CN113545745B - Usage monitoring method of wearable electronic device, medium and electronic device thereof - Google Patents

Abstract

The application relates to the technical field of information processing, and discloses a use monitoring method and medium of wearable electronic equipment and the wearable electronic equipment. The usage monitoring method of the wearable electronic device comprises the following steps: acquiring sleep monitoring data of the wearable electronic equipment during the sleep of a user; if the sleep monitoring data with abnormal monitoring quality exists in the sleep monitoring data, determining the reason of the sleep monitoring data with abnormal monitoring quality; and determining prompt information for prompting the user to improve monitoring quality of the wearable electronic device during sleep of the user based on the determined reason. According to the use monitoring method of the wearable electronic equipment, the reason influencing the sleep monitoring data quality under different scenes is judged, and the prompt is pertinently made to the user according to the reason influencing the sleep monitoring data quality, so that the sleep quality of the user and the monitoring quality of the wearable equipment are improved.

Description

Usage monitoring method of wearable electronic device, medium and electronic device thereof

technical field

The present application relates to the technical field of information processing, and in particular to a usage monitoring method of a wearable electronic device, a medium and an electronic device thereof.

Background technique

Sleep apnea is a common chronic sleep disorder that occurs worldwide. The World Health Organization reports that 1-10% of the world's population is affected by sleep apnea, of which there are about 50 million sleep apnea patients in my country. Sleep apnea is characterized by recurrent respiratory obstruction during sleep, resulting in hypoxia and repeated awakening of the body, which seriously affects people's spirit and health. Due to lack of effective sleep, people will become lethargic, drowsy during the day, and memory loss. This not only endangers health but also indirectly increases the probability of accidents such as traffic accidents and construction sites. If left untreated for a long time, it will lead to diseases such as diabetes, high blood pressure, cardiovascular and cerebrovascular diseases, stroke, neurasthenia, and even sudden death at night.

At present, there are few technologies for sleep apnea detection through wearable electronic devices, and when the signal quality (or the monitoring quality of wearable electronic devices) is not good, the methods adopted generally include: discarding the entire piece of data without using it or filtering The sleep monitoring data with poor signal quality is discarded, and the sleep monitoring data with better signal quality is used for calculation.

Contents of the invention

Embodiments of the present application provide a usage monitoring method of a wearable electronic device, a medium and an electronic device thereof. The usage monitoring method of the wearable electronic device of the present application determines the reasons that affect the quality of sleep monitoring data in different scenarios, and provides targeted reminders to the user according to the reasons that affect the quality of sleep monitoring data, so as to improve the user's sleep quality and Monitoring quality in wearable devices. Next, the content of this application will be specifically introduced.

In the first aspect, the embodiment of the present application provides a method for monitoring the use of a wearable electronic device, including:

Obtain the sleep monitoring data of the wearable electronic device during the user's sleep; in the case of sleep monitoring data with abnormal monitoring quality in the sleep monitoring data, determine the cause of the abnormal sleep monitoring data; based on the sleep monitoring data that affects the monitoring quality The reasons for determining the prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep.

That is, the wearable electronic device will further determine the cause of the abnormal monitoring quality affecting the sleep monitoring data when the monitoring quality of the sleep monitoring data during the monitored user's sleep period is abnormal. Then, according to the determined reasons affecting the quality of sleep monitoring data, the prompt information for prompting the user is further determined, so as to improve the monitoring quality of the wearable electronic device and the sleep quality of the user.

In a possible implementation of the first aspect above, the reason for the sleep monitoring data with abnormal monitoring quality in the above method includes at least one of the following:

The tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirements; the movement range or frequency of the user's movement when wearing the wearable electronic device during sleep affects the monitoring quality; the wearable electronic device is pressed during the user's sleep. Condition.

That is, in some embodiments of the present application, the reasons affecting the quality of the sleep monitoring data of the wearable electronic device during the user's sleep are the above three situations or a combination of the above three situations.

In a possible implementation of the above-mentioned first aspect, based on the judged reasons, determining the prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep includes at least one of the following:

When it is determined that the reason is that the tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirements, it is determined that the prompt information used to improve the monitoring quality is prompt information about wearing the wearable electronic device correctly; when the cause is determined to be the user When the range of motion or frequency of motion when wearing a wearable electronic device during sleep affects the quality of monitoring, it is determined that the prompt information used to improve the quality of monitoring is the prompt information about stable sleep; In the case of being pressed during the period, it is determined that the prompt information for improving the monitoring quality is the suggested prompt information about the wearing position.

That is, the prompt information that the user prompts the user to improve the monitoring quality of the wearable electronic device is determined according to the reasons that affect the monitoring quality of the sleep monitoring data of the wearable electronic device. If the reasons that affect the monitoring quality of the sleep monitoring data of the wearable electronic device are different , then the prompt message to the user will be different. It can be understood that when the reason affecting the sleep monitoring data of the wearable electronic device is a combination of the above three reasons, the prompt information to prompt the user will also be a combination of prompt information corresponding to the above three reasons.

In a possible implementation of the first aspect above, the reasons for determining in the above method that there is sleep monitoring data with abnormal monitoring quality include:

When it is judged that the monitoring quality of the sleep monitoring data of the screen of the wearable electronic device worn by the user is normal and abnormal at the same time under different orientations, it is determined that the reason is that the user wears the wearable electronic device during sleep. The degree of tightness that meets the measurement requirements; when it is judged that the monitoring quality of the sleep monitoring data of the screen of the wearable electronic device worn by the user is only abnormal under different orientations, it is determined that the cause is that the user wears the wearable electronic device during sleep. The degree of tightness of the equipment is tighter than the degree of tightness that meets the measurement requirements.

That is, when the monitoring quality of the user's sleep monitoring data detected by the wearable electronic device under different orientations of the screen is normal and abnormal at the same time, it is considered that the user is wearing the wearable electronic device loosely at this time; if the wearable electronic device If the monitoring quality of the user's sleep monitoring data monitored under different orientations of the screen is abnormal, it is considered that the user wears the wearable electronic device tightly.

In a possible implementation of the above-mentioned first aspect, the above-mentioned wearable electronic device includes a pressure sensor and a display screen, and the pressure sensor is located inside the display screen of the wearable electronic device; and the reason for determining that there is sleep monitoring data with abnormal monitoring quality includes :

According to the pressure monitoring data of the pressure sensor, it is judged whether the cause of the sleep monitoring data with abnormal monitoring quality is that the tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirements.

That is, judging the tightness of the wearable electronic device worn by the user can also be judged by setting a pressure sensor on the wearable electronic device. The tightness of wearing the wearable electronic device.

In a possible implementation of the above-mentioned first aspect, the above-mentioned wearable electronic device includes an acceleration sensor, and the reason for judging that there is sleep monitoring data with abnormal monitoring quality includes:

According to the fluctuation interval and fluctuation amplitude of the measurement data of the acceleration sensor in the acquired sleep monitoring data, it is determined whether the reason is that the motion range or motion frequency of the user wearing the wearable electronic device during sleep affects the monitoring quality.

That is, the wearable electronic device obtains the acceleration sensor data fluctuation interval and the acceleration sensor data fluctuation amplitude in the sleep monitoring data through the acceleration sensor, and calculates the variance of the acceleration sensor data fluctuation interval and the variance of the acceleration sensor data fluctuation amplitude. The variance of the data fluctuation interval and the variance of the acceleration sensor data fluctuation amplitude are compared with the acceleration sensor data fluctuation interval threshold and the acceleration sensor data fluctuation amplitude threshold respectively to determine whether the reason affecting the monitoring quality of the sleep monitoring data of the wearable electronic device is because The user made excessive movements or movements during sleep. It can be understood that the average value of the acceleration sensor data fluctuation interval and the acceleration sensor data fluctuation amplitude or other values that can characterize the fluctuation of the acceleration sensor measurement data can also be calculated to determine the user's motion range or motion frequency during sleep .

In a possible implementation of the first aspect above, the reasons for determining in the above method that there is sleep monitoring data with abnormal monitoring quality include:

If it is judged that the degree of tightness of the wearable electronic device worn by the user during sleep meets the measurement requirements, and the range or frequency of motion of the user when wearing the wearable electronic device during sleep does not affect the monitoring quality, determine that the cause is the wearable electronic device. There are cases of being pinned down while the user is sleeping.

That is, if the way the user wears the wearable electronic device is correct and the user does not have a large range of motion or a high frequency of motion during sleep, then it is considered that the reason that affects the quality of the sleep monitoring data of the wearable electronic device is that the wearable electronic device is in the user's Pressed down during sleep.

In a possible implementation of the above first aspect, the above method further includes:

According to the fluctuation of the photoplethysmography sensor data and/or the fluctuation of the acceleration sensor measurement data in the acquired sleep monitoring data, it is judged whether there is abnormal sleep monitoring data in the sleep monitoring data.

That is, whether the monitoring quality of the sleep monitoring data of the wearable electronic device is abnormal is judged according to the fluctuation of the photoplethysmography sensor data acquired by the wearable electronic device and/or the measurement data of the acceleration sensor.

Specifically, calculate the average value of the heart rate peak interval and the heart rate peak amplitude in the acquired photoplethysmography sensor data and/or calculate the acceleration sensor data fluctuation interval and the acceleration sensor data fluctuation interval and acceleration sensor measurement data (or monitoring data) of the acceleration sensor The average value of the data fluctuation amplitude, and then compare the average value of the heart rate peak interval and the heart rate peak amplitude with the preset heart rate peak interval threshold and the preset heart rate peak amplitude threshold and/or compare the acceleration sensor data fluctuation interval with the acceleration sensor The average value of the data fluctuation amplitude is compared with the preset acceleration sensor data fluctuation interval threshold and the acceleration sensor data fluctuation amplitude threshold respectively to determine whether the monitoring quality of the sleep monitoring data of the wearable electronic device is abnormal.

