Method for recognizing glucose abnormality event, and electronic device

Abstract

Provided are a method for recognizing a glucose abnormality event, and an electronic device. The method for recognizing a glucose abnormality event comprises: after a first electronic device acquires glucose information of a user within a first time interval from a second electronic device, if a glucose fluctuation at a second moment relative to a third moment within the first time interval is greater than or equal to a first threshold value, the first electronic device acquiring first data; and on the basis of the first data, determining that the glucose fluctuation indicates the occurrence of a glucose abnormality event. Thus, the accuracy of recognizing a glucose abnormality event can be improved, and the interference of events such as stress and meals can be excluded without the need for asking a user wearing a CGM device about a sleep time period and / or meal time period.

Description

Method and electronic device for identifying abnormal blood sugar events

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on March 22, 2024, with application number 202410340467.4 and application name “Method and electronic device for identifying abnormal blood sugar events”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The embodiments of the present application relate to the field of smart terminal technology, and in particular to a method and electronic device for identifying abnormal blood sugar events. Background Art

[0003] An abnormal blood sugar event can be an event in which a user's blood sugar level rises during a specific time period. Identifying abnormal blood sugar events and reminding users can help users adjust their behavior (for example, medication dosage and / or exercise, etc.), thereby preventing further abnormal blood sugar events, improving glucose management, and reducing psychological stress.

[0004] Existing related technologies provide some solutions for identifying abnormal blood sugar events based on continuous glucose monitoring (CGM) devices. However, the above solutions have low accuracy in identifying abnormal blood sugar events and also need to ask users about their sleep time periods and / or meal time periods, which will cause disturbances to users and poor user experience. Summary of the Invention

[0005] The embodiments of the present application provide a method and electronic device for identifying abnormal blood sugar events, so as to improve the accuracy of identifying abnormal blood sugar events and eliminate interference from events such as stress and meals without asking the user.

[0006] In a first aspect, an embodiment of the present application provides a method for identifying abnormal blood sugar events, including: a first electronic device obtains blood sugar information of a user within a first time interval; wherein, the start time of the first time interval is a first moment, the end time of the first time interval is a second moment, the first moment is before the current moment, and the second moment includes the current moment; if the blood sugar fluctuation of the second moment relative to the third moment within the first time interval is greater than or equal to a first threshold, first data is obtained; wherein, the third moment is before the second moment; based on the first data, the blood sugar fluctuation is determined to be an abnormal blood sugar event.

[0007] In some examples, the above-mentioned first data may include second data within the first time interval and the second time interval, wherein the start time of the second time interval is the second moment, the end time of the second time interval is the fourth moment, and the fourth moment is after the second moment; in other examples, the above-mentioned first data may include the user's physiological data and / or sensor data of the wearable device, as well as third data within the first time interval.

[0008] In one possible implementation, the first data includes second data within the first time interval and the second time interval; the start time of the second time interval is the second time, the end time of the second time interval is the fourth time, and the fourth time is after the second time; determining that the blood sugar fluctuation is an abnormal blood sugar event based on the first data includes: determining that the blood sugar fluctuation is an abnormal blood sugar event based on the second data.

[0009] In the above implementation, when the first electronic device is a CGM device, the first electronic device can obtain the blood glucose information from the device itself; when the first electronic device is not a CGM device, the first electronic device can obtain the blood glucose information from a CGM device connected to the first electronic device. This blood glucose information may include the user's blood glucose level. Specifically, the blood glucose information is obtained from raw information detected by the CGM device itself. The raw information detected by the CGM device may include current information, temperature information, and an impedance spectrum. The CGM device can obtain the user's blood glucose information based on the detected current information. The CGM device can then calibrate the blood glucose information using the temperature information and the impedance spectrum. In this way, the first electronic device obtains the calibrated blood glucose information.

[0010] The second data in the first time interval and the second time interval may include original information detected by the CGM device. For example, the original information may include current information and temperature information detected by the CGM device. In addition, the original information may also include an impedance spectrum.

[0011] In the above method, after the first electronic device obtains the blood sugar information within the first time interval, if it is found that the blood sugar fluctuation at the second moment relative to the third moment in the first time interval is greater than or equal to the first threshold, the first electronic device can obtain second data within the first time interval and the second time interval. The first time interval and the second time interval include the time interval in which the blood sugar fluctuation relative to the third moment is greater than or equal to the first threshold, and the time interval in which the blood sugar fluctuation relative to the third moment is reduced to less than the first threshold, and the second data includes the current information and temperature information detected by the CGM device within the above time interval. Therefore, the second data includes the current information and temperature information of the entire process of the user's blood sugar fluctuation. In this way, the first electronic device can more accurately determine that the blood sugar fluctuation is an abnormal blood sugar event based on the second data, thereby improving the accuracy of identifying abnormal blood sugar events.

[0012] In one possible implementation, after determining that the blood sugar fluctuation is an abnormal blood sugar event, it also includes: determining the type of the abnormal blood sugar event based on the second moment; recording the third time interval in which the abnormal blood sugar event occurs; wherein the start moment of the third time interval is the third moment, and the end moment of the third time interval is the fifth moment, and the fifth moment is the moment when the blood sugar fluctuation relative to the third moment in the second time interval is reduced to less than the first threshold; and prompting the user with the type of the abnormal blood sugar event and the third time interval.

[0013] This implementation method realizes the determination of the type of abnormal blood sugar event, for example: the type of the abnormal blood sugar event is a dawn phenomenon or a dusk phenomenon; and realizes the determination of the third time interval when the abnormal blood sugar event occurs, and then the type of the abnormal blood sugar event and the third time interval can be prompted to the user, so that the user pays attention to his or her blood sugar changes, adjusts his or her lifestyle and / or medication, etc., and reduces the occurrence of abnormal blood sugar events.

[0014] In one possible implementation, the determining, based on the second data, that the blood sugar fluctuation is before the occurrence of an abnormal blood sugar event also includes: determining, based on the second data, whether the blood sugar fluctuation is caused by a first event; the determining, based on the second data, that the blood sugar fluctuation is the occurrence of an abnormal blood sugar event includes: if, based on the second data, it is determined that the blood sugar fluctuation is not caused by the first event, then determining that the blood sugar fluctuation is the occurrence of an abnormal blood sugar event.

[0015] In this implementation, the first electronic device can determine whether the blood sugar fluctuation is caused by the first event based on the second data, thereby eliminating the interference of the first event on the identification of abnormal blood sugar events without asking the user. This not only improves the accuracy of identifying abnormal blood sugar events, but also reduces disturbance to the user and improves the user experience.

[0016] In one possible implementation, after determining whether the blood sugar fluctuation is caused by a first event based on the second data, the method further includes: if the blood sugar fluctuation is caused by the first event, prompting the user that the blood sugar fluctuation is caused by the first event.

[0017] In one possible implementation, after determining whether the blood sugar fluctuation is caused by the first event based on the second data, the method further includes: if the blood sugar fluctuation is caused by the first event, recording that the blood sugar fluctuation is caused by the first event, and recording the time interval in which the first event occurs.

[0018] In the above implementation, after determining that the blood sugar fluctuation is caused by the first event, the first electronic device can directly record that the blood sugar fluctuation is caused by the first event, and record the time interval when the above first event occurs; or, the first electronic device can also prompt the user that the blood sugar fluctuation is caused by the first event, and after obtaining the user's confirmation information on the first event, record that the blood sugar fluctuation is caused by the first event, and record the time interval when the above first event occurs.

[0019] In one possible implementation, the blood glucose information and the second data are obtained from a second electronic device; wherein the second electronic device is worn on the user.

[0020] In this implementation, the second electronic device may be a CGM device, and the second electronic device is connected to the first electronic device.

[0021] In one possible implementation, the second data includes first current information and first temperature information; the first event includes the user pressing the second electronic device; and determining whether the blood sugar fluctuation is caused by the first event based on the second data includes: when the first current information and the first temperature information conform to a first rule, determining that the blood sugar fluctuation is caused by the user pressing the second electronic device.

[0022] In the above implementation, the first electronic device can determine that the blood sugar fluctuation is caused by the user pressing the second electronic device based on the second data obtained from the second electronic device. Therefore, there is no need to ask the user wearing the second electronic device about the sleeping time period and / or meal time period to determine the cause of the blood sugar fluctuation. This can not only reduce the disturbance to the user and improve the user experience, but also improve the accuracy of identifying abnormal blood sugar events.

[0023] In one possible implementation, prompting the user that the blood sugar fluctuation is caused by the first event includes prompting the user that the blood sugar fluctuation is caused by the user pressing the second electronic device.

[0024] In one possible implementation, recording the blood sugar fluctuation caused by the first event and recording the time interval in which the first event occurs includes: recording the event in which the blood sugar fluctuation is caused by the user pressing the second electronic device, and recording a fourth time interval; wherein the fourth time interval is the time interval in which the user presses the second electronic device, the starting moment of the fourth time interval is the third moment, the ending moment of the fourth time interval is the sixth moment, and the sixth moment is the moment when the blood sugar fluctuation in the second time interval relative to the third moment is reduced to less than the first threshold.

[0025] In one possible implementation, the second data includes first current information and first temperature information; the first event includes the user eating a meal; and determining whether the blood sugar fluctuation is caused by the first event based on the second data includes: when the first current information and the first temperature information conform to a second rule, determining that the blood sugar fluctuation is caused by the user eating a meal.

[0026] In the above implementation, the first electronic device can determine that the blood sugar fluctuation is caused by the user's meals based on the second data obtained from the second electronic device, thereby determining the cause of the blood sugar fluctuation without asking the user wearing the second electronic device about the sleeping time period and / or meal time period. This can not only reduce the disturbance to the user and improve the user experience, but also improve the accuracy of identifying abnormal blood sugar events.

[0027] In one possible implementation, prompting the user that the blood sugar fluctuation is caused by the first event includes: prompting the user that the blood sugar fluctuation is caused by the user's meal.

[0028] In one possible implementation, recording the blood sugar fluctuation caused by the first event and recording the time interval in which the first event occurs includes: recording the event in which the blood sugar fluctuation is caused by the user's meal, and recording a fifth time interval; wherein the fifth time interval is the time interval in which the user eats, the starting time of the fifth time interval is the third moment, the ending time of the fifth time interval is the seventh moment, and the seventh moment is the moment when the blood sugar fluctuation in the second time interval relative to the third moment is reduced to less than the first threshold.

[0029] In one possible implementation, the blood glucose information is obtained from a second electronic device; wherein, the second electronic device is worn on the user; after the first electronic device obtains the user's blood glucose information within a first time interval, it also includes: if the blood glucose fluctuation at the second moment relative to the third moment within the first time interval is greater than or equal to a first threshold, then obtaining the user's physiological data and / or sensor data of the wearable device, and obtaining the third data within the first time interval from the second electronic device; based on the user's physiological data and / or sensor data of the wearable device, and the third data, determining that the blood glucose fluctuation is an abnormal blood glucose event.

[0030] In the above implementation, after the first electronic device obtains the user's blood sugar information within the first time interval from the second electronic device, if the blood sugar fluctuation at the second moment relative to the third moment in the first time interval is greater than or equal to the first threshold, the first electronic device obtains the user's physiological data and / or wearable device sensor data, and obtains the third data within the first time interval from the second electronic device. Based on the above user physiological data and / or wearable device sensor data, and the above third data, the above blood sugar fluctuation is determined to be an abnormal blood sugar event, thereby realizing the identification of abnormal blood sugar events. In addition, in this implementation, the first electronic device can identify abnormal blood sugar events in combination with the user's physiological data and / or wearable device sensor data. Compared with the implementation method that does not combine the user's physiological data and / or wearable device sensor data, there is no need to obtain data within the second time interval from the second electronic device, thereby shortening the time required to identify abnormal blood sugar events and improving the efficiency of identifying abnormal blood sugar events.

[0031] In one possible implementation, before obtaining the physiological data of the user and / or the sensor data of the wearable device, it also includes: if the blood sugar fluctuation at the second moment relative to the third moment in the first time interval is greater than or equal to a first threshold, the first electronic device determines whether the first electronic device has the ability to obtain fourth data of the wearable device; wherein the fourth data includes the physiological data of the user and / or the sensor data of the wearable device; obtaining the physiological data of the user and / or the sensor data of the wearable device, and obtaining the third data in the first time interval from the second electronic device includes: if the first electronic device has the ability to obtain the fourth data of the wearable device, obtaining the physiological data of the user and / or the sensor data of the wearable device, and obtaining the third data in the first time interval from the second electronic device.

[0032] In this implementation, before obtaining the user's physiological data and / or the sensor data of the wearable device, the first electronic device first determines whether it can obtain the fourth data of the wearable device. If the first electronic device can obtain the fourth data of the wearable device, the first electronic device then obtains the user's physiological data and / or the sensor data of the wearable device, as well as the third data. Then, the first electronic device can determine that the blood sugar fluctuation is an abnormal blood sugar event based on these data, thereby identifying the abnormal blood sugar event.

[0033] In one possible implementation, the first electronic device determines whether the first electronic device has the ability to obtain the fourth data of the wearable device, including: the first electronic device determines whether the user is wearing a wearable device; if the user is wearing a wearable device, the first electronic device determines whether the fourth data of the wearable device is obtained; if so, the first electronic device determines that the first electronic device has the ability to obtain the fourth data of the wearable device.

[0034] This implementation provides an example of determining whether the first electronic device can obtain the fourth data of the wearable device.

[0035] In one possible implementation, after determining that the blood sugar fluctuation is an abnormal blood sugar event, it also includes: determining the type of the abnormal blood sugar event based on the second moment; obtaining the sixth time interval in which the abnormal blood sugar event occurs; wherein the starting moment of the sixth time interval is the third moment, and the ending moment of the sixth time interval is the eighth moment, and the eighth moment is the moment when the blood sugar fluctuation relative to the third moment is reduced to less than the first threshold; after determining that the user is not in a sleeping state, the type of the abnormal blood sugar event and the sixth time interval are prompted to the user.

[0036] This implementation allows for determining the type of abnormal blood sugar event, for example, whether it is a dawn phenomenon or a dusk phenomenon; and for determining the sixth time interval during which the abnormal blood sugar event occurs. This allows the user to be notified of the type of abnormal blood sugar event and the sixth time interval, thereby encouraging the user to monitor their blood sugar levels, adjust their lifestyle and / or medication, and reduce the occurrence of abnormal blood sugar events. Furthermore, in this implementation, the first electronic device only notifies the user of the notification after determining that the user is not asleep, thereby avoiding disrupting the user's sleep and improving the user experience.

