Blood glucose monitoring method and electronic device

Abstract

The present application provides a blood glucose monitoring method. The method comprises: determining a first early warning duration according to first blood glucose data, wherein the first blood glucose data comprises blood glucose data within a first time period, and the first early warning duration is used for performing hypoglycemia early warning. The first early warning duration is related to blood glucose fluctuation indicated by the first blood glucose data. If the blood glucose indicated by the first blood glucose data fluctuates little and changes slowly, the first early warning duration can be longer. If the first blood glucose data input into a model indicates that the blood glucose of a user fluctuates greatly and changes rapidly in historical time, the first early warning duration can be shorter. By means of implementing the described method, the electronic device can adaptively adjust the first early warning duration according to the characteristics of the blood glucose variability of a user, thereby improving the accuracy of hypoglycemia early warning.

Description

Blood glucose monitoring method and electronic device Technical Field

[0001] The embodiments of the present invention relate to the field of terminal technology, and in particular to a blood glucose monitoring method and electronic device. Background Art

[0002] Blood glucose monitoring devices can analyze a user's blood glucose levels over time to predict their blood glucose levels over the next period of time. If the predicted blood glucose level falls below the hypoglycemia warning threshold within a certain period of time, the device can issue an alert to remind the user to replenish sugar and avoid hypoglycemia symptoms. Summary of the Invention

[0003] Embodiments of the present invention provide a blood sugar monitoring method and electronic device. Implementing this method enables the electronic device to issue a timely warning before a user's blood sugar drops to a dangerous level, effectively improving the accuracy of hypoglycemia warnings and preventing hypoglycemia from affecting the user's daily life and work.

[0004] In a first aspect, an embodiment of the present invention provides a blood glucose monitoring method, the method comprising: determining a first warning duration based on first blood glucose data, the first blood glucose data comprising blood glucose data within a first time period, and the first warning duration being used for hypoglycemia warning.

[0005] The first warning duration is related to the blood sugar fluctuation indicated by the first blood sugar data. If the blood sugar fluctuation indicated by the first blood sugar data is small and changes slowly, the first warning duration determined by the warning duration model can be longer. If the first blood sugar data input to the model indicates that the user's blood sugar fluctuations are large and change rapidly over time, the first warning duration determined by the warning duration model can be shorter.

[0006] Since the first warning duration is an important parameter in the hypoglycemia warning process and can significantly affect the accuracy of the first result, by implementing the above method, the electronic device can adaptively adjust the first warning duration based on the characteristics of the user's blood sugar fluctuations, thereby improving the accuracy of the hypoglycemia warning.

[0007] In conjunction with the previous embodiment, in some examples, the first time period may be a time period starting from a certain moment in the past to the current moment. In other examples, the first time period may also be a time period starting from a certain moment in the past to a certain moment in the past.

[0008] In conjunction with the first aspect, in some embodiments, the method further includes: obtaining a first result based on the first blood glucose data and the first warning duration, the first result being used to indicate whether a hypoglycemic event will occur in the future within the first warning duration. If the first result indicates that a hypoglycemic event will occur in the future within the first warning duration, a hypoglycemic warning is issued.

[0009] Therefore, electronic devices can issue hypoglycemia warnings when predicting future hypoglycemia events, reminding users to replenish sugar in a timely manner and avoid the occurrence of hypoglycemia symptoms.

[0010] In combination with the first aspect, in some embodiments, the first result indicates that a hypoglycemic event will occur within a first warning period in the future, specifically including: the first result indicates that the blood glucose value will be lower than a first warning threshold within the first warning period in the future.

[0011] In combination with the first aspect, in some embodiments, determining the first warning duration based on the first blood glucose data specifically includes: inputting the first blood glucose data into a warning duration model to obtain the first warning duration.

[0012] Among them, the warning duration model is a pre-trained machine learning model.

[0013] In conjunction with the first aspect, in some embodiments, the training process of the warning duration model includes determining an optimal warning duration corresponding to each blood glucose data item in a training dataset, where the training dataset includes multiple blood glucose data items. The warning duration model is trained by using the blood glucose data as input and outputting the longest hypoglycemia warning duration with an accuracy rate exceeding a threshold for performing hypoglycemia warning based on the blood glucose data.

[0014] It can be understood that a hypoglycemia warning duration with an accuracy higher than the threshold and the longest duration can both meet the accuracy requirements of the hypoglycemia warning and provide the user with sufficient reaction time to replenish sugar as much as possible. Therefore, the warning duration model determined based on the above strategy is a machine learning model that can determine the hypoglycemia warning duration based on the user's historical blood sugar data.

[0015] In conjunction with the first aspect, in some embodiments, the method further includes: acquiring physiological data; determining a time when hypoglycemia symptoms occur based on the physiological data; and determining a first warning threshold based on the blood glucose data corresponding to the time when hypoglycemia symptoms occur, and the first warning duration is used for providing a hypoglycemia warning.

[0016] The time when the hypoglycemia symptom occurs may include one or more times.

[0017] Since the hypoglycemia warning threshold is an important parameter in the hypoglycemia warning process and can significantly affect the accuracy of the first result, based on the above strategy, the hypoglycemia warning threshold can be adaptively adjusted based on the user's past blood sugar levels when hypoglycemia symptoms occurred, thereby improving the accuracy of hypoglycemia warnings.

[0018] In combination with the previous embodiment, in some examples, the physiological data includes one or more of the following: blood glucose value, heart rate, heart rate variability, body temperature, and exercise data.

[0019] In combination with the first aspect, in some embodiments, performing a hypoglycemia warning specifically includes one or more of the following: displaying a notification message, vibrating, and playing a sound.

[0020] In a second aspect, embodiments of the present invention provide a blood glucose monitoring method, comprising: determining a user activity status; determining a first warning duration and / or a first warning threshold based on the user activity status; the first warning duration and the first warning threshold being used to provide a hypoglycemia warning.

[0021] Since users in different activity states have different needs for hypoglycemia warnings, the above-mentioned blood glucose detection method can further improve the user experience during blood glucose monitoring.

[0022] In conjunction with the second aspect, in some embodiments, the user activity state includes a first state and a second state, the activity intensity in the first state is greater than the activity intensity in the second state, the first warning duration corresponding to the first state is less than the first warning duration corresponding to the second state, and the first warning threshold corresponding to the first state is greater than the first warning threshold corresponding to the second state.

[0023] Since the user's blood sugar fluctuates rapidly and changes quickly when the activity intensity is high, using a shorter hypoglycemia warning duration and a higher hypoglycemia warning threshold for users with high activity intensity can provide a more timely hypoglycemia warning when hypoglycemia is about to occur, preventing users from suffering serious consequences due to hypoglycemia during exercise. In addition, since the user's blood sugar fluctuates slowly and changes slowly when the activity intensity is low, and they may not feel mild hypoglycemia. Therefore, using a longer hypoglycemia warning duration and a lower hypoglycemia warning threshold for users with low activity intensity can minimize the disturbance to the user's normal life and rest during the hypoglycemia warning process.

[0024] In combination with the second aspect, in some embodiments, the first warning duration is determined based on the user activity status, specifically including: determining the first warning duration based on the first blood glucose data and the user activity status, the first blood glucose data including the blood glucose data within the first time period.

[0025] Therefore, the first warning duration can be determined based on the user's activity status and historical blood sugar conditions, further improving the accuracy of hypoglycemia warning.

[0026] In conjunction with the second aspect, in some embodiments, determining the first warning threshold based on the user activity state specifically includes: obtaining physiological data; determining the moment when hypoglycemia symptoms occur based on the physiological data; determining the second warning threshold based on the blood glucose data corresponding to the moment when the hypoglycemia symptoms occur; and determining the first warning threshold based on the second warning threshold and the user activity state.

[0027] Therefore, the first warning threshold can be determined based on the user's activity status and the user's historical blood sugar conditions, further improving the accuracy of hypoglycemia warning.

[0028] In conjunction with the second aspect, in some embodiments, the method further includes: obtaining a first result based on the first blood glucose data, the first warning duration, and / or the first warning threshold, where the first result is used to indicate whether a hypoglycemic event will occur in the future within the first warning duration. If the first result indicates that a hypoglycemic event will occur in the future within the first warning duration, a hypoglycemic warning is issued.

[0029] In combination with the second aspect, in some embodiments, the first result indicates that a hypoglycemic event will occur within a first warning period in the future, specifically including: the first result indicates that the blood glucose value will be lower than a first warning threshold within the first warning period in the future.

[0030] In a third aspect, an embodiment of the present invention provides a communication system, which includes: a first device and a second device, where the first device and the second device are configured to collaboratively execute the method described in the first or second aspect above.

[0031] In a fourth aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a sensor. The memory is used to store a computer program, and the processor is used to call the computer program so that the electronic device executes the method described in the first or second aspect above.

[0032] In a fifth aspect, an embodiment of the present invention provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the method described in the first or second aspect above.

