CN113545745B

CN113545745B - Usage monitoring method and medium for wearable electronic device and electronic device thereof

Info

Publication number: CN113545745B
Application number: CN202010330121.8A
Authority: CN
Inventors: 李靖; 张慧; 许德省; 周林峰
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2020-04-23
Filing date: 2020-04-23
Publication date: 2023-03-10
Anticipated expiration: 2040-04-23
Also published as: WO2021213337A1; CN113545745A

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 and medium for wearable electronic device and electronic device thereof

Technical Field

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

Background

Sleep apnea is a common chronic disease of sleep disorders, seen worldwide. The world health organization reports that 1-10% of the world population is affected by sleep apnea, with about 5000 million sleep apnea patients in our country. Sleep apnea is characterized in that a user can repeatedly generate respiratory obstruction in sleep to cause hypoxia and repeated arousal of an organism, the spirit and health of people are seriously affected, and due to lack of effective sleep, people can become sleepy, sleepy in the daytime and have low memory, so that the health is harmed, and the probability of accidents of industrial injuries such as traffic accidents, construction sites and the like is indirectly increased. If the traditional Chinese medicine is not treated for a long time, the diseases such as diabetes, hypertension, cardiovascular and cerebrovascular diseases, stroke, neurasthenia and the like can be caused, and even sudden death at night can occur.

At present, the technology for detecting sleep apnea by wearable electronic equipment is less, and for the condition that the signal quality (or the monitoring quality of the wearable electronic equipment) is not good, the adopted method generally comprises the following steps: and discarding the whole piece of data or filtering out the sleep monitoring data with poor signals, and calculating by using the sleep monitoring data with better signal quality.

Disclosure of Invention

The embodiment of the application provides a use monitoring method and medium of wearable electronic equipment and the wearable electronic equipment. 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. The content of the present application will be specifically described below.

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

acquiring sleep monitoring data of the wearable electronic equipment during the sleep of a user; determining the reason of the sleep monitoring data with abnormal monitoring quality under the condition that the sleep monitoring data with abnormal monitoring quality exists in the sleep monitoring data; determining prompt information for prompting a user to improve monitoring quality of the wearable electronic device during sleep of the user based on reasons affecting the monitoring quality of the sleep monitoring data.

Namely, the wearable electronic equipment can further judge the reason of the abnormal monitoring quality of the sleep monitoring data when the monitoring quality of the sleep monitoring data of the monitored user during the sleep period is abnormal. And then further determining prompt information for prompting the user according to the reason for judging the influence on the sleep monitoring data quality, so that the monitoring quality of the wearable electronic equipment and the sleep quality of the user are improved.

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

the degree of tightness of the wearable electronic equipment worn by a user during sleep does not meet the measurement requirement; the motion amplitude or motion frequency of the user wearing the wearable electronic device during sleep affects the monitoring quality; there are situations when the wearable electronic device is being pressed during the user's sleep.

That is, in some embodiments of the present application, the reason for affecting the quality of sleep monitoring data of the wearable electronic device during sleep of the user is the above three cases or a combination of the above three cases.

In a possible implementation of the first aspect, the method determines, based on the determined reason, prompt information for prompting the user to improve monitoring quality of the wearable electronic device during sleep of the user, where the prompt information includes at least one of:

in the case that the reason is determined that the degree of tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirement, determining prompt information for improving monitoring quality as prompt information about correct wearing of the wearable electronic device; determining prompt information for improving the monitoring quality as prompt information about stable sleep under the condition that the reason is determined that the monitoring quality is influenced by the action amplitude or the action frequency when the user wears the wearable electronic equipment during the sleep; in the case where it is determined that the reason is that the wearable electronic device is pressed during the sleep of the user, the prompt information for improving the monitoring quality is determined as the recommended prompt information about the wearing part.

That is, the prompt information for prompting the user to improve the monitoring quality of the wearable electronic device is determined according to the reason influencing the monitoring quality of the sleep monitoring data of the wearable electronic device, and if the reason influencing the monitoring quality of the sleep monitoring data of the wearable electronic device is different, the prompt information for prompting the user is also 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 message prompting the user may also be a combination of the prompt messages corresponding to the above three reasons.