[0037] In one possible implementation, before determining that the blood sugar fluctuation is an abnormal blood sugar event, it also includes: determining whether the blood sugar fluctuation is caused by a first event based on the user's physiological data and / or sensor data of the wearable device, and the third data; determining that the blood sugar fluctuation is an abnormal blood sugar event includes: if it is determined that the blood sugar fluctuation is not caused by the first event, then determining that the blood sugar fluctuation is an abnormal blood sugar event.

[0038] In this implementation, the first electronic device can determine whether the blood sugar fluctuation is caused by the first event based on the user's physiological data and / or wearable device sensor data, as well as the third data. This eliminates the interference of the first event on the identification of abnormal blood sugar events without asking the user. This not only improves the accuracy of abnormal blood sugar event identification, but also reduces disturbances to the user and improves the user experience. In addition, compared to an implementation that does not incorporate the user's physiological data and / or wearable device sensor data, the first electronic device can identify abnormal blood sugar events without obtaining data within the second time interval from the second electronic device, thereby shortening the time required to identify abnormal blood sugar events and improving the efficiency of abnormal blood sugar event identification.

[0039] In one possible implementation, after determining whether the blood sugar fluctuation is caused by a first event, the method further includes: if the blood sugar fluctuation is caused by the first event, then after determining that the user is not in a sleeping state, prompting the user that the blood sugar fluctuation is caused by the first event.

[0040] In one possible implementation, after determining whether the blood sugar fluctuation is caused by a first event, the method further includes: if the blood sugar fluctuation is caused by the first event, recording that the blood sugar fluctuation is caused by the first event, and recording the time interval in which the first event occurs.

[0041] In the above implementation, after determining that the blood sugar fluctuation is caused by the first event, the first electronic device can directly record that the blood sugar fluctuation is caused by the first event and record the time interval during which the first event occurred; alternatively, the first electronic device can also prompt the user that the blood sugar fluctuation is caused by the first event, and after obtaining the user's confirmation information regarding the first event, record that the blood sugar fluctuation is caused by the first event and record the time interval during which the first event occurred. Similarly, in the above implementation, the first electronic device prompts the user only after determining that the user is not in a sleeping state, thereby not affecting the user's sleep and improving the user's experience.

[0042] In one possible implementation, the third data includes second current information and second temperature information, and the first event includes the user eating a meal; determining whether the blood sugar fluctuation is caused by the first event based on the user's physiological data and / or sensor data of the wearable device, and the third data includes: when the second current information and the second temperature information conform to a second rule, if it is determined based on the user's physiological data and / or sensor data of the wearable device that the user has eaten a meal within the first time interval, then determining that the blood sugar fluctuation is caused by the user eating a meal.

[0043] In the above implementation, the first electronic device can determine that the blood sugar fluctuation is caused by the user's meal based on the third data obtained from the second electronic device, combined with the user's physiological data and / or the sensor data of the wearable device. This eliminates the need to inquire about the sleep time period and / or meal time period of the user wearing the second electronic device to determine the cause of the blood sugar fluctuation. This not only reduces disturbances to the user and improves the user experience, but also improves the accuracy of identifying abnormal blood sugar events. In addition, compared to the implementation method that does not combine the user's physiological data and / or the sensor data of the wearable device, the first electronic device can determine the cause of the blood sugar fluctuation without obtaining data within the second time interval from the second electronic device, thereby shortening the time required to identify abnormal blood sugar events and improving the efficiency of identifying abnormal blood sugar events.

[0044] In one possible implementation, the third data includes second current information and second temperature information, and the first event includes the user pressing the second electronic device; determining whether the blood sugar fluctuation is caused by the first event based on the user's physiological data and / or sensor data of the wearable device, and the third data includes: when the second current information and the second temperature information conform to the first rule, if it is determined based on the user's physiological data and / or sensor data of the wearable device that the user has pressed the second electronic device within the first time interval, then determining that the blood sugar fluctuation is caused by the user pressing the second electronic device.

[0045] In the above implementation, the first electronic device can determine that the blood sugar fluctuation is caused by the user pressing the second electronic device based on the third data obtained from the second electronic device, combined with the user's physiological data and / or the sensor data of the wearable device. Therefore, there is no need to ask the user wearing the second electronic device about the sleep time period and / or meal time period to determine the cause of the blood sugar fluctuation. This can not only reduce the disturbance to the user and improve the user experience, but also improve the accuracy of identifying abnormal blood sugar events. In addition, compared with the implementation method that does not combine the user's physiological data and / or the sensor data of the wearable device, the first electronic device can determine the cause of the blood sugar fluctuation without obtaining data in the second time interval from the second electronic device, thereby shortening the time required to identify abnormal blood sugar events and improving the efficiency of identifying abnormal blood sugar events.

[0046] In a second aspect, an embodiment of the present application provides an electronic device comprising: one or more processors; a memory; multiple applications; and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions, which, when executed by the electronic device, enable the electronic device to execute the method provided in the first aspect.

[0047] It should be understood that the second aspect of the embodiment of the present application is consistent with the technical solution of the first aspect of the embodiment of the present application, and the beneficial effects achieved by each aspect and the corresponding feasible implementation methods are similar and will not be repeated.

[0048] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer executes the method provided in the first aspect.

[0049] In a fourth aspect, an embodiment of the present application provides a computer program, which, when executed by a computer, is used to execute the method provided in the first aspect.

[0050] In one possible design, the program in the fourth aspect may be stored in whole or in part on a storage medium packaged with the processor, or may be stored in whole or in part on a memory not packaged with the processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] FIG1 is a schematic structural diagram of an electronic device 100 provided in one embodiment of the present application;

[0052] FIG2 is a schematic structural diagram of an electronic device 200 provided in one embodiment of the present application;

[0053] FIG3( a ) is a schematic structural diagram of an electronic device 300 provided in one embodiment of the present application;

[0054] FIG3( b ) is a schematic diagram of an application scenario of a method for identifying abnormal blood sugar events provided by an embodiment of the present application;

[0055] FIG4 is a flow chart of a method for identifying abnormal blood sugar events according to an embodiment of the present application;

[0056] FIG5 is a schematic diagram of a prompt interface for abnormal blood sugar events provided by one embodiment of the present application;

[0057] FIG6 is a flow chart of a method for identifying abnormal blood sugar events according to another embodiment of the present application;

[0058] FIG7 is a schematic diagram of a prompt interface for a first event provided by an embodiment of the present application;

[0059] FIG8 is a schematic diagram of a prompt interface for a first event provided by another embodiment of the present application;

[0060] FIG9 is a schematic diagram of an application scenario of a method for identifying abnormal blood sugar events provided by another embodiment of the present application;

[0061] FIG10 is a flow chart of a method for identifying abnormal blood sugar events according to another embodiment of the present application;

[0062] FIG11 is a flow chart of a method for identifying abnormal blood sugar events according to another embodiment of the present application;

[0063] FIG12 is a flow chart of a method for identifying abnormal blood sugar events according to another embodiment of the present application;

[0064] FIG13 is a flow chart of a method for identifying abnormal blood sugar events according to another embodiment of the present application;

[0065] FIG14 is a flow chart of a method for identifying abnormal blood sugar events according to another embodiment of the present application;

[0066] FIG15 is a schematic structural diagram of an electronic device provided in yet another embodiment of the present application. DETAILED DESCRIPTION

[0067] The terms used in the implementation section of this application are only used to explain the specific embodiments of this application and are not intended to limit this application.

[0068] The terms used in the implementation section of this application are only used to explain the specific embodiments of this application and are not intended to limit this application.

[0069] In the solutions provided by existing related technologies for identifying abnormal blood sugar events based on CGM devices, changes in the output values ​​of the CGM device during the pressure recovery process and / or the increase in the user's blood sugar after a meal outside the meal period will lead to misidentification of abnormal blood sugar events, resulting in a low accuracy rate for the existing solutions in identifying abnormal blood sugar events. Among them, the pressure recovery process refers to the process of the CGM device recovering from a compressed state to a non-compressed state. In addition, the existing solutions also need to ask the user about the sleep time period and / or meal time period, which will disturb the user and the user experience is poor.

[0070] Based on the problem of low recognition accuracy of the dawn phenomenon in existing related technologies, an embodiment of the present application provides a method for identifying abnormal blood sugar events, which can improve the recognition accuracy of abnormal blood sugar events (such as the dawn phenomenon) and eliminate the need to ask users wearing CGM devices about their sleep time periods and / or meal time periods. Interference from events such as stress and meals can be eliminated, and the user will not be disturbed, thereby improving the user experience.

[0071] In some examples, the method for identifying abnormal blood sugar events provided in the embodiments of the present application can be applied to an electronic device 100, wherein the above-mentioned electronic device 100 can be a smart phone, a smart screen, a tablet computer, a wearable device, an augmented reality (AR) / virtual reality (VR) device, a laptop computer, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA) and other devices; the embodiments of the present application do not impose any restrictions on the specific type of the electronic device 100.

[0072] Exemplarily, Figure 1 is a structural diagram of an electronic device 100 provided by an embodiment of the present application. As shown in Figure 1, the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 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, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0073] It should be understood that the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown, or may combine or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0074] The processor 110 may include one or more processing units. For example, the processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU). The different processing units may be independent devices or integrated into one or more processors.

[0075] The controller can generate operation control signals according to the instruction operation code and timing signal to complete the control of instruction fetching and execution.

[0076] Processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in processor 110 is a cache memory. This memory can store instructions or data that have just been used or are being recycled by processor 110. If processor 110 needs to use the same instruction or data again, it can directly access the memory. This avoids duplicate accesses, reduces processor 110 latency, and thus improves system efficiency.

[0077] In some embodiments, the processor 110 may include one or more interfaces. The 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.

[0078] The USB interface 130 is an interface that complies with USB standards and may be a Mini USB interface, a Micro USB interface, a USB Type-C interface, or the like. The USB interface 130 can be used to connect a charger to charge the electronic device 100, or to transfer data between the electronic device 100 and peripheral devices. It can also be used to connect headphones to play audio. This interface can also be used to connect other electronic devices, such as augmented reality devices.

[0079] It is understood that the interface connection relationship between the modules illustrated in the embodiments of the present application is merely an illustrative illustration and does not constitute a structural limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may also adopt different interface connection methods from the above embodiments, or a combination of multiple interface connection methods.

[0080] The charging management module 140 is configured to receive charging input from a charger. The charger can be either a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 can receive charging input from the wired charger via the USB interface 130. In some wireless charging embodiments, the charging management module 140 can receive wireless charging input via the wireless charging coil of the electronic device 100. While charging the battery 142, the charging management module 140 can also provide power to the electronic device 100 via the power management module 141.

[0081] The power management module 141 is used to connect the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, and provides power to the processor 110, the internal memory 121, the display 194, the camera 193, and the wireless communication module 160. The power management module 141 can also be used to monitor parameters such as battery capacity, battery cycle count, and battery health status (leakage, impedance). In some other embodiments, the power management module 141 can also be set in the processor 110. In other embodiments, the power management module 141 and the charging management module 140 can also be set in the same device.

[0082] The wireless communication function of the electronic device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

[0083] Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In other embodiments, the antennas can be used in conjunction with a tuning switch.

[0084] The mobile communication module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G applied to the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the same device as at least some of the modules of the processor 110.

[0085] The modem processor may include a modulator and a demodulator. The modulator is used to modulate the low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used to demodulate 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 being processed by the baseband processor, the low-frequency baseband signal is passed to the application processor. The application processor outputs a sound signal through an audio device (not limited to the speaker 170A, the receiver 170B, etc.) or displays an image or video through the display screen 194. In some embodiments, the modem processor may be an independent device. In other embodiments, the modem processor may be independent of the processor 110 and be set in the same device as the mobile communication module 150 or other functional modules.

[0086] The wireless communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), etc., which are applied to the electronic device 100. The wireless communication module 160 can be one or more devices that integrate at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110. The wireless communication module 160 can also receive the signal to be sent from the processor 110, frequency modulate it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2.

[0087] In some embodiments, the antenna 1 of the electronic device 100 is coupled to the mobile communication module 150, and the antenna 2 is coupled to the wireless communication module 160, so that the electronic device 100 can communicate with a network and other devices through wireless communication technologies. The wireless communication technologies may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time-division code division multiple access (TD-CDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology. The GNSS may include a global positioning system (GPS), a global navigation satellite system (GLONASS), a Beidou navigation satellite system (BDS), a quasi-zenith satellite system (QZSS) and / or a satellite based augmentation system (SBAS).

[0088] Electronic device 100 implements display functionality through a GPU, display screen 194, and an application processor. A GPU is a microprocessor for image processing that connects display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs that execute program instructions to generate or modify display information.

[0089] Display screen 194 is used to display images, videos, and the like. Display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a MiniLED, a MicroLED, a Micro-oLed, or a quantum dot light-emitting diode (QLED). In some embodiments, electronic device 100 may include one or N display screens 194, where N is a positive integer greater than one.

[0090] The electronic device 100 can implement a shooting function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, and an application processor.

[0091] The ISP processes data fed back by camera 193. For example, when taking a photo, the shutter is opened, and light is transmitted through the lens to the camera's photosensitive element. The light signal is converted into an electrical signal, which is then passed to the ISP for processing and converted into a visible image. The ISP can also perform algorithmic optimization on image noise, brightness, and skin tone. It can also optimize parameters such as exposure and color temperature of the captured scene. In some embodiments, the ISP can be located within camera 193.

[0092] The camera 193 is used to capture still images or videos. The object generates an optical image through the lens and projects it onto the photosensitive element. The photosensitive element can be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, and then passes the electrical signal to the ISP for conversion into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in a standard RGB, YUV or other format. In some embodiments, the electronic device 100 may include 1 or N cameras 193, where N is a positive integer greater than 1.

[0093] The digital signal processor is used to process digital signals. In addition to processing digital image signals, it can also process other digital signals. For example, when the electronic device 100 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy.

[0094] Video codecs are used to compress or decompress digital video. Electronic device 100 may support one or more video codecs. This allows electronic device 100 to play or record videos in various encoding formats, such as Moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, and MPEG4.

[0095] The NPU is a neural network (NN) computing processor. Drawing on the structure of biological neural networks, such as the transmission patterns between neurons in the human brain, it rapidly processes input information and can continuously self-learn. The NPU can enable intelligent cognitive applications in electronic device 100, such as image recognition, face recognition, speech recognition, and text comprehension.