In a possible implementation of the above first aspect, the above method further includes:

Displaying the determined prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep. That is, the prompt information for prompting the user is displayed on the wearable electronic device.

In a possible implementation of the above first aspect, acquiring sleep monitoring data of the wearable electronic device during the user's sleep in the above method includes:

Sleep monitoring data is received from a wearable electronic device. That is, the above-mentioned judgment process of the monitoring quality of the sleep monitoring data and the judgment process of the reasons affecting the monitoring quality of the sleep monitoring data can also be carried out on other electronic devices (such as mobile phones or servers, etc.). , other electronic devices may receive from the wearable electronic device the sleep monitoring data of the user during sleep monitored by the wearable electronic device.

In a possible implementation of the above first aspect, the above method further includes:

The determined prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep is sent externally. That is, the prompt information for prompting the user may also be displayed on other electronic devices (such as a mobile phone), and at this time, the wearable electronic device will send the prompt information for prompting the user to another electronic device.

In the second aspect, the embodiment of the present application provides a method for monitoring sleep apnea of an electronic device, including:

The wearable electronic device sends the sleep monitoring data of the wearable electronic device during the user's sleep, wherein there are sleep monitoring data with abnormal monitoring quality in the sleep monitoring data; Prompt information during monitoring quality.

That is, judge the monitoring quality of the above sleep monitoring data on other electronic devices and determine the reasons that affect the monitoring quality of the sleep monitoring data, and then determine the reason based on the determined reasons that affect the monitoring quality of the sleep monitoring data of the wearable electronic device. The prompt information for prompting the user is displayed on the wearable electronic device. That is to say, the analysis process of sleep monitoring data is transferred to other electronic devices to reduce the power consumption of wearable electronic devices and improve the battery life of wearable electronic devices.

In a possible implementation of the second aspect above, the prompt information received by the wearable electronic device for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep includes at least one of the following:

Tips on wearing a wearable electronic device correctly; tips on sleeping soundly; tips on recommendations for wearing parts.

Specifically, when other electronic devices (such as mobile phones) determine that the reason is that the tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirements, the prompt information received by the wearable electronic device is about wearing the wearable electronic device correctly. The prompt information of the device; when other electronic devices determine that the reason is that the range of motion or the frequency of motion of the user wearing the wearable electronic device during sleep affects the monitoring quality, the prompt information received by the wearable electronic device is a prompt about a safe sleep Information; when other electronic devices determine that the reason is that the wearable electronic device is pressed while the user is sleeping, the prompt information received by the wearable electronic device is the suggested prompt information about the wearing position. It can be understood that when other electronic devices determine that the reason affecting the sleep monitoring data of the wearable electronic device is a combination of the above three reasons, then the prompt information to prompt the user will also be the prompt information corresponding to the above three reasons. combination.

In a third aspect, an embodiment of the present application is a readable medium of an electronic device, and an instruction is stored on the readable medium, and when the instruction is executed on the electronic device, the electronic device executes the method of any aspect above.

In a fourth aspect, an embodiment of the present application provides an electronic device, including: a memory for storing instructions executed by one or more processors of the electronic device, and a processor, which is one of the processors of the electronic device, used For performing the method of any one of the first aspect and the second aspect above.

In the fifth aspect, the embodiment of the present application provides an electronic device, including: a memory, a processor, a photoplethysmography sensor, and an acceleration sensor; Photoplethysmography sensor data; the acceleration sensor is used to obtain the acceleration sensor monitoring data of the user of the electronic device during sleep; the memory is used to store instructions executed by one or more processors of the electronic device; the processor is the electronic device One of the processors, configured to execute the method of any one of the first aspect and the second aspect above.

In a sixth aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor, a display screen, a photoplethysmography sensor, a pressure sensor, and an acceleration sensor; the photoplethysmography sensor is used to obtain the electronic device The photoplethysmography sensor data of the user during sleep; the acceleration sensor is used to obtain the acceleration sensor monitoring data of the user of the electronic device during sleep; the display screen is used to display and prompt the user to increase the wearable electronic device during the user's sleep The prompt information of monitoring quality; the pressure sensor is located on the inner side of the display screen, which is used to detect the tightness of the user wearing the electronic device; the memory is used to store instructions executed by one or more processors of the electronic device; the processor is the electronic device One of the processors, used in the method of any one of the first aspect and the second aspect above.

In a seventh aspect, the embodiment of the present application provides an electronic device, and the electronic device has a function of implementing the above search method. The functions may be implemented by hardware, or may be implemented by executing corresponding software through hardware. Hardware or software includes one or more units corresponding to the functions described above.

Description of drawings

Fig. 1 shows an application scenario diagram of a usage monitoring method of a wearable electronic device according to some embodiments of the present application.

Fig. 2 shows a schematic diagram of a hardware structure of a wristband according to some embodiments of the present application.

Fig. 3a shows a schematic flowchart of a technical solution according to some embodiments of the present application.

Fig. 3b shows a schematic flowchart of a technical solution according to some embodiments of the present application.

Fig. 4a shows a schematic diagram of a human-computer interaction interface according to some embodiments of the present application.

Fig. 4b shows a schematic diagram of a human-computer interaction interface according to some embodiments of the present application.

Fig. 5a shows a schematic diagram of a human-computer interaction interface according to some embodiments of the present application.

Fig. 5b shows a schematic diagram of a human-computer interaction interface according to some embodiments of the present application.

Fig. 6a shows a schematic diagram of a human-computer interaction interface according to some embodiments of the present application.

Fig. 6b shows a schematic diagram of a human-computer interaction interface according to some embodiments of the present application.

Fig. 7 shows a schematic diagram of interaction between a mobile phone 200 and a wristband 100 according to some embodiments of the present application.

FIG. 8 shows a schematic structural diagram of an electronic device 800 capable of implementing functions of a mobile phone 200 according to some embodiments of the present application.

FIG. 9 shows a software system of an electronic device 800 capable of implementing functions of a mobile phone 200 according to some embodiments of the present application.

Detailed ways

The technical solutions of the embodiments of the present application will be described in further detail below with reference to the drawings and embodiments.

Fig. 1 is an application scene diagram of a method for monitoring the use of a wearable electronic device according to a specific embodiment of the present application. As shown in FIG. 1 , the embodiment of the present application relates to a wearable electronic device 100, which can communicate wirelessly with other electronic devices in various wireless ways, for example, with an electronic device 200 or a server 300 Wireless communication. For another example, the wearable electronic device 100 can send a wireless signal to the server 300 through its own radio frequency circuit and antenna through a wireless communication link, requesting the server 300 to perform wireless network business processing for the specific business needs of the wearable electronic device 100, such as user Registration, data acquisition and monitoring, etc.; as another example, the wearable electronic device 100 can be matched with the electronic device 200 through its own Bluetooth, and after the matching is successful, it can communicate with the electronic device 200 through the Bluetooth communication link. The communication method performs data communication with the electronic device 200, such as radio frequency identification technology, short-range wireless communication technology, and the like. In addition, the wearable electronic device 100 can also detect changes in the external environment through its various sensors.

In a specific embodiment of the present application, the wearable electronic device 100 can monitor the sleep breathing condition of the user during sleep. For example, in a specific implementation, the wearable electronic device 100 acquires sleep monitoring data during sleep of the user, wherein the sleep monitoring data includes photoplethysmography (Photoplethysmo graph, PPG) sensor data, electrocardiography data (Electrocardiography, ECG) ( For example, heart rate peak interval, heart rate peak amplitude, blood oxygen data, body temperature data), acceleration sensor (Acceleration transducer, ACC) measurement data (or monitoring data) (for example, acceleration sensor data fluctuation interval, acceleration sensor data fluctuation amplitude ), gyroscope sensor data, and so on. And when there is sleep monitoring data with abnormal monitoring quality (or poor monitoring quality of sleep monitoring data) in the sleep monitoring data, determine the reason for the sleep monitoring data with abnormal monitoring quality, and then determine the method used to prompt the user according to the determined reason. Improve the prompt information of the monitoring quality of the wearable electronic device during the user's sleep, and push corresponding suggestions or services to the user. For example, when it is determined that the reason for the sleep monitoring data with abnormal monitoring quality is that the tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirements, it is determined that the prompt information for improving the monitoring quality is about correct wearing. Prompt information for wearable electronic devices; when it is determined that the reason for the sleep monitoring data with abnormal monitoring quality is that the range of motion or the frequency of motion when the user wears the wearable electronic device during sleep affects the monitoring quality, determine The prompt information for improving the monitoring quality is prompt information about stable sleep; when it is determined that the reason for the sleep monitoring data with abnormal monitoring quality is that the wearable electronic device is pressed during the user's sleep, it is determined to be used to improve the monitoring quality. The prompt information of the quality is the prompt information of the suggestion about the wearing part, and then these specific reasons are sent to the user.

The technical solution of the present application can provide the user with wearing and sleep suggestions by determining the cause of abnormal monitoring quality of the acquired sleep monitoring data of the wearable electronic device 100 , thereby improving the monitoring quality of the sleep monitoring data of the smart wearable electronic device 100 .

In a specific embodiment of the present application, the wearable electronic device 100 may be a variety of devices, including but not limited to smart watches, smart bracelets or glasses, helmets, headbands and other wearable electronic devices, medical testing instruments, etc. . In the following description, in order to simplify the description, the technical solution of the present application is described by taking the smart bracelet 100 as an example.

The electronic device 200 can be a client capable of communicating with the wearable electronic device 100, and can help the wearable electronic device 100 complete registration, control the firmware update of the wearable electronic device 100, receive the sleep monitoring data of the wearable electronic device 100, assist the wearable electronic device 100 The wearable electronic device 100 analyzes the sleep monitoring data to monitor and prompt the user's wearing style and sleep status. It is understood that the electronic device 200 may include, but is not limited to, a laptop computer, a desktop computer, a tablet computer, a smart phone, a server, a wearable electronic device, a head-mounted display, a mobile email device, a portable game console, a portable music player browser, reader device, television with one or more processors embedded in or coupled to it, or other electronic device capable of accessing a network. In the following description, in order to simplify the description, the mobile phone 200 is taken as an example to illustrate the technical solution of the present application.