[0033] In a sixth aspect, an embodiment of the present invention provides a computer-readable storage medium comprising instructions, which, when executed on an electronic device, enables the electronic device to execute the method described in the first or second aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] FIG1 is a schematic structural diagram of a communication system 10 provided in an embodiment of the present invention;

[0035] FIG2A is a schematic structural diagram of an electronic device 100 provided in an embodiment of the present invention;

[0036] FIG2B is a schematic structural diagram of a communication system 10 provided in an embodiment of the present invention;

[0037] FIG3 is a schematic structural diagram of an electronic device 200 provided in an embodiment of the present invention;

[0038] 4A to 4F are user interfaces involved in a blood glucose monitoring process according to an embodiment of the present invention;

[0039] 5A and 5B are user interfaces involved in the hypoglycemia warning process provided by an embodiment of the present invention;

[0040] FIG6 is a flow chart of a blood glucose monitoring method according to an embodiment of the present invention;

[0041] FIG7 is a flow chart of a training method for a warning duration model according to an embodiment of the present invention;

[0042] FIG8 is a flow chart of another blood glucose monitoring method provided by an embodiment of the present invention;

[0043] FIG9 is a flow chart of another blood glucose monitoring method provided by an embodiment of the present invention;

[0044] FIG10 is a flow chart of another blood glucose monitoring method provided by an embodiment of the present invention;

[0045] FIG11 is a flow chart of another blood glucose monitoring method provided by an embodiment of the present invention;

[0046] FIG12 is a schematic structural diagram of a hypoglycemia warning device 300 provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following is a clear and detailed description of the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings. In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in the text is only a description of the association relationship between related objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0048] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0049] The term "user interface (UI)" in the following embodiments of this application refers to a medium interface for interaction and information exchange between an application or operating system and a user, which realizes the conversion between the internal form of information and the form acceptable to the user. The user interface is a source code written in a specific computer language such as Java and extensible markup language (XML). The interface source code is parsed and rendered on an electronic device and finally presented as content that the user can recognize. The commonly used form of user interface is graphical user interface (GUI), which refers to a user interface related to computer operations that is displayed in a graphical manner. It can be a visual interface element such as text, icons, buttons, menus, tabs, text boxes, dialog boxes, status bars, navigation bars, widgets, etc. displayed on the display screen of an electronic device.

[0050] Currently, electronic devices use fixed hypoglycemia warning durations and thresholds during blood sugar monitoring. However, due to differences in human physiology and lifestyle, blood sugar fluctuations vary significantly among different populations. Therefore, if the same hypoglycemia warning duration and threshold are used for all users, the warning may be overly sensitive or too slow, affecting the user experience of the hypoglycemia warning function.

[0051] The present invention provides a blood sugar monitoring method and electronic device. By implementing this method, the electronic device can promptly issue an early warning before a user's blood sugar drops to a dangerous level, effectively improving the accuracy of hypoglycemia warnings and preventing hypoglycemia from affecting the user's daily life and work.

[0052] FIG1 is a schematic structural diagram of a communication system 10 provided in an embodiment of the present invention.

[0053] Referring to FIG1 , FIG1 shows a communication system 10 provided in an embodiment of the present application. As shown in FIG1 , the communication system 10 may include an electronic device 100 and an electronic device 200. In particular:

[0054] Electronic device 100 may be a continuous glucose monitoring (CGM) device. It may continuously acquire a user's blood glucose data based on electrochemical, optical, or fluorescent detection technologies. Electronic device 100 may be inserted into the human body in various ways, such as by attaching it to the surface of the skin or implanting it subcutaneously.

[0055] The electronic device 200 may be a mobile phone, a smart watch, a smart bracelet, smart glasses, a tablet computer or other electronic device ( FIG. 1 takes a mobile phone as an example).

[0056] In an embodiment of the present application, the electronic device 100 and the electronic device 200 can communicate with each other. The communication methods between the two may include wired communication, wireless communication, etc. Among them, the wireless communication can be a short-range communication method such as high-fidelity wireless communication (wireless fidelity, Wi-Fi), Bluetooth (bluetooth, BT) communication, NearLink, infrared communication, NFC communication, ZigBee communication, etc., or it can be a long-range communication method, and the long-range communication method includes but is not limited to long-range communication based on 2G, 3G, 4G, 5G and subsequent standard protocols of mobile networks. In addition, since the electronic device 100 and the electronic device 200 can both be attached to the surface of the same user's skin. Therefore, in some implementations, the two can use the skin as a transmission medium and communicate through the skin. In some implementations, a pairing relationship can also be established between the electronic device 100 and the electronic device 200. Taking the establishment of a Bluetooth pairing relationship between the electronic device 100 and the electronic device 200 as an example, the electronic device 100 and the electronic device 200 can both have a Bluetooth communication module. The electronic device 200 may search for electronic devices near the electronic device 200 through the Bluetooth communication module, and the electronic devices searched may include the electronic device 100. Thereafter, the electronic device 100 may be paired with the electronic device 200.

[0057] In some implementations, the electronic device 100 and the electronic device 200 may also establish a connection based on a server. For example, the electronic device 100 and the electronic device 200 may log in to the same server and establish a connection and communicate through the server.

[0058] FIG2A is a schematic structural diagram of an electronic device 100 provided in an embodiment of the present invention.

[0059] As shown in FIG2A , the structure of the electronic device 100 may include a measurement module, a data processing module, an algorithm module, and an application module.

[0060] 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 modules than shown, or may combine or separate certain modules, or may have different module arrangements. The illustrated modules may be implemented in hardware, software, or a combination of software and hardware.

[0061] The measurement module is used to obtain the user's blood sugar data, or data related to the user's blood sugar data, such as reaction current, skin temperature, etc.

[0062] The data processing module is used to perform preliminary processing on the data collected by the measurement module. The preliminary processing process may include signal quality judgment and filtering.

[0063] The algorithm module is used to determine whether a hypoglycemia warning is needed. The algorithm module may include a data storage module, an early warning parameter module and an early warning result module. Among them, the data storage module is used to store the user's blood sugar data. The user's blood sugar data may include the blood sugar data collected by the measurement module and then processed by the data processing module. The early warning parameter module is used to determine the hypoglycemia warning duration and / or the hypoglycemia warning threshold. The early warning result module is used to determine whether a hypoglycemia event will occur in the future within the hypoglycemia warning duration based on the blood sugar data of the user in historical time. The blood sugar data of the user in the above historical time may include the blood sugar data read from the data storage module. The early warning result module can execute the above-mentioned hypoglycemia warning process based on the hypoglycemia warning duration and / or the hypoglycemia warning threshold read from the early warning parameter module.

[0064] In some implementations, if the measurement module measures data related to the user's blood glucose data, the algorithm module may further include a blood glucose calculation module, which is used to obtain blood glucose data based on the aforementioned data related to the user's blood glucose data.

[0065] The application module is used to provide hypoglycemia warning. The hypoglycemia warning methods may include: displaying a notification message on the user interface, vibrating, playing a sound, etc.

[0066] In some implementations, the modules shown in FIG. 2A may be located in different devices.

[0067] FIG2B is a schematic structural diagram of a communication system 10 provided in an embodiment of the present invention.

[0068] As shown in Figure 2B, the communication system 10 may include an electronic device 100 and an electronic device 200. The electronic device 100 may include a measurement module, a data processing module, an algorithm module, and a communication module. The electronic device 200 may include an application module and a communication module.

[0069] For detailed descriptions of the measurement module, data processing module, algorithm module, and application module, as well as for detailed descriptions of the interactions between these modules, please refer to the relevant descriptions in the aforementioned embodiments and will not be repeated here. Since the above four modules are distributed among different devices, the interaction process between the modules belonging to different devices can be implemented through the communication modules in electronic device 100 and electronic device 200.

[0070] In the embodiments of the present application, there are other distribution methods for different modules between devices. Specifically, electronic device 100 may include a measurement module. Electronic device 100 or electronic device 200 may include a signal processing and abnormality judgment module, an algorithm module, and an application module. In the case where the modules are distributed between different devices, the communication module in electronic device 100 and the communication module in electronic device 200 can be used to implement the interaction process between the modules belonging to different devices.

[0071] FIG3 shows a schematic structural diagram of the electronic device 200 .

[0072] The electronic device 200 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 200. In other embodiments of the present application, the electronic device 200 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 memory, 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 may be the nerve center and command center of the electronic device 200. The controller may generate an operation control signal according to the instruction operation code and the timing signal to complete the control of fetching and executing instructions.

[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 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 200. While charging the battery 142, the charging management module 140 can also provide power to the electronic device via the power management module 141.

[0079] 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 external memory, 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.

[0080] The wireless communication function of the electronic device 200 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.

[0081] Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 200 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.

[0082] The mobile communication module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G applied to the electronic device 200. 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.

[0083] 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.

[0084] The wireless communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), BT, global navigation satellite system (GNSS), frequency modulation (FM), NFC, infrared technology (IR), etc. applied to the electronic device 200. The wireless communication module 160 can be one or more devices integrating 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.