[0096] The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100. The external memory card communicates with the processor 110 via the external memory interface 120 to implement data storage functions. For example, files such as music and videos can be stored on the external memory card.

[0097] The internal memory 121 can be used to store computer executable program codes, which include instructions. The internal memory 121 may include a program storage area and a data storage area. Among them, the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc. The data storage area may store data created during the use of the electronic device 100 (such as audio data, a phone book, etc.), etc. In addition, the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), etc. The processor 110 executes various functional applications and data processing of the electronic device 100 by running instructions stored in the internal memory 121 and / or instructions stored in a memory provided in the processor.

[0098] The electronic device 100 can implement audio functions such as music playback and recording through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone jack 170D, and the application processor.

[0099] The audio module 170 is used to convert digital audio information into analog audio signal output, and is also used to convert analog audio input into digital audio signals. The audio module 170 can also be used to encode and decode audio signals. In some embodiments, the audio module 170 can be provided in the processor 110, or some functional modules of the audio module 170 can be provided in the processor 110.

[0100] The speaker 170A, also called a "speaker", is used to convert audio electrical signals into sound signals. The electronic device 100 can listen to music or listen to hands-free calls through the speaker 170A.

[0101] The receiver 170B, also called a "handset", is used to convert audio electrical signals into sound signals. When the electronic device 100 receives a call or a voice message, the user can place the receiver 170B close to the ear to hear the voice.

[0102] Microphone 170C, also known as "microphone" or "microphone", is used to convert sound signals into electrical signals. When making a call or sending a voice message, the user can speak by putting their mouth close to the microphone 170C to input the sound signal into the microphone 170C. The electronic device 100 can be provided with at least one microphone 170C. In other embodiments, the electronic device 100 can be provided with two microphones 170C, which can not only collect sound signals but also realize noise reduction function. In other embodiments, the electronic device 100 can also be provided with three, four or more microphones 170C to collect sound signals, reduce noise, identify the source of sound, realize directional recording function, etc.

[0103] The headphone jack 170D is used to connect a wired headphone and can be the USB interface 130 or a 3.5mm open mobile terminal platform (OMTP) standard interface or a cellular telecommunications industry association of the USA (CTIA) standard interface.

[0104] The buttons 190 include a power button, a volume button, and the like. The buttons 190 may be mechanical buttons or touch buttons. The electronic device 100 may receive key inputs and generate key signal inputs related to user settings and function control of the electronic device 100.

[0105] Motor 191 can generate vibration prompts. Motor 191 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback. For example, touch operations acting on different applications (such as taking pictures, audio playback, etc.) can correspond to different vibration feedback effects. For touch operations acting on different areas of the display screen 194, motor 191 can also correspond to different vibration feedback effects. Different application scenarios (for example: time reminders, receiving messages, alarm clocks, games, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect can also support customization.

[0106] The indicator 192 may be an indicator light, which may be used to indicate the charging status, power level changes, messages, missed calls, notifications, etc.

[0107] The SIM card interface 195 is used to connect a SIM card. The SIM card can be connected to and separated from the electronic device 100 by inserting it into or removing it from the SIM card interface 195. The electronic device 100 can support 1 or N SIM card interfaces, where N is a positive integer greater than 1. The SIM card interface 195 can support Nano SIM cards, Micro SIM cards, SIM cards, etc. Multiple cards can be inserted into the same SIM card interface 195 at the same time. The types of the multiple cards can be the same or different. The SIM card interface 195 can also be compatible with different types of SIM cards. The SIM card interface 195 can also be compatible with external memory cards. The electronic device 100 interacts with the network through the SIM card to implement functions such as calls and data communications. In some embodiments, the electronic device 100 uses an eSIM, i.e., an embedded SIM card. The eSIM card can be embedded in the electronic device 100 and cannot be separated from the electronic device 100.

[0108] In other examples, the method for identifying abnormal blood sugar events provided in the embodiments of the present application can be applied to the electronic device 200. The electronic device 200 can be a CGM device.

[0109] For example, FIG2 is a schematic diagram of the structure of an electronic device 200 provided in one embodiment of the present application. The electronic device 200 in this embodiment may be a CGM device. As shown in FIG2 , the electronic device 200 may include a processor 210, a communication interface 220, a memory 230, and a sensor module 240. The processor 210, the communication interface 220, the memory 230, and the sensor module 240 may communicate with each other via internal connection paths to transmit control and / or data signals. The memory 230 is used to store computer programs, and the processor 210 is used to call and execute the computer programs from the memory 230.

[0110] The processor 210 and the memory 230 may be combined into a processing device, or more commonly, they are independent components, with the processor 210 being configured to execute program codes stored in the memory 230. In a specific implementation, the memory 230 may also be integrated into the processor 210 or independent of the processor 210.

[0111] The sensor module 240 may include: a current sensor 2401, a temperature sensor 2402, and an impedance sensor 2403. Of course, this embodiment is not limited thereto, and the sensor module 240 may also include more sensors, which is not limited in this embodiment.

[0112] Among them, the current sensor 2401 is used to collect current information;

[0113] Temperature sensor 2402, used to collect temperature information;

[0114] Impedance sensor 2403 is used to collect impedance information.

[0115] It should be understood that the processor 210 in the electronic device 200 shown in Figure 2 can be a system on a chip SOC, which can include a central processing unit (CPU) and can further include other types of processors, such as a graphics processing unit (GPU).

[0116] In some further examples, the method for identifying abnormal blood sugar events provided in the embodiments of the present application can be applied to the electronic device 300. The electronic device 300 can be a server, which can be set up in the cloud.

[0117] FIG3( a ) is a schematic structural diagram of an electronic device 300 provided in one embodiment of the present application. The electronic device 300 shown in FIG3( a ) is merely an example and should not impose any limitation on the functions and scope of use of the embodiments of this specification.

[0118] As shown in FIG3(a), electronic device 300 is implemented as a general-purpose computing device. Components of electronic device 300 may include, but are not limited to, one or more processors 310, a communication interface 320, a memory 330, and a communication bus 340 connecting the various components (including the memory 330, the communication interface 320, and the processor 310).

[0119] The communication bus 340 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, or a local bus using any of a variety of bus architectures. For example, the communication bus 340 may include, but is not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnection (PCI) bus.

[0120] The electronic device 300 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 300, including volatile and non-volatile media, removable and non-removable media.

[0121] The memory 330 may include a computer system readable medium in the form of a volatile memory, such as a random access memory (RAM) and / or a cache memory. The memory 330 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present application.

[0122] A program / utility having a set (at least one) of program modules may be stored in memory 330. Such program modules include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. The program modules may generally perform the functions and / or methods of the embodiments of the present application.

[0123] The processor 310 executes various functional applications and data processing by running the programs stored in the memory 330, such as implementing the method for identifying abnormal blood sugar events provided in the embodiment of the present application.

[0124] The method for identifying abnormal blood sugar events provided by an embodiment of the present application may include: a first electronic device obtains the blood sugar information of a user within a first time interval; wherein the start time of the first time interval is a first moment, the end time of the first time interval is a second moment, the first moment is before the current moment, and the second moment is the current moment; if the blood sugar fluctuation of the second moment relative to the third moment within the first time interval is greater than or equal to a first threshold, then obtaining first data; wherein the third moment is before the second moment; then, the first electronic device determines, based on the above-mentioned first data, that the blood sugar fluctuation is an abnormal blood sugar event.

[0125] In some examples, the above-mentioned first data may include second data within the first time interval and the second time interval, wherein the start time of the second time interval is the second moment, the end time of the second time interval is the fourth moment, and the fourth moment is after the second moment; in other examples, the above-mentioned first data may include the user's physiological data and / or sensor data of the wearable device, as well as third data within the first time interval.

[0126] The following describes the above-mentioned method for identifying abnormal blood sugar events in detail with reference to the accompanying drawings and application scenarios.

[0127] FIG3( b ) is a schematic diagram of an application scenario of a method for identifying abnormal blood sugar events provided by an embodiment of the present application. As shown in FIG3( b ), the application scenario may include a first electronic device 31 and a second electronic device 32 .

[0128] In some examples, the first electronic device 31 may be an electronic device used by a user. For example, the first electronic device 31 may be a smart phone, a smart screen, a tablet computer, a wearable device, an AR / VR device, a laptop computer, a UMPC, a netbook or a PDA. In these examples, the first electronic device 31 may be implemented using the structure shown in FIG1 ; in other examples, the first electronic device 31 may be a server, which is set up in the cloud. In these examples, the first electronic device 31 may be implemented using the structure shown in FIG3(a).

[0129] The second electronic device 32 may be a CGM device, and the second electronic device 32 is worn on the user. For example, the second electronic device 32 may be implemented using the structure shown in FIG. 2 .

[0130] In addition, in the application scenario shown in Figure 3(b), a communication connection can be established between the first electronic device 31 and the second electronic device 32 to exchange data and / or information. In specific implementation, the first electronic device 31 can directly establish a communication connection with the second electronic device 32; or, the first electronic device 31 can also establish a communication connection with the second electronic device 32 through other electronic devices. The above-mentioned other electronic devices include other electronic devices used by the user in addition to the first electronic device 31 and the second electronic device 32; for example, when the first electronic device 31 is a smart screen or a server, the first electronic device 31 can establish a communication connection with the second electronic device 32 through the smartphone used by the user. Of course, these are only some examples of the first electronic device 31 establishing a communication connection with the second electronic device 32 through other electronic devices. The embodiments of the present application are not limited to this. When the first electronic device 31 is a different type of electronic device, it can establish a communication connection with the second electronic device 32 through other electronic devices used by the user in addition to the first electronic device 31 and the second electronic device 32. The embodiments of the present application are not limited to this.

[0131] Figure 4 is a flowchart of a method for identifying abnormal blood sugar events provided by an embodiment of the present application. This embodiment introduces a method for identifying abnormal blood sugar events in the application scenario shown in Figure 3(b). In this embodiment, the first data may include second data within the first time interval and the second time interval, and the second data is obtained from the second electronic device 32.

[0132] As shown in FIG4 , the above-mentioned method for identifying abnormal blood sugar events may include:

[0133] In step 401 , the first electronic device 31 obtains the blood glucose information of the user within a first time interval from the second electronic device 32 .

[0134] The start time of the first time interval is the first moment, and the end time of the first time interval is the second moment. The first moment is before the current moment, and the second moment can be the current moment. Of course, this embodiment is not limited to this. The second moment can also be before the current moment, and this embodiment does not limit this, as long as the second moment is after the first moment. In addition, the duration of the first time interval can be the first duration. The length of the first duration can be set according to system performance and / or implementation requirements during specific implementation. This embodiment does not limit the above-mentioned first duration.

[0135] The above-mentioned blood glucose information is the blood glucose information of the above-mentioned user output by the second electronic device 32, and the blood glucose information may include the blood glucose value of the user. Specifically, the above-mentioned blood glucose information is obtained by the second electronic device 32 based on the original information detected by itself. The original information detected by the second electronic device 32 may include current information, temperature information and impedance spectrum. The second electronic device 32 can obtain the user's blood glucose information based on the detected current information, and then the second electronic device 32 can calibrate the blood glucose information using the temperature information and impedance spectrum. In this way, the first electronic device 31 obtains the calibrated blood glucose information from the second electronic device 32. Among them, the impedance spectrum can be the impedance spectrum of the electrochemical system in the second electronic device 32 measured by the second electronic device 32. The impedance spectrum can describe the state of the second electronic device 32, and can also be used together with the temperature information to calibrate the blood glucose information obtained by the second electronic device 32.

[0136] In some examples, if the first electronic device 31 directly establishes a communication connection with the second electronic device 32, then the first electronic device 31 can directly obtain the user's blood sugar information within the first time interval from the second electronic device 32; if the first electronic device 31 establishes a communication connection with the second electronic device 32 through other electronic devices used by the user, then the first electronic device 31 can obtain the user's blood sugar information within the first time interval from the second electronic device 32 through the above-mentioned other electronic devices.

[0137] Step 402 : If the blood sugar fluctuation at the second moment relative to the third moment in the first time interval is greater than or equal to the first threshold, the first electronic device 31 obtains second data in the first time interval and the second time interval from the second electronic device 32 .

[0138] Among them, the above-mentioned third moment is before the second moment; the above-mentioned blood sugar fluctuation can be understood as the change of blood sugar value over time, and the blood sugar fluctuation of the second moment relative to the third moment within the first time interval is greater than or equal to the first threshold value, which can be: from the third moment to the second moment, as time goes by, the blood sugar value gradually increases, and the difference between the blood sugar value at the second moment and the blood sugar value at the third moment is greater than or equal to the first threshold value.

[0139] The first threshold value can be set in a specific implementation. This embodiment does not limit the size of the first threshold value. For example, the first threshold value can be 20 mg / dl.

[0140] The starting time of the second time interval is the second moment, and the ending time of the second time interval is the fourth moment. The above-mentioned fourth moment is after the second moment. The length of the second time interval can be the second length. The length of the second length can be set according to system performance and / or implementation requirements during specific implementation. This embodiment does not limit the length of the second length. For example, the second length can be greater than or equal to 0.5 hours and less than or equal to 2 hours.

[0141] The second data may include original information detected by the second electronic device 32 . For example, the original information may include current information and temperature information detected by the second electronic device 32 . In addition, the original information may also include an impedance spectrum.

[0142] Similarly, if the first electronic device 31 directly establishes a communication connection with the second electronic device 32, then the first electronic device 31 can directly obtain the second data from the second electronic device 32; if the first electronic device 31 establishes a communication connection with the second electronic device 32 through other electronic devices used by the user, then the first electronic device 31 can obtain the second data from the second electronic device 32 through the above-mentioned other electronic devices.

[0143] In step 403 , the first electronic device 31 determines that the blood sugar fluctuation is an abnormal blood sugar event based on the second data.

[0144] Among them, an abnormal blood sugar event can be an event in which a user's blood sugar level rises during a specific time period. The specific time period can include the dawn period (e.g., 3:00 AM to 9:00 AM) and / or the dusk period (e.g., 5:00 PM to 7:00 PM). The embodiments of this application do not limit the specific time intervals of the dawn period and the dusk period. Specifically, an abnormal blood sugar event that occurs during the dawn period can be referred to as a dawn phenomenon, and an abnormal blood sugar event that occurs during the dusk period can be referred to as a dusk phenomenon.