FIG. 2 is a schematic diagram of a hardware structure of a smart bracelet 100 provided according to some embodiments of the present application. The smart bracelet may include a smart bracelet main body 100 . In one embodiment of the present application, the main body of the smart bracelet 100 may include a touch screen 101 (also called a touch screen panel), a display screen 102, a housing (the housing includes a front housing (not shown in FIG. 2 ) and Bottom case (not shown in Fig. 2)), and processor 103, micro control unit (micro control unit, MCU) 104, memory 105, wireless communication module 106, pressure sensor 107, PPG sensor 108, acceleration sensor 109, power supply 111 , power management system 112 and so on.

The functional components of the smart bracelet 100 are introduced respectively below:

The touch screen 101, which can also be called a touch panel, can collect the touch operation of the user on the smart bracelet 100 (for example, the user uses any suitable object or accessory such as a finger and a stylus to operate on the touch panel or near the touch panel. ), and drive the corresponding connected device according to the preset program.

The display screen 102 can be used to display information input by the user or provide prompt information and various menus on the wristband to the user. Further, the touch screen 101 may cover the display screen 102. When the touch screen 101 detects a touch operation on or near it, it transmits to the processor 103 to determine the type of the touch event. A corresponding visual output is provided at 102 . For example, in some embodiments of the present application, when the sleep monitoring data of the smart bracelet 100 has sleep monitoring data with abnormal monitoring quality, it is determined that there is a reason for the abnormal monitoring quality of the sleep monitoring data, and according to the reason, it is determined to prompt the user to improve the quality of the sleep monitoring data. The smart bracelet 100 can display the prompt information (such as a teaching video on how to correctly wear the smart bracelet 100 , etc.) on the display screen 102 after the prompt information of the monitoring quality during the user's sleep.

Processor 103 is used for system scheduling, touch screen 101, control display screen 102, support Bluetooth 106 and so on.

The micro control unit 104 is used for controlling the sensor, performing calculations on the sensor data, communicating with the processor 103 and so on. Wherein, the sensor may include a pressure sensor 107, a PPG sensor 108, an acceleration sensor 109, a motion sensor or other sensors. For example, in some embodiments of the present application, the micro control unit 104 collects PPG data (for example, heart rate peak interval, heart rate peak amplitude) and ACC data (for example, ACC data fluctuation interval, ACC data fluctuation amplitude) is analyzed to determine the reason for the abnormal monitoring quality of sleep monitoring data. In addition, it can be understood that, in other embodiments, the above-mentioned processing of the PPG data and the ACC data may also be completed by the processor 103, which is not limited here.

The memory 105 is used to store software programs and data, and the processor 103 executes various functional applications and data processing of the smart bracelet 100 by running the software programs and data stored in the memory 105 . For example, in some embodiments of the present application, the memory 105 may store PPG data collected by the PPG sensor or store ACC data collected by the acceleration sensor. At the same time, the memory can also store the user's registration information, login information, and so on.

The wireless communication module 106, the smart bracelet 100 can exchange information with other electronic devices (such as mobile phones, tablet computers, etc.) through the wireless communication module, and can connect to the network or server through the above-mentioned electronic devices. Wherein, the wireless communication module can provide wireless local area network (wireless local area networks, WLAN), (such as wireless fidelity (wireless fidelity, Wi-Fi) network), Bluetooth (blue tooth, BT) applied on the smart bracelet 100. , global navigation satellite system (global navigation satellite system, GNSS), frequency modulation (frequency modulation, FM), near field communication technology (near field communication, NFC), infrared technology (infrared, IR) and other wireless communication solutions.

It can be understood that the structure shown in FIG. 2 is only a specific structure to realize the function of the smart bracelet 100 in the technical solution of the present application, and the smart bracelet 100 or other types of wearable electronic devices with other structures that can achieve similar functions The equipment is also applicable to the technical solution of this application, which is not limited here.

In the following, the technical solution of the present application will be introduced in detail in combination with specific scenarios.

In some embodiments of the present application, the smart bracelet 100 can independently complete the entire technical solution, for example, the smart bracelet 100 monitors the sleep condition of the user, and according to the sleep monitoring data ( Such as PPG data, ACC data) to judge the monitoring quality of the sleep monitoring data of the smart bracelet 100 during the user's sleep, in the case of abnormal monitoring quality of the sleep monitoring data, determine the reason for the abnormal monitoring quality of the sleep monitoring data, Then, based on specific reasons, the mobile phone 200 is targeted to push suggestions that can improve the monitoring quality of the sleep monitoring data of the smart bracelet 100 to the user.

In addition, in other embodiments of the present application, the mobile phone 200 may also determine that there is a reason for abnormal monitoring quality of the sleep monitoring data. For example, when the user wishes to reduce the power consumption of the smart bracelet 100, he can choose to hand over the cause of the abnormal monitoring quality of the sleep monitoring data to the mobile phone 200, and only display it on the side of the smart bracelet 100 for prompting. prompt information. Specifically, at this time, the smart bracelet 100 can send the monitored sleep monitoring data during the user's sleep to the mobile phone 200 through Bluetooth or wireless network, and then the mobile phone 200 judges the monitoring status of the sleep monitoring data according to the received sleep monitoring data. quality, and determine the cause of the abnormal monitoring quality of the sleep monitoring data, and finally determine the prompt information for the user to prompt the user according to the abnormal monitoring quality of the sleep monitoring data during the user's sleep period monitored by the smart bracelet 100, and then the mobile phone 200 will The prompt information is sent to the side of the smart bracelet 100 worn by the user, and the prompt information is displayed on the display screen on the side of the smart bracelet 100 .

In addition, in some other embodiments of the present application, the server 300 may also perform the judgment of the monitoring quality of the sleep monitoring data. For example, the smart bracelet 100 sends the sleep monitoring data during the user's sleep period monitored by the smart bracelet 100 to the server 300 through wireless communication, and then the server 300 judges the sleep monitoring data according to the received sleep monitoring data during the user's sleep period. The monitoring quality of the data, and determine the reason for the abnormal monitoring quality of the sleep monitoring data, and finally according to the reason for the abnormal monitoring quality of the sleep monitoring data during the user's sleep period monitored by the smart bracelet 100, targeted push to the user can improve the intelligence. The monitoring quality prompt information of the sleep monitoring data of the wristband 100 during the user's sleep.

For the convenience of explanation, the judgment of the monitoring quality of the sleep monitoring data on the side of the smart bracelet 100 and the judgment of the reason for the abnormal quality of the monitoring data of the sleep monitoring data are taken below, and the relevant prompt information is pushed on the side of the mobile phone 200 as an example for illustration. .

Fig. 3a shows a flow chart of the technical solution of the present application according to the embodiment of the present application. Specifically as shown in Figure 3a:

a301: Obtain sleep monitoring data during the user's sleep. For example, obtain PPG data or ACC data during user sleep, where PPG data can include the user's heart rate fluctuation amplitude, heart rate fluctuation interval, pulse data, blood oxygen value, ECG data, etc., and ACC data can It is the ACC data fluctuation interval, the ACC data fluctuation amplitude, the data monitored by the gyroscope, etc.

a302: judge the monitoring quality of the sleep monitoring data of the smart bracelet 100; if the monitoring quality of the sleep monitoring data of the smart bracelet 100 is normal, proceed to a303; if the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal, proceed to a304.

a303: The corresponding sleep monitoring data is marked as "normal", and no prompt is given to the user.

a304: further determine whether the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal due to the user's many actions; , if it is not because of too many user actions, go to a306.

a305: Mark the corresponding sleep monitoring data as "abnormal" and mark the cause of the abnormal monitoring quality at the same time. For example, use the mark "U1" to indicate that the abnormal cause is "many user actions", and then determine the prompt information according to the cause of the abnormal monitoring quality .

a306: further determine whether the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal because the user wears the bracelet too loosely or too tightly. If it is because the user wears the smart bracelet 100 too loosely or too tightly, then proceed to a307 and a310; if it is not because the user wears the smart bracelet 100 too loosely or too tightly, the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal, then proceed to a308 .

a307: Mark the corresponding sleep monitoring data as "abnormal", and mark the cause of the abnormal monitoring quality at the same time. The prompt message for determining the cause of abnormal monitoring quality.

a308: Further judge whether the smart bracelet is pressed. If the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal because the smart bracelet 100 is pressed, then proceed to a309 and a310.

a309: Mark the corresponding sleep monitoring data as "abnormal", and mark the cause of abnormal monitoring quality at the same time. Determine the prompt message for the reason.

a310: Send the corresponding prompt information to the mobile phone.

As shown in FIG. 3 a , in the flow of the above technical solution, there is a sequence limitation in the way of determining the cause of the abnormal monitoring quality of the sleep monitoring data. In some embodiments of the present application, the manner of judging the cause of the abnormal monitoring quality of the sleep monitoring data may also be performed at the same time. For example, at the same time, it is determined whether the cause of the abnormality of the sleep monitoring data is "the user moves too much", "the user wears it too loose or too tight", "the smart bracelet is pressed", and if it is judged that the sleep monitoring data of the smart bracelet 100 is Reasons for abnormal monitoring quality Combination of the above reasons, for example, the monitoring abnormality of sleep monitoring data satisfies both "the user moves too much" and "the smart bracelet is pressed". At this time, when marking the sleep monitoring data as "abnormal", you can mark the sleep monitoring data with abnormal monitoring quality as "U1U3", where "U1" indicates that the reason for the abnormal monitoring quality is "too many user actions", "U3 "Indicates that the reason for the abnormal monitoring quality is "the smart bracelet is pressed", and at the same time determine a variety of prompt information based on the cause of the abnormal monitoring quality of the sleep monitoring data.

