiveness in self-health management.

[0077] It should be noted that in the above methods, the "device" can refer to a terminal device, or it can refer to servers or chips, etc., and this application embodiment does not limit it in this regard; wherein, the terminal device can be a smartwatch, smart bracelet, smart ankle bracelet, computer watch, smart glasses, smart helmet, smart ring, etc. This application embodiment does not impose any restrictions on the specific type of terminal device.

[0078] In order to better understand the embodiments of this application, the following describes the hardware and software structure of the terminal device applicable to this application, taking the above-mentioned device as an example.

[0079] Figure 2 shows a schematic diagram of the hardware structure of a terminal device 100. The terminal device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) connector 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, a display screen 170, and a sensor module 180, etc.

[0080] The processor 110 may include one or more processing units, such as an application processor (AP), a modem processor, a graphics processing unit (GPU), a controller, a digital signal processor (DSP), a baseband processor, etc. These different processing units may be independent devices or integrated into one or more processors.

[0081] The processor 110 can generate operation control signals based on the instruction opcode and timing signals to control the instruction fetching and execution.

[0082] The processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 may be a cache memory. This memory can store instructions or data that the processor 110 has used or that are used frequently. If the processor 110 needs to use the instruction or data, it can directly retrieve it from this memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0083] In some embodiments, the processor 110 may include one or more interfaces. These interfaces may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc. The processor 110 can connect to modules such as wireless communication modules and displays through at least one of these interfaces.

[0084] It is understood that the interface connection relationships between the modules illustrated in the embodiments of this application are merely illustrative and do not constitute a structural limitation on the terminal device 100. In other embodiments of this application, the terminal device 100 may also adopt different interface connection methods or a combination of multiple interface connection methods as described in the above embodiments.

[0085] USB connector 130 is a USB standard compliant interface used to connect terminal device 100 and peripheral devices. Charging management module 140 receives charging input from a charger, which can be either a wireless or wired charger. Power management module 141 connects to battery 142, and charging management module 140 connects to processor 110. Power management module 141 receives input from battery 142 and / or charging management module 140 to power processor 110, internal memory 121, wireless communication module 160, display screen 170, and sensor module 180, etc. In some embodiments, power management module 141 and charging management module 140 may also be housed in the same device.

[0086] The wireless communication function of the terminal device 100 can be implemented through antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor and baseband processor, etc.

[0087] The mobile communication module 150 can provide solutions for wireless communication, including 2G / 3G / 4G / 5G, applied to the terminal device 100. The mobile communication module 150 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), etc. In some embodiments, at least some functional modules of the mobile communication module 150 may be housed in the same device as at least some modules of the processor 110.

[0088] The modem processor may include a modulator and a demodulator. The modulator modulates the low-frequency baseband signal to be transmitted into a mid-to-high frequency signal. The demodulator demodulates the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After processing by the baseband processor, the low-frequency baseband signal is transmitted to the application processor. The application processor outputs a sound signal through an audio device (e.g., a speaker) or displays a first prompt message on the display screen 170. In some embodiments, the modem processor may be a separate device. In other embodiments, the modem processor may be independent of the processor 110 and may be housed in the same device as the mobile communication module 150 or other functional modules.

[0089] The wireless communication module 160 can provide wireless communication solutions for use on the terminal device 100, including wireless local area networks (WLAN) (such as WiFi hotspots), Bluetooth (BT), and near field communication (NFC) technologies.

[0090] In some embodiments, antenna 1 of terminal device 100 is coupled to mobile communication module 150, and antenna 2 is coupled to wireless communication module 160, enabling terminal device 100 to communicate with networks and other terminal devices via wireless communication technology. This wireless communication technology may include Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), etc.

[0091] Terminal device 100 can display information via GPU, display screen 170, etc. Processor 110 may include one or more GPUs, which execute program instructions to generate or change display information.

[0092] The external storage interface 120 can be used to connect an external storage card, such as a Micro SD card, to expand the storage capacity of the terminal device 100. The external storage card communicates with the processor 110 through the external storage interface 120 to perform data storage functions. For example, it can store first data and second data in the external storage card, or transfer first data and second data from the terminal device 100 to the external storage card.

[0093] Internal memory 121 can be used to store computer executable program code, including instructions. Internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system, at least one application required for a function (e.g., a blood glucose monitoring application), etc. The data storage area may store data created during the use of terminal device 100 (e.g., PPG data, etc.). Furthermore, internal memory 121 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc. Processor 110 executes various functional methods or data processing of terminal device 100 by running instructions stored in internal memory 121 and / or instructions stored in memory disposed in the processor.

[0094] The display screen 170 can be used to display information such as time, blood glucose monitoring results, and health tips. In this application, the display screen 170 can be a touch screen or a non-touch screen. The display screen 170 can be manufactured using materials such as organic light-emitting diodes (OLEDs).

[0095] The sensor module 180 may include a gyroscope sensor, an accelerometer sensor, and a PPG sensor, etc.

[0096] The gyroscope sensor can be used to determine the motion posture of the terminal device 100; the terminal device 100 can determine whether the user is in motion based on the posture data (such as the angular velocity of the terminal device 100 around the three axes (i.e., the x, y and z axes)) acquired by the gyroscope sensor.

[0097] An accelerometer can be used to detect the magnitude of acceleration of a terminal device 100 in various directions (generally three axes). When the terminal device 100 is stationary, it can detect the magnitude and direction of gravity, and can also be used to identify the posture of the terminal device 100. It can be applied to applications such as landscape / portrait screen switching and pedometers. The terminal device 100 can also determine whether the user is in motion based on the acceleration data obtained by the accelerometer.

[0098] A PPG sensor is a biosensor that uses optical principles to monitor changes in blood vessel volume. It can include multiple light-emitting diodes (LEDs) and a photodetector (PD). It can be used to monitor physiological parameters such as heart rate, blood oxygen saturation, and blood glucose.

[0099] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the terminal device 100. In other embodiments of this application, the terminal device 100 may also include more or fewer components than those in FIG. 2, or combine some components, or split some components, or have different component arrangements. The components in FIG. 2 may be implemented in hardware, software, or a combination of software and hardware.

[0100] The software system of the aforementioned terminal device 100 can adopt a layered architecture or a service architecture, etc. This embodiment of the invention uses the layered architecture of the Android operating system as an example to exemplify the software architecture of the terminal device 100. It should be understood that the technical solutions provided in this application can also be applied to other types of operating systems such as HarmonyOS, Apple OS, and Windows OS.

[0101] Figure 3 shows a schematic diagram of the software architecture of the terminal device 100 provided in an embodiment of this application.

[0102] As shown in Figure 3, the layered architecture of the terminal device 100 divides the software into several layers, each with a clear role and division of labor. Layers communicate with each other through software interfaces. In some embodiments, the software components, from top to bottom, are the application (APP) layer, the application framework (FW) layer, the Android runtime (ART) and native C / C++ libraries, the hardware abstraction layer (HAL), and the kernel layer.

[0103] The application layer, also known as the application layer, can include a series of application packages. For example, an application package may include an X application (such as a blood glucose monitoring application), a calling application, a navigation application, a Bluetooth application, etc. When the above application packages are run, they can access the various service modules provided by the application framework layer through the application programming interface (API) and execute the corresponding intelligent business.

[0104] The application framework layer (FWK) provides application programming interfaces (APIs) and programming frameworks for applications in the application layer. The application framework layer can include some predefined functions.

[0105] As shown in Figure 3, the application framework layer can include a window manager, content providers, a view system, a resource manager, a notification manager, an activity manager, and an input manager. The window manager manages all windows in the system; the content provider stores and retrieves data (such as PPG data, acceleration data, etc.) and makes this data accessible to the application; the view system includes visual controls, such as controls for displaying text and controls for displaying graphics. The display interface can consist of one or more views. For example, a display interface including information notifications can include views for displaying text and views for displaying graphics; the resource manager provides various resources to the application, such as PPG data and acceleration data; and the notification manager manages the information prompts in the status bar at the top of some terminals (such as smartwatches).

[0106] The Android runtime consists of the core libraries and the Android runtime itself. The Android runtime is responsible for converting source code into machine code. The Android runtime primarily employs ahead-of-time (AOT) compilation and just-in-time (JIT) compilation techniques.

[0107] The core library primarily provides basic Java class library functionalities, such as libraries for fundamental data structures, mathematics, I / O, tools, databases, and networking. It also provides APIs for users to develop Android applications.

[0108] Native C / C++ libraries can include multiple functional modules. Examples include: a surface manager and a media framework. The surface manager manages the display subsystem and provides blending of 2D and 3D layers for multiple applications. The media framework supports playback of various common audio formats, as well as static graphics files.

[0109] The hardware abstraction layer runs in user space, encapsulates kernel-level drivers, and provides calling interfaces to the upper layers. The hardware abstraction layer may include: a sensor control module, a fusion analysis module, a Bluetooth module, and a WiFi module, etc. The sensor control module is used to control sensor 1, ..., sensor n to collect physiological and motion data (such as PPG data, acceleration data, etc.). The fusion analysis module is used to generate prompt information (such as the first prompt information, etc.) based on the physiological and motion data collected by the sensors.

[0110] The kernel layer is the layer between hardware and software. At a minimum, the kernel layer contains Bluetooth and WiFi drivers to drive the corresponding Bluetooth and WiFi chips, respectively.

[0111] The following example uses a terminal device with the structure shown in Figures 2 and 3, and in conjunction with the software architecture diagram of the terminal device 100 shown in Figure 4, to illustrate the overall process of the terminal device performing the above-mentioned blood glucose monitoring method.

[0112] The user can open an application X (such as a physiological monitoring application) at the application layer of the terminal device. After opening the application X, the terminal device sends a first request message to the notification manager. The notification manager generates a first request event based on the first request message and sends the first request event to the sensor control module. The sensor control module generates a first control command based on the first request event and sends the first control command to the sensor driver module. The sensor driver module generates a first drive command based on the first control command and drives sensors 1, ..., n to collect user physiological and user behavior data (such as PPG data, acceleration data, etc.). The fusion analysis module obtains the physiological and user behavior data from sensors 1, ..., n and generates a first prompt message based on the physiological and user behavior data. The fusion analysis module sends the first prompt message to the information display module. The information display module sends the first prompt message to the display driver module and instructs the display driver module to control the display screen to display the first prompt message (such as meal blood glucose monitoring results, etc.).

[0113] It should be noted that the software architecture of the terminal device is not limited to the hardware and software system structures shown in Figures 2 to 4. In actual applications, the hardware and software system structures shown in Figures 2 to 4 can be modified according to specific application scenarios. This application embodiment does not limit this.

[0114] The following example, using the software architecture of another terminal device shown in Figures 5A and 5B, illustrates the overall process of the terminal device executing the above-mentioned blood glucose monitoring method.

[0115] For example, as shown in Figure 5A, the software architecture 500A of the terminal device may include a sensor module (such as sensor 1, ..., sensor n), a data preprocessing module, a fusion analysis module, and an information display module; wherein, the fusion analysis module may include, but is not limited to, a meal blood glucose analysis module, an exercise blood glucose analysis module, and a sleep blood glucose analysis module; the interaction process between these modules in Figure 5A is as follows:

[0116] Step A1: The sensor module (such as sensor 1, ..., sensor n) collects the user's physiological data (such as PPG data), user behavior data (such as acceleration data), temperature data, etc.

[0117] Step A2: The data preprocessing module acquires physiological data, user behavior data, and temperature data from the sensor module, and performs preprocessing on these data (such as data segmentation, filtering, and data quality assessment) and data type classification to obtain different data types (such as user behavior data, temperature data, and blood glucose monitoring data).

[0118] Step A3: The meal analysis module can obtain user behavior data and its associated blood glucose monitoring data from the data preprocessing module, and generate prompt information 1 (i.e., an example of the first prompt information) based on these two data; the meal analysis module sends prompt information 1 to the information display module.

[0119] Similarly, the exercise (or sleep) analysis module can obtain user behavior data and its associated blood glucose monitoring data from the data preprocessing module, and generate prompt information 2 (or prompt information 3) based on these two data; the exercise (or sleep) analysis module sends prompt information 2 (or prompt information 3) to the information display module; where prompt information 2 (or prompt information 3) is another example of the first prompt information.

[0120] Step A4: The information display module displays the received prompt message 1 (or prompt message 2 or prompt message 3) on the terminal device's screen so that the user can promptly view the blood glucose monitoring results associated with the dining behavior (or exercise behavior or sleep behavior) type; where the dining behavior (or exercise behavior or sleep behavior) type is an example of the user's behavior type.

[0121] It should be noted that, in addition to having the software architecture 500A shown in Figure 5A, the terminal device can also have the software architecture 500B shown in Figure 5B.

[0122] The software architecture 500B may include a sensor module (such as sensor 1, ..., sensor n), a data preprocessing module, a blood glucose monitoring module, a behavior analysis module, a fusion analysis module, and an information display module; wherein, the behavior analysis module may include, but is not limited to, a meal analysis module, a motion analysis module, and a sleep analysis module; the interaction process between these modules in Figure 5B is as follows:

[0123] Step B1: The processing steps of the sensor module are similar to those in Step A1 above, and will not be repeated here.

[0124] Step B2: The processing steps of the data preprocessing module are similar to those in step A2 above, and will not be repeated here.

[0125] Step B3: The blood glucose monitoring module can obtain blood glucose monitoring data from the data preprocessing module and determine the blood glucose monitoring result (such as elevated blood glucose) based on the blood glucose monitoring data.

[0126] Step B4: The behavior analysis module can obtain user behavior data from the data preprocessing module. For example, the dining analysis module can obtain user behavior data from the data preprocessing module and identify parameters such as dining behavior type and dining time based on the user behavior data to obtain dining behavior recognition results (i.e., an example of target behavior recognition results); the exercise analysis module can obtain user behavior data from the data preprocessing module and identify parameters such as exercise behavior type and exercise time based on the user behavior data to obtain exercise behavior recognition results (i.e., another example of target behavior recognition results); the sleep analysis module can obtain user behavior data from the data preprocessing module and identify parameters such as sleep behavior type and sleep time based on the user behavior data to obtain sleep behavior recognition results (i.e., another example of target behavior recognition results).

[0127] It should be noted that steps B3 and B4 can be performed simultaneously or sequentially, and this application embodiment does not limit this.

[0128] Step B5: The fusion analysis module can obtain the dining behavior recognition results from the dining analysis module and the blood glucose monitoring data associated with the dining behavior recognition results from the blood glucose monitoring module, and generate prompt information 1 (i.e., an example of the first prompt information) based on the two data; the fusion analysis module sends prompt information 1 to the information display module.

[0129] Similarly, the fusion analysis module can obtain the motion behavior recognition results (or sleep behavior recognition results) from the motion analysis module (or sleep analysis module) and the blood glucose monitoring data associated with the motion behavior recognition results (or sleep behavior recognition results) from the blood glucose monitoring module, and generate prompt information 2 (or prompt information 3) based on these two data; the fusion analysis module sends prompt information 2 (or prompt information 3) to the information display module.

[0130] Step B6: The information display module will display the received prompt message 1 (or prompt message 2 or prompt message 3) on the terminal device's screen so that the user can promptly view the blood glucose monitoring results associated with the user's behavior type.

[0131] It should be noted that the software module division method of the terminal device shown in Figures 5A and 5B is merely an exemplary scheme and should not be construed as a limitation on the software module division of the terminal device. In actual applications, the terminal device may also have software module division methods other than those shown in Figures 5A and 5B, and this application embodiment does not limit this.

[0132] Before introducing the blood glucose monitoring method proposed in this application, the flowchart shown in Figure 6 will be used to describe the steps of the blood glucose monitoring method:

[0133] Step 601: The terminal device acquires PPG data and / or CGM data.

[0134] PPG data can be collected through PPG sensors, while CGM data can be collected through a CGM system.

[0135] In some examples, after the terminal device acquires PPG data, it needs to determine whether the PPG data is valid. The criteria for determining valid data may refer to whether the PPG data acquisition duration, acquisition timing, and data quality meet preset requirements. If they meet the requirements, the PPG data is considered valid, and step 602 is executed below. If they do not meet the requirements, the PPG data is considered invalid, and the PPG data needs to be acquired again (i.e., step 601 is executed).

[0136] Step 602: The terminal device performs data preprocessing on the acquired PPG data (such as data segmentation, filtering, etc.) to obtain data D01, and inputs data D01 into the blood glucose risk prediction model; the blood glucose risk prediction model performs blood glucose risk assessment on data D01 to obtain the blood glucose risk probability (also known as the probability of abnormal blood glucose change risk); wherein, the blood glucose risk prediction model can be used to assess the probability of abnormal blood glucose change risk; the probability of abnormal blood glucose change risk can be the probability of hyperglycemia (also known as abnormal blood glucose elevation) risk (e.g., 80%) and the probability of abnormal blood glucose decrease (e.g., 90%), etc.