[0145] Specifically, the specific manner in which the first electronic device 31 determines that the blood sugar fluctuation is an abnormal blood sugar event based on the second data can be found in the description of step 601 in the embodiment shown in FIG6 , which will not be repeated here.

[0146] In some examples, after step 403, the following steps may also be included:

[0147] Step 404: The first electronic device 31 determines the type of the abnormal blood sugar event according to the second moment.

[0148] Specifically, assuming that the second moment is in the dawn period (for example, 3 to 9 in the morning), the first electronic device 31 can determine that the type of the above-mentioned abnormal blood sugar event is a dawn phenomenon, and if the second moment is in the evening period (for example, 5 to 7 in the afternoon), the first electronic device 31 can determine that the type of the above-mentioned abnormal blood sugar event is a dusk phenomenon.

[0149] Step 405: The first electronic device 31 records the third time interval during which the abnormal blood sugar event occurs.

[0150] Among them, the starting time of the third time interval is the third moment, and the ending time of the third time interval is the fifth moment. The above-mentioned fifth moment is the moment when the blood sugar fluctuation relative to the third moment in the second time interval is reduced to less than the first threshold; generally speaking, the fifth moment is before the fourth moment, or the fifth moment can also be the same as the fourth moment.

[0151] In step 406 , the first electronic device 31 prompts the user with the type of the abnormal blood sugar event and the third time interval.

[0152] Taking the dawn phenomenon as an example of an abnormal blood sugar event, after determining the type of abnormal blood sugar event and recording the third time interval, the first electronic device 31 can prompt the user with the type of abnormal blood sugar event and the third time interval through a prompt interface for the abnormal blood sugar event. This interface may include the user's blood sugar information, the type of abnormal blood sugar event, and the third time interval. It may also include a basic description of the abnormal blood sugar event and some suggestions for the user regarding the abnormal blood sugar event. Figure 5 is a schematic diagram of a prompt interface for an abnormal blood sugar event provided in one embodiment of the present application.

[0153] In Figure 5 , reference 51 indicates the user's blood sugar information, and the text indicated by 52 includes the type of abnormal blood sugar event, "dawn phenomenon," and the third time period, "5:00 AM to 6:00 AM." Furthermore, the text indicated by 52 includes a basic description of the dawn phenomenon, "The dawn phenomenon is a state of high blood sugar levels in the early morning, characterized by fluctuations in various hormones..." It also includes user advice regarding the dawn phenomenon, such as "eliminating mental stress...helps control the dawn phenomenon." Figure 5 also includes an "Exercise Suggestion" icon 53 and a "Dietary Suggestion" icon 54. Clicking the "Exercise Suggestion" icon causes the first electronic device 31 to display specific exercise recommendations for the dawn phenomenon. Clicking the "Dietary Suggestion" icon 54 causes the first electronic device 31 to display specific dietary recommendations for the dawn phenomenon.

[0154] In addition, it should be noted that when the first electronic device 31 is an electronic device used by the user, for example, when the first electronic device 31 is implemented using the structure shown in Figure 1, the first electronic device 31 can display the prompt interface of the above-mentioned abnormal blood sugar event through its own display screen 194; of course, in this case, the first electronic device 31 can also send the type of the above-mentioned abnormal blood sugar event and the third time interval to other electronic devices used by the user other than the first electronic device 31 and the second electronic device 32, and the prompt interface of the above-mentioned abnormal blood sugar event is displayed by the above-mentioned other electronic devices and / or the first electronic device 31. For example, when the first electronic device 31 is a smart phone, the first electronic device 31 can send the type of the above-mentioned abnormal blood sugar event and the third time interval to the smart screen used by the user, and the prompt interface of the above-mentioned abnormal blood sugar event is displayed by the smart screen used by the user and / or the first electronic device 31.

[0155] When the first electronic device 31 is a server, for example, when the first electronic device 31 is implemented using the structure shown in Figure 3(a), the first electronic device 31 can send the type of the above-mentioned abnormal blood sugar event and the third time interval to other electronic devices used by the user except the first electronic device 31 and the second electronic device 32, and the other electronic devices used by the user display a prompt interface of the above-mentioned abnormal blood sugar event. For example, the first electronic device 31 can send the type of the above-mentioned abnormal blood sugar event and the third time interval to the smartphone used by the user, and the smartphone used by the user displays a prompt interface of the above-mentioned abnormal blood sugar event.

[0156] Of course, the way in which the first electronic device 31 prompts the user of the type of the above-mentioned abnormal blood sugar event and the third time interval is not limited to displaying the prompt interface of the above-mentioned abnormal blood sugar event. The first electronic device 31 can also prompt the user in other ways, for example: through voice broadcast. This embodiment does not limit the prompt method of the first electronic device 31.

[0157] In the above-mentioned method for identifying abnormal blood sugar events, after the first electronic device 31 obtains the user's blood sugar information within the first time interval from the second electronic device 32, if the blood sugar fluctuation at the second moment relative to the third moment in the first time interval is greater than or equal to the first threshold, the first electronic device 31 obtains the second data within the first time interval and the second time interval from the second electronic device 32. Based on the above-mentioned second data, it is determined that the above-mentioned blood sugar fluctuation is an abnormal blood sugar event, thereby improving the accuracy of identifying abnormal blood sugar events, and there is no need to ask the user wearing the CGM device about the sleep time period and / or meal time period, and the interference of events such as stress and meals can be eliminated.

[0158] FIG6 is a flow chart of a method for identifying abnormal blood sugar events according to another embodiment of the present application. As shown in FIG6 , in the embodiment shown in FIG4 of the present application, before step 403, the following steps may also be included:

[0159] In step 601, the first electronic device 31 determines whether the blood sugar fluctuation is caused by the first event based on the second data. If the blood sugar fluctuation is not caused by the first event, step 403 is executed; if the blood sugar fluctuation is caused by the first event, step 602 is executed.

[0160] In step 602 , the first electronic device 31 prompts the user that the blood sugar fluctuation is caused by the first event.

[0161] In step 603 , the first electronic device 31 records that the blood sugar fluctuation is caused by the first event, and records the time interval when the first event occurs.

[0162] In a specific implementation, after the first electronic device 31 determines that the blood sugar fluctuation is caused by the first event, the first electronic device 31 can directly record that the blood sugar fluctuation is caused by the first event and record the time interval when the first event occurred. In other words, step 602 and step 603 can be performed in parallel. Of course, steps 602 and 603 can also be performed one after another, which is not limited in this embodiment. Alternatively, the first electronic device 32 can also prompt the user that the blood sugar fluctuation is caused by the first event after the first electronic device 31 and obtain the user's confirmation information regarding the first event, and then record that the blood sugar fluctuation is caused by the first event and record the time interval when the first event occurred. In other words, step 603 is performed after step 602. Figure 6 shows that step 603 is performed after step 602 as an example.

[0163] The specific implementation of steps 601 to 603 is described below.

[0164] In one implementation, the second data may include first current information and first temperature information; the first event may be a user pressing the second electronic device 32. Thus, based on the second data, determining whether the blood sugar fluctuation is caused by the first event may be: when the first current information and the first temperature information conform to a first pattern, the first electronic device 31 determines that the blood sugar fluctuation is caused by the user pressing the second electronic device 32. The first pattern may be that the first current information first increases, then decreases, then increases again, and then returns to a stable state, and the first temperature information first decreases, then increases, then decreases again, and then returns to a stable state. Specifically, the first pattern may be: in the period before and after the blood sugar rise period, the first current information first increases from a relatively stable state, then decreases, and then rapidly increases and returns to a stable state during the pressure recovery period. Furthermore, in the period before and after the blood sugar rise period, the first temperature information first decreases (with a short period of fluctuation before the decrease), then increases, and then suddenly decreases at the beginning of the pressure recovery period and tends to another relatively stable state. Furthermore, the changing trends of the first temperature information and the first current information are significantly correlated over time. From the stable period to the fluctuating period and then to the stable period, the current signal quality generally deteriorates and then improves. Of course, it can be understood that the changing trends of the first current information and the first temperature information in the above first rule are only examples and do not constitute a limitation to this embodiment. The changing trends of the first current information and the first temperature information in the first rule can also be other trends, as long as they can reflect that the blood sugar fluctuations are caused by the user pressing the second electronic device. This embodiment does not limit the first rule.

[0165] In addition, based on the second data, other methods can also be used to determine whether the above-mentioned blood sugar fluctuations are caused by the user pressing the second electronic device 32. For example: the first electronic device 31 can input the first current information and the first temperature information into a pre-trained artificial intelligence (AI) model, and then the first electronic device 31 obtains the result output by the AI ​​model. The above result can be that the above-mentioned blood sugar fluctuations are caused by the user pressing the second electronic device 32.

[0166] In the above implementation, the first electronic device 31 prompts the user that the above blood sugar fluctuation is caused by the first event, which can be: the first electronic device 31 prompts the user of the event that the above blood sugar fluctuation is caused by the user pressing the second electronic device 32; specifically, the first electronic device 31 can prompt the user of the event that the above blood sugar fluctuation is caused by the user pressing the second electronic device 32 through a prompt interface, and the prompt interface can include the user's blood sugar information, the cause of the blood sugar fluctuation and the time interval of the first event. Figure 7 is a schematic diagram of the prompt interface of the first event provided in an embodiment of the present application.

[0167] In FIG7 , reference 71 indicates the user's blood sugar information. The text portion indicated by reference 72 includes the cause of the blood sugar fluctuation, "Suspected blood sugar fluctuation caused by pressure on the second electronic device," and the time period of the first event, "5:00 AM to 6:00 AM." Furthermore, the interface shown in FIG7 may also include a "Yes" icon 73 and a "No" icon 74 for the user to confirm whether the second electronic device 32 was pressed during the time period of "5:00 AM to 6:00 AM."

[0168] Thus, the first electronic device 31 records that the blood glucose fluctuation is caused by the first event and records the time period of the first event. This can be done by, after obtaining user confirmation information regarding the compression event, recording the event that the blood glucose fluctuation is caused by the user compressing the second electronic device 32, and recording a fourth time interval. The fourth time interval is the time interval during which the user compresses the second electronic device 32. The fourth time interval begins at the third time, ends at the sixth time, and is the time at which the blood glucose fluctuation within the second time interval relative to the third time decreases to less than the first threshold. It can be seen that the start time of the fourth time interval is the same as the start time of the third time interval, and the end time of the fourth time interval may also be the same as the end time of the third time interval. That is, the fourth time interval and the third time interval can be the same time interval, for example, 5:00 AM to 6:00 AM. This embodiment uses "third" and "fourth" to distinguish for ease of description. Of course, the end time of the fourth time interval may also be different from the end time of the third time interval. That is, the fourth time interval and the third time interval are different time intervals, and this embodiment does not limit this.

[0169] As described above, two icons of "Yes" and "No" are displayed in Figure 7. If the user clicks "Yes", the first electronic device 31 can obtain the user's confirmation information regarding the compression event, and then the first electronic device 31 can record the above-mentioned blood sugar fluctuation caused by the user compressing the second electronic device 32, and record the fourth time interval; on the contrary, if the user clicks "No", the first electronic device 31 obtains the user's denial information regarding the compression event, and the first electronic device 31 does not perform the recording operation.

[0170] In addition, the interface shown in Figure 7 may also not include the "Yes" icon 73 and the "No" icon 74. In this way, after the first electronic device 31 determines that the above-mentioned blood sugar fluctuation is caused by the user pressing the second electronic device 32, on the one hand, the first electronic device 31 prompts the user of the event that the above-mentioned blood sugar fluctuation is caused by the user pressing the second electronic device 32 through the interface shown in Figure 7. On the other hand, the first electronic device 31 does not need to wait for user confirmation, and can directly record the event that the above-mentioned blood sugar fluctuation is caused by the user pressing the second electronic device 32, as well as record the fourth time interval.

[0171] In another implementation, the second data may include first current information and first temperature information; the first event may be a user eating a meal; thus, determining whether the blood sugar fluctuation is caused by the first event based on the second data may be: when the first current information and the first temperature information conform to a second rule, determining that the blood sugar fluctuation is caused by the user eating a meal. The second rule may be: the first current information and the second temperature information show that the current value rises first, the temperature value rises later, and the current value reaches a peak after a third time period, and the temperature value subsequently reaches a peak, and then the temperature value and the current value show a decreasing trend to a stable state. The length of the third time period may be set according to system performance and / or implementation requirements during implementation. This embodiment does not limit the length of the third time period. For example, the third time period may be greater than or equal to 1 hour and less than or equal to 1.5 hours. Specifically, the second rule may be: approximately 0.5 to 1 hour after blood sugar rises, the temperature value begins to gradually increase; the current value rises first, the temperature value rises later, and the current value reaches a peak approximately 1 to 1.5 hours after rising, and then shows a decreasing trend to a stable state. Of course, it can be understood that the changing trends of the first current information and the first temperature information in the above second rule are only examples and do not constitute a limitation on this embodiment. The changing trends of the first current information and the first temperature information in the second rule can also be other trends, as long as they can reflect that the blood sugar fluctuations are caused by the user's meals. This embodiment does not limit the second rule.

[0172] In addition, based on the second data, other methods can also be used to determine whether the above-mentioned blood sugar fluctuations are caused by the user's meals. For example: the first electronic device 31 can input the first current information and the first temperature information into a pre-trained AI model, and then the first electronic device 31 obtains the result output by the AI ​​model. The above result can be that the above-mentioned blood sugar fluctuations are caused by the user's meals.

[0173] In this implementation, the first electronic device 31 prompts the user that the above-mentioned blood sugar fluctuation is caused by the first event as follows: the first electronic device 31 prompts the user that the above-mentioned blood sugar fluctuation is caused by the user's meal; specifically, the first electronic device 31 can prompt the user that the above-mentioned blood sugar fluctuation is caused by the user's meal through a prompt interface, and the prompt interface may include the user's blood sugar information, the cause of the blood sugar fluctuation and the time interval of the first event. Figure 8 is a schematic diagram of the prompt interface of the first event provided in another embodiment of the present application.

[0174] In FIG8 , reference 81 indicates the user's blood sugar information. The text portion indicated by reference 82 includes the reason for the blood sugar fluctuation, "blood sugar fluctuation suspected to be caused by a meal," and the time interval of the first event, "5:00 AM to 6:00 AM." Furthermore, the interface shown in FIG8 may also include a "Yes" icon 83 and a "No" icon 84 for the user to confirm whether a meal was consumed during the "5:00 AM to 6:00 AM" time interval.