In addition, it can be understood that in other embodiments of the present application, the method of determining the cause of abnormal monitoring quality of sleep monitoring data may not be judged according to the order of a304, a306, and a308, and the order of judgment may be arbitrary. For example, in specific In the implementation process, the above methods can be:

First determine whether the reason for the abnormal monitoring quality of the sleep monitoring data of the smart bracelet 100 is because "the user wears it too loose or too tight" (a306); If the monitoring quality of the sleep monitoring data of 100 is abnormal, then it is judged whether the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal (a304) because of "many user actions". If the monitoring quality of the sleep monitoring data is abnormal, it is judged whether the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal due to "the smart bracelet is pressed" (a308). In this judging manner, other steps are consistent with the flow of the technical solution described in FIG. 3 a , and will not be repeated here.

Figure 3b shows that after determining the cause of the abnormal monitoring quality of the sleep monitoring data of the smart bracelet 100 through the above technical solution and determining the prompt message according to the specific abnormal cause, the mobile phone 200 pushes the relevant prompt information to the user specific circumstances. For example, when it is determined that "the user wears and operates without problems b302", that is, when the monitoring quality of the sleep monitoring data of the smart bracelet 100 is normal, the user is "not prompted (b304)"; )" that is, when the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal, if the user is "wearing normally but moving a lot at night (b306)", that is, the user is not wearing the smart bracelet too tightly or too loosely but the user's movements are large or If the frequency is high, perform "mark data abnormality and confirm that the prompt message is "suggested push for safe sleep, it is recommended to wear it multiple times" (b307); if the user "wears too loose or too tight (b308)", then "mark data Abnormal and confirm that the prompt information is "play the wearing guidance video" (b309); On the contralateral hand in the main lateral position" (b311)"; if it is "combination of multiple reasons (b312)", then confirm that the prompt information is "combination of multiple suggestions (b313)".

Among them, the specific way of judging the monitoring quality of the sleep monitoring data of the smart bracelet 100 and the way of determining the reason for the abnormal monitoring quality of the sleep monitoring data of the smart bracelet 100 are as follows:

Obtain sleep monitoring data during the user's sleep

In a specific embodiment of the present application, the smart bracelet 100 monitors the sleep condition of the user, and obtains the sleep monitoring data (such as heart rate peak interval, heart rate peak amplitude) of the user during sleep through the PPG sensor 108 and the acceleration sensor 109. , ACC data fluctuation interval, ACC data fluctuation amplitude, etc.).

In some embodiments of the present application, the smart bracelet 100 can acquire the sleep monitoring data during the user's sleep period by time period, and can also acquire the sleep monitoring data during the user's sleep period in real time. For example, a user's sleep is generally divided into daytime and nighttime. But during the day, it may be only half an hour or 1 hour of nap, which is short, so the smart bracelet 100 can monitor the user in real time to obtain the sleep monitoring data of the user at this time; at night, the user generally sleeps at 7 -8 hours, at this time, real-time monitoring will increase the power consumption of the bracelet 100, so the user's sleep monitoring data can be obtained in different time periods (for example, sleep monitoring data from 9:00 p.m. to 3:00 a.m. or in the early morning Sleep monitoring data from 1 am to 5 am). Or, because it is less likely to be able to enter deep sleep during a nap during the day, and the user has less sleep apnea, the sleep monitoring data during the user's sleep period can be obtained in time segments, and at night, the user's If the sleep time is sufficient, there are more cases of sleep apnea, and the user's sleep monitoring data at this time can be monitored and acquired in real time.

Hereinafter, the real-time monitoring of the user by the smart bracelet 100 from 1:00 p.m. to 5:00 a.m. will be taken as an example for specific description.

Judging the monitoring quality of the acquired sleep monitoring data

The monitoring quality of the acquired sleep monitoring data is judged, wherein the sleep monitoring data includes the heart rate peak interval and the heart rate peak amplitude obtained by the PPG sensor 108 . Of course, it can be understood that in other embodiments, the sleep monitoring data can also be other data characteristics that characterize the monitoring quality of the sleep monitoring data of the smart bracelet, such as related pulse data, blood pressure data, and the like.

In an embodiment of the present application, the smart bracelet 100 can judge the monitoring quality of the sleep monitoring data of the smart bracelet based on the heart rate peak interval and the heart rate peak amplitude obtained by the PPG sensor 108 . For example, the heart rate peak interval threshold T1 and the heart rate peak amplitude threshold A1 can be preset through the historical heart rate peak interval and historical heart rate peak amplitude monitored by the smart bracelet 100. When the heart rate peak value obtained by the smart bracelet 100 If the interval time is less than T1 and the heart rate peak amplitude is less than A1, then the monitoring quality of the sleep monitoring data of the smart bracelet is normal at this time, otherwise it is considered that the monitoring quality of the sleep monitoring data of the smart bracelet is abnormal.

以及平均心率波峰幅值

(在其他实施例中，还可以是用户在时间段T内的心率波峰和心率间隔的方差、极差等等)For example, in a specific implementation process, the smart bracelet 100 monitors the user's heart rate peak intervals t1, t2, t3...tn and heart rate peak amplitudes a1, a2, a3...an in the time period T, and then The smart bracelet 100 calculates the average heart rate peak interval of the user in the time period T according to the formula (1)

and average heart rate peak amplitude

(In other embodiments, it can also be the variance, extreme difference, etc. of the user's heart rate peak and heart rate interval within the time period T)

Among them, μ represents the average value of the data, h1, h2, h3...hn represent the data, and n represents the number of data

以及平均心率波峰幅值

预设心率波峰间隔阈值T1和预设心率波峰幅值阈值A1进行比较，如果用户在时间段T内的平均心率波峰间隔

小于预设心率波峰间隔阈值T1以及平均心率波峰幅值

小于预设心率波峰幅值阈值A1，则认为智能手环的睡眠监测数据的监测质量正常，如果用户在时间段T内的平均心率波峰间隔

大于预设心率波峰间隔阈值T1或者平均心率波峰幅值

大于预设心率波峰幅值阈值A1，则认为智能手环的睡眠监测数据的监测质量异常。At the same time, the smart bracelet 100 sets the heart rate peak interval threshold T1 and the heart rate peak amplitude threshold A1 according to the monitored historical heart rate peak interval and historical heart rate peak amplitude (the values of T1 and A1 can also be determined by calculating the historical heart rate peak interval and historical heart rate peak value). The average value or variance of the heart rate peak amplitude is set)), then, the smart bracelet 100 calculates the average heart rate peak interval of the user in the time period T

and average heart rate peak amplitude

The preset heart rate peak interval threshold T1 is compared with the preset heart rate peak amplitude threshold A1, if the user's average heart rate peak interval within the time period T

Less than the preset heart rate peak interval threshold T1 and the average heart rate peak amplitude

If it is less than the preset heart rate peak amplitude threshold A1, it is considered that the monitoring quality of the sleep monitoring data of the smart bracelet is normal. If the user's average heart rate peak interval within the time period T

Greater than the preset heart rate peak interval threshold T1 or the average heart rate peak amplitude

If it is greater than the preset heart rate peak amplitude threshold A1, it is considered that the monitoring quality of the sleep monitoring data of the smart bracelet is abnormal.

In addition, in some embodiments of the present application, other methods may also be used to judge the quality of the physiological data monitored by the smart bracelet 100 .

以及平均波动间隔

并将用户在时间段T内的ACC数据的平均波动幅值

以及平均波动间隔

与ACC数据波动幅值阈值A2和ACC数据波动间隔阈值T2比较，如果用户在时间段T内的ACC数据的平均波动幅值

小于ACC数据波动幅值阈值A2并且平均波动间隔

小于ACC数据波动间隔阈值T2，则认为智能手环智能手环100的睡眠监测数据的监测质量正常，如果用户在时间段T内的ACC数据的平均波动幅值

大于ACC数据波动幅值阈值A2或者平均波动间隔

大于ACC数据波动间隔阈值T2，则认为智能手环100的睡眠监测数据的监测质量异常。For example, in one embodiment of the present application, the smart bracelet 100 may also judge the monitoring quality of the sleep monitoring data of the smart bracelet 100 based on the ACC data. In a specific implementation, when the fluctuation amplitude of the ACC data is small and the fluctuation interval is short, it can be considered that the monitoring quality of the sleep monitoring data of the smart bracelet is normal at this time. Specifically, the smart bracelet 100 presets the ACC data fluctuation amplitude threshold A2 and the ACC data fluctuation interval threshold T2 according to the monitored user's historical ACC data fluctuation interval and historical ACC data fluctuation amplitude (the values of A2 and T2 are also It can be set by calculating the historical ACC data fluctuation interval and the average value or variance of the historical ACC data fluctuation amplitude, etc.), at the same time, the smart bracelet 100 monitors the user's ACC data fluctuation amplitude b1, b2, b3 within the time period T. · · bn and ACC data fluctuation intervals c1, c2, c3 · · · c4, and calculate the average fluctuation amplitude of the user's ACC data within the time period T according to the formula (1)

and the average fluctuation interval

And the average fluctuation amplitude of the user's ACC data in the time period T

and the average fluctuation interval

Compared with the ACC data fluctuation amplitude threshold A2 and the ACC data fluctuation interval threshold T2, if the average fluctuation amplitude of the user's ACC data in the time period T

Less than the ACC data fluctuation amplitude threshold A2 and the average fluctuation interval

If it is less than the ACC data fluctuation interval threshold T2, it is considered that the monitoring quality of the sleep monitoring data of the smart bracelet smart bracelet 100 is normal, if the average fluctuation amplitude of the ACC data of the user in the time period T

Greater than the ACC data fluctuation amplitude threshold A2 or the average fluctuation interval

If it is greater than the ACC data fluctuation interval threshold T2, it is considered that the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal.