In a possible implementation of the first aspect, the determining the reason for the presence of the sleep monitoring data with abnormal monitoring quality in the method includes:

under the condition that the monitoring quality of sleep monitoring data of a screen of wearable electronic equipment worn by a user in different directions is judged to be normal and abnormal at the same time, determining the reason that the tightness degree of the wearable electronic equipment worn by the user in the sleep period is looser than the tightness degree meeting the measurement requirement; under the condition that the monitoring quality of the sleep monitoring data of the screen of the wearable electronic equipment worn by the user in different directions is judged to be only abnormal, the reason is determined to be that the tightness degree of the wearable electronic equipment worn by the user in the sleep period is the tightness degree which is tightly close to the tightness degree meeting the measurement requirement.

When the monitoring quality of the sleep monitoring data of the user monitored by the wearable electronic equipment in different directions of the screen is normal and abnormal, the user is considered to wear the wearable electronic equipment loosely; if the monitoring quality of the sleep monitoring data of the user monitored by the wearable electronic equipment in different directions of the screen is abnormal, the user is considered to be more tightly worn by the wearable electronic equipment.

In one possible implementation of the first aspect, the 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 determining the reason for the presence of sleep monitoring data for monitoring quality anomalies includes:

and judging whether the reason of the sleep monitoring data with abnormal monitoring quality is that the tightness degree of the wearable electronic equipment worn by the user during the sleep does not meet the measurement requirement according to the pressure monitoring data of the pressure sensor.

The tightness degree of wearing the wearable electronic equipment by the user can be judged by arranging the pressure sensor on the wearable electronic equipment, for example, the pressure sensor is arranged on the inner side of a display screen of the wearable electronic equipment, and the tightness degree of wearing the wearable electronic equipment by the user is judged through monitoring data of the pressure sensor.

In one possible implementation of the first aspect, the wearable electronic device includes an acceleration sensor, and determining that the reason for the presence of the sleep monitoring data with abnormal monitoring quality includes:

and judging whether the reason is that the monitoring quality is influenced by the action amplitude or the action frequency of the user wearing the wearable electronic equipment during the sleep period according to the fluctuation interval and the fluctuation amplitude of the measurement data of the acceleration sensor in the acquired sleep monitoring data.

The wearable electronic equipment can acquire an acceleration sensor data fluctuation interval and an acceleration sensor data fluctuation amplitude in sleep monitoring data through an acceleration sensor, and judge whether the reason influencing the monitoring quality of the sleep monitoring data of the wearable electronic equipment is too large because of the action amplitude or too much action frequency of a user in the sleep period by calculating the variance of the acceleration sensor data fluctuation interval and the variance of the acceleration sensor data fluctuation amplitude and respectively comparing the variance of the acceleration sensor data fluctuation interval and the variance of the acceleration sensor data fluctuation amplitude with an acceleration sensor data fluctuation interval threshold and an acceleration sensor data fluctuation amplitude threshold. It is understood that the average value of the fluctuation intervals of the acceleration sensor data and the fluctuation amplitude of the acceleration sensor data or other values which can characterize the fluctuation condition of the measurement data of the acceleration sensor can be calculated to judge the action amplitude or action frequency of the user during the sleep.

under the condition that the degree of tightness of the wearable electronic device worn by the user during sleep meets the measurement requirement and the action amplitude or action frequency of the wearable electronic device worn by the user during sleep does not influence the monitoring quality, the reason is determined to be that the wearable electronic device is pressed during sleep of the user.

That is, if the user wears the wearable electronic device correctly and the user does not have a large motion amplitude or a large motion frequency during sleep, it is considered that the reason for affecting the quality of the sleep monitoring data of the wearable electronic device is that the wearable electronic device is pressed during the sleep of the user.

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

and judging whether the sleep monitoring data with abnormal monitoring quality exist in the sleep monitoring data according to the fluctuation condition of the data of the photoplethysmography sensor and/or the fluctuation condition of the measurement data of the acceleration sensor in the acquired sleep monitoring data.