[0137] And / or, the terminal device performs data preprocessing on the acquired CGM data (such as data partitioning, filtering, etc.) to obtain data D02.

[0138] Step 603: The terminal device can perform blood glucose level analysis (such as elevated blood glucose or blood glucose changes exceeding the threshold) based on the blood glucose risk probability and / or data D02, and obtain blood glucose analysis results (or blood glucose monitoring results).

[0139] Step 604: The terminal device acquires user behavior data; this user behavior data can be collected by sensors such as accelerometers and gyroscopes; this user behavior data can be used to identify dining behavior types.

[0140] Step 605: The terminal device performs data preprocessing (such as data segmentation, filtering, etc.) on the acquired user behavior data to obtain data D2, and inputs data D2 into the dining behavior recognition model (i.e., an example of a dining behavior model); the dining behavior recognition model evaluates the dining probability of data D2 to obtain dining behavior information (such as the probability corresponding to different dining behavior types); wherein, the dining behavior recognition model can be used to evaluate the probability of different dining behavior types occurring.

[0141] Step 606: The terminal device can perform dining behavior analysis based on dining behavior information to obtain dining behavior analysis results (such as breakfast, lunch, or dinner).

[0142] Step 607: The terminal device acquires the above-mentioned user behavior data; this user behavior data can also be used to identify the type of motion behavior.

[0143] Step 608: The terminal device performs data preprocessing on the acquired user behavior data (such as data segmentation, filtering, etc.) to obtain data D3, and inputs data D3 into the motion behavior recognition model (i.e., an example of a motion behavior model); the motion behavior recognition model performs motion type analysis on data D3 to obtain motion behavior information (such as the probability corresponding to different motion behavior types).

[0144] Step 609: The terminal device performs motion behavior analysis based on the motion behavior information to obtain motion behavior analysis results (such as running or strength training).

[0145] Step 610: The terminal device acquires the above-mentioned user behavior data; the user behavior data can also be used to identify sleep behavior types.

[0146] It should be noted that although the user behavior data collected within the same time period (such as the first time period) is fixed, the user behavior data can be input into different behavior models (such as dining behavior models) to identify different types of user behavior.

[0147] Step 611: The terminal device performs data preprocessing on the acquired sleep behavior data (such as data segmentation, filtering, etc.) to obtain data D4, and inputs data D4 into the sleep behavior recognition model (i.e., an example of a sleep behavior model); the sleep behavior recognition model performs sleep staging on data D4 to obtain sleep behavior information (such as the probability corresponding to different sleep behavior types).

[0148] Step 612: The terminal device performs sleep behavior analysis based on sleep behavior information to obtain sleep behavior analysis results (such as light sleep stage or deep sleep stage).

[0149] It should be noted that the above blood glucose analysis results are correlated with the above meal behavior analysis results (or exercise behavior analysis results or sleep behavior analysis results).

[0150] It should also be noted that the execution order of steps 601 to 603, 604 to 606, 607 to 609, and 610 to 612 can be adjusted according to the actual application scenario, and this application does not limit it.

[0151] Step 613: The terminal device can perform fusion analysis on the above blood glucose analysis results and their associated meal behavior analysis results (or exercise behavior analysis results or sleep behavior analysis results) to generate the first prompt information.

[0152] For example, the terminal device inputs the acquired user behavior data associated with the first time period into a dining behavior recognition model, an exercise behavior recognition model, and a sleep behavior recognition model, respectively. The dining behavior recognition model can output the probability of different dining behavior types based on the user behavior data; for example, it can output the probability of breakfast (an example of a dining behavior type) as 8%. The exercise behavior recognition model can output the probability of different exercise behavior types based on the user behavior data; for example, it can output the probability of running (an example of an exercise behavior type) as 1% and walking (another example of an exercise behavior type) as 1%. The sleep behavior recognition model can output the probability of different exercise behavior types based on the user behavior data. It outputs the probabilities of different sleep behavior types; for example, it can output a probability of 55% for sleep before bedtime (i.e., an example of sleep behavior type) and a probability of 90% for sleep onset (i.e., another example of sleep behavior type). The terminal device can determine the user behavior type with the highest probability from the results output by these three models. This user behavior type (taking a probability of 90% for sleep onset as an example) is determined as the target behavior type associated with the first time period. If the blood glucose monitoring result corresponding to the first time period is: blood glucose decreases, the terminal device can comprehensively determine the content of the first prompt information based on the target behavior type associated with the first time period (such as sleep onset) and the blood glucose monitoring result corresponding to the first time period, such as blood glucose decreases during sleep onset.

[0153] Step 614: The terminal device can display the first prompt information so that users can understand the relationship between their own behavior and blood glucose changes in a timely manner.

[0154] The above describes the process steps of a terminal device performing blood glucose monitoring in conjunction with different software architectures. The following section will continue to illustrate the blood glucose monitoring method provided in the embodiments of this application with reference to the accompanying drawings.

[0155] Figure 7 shows an interactive schematic diagram of a blood glucose monitoring method 700 provided in an embodiment of this application. It should be noted that, for ease of description, the following uses a terminal device as an example to introduce the relevant embodiments of method 700.

[0156] Before introducing the method 700 provided in this application, a brief description of the execution subject involved in the embodiments of this application will be given first; the above-mentioned method 700 can be executed by a terminal device, or by a module applied in the terminal device (such as a processor, chip, or chip system, etc.), or by a logic module or software that can implement all or part of the functions of the terminal device. The following embodiments only use a terminal device as an example to executively introduce the method 700 proposed in this application, but the embodiments of this application do not limit the execution subject.

[0157] The above method 700 may include the following steps:

[0158] Step 701, the terminal device determines the first information and the second information; wherein, the first information is the blood glucose monitoring result corresponding to the first time period, and the second information is the target behavior type associated with the first time period. The target behavior type is one of the user behavior types, which may include one or more of the following: eating behavior type, exercise behavior type, or sleep behavior type.

[0159] It should be noted that the terminal device can determine the first information and the second information simultaneously, or it can determine the first information and the second information sequentially. The embodiments of this application do not limit the order of obtaining the first information and the second information.

[0160] The first time period mentioned above can be understood as the period during which blood glucose monitoring (or blood glucose assessment) is required; the first time period can be understood as one or more of the following: a period before the start of the target behavior type, a period after the end of the target behavior type, or the entire period during the duration of the target behavior type or a part of the duration of the target behavior type.

[0161] The first time period is the period before the start of the target behavior type. It can be understood as the period before the user begins to perform the specific behavior corresponding to the target behavior type. For example, if the target behavior type is breakfast, then the specific behavior corresponding to breakfast can be eating breakfast. The time period before breakfast can be understood as the period before the user starts eating breakfast. For another example, if the target behavior type is breakfast, then the first time period can be half an hour or an hour before the user eats breakfast, such as from 8:00 am to 9:00 am.

[0162] The first time period is the period after the end of the target behavior type. It can be understood as the period after the user completes the specific behavior corresponding to the target behavior type. For example, if the target behavior type is yoga, then the specific behavior corresponding to yoga can be yoga practice (also known as practicing yoga or doing yoga). The period after yoga can be understood as the period after the user completes yoga practice. For another example, if the target behavior type is yoga, the first time period can be half an hour or an hour after the user completes yoga practice, etc.

[0163] The first time period refers to the entire or part of the time during which the target behavior type occurs. It can be understood as the entire or part of the time during which the user performs the specific behavior corresponding to the target behavior type; in other words, the first time period can cover the entire or part of the time from the start to the end of the specific behavior corresponding to the target behavior type. For example, if the specific behavior corresponding to the target behavior type is eating breakfast, then the first time period could be the entire or part of the time spent eating breakfast.

[0164] For example, taking breakfast as the target behavior type, the breakfast starts at 8:00 AM and ends at 8:30 AM. The first time period can be a period after 8:30 AM, such as 9:00 AM to 9:30 AM, or it can be a period before 8:00 AM, such as 7:00 AM to 7:30 AM, or it can be a period during breakfast, such as 8:10 AM to 8:25 AM.

[0165] Therefore, the definition of the first time period is not limited to a single situation, but can cover one or more of the above three time periods according to the specific application scenario and actual situation. This flexibility allows the first time period to be widely used in various user behavior analysis, health monitoring (such as blood glucose monitoring) and other scenarios.

[0166] When applying the first time period, which has multiple meanings, to a blood glucose monitoring scenario, the blood glucose monitoring can be performed before (or after) or during the duration of the target behavior type, thus obtaining blood glucose monitoring results associated with the start (or end) or duration of the target behavior type.

[0167] For example, monitoring blood glucose before the start of a target behavior type can yield the blood glucose monitoring results corresponding to the specific behavior type before its commencement. This result helps users understand their blood glucose status before the start of the target behavior type, preventing abnormal blood glucose levels during or after the target behavior type. For instance, if the terminal device detects that the user's blood glucose was high after their last meal, it can issue a reminder (such as generating a first alert and meal guidance information) based on the current blood glucose monitoring results, reminding the user to adjust their diet appropriately for the next meal to avoid consuming too much high-sugar food and prevent post-meal hyperglycemia. Furthermore... For example, monitoring blood glucose during a user's sleep can yield blood glucose monitoring results associated with the duration of the target behavior type. These results can help users understand their blood glucose changes during sleep, thus avoiding abnormal blood glucose fluctuations (such as abnormal drops). Similarly, monitoring blood glucose after the target behavior type has ended can yield blood glucose monitoring results associated with that end. These results can assess the impact of the target behavior type on blood glucose levels. For instance, monitoring blood glucose two hours after lunch can help users understand the impact of lunch on their blood glucose; monitoring blood glucose after a workout can assess the impact of that workout on blood glucose levels.

[0168] It should be noted that the above-mentioned user behavior types may include one or more of the following: dining behavior type, exercise behavior type, or sleep behavior type. Of course, other behavior types (such as work and study behavior type, entertainment behavior type, etc.) may also be included, but this application embodiment does not limit them.

[0169] In some embodiments, when the target behavior type is a dining behavior type, the aforementioned first prompt information can be used to prompt the blood glucose monitoring results associated with the dining behavior type; and the dining behavior type may include at least one of the following: breakfast, lunch, or dinner.

[0170] Specifically, when the target behavior type is a meal behavior type, the terminal device can notify the user of the blood glucose monitoring results associated with that meal behavior type by generating a first prompt message. The meal behavior type mentioned here can specifically refer to any one or more meals, such as breakfast, lunch, or dinner. In other words, whether it is breakfast, lunch, or dinner, the terminal device can display the blood glucose monitoring results associated with (or corresponding to) that meal to the user through the first prompt message.

[0171] It should be noted that the above-mentioned dining behavior types can be divided into three main meal types: breakfast, lunch, and dinner, based on the time of the meal. Specifically, at least one meal activity taken between 6:00 AM and 11:00 AM each day can be considered breakfast; at least one meal taken between 11:00 AM and 3:00 PM can be considered lunch; and at least one meal taken between 3:00 PM and 10:00 PM can be considered dinner. It is worth noting that this is only an example of a method for classifying dining behavior types. In actual applications, the time division may be different, and this application embodiment does not limit the time division method for dining behavior types.

[0172] In this embodiment, the terminal device can generate a first prompt message containing specific dining behavior types (such as breakfast), so that the blood glucose monitoring results can be refined to the user's specific lifestyle behavior level. This not only makes it easier for users to intuitively understand the direct impact of dining behavior types on blood glucose levels, but also provides users with accurate and efficient guidelines for adjusting dining behavior types when blood glucose fluctuates abnormally due to specific dining behavior types, making the user's blood glucose management strategy more targeted and effective.

[0173] In some embodiments, when the target behavior type is an exercise behavior type, the first prompt information is used to prompt the blood glucose monitoring results associated with the exercise behavior type.

[0174] Specifically, when the target behavior type is exercise, the terminal device can notify the user of the blood glucose monitoring results associated with that exercise behavior type by generating a first prompt message. The exercise behavior type mentioned here can include at least one of the following: aerobic exercise (such as aerobics), anaerobic exercise (such as strength training), flexibility exercise (such as yoga), balance exercise (such as standing on one leg), recreational exercise (such as mountain climbing), or competitive exercise (such as track and field). In other words, regardless of the type of exercise behavior, the terminal device can display the blood glucose monitoring results associated with (or corresponding to) that exercise behavior type to the user through the first prompt message.

[0175] It should be noted that the above-mentioned exercise behavior types can be divided into aerobic exercise, anaerobic exercise, etc., according to the form of exercise; however, the classification of exercise behavior types is not limited to this classification method according to the form of exercise; in fact, exercise behavior types can also be classified according to other criteria, such as according to the sport or category (such as dance). The embodiments of this application do not limit the classification method of exercise behavior types.

[0176] In this embodiment, the terminal device can generate a first prompt message containing the specific type of exercise behavior (such as aerobic exercise), so that the blood glucose monitoring results can be refined to the user's specific lifestyle behavior level. This not only makes it easier for users to intuitively understand the direct impact of different types of exercise behavior on blood glucose levels, but also provides users with accurate and efficient exercise behavior type adjustment guidelines when blood glucose fluctuates abnormally due to specific types of exercise behavior, making the user's blood glucose management strategy more targeted and effective.

[0177] In some embodiments, when the target behavior type is a sleep behavior type, the first prompt information can be used to prompt the blood glucose monitoring results associated with the sleep behavior type.

[0178] Specifically, when the target behavior type is a sleep behavior type, the terminal device can notify the user of the blood glucose monitoring results associated with that sleep behavior type by generating a first prompt message. The sleep behavior type mentioned here can include at least one of the following: before sleep, sleep onset, light sleep, deep sleep, REM sleep, or after sleep. In other words, regardless of the sleep behavior type, the terminal device can display the blood glucose monitoring results associated with (or corresponding to) that sleep behavior type to the user through the first prompt message.

[0179] It should be noted that the above-mentioned sleep behavior types are classified according to the user's physiological changes and brainwave activity during sleep, such as pre-sleep, sleep onset, and light sleep. However, the classification of sleep behavior types is not limited to this method. In fact, sleep behavior types can also be classified according to other criteria, such as dividing the entire sleep stage into REM stage and non-REM stage based on whether the user is in the REM stage. The embodiments of this application do not limit the classification method of sleep behavior types.

[0180] In this embodiment, the terminal device can generate a first prompt message containing specific sleep behavior types (such as before bedtime), so that the blood glucose monitoring results can be refined to the user's specific lifestyle behavior level. This not only makes it easier for users to intuitively understand the direct impact of different sleep behavior types on blood glucose levels, but also provides users with accurate and efficient sleep behavior type adjustment guidelines when specific sleep behavior types cause abnormal fluctuations in blood glucose, making the user's blood glucose management strategy more targeted and effective.

[0181] Step 702: The terminal device generates a first prompt message based on the first information and the second information. The first prompt message is used to prompt the blood glucose monitoring results associated with the target user's behavior.

[0182] The aforementioned first prompt information may include, but is not limited to, blood glucose monitoring results associated with the target user's behavior; for example, it may also include information such as the type of target behavior and the start time of the occurrence of the target behavior type. This application embodiment does not limit the specific content included in the first prompt information.

[0183] After determining the first and second information, the terminal device can generate a first prompt message by combining the first and second information, establishing a correlation between the blood glucose monitoring results corresponding to the first time period and the target behavior type associated with the first time period. In this way, the first prompt message can display the blood glucose monitoring results corresponding to the target behavior type (such as the type of eating behavior) associated with the first time period to the user. If the blood glucose monitoring result shows an abnormality, the user can quickly know which target behavior type caused the abnormal change in blood glucose. Furthermore, the terminal device can also provide users with more personalized behavior adjustment suggestions based on the target behavior type that caused the abnormal blood glucose, thereby helping users achieve more refined and effective blood glucose management.

[0184] It should be noted that after the terminal device generates the first prompt information, it can either play the first prompt information by voice, display the first prompt information on its own display screen, or display the first prompt information by a combination of voice and display. This application embodiment does not limit this.

[0185] For example, taking the first time period as 8:30 to 9:00 AM as an example; this first time period is a period after breakfast; the first information is the blood glucose monitoring result during the period of 8:30 to 9:00 AM, such as elevated blood glucose (i.e., an example of blood glucose monitoring results); the target behavior type associated with 8:30 to 9:00 AM is breakfast (i.e., an example of second information); the terminal device generates a prompt message X1 (i.e., an example of the first prompt message) based on the blood glucose monitoring result (such as elevated blood glucose) and the target behavior type (such as breakfast) associated with 8:30 to 9:00 AM; the specific content of the prompt message X1 can be elevated blood glucose after breakfast.