In addition, in some embodiments of the present application, the smart bracelet 100 can also judge the monitoring quality of the sleep monitoring data by means of machine learning. For example, in a specific implementation, the smart bracelet 100 manually calibrates these historical sleep monitoring data according to the monitored historical sleep monitoring data of the user (wherein, the quality of these historical sleep monitoring data is normal or abnormal), such as , the data with normal quality can be marked as "normal", and the data with abnormal quality can be marked as "abnormal". Then feature extraction is performed on these historical sleep monitoring data to generate feature vectors, and then the extracted feature vectors are input into the convolutional neural network model (Convolutional Neural Networks, CNN), and the convolutional neural network model is trained so that the model can Judge the quality of historical physiological data and historical physical data. For example, the difference between the input and output of the model can be used as a loss function. For example, historical sleep monitoring data is randomly input, and the output of the model is compared with the input historical sleep monitoring number. If the input historical sleep monitoring data If the mark is "normal", and the output result of the model is also "normal", the loss function is considered to be close to 0, and the model has been trained. If the mark of the input historical sleep data is "abnormal", but the output result is not " Abnormal", it is considered that the loss function is not close to 0, then adjust the relevant parameters of the model, and carry out the next round of training until the loss function between the input and output is close to 0, then the training of the model is completed. Then input the user's sleep monitoring data currently acquired by the smart bracelet 100 into the trained convolutional neural network model, and the model can make a judgment on the quality of the input sleep monitoring data.

In other embodiments of the present application, the smart bracelet 100 may also judge the data quality of the smart bracelet based on other data, such as blood pressure data. Wherein, the specific judging method may be to replace the heart rate data in the PPG data described above with blood pressure data, and then the specific judging method is similar to the above judging method, and will not be repeated here.

In some embodiments of the present application, the smart bracelet 100 can also simultaneously judge the monitoring quality of the sleep monitoring data of the smart bracelet according to the combination of the above-mentioned multiple sleep monitoring data. For example, each sleep monitoring data can be weighted, and the specific way of assigning the value can be based on how each sleep monitoring data reflects the user's physical health. For example, the heart rate peak interval and heart rate peak amplitude are obviously more reflective of the user's physical condition than the ACC data fluctuation interval and ACC data fluctuation amplitude, so the heart rate peak interval and heart rate peak amplitude are more important than the ACC data fluctuation interval and ACC data fluctuation interval. The weight of data volatility is high.

以及平均心率波峰幅值

以及ACC运动数据的平均波动幅值

以及平均波动间隔

并且同时智能手环100根据监测过的历史睡眠监测数据来预先设置用户智能手环的可信度阈值P，然后基于预先设置的用户各个睡眠监测数据的权重根据公式(二)计算智能手环100的睡眠监测数据的监测质量的可信度，For example, in a specific implementation process, the weight of A heart rate peak interval and heart rate peak amplitude is 80%, and the weight of ACC data fluctuation interval and ACC data fluctuation amplitude is 20%. The smart bracelet 100 monitors the user's heart rate peak intervals t1, t2, t3...tn and heart rate peak amplitudes a1, a2, a3...an in the time period T, and the user's ACC in the time period T Motion data fluctuation amplitude b1, b2, b3···bn and ACC fluctuation interval c1, c2, c3···c4, and calculate the average heart rate peak interval of the user within the time period T

and average heart rate peak amplitude

And the average fluctuation amplitude of ACC sports data

and the average fluctuation interval

And at the same time, the smart bracelet 100 presets the credibility threshold P of the user's smart bracelet according to the monitored historical sleep monitoring data, and then calculates the smart bracelet 100 according to the formula (2) based on the preset weight of each sleep monitoring data of the user. The reliability of the monitoring quality of the sleep monitoring data,

p=α×(A+T)+β×(B+C) (two)

Among them, p represents credibility, α represents weight, β weight, A represents heart rate peak amplitude, T represents heart rate peak interval, B represents ACC data fluctuation amplitude, C represents ACC data fluctuation interval

Then compare p with the credibility threshold P. When the credibility of the user's smart bracelet is greater than the credibility threshold P, it is considered that the monitoring quality of the sleep monitoring data of the smart bracelet is normal; otherwise, the sleep monitoring data of the smart bracelet is considered normal. The monitoring quality of the monitoring data is abnormal.

Determine the cause of abnormal monitoring quality of the sleep monitoring number of the smart bracelet

Determine the cause of the abnormal monitoring quality of the sleep monitoring data of the smart bracelet, the specific process is as follows:

A. Determine whether the abnormal quality of sleep monitoring data is caused by the user's large movement range or high movement frequency during sleep

Usually the user often has unconscious movements during sleep, and these movements can be reflected by the data of the ACC sensor or the gyroscope sensor of the smart bracelet. For example, when the user's movement range is large, the fluctuation of ACC data will become stronger, which is specifically reflected in the fluctuation interval and fluctuation amplitude of ACC data will become larger. When the user's movement range is small, the fluctuation of the ACC data will become moderate, and the corresponding fluctuation interval and fluctuation amplitude of the ACC data will also become smaller.

以及平均波动间隔

In some embodiments, when it is judged that the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal, the smart bracelet 100 can be preset according to the monitored historical ACC data fluctuation amplitude and ACC data fluctuation interval data of the user. ACC data fluctuation amplitude threshold A3 and ACC data fluctuation interval threshold T3, at the same time, the smart bracelet 100 monitors the user's ACC data fluctuation amplitude b1, b2, b3...bn and ACC fluctuation interval c1, c2 within the time period T , c3···c4, and calculate the average fluctuation amplitude of ACC data according to formula (1)

and the average fluctuation interval

Calculate the fluctuation amplitude variance D and fluctuation interval variance E of the user's ACC data in the time period T according to formula (3),

Among them, ^δ2 represents the variance of the data to be calculated, n represents the number of data, μ is the average value of the data to be calculated, and X is the real-time data monitored by the smart bracelet. In the calculation, the ACC data fluctuation amplitude can be substituted as μ, and the obtained δ ² is the ACC data fluctuation amplitude variance D, and the ACC data fluctuation interval is substituted as μ, and the obtained δ ² is the ACC data fluctuation interval variance e.

At the same time, the smart bracelet 100 sets the ACC data fluctuation amplitude threshold A3 and the ACC exercise data fluctuation interval threshold T3 according to the monitored user's historical ACC data fluctuation amplitude and ACC data fluctuation interval. Compare the user's ACC data fluctuation amplitude variance D and ACC data fluctuation interval variance E in the time period T with the ACC data fluctuation amplitude threshold A3 and ACC data fluctuation interval threshold T3 respectively, if the user's ACC movement in the time period T If the fluctuation amplitude variance D of the data is greater than A3 and the fluctuation interval variance E is greater than T3, then the current period of time is considered to be a large range of user actions.

Further, statistical calculations are performed in each time period T of the user's sleep stage according to the above-mentioned method, and the proportion of the time period with large user action ranges relative to the user's total sleep time is calculated. If the ratio of the two is higher than the set Threshold V1, it is considered that the user's data action frequency is high that night. For example, the smart bracelet 100 can count the actions of the user during the sleep time period (taking 8 hours as an example) at night.

Specifically, the smart bracelet 100 can count the fluctuation amplitude ( d1, d2, d3...dn), (dn+1, dn+2, dn+3...d2n), (d2n+1, d2n+2, d2n+3...d3n), (d3n+ 1, d3n+2, d3n+3···d4n) and ACC motion data fluctuation interval (e1, e2, e3···en), (en+1, en+2, en+3···e2n) , (e2n+1, e2n+2, e2n+3...e3n), (e3n+1, e3n+2, e3n+3...e4n).

Then according to the formulas (1) and (2), calculate the user's ACC data fluctuation amplitude variance (D1, D2, D3, D4) and fluctuation interval variance (E1, E2, E3, E4) in the above time period, assuming that the fluctuation is satisfied The time periods when the amplitude variance is greater than A3 and the fluctuation interval variance is greater than T3 are 00:00-01:00, 02:00-03:00, 04:00-05:00, that is, data (D2, D3, D4) and (E2 , E3, E4) Then it is considered that the user's motion range is large during the time period of 00:00-01:00, 02:00-03:00, and 04:00-05:00. In other words, the time period for the user's large motion range is 3 hours, then the proportion of the period of time with large user movements relative to the user's total sleep time is (3/8), and then compare the specific calculation results with the threshold V1 to determine the user's movement frequency during sleep time . If the calculation result is greater than V1, it means that the user's action frequency is high, otherwise it is considered that the user's action frequency is low.

In some embodiments of the present application, the smart bracelet 100 can also judge whether the user has a continuous time period with a large movement range through the above-mentioned method for judging the user's movement range. If the user's movement range is always large in a certain continuous time period, It can be judged that the user has a long night awake at night. And because being awake for a long time at night will also affect the accuracy of sleep apnea detection, so the sleep monitoring data of the corresponding time period will be abnormally marked or prompted.

B. Determine whether the abnormality of the monitoring data is due to the improper fastening of the smart bracelet worn by the user

Generally, the monitoring quality of the sleep monitoring data of the smart bracelet is also affected by the way the user wears the smart bracelet. When the user wears the bracelet too loosely or too tightly, the monitoring quality of the sleep monitoring data of the smart bracelet will also be abnormal. To judge whether the user is wearing the smart bracelet too loose or too tight, it can be judged specifically through the acceleration sensor. The ACC sensor can identify the screen orientation of the smart bracelet. When the screen orientation of the smart bracelet is in different directions, and the monitoring quality of the sleep monitoring data of the smart bracelet is abnormal, it can be considered that the user is wearing the bracelet too tightly; When the screen orientation of the smart bracelet is in different directions, the monitoring quality of the sleep monitoring data of the smart bracelet is normal or abnormal, that is, when the monitoring quality is inconsistent, it can be considered that the user is wearing the bracelet too loosely.