Namely, whether the monitoring quality of the sleep monitoring data of the wearable electronic equipment is abnormal or not is judged according to the fluctuation condition of the acquired photoplethysmography sensor data of the wearable electronic equipment and/or the measurement data of the acceleration sensor.

Specifically, the average value of the heart rate peak interval and the heart rate peak amplitude in the acquired photoplethysmography sensor data is calculated, and/or the average value of the acceleration sensor data fluctuation interval and the acceleration sensor data fluctuation amplitude in the measurement data (or monitoring data) of the acceleration sensor is calculated, and then the average value of the heart rate peak interval and the heart rate peak amplitude is compared with a preset heart rate peak interval threshold value and a preset heart rate peak amplitude threshold value respectively and/or the average value of the acceleration sensor data fluctuation interval and the acceleration sensor data fluctuation amplitude is compared with a preset acceleration sensor data fluctuation interval threshold value and an acceleration sensor data fluctuation amplitude threshold value respectively, so as to judge whether the monitoring quality of the sleep monitoring data of the wearable electronic device is abnormal or not.

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

displaying the determined prompt information for prompting the user to improve monitoring quality of the wearable electronic device during sleep of the user. Namely, prompt information for prompting the user is displayed on the wearable electronic device.

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

sleep monitoring data is received from a wearable electronic device. That is, the above-mentioned determination process of the monitoring quality of the sleep monitoring data and the determination process of the reason affecting the monitoring quality of the sleep monitoring data may also be performed on other electronic devices (for example, a mobile phone or a server, etc.), and when performed on the other electronic devices, the other electronic devices may receive, from the wearable electronic device, the sleep monitoring data of the user monitored by the wearable electronic device during sleep.

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

and sending the determined prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the sleep period of the user. That is, the prompting message for prompting the user may also be displayed on another electronic device (such as a mobile phone), and at this time, the wearable electronic device sends the prompting message for prompting the user to another electronic device.

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

the wearable electronic equipment sends sleep monitoring data of the wearable electronic equipment during the sleep period of a user, wherein the sleep monitoring data with abnormal monitoring quality exists; the wearable electronic device receives prompting information for prompting a user to improve monitoring quality of the wearable electronic device during sleep of the user.

Namely, the monitoring quality of the sleep monitoring data is judged and the reason influencing the monitoring quality of the sleep monitoring data is determined on other electronic equipment, and then the prompt information which is determined according to the determined reason influencing the monitoring quality of the sleep monitoring data of the wearable electronic equipment and is used for prompting the user is displayed on the wearable electronic equipment. The analysis process of the sleep monitoring data is transferred to other electronic equipment to reduce the power consumption of the wearable electronic equipment and improve the cruising ability of the wearable electronic equipment.

In one possible implementation of the second aspect, the wearable electronic device receiving prompting information for prompting a user to improve monitoring quality of the wearable electronic device during sleep of the user includes at least one of:

prompt information regarding proper wearing of the wearable electronic device; prompt information about stable sleep; a suggested reminder information about the wearing location.

Specifically, in the case that the other electronic device (such as a mobile phone) determines that the degree of tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirement, the prompt information received by the wearable electronic device is prompt information about correct wearing of the wearable electronic device; when other electronic equipment determines that the reason is that the monitoring quality is influenced by the action amplitude or the action frequency when the user wears the wearable electronic equipment during the sleep period, the prompt information received by the wearable electronic equipment is prompt information about stable sleep; in the case where the other electronic device determines that the reason is that the wearable electronic device is being pressed during the sleep of the user, the reminder information received by the wearable electronic device is reminder information regarding a suggested wearing location. It can be understood that, when the other electronic device determines that the reason affecting the sleep monitoring data of the wearable electronic device is the combination of the three reasons, the prompt message prompting the user may also be the combination of the prompt messages corresponding to the three reasons.

In a third aspect, an embodiment of the present application is a readable medium of an electronic device, where the readable medium has instructions stored thereon, and the instructions, when executed on the electronic device, cause the electronic device to perform the method of any one of the above aspects.

In a fourth aspect, an embodiment of the present application provides an electronic device, including: a memory for storing instructions for execution by one or more processors of the electronic device, and the processor, being one of the processors of the electronic device, is configured to perform the method of any of the first and second aspects described above.