[0085] In some embodiments, the antenna 1 of the electronic device 200 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 200 can communicate with the network and other devices through wireless communication technology. The wireless communication technology 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-SCDMA), 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).

[0086] Electronic device 200 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.

[0087] Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD). The display panel can also be made of an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a miniLED, a microLED, a micro-OLED, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the electronic device can include one or N display screens 194, where N is a positive integer greater than one.

[0088] The electronic device 200 can implement the shooting function through the ISP, camera 193, video codec, GPU, display screen 194 and application processor.

[0089] 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.

[0090] 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 200 may include 1 or N cameras 193, where N is a positive integer greater than 1.

[0091] 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 200 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy.

[0092] Video codecs are used to compress or decompress digital video. Electronic device 200 may support one or more video codecs. This allows electronic device 200 to play or record videos in various encoding formats, such as Moving Picture Experts Group (MPEG) 1, MPEG2, MPEG3, and MPEG4.

[0093] 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 200, such as image recognition, face recognition, speech recognition, and text comprehension.

[0094] 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 200. 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.

[0095] The internal memory 121 can be used to store computer executable program codes, which include instructions. The processor 110 executes various functional applications and data processing of the electronic device 200 by running the instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. Among them, the program storage area can 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 can store data created during the use of the electronic device 200 (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.

[0096] The electronic device 200 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.

[0097] 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 200 may receive key inputs and generate key signal inputs related to user settings and function control of the electronic device 200.

[0098] 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.

[0099] 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.

[0100] The SIM card interface 195 is used to connect a SIM card. The SIM card can be connected to or removed from the electronic device 200 by inserting it into or removing it from the SIM card interface 195. The electronic device 200 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, and the like. 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 200 interacts with the network through the SIM card to implement functions such as calls and data communications. In some embodiments, the electronic device 200 uses an eSIM, i.e., an embedded SIM card. The eSIM card can be embedded in the electronic device 200 and cannot be separated from the electronic device 200.

[0101] The following is an exemplary description of the user interface involved in the blood glucose monitoring process provided in the embodiments of the present application.

[0102] Figure 4A illustrates an exemplary user interface 210, which can be used for setting reminders for a blood glucose monitoring application. As shown in Figure 4A , user interface 210 includes an alert module 211. This module allows the user to view and modify parameters related to the hypoglycemia alert function. For example, the module may include a switch 212, an alert threshold prompt 213, an alert duration field 214, and an effective time field 215.

[0103] in,

[0104] Switch 212 is used to trigger the electronic device 200 to turn on or off the hypoglycemia warning function. When the hypoglycemia warning function is turned on, the electronic device 200 can remind the user to pay attention to the blood sugar status before the user's blood sugar drops to a dangerous level, replenish sugar in time, and prevent the occurrence of hypoglycemia.

[0105] The warning threshold prompt information 213 and the warning duration column 214 are used for the user to view the hypoglycemia warning threshold and hypoglycemia warning duration used by the electronic device 200 when performing blood glucose monitoring. For example, as shown in FIG4A , the warning threshold prompt information 213 may be “give a reminder when the future blood glucose is predicted to be lower than 3.9 mmol / L”. If the electronic device 100 or the electronic device 200 predicts that a hypoglycemia event will occur after the hypoglycemia warning duration has passed in the future based on the user's blood glucose data over a historical period, then the electronic device 100 may instruct the electronic device 200 to issue a hypoglycemia warning, or the electronic device 200 may spontaneously issue a hypoglycemia warning.

[0106] The effective time bar 215 is used for the user to view and modify the time period for the electronic device 200 to turn on the hypoglycemia warning function. For example, as shown in Figure 4A, the time period for the electronic device 200 to turn on the hypoglycemia warning function can be "08:00-22:00". In addition, in some examples, the effective time bar 215 may also include a switch control. The switch control is used to control the switch of the warning do not disturb function. The warning do not disturb function is a function that detects that the user has mild hypoglycemia when the user is in a sleeping state, and then prompts the user of a hypoglycemia event during sleep in response to detecting that the user has woken up.

[0107] As shown in FIG4A , the electronic device 200 is in a state where the hypoglycemia warning function is enabled, and the hypoglycemia warning threshold used is 3.9 mmol / L, and the hypoglycemia warning duration is 30 minutes.

[0108] In addition, in some implementations, the user interface 210 further includes an alarm module 216. The alarm module 216 is used to allow the user to view and modify parameters related to the abnormal blood sugar alarm function. The abnormal blood sugar alarm function includes a hypoglycemia alarm function and a hyperglycemia alarm function. Among them, the hypoglycemia alarm function is used to immediately alarm when the user's blood sugar drops to a hypoglycemia alarm threshold, and the hyperglycemia alarm function is used to immediately alarm when the user's blood sugar rises to a hyperglycemia alarm threshold, so as to prompt the user to pay attention to the blood sugar situation and avoid further deterioration of hypoglycemia or hyperglycemia events.

[0109] Illustratively, the alarm module 216 may include a hypoglycemia alarm module 216A and a hyperglycemia alarm module 216B. Both modules may include a switch, alarm threshold prompt information, and a reminder frequency column. The switch is used to trigger the electronic device 200 to turn on or off the hypoglycemia / hyperglycemia alarm function. The alarm threshold prompt information allows the user to view the hypoglycemia / hyperglycemia alarm thresholds used by the electronic device 200 when performing blood glucose monitoring. The reminder frequency column allows the user to view and modify the frequency at which the electronic device 200 issues alarms. If the electronic device 100 or the electronic device 200 determines that the user's current blood glucose level is below the hypoglycemia alarm threshold, the electronic device 100 may instruct the electronic device 200 to issue a hypoglycemia alarm at a set frequency, or the electronic device 200 may automatically issue a hypoglycemia alarm at a set frequency. Similarly, if the electronic device 100 or the electronic device 200 determines that the user's current blood glucose level is above the hyperglycemia alarm threshold, the electronic device 100 may instruct the electronic device 200 to issue a hyperglycemia alarm at a set frequency, or the electronic device 200 may automatically issue a hyperglycemia alarm at a set frequency.

[0110] As shown in FIG4A , the electronic device 200 is in a state where the hypoglycemia alarm function and the hyperglycemia alarm function are turned on, and the hypoglycemia alarm threshold used is 3.9 mmol / L, and the hyperglycemia alarm threshold used is 10 mmol / L. The alarm frequency is 3 times at a time interval of 10 minutes.

[0111] The electronic device 200 can provide a hypoglycemia warning in the form of a notification message. FIG4B exemplarily shows a user interface 220 of the electronic device 200 for providing a hypoglycemia warning. As shown in FIG4B , the user interface 220 is a drop-down notification page of the electronic device 200. It includes one or more notification messages, including a notification message 221 for providing a hypoglycemia warning. The notification message 221 may include an icon of a blood glucose monitoring application, a warning message 222, a later reminder control 223A, and a notification control 223B. Among them,

[0112] The warning information 222 is used to remind the user that a hypoglycemic event will occur within the hypoglycemic warning period in the future. The warning information 222 can be displayed in the form of text, pictures, animations, etc. The specific form of the warning information 222 is not limited in this embodiment of the application.

[0113] As shown in FIG4B , warning message 222 may be used to indicate the duration of the hypoglycemia warning. For example, warning message 222 may include the text: "You are predicted to experience hypoglycemia symptoms within 30 minutes. Please pay attention." Additionally, warning message 222 may be used to indicate the real-time blood glucose value, such as the text in FIG4B : "5.6 mmol / L."

[0114] In other implementations, the electronic device 200 can also provide hypoglycemia warnings in the form of voice broadcasts, vibrations, etc.

[0115] The later reminder control 223A and the aware control 223B are both used to trigger the electronic device 200 to no longer display the notification message 221. The difference is that the later reminder control 223A is also used to trigger the electronic device 200 to issue a hypoglycemia warning again after a preset time. In some implementations, when a hypoglycemia warning is issued again, the warning information displayed by the electronic device 200 may include more content than the aforementioned warning information 222, such as the number of reminders, prompt information for prompting the dangers of hypoglycemia events, etc. In addition, in some implementations, when a hypoglycemia warning is issued again, the electronic device 200 may also adopt a stronger reminder method, such as using multiple methods for warning at the same time, including vibration, sounding an alarm, displaying warning information, etc.

[0116] In the embodiment of the present application, the first warning duration can be determined based on the user's historical blood sugar level, and the first warning duration can be used as the hypoglycemia warning duration for the hypoglycemia warning process. The above process will be described in detail in the subsequent embodiments of this application, so a detailed description is not given here.

[0117] After determining the first warning duration, the electronic device 200 may suggest setting the hypoglycemia warning duration as the first warning duration in the form of a notification message.