In some embodiments of the present application, the smart bracelet 100 is provided with an acceleration sensor 109 , and generally the Z axis is perpendicular to the screen (touch screen) of the smart bracelet 100 . The smart bracelet 100 can obtain ACC data during the user's sleep period through the acceleration sensor 109, and can identify the screen orientation of the smart bracelet worn by the user by analyzing the ACC data fluctuations. Generally, the screen of the smart bracelet can be: Up, screen down, and screen on its side.

For example, if the smart bracelet acceleration sensor 109 recognizes that the value of the Z axis is larger and greater than 0, and the value of the X/Y axis is close to 0, it can be considered that the screen of the smart bracelet in this time period is facing up; if the smart bracelet The acceleration sensor 109 recognizes that the value of the Z axis is less than 0, and the value of the X/Y axis is close to 0, then it can be considered that the screen of the smart bracelet in this time period is facing down; if the smart bracelet acceleration sensor 109 recognizes that the value of the Y axis is 0, and the value of the X/Z axis is close to 0, it can be considered that the screen of the smart bracelet in this time period is placed sideways.

In some embodiments of the present application, the direction of each axis of the acceleration sensor 109 in the smart bracelet and the position of the smart bracelet are not limited to the above-mentioned situation. If the relative position changes, the above identification rules should also change accordingly. However, as long as the relative positions of the directions of the axes of the acceleration sensor 109 and the screen of the smart bracelet are determined, the rules for identifying the direction of the screen are also determined, and will not be repeated here.

For example, if the monitoring quality of the sleep monitoring data obtained by the smart bracelet 100 under different screen placement states is normal and the characteristics of the sleep monitoring data are consistent, it is considered that the user is wearing it normally; If the monitoring quality of the sleep monitoring data obtained under the following circumstances is abnormal, it can be considered that the user wears the smart bracelet too tightly; According to the characteristics of the monitoring data, it can be considered that the user wears the smart bracelet too loosely. Wherein, the feature performance of the sleep monitoring data is consistent means that similar or identical features of the sleep monitoring data may periodically appear in different states. For example, when the screen of the smart bracelet is facing up and the screen of the smart bracelet is facing down, the heart rate will have periodic peaks, and the amplitudes of the peaks in the two states are similar or the same, and the peak intervals are also similar or the same.

In some other embodiments of the present application, the smart bracelet 100 can also measure the position close to the human body on the screen of the smart bracelet, and add a pressure sensor 106 to determine the tightness of the smart bracelet 100 worn by the user. For example, the pressure sensor 106 is used to obtain the pressure value of the user's sleep time period on the smart bracelet. If the pressure value is always high, it can be considered that the user's smart bracelet is worn too tightly; if the pressure value is always moderate, Then it can be considered that the user's smart bracelet is worn with a moderate degree of tightness; if the pressure value is in a fluctuating state, it can be considered that the user's smart bracelet is worn too loosely. Specifically, the smart bracelet 100 can calculate the average value (or variance, etc.) of the data of the pressure sensor 106 in the normal wearing time period of the user as the reference data, and then use the user's sleep time period pressure sensor 106 acquired by the smart bracelet 100 If the ratio of the real-time pressure value of the user's sleep time pressure sensor 106 to the reference data is (0-0.4), it can be considered that the user's smart bracelet is too loose; If the ratio of the real-time pressure value of the sensor 106 to the reference data is at (0.4-0.6), it can be considered that the user's smart bracelet is moderately worn; Then it can be considered that the user's smart bracelet is worn too tightly.

C. Determine whether the abnormality of the monitoring data is caused by the user's smart bracelet being pressed

In some embodiments, it may be further identified whether the user's smart bracelet is pressed according to the wearing situation of the user's smart bracelet identified in step B. In a specific implementation, if the user's smart bracelet is worn with a moderate degree of tightness and the user's movement range is small, the monitoring quality of the sleep monitoring data of the smart bracelet is still abnormal, then it can be considered that the smart bracelet is pressed. For example, if the user wears the smart bracelet to a moderate degree during the sleep period, and the user's movement range is small, but the monitoring quality of the user's sleep monitoring data obtained during this period is still abnormal, then the user's smart bracelet is considered to be abnormal. The ring is pressed down. The specific method for judging the looseness of the smart bracelet and the monitoring quality of the sleep monitoring data of the smart bracelet is the same as the above-mentioned specific judgment method, and will not be repeated here.

Through the judgment of the above steps, it is possible to detect the cause of abnormal monitoring quality of the sleep monitoring data of the user's smart bracelet, and then mark the abnormality of the user's sleep monitoring in the corresponding time period.

Provide corresponding prompts to the user based on the determined cause of abnormal monitoring quality of sleep monitoring data

As shown in FIG. 3 b , after determining the cause of the abnormal monitoring quality of the sleep monitoring data, the prompt information for prompting the user to improve the monitoring quality of the sleep monitoring data of the smart bracelet is determined and prompted to the user. Wherein, the specific prompt can be performed through the smart bracelet 100 or through the mobile phone 200 .

In one embodiment of the present application, the mobile phone 200 is used to provide targeted prompts to the user, and the specific method is as follows:

The mobile phone 200 and the smart bracelet 100 perform data synchronization. When the mobile phone 200 recognizes that the reason for the abnormal monitoring quality of the sleep monitoring data of the smart bracelet is "the user's movement range is large or the frequency is high", the mobile phone 200 will interact with the user through the main interface 210. Recommend suggestions and services for a safe sleep to the user. Specifically, as shown in Figure 4a, if the user is using a mobile phone, a pop-up dialog box can be directly popped up to remind the user that the movement range is large at this time, and the user is pushed "Sleep Safe Sleep". Tips" 211, the user can operate by selecting "exit" 212 or "remind later" 213; if the user is still in a sleep state or other state of not using the mobile phone at this time, as shown in Figure 4b, you can click on The lock screen interface 220 of the mobile phone records and prompts, and displays "Tips for Safe Sleep" (specifically, some health exercises videos or popular science posts on sleeping postures, etc.) 211, and the same user can also select "Display" 221 and "Delete" 222 Relevant operations are convenient for the user to see relevant suggestions when using the mobile phone without disturbing the user's sleep or work. At the same time, the mobile phone 200 can also selectively set the time period for the smart bracelet 100 to obtain the user's sleep monitoring data according to the user's habit of wearing the smart bracelet 100. The way of the instruction makes the smart bracelet 100 not acquire the sleep monitoring data of the user in this time period, so as to improve the monitoring quality of the sleep monitoring data of the smart bracelet 100 .

And when it is identified that the cause of the abnormal monitoring quality of the sleep monitoring data of the smart bracelet is "the user's smart bracelet is too loose or too tight", the mobile phone 200 recommends suggestions and services for a safe sleep to the user through the user interface 210, specifically Yes, as shown in Figure 5a, if the user is using a mobile phone, a pop-up dialog box can be displayed to remind the user that the smart wristband is not suitable for wearing at this time, and the user can be pushed to guide articles or videos on how to wear the device correctly, such as " Smart Bracelet Wearing Mode Guidance" (215), the user can operate by selecting "exit" (212) or "remind later" (213); As shown in Figure 5b, a reminder can be recorded on the lock screen interface of the mobile phone, and the "smart bracelet wearing method guidance" (215) (for example, the smart bracelet user manual or the smart bracelet wearing video guidance link, etc.) is displayed, and the same The user can also select "display" (221) and "delete" (222) to perform related operations, so that the user can see relevant suggestions when using the mobile phone and will not disturb the user's sleep or work. At the same time, the mobile phone 200 can also selectively set the time period for the smart bracelet 100 to obtain the user's sleep monitoring data according to the user's habit of wearing the smart bracelet 100. By sending instructions, the smart bracelet 100 does not acquire the sleep monitoring data of the user in this time period, thereby improving the monitoring quality of the sleep monitoring data of the smart bracelet 100 .

Similarly, when it is identified that the cause of the abnormal monitoring quality of the sleep monitoring data of the smart bracelet is "the smart bracelet is pressed", the mobile phone 200 recommends suggestions and services for a safe sleep to the user through the user interface 210, specifically , as shown in Figure 6a, if the user is using a mobile phone, the user can be reminded that the smart bracelet is pressed at this time by directly popping up a dialog box, and the user is advised to wear the device on the opposite hand in the main lateral position Or adjust the sleeping position, such as displaying "sleep position guidance" (216) (for example, popular science posts about healthy sleep, etc.), the user can operate by selecting "exit" (212) or "remind later" (213) ; If the user is still in sleep state or other state of not using the mobile phone at this time, as shown in Figure 6b, then it can be prompted in the lock screen interface record of the mobile phone, displaying "sleep posture guidance" (216), and the same user can also choose "Display" (221) and "delete" (222) are used to perform relevant operations, so that the user can see relevant suggestions when using the mobile phone and will not disturb the user's sleep or work. At the same time, the mobile phone 200 can also selectively set the time period for the smart bracelet 100 to obtain the user's sleep monitoring data according to the user's habit of wearing the smart bracelet 100. For example, during the time period when the smart bracelet is pressed, the mobile phone 200 can By sending instructions, the smart bracelet 100 does not acquire the sleep monitoring data of the user in this time period, thereby improving the monitoring quality of the sleep monitoring data of the smart bracelet 100 .

In addition, as mentioned above, in some embodiments of the present application, the monitoring and analysis of the corresponding sleep monitoring data can also be carried out on the mobile phone 200 side, and then the mobile phone 200 can directly use the sleep monitoring data of the smart bracelet 100 according to the specific results. The reason for abnormal monitoring quality is to push relevant suggestions to users in a targeted manner, as shown in Figure 7:

700: The mobile phone 200 establishes a communication connection with the smart bracelet 100 .