[0175] Thus, the first electronic device 31 records that the blood glucose fluctuation is caused by the first event and records the time interval during which the first event occurs. This may include: the first electronic device 31 records the event that the blood glucose fluctuation is caused by the user eating a meal, and records a fifth time interval. The fifth time interval is the time interval during which the user eats a meal. The start time of the fifth time interval is the third time interval, and the end time of the fifth time interval is the seventh time interval. The seventh time interval is the time when the blood glucose fluctuation relative to the third time interval within the second time interval decreases to less than the first threshold. It can be seen that the start time of the fifth time interval is the same as the start time of the third time interval, and the end time of the fifth time interval may also be the same as the end time of the third time interval. In other words, the fifth time interval and the third time interval can be the same time interval, for example, 5:00 AM to 6:00 AM. This embodiment uses "third" and "fifth" to distinguish for ease of description. Of course, the end time of the fifth time interval may also be different from the end time of the third time interval. In other words, the fifth time interval and the third time interval are different time intervals, and this embodiment does not limit this.

[0176] As described above, two icons of "Yes" and "No" are displayed in Figure 8. If the user clicks "Yes", the first electronic device 31 can obtain the user's confirmation information regarding the meal event, and then the first electronic device 31 can record the above-mentioned blood sugar fluctuation event caused by the user's meal, and record the fifth time interval; on the contrary, if the user clicks "No", the first electronic device 31 obtains the user's denial information regarding the meal event, and the first electronic device 31 does not perform the recording operation.

[0177] In addition, the interface shown in Figure 8 may also not include the "Yes" icon 83 and the "No" icon 84. In this way, after the first electronic device 31 determines that the above-mentioned blood sugar fluctuation is caused by the user's meal, on the one hand, the first electronic device 31 can prompt the user of the event that the above-mentioned blood sugar fluctuation is caused by the user's meal through the interface shown in Figure 8. On the other hand, the first electronic device 31 does not need to wait for user confirmation, and can directly record the event that the above-mentioned blood sugar fluctuation is caused by the user's meal, as well as record the fifth time interval.

[0178] In addition, it should be noted that, in this embodiment, when the first electronic device 31 is an electronic device used by the user, for example, when the first electronic device 31 is implemented using the structure shown in Figure 1, the first electronic device 31 can display the prompt interface shown in Figure 7 or Figure 8 through its own display screen 194; of course, in this case, the first electronic device 31 can also send the first event and the time interval of the first event to other electronic devices used by the user other than the first electronic device 31 and the second electronic device 32, and the above-mentioned other electronic devices and / or the first electronic device 31 display the prompt interface shown in Figure 7 or Figure 8. For example, when the first electronic device 31 is a smart phone, the first electronic device 31 can send the above-mentioned blood sugar fluctuation event caused by the user's meal and the fifth time interval to the smart screen used by the user, and the above-mentioned smart screen and / or the first electronic device 31 display the prompt interface shown in Figure 8.

[0179] When the first electronic device 31 is a server, for example, when the first electronic device 31 is implemented using the structure shown in FIG3(a), the first electronic device 31 can send the first event and the time interval during which the first event occurs to other electronic devices used by the user other than the first electronic device 31 and the second electronic device 32, and the other electronic devices used by the user display the prompt interface shown in FIG7 or FIG8. For example, the first electronic device 31 can send the event that the blood sugar fluctuation is caused by the user's meal and the fifth time interval to the smartphone used by the user, and the smartphone used by the user displays the prompt interface of the abnormal blood sugar event.

[0180] Of course, the way in which the first electronic device 31 prompts the user that the above-mentioned blood sugar fluctuation is caused by the first event is not limited to prompting by displaying the prompt interface shown in Figure 7 or Figure 8. The first electronic device 31 can also prompt the user in other ways, for example: through voice broadcast. This embodiment does not limit the prompting method of the first electronic device 31.

[0181] In this embodiment, the first electronic device 31 can determine the cause of the blood sugar fluctuation based on the second data obtained from the second electronic device 32, without asking the user wearing the second electronic device about the sleeping time period and / or meal time period, thereby eliminating the interference of events such as stress and meals, thereby improving the accuracy of identifying abnormal blood sugar events.

[0182] In the application scenario shown in Figure 3(b), if the first electronic device 31 is a wearable device, for example, the first electronic device 31 is a smart watch or a smart bracelet, and the first electronic device 31 is worn by the user, then in the scenario shown in Figure 3(b), the first electronic device 31 generally directly establishes a communication connection with the second electronic device 32 to interact with data and / or information; or, as shown in Figure 9, the first electronic device 31 is not a wearable device, and the user also wears a third electronic device 33, which is a wearable device, then the method for identifying abnormal blood sugar events provided in the embodiment of the present application can refer to the description of the embodiments shown in Figures 10 and 11.

[0183] Figure 9 is a schematic diagram of an application scenario of a method for identifying abnormal blood sugar events provided by another embodiment of the present application. The above-mentioned third electronic device 33 can be a smart watch or a smart bracelet. Exemplarily, the third electronic device 33 can also be implemented using the structure shown in Figure 1; in Figure 9, a communication connection can be established between the first electronic device 31 and the third electronic device 33, and between the first electronic device 31 and the second electronic device 32 to exchange data and / or information. In specific implementation, the first electronic device 31 can directly establish communication connections with the second electronic device 32 and the third electronic device 33 respectively; or, the first electronic device 31 can also establish communication connections with the second electronic device 32 and the third electronic device 33 respectively through other electronic devices. The above-mentioned other electronic devices include other electronic devices used by the user in addition to the first electronic device 31, the second electronic device 32 and the third electronic device 33; for example, when the first electronic device 31 is a smart screen or a server, the first electronic device 31 can establish communication connections with the second electronic device 32 and the third electronic device 33 respectively through the smart phone used by the user. Of course, these are only some examples of the first electronic device 31 establishing communication connections with the second electronic device 32 and the third electronic device 33 respectively through other electronic devices. The embodiments of the present application are not limited to this. When the first electronic device 31 is an electronic device of different types, it can establish communication connections with the second electronic device 32 and the third electronic device 33 respectively through other electronic devices used by the user in addition to the first electronic device 31, the second electronic device 32 and the third electronic device 33. The embodiments of the present application are not limited to this.

[0184] In FIG9 , the third electronic device 33 is taken as an example as a smart watch.

[0185] The following describes a method for identifying abnormal blood sugar events in the application scenario shown in FIG3( b ), where the first electronic device 31 is a wearable device and is worn by the user, or in the application scenario shown in FIG9 .

[0186] Figure 10 is a flowchart of a method for identifying abnormal blood sugar events provided in another embodiment of the present application. In this embodiment, the first data may include the user's physiological data and / or sensor data of the wearable device, as well as third data within the first time interval; the third data is obtained from the second electronic device 32.

[0187] As shown in FIG10 , the above-mentioned method for identifying abnormal blood sugar events may include:

[0188] Step 1001 : The first electronic device 31 obtains the blood glucose information of the user within a first time interval from the second electronic device 32 .

[0189] The start time of the first time interval is the first moment, and the end time of the first time interval is the second moment. The first moment is before the current moment, and the second moment can be the current moment. Of course, this embodiment is not limited to this. The second moment can also be before the current moment, and this embodiment does not limit this, as long as the second moment is after the first moment. In addition, the duration of the first time interval can be the first duration. The length of the first duration can be set according to system performance and / or implementation requirements during specific implementation. This embodiment does not limit the above-mentioned first duration.

[0190] The above-mentioned blood glucose information is the blood glucose information of the above-mentioned user output by the second electronic device 32, and the blood glucose information may include the blood glucose value of the user. Specifically, the above-mentioned blood glucose information is obtained by the second electronic device 32 based on the original information detected by itself. The original information detected by the second electronic device 32 may include current information, temperature information and impedance spectrum. The second electronic device 32 can obtain the user's blood glucose information based on the detected current information, and then the second electronic device 32 can calibrate the blood glucose information using the temperature information and impedance spectrum. In this way, the first electronic device 31 obtains the calibrated blood glucose information from the second electronic device 32. Among them, the impedance spectrum can be the impedance spectrum of the electrochemical system in the second electronic device 32 measured by the second electronic device 32. The impedance spectrum can describe the state of the second electronic device 32, and can also be used together with the temperature information to calibrate the blood glucose information obtained by the second electronic device 32.

[0191] In some examples, if the first electronic device 31 directly establishes a communication connection with the second electronic device 32, then the first electronic device 31 can directly obtain the user's blood sugar information within the first time interval from the second electronic device 32; if the first electronic device 31 establishes a communication connection with the second electronic device 32 through other electronic devices used by the user, then the first electronic device 31 can obtain the user's blood sugar information within the first time interval from the second electronic device 32 through the above-mentioned other electronic devices.

[0192] Step 1002: If the blood sugar fluctuation at the second moment relative to the third moment within the first time interval is greater than or equal to the first threshold, the first electronic device 31 obtains the user's physiological data and / or sensor data of the wearable device, and obtains the third data within the first time interval from the second electronic device 32.

[0193] Among them, the above-mentioned third moment is before the second moment; the above-mentioned blood sugar fluctuation can be that the blood sugar value changes with time, and the blood sugar fluctuation of the second moment relative to the third moment within the first time interval is greater than or equal to the first threshold value can be: from the third moment to the second moment, as time goes by, the blood sugar value increases, and the difference between the blood sugar value at the second moment and the blood sugar value at the third moment is greater than or equal to the first threshold value.

[0194] The first threshold value can be set in a specific implementation. This embodiment does not limit the size of the first threshold value. For example, the first threshold value can be 20 mg / dl.

[0195] The third data may include original information detected by the second electronic device 32 . For example, the original information may include current information and temperature information detected by the second electronic device 32 . In addition, the original information may also include an impedance spectrum.

[0196] Similarly, if the first electronic device 31 directly establishes a communication connection with the second electronic device 32, then the first electronic device 31 can directly obtain the third data from the second electronic device 32; if the first electronic device 31 establishes a communication connection with the second electronic device 32 through other electronic devices used by the user, then the first electronic device 31 can obtain the third data from the second electronic device 32 through the above-mentioned other electronic devices.

[0197] Specifically, in the application scenario shown in FIG3(b), when the first electronic device 31 is a wearable device, the first electronic device 31 can obtain the physiological data of the user detected by the first electronic device 31 and / or the sensor data of the first electronic device 31; in the application scenario shown in FIG9, the first electronic device 31 can obtain the physiological data of the user and / or the sensor data of the third electronic device 33 from the third electronic device 33. In addition, in the application scenario shown in FIG9, if the first electronic device 31 directly establishes a communication connection with the third electronic device 33, then the first electronic device 31 can directly obtain the physiological data of the user and / or the sensor data of the third electronic device 33 from the third electronic device 33; if the first electronic device 31 establishes a communication connection with the third electronic device 33 through other electronic devices used by the user, then the first electronic device 31 can obtain the physiological data of the user and / or the sensor data of the third electronic device 33 from the third electronic device 33 through the above-mentioned other electronic devices.

[0198] The above-mentioned user's physiological data may include: the user's heart rate and / or body temperature. In some examples, the wearable device can be implemented through the structure shown in Figure 1. In this way, the wearable device can detect the user's body temperature through the temperature sensor 180J and detect the user's heart rate through the bone conduction sensor 180M. Of course, the user's physiological data is not limited to this. The wearable device can also detect other physiological data of the user, such as: pulse, etc. This embodiment does not limit the user's physiological data.

[0199] The sensor data of the above-mentioned wearable device may include: the swing path and / or swing frequency of the wearable device. The wearable device can detect the swing path and / or swing frequency of the wearable device through the acceleration sensor 180E and the gyroscope sensor 180B; similarly, the sensor data of the wearable device is not limited to this. For example, the sensor data of the wearable device may also include ambient light brightness, etc. This embodiment does not limit the sensor data of the above-mentioned wearable device.

[0200] In step 1003 , the first electronic device 31 determines that the blood sugar fluctuation is an abnormal blood sugar event based on the physiological data of the user and / or the sensor data of the wearable device, as well as the third data.

[0201] Among them, an abnormal blood sugar event can be an event in which a user's blood sugar level rises during a specific time period. The specific time period can include the dawn period (e.g., 3:00 AM to 9:00 AM) and / or the dusk period (e.g., 5:00 PM to 7:00 PM). The embodiments of this application do not limit the specific time intervals of the dawn period and the dusk period. Specifically, an abnormal blood sugar event that occurs during the dawn period can be referred to as a dawn phenomenon, and an abnormal blood sugar event that occurs during the dusk period can be referred to as a dusk phenomenon.

[0202] Specifically, the first electronic device 31 determines that the above-mentioned blood sugar fluctuation is an abnormal blood sugar event based on the physiological data of the above-mentioned user and / or the sensor data of the wearable device, as well as the above-mentioned third data. The specific manner in which this is determined can be found in the description of step 1101 in the embodiment shown in Figure 11 and will not be repeated here.

[0203] In some examples, after step 1003, the following steps may also be performed:

[0204] Step 1004: The first electronic device 31 determines the type of the abnormal blood sugar event according to the second moment.

[0205] Specifically, assuming that the second moment is in the dawn period (for example, 3 to 9 in the morning), the first electronic device 31 can determine that the type of the above-mentioned abnormal blood sugar event is a dawn phenomenon, and if the second moment is in the evening period (for example, 5 to 7 in the afternoon), the first electronic device 31 can determine that the type of the above-mentioned abnormal blood sugar event is a dusk phenomenon.

[0206] Step 1005: The first electronic device 31 obtains a sixth time interval during which the abnormal blood sugar event occurs.

[0207] The start time of the sixth time interval is the third time, and the end time of the sixth time interval is the eighth time. The eighth time is the time when the blood sugar fluctuation relative to the third time decreases to less than the first threshold.