[0186] In summary, in the aforementioned method 700, the terminal device determines two types of key information: first information and second information, and generates a first prompt based on (or a combination of) these two types of information. The first prompt reflects the dynamic correlation between the target behavior type and the blood glucose monitoring results. This method has the following advantages: Firstly, by analyzing the correlation between the target behavior type and the blood glucose monitoring results, the terminal device can generate more detailed and personalized health guidance plans for users, facilitating more precise and effective blood glucose management. Secondly, the first prompt helps users understand the direct impact of their behavior on their blood glucose levels; for example, when blood glucose rises or fluctuates abnormally, users can quickly... Quickly understanding the specific behavioral types that cause this change allows users to adjust their behavior in a timely manner and take more scientific health management measures to achieve precise control of blood sugar levels. For example, when a user discovers that their previous lunch (an example of a user's behavioral type) is the main cause of elevated blood sugar, they can adjust their diet at the next meal based on the first prompt (such as a reminder that blood sugar rose after the previous lunch), thus effectively avoiding a sustained rise in blood sugar. It is evident that by analyzing target behavioral types and blood sugar monitoring results, terminal devices generate targeted first prompts, which not only enhance the personalization and precision of user health management but also promote the user's initiative and effectiveness in self-health management.

[0187] In some embodiments, step 701 above can also be implemented through the following steps:

[0188] Step 7011: The terminal device acquires the first data.

[0189] The first data refers to the physiological data corresponding to the first time period; this physiological data may include PPG data, temperature data, and blood glucose data (such as blood glucose level data).

[0190] In some embodiments, the terminal device may acquire first data through at least one of the following devices: an optical sensor, a temperature sensor, or a continuous glucose monitoring (CGM) system.

[0191] The optical sensor may include not only PPG sensors, but also infrared sensors, etc., and this application embodiment does not limit this; the PPG sensor can be used to acquire PPG data.

[0192] Temperature sensors can be used to collect temperature data from a user's skin surface. When a user's blood sugar level fluctuates abnormally, such as rising, changes occur in the body's metabolism, such as accelerated metabolism. These changes are indirectly reflected in changes in skin temperature. Therefore, the terminal device can use temperature data to assess changes in the user's blood sugar status. In addition, the terminal device can also combine temperature data and PPG data to comprehensively analyze changes in the user's blood sugar, thereby further improving the accuracy of blood sugar assessment.

[0193] A CGM system can be used to acquire blood glucose data; wherein, blood glucose data may include blood glucose value data; it should be noted that, in addition to a CGM system, other dynamic blood glucose monitoring systems may also be used to acquire blood glucose data, and this application embodiment does not limit this.

[0194] In some embodiments, the terminal device can combine PPG data, temperature data, and blood glucose data to comprehensively analyze changes in blood glucose levels within the user's body, thereby further improving the accuracy of blood glucose assessment.

[0195] Therefore, in diverse application scenarios, on the one hand, terminal devices can non-invasively acquire users' physiological data (i.e., an example of primary data) through sensors such as PPG and temperature. This process does not require piercing the skin, greatly reducing the user's physical burden and discomfort, and providing a painless and efficient blood glucose monitoring experience. On the other hand, terminal devices can also accurately acquire blood glucose data (i.e., an example of physiological data) through CGM systems, and based on this, provide users with more refined blood glucose monitoring results and personalized blood glucose management strategies, thereby helping users achieve more scientific and effective blood glucose management. In addition, terminal devices can also simultaneously utilize optical sensors such as PPG. The use of temperature sensors and CGM systems to acquire the aforementioned physiological data offers the following advantages: 1) When multiple data types are available, the terminal device can integrate these data to generate more accurate blood glucose monitoring results; 2) These different data types play complementary roles in blood glucose monitoring. For example, in certain scenarios, when one type of data (such as temperature data) cannot be obtained for some reason, the terminal device can still rely on another type of data (such as PPG data) to generate blood glucose monitoring results. This flexible data application strategy effectively avoids the problem of blood glucose monitoring interruption caused by the lack of a single data source, ensuring that users can obtain reliable blood glucose monitoring information under any circumstances.

[0196] Step 7012: The terminal device acquires the second data.

[0197] The second data may be user behavior data associated with the first time period; the second data may be data collected by the terminal device during the first time period, or data collected before the first time period, or data collected after the first time period, and this application embodiment does not limit this.

[0198] The aforementioned user behavior data can include various types of data information, such as acceleration, tilt angle, and rotation angle; the terminal device can acquire these different types of data information through different types of sensors (such as accelerometers, gyroscopes, etc.).

[0199] For example, the terminal device can use an internal accelerometer to obtain information on the acceleration changes of the user's hand or body movements during the meal; this acceleration change information can reflect the user's eating habits or movement patterns, such as eating quickly or chewing slowly; in addition, the terminal device can also use an internal gyroscope to obtain information such as the user's rotation angle and tilt angle during the meal, so as to analyze the type of eating behavior the user is in, such as breakfast.

[0200] For example, a terminal device can use an internal accelerometer to obtain information on the acceleration changes of a user's body movements during exercise; this acceleration change information can reflect the user's movement state, such as running, walking, or jumping; in addition, the terminal device can also use an internal gyroscope to obtain information such as the user's rotation angle and tilt angle during exercise, and this information can be used by the terminal device to analyze what type of exercise the user is doing, such as running.

[0201] For example, the terminal device can obtain information on the acceleration changes of the user's body movements during sleep through the internal accelerometer; this acceleration change information can reflect the user's state during sleep, such as turning over, kicking, or subtle movements during deep sleep; in addition, the terminal device can also obtain information such as the user's rotation angle and tilt angle during sleep through the internal gyroscope, so as to analyze the type of sleep behavior the user is in, such as light sleep, based on this information.

[0202] Step 7013: The terminal device determines the first information based on the first data.

[0203] After the terminal device obtains the first data, it can determine the first information based on the first data; for example, if the first data is PPG data (i.e., an example of physiological data), the terminal device can obtain the PPG data through the internal PPG sensor and determine the blood glucose monitoring result 1 (i.e., an example of the first information) based on the PPG data.

[0204] For example, the first data is blood glucose data (another example of physiological data). The terminal device can obtain this blood glucose data through its internal CGM system and generate blood glucose monitoring result 2 (another example of the first information) based on this blood glucose data.

[0205] Step 7014: The terminal device determines the second information based on the second data.

[0206] Wherein, the second information is the target behavior type associated with the first time period; the second data is the user behavior data associated with the first time period; in some examples, after the terminal device obtains the second data, it can input the second data into at least one of the following user behavior models: dining behavior model, exercise behavior model, or sleep behavior model; the user behavior model can perform behavior recognition on the second data and output the user behavior recognition result; the user behavior recognition result can be referred to the relevant description in step 7014a below, which will not be repeated here.

[0207] It should be noted that when the second data is input into the dining behavior recognition model, the model can output dining behavior information, such as the probability corresponding to the dining behavior type (i.e., an example of the target behavior type), for example, the probability of breakfast is 90%, the probability of lunch is 10%, and the probability of dinner is 10%. Similarly, when the second data is input into the exercise behavior recognition model, the model can output the probability corresponding to the exercise behavior type (i.e., another example of the target behavior type), for example, the probability of running (i.e., an example of aerobic exercise) is 90%, and the probability of weightlifting (i.e., an example of anaerobic exercise) is 20%. When the second data is input into the sleep behavior recognition model, the model can output the probability corresponding to the sleep behavior type (i.e., yet another example of the target behavior type), for example, the probability of sleeping before bed is 20%.

[0208] For example, after acquiring the second data, the terminal device can input the second data into the dining behavior recognition model (i.e., an example of a dining behavior model), the exercise behavior recognition model (i.e., an example of an exercise behavior model), and the sleep behavior recognition model (i.e., an example of a sleep behavior model) shown in Figure 6, respectively. The dining behavior recognition model can output the probabilities corresponding to different dining behavior types (i.e., an example of dining behavior information), such as a 90% probability for breakfast, a 10% probability for lunch, and a 10% probability for dinner. The exercise behavior recognition model can output the probabilities corresponding to different exercise behavior types (i.e., an example of exercise behavior information), such as a 10% probability for running and a 2% probability for weightlifting. The sleep behavior recognition model can output the probability corresponding to the sleep behavior type (i.e., an example of sleep behavior information), such as a 20% probability of sleeping before bed, a 10% probability of falling asleep, and a 2% probability of light sleep. The terminal device can determine the user behavior type with the highest probability from the results output by these three models. This user behavior type (taking breakfast as an example with a 90% probability) is determined as the target behavior type associated with the first time period. If the blood glucose monitoring result corresponding to the first time period is: elevated blood glucose, the terminal device can comprehensively determine the content of the first prompt information based on the target behavior type associated with the first time period (such as breakfast) and the blood glucose monitoring result corresponding to the first time period, such as blood glucose decreasing after breakfast.

[0209] In this embodiment, when determining the first information (or the second information), the terminal device can first acquire the first data and the second data corresponding to this information. The first data can be physiological data, such as PPG data or blood glucose data, which can be used to reflect the user's blood glucose changes. The second data is user behavior data associated with the first time period, which can be used to determine the target behavior type. By acquiring and analyzing the first data and the second data, the terminal device can provide the user with blood glucose monitoring results for the target behavior type.

[0210] In some embodiments, step 7014 above can also be implemented through the following steps:

[0211] Step 7014a: The terminal device can perform behavior recognition on the second data through the user behavior model to obtain the user behavior recognition result.

[0212] The user behavior model can be one or more of the following: a dining behavior model (such as the dining behavior recognition model mentioned above), a movement behavior model (such as the movement behavior recognition model mentioned above), or a sleep behavior model (such as the sleep behavior recognition model mentioned above). The dining behavior model can be used to identify the type of dining behavior based on the dining behavior data, the movement behavior model can be used to identify the type of movement behavior based on the movement behavior data, and the sleep behavior model can be used to identify the type of sleep behavior based on the sleep behavior data.

[0213] The aforementioned user behavior recognition results can be probabilities corresponding to different user behavior types (such as dining behavior type, exercise behavior type, or sleep behavior type), target behavior type, or other information used to indicate different user behavior types. This application embodiment does not limit these.

[0214] In other words, the user behavior model can output the probability corresponding to different user behavior types (such as the probability of dining behavior type, the probability of exercise behavior type, etc.) based on the input user behavior data, or it can directly output the target behavior type based on the input user behavior data.

[0215] For example, the terminal device can input user behavior data into a dining behavior model and an exercise behavior model respectively; the dining behavior model outputs a 90% probability of breakfast and a 20% probability of dinner; the exercise behavior model outputs a 30% probability of running and a 10% probability of yoga; the terminal device can determine the user behavior type with the highest probability from the results output by these two models; and this user behavior type (taking a 90% probability of breakfast as an example) is determined as the target behavior type associated with the first time period; after determining the target behavior type, the terminal device will output the target behavior type (i.e., an example of the user behavior recognition result).

[0216] Step 7014b: The terminal device determines the second information based on the user behavior recognition result.

[0217] Once the terminal device determines the user behavior recognition result, it can determine the target behavior type based on the user behavior recognition result; and the target behavior type is the behavior type associated with the first time period. Therefore, the terminal device can determine the second information based on the target behavior type.

[0218] In some examples, when the user behavior recognition result is the probability of a user behavior type, the terminal device can determine the user behavior type with the highest probability from the probabilities of at least one user behavior type; and the user behavior type with the highest probability is the target behavior type; after the terminal device determines the target behavior type associated with the first time period, it determines the second information.

[0219] For example, after the terminal device obtains the user behavior data corresponding to the first time period, it can input the user behavior data into the dining behavior model, exercise behavior model, and sleep behavior model respectively. The dining behavior model can output a probability of 20% for breakfast and 90% for dinner; the exercise behavior model can output a probability of 20% for running and 30% for weightlifting; and the sleep behavior model can output a probability of 20% for before bed and 5% for falling asleep. The terminal device determines the user behavior type with the highest probability from the probabilities of breakfast, dinner, running, weightlifting, before bed, and falling asleep. This user behavior type (taking a 90% probability of dinner as an example) is determined as the target behavior type associated with the first time period. The terminal device determines the target behavior type associated with the first time period, which means it has determined the second information.

[0220] In this embodiment, since the user behavior model can output high-precision user behavior recognition results, the terminal device can generate more accurate second information based on the user behavior recognition results, so as to provide accurate and effective basis for subsequent user behavior analysis, blood glucose monitoring result generation and other processing processes.

[0221] In some embodiments, the method 700 described above may further include:

[0222] Step 703: The terminal device displays the first interface.

[0223] In some embodiments, the terminal device may display various information (such as a first prompt message) to the user by displaying a first interface; wherein, the first interface may include, but is not limited to, the first prompt message and a first control, which can be understood as an element for the user to interact with the first interface, and can be used to view the detailed content of the first prompt message; the first interface may be interface 912 in Figure 9F below, or interface 1001 in Figure 10A below, or interface 1101 in Figure 11A below; the first control may be the meal blood glucose details 913 control in Figure 9F below, or exercise blood glucose details 1002 control in Figure 10A below, or sleep blood glucose details 1102 control in Figure 11A below; the user may trigger the first control in some way (such as clicking, touching, etc.) to view the detailed content of the first prompt message; wherein, the detailed content of the first prompt message may include, but is not limited to, the target behavior type (such as breakfast), the time period of occurrence of the target behavior type (such as 8:00 to 8:30 am), and the blood glucose monitoring results associated with the target behavior type (such as post-breakfast blood glucose elevation).

[0224] It should be noted that, in addition to providing the primary control for users to view the detailed content of the initial prompt information, the terminal device can also provide the detailed content of the initial prompt information via physical buttons on the terminal device, such as a physical button on the terminal device.

[0225] It should also be noted that the aforementioned first control can be a virtual button on the first interface; the user can touch the virtual button to view the detailed content of the first prompt information; in addition, the first control can also be a floating button on the first interface (such as a button that floats on the first interface in a certain way (such as with an animation effect); the user can trigger the floating button to view the detailed content of the first prompt information. Of course, the presentation form of the first control on the first interface can also be other available forms, and this application embodiment does not limit this.

[0226] In this embodiment, while displaying the first prompt information on the first interface, the terminal device can also provide a first control for displaying blood glucose details, so that users can easily learn more about the detailed content of the blood glucose monitoring results associated with the target behavior type by triggering the first control at any time, thereby improving the user experience and blood glucose management efficiency.

[0227] In some embodiments, when the first prompt information is used to prompt the blood glucose monitoring results corresponding to the dining behavior type associated with the first time period (i.e., an example of the target behavior type), the first control can be used as a control for viewing dining blood glucose details, as shown in the dining blood glucose details 913 control in Figure 9F below; the user can operate the first control in some way (such as clicking, swiping, etc.).

[0228] Since users may need to view more detailed meal blood glucose information in some application scenarios, the terminal device can display the first prompt information on the first interface, while also providing a first control for displaying meal blood glucose details. This allows users to easily access more detailed information about the blood glucose monitoring results associated with the meal behavior type by triggering the first control at any time.

[0229] Step 704: The terminal device receives the first operation.

[0230] The first operation is used to trigger the first control; the first operation can be a click operation, a swipe operation, or a hover operation, etc. The specific form of the first operation is not limited in the embodiments of this application.

[0231] For example, the first operation could be the user clicking the "Mealtime Blood Glucose Details 913" control in Figure 9F below, or the user clicking the "Exercise Blood Glucose Details 1002" control in Figure 10A below, or the user clicking the "Sleep Blood Glucose Details 1102" control in Figure 11A below.

[0232] When a user triggers (or operates or activates) a first control on the first interface of a terminal device in a certain way (e.g., by tapping with a finger), the terminal device can receive (or detect) the first operation.

[0233] Step 705: The terminal device responds to the first operation and displays the second interface.

[0234] After receiving the first operation, the terminal device can respond to the first operation by displaying a second interface. The second interface may include, but is not limited to, third and fourth information. The third information may be used to provide feedback on the types of user behavior detected within a preset time period, and the fourth information may be used to provide feedback on the blood glucose monitoring results corresponding to the types of user behavior detected within the preset time period. It should be noted that the blood glucose monitoring results may include normal blood glucose monitoring results and / or abnormal blood glucose monitoring results. Normal blood glucose monitoring results can be understood as blood glucose monitoring results indicating that the user's blood glucose is within the normal range. Abnormal blood glucose monitoring results can be understood as blood glucose monitoring results indicating abnormal changes in the user's blood glucose (such as hyperglycemia or abnormally low blood glucose).

[0235] In some examples, the third information mentioned above may include, but is not limited to, at least one of the following: user behavior type (e.g., dining behavior type), the number of times the user behavior type occurs (e.g., the number of times the dining behavior type occurs), or the time when the user behavior type occurs (e.g., the time when the dining behavior type occurs). The fourth information may include, but is not limited to, blood glucose monitoring results associated with the user behavior type. The user behavior type may be one of the following: dining behavior type, exercise behavior type, or sleep behavior type. The preset time period may include a first time period, for example, the preset time period may be within 24 hours of the same day, or within 8 hours of the same day, etc. The first time period is all or part of the time period within the preset time period.