702: Send the user's historical sleep monitoring data and the sleep monitoring data acquired within the T time period. Wherein, the historical sleep monitoring data is used to set the relevant threshold, and the time period T represents the time period currently monitored by the smart bracelet 100 .

704: Judging the monitoring quality of the sleep monitoring data acquired in the T time period. The specific judgment method is the same as the above judgment method on the side of the smart bracelet 100 , and will not be repeated here.

706: If it is determined that the monitoring quality of the sleep monitoring data of the smart bracelet is abnormal, further determine the cause of the abnormal monitoring quality of the sleep monitoring data of the smart bracelet. The specific judgment method is the same as the above judgment method on the side of the smart bracelet 100 , and will not be repeated here.

708: According to the specific cause of abnormal monitoring quality, push relevant prompt information to the user in a targeted manner. The specific pushing method is the same as the above-mentioned pushing method on the mobile phone 200, and will not be repeated here.

FIG. 8 shows a structural block diagram of an electronic device 800 capable of implementing the functions of the electronic device 200 shown in FIG. 1 according to an embodiment of the present invention. Specifically, as shown in FIG. 8 , the electronic device 800 may include a processor 810, an external memory interface 820, an internal memory 821, a universal serial bus (universal serial bus, USB) interface 830, a charging management module 840, and a power management module 841 , battery 842, antenna 1, antenna 2, mobile communication module 850, wireless communication module 860, audio module 870, speaker 870A, receiver 870B, microphone 870C, earphone jack 870D, sensor module 880, button 890, motor 898, indicator 892 , a camera 893, a display screen 894, and a subscriber identification module (subscriber identification module, SIM) card interface 895, etc. The sensor module 880 may include a pressure sensor 880A, a gyroscope sensor 880B, an air pressure sensor 880C, a magnetic sensor 880D, an acceleration sensor 880E, a distance sensor 880F, a proximity light sensor 880G, a fingerprint sensor 880H, a temperature sensor 880J, a touch sensor 880K, and ambient light Sensor 880L, bone conduction sensor 880M, etc.

It can be understood that, the structure shown in the embodiment of the present invention does not constitute a specific limitation on the electronic device 800 . In other embodiments of the present application, the electronic device 800 may include more or fewer components than shown in the figure, or combine certain components, or separate certain components, or arrange different components. The illustrated components can be realized in hardware, software or a combination of software and hardware.

The processor 810 may include one or more processing units, for example: the processor 810 may include an application processor (application processor, AP), a modem processor, a graphics processing unit (graphics processing unit, GPU), an image signal processor ( image signal processor (ISP), controller, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural network processor (neural-network processing unit, NPU), etc. Wherein, different processing units may be independent devices, or may be integrated in one or more processors. For example, the processor 810 can calculate the reliability of the monitoring quality of the sleep monitoring data of the smart bracelet 100, judge the monitoring quality of the sleep monitoring data of the smart bracelet 100, and judge the quality of the sleep monitoring data of the smart bracelet 100. Monitor the cause of quality anomalies.

The controller can generate an operation control signal according to the instruction opcode and timing signal, and complete the control of fetching and executing the instruction.

A memory may also be provided in the processor 810 for storing instructions and data. In some embodiments, the memory in processor 810 is a cache memory. The memory may hold instructions or data that the processor 810 has just used or recycled. If the processor 810 needs to use the instruction or data again, it can be directly recalled from the memory. Repeated access is avoided, and the waiting time of the processor 810 is reduced, thereby improving the efficiency of the system. At the same time, the processor 810 may also store the user's sleep monitoring data and historical sleep monitoring data received by the electronic device 200 and sent by the bracelet 100 .

In some embodiments, processor 810 may include one or more interfaces. The interface may include an integrated circuit (inter-integrated circuit, 12C) interface, an integrated circuit built-in audio (inter-integrated circuitsound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous receiver (universal asynchronous receiver) /transmitter, UART) interface, mobile industry processor interface (mobile industry processor interface, MIPI), general-purpose input and output (general-purpose input/output, GPIO) interface, subscriber identity module (subscriber identity module, SIM) interface, and/or A universal serial bus (universal serial bus, USB) interface, etc.

Micro USB interface, USB Type C interface, etc. The USB interface 830 can be used to connect a charger to charge the electronic device 800, and can also be used to transmit data between the electronic device 800 and peripheral devices. It can also be used to connect headphones and play audio through them. This interface can also be used to connect other electronic devices, such as AR devices.

It can be understood that the interface connection relationship between the modules shown in the embodiment of the present invention is only a schematic illustration, and does not constitute a structural limitation of the electronic device 800 . In other embodiments of the present application, the electronic device 800 may also adopt different interface connection manners in the foregoing embodiments, or a combination of multiple interface connection manners.

The charging management module 840 is configured to receive charging input from the charger. The power management module 848 is used to connect the battery 842 , the charging management module 840 and the processor 880 . The power management module 848 receives the input from the battery 842 and/or the charging management module 840, and supplies power to the processor 880, the internal memory 821, the display screen 894, the camera 893, and the wireless communication module 860, etc. The power management module 848 can also be used to monitor parameters such as battery capacity, battery cycle times, and battery health status (leakage, impedance). In some other embodiments, the power management module 841 can also be set in the processor 880 . In some other embodiments, the power management module 841 and the charging management module 840 may also be set in the same device.

The wireless communication function of the electronic device 800 can be realized by the antenna 1, the antenna 2, the mobile communication module 850, the wireless communication module 860, the modem processor and the baseband processor.

Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 800 may be used to cover single or multiple communication frequency bands. Different antennas can also be multiplexed to improve the utilization of the antennas. For example: Antenna 1 can be multiplexed as a diversity antenna of a wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 850 can provide wireless communication solutions including 2G/3G/4G/5G applied on the electronic device 800 . The wireless communication module 860 can provide wireless local area networks (wireless local area networks, WLAN) (such as wireless fidelity (Wireless Fidelity, Wi-Fi) network), bluetooth (bluetooth, BT), global navigation satellite, etc. Wireless communication solutions such as global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared (IR). The wireless communication module 860 may be one or more devices integrating at least one communication processing module. The wireless communication module 860 receives electromagnetic waves via the antenna 2 , frequency-modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 810 . The wireless communication module 860 can also receive the signal to be sent from the processor 810, frequency-modulate it, amplify it, and convert it into electromagnetic waves through the antenna 2 to radiate out.

In some embodiments, the electronic device 800 can communicate with the smart bracelet 100 through the mobile communication module 850 or the wireless communication module 860 .

In some embodiments, the antenna 1 of the electronic device 800 is coupled to the mobile communication module 850, and the antenna 2 is coupled to the wireless communication module 860, so that the electronic device 800 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 (general packet radio service, GPRS), code division multiple access (codedivision multiple access, CDMA), wideband code 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, etc. The GNSS may include a global positioning system (global positioning system, GPS), a global navigation satellite system (global navigation satellite system, GLONASS), a Beidou satellite navigation system (beidounavigation satellite system, BDS), a quasi-zenith satellite system (quasi- zenith satellite system (QZSS) and/or satellite based augmentation systems (SBAS).

The electronic device 800 implements a display function through a GPU, a display screen 894, an application processor, and the like. The GPU is a microprocessor for image processing, and is connected to the display screen 894 and the application processor. GPUs are used to perform mathematical and geometric calculations for graphics rendering. Processor 810 may include one or more GPUs that execute program instructions to generate or change display information.

The electronic device 800 can realize the shooting function through an ISP, a camera 893 , a video codec, a GPU, a display screen 894 , and an application processor. In some embodiments of the present application, the display screen 894 is used to realize human-computer interaction with the user.

The external memory interface 820 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 800 . The external memory card communicates with the processor 810 through the external memory interface 820 to realize the data storage function. Such as saving music, video and other files in the external memory card.

Internal memory 821 may be used to store computer-executable program code, which includes instructions. The internal memory 821 may include an area for storing programs and an area for storing data. Wherein, the stored program area can store an operating system, at least one application program required by a function (such as a sound playing function, an image playing function, etc.) and the like. The storage data area can store data created during the use of the electronic device 800 (such as audio data, phonebook, etc.) and the like. In addition, the internal memory 821 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, universal flash storage (universal flash storage, UFS) and the like. The processor 810 executes various functional applications and data processing of the electronic device 800 by executing instructions stored in the internal memory 821 and/or instructions stored in a memory provided in the processor.

The electronic device 800 may implement an audio function through an audio module 870 , a speaker 870A, a receiver 870B, a microphone 870C, an earphone interface 870D, and an application processor. Such as music playback, recording, etc.

The keys 890 include a power key, a volume key and the like. Key 890 may be a mechanical key. It can also be a touch button. The electronic device 800 may receive key input and generate key signal input related to user settings and function control of the electronic device 800 .

The motor 891 can generate a vibrating prompt. The motor 891 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback. For example, touch operations applied to different applications (such as taking pictures, playing audio, etc.) may correspond to different vibration feedback effects. The motor 891 can also correspond to different vibration feedback effects for touch operations on different areas of the display screen 894 . Different application scenarios (for example: time reminder, receiving information, alarm clock, games, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect can also support customization.

The indicator 892 can be an indicator light, and can be used to indicate charging status, power change, and can also be used to indicate messages, missed calls, notifications, and the like.

The SIM card interface 895 is used for connecting a SIM card.

Referring now to FIG. 9 , the software system of the electronic device 800 may adopt a layered architecture, an event-driven architecture, a micro-kernel architecture, a micro-service architecture, or a cloud architecture. In the embodiment of the present invention, the Android system with layered architecture is taken as an example to illustrate the software structure of the terminal device. FIG. 9 is a block diagram of a software structure of a terminal device according to an embodiment of the present invention.