[0118] FIG4C exemplarily shows a user interface 230. As shown in FIG4C , the user interface 230 is a drop-down notification page of the electronic device 200. It may include one or more notification messages, including a notification message 231 for suggesting that the user adjust the hypoglycemia warning duration. The notification message 231 may include an icon of a blood glucose monitoring application, change suggestion information 232, a confirmation control 233A, and a notification control 233B.

[0119] The change suggestion information 232 can be displayed in the form of text, images, animations, etc., and the specific form of the change suggestion information 232 is not limited in this embodiment of the present application. As shown in Figure 4C, the warning message can be implemented as text: "Based on the blood sugar data of the past 24 hours, your blood sugar fluctuations have increased. It is recommended to change the hypoglycemia warning prediction time to 15 minutes to ensure the accuracy of the hypoglycemia warning."

[0120] The confirmation control 233A is used to trigger the electronic device 200 to set the hypoglycemia warning duration to the first warning duration.

[0121] The awareness control 233B is used to trigger the electronic device 200 to no longer display the notification message 233B. It is understandable that in response to the user's input operation (such as a touch operation) on the awareness control 233B, the electronic device 200 does not change the lower blood sugar warning duration.

[0122] In response to the user's input operation (eg, a touch operation) on the confirmation control 233A, as shown in FIG4D , the electronic device 200 may update the hypoglycemia warning duration to 15 minutes.

[0123] In the embodiment of the present application, a first warning threshold can be determined based on the user's historical blood sugar level, and the first warning threshold can be used as a hypoglycemia warning threshold for the hypoglycemia warning process. This process will be described in detail in the subsequent embodiments of the present application and will not be described in detail here.

[0124] After determining the first warning threshold, the electronic device 200 may suggest setting the hypoglycemia warning threshold as the first warning threshold in the form of a notification message.

[0125] FIG4E exemplarily shows a user interface 250. As shown in FIG4E , the user interface 250 is a drop-down notification page of the electronic device 200. It may include one or more notification messages, including a notification message 251 for suggesting that the user adjust the hypoglycemia warning threshold. The notification message 251 may include an icon of a blood glucose monitoring application, change suggestion information 252, a confirmation control 253A, and a notification control 253B.

[0126] The change suggestion information 252 can be displayed in the form of text, images, animations, etc. The specific form of the change suggestion information 232 is not limited in this embodiment of the application. As shown in Figure 4E, the warning message can be implemented as text: "Based on the physiological data of the past 24 hours, it is recommended to change the hypoglycemia warning threshold to 4.4mmol / L to ensure that you can promptly understand your hypoglycemia status."

[0127] The confirmation control 253A is used to trigger the electronic device 200 to set the hypoglycemia warning threshold to the first warning threshold.

[0128] The awareness control 253B is used to trigger the electronic device 200 to no longer display the notification message 253B.

[0129] In response to the user's input operation (eg, a touch operation) on the confirmation control 253A, as shown in FIG4F , the electronic device 200 may update the hypoglycemia warning threshold to 4.4 mmol / L.

[0130] In the embodiment of the present application, different hypoglycemia warning strategies can be adopted according to the activity state of the user. The activity state can include, for example, exercise state, calm state, and sleep state.

[0131] When it is determined that the user is currently in a state of exercise, the electronic device 200 can perform a hypoglycemia warning by displaying a user interface 310 as shown in FIG5A. The user interface 310 is a drop-down notification page of the electronic device 200. It may include one or more notification messages, including a notification message 311 for suggesting that the user adjust the hypoglycemia warning duration. The notification message 311 may include an icon of a blood glucose monitoring application, warning information 312, a later reminder control 313A, and a notification control 313B. Among them,

[0132] For a description of warning message 312, please refer to the description of warning message 222 of user interface 220 in FIG. 5B in the aforementioned embodiment. Warning message 312 may also indicate the user's current activity status, such as the text "Based on your current activity status, you are predicted to experience hypoglycemia within 30 minutes. Please pay attention." as shown in FIG. 5A .

[0133] For the description of the later reminder control 313A and the aware control 313B, reference may be made to the related description of the later reminder control 223A and the aware control 223B of the user interface 220 in FIG. 5B in the aforementioned embodiment.

[0134] In an embodiment of the present application, if it is detected that the user has mild hypoglycemia while the user is in a sleeping state, then the electronic device 200 can prompt the user of the hypoglycemia event during sleep after detecting that the user has woken up, or after receiving a message from other wearable devices instructing the user to wake up. The electronic device 200 can display a user interface 320 as shown in Figure 5B. As shown in Figure 5B, the user interface 320 is a drop-down notification page of the electronic device 200. It may include one or more notification messages, including a notification message 321 for notifying the occurrence of a hypoglycemia event. The notification message 321 may include an icon of a blood glucose monitoring application and notification information 322. The notification information 322 can be implemented in the form of text, pictures, animations, etc. The embodiment of the present application does not limit the specific form of the notification information 322. As shown in Figure 5B, the notification information 322 can be implemented as text: "You had mild hypoglycemia symptoms last night. Please pay attention to your blood glucose status in time to avoid severe hypoglycemia events."

[0135] In the process of hypoglycemia warning, factors that may affect the results of hypoglycemia warning include hypoglycemia warning duration and hypoglycemia warning threshold.

[0136] The hypoglycemia warning duration is the length of time the electronic device 100 uses to predict the user's future blood sugar levels. A longer hypoglycemia warning duration provides the user with more time to react before hypoglycemia symptoms occur, allowing them to replenish sugar, stabilize their blood sugar, and avoid hypoglycemia. However, as time passes, the uncertainty of the blood sugar prediction increases. Therefore, a longer hypoglycemia warning duration reduces the accuracy of the hypoglycemia warning result.

[0137] Because blood sugar fluctuations vary among different people, users with larger blood sugar fluctuations have faster changes in their blood sugar, making it more difficult to predict their blood sugar levels in the distant future. Users with smaller blood sugar fluctuations have slower changes in their blood sugar, making it easier to predict their blood sugar levels in the distant future. Therefore, it is necessary to select different hypoglycemia warning durations based on the user's blood sugar fluctuation characteristics.

[0138] The hypoglycemia warning threshold is the blood glucose threshold that triggers the electronic device 100 to issue a hypoglycemia warning. Due to different sensitivities to blood glucose fluctuations among different groups of people, some people will experience hypoglycemia symptoms when their blood glucose values ​​drop slightly below normal levels, while others will experience hypoglycemia symptoms only when their blood glucose values ​​drop significantly. In addition, the blood glucose values ​​of patients with abnormal blood glucose levels (hyperglycemia, hypoglycemia) when they experience hypoglycemia symptoms may differ significantly from those of healthy people when they experience hypoglycemia symptoms. Therefore, it is also necessary to select different hypoglycemia warning thresholds for users based on their blood glucose fluctuation characteristics.

[0139] The electronic device can provide a hypoglycemia warning based on a hypoglycemia warning model. The hypoglycemia warning model is a machine learning model that can determine whether the user's blood sugar value will be lower than the hypoglycemia warning threshold in the future within the hypoglycemia warning duration based on the user's historical blood sugar conditions. The input of the hypoglycemia warning model can be data indicating the user's historical blood sugar conditions, and the output can be a warning result. The value of the warning result may include a first value or a second value. Among them, the first value indicates that the user's blood sugar value will be lower than the hypoglycemia warning threshold within the hypoglycemia warning duration, that is, the first value indicates that the user will experience hypoglycemia within the hypoglycemia warning duration in the future. The second value indicates that the user's blood sugar value will not be lower than the hypoglycemia warning threshold within the hypoglycemia warning duration, that is, the second value indicates that the user will not experience hypoglycemia within the hypoglycemia warning duration in the future.

[0140] Different hypoglycemia warning durations can correspond to different hypoglycemia warning models. For the same hypoglycemia warning model, under the same input, different outputs can be obtained by adjusting the hypoglycemia warning threshold within the model. That is, by adjusting the hypoglycemia warning threshold, the warning result output by the hypoglycemia warning model can be adjusted.

[0141] FIG6 is a flow chart of a blood glucose monitoring method provided in an embodiment of the present invention. The method can be applied to electronic device 100 or electronic device 200. The embodiment of the present application does not specifically limit the execution subject of each step in the method.

[0142] As shown in FIG6 , the method includes:

[0143] Step S601: Determine a first warning duration based on first blood glucose data.

[0144] The electronic device 100 or the electronic device 200 can obtain the first blood glucose data. The first blood glucose data includes blood glucose data within a first time period. In some implementations, the first time period can be a time period starting from a certain moment in the past to the current moment. In other implementations, the first time period can also be a time period starting from a certain moment in the past to a certain moment in the past. This application does not make specific restrictions on this. In some implementations, the duration of the first time period can be preset, such as 24 hours, 48 ​​hours, etc. In other implementations, the first blood glucose data can include all blood glucose data stored or obtained. Among them, the blood glucose data can include blood glucose values.