[0236] For example, the second interface can be the meal blood glucose details interface 914 in Figure 9G below, or the exercise blood glucose details interface 1003 in Figure 10B below, or the sleep blood glucose details interface 1103 in Figure 11B below.

[0237] For example, the third information could be the meal detection result on the meal blood glucose details interface 914 in Figure 9G below, and the fourth information could be the details of key events associated with the meal in Figure 9G below; or, the third information could be the exercise detection result on the exercise blood glucose details interface 1003 in Figure 10B below, and the fourth information could be the details of key events associated with the exercise in Figure 10B below; or, the third information could be the sleep detection result on the sleep blood glucose details interface 1103 in Figure 11B below, and the fourth information could be the details of key events associated with the sleep in Figure 11B below.

[0238] It should be noted that the relationship between the user behavior type and the frequency of occurrence of the above-mentioned user behavior type can be one-to-one or one-to-many.

[0239] Taking dining behavior type as an example, the relevant understanding of dining behavior type in the third information can be found in the relevant explanation in step 701 above, and will not be repeated here; the frequency of dining behavior type can be 2 times / day or 3 times / day, etc., and the time of dining behavior type can be 8:00 to 8:30 am, or 12:00 to 12:30 pm, etc.; the blood glucose monitoring result associated with dining behavior type can be blood glucose rise after breakfast, or blood glucose rise after lunch, etc.

[0240] For example, if a user's dining behavior types throughout the day (i.e., an example of a preset time period) are breakfast, lunch, and dinner, and each type of dining behavior is performed once within its respective time period, then the user's dining behavior types throughout the day are 3 (i.e., breakfast, lunch, and dinner), and these dining behavior types occur a total of 3 times; at this time, there is a one-to-one correspondence between the dining behavior types and the number of times the dining behavior types occur.

[0241] For example, if a user's dining behaviors throughout the day are breakfast and lunch, and each type of dining behavior is performed twice within its respective time period, then the user's total dining behaviors throughout the day are two types (i.e., breakfast and lunch), and these dining behaviors occur four times. In this case, the dining behavior types and the number of times each dining behavior type occurs form a one-to-many relationship.

[0242] In some application scenarios, users can trigger a first control to display a second interface on the terminal device. This second interface can show users detailed blood glucose information, such as the type of user behavior and the number of times the user behavior occurred, so that users can clearly understand the impact of user behavior on blood glucose levels. This will encourage users to flexibly adjust their lifestyles according to the actual situation and ensure that blood glucose is kept stable within the healthy range.

[0243] In some embodiments, when the user behavior type is dining behavior, the second interface may further include a second control, which can be used to view historical blood glucose levels after meals. The method 700 may further include the following steps:

[0244] Step 706: The terminal device receives the second operation.

[0245] The second operation is used to trigger the second control. The second operation is similar to the first operation, and the second control is similar to the first control. For details, please refer to the relevant descriptions of the first operation and the first control in steps 703 and 704 above. They will not be repeated here.

[0246] For example, the second control can be the dining history comparison control 915 in Figure 9G below; the second operation can be the operation of the user clicking "dining history comparison control 915" in Figure 9G below.

[0247] When a user triggers (or operates or activates) a second control on the second interface of the terminal device in a certain way (e.g., by tapping with a finger), the terminal device can receive (or detect) the second operation.

[0248] Step 707: The terminal device responds to the second operation and displays the third interface.

[0249] After receiving the second operation, the terminal device will respond to the second operation by displaying a third interface; for example, the third interface can be the meal blood glucose history interface 916 in Figure 9H below.

[0250] The third interface may include at least one of the following: meal-related blood glucose risk curve, meal-related historical blood glucose reports, or meal guidance information.

[0251] The mealtime blood glucose risk curve can be used to describe the trend of mealtime blood glucose risk over time in the second time period. This mealtime blood glucose risk curve can be seen in the mealtime blood glucose risk curve 917 in Figure 9H below. The second time period occurs before the first time period, that is, the second time period can be understood as a certain historical time period that has already occurred, such as from 00:00:00 on October 1, ** to 00:00:00 on October 7, ** (see Figure 9H below). This mealtime blood glucose risk curve can also be understood as a historical mealtime blood glucose risk curve.

[0252] For example, the above-mentioned risk of postprandial hyperglycemia can be one of the following: the number of times postprandial hyperglycemia occurs, the percentage of postprandial hyperglycemia, or the average probability of postprandial hyperglycemia.

[0253] The frequency of postprandial hyperglycemia can be understood as the number of times a user experiences hyperglycemia after a meal (i.e., after the meal behavior occurs) within a specific time period (such as a day, a week, or a month). Hyperglycemia can generally be understood as a blood sugar level exceeding the normal range (e.g., for healthy users, the blood sugar level n hours after a meal generally does not exceed X mmol / L, where n can be a positive integer).

[0254] The percentage of postprandial hyperglycemia can be understood as the proportion of times a user experiences postprandial hyperglycemia (i.e., after a meal behavior occurs) within a specific time period, out of the total number of postprandial blood glucose monitoring sessions. For example, if the terminal device performs 5 postprandial blood glucose monitoring sessions in a day, and 3 of them exceed the normal range, then the user's postprandial hyperglycemia percentage is three-fifths (i.e., 60%).

[0255] The average probability of postprandial hyperglycemia can be used to assess the risk of a user experiencing postprandial hyperglycemia (i.e., after a specific type of meal) within a specific time period. It can typically be obtained by calculating the average probability of exceeding the normal range in multiple postprandial blood glucose monitoring results. For example, if a terminal device performs three postprandial blood glucose monitoring tests in one day, and the probability of the first test indicating a risk of hyperglycemia is 60%, the second test indicates a risk of hyperglycemia is 90%, and the third test indicates a risk of hyperglycemia is 80%, then the average probability of postprandial hyperglycemia is approximately 77% (i.e., (60% + 90% + 80%) ÷ 3).

[0256] In some application scenarios, users can trigger a second control to display a third interface on the terminal device. The third interface shows users information such as the blood glucose risk curve for meals during a second time period (i.e., a certain historical time period), so that users can understand the changes in blood glucose risk during meals in the past. This design not only makes it easier for users to comprehensively review and analyze their own blood glucose status, but also helps users adjust their blood glucose control strategies to ensure that blood glucose levels are maintained within a healthy range, thereby achieving more refined blood glucose management.

[0257] The meal history blood glucose report and meal guidance information are shown in Figures 9I and 9J below. This meal history blood glucose report can be understood as a report on the user's blood glucose level and its trend before and after each meal (i.e., meal behavior type) within a second time period (such as a week, a month, etc.). It may include, but is not limited to, the user's meal habits and the pattern of changes in meal-related blood glucose risk within the second time period. Among them, meal habits may include, but are not limited to, the regularity of the number of meals per day, the amount of each meal, and the meal time. The pattern of changes in meal-related blood glucose risk can be understood as the trend and characteristics of changes in blood glucose after a meal (i.e., the occurrence of a meal behavior type) when the user follows specific meal habits.

[0258] In some examples, the above-mentioned meal guidance information may include, but is not limited to, at least one of the following: order of eating, type of food, or dietary recommendations; wherein, the order of eating can be understood as the order in which food is consumed during a meal; for example, the order of eating could be to eat vegetables first, then protein (such as meat, fish, and soy products), and finally carbohydrates (such as rice, noodles, etc.); such an order helps control the rise in blood sugar after a meal. The type of food can be understood as the type of food consumed; for example, the type of food can include low-fat, low-sugar, high-protein, and high-fiber foods. Dietary recommendations can include food intake, meal distribution, drinking habits, and avoiding or restricting certain foods; these dietary recommendations aim to help individuals establish healthy eating habits to improve blood sugar control.

[0259] Therefore, it is evident that the terminal device's intuitive display of historical blood glucose reports through a third interface helps users clearly understand their blood glucose responses at different times and with different eating behaviors, thereby increasing users' awareness of the importance of blood glucose management. In addition, displaying meal guidance information through the third interface can help users optimize their subsequent eating habits, ensure that blood glucose remains stable at a healthy level, and achieve more refined blood glucose management.

[0260] It should be noted that when the terminal device provides feedback on historical blood glucose levels after meals to the user, in addition to assisting the user in viewing historical blood glucose levels through the second control and the third interface as mentioned above, it can also directly display historical blood glucose levels on the second interface; for example, the user can view historical blood glucose details by swiping up and down on the second interface. Of course, the terminal device can also have other ways of presenting historical blood glucose details, and this application embodiment does not limit the interface where the historical blood glucose details are located or the viewing method.

[0261] In some embodiments, when the first prompt information is used to prompt the blood glucose monitoring results corresponding to the exercise behavior type associated with the first time period (i.e., another example of the target behavior type), the first control can be used as a control for viewing exercise blood glucose details, as shown in the exercise blood glucose details 1002 control in Figure 9A below; the user can operate the first control in some way (such as clicking, swiping, etc.).

[0262] Since users may need to view more detailed exercise blood glucose information in some application scenarios, the terminal device can provide a first control to display exercise blood glucose details while displaying the first prompt information on the first interface. This allows users to easily access more detailed information about the blood glucose monitoring results associated with the type of exercise by triggering the first control at any time.

[0263] In some other embodiments, when the user behavior type is exercise behavior, the third information mentioned above may include, but is not limited to, at least one of the exercise behavior type, the number of times the exercise behavior type occurs, or the time when the exercise behavior type occurs. The fourth information may include, but is not limited to, the blood glucose monitoring results associated with the exercise behavior type. The exercise behavior type can be referred to the relevant explanation in step 701 above, and will not be repeated here. The number of times the exercise behavior type occurs may be 2 times / day or 3 times / day, etc. The time when the exercise behavior type occurs may be from 8:00 to 9:30 in the morning, or from 19:00 to 20:00 in the afternoon, etc. The blood glucose monitoring results associated with the exercise behavior type may be abnormally low blood glucose after running, or abnormally low blood glucose after strength training, etc.

[0264] For example, if a user's exercise behavior throughout the day (i.e., an example of a preset time period) consists of running, yoga, and strength training, and each type of exercise behavior is performed once within its respective time period, then the user's total exercise behavior types for the day are 3 (i.e., running, yoga, and strength training), and these exercise behavior types occur a total of 3 times; in this case, there is a one-to-one correspondence between the exercise behavior types and the number of times the exercise behavior types occur.

[0265] For example, if a user's exercise behavior throughout the day consists of running and strength training, and each type of exercise behavior is performed twice within its respective time period, then the user's total exercise behavior types for the day are two (i.e., running and strength training), and these exercise behavior types occur four times. In this case, the relationship between exercise behavior types and the number of times exercise behavior types occur forms a one-to-many relationship.

[0266] In some application scenarios, users can trigger the first control to display a second interface on the terminal device. The terminal device can then display detailed exercise blood glucose information such as the type of exercise behavior and the number of times the exercise behavior occurred, so that users can clearly understand the impact of exercise behavior on blood glucose levels. This will encourage users to flexibly adjust their exercise habits according to the actual situation and ensure that blood glucose is kept stable within the healthy range.

[0267] In some embodiments, when the user behavior type is exercise behavior, the second control on the second interface can be used to view historical exercise blood glucose levels, and the method 700 may further include:

[0268] Step A1: The terminal device receives the second operation.

[0269] The second operation is used to trigger the second control. The second operation is similar to the first operation, and the second control is similar to the first control. For a detailed explanation of the second operation and the second control, please refer to the descriptions of the first operation and the first control in steps 703 and 704 above. They will not be repeated here.

[0270] When a user triggers (or operates or activates) a second control on the second interface of the terminal device in a specific manner (such as by tapping with a finger), the terminal device will receive (or detect) the second operation.

[0271] Step A2: The terminal device responds to the second operation and displays a third interface; wherein, the third interface can be the exercise blood glucose history interface 1005 in Figure 10C below.

[0272] The third interface may include one or more of the following: exercise glucose risk curve, exercise history glucose report, or exercise guidance information.

[0273] The exercise glucose risk curve can be used to describe the trend of exercise glucose risk over time in the second period. The exercise glucose risk curve can be the exercise glucose risk curve 1007 in Figure 10C below; the exercise glucose risk curve can also be understood as the historical exercise glucose risk curve.

[0274] The aforementioned exercise-induced blood glucose risk can be one of the following: the number of times blood glucose changes before and after exercise exceed the first threshold, the percentage of times blood glucose changes before and after exercise exceed the first threshold, or the average probability value of blood glucose changes before and after exercise exceeding the first threshold.

[0275] The number of times the change in blood glucose before and after exercise exceeds the first threshold can be understood as the number of times the user's blood glucose changes exceed the first threshold after exercise (also known as after the type of exercise behavior) within a specific time period (such as one day, one week, or one month); the first threshold can be 3 mmol / L or 4 mmol / L, etc.; the change in blood glucose before and after exercise (also known as before and after the type of exercise behavior) can be 2 mmol / L or 3 mmol / L, etc.

[0276] The percentage of changes in blood glucose levels before and after exercise exceeding the first threshold can be understood as the proportion of times a user's blood glucose levels before and after exercise exceeded the first threshold within a specific time period, out of the total number of times blood glucose levels before and after exercise were monitored. For example, if the terminal device monitored blood glucose levels before and after exercise 3 times in one day, and the blood glucose levels before and after exercise exceeded the first threshold in 2 of those times, then the percentage of the user's blood glucose levels before and after exercise exceeding the first threshold is two-thirds (i.e., 67%).

[0277] The average probability of blood glucose changes exceeding the first threshold before and after exercise can be understood as the likelihood (or probability) of an abnormal decrease in blood glucose after exercise within a specific time period. It can usually be obtained by calculating the average probability of blood glucose changes exceeding the first threshold multiple times. For example, if the terminal device monitors blood glucose changes before and after exercise 3 times in a day, and the first monitoring result indicates a 30% probability of an abnormal decrease in blood glucose, the second monitoring result indicates a 90% probability of an abnormal decrease in blood glucose, and the third monitoring result indicates a 60% probability of an abnormal decrease in blood glucose, then the average probability of an abnormal decrease in blood glucose before and after exercise is approximately 60% (i.e., (30% + 90% + 60%) ÷ 3).

[0278] In some application scenarios, users can trigger a second control to display a third interface on the terminal device. The third interface shows users information such as the exercise blood glucose risk curve within a second time period (i.e., a certain historical time period), so that users can understand the changes in historical exercise blood glucose risk. This design not only makes it easier for users to comprehensively review and analyze their own blood glucose status, but also helps users adjust their blood glucose control strategies to ensure that blood glucose levels are maintained within a healthy range, thereby achieving more refined blood glucose management.

[0279] For exercise history blood glucose reports and / or exercise guidance information, as shown in Figures 10D and 10E below; the exercise history blood glucose report can be understood as a report on the user's blood glucose levels and their trends before and after exercise each day (or each time) within a second time period (such as a week, a month, etc.). It may include, but is not limited to, the user's exercise habits and the pattern of changes in exercise-induced blood glucose risk within the second time period. Among them, exercise habits may include, but are not limited to, the regularity of the number of times of exercise per day, the amount of exercise per time, and the exercise time. The pattern of changes in exercise-induced blood glucose risk can be understood as the trend and characteristics of changes in blood glucose before and after exercise when the user follows specific exercise habits.

[0280] In some examples, the exercise guidance information mentioned above may include, but is not limited to, at least one of the following: single exercise volume, exercise frequency, or exercise type; wherein, single exercise volume can be understood as the amount of exercise achieved each time exercise is performed; this amount of exercise can be measured by exercise duration (e.g., 30 minutes of running each time), exercise intensity (e.g., moderate intensity), or the number of calories burned; exercise frequency can be understood as the number of times exercise is performed within a specific period of time, such as the number of times exercise is performed per week or per month; for example, if a user exercises 3 times a week, the exercise frequency is 3 times / week; exercise type can be understood as the type of exercise performed by the user, such as aerobic exercise (e.g., running, swimming, cycling, etc.), strength training (e.g., weightlifting, doing push-ups), flexibility training (e.g., yoga, stretching, etc.).

[0281] In this embodiment, the terminal device intuitively displays the exercise history blood glucose report through a third interface, which helps users clearly understand their blood glucose response at different times and under different exercise behaviors, thereby increasing users' attention to blood glucose management. In addition, displaying exercise guidance information through the third interface can help users optimize their subsequent exercise habits, ensure that blood glucose remains stable at a healthy level, and achieve more refined blood glucose management.

[0282] It should be noted that when the terminal device provides feedback on historical exercise blood glucose levels to the user, in addition to assisting the user in viewing the historical exercise blood glucose levels through the second control and the third interface as mentioned above, the historical exercise blood glucose levels can also be displayed directly on the second interface; for example, the user can view the historical exercise blood glucose details by swiping up and down on the second interface. Of course, the terminal device can also have other ways of presenting historical exercise blood glucose details, and this application embodiment does not limit the interface where the historical exercise blood glucose details are located or the viewing method.