[0208] In a specific implementation, if the blood sugar fluctuation at the second moment relative to the third moment within the first time interval is greater than or equal to the first threshold, the first electronic device 31 may first record the time interval of the blood sugar fluctuation, with the start time of the blood sugar fluctuation time interval being the third moment and the end time of the blood sugar fluctuation time interval being the second moment. After determining in step 1003 that the blood sugar fluctuation is a blood sugar abnormality event, the current blood sugar abnormality event identification process ends and the next identification process begins. If the blood sugar fluctuation at the start time of the next identification process relative to the third moment is still greater than or equal to the first threshold, then after executing steps 1002 and 1003, the first electronic device 31 may update the end time of the blood sugar fluctuation time interval to the start time of the next identification process, and then restart the next identification process. This continues until the blood sugar fluctuation at the start time of the Nth identification process relative to the third moment is less than the first threshold. At this point, the first electronic device 31 does not execute steps 1002 and 1003, but instead updates the end time of the blood sugar fluctuation time interval to the start time of the Nth identification process, and uses the blood sugar fluctuation time interval as the sixth time interval. As can be seen from the above description, the end time of the sixth time interval is later than the second moment.

[0209] It should be noted that the start time of the sixth time interval is the same as the start time of the third time interval, and the end time of the sixth time interval may also be the same as the end time of the third time interval. That is to say, the sixth time interval and the third time interval can be the same time interval in terms of time, for example: 5:00-6:00 in the morning. This embodiment uses "third" and "sixth" to distinguish for the convenience of description; of course, the end time of the sixth time interval may also be different from the end time of the third time interval. That is to say, the sixth time interval and the third time interval are different time intervals, and this embodiment does not limit this.

[0210] Step 1006: After determining that the user is not in a sleeping state, the first electronic device 31 prompts the user with the type of the abnormal blood sugar event and the sixth time interval.

[0211] Taking the dawn phenomenon as an example, after determining the type of abnormal blood sugar event, obtaining the sixth time interval, and determining that the user is not asleep, the first electronic device 31 can notify the user of the type of abnormal blood sugar event and the sixth time interval through a prompt interface for the abnormal blood sugar event. The prompt interface for the abnormal blood sugar event can be shown in FIG5 and is not further described here. In this embodiment, the first electronic device 31 only notifies the user after determining that the user is not asleep, thereby avoiding disturbing the user's sleep and improving the user experience.

[0212] It should be noted that in the scenario shown in Figure 3(b), when the first electronic device 31 is a wearable device, the first electronic device 31 can directly display the prompt interface shown in Figure 5, or it can send the type of abnormal blood sugar event and the sixth time interval to other electronic devices used by the user (for example, the smartphone used by the user) in addition to the first electronic device 31 and the second electronic device 32, and the prompt interface shown in Figure 5 will be displayed by the first electronic device 31 and / or the above-mentioned other electronic devices.

[0213] Similarly, in the scenario shown in FIG9 , the first electronic device 31 can directly display the prompt interface shown in FIG5 , or it can send the type of abnormal blood sugar event and the sixth time interval to other electronic devices used by the user in addition to the first electronic device 31 and the second electronic device 32 , and have the other electronic devices display the prompt interface shown in FIG5 . For example, in the scenario shown in FIG9 , when the first electronic device 31 is a smartphone, the first electronic device 31 can send the type of abnormal blood sugar event and the sixth time interval to the third electronic device 33 and / or the smart screen used by the user, and have the first electronic device 31, the third electronic device 33 and / or the smart screen used by the user display the prompt interface shown in FIG5 .

[0214] In some examples of this embodiment, the first electronic device 31 determines that the user is not in a sleep state as follows: the first electronic device 31 obtains the user's bedtime and wake-up time from the wearable device, and determines the time interval in which the user is in a sleep state based on the above-mentioned bedtime and wake-up time of the user. In this way, based on the time interval in which the user is in a sleep state, it can be determined whether the user is in a sleep state; when a certain moment does not belong to the time interval in which the user is in a sleep state, the first electronic device 31 can determine that the user is not in a sleep state at that moment.

[0215] In other examples, the first electronic device 31 may determine that the user is not asleep based on the user's physiological data and / or sensor data from the wearable device. As described above, the user's physiological data may include the user's heart rate and / or body temperature, and the wearable device's sensor data may include the wearable device's swing path and / or swing frequency. For example, a user's heart rate is typically lower when sleeping than when awake, and varies with different sleep stages. For example, in deep sleep, the heart rate is often lower and more stable. Therefore, the first electronic device 31 may determine whether the user is asleep based on the user's heart rate. Alternatively, a user's body temperature typically decreases during sleep, so the first electronic device 31 may determine whether the user is asleep based on the user's heart rate. Alternatively, when a user lies down and remains still for an extended period, the amplitude of the wearable device's swing path and the frequency of the wearable device's swing path decrease significantly. Therefore, if the wearable device's swing path and frequency are consistent with low-frequency, small-amplitude movements during sleep, the first electronic device 31 may also determine that the user has entered a sleep state.

[0216] The above introduces the way in which the first electronic device 31 determines whether the user is in a sleep state based on heart rate, body temperature, and the swing path and swing frequency of the wearable device, but this embodiment is not limited to this. The first electronic device 31 can not only determine whether the user is in a sleep state based on the above factors, but also combine the above factors to determine whether the user is in a sleep state. For example: the first electronic device 31 can determine whether the user is in a sleep state based on heart rate and body temperature, or the first electronic device 31 can determine whether the user is in a sleep state based on heart rate, swing path and swing frequency, or the first electronic device 31 can determine whether the user is in a sleep state based on heart rate, body temperature, and swing path and swing frequency. This embodiment does not limit this.

[0217] In the above-described method for identifying abnormal blood sugar events, after the first electronic device 31 obtains the user's blood sugar information for a first time interval from the second electronic device 32, if the blood sugar fluctuation at a second moment relative to a third moment in the first time interval is greater than or equal to a first threshold, the first electronic device 31 obtains the user's physiological data and / or wearable device sensor data, and obtains third data for the first time interval from the second electronic device 32. Based on the user's physiological data and / or wearable device sensor data, and the third data, the first electronic device 31 determines that the blood sugar fluctuation is a abnormal blood sugar event. This improves the accuracy of identifying abnormal blood sugar events and eliminates interference from events such as stress and meals by eliminating the need to inquire about sleep and / or meal times from the user wearing the CGM sensor. Furthermore, in this embodiment, the first electronic device 31 can identify abnormal blood sugar events in combination with the user's physiological data and / or wearable device sensor data. Compared to the embodiment shown in FIG4 , this eliminates the need to obtain data for the second time interval from the second electronic device 32, thereby shortening the time required to identify abnormal blood sugar events and improving the efficiency of abnormal blood sugar event identification.

[0218] FIG11 is a flow chart of a method for identifying abnormal blood sugar events according to another embodiment of the present application. As shown in FIG11 , in the embodiment shown in FIG10 of the present application, before step 1003, the following steps may also be included:

[0219] In step 1101, the first electronic device 31 determines whether the blood sugar fluctuation is caused by a first event based on the user's physiological data and / or sensor data from the wearable device, as well as the third data. If the blood sugar fluctuation is not caused by the first event, step 1003 is executed; if the blood sugar fluctuation is caused by the first event, step 1102 is executed.

[0220] Step 1102: After determining that the user is not in a sleeping state, the first electronic device 31 prompts the user that the blood sugar fluctuation is caused by the first event.

[0221] The manner in which the first electronic device 31 determines that the user is not in a sleeping state may refer to the description in step 1006 of the embodiment shown in FIG10 , and will not be repeated here.

[0222] In this embodiment, the first electronic device 31 prompts the user only after determining that the user is not in a sleeping state, thereby not disturbing the user's sleep and improving the user's usage experience.

[0223] In step 1103 , the first electronic device 31 records that the blood sugar fluctuation is caused by the first event, and records the time interval when the first event occurs.

[0224] The start time of the time interval in which the first event occurs is the third time, and the end time may be the time when the blood glucose fluctuation relative to the first time decreases to less than the first threshold. In a specific implementation, the end time of the time interval in which the first event occurs is determined in the same manner as the end time of the sixth time interval. Please refer to the relevant description in step 1005 of the embodiment shown in FIG10 , and will not be repeated here.

[0225] In a specific implementation, after the first electronic device 31 determines that the blood sugar fluctuation is caused by the first event, the first electronic device 31 can directly record that the blood sugar fluctuation is caused by the first event and record the time interval when the first event occurred. In other words, step 1102 and step 1103 can be performed in parallel. Of course, step 1102 and step 1103 can also be performed successively, which is not limited in this embodiment. Alternatively, the first electronic device 32 can also prompt the user that the blood sugar fluctuation is caused by the first event after the first electronic device 31 and obtain the user's confirmation information regarding the first event, and then record that the blood sugar fluctuation is caused by the first event and record the time interval when the first event occurred. In other words, step 1103 is performed after step 1102. Figure 11 shows an example of step 1103 being performed after step 1102.

[0226] The specific implementation of steps 1101 to 1103 is described below.

[0227] In one implementation, the third data may include second current information and second temperature information, and the first event may be a user eating a meal. Thus, based on the user's physiological data and / or sensor data of the wearable device, as well as the third data, determining whether the blood sugar fluctuation is caused by the first event may be as follows: when the second current information and the second temperature information conform to the second rule, if, based on the user's physiological data and / or sensor data of the wearable device, it is determined that the user has eaten a meal within the first time interval, then determining that the blood sugar fluctuation is caused by the user eating a meal. For the second rule, please refer to the description of the second rule in the embodiment shown in FIG6 of this application, which will not be repeated here.

[0228] The physiological data of the above-mentioned user may include: the user's heart rate, and the sensor data of the above-mentioned wearable device may include: the swing path and / or swing frequency of the wearable device. In this way, according to the physiological data of the above-mentioned user and / or the sensor data of the wearable device, determining that the user has a dining behavior in the first time interval can be: according to the swing path of the wearable device, determining that the user has a wrist movement from the mouth in the first time interval, and according to the swing frequency of the wearable device, determining that the movement frequency of the user's wrist movement from the mouth is consistent with the movement frequency of the dining behavior, the first electronic device 31 can determine that the user has a dining behavior in the first time interval; and / or, according to the user's heart rate, when the user's heart rate is high for a period of time in the first time interval, the first electronic device 31 can also determine that the user has a dining behavior in the first time interval. This is because before and after a meal, especially after ingesting food, the human body's basal metabolic rate may temporarily increase, resulting in a certain degree of increase in heart rate.

[0229] In addition, based on the user's physiological data and / or the sensor data of the wearable device, as well as the third data, other methods can also be used to determine whether the above-mentioned blood sugar fluctuations are caused by the user's meals. For example: the first electronic device 31 can input the user's physiological data and / or the sensor data of the wearable device, the second current information and the second temperature information into a pre-trained AI model, and then the first electronic device 31 obtains the result output by the AI ​​model. The above result can be that the above-mentioned blood sugar fluctuations are caused by the user's meals.

[0230] Next, the first electronic device 31 can prompt the user of the event that the above-mentioned blood sugar fluctuation is caused by the user's meal through the interface shown in Figure 8. For details, please refer to the relevant description in the embodiment shown in Figure 6 of this application, which will not be repeated here.

[0231] In another implementation, the third data may include second current information and second temperature information, and the first event may be the user pressing the second electronic device 32. Thus, based on the user's physiological data and / or wearable device sensor data, and the third data, determining whether the blood sugar fluctuation is caused by the first event may be as follows: when the second current information and the second temperature information conform to the first rule, if, based on the user's physiological data and / or wearable device sensor data, it is determined that the user pressed the second electronic device 32 during the first time interval, then determining that the blood sugar fluctuation is caused by the user pressing the second electronic device 32. For the first rule, reference may be made to the description of the first rule in the embodiment shown in FIG. 6 of this application, and no further details will be given here.

[0232] As described above, the physiological data of the above-mentioned user may include: the user's heart rate, and the sensor data of the above-mentioned wearable device may include: the swing path and / or swing frequency of the wearable device. In this way, based on the above-mentioned physiological data of the user and / or the sensor data of the wearable device, determining that the user has pressed the second electronic device 32 in the first time interval can be: based on the swing path and / or swing frequency of the wearable device, determining that the user's arm has not moved for a long period of time in the first time interval, and the arm is the arm on which the user wears the second electronic device 32, the first electronic device 31 can determine that the user has pressed the second electronic device 32 in the first time interval; and / or, based on the user's heart rate, when the user's heart rate is low for a period of time in the first time interval, the first electronic device 31 can determine that the user has pressed the second electronic device 32 in the first time interval.

[0233] In addition, based on the user's physiological data and / or the sensor data of the wearable device, as well as the third data, other methods can also be used to determine whether the above-mentioned blood sugar fluctuations are caused by the user pressing the second electronic device 32. For example: the first electronic device 31 can input the user's physiological data and / or the sensor data of the wearable device, the second current information and the second temperature information into a pre-trained AI model, and then the first electronic device 31 obtains the result output by the AI ​​model. The above result can be that the above-mentioned blood sugar fluctuations are caused by the user pressing the second electronic device 32.

[0234] Next, the first electronic device 31 can prompt the user through the interface shown in Figure 7 that the above-mentioned blood sugar fluctuation is caused by the user pressing the second electronic device 32. For details, please refer to the relevant description in the embodiment shown in Figure 6 of this application, which will not be repeated here.

[0235] In this embodiment, the first electronic device 31 can combine the user's physiological data and / or wearable device sensor data with the third data to determine whether blood sugar fluctuations are caused by eating or by stressing the second electronic device 32. This eliminates the need to inquire about sleep and / or meal times from the user wearing the second electronic device 32, thereby eliminating interference from events such as stress and eating, and thus improving the accuracy of identifying abnormal blood sugar events. In addition, compared to the embodiments shown in Figures 4 and 6, the first electronic device 31 can identify abnormal blood sugar events without obtaining data within the second time interval from the second electronic device 32, thereby shortening the time required to identify abnormal blood sugar events and improving the efficiency of identifying abnormal blood sugar events.

[0236] In specific implementation, the methods provided in the embodiments shown in Figures 4 to 6 of the present application may also be used in combination with the methods provided in the embodiments shown in Figures 10 to 11. Referring to Figure 12, Figure 12 is a flow chart of a method for identifying abnormal blood sugar events provided in another embodiment of the present application. As shown in Figure 12, the above-mentioned method for identifying abnormal blood sugar events may include:

[0237] Step 1201 : The first electronic device 31 obtains the blood glucose information of the user within a first time interval from the second electronic device 32 .

[0238] For the introduction of the first time interval and the blood glucose information, please refer to the description of step 401 in the embodiment shown in FIG4 , which will not be repeated here.