[0145] In some implementations, the first warning duration can be obtained by inputting the first blood glucose data into a warning duration model. The warning duration model is a machine learning model that can determine the hypoglycemia warning duration based on the user's historical blood glucose data. The trainer can be the manufacturer of the electronic device 100 or the electronic device 200, or an application developer that provides a blood glucose monitoring application. The embodiments of the present application do not specifically limit the trainer of the model.

[0146] FIG7 is a flow chart of a method for training a warning duration model provided by an embodiment of the present invention. As shown in FIG7 , the method includes:

[0147] 1. Determine the first warning duration corresponding to each blood glucose data in the training data set.

[0148] The training data set is a data set used to train the model. The training data set includes multiple blood glucose data. The multiple blood glucose data are collected in advance and may include blood glucose values.

[0149] The following is a possible method for determining the first warning duration corresponding to each blood glucose data point in the training dataset:

[0150] (1) First, for any piece of blood sugar data, the blood sugar data in the second time period of the blood sugar data can be input into the hypoglycemia early warning model to obtain an early warning result. The early warning result is used to indicate whether the blood sugar value in the third time period will be lower than the hypoglycemia early warning threshold. The starting time of the third time period is the end time of the second time period, and the duration of the third time period is equal to the hypoglycemia early warning duration corresponding to the hypoglycemia early warning model. It can be understood that the above early warning result is the result obtained by predicting the future blood sugar situation after the second time period.

[0151] (2) By inputting the blood glucose data in the second time period into different hypoglycemia warning models corresponding to m hypoglycemia warning durations, m warning results can be obtained. The hypoglycemia warning thresholds in the above hypoglycemia warning models are the same.

[0152] (3) For any warning result, the accuracy of the warning result can be determined based on the warning result and the blood glucose data in the third time period in the blood glucose data.

[0153] If the warning result and the blood glucose data in the third time period in the blood glucose data both indicate that the blood glucose value in the third time period will be lower than the hypoglycemia warning threshold, then the warning result can be determined to be accurate. If the warning result and the blood glucose data in the third time period in the blood glucose data both indicate that the blood glucose value in the third time period will not be lower than the hypoglycemia warning threshold, then the warning result can also be determined to be accurate. Otherwise, if other circumstances occur, the warning result can be determined to be inaccurate.

[0154] (4) The hypoglycemia warning duration with the longest duration and the corresponding warning result is determined as the first warning duration corresponding to the blood glucose data.

[0155] In addition, in some implementations, for any piece of blood glucose data, n segments of data can be selected from the piece of blood glucose data based on the sliding window principle. Each segment of data is used to indicate the blood glucose status in a different second time period. For any segment of data, m early warning results can be obtained by performing the aforementioned processes (1) to (3) respectively, and the accuracy of each early warning result can be determined. Thus, a total of m*n early warning results and the accuracy of each early warning result can be determined.

[0156] Then, based on the accuracy of the m*n warning results, the warning accuracy rate for each hypoglycemia warning duration can be determined. Specifically, for any hypoglycemia warning duration, the ratio of the number of accurate warning results corresponding to it to the number of all corresponding warning results can be calculated. This ratio is then determined as the warning accuracy rate for that hypoglycemia warning duration.

[0157] Finally, the hypoglycemia warning duration with a warning accuracy higher than a preset value, such as 90%, and the longest duration among all hypoglycemia warning durations can be determined as the first warning duration.

[0158] 2. Based on each piece of blood sugar data and the corresponding first warning duration, a warning duration model is trained.

[0159] By taking each blood glucose data item in the training data set as input and the first warning duration corresponding to the blood glucose data item as output for model training, a warning duration model can be obtained. By inputting historical blood glucose data into the warning duration model, the first warning duration can be obtained.

[0160] In some implementations, before model training, the first warning duration corresponding to each blood glucose data item can be rounded down to obtain an approximate value of the first warning duration. Subsequently, model training can be performed using each blood glucose data item in the training dataset as input and the approximate value of the first warning duration corresponding to the blood glucose data item as output to obtain a warning duration model. Rounding down is the process of determining the numerical interval within which the numerical value falls based on the numerical value and a preset numerical interval, and determining the minimum value of the numerical interval as the approximate value of the numerical value. Exemplarily, the preset numerical intervals may include: greater than or equal to 5 minutes and less than 15 minutes, greater than or equal to 15 minutes and less than 30 minutes, greater than or equal to 30 minutes and less than 45 minutes, and greater than or equal to 45 minutes and less than 60 minutes. Alternatively, the preset numerical intervals may also include: greater than or equal to 5 minutes and less than 10 minutes, greater than or equal to 10 minutes and less than 20 minutes, ..., greater than or equal to 50 minutes and less than 60 minutes. This embodiment of the present application is not limited to this. For example, if the first warning duration corresponding to a piece of blood glucose data is 18 minutes, then when rounding down using the first of the two preset numerical intervals mentioned above, since 18 minutes falls into the numerical interval of "greater than or equal to 15 minutes and less than 30 minutes", the minimum value of the numerical interval, 15 minutes, can be determined as the approximate value of the numerical value.

[0161] The first warning duration determined according to the first blood glucose data can be used as a hypoglycemia warning duration in the hypoglycemia warning process. The first warning duration is related to the blood glucose fluctuation indicated by the first blood glucose data. The blood glucose fluctuation indicated by the first blood glucose data can be characterized by the blood glucose coefficient of variation (CV), interquartile range (IQR), inter-decile range (IDR), postprandial glucose excursion (PPGE), maximum amplitutude of glycemic excursions (LAGE), standard deviation of blood glucose (SDBG), etc. For example, the larger the CV, the greater the blood glucose fluctuation. The larger the IQR or IDR, the greater the blood glucose fluctuation. The larger the PPGE or LAGE, the greater the blood glucose fluctuation.

[0162] If the first blood glucose data indicates that the blood glucose fluctuation is small and changes slowly, the first warning duration determined by the warning duration model can be longer. If the first blood glucose data input to the model indicates that the user's blood glucose fluctuation is large and changes rapidly in the past, the first warning duration determined by the warning duration model can be shorter.

[0163] Based on the above strategy, different first warning durations can be determined in a refined and personalized manner for different users. This allows users with small blood sugar fluctuations and slow changes to have more time to react and replenish sugar, preventing hypoglycemia, while ensuring warning accuracy. This also provides users with large blood sugar fluctuations and rapid changes with more accurate and effective hypoglycemia warnings, improving the user experience during blood sugar monitoring.

[0164] Optionally, after executing step S601, step Opt1 may be executed to determine whether the first warning duration is consistent with the currently used hypoglycemia warning duration. If they are consistent, step S603 may be executed. If they are inconsistent, step S602 may be executed.

[0165] In some implementations, after determining that the first warning duration is inconsistent with the currently used hypoglycemia warning duration, step Opt2 may be performed to determine whether the error between the first warning duration and the currently used hypoglycemia warning duration is greater than a preset value. The preset value may be, for example, 5%. If the error is greater than the preset value, step S602 may be performed. If the error is less than or equal to the preset value, step S603 may be performed.

[0166] Therefore, a certain threshold can be set for updating the hypoglycemia warning duration to prevent constant fine-tuning of the hypoglycemia warning duration, which leads to a waste of device resources and confusion for users.

[0167] Step S602: Set the hypoglycemia warning duration to the first warning duration.

[0168] In some implementations, the user may be asked whether they agree to the change before the setting is made. This inquiry may be performed, for example, by displaying a notification message 231 in the user interface 230 shown in FIG4C . If the user agrees to the change, i.e., by touching the confirmation control 233A in the notification message 231, the hypoglycemia warning duration may be set to the first warning duration.

[0169] Step S603: Obtain a first result based on the first blood sugar data and the hypoglycemia warning duration.

[0170] In some implementations, the first result can be obtained by inputting the first blood glucose data into a hypoglycemia warning model corresponding to the hypoglycemia warning duration. The hypoglycemia warning model is a machine learning model that can determine whether the user's blood glucose value will fall below the hypoglycemia warning threshold within the hypoglycemia warning duration based on the user's historical blood glucose levels. In addition, for a description of the hypoglycemia warning model, reference can be made to the relevant description in the aforementioned step S601 and will not be repeated here.

[0171] Step S604: If the first result indicates that a hypoglycemia event will occur within the hypoglycemia warning period in the future, a hypoglycemia warning is issued.

[0172] The method for providing a hypoglycemia warning may be, for example, displaying a notification message 221 in the user interface 220 shown in FIG5B . In addition, other methods may be used to provide a hypoglycemia warning, such as vibration, playing a sound, etc. The embodiment of the present application does not specifically limit the method for providing a hypoglycemia warning.

[0173] In some implementations, the method can be collaboratively performed by electronic device 100 and electronic device 200, with each device separately performing some of the steps in the method. For example, electronic device 100 performs steps S601 to S603, and if the first result indicates that a hypoglycemic event will occur within the hypoglycemic warning period in the future, electronic device 100 can send an instruction to electronic device 200, and electronic device 200 can perform step S604 based on the instruction.