[0283] In some other embodiments, when the first prompt information is used to prompt the blood glucose monitoring results corresponding to the sleep behavior type associated with the first time period (i.e., another example of the target behavior type), the aforementioned first control can also serve as a control for viewing sleep blood glucose details; the user can operate the first control in some way (such as by clicking, swiping, etc.).

[0284] Since users may need to view more detailed sleep blood glucose information in some application scenarios, the terminal device can provide a first control to display sleep blood glucose details while displaying the first prompt information on the first interface. This allows users to easily access more detailed information about the blood glucose monitoring results associated with their sleep behavior type by triggering the first control at any time.

[0285] In some other embodiments, when the user behavior type is sleep behavior type, the third information mentioned above may include, but is not limited to, at least one of the sleep behavior type, the number of times the sleep behavior type occurs, or the time when the sleep behavior type occurs, and the fourth information may include the blood glucose monitoring results associated with the sleep behavior type associated with the first time period.

[0286] The sleep behavior type can be referred to the relevant explanation in step 701 above, and will not be repeated here; the frequency of the sleep behavior type can be 2 times / day or 3 times / day, etc., and the time of the sleep behavior type can be from 13:00 to 14:00 at noon, or from 21:00 the previous night to 6:00 the next morning, etc.; the blood glucose monitoring results associated with the sleep behavior type can be abnormally low blood glucose after nap, or abnormally low blood glucose after waking up the next morning, etc.

[0287] In some application scenarios, users can trigger a first control to display a second interface on the terminal device. The terminal device then uses the second interface to show users detailed sleep blood glucose information, such as sleep behavior type and the frequency of occurrence of sleep behavior type. This allows users to clearly understand the impact of sleep behavior type on blood glucose levels, thereby encouraging them to flexibly adjust their sleep habits according to actual conditions and ensure that blood glucose is maintained stably within the healthy range.

[0288] It should be noted that since a fixed time period (such as the first time period) is usually associated with a target behavior type (such as one of the eating behavior type, exercise behavior type, or sleep behavior type), the second control can be used to view one of the following within the fixed time period: historical meal blood glucose, historical exercise blood glucose, or historical sleep blood glucose.

[0289] The above introduced an example of using the second control to view historical blood glucose levels during meals and exercise. Below, we will continue to introduce an example of using the second control to view historical blood glucose levels during sleep.

[0290] In some embodiments, when the user behavior type is sleep behavior, the second control on the second interface can be used to view historical sleep blood glucose levels, and the method 700 may further include the following steps:

[0291] Step B1: The terminal device receives the second operation.

[0292] The second operation can be used to trigger the second control; the second operation is similar to the first operation, and the second control is similar to the first control. For details, please refer to the relevant descriptions of the first operation and the first control in steps 703 and 704 above, which will not be repeated here.

[0293] When a user triggers (or operates or activates) a second control on the second interface of the terminal device in a certain way (e.g., by tapping with a finger), the terminal device can receive (or detect) the second operation.

[0294] Step B2: The terminal device responds to the second operation and displays a third interface; wherein, the third interface can be the sleep blood glucose history interface 1105 in Figure 11C below.

[0295] The third interface may include at least one of the following: a sleep glucose risk curve, a sleep history glucose report, or sleep guidance information.

[0296] The sleep glucose risk curve can be used to describe the trend of sleep glucose risk over time in the second period. The sleep glucose risk curve can be the sleep glucose risk curve 1107 in Figure 11C below; the sleep glucose risk curve can also be understood as the historical sleep glucose risk curve.

[0297] The aforementioned sleep blood glucose risk can be one of the following: the number of times sleep blood glucose changes exceed the second threshold, the percentage of sleep blood glucose changes exceeding the second threshold, or the average probability of sleep blood glucose changes exceeding the second threshold.

[0298] The number of times the blood glucose level changes during sleep exceeds the second threshold can be understood as the number of times the user's blood glucose level changes exceed the second threshold within a specific time period (such as within a day, a week, or a month) before and after sleep (also known as before and after sleep behavior type) or during sleep (also known as during sleep behavior type); the second threshold can be 3 mmol / L or 4 mmol / L, etc.; the blood glucose level changes before and after sleep (or during sleep) can be 2 mmol / L or 3 mmol / L, etc.

[0299] The percentage of sleep blood glucose changes exceeding the second threshold can be understood as the proportion of times a user's sleep blood glucose changes exceed the second threshold within a specific time period, out of the total number of sleep blood glucose change monitoring sessions. For example, if a terminal device monitors sleep blood glucose changes 3 times in a day, and the sleep blood glucose changes exceed the second threshold in 2 of those monitoring sessions, then the user's sleep blood glucose changes exceeding the second threshold account for two-thirds (i.e., 67%).

[0300] The average probability of blood glucose changes exceeding the second threshold during sleep can be understood as the likelihood of an abnormal decrease in blood glucose after a user falls asleep (or after a specific sleep behavior pattern) within a specific time period. It can usually be obtained by calculating the average probability of blood glucose changes exceeding the second threshold multiple times during sleep. For example, if the terminal device monitors blood glucose changes during sleep three times in one day, and the first monitoring result indicates a 40% probability of an abnormal decrease in blood glucose, the second monitoring result indicates an 80% probability of an abnormal decrease in blood glucose, and the third monitoring result indicates a 30% probability of an abnormal decrease in blood glucose, then the average probability of an abnormal decrease in blood glucose before and after sleep is approximately 50% (i.e., (40% + 80% + 30%) ÷ 3).

[0301] In some application scenarios, users can also trigger a second control to display a third interface on the terminal device. This third interface can show users information such as the sleep blood glucose risk curve within a second time period (i.e., a certain historical time period), so that users can understand the changes in historical sleep blood glucose risk. This design not only makes it easier for users to comprehensively review and analyze their own blood glucose status, but also helps users adjust their blood glucose control strategies to ensure that blood glucose levels are maintained within a healthy range, thereby achieving more refined blood glucose management.

[0302] For sleep history blood glucose reports and / or sleep guidance information, as shown in Figures 11D and 11E below; the sleep history blood glucose report can be understood as a report on the user's blood glucose levels and their trends before and after sleep or during sleep each day (or each time) within a second time period (such as a week, a month, etc.). It may include, but is not limited to, the user's sleep habits and the pattern of changes in sleep blood glucose risk within the second time period. Among them, sleep habits may include, but are not limited to, the regularity of the number of times of sleep per day, the amount of sleep per sleep, and the sleep duration. The pattern of changes in sleep blood glucose risk can be understood as the trend and characteristics of changes in blood glucose before and after sleep or during sleep when the user follows specific sleep habits.

[0303] In some examples, the aforementioned sleep guidance information may include, but is not limited to, adjustments to sleep schedules and / or dietary adjustments. Adjustments to sleep schedules can be understood as changing daily sleep and wake-up habits, and rationally arranging daily activities to establish a regular biological clock, thereby ensuring blood sugar levels remain normal. This may include, but is not limited to, establishing regular sleep times and adjusting pre-sleep activities, such as trying to fall asleep and wake up at the same time every day to ensure sufficient sleep time and establish a stable biological clock; and relieving tension and anxiety before bed through listening to music, meditation, or other methods to help fall asleep more easily.

[0304] Dietary adjustments can be understood as maintaining physical health and nutritional balance by rationally combining meals, controlling food intake, and choosing healthy foods. This can include, but is not limited to, balancing dietary structure, controlling food portions, and eating at regular times and in fixed quantities. For example, a balanced dietary structure ensures that daily meals include the five major food groups: grains, vegetables, fruits, protein, and dairy products; rationally combining these foods ensures sufficient nutrient intake. Controlling food portions: using smaller plates helps control food intake, and regularly recording eating habits and self-monitoring can help identify and adjust overeating habits. Eating at regular times and in fixed quantities: developing a habit of eating three meals a day at regular times ensures a continuous supply of nutrients.

[0305] In this embodiment, the terminal device intuitively displays the sleep history blood glucose report through a third interface, which helps users to clearly understand their blood glucose response at different times and under different sleep behaviors, thereby increasing the user's attention to blood glucose management. In addition, displaying sleep guidance information through the third interface can help users optimize their current exercise habits and ensure that blood glucose is stable at a healthy level, thereby achieving more refined blood glucose management.

[0306] It should be noted that when the terminal device provides feedback on historical sleep blood glucose levels to the user, in addition to assisting the user in viewing historical sleep blood glucose levels through the second control and the third interface as mentioned above, it can also directly display historical sleep blood glucose levels on the second interface; for example, the user can view historical sleep blood glucose details by swiping up and down on the second interface. Of course, the terminal device can also have other ways of presenting historical sleep blood glucose details, and this application embodiment does not limit the interface where the historical sleep blood glucose details are located or the viewing method.

[0307] In some other embodiments, the method 700 described above may further include the following steps:

[0308] Step C1: The terminal device receives the third operation on the first interface and displays the fourth interface.

[0309] It should be noted that the third operation can be understood as an operation on a certain control on the first interface, or an operation on a certain activatable area on the first interface, etc. The embodiments of this application do not limit the specific object on the first interface to which the third operation is performed. In actual applications, developers can design the object on the first interface to which the third operation is performed according to the specific scenario.

[0310] For example, in some examples, the first interface mentioned above may also include: a third control, which can be used to view fifth information and / or sixth information, wherein the fifth information is used to reflect the overall situation of abnormal blood glucose changes within a preset period, and the sixth information is used to reflect the blood glucose monitoring results associated with user behavior types within the preset period; the third operation mentioned above can be used to trigger the third control; the understanding of the third operation is similar to that of the first operation, and the understanding of the third control is similar to that of the first control. For details, please refer to the relevant descriptions of the first operation and the first control in steps 703 and 704 above, which will not be repeated here.

[0311] For example, the third control can be the overview control 1201 in Figure 12A below; the third operation can be the user clicking on the "overview control 1201".

[0312] When a user triggers (or operates or activates) a third control on the first interface of a terminal device in a certain way (e.g., by tapping with a finger), the terminal device can receive (or detect) the third operation on the first interface.

[0313] In some examples, the terminal device may respond to a third operation by displaying a fourth interface; wherein the fourth interface may be the blood glucose health overview interface 1202 in Figure 12B below.

[0314] The fourth interface may include, but is not limited to, fifth information and / or sixth information; the aforementioned preset period may include a first time period, which may be 24 hours a day, 12 hours, or a week, etc. The embodiments of this application do not limit the value of the preset period.

[0315] The sixth piece of information mentioned above may include, but is not limited to, at least one of the following: blood glucose monitoring results associated with meal behavior type (such as breakfast), blood glucose monitoring results associated with exercise behavior type (such as running), or blood glucose monitoring results associated with sleep behavior type (such as before bed).

[0316] For example, the fifth piece of information mentioned above can be an overview of blood glucose throughout the day as shown in Figure 12B below, and the sixth piece of information can be one or more of the following: an overview of blood glucose during meals, an overview of blood glucose during exercise, or an overview of blood glucose during sleep as shown in Figure 12B below.

[0317] In this embodiment, the user can also trigger a third control to display a fourth interface on the terminal device. This fourth interface can not only present a comprehensive picture of abnormal blood glucose changes within a preset period, but also present blood glucose monitoring results associated with all user behavior types, so that the user can intuitively and clearly grasp the blood glucose status within the entire preset period.

[0318] In some embodiments, the method 700 described above may further include the following steps:

[0319] Step D1: The terminal device receives the fourth operation on the fourth interface and displays the sixth interface.

[0320] It should be noted that the fourth operation can be understood as an operation on a certain control on the fourth interface, or as an operation on a certain activatable area on the fourth interface, etc. The embodiments of this application do not limit the specific object on the fourth interface to which the fourth operation is performed. In actual applications, developers can design the object on the fourth interface to which the fourth operation is performed according to the specific scenario.

[0321] For example, in some examples, the fourth interface mentioned above may also include a fourth control, which can be used to view the detailed content of the fifth information; the fourth operation mentioned above can be used to trigger the fourth control; the understanding of the fourth operation is similar to that of the first operation, and the understanding of the fourth control is similar to that of the first control. For details, please refer to the relevant descriptions of the first operation and the first control in steps 703 and 704 above, which will not be repeated here.

[0322] For example, the fourth control could be the details control 1204 corresponding to the daily blood glucose level in Figure 12B below; the fourth operation could be the user clicking on "details control 1204".

[0323] When a user triggers (or operates or activates) a fourth control on the fourth interface of a terminal device in some form (such as by tapping with a finger), the terminal device can receive (or detect) the fourth operation on the fourth interface.

[0324] In some examples, the terminal device may respond to a fourth action by displaying a fifth interface.

[0325] The fifth interface may include, but is not limited to, the total number of blood glucose monitoring sessions and / or the total number of abnormal blood glucose changes. The total number of blood glucose monitoring sessions can be understood as the number of times blood glucose is monitored within a preset period (such as one day, one week, or one month). The total number of abnormal blood glucose changes can be understood as the number of times abnormal blood glucose changes are detected within a preset period, which can reflect the stability and volatility of the user's blood glucose control. Abnormal blood glucose changes can include abnormally high blood glucose and abnormally low blood glucose. It should be noted that abnormally high blood glucose can sometimes be called hyperglycemia, and abnormally low blood glucose can sometimes be called hypoglycemia. The fifth interface can be the 24-hour blood glucose details interface 1205 in Figure 12D below.

[0326] In this embodiment, the user can also trigger the fourth control to display a fifth interface on the terminal device; the fifth interface displays the total number of blood glucose monitoring and / or the total number of abnormal blood glucose changes, so that the user can quickly understand the blood glucose status within the entire preset period.

[0327] In some embodiments, the method 700 described above may further include the following steps:

[0328] Step E1: The terminal device receives the fifth operation on the fifth interface and displays the sixth interface.

[0329] It should be noted that the fifth operation can be understood as an operation on a certain control on the fifth interface, or as an operation on a certain activatable area on the fifth interface, etc. The embodiments of this application do not limit the specific object on the fifth interface to which the fifth operation is performed. In actual applications, developers can design the object on the fifth interface to which the fifth operation is performed according to the specific scenario.

[0330] For example, in some examples, the fifth interface mentioned above may also include a fifth control, which can be used to trigger the fifth control. The understanding of the fifth operation is similar to that of the first operation, and the understanding of the fifth control is similar to that of the first control. For details, please refer to the relevant descriptions of the first operation and the first control in steps 703 and 704 above, which will not be repeated here.

[0331] For example, the fifth control can be the history comparison control 1301 in Figure 13A below; the fifth operation can be the user clicking on the "history comparison control 1301".

[0332] When a user triggers (or operates or activates) a fifth control on the fifth interface of a terminal device in a specific manner (such as by tapping with a finger), the terminal device can receive (or detect) the fifth operation on the fifth interface.

[0333] In some examples, the terminal device may respond to the fifth operation by displaying a sixth interface; the sixth interface may be the daily blood glucose risk history interface 1302 in Figure 13B below; the sixth interface may include seventh and / or eighth information, wherein the seventh information may be used to describe the trend of total blood glucose risk over time in the second period, and the seventh information may be the daily blood glucose risk history curve 1303 on interface 1302 in Figure 13B; the total blood glucose risk may be one of the following: the number of abnormal changes in total blood glucose, the proportion of abnormal changes in total blood glucose, or the average probability value of abnormal changes in total blood glucose.

[0334] The total number of abnormal blood glucose changes can be understood as the number of times a user's blood glucose levels change abnormally within a second time period (e.g., one day, one week, one month, etc.). This indicator can be used to reflect the stability and fluctuation of blood glucose control. When the total number of abnormal blood glucose changes is high, it indicates that the user's blood glucose control is poor and the blood glucose control strategy needs to be adjusted.

[0335] The percentage of total abnormal blood glucose changes can be understood as the proportion of abnormal blood glucose changes in the second time period out of the total number of blood glucose monitoring times. This indicator can also be used to reflect the stability and fluctuation of blood glucose control. When the percentage is high, it indicates that abnormal blood glucose changes are more frequent and blood glucose control strategies need to be adjusted.

[0336] The average probability of abnormal blood glucose changes can be understood as the likelihood (or probability) of a user experiencing abnormal blood glucose changes during the second time period. It can usually be obtained by calculating the average probability of abnormal blood glucose changes corresponding to the amount of blood glucose change exceeding the third threshold multiple times before and after (or during) a certain behavior. For example, the second time period can be a week. If the terminal device monitors blood glucose changes during sleep 3 times on a certain day of the week, and the first monitoring result (i.e., the monitoring result of blood glucose change exceeding the third threshold before and after sleep) indicates a 90% probability of abnormal blood glucose decrease, the second monitoring result indicates a 70% probability of abnormal blood glucose decrease, and the third monitoring result indicates a 20% probability of abnormal blood glucose decrease, then the average probability of abnormal blood glucose decrease before and after sleep is approximately 60% (i.e., (90% + 70% + 20%) ÷ 3).