The layered architecture divides the software into several layers, and each layer has a clear role and division of labor. Layers communicate through software interfaces. In some embodiments, the Android system is divided into four layers, which are, from top to bottom, the application program layer, the application program framework layer, the Android runtime (Android runtime) and the system library, and the kernel layer.

The application layer can consist of a series of application packages.

As shown in FIG. 9, the application package may include applications such as phone, camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, and short message.

The application framework layer provides an application programming interface (application programming interface, API) and a programming framework for applications in the application layer. The application framework layer includes some predefined functions.

As shown in Figure 9, the application framework layer can include window manager, content provider, view system, phone manager, resource manager, notification manager, etc.

A window manager is used to manage window programs. The window manager can get the size of the display screen, determine whether there is a status bar, lock the screen, capture the screen, etc.

Content providers are used to store and retrieve data and make it accessible to applications. Said data may include video, images, audio, calls made and received, browsing history and bookmarks, phonebook, etc.

The view system includes visual controls, such as controls for displaying text, controls for displaying pictures, and so on. The view system can be used to build applications. A display interface can consist of one or more views. For example, a display interface including a text message notification icon may include a view for displaying text and a view for displaying pictures.

The telephony manager is used to provide the communication function of the terminal equipment. For example, the management of call status (including connected, hung up, etc.).

The resource manager provides various resources for the application, such as localized strings, icons, pictures, layout files, video files, and so on.

The notification manager enables the application to display notification information in the status bar, which can be used to convey notification-type messages, and can automatically disappear after a short stay without user interaction. For example, the notification manager is used to notify the download completion, message reminder, etc. The notification manager can also be a notification that appears on the top status bar of the system in the form of a chart or scroll bar text, such as a notification of an application running in the background, or a notification that appears on the screen in the form of a dialog window. For example, a text message is displayed in the status bar, a prompt sound is issued, the terminal device vibrates, and the indicator light flashes, etc.

Android Runtime includes core library and virtual machine. The Android runtime is responsible for the scheduling and management of the Android system.

The core library consists of two parts: one part is the function function that the java language needs to call, and the other part is the core library of Android.

The application layer and the application framework layer run in virtual machines. The virtual machine executes the java files of the application program layer and the application program framework layer as binary files. The virtual machine is used to perform functions such as object life cycle management, stack management, thread management, security and exception management, and garbage collection.

A system library can include multiple function modules. For example: surface manager (surface manager), media library (Media Libraries), 3D graphics processing library (eg: OpenGL ES), 2D graphics engine (eg: SGL), etc.

The surface manager is used to manage the display subsystem and provides the fusion of 2D and 3D layers for multiple applications.

The media library supports playback and recording of various commonly used audio and video formats, as well as still image files, etc. The media library can support a variety of audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.

The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing, etc.

2D graphics engine is a drawing engine for 2D drawing.

The kernel layer is the layer between hardware and software. The kernel layer includes at least a display driver, a camera driver, an audio driver, and a sensor driver.

Reference to "one embodiment" or "an embodiment" in the specification means that a specific feature, structure or characteristic described in connection with the embodiment is included in at least one exemplary implementation or technique according to the present disclosure. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment.

The processes and displays presented herein are not inherently related to any specific computer or other device. Various general-purpose systems may also be used with programs in accordance with the teachings herein, or it may prove convenient to construct a more specialized apparatus to perform one or more method steps. The architecture for a variety of these systems is discussed in the description below. In addition, any specific programming language sufficient to implement the techniques and embodiments of this disclosure may be used. Various programming languages can be used to implement the present disclosure, as discussed herein.

Additionally, the language used in this specification has been chosen primarily for readability and instructional purposes and may not have been chosen to delineate or limit the subject matter disclosed. Accordingly, this disclosure is intended to illustrate, not to limit, the scope of the concepts discussed herein.

Claims (16)

1. A usage monitoring method of a wearable electronic device, characterized in that, comprising: Obtain sleep monitoring data of the wearable electronic device during the user's sleep; In the case that there is sleep monitoring data with abnormal monitoring quality in the sleep monitoring data, determining the reason for the existence of the sleep monitoring data with abnormal monitoring quality includes: after judging that the user is wearing the wearable electronic device during sleep If the degree of tightness meets the measurement requirements and the range of motion or frequency of motion when the user wears the wearable electronic device during sleep does not affect the monitoring quality, it is determined that the cause is that the wearable electronic device exists during the user's sleep. being held down; Based on the reason, determine prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep. 2. The method according to claim 1, wherein the reasons for the abnormal sleep monitoring data of monitoring quality include at least one of the following: The degree of tightness with which the user wears the wearable electronic device during sleep does not meet the measurement requirements; The range of motion or the frequency of motion when the user wears the wearable electronic device during sleep affects the monitoring quality; The wearable electronic device may be pressed while the user is sleeping. 3. The method according to claim 2, wherein, based on the reason, determining the prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep includes at least one of the following item: When it is determined that the reason is that the tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirements, it is determined that the prompt information for improving the monitoring quality is prompt information about wearing the wearable electronic device correctly ; When it is determined that the reason is that the range of motion or the frequency of motion of the user wearing the wearable electronic device during sleep affects the monitoring quality, determine that the prompt information for improving the monitoring quality is prompt information about stable sleep; When it is determined that the reason is that the wearable electronic device is pressed while the user is sleeping, it is determined that the prompt information for improving the monitoring quality is the suggested prompt information about the wearing position. 4. The method according to claim 2 or 3, wherein the reason for determining that there is abnormal sleep monitoring data of the monitoring quality comprises: When it is determined that the monitoring quality of the sleep monitoring data of the screen of the wearable electronic device worn by the user is normal and abnormal at the same time under different orientations, it is determined that the cause is that the user wears the wearable electronic device during sleep. The degree of tightness of the wearable electronic device is looser than the degree of tightness that meets the measurement requirements; When it is judged that the monitoring quality of the sleep monitoring data of the screen of the wearable electronic device worn by the user is only abnormal in different orientations, it is determined that the cause is that the user wears the wearable electronic device during sleep. The degree of tightness of the equipment is tighter than the degree of tightness that meets the measurement requirements. 5. The method according to claim 2 or 3, wherein the wearable electronic device comprises a pressure sensor and a display screen, and the pressure sensor is located inside the display screen of the wearable electronic device; and The reasons for determining that there is abnormal sleep monitoring data of the monitoring quality include: According to the pressure monitoring data of the pressure sensor, it is judged whether the reason for the sleep monitoring data with abnormal monitoring quality is that the tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirements. 6. The method according to claim 2 or 3, wherein the wearable electronic device comprises an acceleration sensor, and The reasons for determining that there is abnormal sleep monitoring data of the monitoring quality include: According to the fluctuation interval and fluctuation amplitude of the measurement data of the acceleration sensor in the acquired sleep monitoring data, it is judged whether the reason is that the motion range or motion frequency of the user wearing the wearable electronic device during sleep affects the Monitor quality. 7. The method according to any one of claims 1 to 6, further comprising: According to the fluctuation of the photoplethysmography sensor data and/or the fluctuation of the acceleration sensor measurement data in the acquired sleep monitoring data, it is judged whether there is sleep monitoring data with abnormal monitoring quality in the sleep monitoring data. 8. The method of claim 1, further comprising: Displaying the determined prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep. 9. The method according to claim 1, wherein the acquiring the sleep monitoring data of the wearable electronic device during the sleep of the user comprises: The sleep monitoring data is received from the wearable electronic device. 10. The method of claim 1, further comprising: Sending out the determined prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep. 11. A usage monitoring method of a wearable electronic device, comprising: The wearable electronic device sends the sleep monitoring data of the wearable electronic device during the user's sleep, wherein there is sleep monitoring data with abnormal monitoring quality in the sleep monitoring data, and the sleep monitoring data with abnormal monitoring quality is used for Determining the reason for the sleep monitoring data with abnormal monitoring quality includes: when it is judged that the tightness of the wearable electronic device worn by the user during sleep meets the measurement requirements and the wearable electronic device is worn by the user during sleep If the range of motion or frequency of motion does not affect the monitoring quality, it is determined that the cause is that the wearable electronic device is pressed during the user's sleep; The wearable electronic device receives prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep. 12. The method according to claim 11, the prompt information received by the wearable electronic device for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep includes at least one of the following: Prompt information about wearing the wearable electronic device correctly; Tips about sound sleep; Tips for advice on where to wear. 13. A readable medium of an electronic device, wherein instructions are stored on the readable medium, and when the instruction is executed on the electronic device, the electronic device executes the electronic device according to any one of claims 1 to 12. Methods. 14. An electronic device comprising: a memory for storing instructions to be executed by one or more processors of the electronic device, and a processor which is one of the processors of the electronic device for performing any of claims 1 to 12 any one of the methods described. 15. An electronic device comprising: a memory, a processor, a photoplethysmography sensor, and an acceleration sensor; The photoplethysmography sensor is used to acquire photoplethysmography sensor data of the user of the electronic device during sleep; The acceleration sensor is used to obtain acceleration sensor monitoring data of the user of the electronic device during sleep; said memory for storing instructions executed by one or more of said processors of an electronic device; The processor is one of the processors of the electronic device, configured to execute the method according to any one of claims 1-12. 16. An electronic device, comprising: a memory, a processor, a display screen, a photoplethysmography sensor, a pressure sensor, and an acceleration sensor; the photoplethysmography sensor for acquiring photoplethysmography data of a user of the electronic device during sleep; The acceleration sensor is used to obtain acceleration sensor monitoring data of the user of the electronic device during sleep; The display screen is used to display prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep; The pressure sensor is located on the inner side of the display screen, and is used to detect the degree of tightness of the user wearing the electronic device; said memory for storing instructions executed by one or more of said processors of an electronic device; The processor is one of the processors of the electronic device, configured to execute the method according to any one of claims 1-12.

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