[0174] In some implementations, the method shown in FIG. 6 may be performed in a certain period, such as 24 hours.

[0175] As previously mentioned, the first warning duration, as an important parameter in the hypoglycemia warning process, can significantly impact the accuracy of the first result. Therefore, implementing the blood glucose monitoring method shown in FIG6 can adaptively adjust the hypoglycemia warning duration based on the characteristics of the user's blood glucose fluctuations, thereby improving the accuracy of the hypoglycemia warning.

[0176] FIG8 is a flow chart of another blood glucose monitoring method provided by an embodiment of the present invention. This method can be applied to electronic device 100 or electronic device 200. This embodiment of the application does not specifically limit the execution subject of each step in this method.

[0177] The blood glucose detection method shown in FIG8 is a blood glucose detection method that determines a hypoglycemia warning threshold according to the user's blood glucose fluctuations and applies the hypoglycemia warning threshold to the hypoglycemia warning process. As shown in FIG8, the method includes:

[0178] S801. Determine the historical moment when the user experiences hypoglycemia symptoms.

[0179] In some implementations, historical moments when a user experienced hypoglycemia symptoms can be determined based on physiological data. Physiological data is data reflecting the user's physical condition and activity status. This data can be collected by electronic device 100 or electronic device 200, or data collected by other devices. Physiological data can include blood glucose levels, heart rate, heart rate variability, body temperature, exercise data, etc. The embodiments of this application do not limit the specific data types included in physiological data.

[0180] Because the human body will experience corresponding symptoms in the state of hypoglycemia, such as palpitations, cold limbs, and even coma, the user's historical moments of hypoglycemia symptoms can be determined based on physiological data.

[0181] In other implementations, the electronic device 100 and / or the electronic device 200 may support the user to record when he / she notices that he / she has hypoglycemia symptoms. In the process of performing this step, the hypoglycemia event recording time may also be determined as the historical moment when the user has hypoglycemia symptoms.

[0182] S802: Determine a first warning threshold value based on the blood sugar values ​​corresponding to the historical moments when the user experienced hypoglycemia symptoms.

[0183] For example, the average of the blood glucose levels of all users at the time of hypoglycemia symptoms can be calculated and used as the first warning threshold. In addition, the first warning threshold can also be determined by other methods, and the embodiment of the present application does not specifically limit the determination method.

[0184] In the process of hypoglycemia warning, the hypoglycemia warning threshold is also an important parameter related to the accuracy of the first result. Due to differences in lifestyle, health status, and sensitivity to blood sugar changes among different groups of people, these differences may lead to different users' sensitivity to hypoglycemia risks and actual needs for warnings. Therefore, based on the above strategy, different hypoglycemia warning thresholds can be determined for different users in a refined and personalized manner, so that users with different blood sugar health conditions and different sensitivity to blood sugar changes can be given more accurate and effective hypoglycemia warnings, thereby improving the user experience during blood sugar monitoring.

[0185] Optionally, after executing step S802, step Opt3 may be executed to determine whether the first warning threshold is consistent with the currently used hypoglycemia warning threshold. If they are consistent, step S804 may be executed. If they are not consistent, step S803 may be executed.

[0186] In some implementations, after determining that the first warning threshold is inconsistent with the currently used hypoglycemia warning threshold, step Opt4 may be performed to determine whether the error between the first warning threshold and the currently used hypoglycemia warning threshold is greater than a preset value. The preset value may be, for example, 5%. If the error is greater than the preset value, step S803 may be performed. If the error is less than the preset value, step S804 may be performed.

[0187] Therefore, a certain threshold can be set for updating the hypoglycemia warning threshold to prevent constant fine-tuning of the hypoglycemia warning threshold, which leads to waste of device resources and confusion for users.

[0188] Step S803: Set the hypoglycemia warning threshold to the first warning threshold.

[0189] In some implementations, before the setting is made, the user may be asked whether they agree to the modification. This inquiry may be performed, for example, by displaying a notification message 251 in the user interface 250 shown in FIG4E . If the user agrees to the modification, the hypoglycemia warning threshold may be set to the first warning threshold.

[0190] The hypoglycemia warning threshold is a key parameter in the hypoglycemia warning process, largely determining the accuracy of the initial result. By adjusting the hypoglycemia warning threshold based on the user's historical blood sugar levels, the accuracy of the hypoglycemia warning can be improved.

[0191] Step S804: Obtain a first result based on the first blood glucose data and the hypoglycemia warning threshold.

[0192] In some implementations, the first result can be obtained by inputting the first blood glucose data into a hypoglycemia early warning model. The hypoglycemia early warning model is a machine learning model that can determine whether the user's blood glucose value will fall below a hypoglycemia early warning threshold within the hypoglycemia early warning period based on the user's historical blood glucose levels. For a description of the hypoglycemia early warning model, please refer to the relevant description in the aforementioned step S601 and will not be repeated here.

[0193] Step S805: If the first result indicates that a hypoglycemia event will occur within the hypoglycemia warning time period in the future, a hypoglycemia warning is issued.

[0194] For the description of executing step S805 , reference may be made to the description of executing step S604 in the aforementioned embodiment, which will not be repeated here.

[0195] In some implementations, the method shown in FIG8 may be performed periodically, such as every 24 hours. Furthermore, in some implementations, during step S804, a portion of the first blood glucose data may be input into a hypoglycemia early warning model. For example, the user's blood glucose values ​​over the past 24 hours may be input into the hypoglycemia early warning model.

[0196] As previously mentioned, the hypoglycemia warning threshold, as an important parameter in the hypoglycemia warning process, can significantly impact the accuracy of the first result. Implementing the blood glucose monitoring method shown in FIG8 can adaptively adjust the hypoglycemia warning threshold based on the user's past hypoglycemia blood glucose levels, thereby improving the accuracy of hypoglycemia warnings.

[0197] In some implementations, after executing step S802, the hypoglycemia alarm threshold may also be set as a first warning threshold. For example, the initial value of the hypoglycemia alarm threshold may be 3.9 mmol / L. If the first warning threshold determined by executing step S802 is 4.4 mmol / L, the hypoglycemia alarm threshold may be updated from 3.9 mmol / L to 4.4 mmol / L through setting. The hypoglycemia alarm threshold is used for hypoglycemia alarm. The hypoglycemia alarm is a function that sounds an alarm when it is determined that hypoglycemia symptoms are currently occurring, so as to remind the user to pay attention to the blood sugar situation.

[0198] After the hypoglycemia alarm threshold is set to the first warning threshold, a second result can be obtained based on the second blood glucose data and the hypoglycemia alarm threshold. The second blood glucose data includes blood glucose data within a fourth time period. In some implementations, the fourth time period can be a time period starting from a certain moment in the past to the current moment. In other implementations, the fourth time period can also be a time period starting from a certain moment in the past to a certain moment in the past. This application does not make specific restrictions on this. The duration of the fourth time period is shorter than the duration of the first time period. In some implementations, the duration of the fourth time period can be a preset duration, such as 10 minutes, 5 minutes, etc. In other implementations, the second blood glucose data can include the most recent partial blood glucose data, such as the most recent blood glucose data, etc. In addition, for the description of blood glucose data, reference can be made to the relevant description among the aforementioned embodiments, which will not be repeated here.

[0199] The second result obtained based on the second blood sugar data and the hypoglycemia alarm threshold is used to indicate whether a hypoglycemic event currently occurs. Exemplary, if it is determined that the current blood sugar value is lower than the hypoglycemic alarm threshold, it can be determined that a hypoglycemic event currently occurs. Otherwise, it can be determined that no hypoglycemic event currently occurs. After obtaining the second result, if the second result indicates that a hypoglycemic event currently occurs, a hypoglycemic alarm is performed. For the description of the process of performing a hypoglycemic alarm, reference can be made to the description of performing a hypoglycemic early warning in the aforementioned embodiment, which will not be repeated here.

[0200] Since the hypoglycemia alarm threshold is a key parameter in the hypoglycemia alarm process and can significantly impact the accuracy of the second result, the above process can be used to adaptively adjust the hypoglycemia alarm threshold based on the user's past hypoglycemia blood glucose levels, thereby improving the accuracy of the hypoglycemia alarm.

[0201] In some implementations, the method can be collaboratively performed by electronic device 100 and electronic device 200, with each device separately performing some of the steps in the method. For example, electronic device 100 performs steps S801 to S804, and if the first result indicates that a hypoglycemic event will occur within the hypoglycemic warning period in the future, electronic device 100 can send an instruction to electronic device 200, and electronic device 200 can perform step S805 based on the instruction.

[0202] In some implementations, the blood glucose monitoring method shown in FIG. 6 and the blood glucose monitoring method shown in FIG. 8 may be implemented in combination.

[0203] FIG9 is a flow chart of a blood glucose monitoring method provided in an embodiment of the present invention. The method can be applied to electronic device 100 or electronic device 200. The embodiment of the present application does not specifically limit the execution subject of each step in the method.