[0337] The aforementioned eighth information may include at least one of the following: meal glucose risk curve, exercise glucose risk curve, or sleep glucose risk curve. The meal glucose risk curve, exercise glucose risk curve, and sleep glucose risk curve can be referred to the relevant descriptions in steps 707, A2, and B2 above, respectively, and will not be repeated here. The eighth information may be curves 1307, 1309, and 1311 on interface 1302 in Figure 13C.

[0338] In this embodiment, the terminal device intuitively displays the seventh information in a graphical manner (such as a curve graph) through the sixth interface, providing users with a global overview of blood glucose management during the second time period. At the same time, the sixth interface displays the eighth information, including meal blood glucose risk curves, exercise blood glucose risk curves, and sleep blood glucose risk curves. This allows users to not only further understand the specific situation of blood glucose management under different lifestyle behaviors, but also to formulate more scientific and reasonable blood glucose management strategies based on historical risk trends, thereby effectively reducing the risk of abnormal blood glucose and improving quality of life.

[0339] In other embodiments, the sixth interface may further include a sixth control that can be used to view overall health guidance information. This sixth control may be the "Health Summary 1306" control shown in Figure 13B below; for example, a user can click the "Health Summary 1306" control to view overall health guidance information on the blood glucose health prompt interface 1312 shown in Figure 13D below.

[0340] The overall health guidance information may include, but is not limited to, blood glucose monitoring recommendations and / or behavioral adjustment recommendations. Blood glucose monitoring recommendations can be understood as suggestions regarding the timing and frequency of blood glucose monitoring. For example, the device may suggest that users monitor their blood glucose at times such as fasting, 2 hours after meals, before bedtime, and in the early morning (an example of blood glucose monitoring time). Another example is the blood glucose monitoring frequency, which could be twice a week.

[0341] Behavioral modification suggestions can be understood as providing users with behavioral modification methods based on blood glucose monitoring results to help them better control their blood glucose levels; for example, behavioral modification suggestions could include adjusting dietary structure, eating regularly, and exercising more.

[0342] In this embodiment, the terminal device displays a sixth control through a sixth interface, so that users can view the overall health guidance information through the sixth control, thereby providing users with a comprehensive blood glucose management strategy to help users better manage their blood glucose levels.

[0343] In some other embodiments, the above method may further include the following steps:

[0344] Step F1: The terminal device receives the sixth operation on the fourth interface.

[0345] It should be noted that the sixth operation can be understood as an operation on a certain control on the fourth interface, or as an operation on a certain activatable area on the fourth interface, etc. The embodiments of this application do not limit the specific object on the fourth interface to which the sixth operation is performed. In actual applications, developers can design the object on the fourth interface to which the sixth operation is performed according to the specific scenario.

[0346] For example, in some examples, the fourth interface mentioned above may also include a seventh control, which can be used to view the detailed content of the sixth information; wherein, the sixth operation can be used to trigger the seventh control; the sixth operation is similar to the first operation, and the seventh control is similar to the first control. For details, please refer to the relevant descriptions of the first operation and the first control in steps 703 and 704 above, which will not be repeated here.

[0347] For example, the seventh control could be the details control 1211 corresponding to the sleep blood glucose level in Figure 12F below; the sixth operation could be the user clicking on "details control 1211".

[0348] When a user triggers (or operates or activates) the seventh control on the fourth interface of the terminal device in a specific way (such as by tapping with a finger), the terminal device can receive (or detect) the sixth operation on the fourth interface.

[0349] In some examples, the terminal device may respond to the sixth operation by displaying the seventh interface.

[0350] The seventh interface may include, but is not limited to, behavior identification controls and / or detailed content of blood glucose monitoring results associated with user behavior types; the seventh interface may be the sleep blood glucose details interface 1212 in Figure 12G below; the behavior identification control can be used to identify blood glucose monitoring information corresponding to user behavior types, and may include at least one of meal identification controls, exercise identification controls, or sleep identification controls. For example, meal identification controls may be breakfast identification controls, lunch identification controls, etc., exercise identification controls may be aerobic exercise identification controls, anaerobic exercise identification controls, etc., and sleep identification controls may be bedtime identification controls, sleep onset identification controls, and light sleep identification controls, etc., as described in the relevant description in Figure 12D below.

[0351] The aforementioned dining identification control can be used to identify blood glucose monitoring information associated with dining behavior types; this blood glucose monitoring information may include, but is not limited to, blood glucose monitoring time, dining behavior type and its associated blood glucose monitoring results; wherein, the blood glucose monitoring results may include the following: abnormal increase in blood glucose after dining behavior type (such as breakfast).

[0352] The exercise identification control can be used to identify blood glucose monitoring information associated with exercise behavior types; this blood glucose monitoring information may include, but is not limited to, blood glucose monitoring time, exercise behavior type and its associated blood glucose monitoring results; wherein, the blood glucose monitoring results may include the following: abnormal decrease in blood glucose after exercise behavior type (such as running).

[0353] The sleep label control can be used to identify blood glucose monitoring information associated with sleep behavior types; this blood glucose monitoring information may include, but is not limited to, blood glucose monitoring time, sleep behavior type and its associated blood glucose monitoring results; wherein, the blood glucose monitoring results may include the following: abnormal decrease in blood glucose after a sleep behavior type (such as light sleep).

[0354] The aforementioned behavior identifier controls can be displayed on the seventh interface in the form of virtual buttons or floating buttons.

[0355] The terminal device can intuitively reflect the blood glucose monitoring information associated with a user behavior type by controlling the appearance of the behavior identifier control. For example, when the appearance of the behavior identifier control is inactive (e.g., grayed out and unclickable), it indicates that the blood glucose monitoring information corresponding to the user behavior type identified by the behavior identifier control is within the normal range. When the appearance of the behavior identifier control is active (e.g., lit up and clickable), it indicates that the blood glucose monitoring information associated with the user behavior type identified by the behavior identifier control is abnormal. At this time, the user can click on the behavior identifier control to view the blood glucose monitoring information associated with the user behavior type, as shown in interface 1210 in Figure 12E and interface 1213 in Figure 12H. In this way, the user can quickly distinguish which blood glucose monitoring results corresponding to which behavior identifier controls are normal and which blood glucose monitoring information is abnormal by observing the active state of the behavior identifier controls. For a detailed description, please refer to the examples in Figures 12D to 12J below, which will not be elaborated here.

[0356] In this embodiment, the terminal device displays a seventh control on the fourth interface, allowing the user to access detailed blood glucose monitoring results associated with a specific user behavior type (e.g., eating, exercising, or sleeping) in the sixth information at any time. For example, after the user triggers the seventh control, the terminal device displays the blood glucose monitoring results for the user behavior type on the seventh interface and helps the user quickly view the required information by displaying behavior identification controls, such as those corresponding to eating, exercising, and sleeping behaviors. This eliminates the need to frequently switch between multiple interfaces, simplifying the operation process, improving information acquisition efficiency, and effectively reducing device energy consumption.

[0357] The above text details the blood glucose monitoring method 700 provided in this application. Below, using an example of a smartwatch (hereinafter referred to as a watch) as the terminal device, we will introduce the application of method 700 in different application scenarios.

[0358] Figure 8A shows a structural schematic diagram of a watch 800 (i.e., an example of a terminal device) provided in an embodiment of this application. The watch 800 may include, but is not limited to, a watch strap, a watch body, and a functional module. The watch strap is used to fix the watch body on the wearer's wrist. The watch body is the main part of the watch 800, and may include, but is not limited to, the mechanical parts, electronic parts, and a display screen for displaying time, prompts (such as first prompts), etc. The functional module can be used to realize specific functions of the watch 800. For example, the functional module can be a health monitoring module, such as a PPG module, for monitoring physiological indicators such as blood oxygen and blood sugar.

[0359] It should be noted that when the watch 800 performs blood glucose monitoring, it can provide feedback on the blood glucose monitoring results to the user at preset intervals (such as 15 minutes, 30 minutes or 1 hour as a time granularity) (such as a high blood glucose event after lunch), or it can provide feedback on the blood glucose monitoring results to the user in real time. This application embodiment does not limit this.

[0360] For example, Figure 8B shows the distribution of blood glucose data over 24 hours; when the watch 800 collects blood glucose data over 24 hours, it does so according to the preset single collection duration T (such as half an hour or 1 hour) and the preset collection interval; this distribution map may include, but is not limited to, hyperglycemic data, normal blood glucose data, invalid blood glucose data, and behavioral markers (such as breakfast, lunch, etc.); among them, the blood glucose assessment result corresponding to hyperglycemic data is a hyperglycemic event associated with a certain behavior (or an increase in blood glucose associated with a certain behavior), for example, hyperglycemic events occur after both breakfast and dinner; the blood glucose assessment result corresponding to non-hyperglycemic data is a non-hyperglycemic event associated with a certain behavior (or a normal or non-hyperglycemic event associated with a certain behavior). (Individual behavior-related decrease in blood glucose); invalid blood glucose data usually refers to data that cannot be used for blood glucose assessment, or data that, even if used for blood glucose assessment, has extremely low accuracy; for example, blood glucose data collected during some exercises (such as high-intensity exercise) is often considered invalid blood glucose data because it may be affected by various factors such as exercise, and cannot accurately reflect the true blood glucose status; in addition, when the user does not wear or does not wear the watch 800 correctly, the data collected by the watch 800 may only be noise data, not valid blood glucose data, and therefore, this noise data is also considered invalid blood glucose data; among them, the blood glucose assessment result corresponding to invalid blood glucose data is invalid blood glucose event (or blood glucose not detected).

[0361] It should be noted that in some optional embodiments, the distribution map shown in Figure 8B can also be displayed on other terminal devices capable of data interaction with the watch 800; for example, as shown in Figure 8C, the mobile phone 1 and the watch 800 can interact; the user can click the shortcut icon of "Health Management 801" on the main interface of the mobile phone 1 to enter the health management homepage 802; the user can view the "All-day Blood Glucose Monitoring Data 803" shown in Figure 8B in the blood glucose option of the homepage 802; by viewing data 803, the user can clearly understand the distribution of blood glucose data throughout the day on October 8th. For example, in the 24-hour blood glucose data, there are two instances of high blood glucose data, one after lunch, as shown in 804 in Figure 8D; and the other after dinner, as shown in 805 in Figure 8D; in addition, the user can also determine which time periods of data are valid and which time periods are invalid by viewing data 803.

[0362] It should also be noted that all blood glucose-related data on the watch 800 can be synchronously displayed in the health management 801. Users can use the health management 801 to view blood glucose monitoring results, weekly blood glucose reports, and health guidance information corresponding to various user behavior types. For example, users can view the overall blood glucose health information 806 in the health management 801, such as blood glucose throughout the day, blood glucose during sleep, blood glucose after meals, and blood glucose during exercise, as shown in Figure 8D.

[0363] The first scenario example (as shown in Figures 9A-9J)

[0364] As shown in Figure 9A, the user can click the "Vital Signs Monitoring 902" icon on the main interface 901 of the watch 800, causing the watch 800 to jump to the function selection interface 903, as shown in Figure 9B. On interface 903, after the user clicks the "Blood Glucose Health Research 904" icon, the watch 800 will jump to the main interface 905, as shown in Figure 9C. Immediately afterwards, the watch 800 will automatically switch from the main interface 905 to the blood glucose risk assessment interface 906. Optionally, after the user clicks the "Blood Glucose Health Research 904" icon, the watch 800 can also jump directly from interface 903 to interface 906 without going through interface 905.

[0365] Users can set the blood glucose monitoring period 907 on interface 906, for example, from October 8th to October 14th, as shown in Figure 9D. After setting the blood glucose monitoring period 907, users can click the "Start Assessment" button 908 to trigger the watch 800 to perform a week-long blood glucose assessment. The watch 800 can provide timely feedback on the blood glucose monitoring results to the user according to the preset collection interval (e.g., one hour as a time granularity). When the user clicks the "Start Assessment" button 908, the "Assessing..." indicator 909 will appear on interface 906, as shown in Figure 9E. In addition, when the user clicks the "Start Assessment" button 908, the watch 800 will update the original "Start Assessment" button 908 to the "Stop Assessment" button 910, as shown in Figure 9E.

[0366] If a user wants to view the blood glucose risk assessment results, they can perform an up swipe operation 911 on a certain area (such as a blank area) of interface 906, causing the watch 800 to switch to the blood glucose risk assessment results interface 912 (i.e., an example of the first interface), as shown in Figure 9F; on this interface 912, the user can also see meal blood glucose alert information (i.e., an example of the first alert information); this meal blood glucose alert information may include the following: a high blood glucose event was detected after your most recent meal; the user can trigger the "Meal Blood Glucose Details 913" control (i.e., an example of the first control), causing the watch 800 to enter the meal blood glucose details interface 914 (i.e., the second interface). As shown in Figure 9G, the interface 914 may include at least one of the following: meal detection results (i.e., an example of the third information) or meal-related key event details (i.e., an example of the fourth information); the meal detection results may include at least one of the following: number of meals on the day (i.e., an example of the number of times a meal behavior type occurs), the meal behavior type, and the time when the meal behavior type occurs; for example, the number of meals on the day may include the following: two meals were detected on the day; the meal behavior type may include the following: breakfast and lunch; the time when the meal behavior type occurs may include the following: breakfast at approximately 7:30 and lunch at approximately 12:25. The meal-related key event details (i.e., an example of the fourth information) may include, but are not limited to, the blood glucose monitoring results corresponding to the meal behavior type. For example, the blood glucose monitoring results corresponding to the meal behavior type may include the following: a postprandial hyperglycemia event was detected on the day, and blood glucose was abnormally elevated after lunch, as shown in Figure 9G.

[0367] In addition, the aforementioned interface 914 may also include a meal-related historical comparison control 915 (i.e., an example of the second control); the user can click on the control 915 to view the meal-related historical blood glucose levels, as shown in Figure 9G; in response to the user's click operation on the control 915, the watch 800 will switch to the meal blood glucose history interface 916 (i.e., an example of the third interface), as shown in Figure 9H; on this interface 916, the meal blood glucose risk curve 917 (i.e., an example of the meal blood glucose risk curve) for the previous week (i.e., an example of the second time period) will be displayed; the user can review the meal blood glucose situation of the previous week through this curve 917.

[0368] For example, as shown in Figure 9H, users can clearly see from curve 917 that the blood sugar risk during the meal on October 7 has exceeded the warning line 918. The warning line 918 can be understood as a risk threshold curve, for example, it can be a straight line segment with the risk threshold set at K1 (e.g., 80%). By reviewing the meal situation on October 7, users can adjust their subsequent diet accordingly to avoid abnormal increases in blood sugar again.

[0369] Optionally, users can also view the weekly meal blood glucose report 921 (an example of a meal history blood glucose report) corresponding to the curve 917 by swiping up on the interface 916 (919), as shown in Figure 9I. This weekly report 921 will show the user's eating habits and the changing pattern of meal blood glucose risk in the past week (i.e., the previous week). The eating habits may include the following: the number of meals you eat per day has fluctuated in the past week, with more meals eaten at night; and the changing pattern of meal blood glucose risk may include the following: your meal blood glucose risk has fluctuated and increased in the past week.

[0370] In addition, as shown in Figure 9H, users can also trigger the "Health Summary 920" control on interface 916 to bring the watch 800 into the meal blood glucose health summary interface 922, as shown in Figure 9J. This interface 922 will display meal health guidance information (i.e., an example of meal guidance information) to help users adjust their blood glucose management strategy. The meal health guidance information may include at least one of the following: regular eating, controlling carbohydrate intake, and the order of eating. For example, regular eating may include the following: it is recommended that you eat regularly and reduce the number of late-night snacks; controlling carbohydrate intake may include the following: choose foods with a low glycemic index (GI), such as whole grains and vegetables, which have a smaller impact on blood glucose; and the order of eating may include the following: the recommended order of eating is soup, vegetables, meat, and staple food, which can delay the rise in blood glucose after meals.