[0239] In step 1202, if the blood glucose fluctuation between the second moment and the third moment within the first time interval is greater than or equal to the first threshold, the first electronic device 31 determines whether the first electronic device 31 has the capability to obtain the fourth data from the wearable device. If the first electronic device 31 has the capability to obtain the fourth data from the wearable device, step 1211 is executed; if the first electronic device 31 does not have the capability to obtain the fourth data from the wearable device, step 1203 is executed.

[0240] Specifically, the first electronic device 31 determines whether the first electronic device 31 has the ability to obtain the fourth data of the wearable device as follows: the first electronic device 31 determines whether the user is wearing a wearable device. If the user is wearing a wearable device, the first electronic device 31 determines whether the fourth data of the wearable device can be obtained. If the first electronic device 31 obtains the fourth data of the wearable device, the first electronic device 31 determines that it has the ability to obtain the fourth data of the wearable device; if the first electronic device 31 does not obtain the fourth data of the wearable device, and / or the user is not wearing the wearable device, the first electronic device 31 determines that it does not have the ability to obtain the fourth data of the wearable device.

[0241] Specifically, in the scenario shown in Figure 3(b), when the first electronic device 31 is not a wearable device, the first electronic device 31 cannot obtain the information of the wearable device worn by the user, so the first electronic device 31 can determine that the fourth data cannot be obtained; and in the scenario shown in Figure 3(b), when the first electronic device 31 is a wearable device, if the first electronic device 31 is worn by the user, then the first electronic device 31 can obtain the information of the wearable device worn by the user, and then the first electronic device 31 can determine whether the fourth data of the wearable device can be obtained.

[0242] In the scenario shown in Figure 9, the first electronic device 31 can obtain information from the third electronic device 33 whether the user is wearing the third electronic device 33. If the user is wearing the third electronic device 33, the first electronic device 31 determines whether the fourth data of the third electronic device 33 can be obtained.

[0243] The fourth data may include physiological data of the user and / or sensor data of the wearable device. Of course, the fourth data may also include other data. This embodiment does not limit the data included in the fourth data.

[0244] Steps 1203 to 1210 are the same as steps 402 to 603.

[0245] Steps 1211 to 1218 are the same as steps 1002 to 1103.

[0246] In the above-mentioned method for identifying abnormal blood sugar events, the first electronic device 31 obtains the blood sugar information of the user within a first time interval from the second electronic device 32. If the blood sugar fluctuation between the second current moment and the first three moments within the first time interval is greater than or equal to the first threshold, the first electronic device 31 determines whether the fourth data of the wearable device is obtained. If the fourth data of the wearable device is not obtained, the first electronic device 31 obtains the second data within the first time interval and the second time interval from the second electronic device 32. Based on the above-mentioned second data, it is determined that the above-mentioned blood sugar fluctuation is an abnormal blood sugar event, thereby improving the accuracy of identifying abnormal blood sugar events, and there is no need to ask the user wearing the CGM device about the sleep time period and / or the use time. meal time period, which can eliminate the interference of events such as stress and meals; and if the fourth data of the wearable device is obtained, the first electronic device 31 obtains the user's physiological data and / or the sensor data of the wearable device, and obtains the third data within the first time interval from the second electronic device 32. According to the above-mentioned user physiological data and / or the sensor data of the wearable device, and the above-mentioned third data, it is determined that the above-mentioned blood sugar fluctuation is an abnormal blood sugar event, so that the abnormal blood sugar event can be identified in combination with the user's physiological data and / or the sensor data of the wearable device, and there is no need to obtain the data within the second time interval from the second electronic device 32, thereby shortening the time required for identifying abnormal blood sugar events and improving the efficiency of identifying abnormal blood sugar events.

[0247] In addition, in the description of the above embodiments, the first electronic device 31 is used as the execution entity to illustrate the method for identifying abnormal blood sugar events provided by the embodiments of the present application, but the embodiments of the present application are not limited to this. In the scenarios shown in Figures 3(b) and 9, the method for identifying abnormal blood sugar events provided by the embodiments of the present application can also be executed by the second electronic device 32.

[0248] Figure 13 is a flowchart of a method for identifying abnormal blood sugar events provided in another embodiment of the present application. This embodiment introduces a method for identifying abnormal blood sugar events in the scenario shown in Figure 3(b). In this embodiment, the first data may include second data within the first time interval and the second time interval.

[0249] As shown in FIG13 , the above-mentioned method for identifying abnormal blood sugar events may include:

[0250] Step 1301: The second electronic device 32 obtains the blood glucose information of the user within a first time interval.

[0251] The description of the first time interval and blood glucose information can be found in step 401 of the embodiment shown in FIG4 , and will not be repeated here. This step differs from step 401 in that the second electronic device 32 obtains the user's blood glucose information from itself, whereas in step 401, the first electronic device 31 obtains the user's blood glucose information from the second electronic device 32.

[0252] Step 1302: If the blood sugar fluctuation at the second moment relative to the third moment in the first time interval is greater than or equal to the first threshold, the second electronic device 32 obtains second data in the first time interval and the second time interval.

[0253] A detailed description of this step can be found in the description of step 402 of the embodiment shown in FIG4 , which will not be repeated here. The difference between this step and step 402 is that the second electronic device 32 obtains the second data from itself, while in step 402, the first electronic device 31 obtains the second data from the second electronic device 32.

[0254] In step 1303 , the second electronic device 32 determines that the blood sugar fluctuation is an abnormal blood sugar event based on the second data.

[0255] For the description of abnormal blood sugar events, please refer to the description of step 403 of the embodiment shown in FIG4 , which will not be repeated here.

[0256] Specifically, before step 1303, the second electronic device 32 can determine whether the blood sugar fluctuation is caused by the first event based on the second data. If the blood sugar fluctuation is not caused by the first event, the second electronic device 32 can determine that the blood sugar fluctuation is an abnormal blood sugar event; if the blood sugar fluctuation is caused by the first event, the second electronic device 32 prompts the user that the blood sugar fluctuation is caused by the first event, records the blood sugar fluctuation as being caused by the first event, and records the time interval during which the first event occurred. The specific implementation of the above steps can be found in the description of steps 601 to 603 in the embodiment shown in Figure 6, and will not be repeated here.

[0257] In some examples, after step 1303, the following steps may also be performed:

[0258] Step 1304: The second electronic device 32 determines the type of the abnormal blood sugar event according to the second moment.

[0259] For detailed description, please refer to the description of step 404 in the embodiment shown in FIG4 , which will not be repeated here.

[0260] Step 1305: The second electronic device 32 records the third time interval during which the abnormal blood sugar event occurs.

[0261] For the description of the third time interval, please refer to the description of step 405 in the embodiment shown in FIG4 , which will not be repeated here.

[0262] In step 1306 , the second electronic device 32 prompts the user with the type of the abnormal blood sugar event and the third time interval.

[0263] Specifically, the second electronic device 32 prompts the user with the type of the above-mentioned abnormal blood sugar event and the third time interval as follows: the second electronic device 32 sends the type of the above-mentioned abnormal blood sugar event and the third time interval to other electronic devices used by the user except the second electronic device 32, and then the other electronic devices prompt the user with the type of the above-mentioned abnormal blood sugar event and the third time interval through the interface shown in Figure 5.

[0264] For example, in the scenario shown in Figure 3(b), when the first electronic device 31 is an electronic device used by the user, such as a smartphone, tablet computer and / or wearable device, the second electronic device 32 can send the type of the above-mentioned abnormal blood sugar event and the third time interval to the first electronic device 31, and the first electronic device 31 displays the interface shown in Figure 5 through the display screen 194; or, in the scenario shown in Figure 3(b), when the first electronic device 31 is a server, the second electronic device 32 can send the type of the above-mentioned abnormal blood sugar event and the third time interval to the first electronic device 31, and then the first electronic device 31 sends the type of the above-mentioned abnormal blood sugar event and the third time interval to the electronic device used by the user, such as a smartphone, tablet computer or wearable device, and the electronic device used by the above-mentioned user displays the interface shown in Figure 5.

[0265] In the above-mentioned method for identifying abnormal blood sugar events, after the second electronic device 32 obtains the blood sugar information of the user in the first time interval, if the blood sugar fluctuation at the second moment relative to the third moment in the first time interval is greater than or equal to the first threshold, the second electronic device 32 obtains second data in the first time interval and the second time interval, and determines that the above-mentioned blood sugar fluctuation is an abnormal blood sugar event based on the above-mentioned second data, thereby improving the accuracy of identifying abnormal blood sugar events, and there is no need to inquire about the sleeping time period and / or meal time period from the user wearing the CGM device, thereby eliminating interference from events such as stress and meals.

[0266] Figure 14 is a flowchart of a method for identifying abnormal blood sugar events provided in yet another embodiment of the present application. This embodiment describes the method for identifying abnormal blood sugar events in the scenario shown in Figure 3(b), where the first electronic device 31 is a wearable device and is worn by the user, or in the scenario shown in Figure 9. In this embodiment, the first data includes the user's physiological data and / or sensor data of the wearable device, as well as third data within the first time interval.

[0267] As shown in FIG14 , the above-mentioned method for identifying abnormal blood sugar events may include:

[0268] Step 1401: The second electronic device 32 obtains the blood glucose information of the user within a first time interval.

[0269] The description of the first time interval and blood glucose information can be found in the description of step 1001 of the embodiment shown in FIG10 , and will not be repeated here. This step differs from step 1001 in that the second electronic device 32 obtains the user's blood glucose information from itself, while in step 1001, the first electronic device 31 obtains the user's blood glucose information from the second electronic device 32.

[0270] Step 1402: If the blood sugar fluctuation at the second moment relative to the third moment in the first time interval is greater than or equal to the first threshold, the second electronic device 32 obtains the user's physiological data and / or sensor data of the wearable device, and obtains the third data in the first time interval.

[0271] A detailed description of this step can be found in the description of step 1002 of the embodiment shown in FIG10 , which will not be repeated here. The difference between this step and step 1002 is that the second electronic device 32 obtains the third data from itself, while in step 1002, the first electronic device 31 obtains the third data from the second electronic device 32.

[0272] In addition, in this step, when the first electronic device 31 is a wearable device, the second electronic device 32 can obtain the user's physiological data and / or sensor data of the wearable device from the first electronic device 31; or, when the first electronic device 31 is not a wearable device, the second electronic device 32 can obtain the user's physiological data and / or sensor data of the wearable device from the third electronic device 33.

[0273] In step 1403 , the second electronic device 32 determines that the blood sugar fluctuation is an abnormal blood sugar event based on the physiological data of the user and / or the sensor data of the wearable device, as well as the third data.

[0274] For the description of abnormal blood sugar events, please refer to the description of step 1003 of the embodiment shown in FIG10 , which will not be repeated here.

[0275] Compared with the embodiment shown in Figure 13, the difference is that in this embodiment, the user wears a wearable device, so the second electronic device 32 can obtain the user's physiological data and / or the sensor data of the wearable device. In this way, the second electronic device 32 only needs to obtain the third data within the first time interval, and can identify abnormal blood sugar events based on the user's physiological data and / or the sensor data of the wearable device, as well as the third data, thereby shortening the time required to identify abnormal blood sugar events and improving the efficiency of identifying abnormal blood sugar events.

[0276] Specifically, before step 1403, the second electronic device 32 can determine whether the above-mentioned blood sugar fluctuation is caused by the first event based on the physiological data of the above-mentioned user and / or the sensor data of the wearable device, as well as the above-mentioned third data. If the above-mentioned blood sugar fluctuation is not caused by the first event, the second electronic device 32 can determine that the above-mentioned blood sugar fluctuation is an abnormal blood sugar event; if the above-mentioned blood sugar fluctuation is caused by the first event, the second electronic device 32 determines that the user is not in a sleeping state, prompts the user that the above-mentioned blood sugar fluctuation is caused by the first event, and records the blood sugar fluctuation caused by the first event, and records the time interval of the above-mentioned first event. The specific implementation methods of the above steps can be found in the description of steps 1101 to 1103 in the embodiment shown in Figure 10, which will not be repeated here.

[0277] In some examples, after step 1403, the following steps may also be performed:

[0278] Step 1404: The second electronic device 32 determines the type of the abnormal blood sugar event according to the second moment.

[0279] For detailed description, please refer to the description of step 1004 in the embodiment shown in FIG10 , which will not be repeated here.

[0280] Step 1405: The second electronic device 32 obtains a sixth time interval during which the abnormal blood sugar event occurs.

[0281] For the description of the sixth time interval, please refer to the description of step 1005 in the embodiment shown in FIG10 , which will not be repeated here.

[0282] Step 1406: After determining that the user is not in a sleeping state, the second electronic device 32 prompts the user with the type of the abnormal blood sugar event and the sixth time interval.

[0283] Specifically, the second electronic device 32 prompts the user of the type of abnormal blood sugar event and the sixth time interval as follows: the second electronic device 32 sends the type of abnormal blood sugar event and the sixth time interval to other electronic devices used by the user other than the second electronic device 32, and then the other electronic devices prompt the user of the type of abnormal blood sugar event and the third time interval through the interface shown in Figure 5.

[0284] For example, in the scenario shown in Figure 3(b), when the first electronic device 31 is a wearable device, the second electronic device 32 can send the type of the above-mentioned abnormal blood sugar event and the sixth time interval to the first electronic device 31, and the first electronic device 31 displays the interface shown in Figure 5 through the display screen 194.

[0285] In the scenario shown in Figure 9, the second electronic device 32 can send the type of the above-mentioned abnormal blood sugar event and the sixth time interval to the first electronic device 31 and the third electronic device 33; when the first electronic device 31 is an electronic device used by the user, such as a smartphone and / or a tablet computer, the first electronic device 31 and / or the third electronic device 33 display the interface shown in Figure 5; or, when the first electronic device 31 is a server, the first electronic device 31 sends the type of the above-mentioned abnormal blood sugar event and the third time interval to the electronic device used by the user, such as a smartphone and / or a tablet computer, and the electronic device used by the above-mentioned user and / or the third electronic device 33 display the interface shown in Figure 5.