[0204] As shown in FIG9 , the method includes:

[0205] S901. Determine a first warning duration according to first blood glucose data.

[0206] S902: Set the hypoglycemia warning duration as the first warning duration.

[0207] For the description of the electronic device 100 executing steps S901 and S902 , reference may be made to the description of the electronic device 100 executing steps S601 and S602 in the aforementioned embodiment, which will not be repeated here.

[0208] S903: Determine the historical moment when the user experiences hypoglycemia symptoms.

[0209] S904: Determine a first warning threshold value based on the blood sugar values ​​corresponding to the historical moments when the user experienced hypoglycemia symptoms.

[0210] S905: Set the hypoglycemia warning threshold as the first warning threshold.

[0211] For the description of the electronic device 100 executing steps S903 to S905 , reference may be made to the description of the electronic device 100 executing steps S801 to S803 in the aforementioned embodiment, which will not be repeated here.

[0212] S906: Obtain a first result based on the first blood sugar data and the hypoglycemia warning threshold.

[0213] S907: If the first result indicates that a hypoglycemia event will occur within the hypoglycemia warning period in the future, a hypoglycemia warning is issued.

[0214] For the description of the electronic device 100 executing steps S906 to S907 , reference may be made to the description of the electronic device 100 executing steps S603 to S604 in the aforementioned embodiment, which will not be repeated here.

[0215] In some implementations, steps S901 to S902 may be performed first, followed by steps S903 to S905. In other implementations, steps S903 to S905 may be performed first, followed by steps S901 to S902. This embodiment of the application does not specifically limit the order in which steps S901 to S902 and steps S903 to S905 are performed.

[0216] By executing the blood glucose monitoring method shown in FIG9 , the hypoglycemia warning duration and hypoglycemia warning threshold can be determined individually for the user based on the user's historical blood glucose status, thereby improving the accuracy of the hypoglycemia warning.

[0217] FIG10 is a flow chart of another blood glucose monitoring method provided by an embodiment of the present invention. The method can be applied to electronic device 100 or electronic device 200. The embodiment of the present application does not specifically limit the execution subject of each step in the method.

[0218] As shown in FIG10 , the method includes:

[0219] S1001. Determine user activity status.

[0220] User activity status is used to characterize the intensity of user activity. User activity intensity can be correlated with physiological data and / or sensor data. Physiological data can include heart rate, respiratory rate, blood oxygen saturation, etc. Motion sensor data can include accelerometer data, gyroscope sensor data, etc. For example, a higher heart rate can indicate a greater intensity of user activity.

[0221] In some implementations, user activity states can be categorized into the following three types: motion state, rest state, and sleep state. Different user activity states correspond to different user activity intensities. The user activity intensity corresponding to the motion state is greater than the user activity intensity corresponding to the rest state, and the user activity intensity corresponding to the rest state is greater than the user activity intensity corresponding to the sleep state.

[0222] The embodiments of the present application do not limit the specific types and names of user activity states. The subsequent embodiments will be specifically described using the above three user activity states as examples: exercise state, quiet state, and sleep state.

[0223] S1002: Determine the hypoglycemia warning duration and / or hypoglycemia warning threshold corresponding to the user's activity status.

[0224] Different user activity states may correspond to different hypoglycemia warning durations and / or hypoglycemia warning thresholds. The correspondence between user activity states and hypoglycemia warning durations, and the correspondence between user activity states and hypoglycemia warning thresholds may be preset.

[0225] Regarding the hypoglycemia warning duration: the hypoglycemia warning duration corresponding to the exercise state is shorter than the hypoglycemia warning duration corresponding to the rest state, and the hypoglycemia warning duration corresponding to the rest state is shorter than the hypoglycemia warning duration corresponding to the sleep state. For example, the hypoglycemia warning duration corresponding to the exercise state can be 5 minutes, the hypoglycemia warning duration corresponding to the rest state can be 15 minutes, and the hypoglycemia warning duration corresponding to the sleep state can be 30 minutes.

[0226] Regarding the hypoglycemia warning threshold: the hypoglycemia warning threshold corresponding to the exercise state is greater than the hypoglycemia warning threshold corresponding to the rest state, and the hypoglycemia warning threshold corresponding to the rest state is greater than the hypoglycemia warning threshold corresponding to the sleep state. For example, the hypoglycemia warning threshold corresponding to the exercise state may be 6 mmol / L, the hypoglycemia warning threshold corresponding to the rest state may be 5 mmol / L, and the hypoglycemia warning threshold corresponding to the sleep state may be 4.5 mmol / L.

[0227] Since the blood sugar of users in a state of exercise fluctuates rapidly and changes quickly, using a shorter hypoglycemia warning duration and a higher hypoglycemia warning threshold for users in a state of exercise can provide a more timely hypoglycemia warning when hypoglycemia is about to occur, preventing users from suffering serious consequences due to hypoglycemia during exercise. In addition, since the blood sugar of users in a state of sleep fluctuates slowly and changes slowly, and they may not be sensitive to mild hypoglycemia, using a longer hypoglycemia warning duration and a lower hypoglycemia warning threshold for users in a state of sleep can minimize the disturbance to the user's normal life and rest during the hypoglycemia warning process.

[0228] S1003. Obtain a first result based on the first blood sugar data and the hypoglycemia warning duration.

[0229] For the description of executing step S1003 , reference may be made to the description of executing step S603 in the aforementioned embodiment, which will not be repeated here.

[0230] S1004: If the first result indicates that a hypoglycemia event will occur within the first hypoglycemia warning period in the future, a hypoglycemia warning is issued.

[0231] For the description of the electronic device 100 executing step S1004 , reference may be made to the description of the execution of step S604 in the aforementioned embodiment, which will not be repeated here.

[0232] In some implementations, if the user's activity state is sleeping, then the hypoglycemia warning can be issued after the user wakes up.

[0233] In some implementations, the method shown in FIG. 10 may be performed periodically, such as every 24 hours. Furthermore, in some implementations, during step S1003, a portion of the first blood glucose data may be input into the hypoglycemia early warning model. For example, all of the user's blood glucose values ​​over the past 24 hours may be input into the hypoglycemia early warning model.

[0234] Since users in different activity states have different requirements for hypoglycemia warning, the user experience during blood glucose monitoring can be further improved by executing the blood glucose detection method shown in FIG10 .

[0235] In some implementations, the method can be collaboratively performed by electronic device 100 and electronic device 200, with each device separately performing some of the steps in the method. For example, electronic device 100 performs steps S1001 to S1003, and if the first result indicates that a hypoglycemic event will occur within the hypoglycemic warning period in the future, electronic device 100 can send an instruction to electronic device 200, and electronic device 200 performs step S1004.

[0236] In some implementations, the blood glucose detection method shown in FIG. 6 , the blood glucose detection method shown in FIG. 8 , and the blood glucose detection method shown in FIG. 10 may be implemented in combination.

[0237] Figure 11 is a schematic diagram of another blood glucose detection method provided by an embodiment of the present invention. This method can be applied to electronic device 100 or electronic device 200. This embodiment of the application does not specifically limit the execution entity of each step in this method.

[0238] As shown in FIG11 , the method includes:

[0239] Step S1101: Determine a first warning duration based on first blood glucose data.

[0240] For the description of executing step S1101 , reference may be made to the description of executing step S601 in the aforementioned embodiment, which will not be repeated here.

[0241] Step S1102: Determine the historical moment when the user experiences hypoglycemia symptoms.

[0242] Step S1103: Determine a first warning threshold value based on the blood glucose values ​​corresponding to the historical moments when the user experienced hypoglycemia symptoms.

[0243] For the description of executing steps S1102 to S1103 , reference may be made to the description of executing steps S801 to S802 in the aforementioned embodiment, which will not be repeated here.

[0244] Step S1104: Determine the user activity status.

[0245] For the description of executing step S1104 , reference may be made to the description of executing step S1001 in the aforementioned embodiment, which will not be repeated here.

[0246] Step S1105: Determine a second warning duration based on the first warning duration and the user activity status.

[0247] Specifically, when the user's activity state is in motion, the second warning duration may be greater than the first warning duration. Exemplarily, the second warning duration may be 1.2 times the first warning duration. When the user's activity state is quiet, the second warning duration may be equal to the first warning duration. When the user's activity state is quiet, the second warning duration may be less than the first warning duration. Exemplarily, the second warning duration may be 0.9 times the first warning duration.

[0248] Step S1106: Determine a second warning threshold based on the first warning threshold and the user activity status.

[0249] Specifically, when the user's activity state is in motion, the second warning threshold may be greater than the first warning threshold. Exemplarily, the second warning threshold may be 1.2 times the first warning threshold. When the user's activity state is quiet, the second warning threshold may be equal to the first warning threshold. When the user's activity state is quiet, the second warning threshold may be less than the first warning threshold. Exemplarily, the second warning threshold may be 0.9 times the first warning threshold.