[0371] The second scenario example (as shown in Figures 10A-10E)

[0372] In some optional embodiments, when the watch 800 detects an exercise behavior type, the interface 912 shown in Figure 9F can also display exercise blood glucose alert information (another example of the first alert information); the exercise blood glucose alert information may include the following: an abnormal blood glucose change event was detected after your most recent exercise, as shown in Figure 10A; the user can trigger the "Exercise Blood Glucose Details 1002" control (another example of the first control) to make the watch 800 enter the exercise blood glucose details interface 1003 (an example of the second interface), as shown in Figure 10B; the interface 1003 may include at least one of the following: exercise detection results (another example of the third information) or details of key events associated with exercise (another example of the fourth information); wherein, the exercise detection results (another example of the third information) may include at least one of the following: exercise behavior type, number of times the exercise behavior type occurred, and time when the exercise behavior type occurred; for example, the number of times the exercise behavior type occurred may include: exercise has been detected twice on the same day; the exercise behavior type may include: running and swimming; the time when the exercise behavior type occurred may include: running at approximately 7:30 and swimming at approximately 19:00. Details of key events associated with exercise (another example of the fourth information) may include, but are not limited to, blood glucose monitoring results corresponding to the type of exercise behavior, such as the blood glucose change before and after exercise exceeding the K2 value on the same day (an example of the first threshold), or the blood glucose change after swimming exceeding the K2 value, as shown in Figure 10B.

[0373] In addition, interface 1003 may also include a historical comparison control 1004 related to exercise (i.e., an example of the second control); users can click on the control 1004 to view historical blood glucose levels related to exercise, as shown in Figure 10B; in response to the user's click operation on the control 1004, watch 800 will switch to the exercise blood glucose history interface 1005 (i.e., an example of the third interface), as shown in Figure 10C; this interface 1005 will display the exercise blood glucose risk curve 1007 (i.e., an example of the exercise blood glucose risk curve) for the previous week (i.e., an example of the second time period); users can review the exercise blood glucose situation of the previous week through curve 1007.

[0374] For example, as shown in Figure 10C, users can clearly see from curve 1007 that the exercise blood glucose risk on October 2nd and October 4th exceeded the warning line 1006. The warning line 1006 can also be understood as a risk threshold curve, for example, it can be a straight line segment with the risk threshold set at K2 (such as 90%). By reviewing the exercise situation on October 2nd and October 4th, users can adjust their subsequent exercise volume accordingly to avoid abnormal changes in blood glucose (such as a decrease) in the future.

[0375] Optionally, users can also view the previous week's exercise blood glucose weekly report 1010 (i.e., an example of an exercise history blood glucose report) corresponding to curve 1007 by performing an up swipe operation 1008 on interface 1005, as shown in Figure 10D; this weekly report 1010 will show the user's exercise habits and the changing pattern of exercise blood glucose risk in the past week (i.e., the previous week); among them, exercise habits may include the following: your daily exercise frequency has fluctuated in the past week, with more exercise in the morning; the changing pattern of exercise blood glucose risk may include the following: your exercise blood glucose risk has fluctuated too much in the past week.

[0376] In addition, as shown in Figure 10C, users can also click the "Health Summary 1009" control on interface 1005, causing watch 800 to respond to the click operation and enter the exercise blood glucose health summary interface 1011, as shown in Figure 10E. This interface 1011 will display exercise health guidance information (i.e., an example of exercise guidance information) to help users adjust their blood glucose management strategy. The exercise health guidance information may include at least one of the following: regular exercise and controlled exercise volume. Regular exercise may include the following: It is recommended that you exercise regularly and reduce the time spent exercising in the morning. Controlled exercise volume may include the following: Choose aerobic exercise (such as walking, running, Tai Chi, etc.).

[0377] The third scenario example (as shown in Figures 11A-11E)

[0378] In some embodiments, when the watch 800 detects a sleep behavior type, the interface 912 shown in Figure 9F may also display sleep blood glucose alert information (another example of the first alert information); the sleep blood glucose alert information may include the following: an abnormal blood glucose change event was detected after you fell into deep sleep at night, as shown in Figure 11A; the user can trigger the "Sleep Blood Glucose Details 1102" control (another example of the first control) to make the watch 800 enter the sleep blood glucose details interface 1103 (an example of the second interface), as shown in Figure 11B; the interface 1103 may include at least one of the following: sleep detection results The sleep monitoring results may include at least one of the following: the number of times a sleep behavior type occurred, the sleep behavior type, and the time of occurrence of the sleep behavior type. The number of times a sleep behavior type occurred may include: 4 sleep monitoring sessions during the night; the sleep behavior type may include: sleep onset, light sleep, deep sleep, and REM sleep; the time of occurrence of the sleep behavior type may include: sleep onset approximately 21:30, light sleep approximately 23:00, deep sleep approximately 00:30, and REM sleep approximately 06:00. The sleep-related key event details may include, but are not limited to: blood glucose monitoring results corresponding to the sleep behavior type, such as a nighttime blood glucose change exceeding the K3 value (an example of the second threshold), or a blood glucose change exceeding the K3 value after deep sleep, as shown in Figure 11B.

[0379] In addition, the interface 1103 may also include a sleep-related historical comparison control 1104; users can view historical blood glucose levels by triggering the control 1104, as shown in Figure 11B; in response to the user's click operation on the control 1104, the watch 800 will enter the exercise blood glucose history interface 1105, as shown in Figure 11C; this interface 1105 will display the sleep blood glucose risk curve 1107 (i.e., an example of the sleep blood glucose risk curve) for the previous week (i.e., the second time period); users can review the sleep blood glucose situation of the previous week through the curve 1107.

[0380] For example, as shown in Figure 11C, users can clearly see from curve 1107 that the risk of blood glucose during sleep on October 2nd, October 4th, and October 6th exceeded the warning line 1106; this warning line 1106 can also be understood as a risk threshold curve, for example, it can be a straight line segment with the risk threshold set at K3 (such as 70%); by reviewing the sleep patterns on October 2nd, October 4th, and October 6th, users can adjust their subsequent sleep habits accordingly to avoid abnormal changes in blood glucose (such as a decrease) in the future.

[0381] Optionally, users can also view the previous week's sleep blood glucose weekly report 1110 (i.e., an example of a sleep history blood glucose report) corresponding to curve 1107 by performing an up swipe operation 1108 on interface 1105, as shown in Figure 10D; this weekly report 1110 will show the user's sleep habits and the changing pattern of sleep blood glucose risk in the past week (i.e., the previous week); among them, sleep habits may include the following: in the past week, your blood glucose has fluctuated abnormally more during each night's sleep, and there have been more abnormal blood glucose fluctuations after deep sleep; the changing pattern of sleep blood glucose risk may include the following: in the past week, your sleep blood glucose risk has fluctuated too much.

[0382] In addition, as shown in Figure 11C, users can also trigger the "Health Summary 1109" control on interface 1105 to bring the watch 800 into the sleep blood glucose health summary interface 1111, as shown in Figure 11E. This interface 1111 will display sleep health guidance information (i.e., an example of sleep guidance information) to help users adjust their blood glucose management strategy. The sleep health guidance information may include at least one of the following: improving sleep quality and a reasonable diet. Improving sleep quality may include the following: maintaining a regular sleep schedule and avoiding staying up late and long-term insomnia. A reasonable diet may include the following: dinner should be light and moderate, and avoid consuming too much high-sugar and high-fat food, as shown in Figure 11E.

[0383] The fourth scenario example (as shown in Figures 12A-12H)

[0384] In some embodiments, the watch 800 can also provide the user with a blood glucose overview function; as shown in FIG12A, the user can trigger the "overview control 1201" (i.e., an example of the third control) on the interface 912 shown in FIG9F by clicking (as an example of the third operation), so that the watch 800 enters the blood glucose health overview interface 1202 (i.e., an example of the fourth interface); the interface 1202 can make it convenient for the user to view the blood glucose status throughout the day, as shown in FIG12B; the interface 1202 can include at least one of the following: a summary of blood glucose for a single day (e.g., October 8) (i.e., an example of a preset period) (i.e., an example of the fifth information), a summary of blood glucose during meals (i.e., an example of the sixth information), a summary of blood glucose during sleep (i.e., another example of the sixth information), and a summary of blood glucose during exercise (i.e., yet another example of the sixth information). For example, a summary of blood glucose levels throughout the day may include the following: more high blood glucose events today; a summary of blood glucose levels during sleep may include the following: less blood glucose fluctuations during sleep; a summary of blood glucose levels after meals may include the following: abnormally high blood glucose levels after lunch; a summary of blood glucose levels during exercise may include the following: less blood glucose fluctuations before and after exercise, as shown in Figures 12B and 12C; in addition, users can also browse the summaries of various blood glucose levels on interface 1202 by using the up and down swiping operation 1203 in Figure 12B.

[0385] It should be noted that, in addition to displaying an overview of various types of blood sugar on interface 1202, the Watch 800 also provides detailed controls for each type of blood sugar, allowing users to view the specific details of each type of blood sugar through these controls.

[0386] For example, as shown in Figure 12B, the user can click on the "Details Control 1204 for Blood Glucose Throughout the Day" (i.e., an example of the seventh control) (i.e., an example of the sixth operation) to make the watch 800 enter the Blood Glucose Throughout the Day Details Interface 1205 (i.e., an example of the seventh interface), as shown in Figure 12D; in some examples, the interface 1205 may include the total number of blood glucose monitoring (e.g., 68 times) and / or the total number of abnormal blood glucose changes (e.g., 10 times of hyperglycemia).

[0387] In some other embodiments, when the watch 800 detects an abnormal blood glucose monitoring result associated with a certain user behavior type, the abnormal blood glucose monitoring information corresponding to that user behavior type can be displayed intuitively on the interface 1205 in the form of a behavior identification control.

[0388] For example, as shown in Figure 12D, the interface 1205 may also include a behavior identification control; the watch 800 may use the behavior identification control to display at least one of the following: the user behavior type, the time when the user behavior type occurred, or the blood glucose monitoring result corresponding to the user behavior type.

[0389] It should be noted that the Watch 800 can align the display position of the behavior indicator control with the time on the edge of its watch face to present the time when the user's behavior type occurred. Furthermore, the Watch 800 can also display blood glucose monitoring information associated with the user's behavior type through the appearance of the behavior indicator control. For example, when the behavior indicator control is grayed out (or any other color, this is just an example) and inactive, it indicates that the blood glucose monitoring result corresponding to that user behavior type is within the normal range. When the behavior indicator control is lit up and clickable (i.e., the behavior indicator control is active), it indicates that the blood glucose monitoring result corresponding to that user behavior type is abnormal. Optionally, the user can click the behavior indicator control to view the potentially abnormal blood glucose monitoring result.

[0390] Since the behavior identification control may include at least one of the dining identification control, exercise identification control and sleep identification control, the watch 800 can display various user behavior types throughout the day on the interface 1205 in the form of behavior identification controls; optionally, the watch 800 may also display behavior identification controls on the interface 1205 indicating abnormal blood glucose monitoring results, which is not limited in this embodiment.

[0391] For example, as shown in Figure 12D, interface 1205 includes a breakfast indicator control 1206, a lunch indicator control 1207, an exercise indicator control 1208, and a sleep indicator control 1209. The display positions of these controls correspond to the time on the edge of the watch face of watch 800. The breakfast indicator control 1206 indicates that the user had breakfast around 7:30 AM. The breakfast indicator control 1206 is in an active, lit state, indicating that the blood glucose monitoring result corresponding to breakfast is abnormal. The user can access the blood glucose monitoring information corresponding to the meal behavior type by triggering the breakfast indicator control 1206 to view the blood glucose monitoring result for breakfast. The lunch indicator control 1207 indicates that the user had lunch around 12:00 PM. The lunch indicator control 1208... 07 is grayed out and inactive, indicating that the blood sugar level corresponding to lunch is within the normal range; Exercise icon control 1208 shows that the user performed a certain type of exercise (such as running) around 18:30 in the afternoon; Exercise icon control 1208 is lit up and active, indicating that the blood sugar level corresponding to this type of exercise is abnormal; The user can open the blood sugar monitoring information corresponding to this type of exercise by clicking on Exercise icon control 1208 to view the blood sugar monitoring results for this type of exercise; Similarly, Sleep icon control 1208 shows that the user performed a certain type of sleep activity around 21:30; Sleep icon control 1209 is grayed out and inactive, indicating that the blood sugar level corresponding to this type of sleep activity is within the normal range.

[0392] For example, taking the user clicking the exercise icon control 1208 as an example, after the user clicks the control 1208, the watch 800 will respond to the click operation and display the exercise blood glucose overview interface 1210, as shown in Figure 12E. This interface 1210 can be understood as a temporary interface, floating above the interface 1205. Through this interface 1210, the user can quickly understand the abnormal blood glucose monitoring information related to exercise. For example, the abnormal blood glucose monitoring information may include the following: the blood glucose change after running (around 18:30) exceeded the K2 value on the same day, and the blood glucose change after swimming (around 19:30) exceeded the K2 value. This method of displaying abnormal blood glucose monitoring information through a temporary interface avoids frequent switching between multiple interfaces, simplifies the operation process, and improves the efficiency of information acquisition.

[0393] Optionally, after the user clicks the control 1208, the watch 800 can also respond to the click operation and jump directly from the interface 1205 to the exercise blood glucose details interface 1003 shown in Figure 10B, omitting the creation of an intermediate temporary interface, thereby improving the efficiency of information display.

[0394] It should be noted that the content of the exercise blood glucose overview displayed on interface 1210 may be the same as or different from the content presented on exercise blood glucose details interface 1003 shown on 10B. This application embodiment does not limit this. For example, interface 1210 may display part of the content in interface 1003 (such as the blood glucose change exceeding the K2 value after running (around 18:30) and the blood glucose change exceeding the K2 value after swimming (around 19:30) on the same day).

[0395] For example, as shown in Figure 12F, the user can click on the "Details Control 1211 for Sleep Blood Glucose" (an example of the seventh control) in interface 1202 (an example of the sixth operation) to cause the watch 800 to enter the sleep blood glucose details interface 1212 (an example of the seventh interface). In some examples, this interface 1212 may include detailed information about blood glucose monitoring results associated with sleep behavior types. The detailed information about blood glucose monitoring results associated with sleep behavior types may include, but is not limited to, the sleep blood glucose monitoring time and blood glucose fluctuations during sleep. For example, the sleep blood glucose monitoring time may be 23:00-07:25; blood glucose fluctuations during sleep may include normal blood glucose before sleep, normal blood glucose during sleep, and normal blood glucose after sleep, as shown in Figure 12G.

[0396] Optionally, the interface 1212 may also include the aforementioned behavior identification control; for example, as shown in Figure 12G, after the user clicks the breakfast identification control 1206, the watch 800 will respond to the click operation and display the meal blood glucose overview interface 1213, as shown in Figure 12H; this interface 1213 can be understood as a temporary interface, floating on the interface 1212; optionally, the watch 800 may also respond to the click operation and jump directly from the interface 1212 to the meal blood glucose details interface 914 shown in Figure 9G; the user can view the blood glucose monitoring information associated with breakfast through this interface 1213; the blood glucose monitoring information may include the following: abnormal blood glucose levels detected at breakfast (approximately 7:30), lunch (approximately 12:45), and after lunch.

[0397] It should be noted that the content of the meal blood glucose overview displayed on interface 1213 may be the same as or different from the content presented on the meal blood glucose details interface 914 shown in Figure 9G. This application embodiment does not limit this. For example, interface 1213 may display part of the content in interface 914, such as abnormal blood glucose levels detected at breakfast (about 7:30), lunch (about 12:45) and after lunch.

[0398] It should also be noted that users can also click on the "Details Controls for Exercise-Related Blood Glucose" and "Details Controls for Meal-Related Blood Glucose" on the overview interface 1202 to view the detailed content of blood glucose monitoring results associated with exercise and meal, respectively. For specific operation methods, please refer to the above description of users viewing the detailed content of blood glucose monitoring results associated with sleep, which will not be repeated here.

[0399] It should be noted that, in addition to being displayed on blood glucose-related interfaces (such as interface 1205), this behavior identification control can also be displayed on the interfaces of other applications, such as the main interface of watch 800 or specific application interfaces (such as video playback interfaces). This application embodiment does not limit this.

[0400] For example, as shown in Figure 12I, the behavior indicator control can remain persistent on the interface. For instance, when the user exits from the vital signs monitor 902 and returns to the main interface 901 of the watch 800, the behavior indicator control remains visible on the main interface 901. Alternatively, the behavior indicator control can be displayed around the edge of the watch face of the watch 800. When a user wants to view the blood glucose monitoring information corresponding to a certain user behavior type, they can click the corresponding behavior indicator control to view the blood glucose monitoring information for that user behavior type. For example, when a user clicks the breakfast indicator control 1206 on the main interface 901, the watch 800 can respond to this click and display the meal blood glucose overview interface 1213, as shown in Figure 12J. This interface 1213 can be understood as a temporary interface, floating on the main interface 901. Optionally, the watch 800 can also respond to this click by starting the vital signs monitor 902 and directly jumping from the main interface 901 to the meal blood glucose details interface 914 shown in Figure 9G. Through interface 1213, users can view blood glucose monitoring information associated with meal behavior types; this blood glucose monitoring information may include the following: abnormal blood glucose levels detected at breakfast (approximately 7:30), lunch (approximately 12:45), and after lunch.