[0286] In the above-described method for identifying abnormal blood sugar events, after the second electronic device 32 obtains the user's blood sugar information during a first time interval, if the blood sugar fluctuation at a second moment relative to a third moment within the first time interval is greater than or equal to a first threshold, the second electronic device 32 obtains the user's physiological data and / or wearable device sensor data, as well as the third data within the first time interval. Based on the user's physiological data and / or wearable device sensor data, and the third data, the second electronic device 32 determines that the blood sugar fluctuation is a abnormal blood sugar event. This improves the accuracy of identifying abnormal blood sugar events and eliminates interference from events such as stress and meals by eliminating the need to inquire about sleep and / or meal times from the user wearing the CGM sensor. Furthermore, in this embodiment, the second electronic device 32 can combine the user's physiological data and / or wearable device sensor data to identify abnormal blood sugar events. Compared to the embodiment shown in FIG13 , this eliminates the need to obtain data within the second time interval, thereby shortening the time required to identify abnormal blood sugar events and improving the efficiency of identifying abnormal blood sugar events.

[0287] In addition, similar to the embodiment shown in FIG12 , the embodiment shown in FIG13 and the embodiment shown in FIG14 can also be used in combination. That is, after the second electronic device 32 obtains the user's blood sugar information within the first time interval, if the blood sugar fluctuation at the second moment relative to the third moment within the first time interval is greater than or equal to the first threshold, the second electronic device 32 determines whether the fourth data from the wearable device has been obtained. If the second electronic device 32 obtains the fourth data from the wearable device, steps 1302 to 1306 are executed; if the second electronic device 32 does not obtain the fourth data from the wearable device, steps 1402 to 1406 are executed.

[0288] Among them, the way in which the second electronic device 32 determines whether the fourth data of the wearable device is obtained can be referred to the description in step 1202 of the embodiment shown in Figure 12, and will not be repeated here.

[0289] It is understood that some or all of the steps or operations in the above embodiments are merely examples, and the present application embodiments may also perform other operations or variations of various operations. In addition, the various steps may be performed in a different order than those presented in the above embodiments, and it is possible that not all of the operations in the above embodiments need to be performed.

[0290] It is understandable that, in order to realize the above functions, the electronic device includes hardware and / or software modules corresponding to the execution of each function. In combination with the algorithm steps of each example described in the embodiments disclosed in this application, this application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or 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 in combination with the embodiments, but such implementation should not be considered to be beyond the scope of this application.

[0291] This embodiment can divide the electronic device into functional modules based on the above-mentioned method embodiment. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is illustrative and is only a logical functional division. In actual implementation, other division methods may be used.

[0292] FIG15 is a schematic diagram of the structure of an electronic device provided in yet another embodiment of the present application. In the case where each functional module is divided according to its function, FIG15 shows a possible schematic diagram of the composition of an electronic device 1500 involved in the above embodiment. As shown in FIG15 , the electronic device 1500 may include: a receiver 1501, a processor 1502, and a transmitter 1503.

[0293] The receiver 1501 may be used to support the electronic device 1500 in executing step 401, step 402, steps 1001 to 1002, step 1201, steps 1301 to 1302, steps 1401 to 1402, and / or other processes of the technical solutions described in the embodiments of the present application.

[0294] Processor 1502 can be used to support electronic device 1500 to execute steps 403 to 406, steps 601 to 603, steps 1003 to 1006, steps 1101 to 1103, steps 1202 to 1218, steps 1303 to 1306, steps 1403 to 1406, etc., and / or other processes of the technical solutions described in the embodiments of the present application.

[0295] It should be noted that all relevant contents of each step involved in the method embodiments shown in Figures 3 to 14 of the present application can be referred to the functional description of the corresponding functional modules and will not be repeated here.

[0296] The electronic device 1500 provided in this embodiment is used to execute the above-mentioned method for identifying abnormal blood sugar events, and thus can achieve the same effect as the above-mentioned method.

[0297] It should be understood that the electronic device 1500 may correspond to the electronic device 100 shown in FIG1 . The functions of the receiver 1501 and the transmitter 1503 may be implemented by the processor 110, antenna 1, and mobile communication module 150, and / or by the processor 110, antenna 2, and wireless communication module 160, in the electronic device 100 shown in FIG1 ; the function of the processor 1502 may be implemented by the processor 110 and display screen 194 in the electronic device 100 shown in FIG1 .

[0298] In the case of an integrated device, the electronic device 1500 may include a processing module, a storage module, and a communication module.

[0299] The processing module can be used to control and manage the operation of the electronic device 1500. For example, it can be used to support the electronic device 1500 in executing the steps performed by the receiver 1501, processor 1502, and transmitter 1503. The storage module can be used to support the electronic device 1500 in storing program code and data. The communication module can be used to support the electronic device 1500 in communicating with other devices.

[0300] Among them, the processing module can be a processor or a controller, which can implement or execute the various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, and so on. The storage module can be a memory. The communication module can specifically be a device that interacts with other electronic devices, such as a radio frequency circuit, a Bluetooth chip and / or a Wi-Fi chip.

[0301] In one embodiment, when the processing module is a processor and the storage module is a memory, the electronic device 1500 involved in this embodiment may be a device having the structure shown in FIG. 1 .

[0302] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer-readable storage medium is run on a computer, it enables the computer to execute the method provided in the embodiments shown in Figures 3 to 14 of the present application.

[0303] An embodiment of the present application further provides a computer program product, which includes a computer program. When the computer program is run on a computer, the computer executes the method provided in the embodiments shown in Figures 3 to 14 of the present application.

[0304] In the embodiments of the present application, "at least one" refers to one or more, and "more" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can represent: a, b, c, a and b, a and c, b and c or a and b and c, where a, b, c can be single or multiple.

[0305] Those skilled in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented using a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians 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.

[0306] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0307] In the several embodiments provided in this application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of this application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0308] The above description is merely a specific embodiment of the present application. Any person skilled in the art may easily conceive of variations or substitutions within the technical scope disclosed in this application, and such variations or substitutions shall be within the scope of protection of this application. The scope of protection of this application shall be subject to the scope of protection of the claims.

Claims

1. A method for identifying abnormal blood sugar events, characterized in that: include: The first electronic device obtains the blood glucose information of the user within a first time interval, wherein the start time of the first time interval is a first time, the end time of the first time interval is a second time, the first time is before the current time, and the second time is the current time; If the blood sugar fluctuation at the second moment relative to a third moment within the first time interval is greater than or equal to a first threshold, acquiring the first data; wherein the third moment is before the second moment; According to the first data, the blood sugar fluctuation is determined to be an abnormal blood sugar event.

2. The method according to claim 1, characterized in that The first data includes second data within the first time interval and a second time interval; the start time of the second time interval is the second time, the end time of the second time interval is a fourth time, and the fourth time is after the second time; Determining, based on the first data, that the blood sugar fluctuation is a blood sugar abnormality event includes: According to the second data, the blood sugar fluctuation is determined to be an abnormal blood sugar event.

3. The method according to claim 2, characterized in that After determining that the blood sugar fluctuation is a blood sugar abnormality event, the method further includes: determining the type of the abnormal blood sugar event according to the second moment; Recording a third time interval in which the abnormal blood sugar event occurs; wherein the start time of the third time interval is the third moment, the end time of the third time interval is the fifth moment, and the fifth moment is the moment when the blood sugar fluctuation relative to the third moment in the second time interval decreases to less than the first threshold; The type of the abnormal blood sugar event and the third time interval are prompted to the user.

4. The method according to claim 2 or 3, characterized in that The step of determining, based on the second data, that the blood sugar fluctuation is before an abnormal blood sugar event occurs further includes: determining, based on the second data, whether the blood sugar fluctuation is caused by a first event; Determining, based on the second data, that the blood sugar fluctuation is a blood sugar abnormality event includes: If it is determined based on the second data that the blood sugar fluctuation is not caused by the first event, the blood sugar fluctuation is determined to be an abnormal blood sugar event.

5. The method according to claim 4, characterized in that After determining whether the blood sugar fluctuation is caused by the first event based on the second data, the method further includes: If the blood sugar fluctuation is caused by the first event, the user is prompted that the blood sugar fluctuation is caused by the first event.

6. The method according to claim 5, characterized in that After determining whether the blood sugar fluctuation is caused by the first event based on the second data, the method further includes: If the blood sugar fluctuation is caused by the first event, it is recorded that the blood sugar fluctuation is caused by the first event, and the time interval in which the first event occurs is recorded.

7. The method according to claim 6, characterized in that The blood sugar information and the second data are obtained from a second electronic device; wherein the second electronic device is worn on the user.

8. The method according to claim 7, characterized in that The second data includes first current information and first temperature information; the first event includes the user pressing the second electronic device; Determining, based on the second data, whether the blood sugar fluctuation is caused by the first event includes: When the first current information and the first temperature information conform to a first rule, it is determined that the blood sugar fluctuation is caused by the user pressing the second electronic device.

9. The method according to claim 8, characterized in that Prompting the user that the blood sugar fluctuation is caused by the first event includes: The event that the blood sugar fluctuation is caused by the user pressing the second electronic device is notified to the user.

10. The method according to claim 8, characterized in that The step of recording that the blood sugar fluctuation is caused by the first event and recording the time interval during which the first event occurs includes: Record the event that the blood sugar fluctuation is caused by the user pressing the second electronic device, and record a fourth time interval; wherein the fourth time interval is the time interval when the user presses the second electronic device, the start time of the fourth time interval is the third time, and the end time of the fourth time interval is the sixth time, and the sixth time is the time when the blood sugar fluctuation in the second time interval relative to the third time is reduced to less than the first threshold.

11. The method according to claim 7, characterized in that The second data includes first current information and first temperature information; the first event includes the user eating; Determining, based on the second data, whether the blood sugar fluctuation is caused by the first event includes: When the first current information and the first temperature information conform to a second rule, it is determined that the blood sugar fluctuation is caused by the user eating a meal.

12. The method according to claim 11, characterized in that Prompting the user that the blood sugar fluctuation is caused by the first event includes: The user is notified of an event that the blood sugar fluctuation is caused by the user's meal.

13. The method according to claim 11, characterized in that The step of recording that the blood sugar fluctuation is caused by the first event and recording the time interval during which the first event occurs includes: Record the event that the blood sugar fluctuation is caused by the user's meal, and record a fifth time interval; wherein the fifth time interval is the time interval when the user eats, the start time of the fifth time interval is the third time, and the end time of the fifth time interval is the seventh time, and the seventh time is the time when the blood sugar fluctuation relative to the third time in the second time interval decreases to less than the first threshold.

14. The method according to claim 1, wherein The first data includes physiological data of the user and / or sensor data of the wearable device, and third data within the first time interval; wherein the blood glucose information is obtained from a second electronic device, and the third data is obtained from the second electronic device, and the second electronic device is worn by the user; Determining, based on the first data, that the blood sugar fluctuation is a blood sugar abnormality event includes: The blood sugar fluctuation is determined to be an abnormal blood sugar event based on the user's physiological data and / or sensor data of the wearable device, as well as the third data.

15. The method according to claim 14, characterized in that Before acquiring the physiological data of the user and / or the sensor data of the wearable device, the method further includes: If the blood glucose fluctuation at the second moment relative to the third moment within the first time interval is greater than or equal to a first threshold, the first electronic device determines whether the first electronic device has the ability to obtain fourth data from the wearable device; wherein the fourth data includes physiological data of the user and / or sensor data of the wearable device; The acquiring of the physiological data of the user and / or sensor data of the wearable device, and acquiring third data within the first time interval from the second electronic device includes: If the first electronic device has the ability to obtain the fourth data of the wearable device, the physiological data of the user and / or the sensor data of the wearable device are obtained, and the third data within the first time interval is obtained from the second electronic device.

16. The method according to claim 15, characterized in that The first electronic device determining whether the first electronic device has the ability to obtain the fourth data of the wearable device includes: The first electronic device determines whether the user is wearing a wearable device; If the user wears a wearable device, the first electronic device determines whether fourth data of the wearable device is obtained; If yes, the first electronic device determines that the first electronic device has the ability to obtain the fourth data of the wearable device.

17. The method according to claim 14, characterized in that After determining that the blood sugar fluctuation is a blood sugar abnormality event, the method further includes: determining the type of the abnormal blood sugar event according to the second moment; Obtaining a sixth time interval in which the abnormal blood sugar event occurs; wherein the start time of the sixth time interval is the third time, the end time of the sixth time interval is the eighth time, and the eighth time is the time when the blood sugar fluctuation relative to the third time decreases to less than the first threshold; After determining that the user is not in a sleeping state, the type of the abnormal blood sugar event and the sixth time interval are prompted to the user.

18. The method according to any one of claims 14 to 17, characterized in that: Before determining that the blood sugar fluctuation is a blood sugar abnormality event, the method further includes: determining whether the blood sugar fluctuation is caused by a first event based on the user's physiological data and / or sensor data of the wearable device, and the third data; Determining that the blood sugar fluctuation is a blood sugar abnormality event includes: If it is determined that the blood sugar fluctuation is not caused by the first event, the blood sugar fluctuation is determined to be an abnormal blood sugar event.

19. The method according to claim 18, characterized in that After determining whether the blood sugar fluctuation is caused by the first event, the method further includes: If the blood sugar fluctuation is caused by the first event, after determining that the user is not in a sleeping state, the user is prompted that the blood sugar fluctuation is caused by the first event.

20. The method according to claim 18, wherein After determining whether the blood sugar fluctuation is caused by the first event, the method further includes: If the blood sugar fluctuation is caused by the first event, it is recorded that the blood sugar fluctuation is caused by the first event, and the time interval in which the first event occurs is recorded.

21. The method according to claim 19 or 20, characterized in that The third data includes second current information and second temperature information, and the first event includes the user eating a meal; The determining, based on the physiological data of the user and / or the sensor data of the wearable device, and the third data, whether the blood sugar fluctuation is caused by the first event includes: When the second current information and the second temperature information conform to the second rule, if it is determined based on the user's physiological data and / or the sensor data of the wearable device that the user has eaten within the first time interval, it is determined that the blood sugar fluctuation is caused by the user's eating.

22. The method according to claim 19 or 20, characterized in that The third data includes second current information and second temperature information, and the first event includes the user pressing the second electronic device; The determining, based on the physiological data of the user and / or the sensor data of the wearable device, and the third data, whether the blood sugar fluctuation is caused by the first event includes: When the second current information and the second temperature information conform to the first rule, if it is determined based on the user's physiological data and / or the sensor data of the wearable device that the user has pressed the second electronic device within the first time interval, then it is determined that the blood sugar fluctuation is caused by the user pressing the second electronic device.

23. An electronic device, characterized in that: include: one or more processors; Memory; Multiple applications; and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions that, when executed by the electronic device, cause the electronic device to perform the method according to any one of claims 1 to 22.

24. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed on a computer, enables the computer to execute the method according to any one of claims 1 to 22.

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