[0250] Step S1107: Obtain a first result based on the first blood glucose data and the second warning duration.

[0251] For the description of executing step S1107, reference can be made to the description of executing step S603 in the above embodiment, which will not be repeated here. The second warning duration in step S1107 corresponds to the hypoglycemia warning duration in step S603.

[0252] Step S1108: If the first result indicates that a hypoglycemia event will occur within the second warning time period in the future, a hypoglycemia warning is issued.

[0253] For the description of executing step S1108, reference can be made to the description of executing step S604 in the above embodiment, which will not be repeated here. Among them, the second warning duration in step S1108 corresponds to the hypoglycemia warning duration in step S604.

[0254] In some implementations, step S1101 may be performed first, followed by steps S1102 to S1103. In other implementations, steps S1102 to S1103 may be performed first, followed by step S1101. This embodiment of the application does not specifically limit the order in which step S1101 and steps S1102 to S1103 are performed.

[0255] In some implementations, step S1105 may be performed first, and then step S1106. In other implementations, step S1106 may be performed first, and then step S1105. The present embodiment does not specifically limit the order in which steps S1105 and S1106 are performed.

[0256] By implementing the blood glucose monitoring method shown in FIG11 , the hypoglycemia warning duration and hypoglycemia warning threshold can be personalized for the user based not only on the user's historical blood glucose levels but also on the user's current activity status, further improving the accuracy of hypoglycemia warnings.

[0257] It is understandable that the blood glucose monitoring method provided in the embodiment of the present application can also be used for monitoring other body indicators, such as heart rate, body temperature, blood pressure, blood lipids, blood ketones, pH, creatinine, uric acid, etc.

[0258] FIG12 is a schematic structural diagram of a blood glucose monitoring device 300 provided in an embodiment of the present application.

[0259] As shown in FIG12 , the blood glucose monitoring device 300 may include components such as a processor 301, a memory 302, and a communication module 303. These components may be connected via a bus 304 or other means. FIG12 uses bus connection as an example, where the bus 304 is used to implement communication between the processor 301, the memory 302, and the communication module 303.

[0260] The processor 301 may include one or more processing units. The processor 301 may be used to provide computing and control capabilities to support the operation of the entire blood glucose monitoring device 300.

[0261] The memory 302 may be used to store various software programs and / or multiple sets of instructions. Specifically, the memory 302 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more disk storage devices, flash memory devices, or other non-volatile solid-state storage devices.

[0262] The communication module 303 can be used for the blood glucose monitoring device 300 to communicate with other communication devices. Specifically, the communication module 303 may include a communication interface, which may be a 3G communication interface, a long-term evolution (LTE) (4G) communication interface, a 5G communication interface, a WLAN communication interface, a WAN communication interface, a human skin communication interface, etc. In addition to being limited to a wireless communication interface, the blood glucose monitoring device 300 may also be configured with a wired communication interface to support wired communication.

[0263] In an embodiment of the present application, the blood glucose monitoring device 300 may be the electronic device 100 or the electronic device 200 described above, wherein the communication module 303 may be used to send and receive blood glucose data and instructions. The processor 301 may be used to determine the duration of a hypoglycemia warning and a hypoglycemia warning threshold, as well as to determine whether a hypoglycemia warning is required. The memory 302 may be used to store blood glucose data, as well as the software or program code required for all or part of the functions of the electronic device 100 or the electronic device 200 in the above method embodiment.

[0264] It should be noted that the blood glucose monitoring device 300 shown in FIG12 is only one implementation of an embodiment of the present application. In actual applications, the blood glucose monitoring device 300 may include more or fewer components than shown in the figure, or combine certain components, or deploy different components, which is not limited here.

[0265] The various implementation modes of this application can be combined arbitrarily to achieve different technical effects.

[0266] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described herein are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0267] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

[0268] In short, the above description is only an embodiment of the technical solution of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made based on the disclosure of the present invention should be included in the scope of protection of the present invention.

Claims

1. A blood glucose monitoring method, characterized in that: The method comprises: A first warning duration is determined based on first blood glucose data, where the first blood glucose data includes blood glucose data within a first time period, and the first warning duration is used for hypoglycemia warning.

2. The method according to claim 1, characterized in that The method further comprises: Obtaining a first result based on the first blood glucose data and the first warning time, where the first result is used to indicate whether a hypoglycemic event will occur within the first warning time in the future; If the first result indicates that a hypoglycemia event will occur within the first warning time period in the future, a hypoglycemia warning is issued.

3. The method according to claim 2, characterized in that Obtaining a first result according to the first blood glucose data and the first warning duration specifically includes: inputting the first blood glucose data into a hypoglycemia early warning model, wherein the hypoglycemia early warning model corresponds to the first early warning duration; The hypoglycemia early warning model outputs the first result.

4. The method according to claim 2 or 3, wherein the first result indicates that a hypoglycemic event will occur within the first warning time period in the future, specifically comprising: The first result indicates that the blood glucose value will be lower than the first warning threshold within the first warning time period in the future.

5. The method according to any one of claims 1 to 4, characterized in that Determining the first warning duration according to the first blood glucose data specifically includes: The first blood glucose data is input into a warning duration model to obtain the first warning duration.

6. The method according to claim 5, characterized in that The training process of the warning duration model includes: Determining an optimal warning duration corresponding to each piece of blood glucose data in a training data set, wherein the training data set includes a plurality of pieces of blood glucose data; The blood glucose data is used as input, and the accuracy of the hypoglycemia warning performed according to the blood glucose data is higher than a threshold and the hypoglycemia warning duration with the longest duration is used as output to train a warning duration model.

7. The method according to any one of claims 1 to 6, characterized in that The method further comprises: The first warning threshold is determined according to the blood sugar data corresponding to the moment when the hypoglycemia symptom occurs, and the first warning threshold is used for hypoglycemia warning.

8. The method according to claim 7, characterized in that Before determining the first warning threshold value based on the blood glucose data corresponding to the moment when the hypoglycemia symptom occurs, the method further includes: Acquiring physiological data, and determining the time when the hypoglycemic symptom occurs based on the physiological data; Alternatively, the moment when the hypoglycemia symptom occurs is determined based on the recording time of the hypoglycemia event.

9. The method according to claim 7 or 8, characterized in that The physiological data includes one or more of the following: Blood sugar levels, heart rate, heart rate variability, body temperature, exercise data.

10. The method according to any one of claims 2 to 9, characterized in that: The hypoglycemia warning may include one or more of the following: Display notification message, vibrate, and play sound.

11. A blood glucose monitoring method, characterized in that: The method comprises: Determine user activity status; A first warning duration and / or a first warning threshold is determined according to the user activity status, and the first warning duration and the first warning threshold are used for performing a hypoglycemia warning.

12. The method according to claim 11, characterized in that The user activity state includes a first state and a second state, and the activity intensity in the first state is greater than the activity intensity in the second state; The first warning duration corresponding to the first state is shorter than the first warning duration corresponding to the second state; The first warning threshold corresponding to the first state is greater than the first warning threshold corresponding to the second state.

13. The method according to claim 11 or 12, characterized in that Determining a first warning duration based on the user activity status includes: The first warning duration is determined according to first blood glucose data and the user activity status, where the first blood glucose data includes blood glucose data within a first time period.

14. The method according to any one of claims 11 to 13, characterized in that: Determining a first warning threshold according to the user activity status specifically includes: determining a second warning threshold value based on blood sugar data corresponding to the moment when the hypoglycemia symptom occurs; The first warning threshold is determined according to the second warning threshold and the user activity state.

15. The method according to claim 14, characterized in that Before determining the second warning threshold value based on the blood glucose data corresponding to the moment when the hypoglycemia symptom occurs, the method further includes: Acquiring physiological data, and determining the time when the hypoglycemic symptom occurs based on the physiological data; Alternatively, the moment when the hypoglycemia symptom occurs is determined based on the recording time of the hypoglycemia event.

16. The method according to any one of claims 11 to 15, characterized in that The method further comprises: Obtaining a first result based on the first blood glucose data, the first warning duration, and / or the first warning threshold, wherein the first result is used to indicate whether a hypoglycemic event will occur within the first warning duration in the future; If the first result indicates that a hypoglycemia event will occur within the first warning time period in the future, a hypoglycemia warning is issued.

17. The method according to claim 16, characterized in that The first result indicates that a hypoglycemic event will occur within the first warning period in the future, specifically including: The first result indicates that the blood glucose value will be lower than the first warning threshold within the first warning time period in the future.

18. An electronic device, characterized in that: The electronic device includes a memory, a processor, and a sensor. The memory is used to store a computer program, and the processor is used to call the computer program, so that the electronic device executes the method according to any one of claims 1 to 17.

19. A computer program product comprising instructions, characterized in that When the computer program product is run on an electronic device, the electronic device is caused to execute the method according to any one of claims 1 to 17.

20. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on an electronic device, the electronic device is caused to execute the method according to any one of claims 1 to 17.

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