[0401] The fifth scenario example (as shown in Figures 13A-13E)

[0402] In some embodiments, as shown in FIG13A, a user can click on the historical comparison control 1301 (an example of the seventh control) on the interface 1205 shown in FIG12D (or the details interface 1212 shown in FIG12G) to view the historical 24-hour blood glucose details (i.e., the blood glucose details for each day within a preset period); the user performs a click operation on the control 1301 (an example of the fifth operation), causing the watch 800 to switch to the daily blood glucose risk history interface 1302 (an example of the sixth interface), as shown in FIG13B; the interface 1302 may include a daily blood glucose risk history curve 1303 (an example of the seventh information); the curve 1303 can be used to describe the user's daily blood glucose risk (i.e., the risk of blood glucose in the previous week (e.g., from October 1st to October 7th) (an example of the second time period)). (An example of total blood glucose risk) trend over time; where daily blood glucose risk can be understood as the number of abnormal changes in total blood glucose each day, the percentage of abnormal changes in total blood glucose each day, or the average probability value of abnormal changes in total blood glucose each day; users can review their daily blood glucose status in the previous week through curve 1303; for example, users can clearly see from curve 1303 that the daily total blood glucose risk from October 1st to October 7th did not exceed the warning line 1304; the warning line 1304 can also be understood as a risk threshold curve, for example, it can be a straight line segment with the risk threshold set at K4 (such as 70%) (i.e., an example of the third threshold); by reviewing the daily blood glucose status from October 1st to October 7th, users can have a comprehensive understanding of their blood glucose status in the previous week, thereby more effectively maintaining blood glucose within a healthy range.

[0403] In some optional embodiments, as shown in Figure 13C, interface 1302 may also include blood glucose risk curves corresponding to various user behavior types (i.e., an example of the eighth information), such as meal blood glucose risk curves, exercise blood glucose risk curves, or sleep blood glucose risk curves. In addition, users can view the blood glucose risk curves corresponding to various user behavior types on interface 1302 through the upward swipe operation 1305 in Figure 13B, as shown in Figure 13C. For example, users can review their daily meal blood glucose levels in the previous week through curve 1307. For instance, users can clearly see from curve 1307 that the meal blood glucose risk on October 4th has exceeded the warning line 1308. By reviewing the meal situation on October 4th, users can adjust their diet accordingly to prevent blood glucose from rising abnormally again.

[0404] For example, users can review their exercise blood glucose levels from the previous week using curve 1309. For instance, users can clearly see from curve 1309 that the exercise blood glucose risk on October 7 exceeded the warning line 1310. By reviewing their exercise on October 7, users can adjust their subsequent exercise levels accordingly to avoid abnormal changes in blood glucose levels (such as a decrease) in the future.

[0405] For example, users can review their blood sugar levels during sleep in the previous week through curve 1311; for example, users can clearly see from curve 1311 that the risk of blood sugar during sleep from October 1st to October 7th did not exceed the warning line 1310; by reviewing their sleep from October 1st to October 7th, users can gain a comprehensive understanding of their blood sugar levels in the previous week, thereby more effectively maintaining their blood sugar within a healthy range.

[0406] Optionally, as shown in Figure 13B, interface 1302 may also include a health summary 1306 control (i.e., an example of the sixth control); it can help users view total health guidance information; for example, users can trigger the "health summary 1306" control to make watch 800 jump to blood glucose health reminder interface 1312, as shown in Figure 13D; this interface 1312 may include, but is not limited to: health reminder information for blood glucose throughout the day (i.e., an example of total health guidance information); in some examples, the health reminder information for blood glucose throughout the day can be understood as total health guidance information generated by watch 800 based on the user's historical and daily blood glucose monitoring results; it may include at least one of the following: guidance information for blood glucose throughout the day, guidance information for blood glucose during sleep, guidance information for blood glucose during meals, or guidance information for blood glucose during exercise; for example, as shown in Figures 13D and 13E, guidance information for blood glucose throughout the day may include the following: there are more high blood glucose times today, and it is at a historical high level, so it is recommended to continue monitoring, etc.; guidance information for blood glucose during sleep may include the following: blood glucose fluctuations are small during sleep, but it has been rising recently.

[0407] It is recommended to continue monitoring. Guidance information on mealtime blood glucose can include the following: If blood glucose rises abnormally after lunch and occurs frequently, it is recommended to control lunch intake. Guidance information on exercise blood glucose can include the following: If blood glucose fluctuates significantly before and after exercise, it is recommended to control exercise intensity and monitor continuously, as shown in Figures 13D and 13E.

[0408] The foregoing section details examples of blood glucose monitoring methods provided in this application. It is understood that, to achieve the aforementioned functions, the terminal device includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, based on the units and algorithm steps described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application. This application can divide the blood glucose monitoring method into functional units based on the above method examples. For example, each function can be divided into separate functional units, or two or more functions can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. It should be noted that the unit division in this application is illustrative and merely a logical functional division; other division methods may exist in actual implementation, and this application does not limit this division.

[0409] Figure 14 shows a schematic diagram of the structure of a device provided in this application. The dashed lines in Figure 14 indicate that the unit or module is optional. Device 1400 can be used to implement the methods described in the above method embodiments. Device 1400 can be a terminal device, a server, or a chip (system).

[0410] Device 1400 includes one or more processors 1401, which can support the device 1400 in implementing the methods in the method embodiment corresponding to FIG7. Processor 1401 can be a general-purpose processor or a special-purpose processor. For example, processor 1401 can be a central processing unit (CPU). The CPU can be used to control device 1400, execute software programs, and process data from the software programs. Device 1400 may also include a communication unit 1405 for implementing signal input (reception) and output (transmission).

[0411] The aforementioned device 1400 may be a chip (system) including a memory and a processor, wherein the processor is configured to execute a computer program stored in the memory to implement the methods shown in the various embodiments above.

[0412] The communication unit 1405 may be an input and / or output circuit of the chip (system), or the communication unit 1405 may be a communication interface of the chip (system), and the chip (system) may be a component of the device 1400.

[0413] For example, communication unit 1405 may be a transceiver of device 1400, or communication unit 1405 may be a transceiver circuit of device 1400. Device 1400 may include one or more memories 1402, which store program 1404. Program 1404 may be executed by processor 1401 to generate instructions 1403, causing processor 1401 to execute the method described in the above method embodiments according to instructions 1403.

[0414] Optionally, the memory 1402 may also store data. Optionally, the processor 1401 may also read the data stored in the memory 1402, which may be stored at the same memory address as the program 1404, or the data may be stored at a different memory address than the program 1404.

[0415] The processor 1401 and memory 1402 can be configured separately or integrated together, for example, integrated on the system-on-chip (SOC) of the device. For details on how the processor 1401 executes the blood glucose monitoring method, please refer to the relevant description in the method embodiments.

[0416] It should be understood that the steps of the above method embodiments can be implemented by hardware logic circuits or software instructions in the processor 1401. The processor 1401 may be a CPU, a digital signal processor (DSP), a field programmable gate array (FPGA), or other programmable logic devices, such as discrete gate, transistor logic devices, or discrete hardware components.

[0417] This application also provides a computer program product that, when executed by processor 1401, implements the method of any of the method embodiments in this application. The computer program product can be stored in memory 1402, for example, it can be program 1404. Program 1404, after undergoing preprocessing, compilation, assembly, and linking processes, can ultimately be converted into an executable object file that can be executed by processor 1401.

[0418] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computer, implements the method of any of the method embodiments of this application. The computer program may be a high-level language program or an executable object program.

[0419] The computer-readable storage medium is, for example, memory 1402. Memory 1402 can be volatile memory or non-volatile memory, or memory 1402 can include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DRRAM).

[0420] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process and technical effects of the above-described apparatus and equipment can be referred to the corresponding processes and technical effects in the foregoing method embodiments, and will not be repeated here.

[0421] The systems, apparatuses, and methods disclosed in the embodiments provided in this application can be implemented in other ways. For example, some features of the method embodiments described above may be omitted or not performed. The apparatus embodiments described above are merely illustrative; the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Multiple units or components may be combined or integrated into another system. Furthermore, the coupling between units or components can be direct or indirect, including electrical, mechanical, or other forms of connection.

[0422] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

[0423] Finally, the above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for monitoring blood glucose, characterized in that, The method includes: First information and second information are determined. The first information is the blood glucose monitoring result corresponding to the first time period. The second information is the target behavior type associated with the first time period. The target behavior type is one of the user behavior types, including one or more of the following: eating behavior type, exercise behavior type, or sleep behavior type. A first prompt message is generated based on the first information and the second information. The first prompt message is used to prompt the blood glucose monitoring result associated with the target behavior type.

2. The method according to claim 1, characterized in that, The determination of the first information and the second information includes: Acquire first data, which is the physiological data corresponding to the first time period; Acquire second data, which is user behavior data associated with the first time period, and the user behavior data is used to determine the target behavior type; The first information is determined based on the first data; The second information is determined based on the second data.

3. The method according to claim 2, characterized in that, The acquisition of the first data includes: The first data is acquired using at least one of the following devices: an optical sensor, a temperature sensor, or a continuous glucose monitoring (CGM) system.

4. The method according to claim 2 or 3, characterized in that, Determining the second information based on the second data includes: The second data is subjected to behavior recognition by a user behavior model to obtain user behavior recognition results. The user behavior model is one or more of a dining behavior model, an exercise behavior model, or a sleep behavior model. The dining behavior model is used to identify the dining behavior type based on the user behavior data. The exercise behavior model is used to identify the exercise behavior type based on the user behavior data. The sleep behavior model is used to identify the sleep behavior type based on the user behavior data. The second information is determined based on the user behavior recognition results.

5. The method according to any one of claims 1 to 4, characterized in that, When the target behavior type is a dining behavior type, the first prompt information is used to prompt the blood glucose monitoring result associated with the dining behavior type; the dining behavior type includes at least one of the following: breakfast, lunch or dinner.

6. The method according to any one of claims 1 to 4, characterized in that, When the target behavior type is an exercise behavior type, the first prompt information is used to prompt the blood glucose monitoring result associated with the exercise behavior type; the exercise behavior type includes at least one of the following: aerobic exercise, anaerobic exercise, flexibility exercise, balance exercise, recreational exercise, or competitive exercise.

7. The method according to any one of claims 1 to 4, characterized in that, When the target behavior type is a sleep behavior type, the first prompt information is used to prompt the blood glucose monitoring result associated with the sleep behavior type; the sleep behavior type includes at least one of the following: before sleep, sleep onset period, light sleep period, deep sleep period, REM sleep period, or after sleep.

8. The method according to any one of claims 1 to 7, characterized in that, The first time period is one or more of the following: A period of time before the start of the target behavior type, a period of time after the end of the target behavior type, all periods of the duration of the target behavior type, or a portion of the duration of the target behavior type.

9. The method according to any one of claims 1 to 8, characterized in that, The method further includes: Display a first interface, the first interface including: the first prompt message and the first control; Receive a first operation, which is used to trigger the first control; In response to the first operation, a second interface is displayed. The second interface includes third information and fourth information. The third information includes at least one of the user behavior type, the number of times the user behavior type occurs, or the time when the user behavior type occurs. The fourth information includes the blood glucose monitoring result associated with the user behavior type. The preset time period includes the first time period.

10. The method according to claim 9, characterized in that, When the user behavior type is the dining behavior type, the second interface further includes a second control, which is used to view historical blood glucose levels after meals. The method further includes: Receive a second operation, which is used to trigger the second control; In response to the second operation, a third interface is displayed, which includes a meal blood glucose risk curve. The meal blood glucose risk curve is used to describe the trend of meal blood glucose risk over time in a second time period, which occurs before the first time period. The meal blood glucose risk is one of the following: the number of times postprandial hyperglycemia occurs, the proportion of postprandial hyperglycemia, or the average probability value of postprandial hyperglycemia.

11. The method according to claim 10, characterized in that, The third interface also includes a meal history blood glucose report and / or meal guidance information. The meal history blood glucose report includes the user's eating habits and the pattern of changes in meal blood glucose risk during the second time period. The meal guidance information includes at least one of the following: order of eating, type of eating, or dietary recommendations.

12. The method according to claim 9, characterized in that, When the user behavior type is the exercise behavior type, the second interface further includes a second control, which is used to view historical exercise blood glucose levels. The method further includes: Receive a second operation, which is used to trigger the second control; In response to the second operation, a third interface is displayed, the third interface including an exercise blood glucose risk curve, the exercise blood glucose risk curve being used to describe the trend of change of exercise blood glucose risk over time in a second time period, the second time period occurring before the first time period, the exercise blood glucose risk being one of the following: the number of times the change in blood glucose before and after exercise exceeds a first threshold, the percentage of the change in blood glucose before and after exercise exceeding the first threshold, or the average probability value of the change in blood glucose before and after exercise exceeding the first threshold.

13. The method according to claim 12, characterized in that, The third interface also includes exercise history blood glucose reports and / or exercise guidance information. The exercise history blood glucose reports include the user's exercise habits and the change pattern of exercise blood glucose risk during the second time period. The exercise guidance information includes at least one of the following: single exercise volume, exercise frequency, or exercise type.

14. The method according to claim 9, characterized in that, When the user behavior type is the sleep behavior type, the second interface further includes a second control, which is used to view historical sleep blood glucose levels. The method further includes: Receive a second operation, which is used to trigger the second control; In response to the second operation, a third interface is displayed, which includes a sleep blood glucose risk curve. The sleep blood glucose risk curve is used to describe the trend of sleep blood glucose risk over time in a second time period, which occurs before the first time period. The sleep blood glucose risk is one of the following: the number of times the sleep blood glucose change exceeds a second threshold, the percentage of sleep blood glucose changes exceeding the second threshold, or the average probability value of sleep blood glucose changes exceeding the second threshold.

15. The method according to claim 14, characterized in that, The third interface also includes a sleep history blood glucose report and / or sleep guidance information. The sleep history blood glucose report includes the user's sleep habits and the change pattern of sleep blood glucose risk during the second time period. The sleep guidance information includes methods for adjusting work and rest and / or adjusting diet.

16. The method according to any one of claims 9 to 15, characterized in that, The method further includes: A third operation is received on the first interface, and a fourth interface is displayed. The fourth interface includes the fifth information and / or the sixth information. The fifth information is used to reflect the overall situation of abnormal blood glucose changes within a preset period. The sixth information is used to reflect the blood glucose monitoring results associated with the user behavior type within the preset period. The preset period includes the first time period. The sixth information includes at least one of the following: blood glucose monitoring results associated with the eating behavior type, blood glucose monitoring results associated with the exercise behavior type, or blood glucose monitoring results associated with the sleep behavior type.

17. The method according to claim 16, characterized in that, The method further includes: A fourth operation is received on the fourth interface, and a fifth interface is displayed, the fifth interface including the total number of blood glucose monitoring and / or the total number of abnormal blood glucose changes.

18. The method according to claim 17, characterized in that, The method further includes: A fifth operation is received on the fifth interface, and a sixth interface is displayed. The sixth interface includes seventh information and / or eighth information. The seventh information is used to describe the trend of total blood glucose risk over time in a second time period, which occurs before the first time period. The total blood glucose risk is one of the following: the number of abnormal changes in total blood glucose, the proportion of abnormal changes in total blood glucose, or the average probability value of abnormal changes in total blood glucose. The eighth information includes at least one of the following: a meal blood glucose risk curve, an exercise blood glucose risk curve, or a sleep blood glucose risk curve. The meal blood glucose risk curve is used to describe the trend of sleep blood glucose risk over time in the second time period. The exercise blood glucose risk curve is used to describe the trend of exercise blood glucose risk over time in the second time period. The sleep blood glucose risk curve is used to describe the trend of sleep blood glucose risk over time in the second time period.

19. The method according to claim 16 or 17, characterized in that, The method further includes: A sixth operation is received on the fourth interface, and a seventh interface is displayed. The seventh interface includes a behavior identification control and / or detailed content of the blood glucose monitoring results associated with the user behavior type. The behavior identification control is used to identify the blood glucose monitoring information corresponding to the user behavior type, including at least one of a meal identification control, an exercise identification control, or a sleep identification control. The meal identification control is used to identify the blood glucose monitoring information corresponding to the meal behavior type, the exercise identification control is used to identify the blood glucose monitoring information corresponding to the exercise behavior type, and the sleep identification control is used to identify the blood glucose monitoring information corresponding to the sleep behavior type.

20. A device, characterized in that, The device includes a processor and a memory for storing a computer program, and the processor for calling and running the computer program from the memory, causing the device to perform the method of any one of claims 1 to 19.

21. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to perform the method of any one of claims 1 to 19.

22. A computer program product, characterized in that, The computer program product includes: computer program code, which, when executed by a processor, causes the processor to perform the method of any one of claims 1 to 19.

23. A chip system, characterized in that, The chip system includes a processor configured to execute a computer program to implement the method as described in any one of claims 1 to 19.

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