In a fifth aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor, a photoplethysmography sensor, and an acceleration sensor; the photoplethysmography sensor is used for acquiring photoplethysmography sensor data of a user of the electronic equipment during sleep; the acceleration sensor is used for acquiring monitoring data of the acceleration sensor during the sleep period of a user of the electronic equipment; the memory is to store instructions for execution by one or more processors of the electronic device; the processor, being one of the processors of the electronic device, is configured to perform the method of any one of the first and second aspects.

In a sixth aspect, an embodiment of the present application provides an electronic device, including: the device comprises a memory, a processor, a display screen, a photoplethysmography sensor, a pressure sensor and an acceleration sensor; the photoplethysmography sensor is used for acquiring photoplethysmography sensor data of a user of the electronic equipment during sleep; the acceleration sensor is used for acquiring monitoring data of the acceleration sensor during the sleep period of a user of the electronic equipment; the display screen is used for displaying prompt information for prompting a user to improve monitoring quality of the wearable electronic equipment during sleep of the user; the pressure sensor is positioned on the inner side of the display screen and used for detecting the tightness degree of the electronic equipment worn by a user; the memory is to store instructions for execution by one or more processors of the electronic device; the processor, being one of processors of an electronic device, is configured to perform the method of any one of the first and second aspects.

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

Drawings

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

Fig. 2 illustrates a hardware structure diagram of a bracelet according to some embodiments of the present application.

Fig. 3a illustrates a technical solution flow diagram according to some embodiments of the present application.

Fig. 3b illustrates a technical solution flow diagram according to some embodiments of the present application.

FIG. 4a illustrates a human-machine interface diagram, according to some embodiments of the present application.

FIG. 4b illustrates a human-machine interface diagram according to some embodiments of the present application.

FIG. 5a illustrates a human-machine interface diagram according to some embodiments of the present application.

FIG. 5b illustrates a human-machine interface diagram according to some embodiments of the present application.

FIG. 6a illustrates a human-machine interface diagram, according to some embodiments of the present application.

FIG. 6b illustrates a human-machine interface diagram according to some embodiments of the present application.

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

Fig. 8 illustrates a schematic structural diagram of an electronic device 800 capable of implementing the functions of the cell phone 200 according to some embodiments of the present application.

Fig. 9 illustrates a software system of an electronic device 800 capable of implementing the functionality of the handset 200, according to some embodiments of the present application.

Detailed Description

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

Fig. 1 is an application scenario diagram of a usage monitoring method for a wearable electronic device according to an embodiment of the present application. As shown in fig. 1, embodiments of the present application relate to a wearable electronic device 100, where the wearable electronic device 100 may wirelessly communicate with other electronic devices in various wireless manners, for example, wirelessly communicate with an electronic device 200 or a server 300. For another example, the wearable electronic device 100 may send a wireless signal to the server 300 through a wireless communication link via a radio frequency circuit and an antenna thereof, and request the server 300 to perform a wireless network service to process specific service requirements of the wearable electronic device 100, such as user registration, data acquisition and monitoring, and the like; for another example, the wearable electronic device 100 may match with the electronic device 200 through its own bluetooth, and perform data communication with the electronic device 200 through a bluetooth communication link after the matching is successful, or certainly may perform data communication with the electronic device 200 through other wireless communication methods, such as a radio frequency identification technology, a near field wireless communication technology, and the like. In addition, the wearable electronic device 100 may also detect a change in the external environment through its various sensors.

In particular embodiments of the present application, wearable electronic device 100 may monitor a sleep breathing condition of a 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 (PPG) sensor data, electrocardiography (ECG) data (e.g., heart rate peak interval, heart rate peak amplitude, blood oxygen data, body temperature data), measurement data (or monitoring data) of an Acceleration sensor (ACC) (e.g., acceleration sensor data fluctuation interval, acceleration sensor data fluctuation amplitude), gyroscope sensor data, and so on. And determining the reason of the sleep monitoring data with abnormal monitoring quality when the sleep monitoring data has the sleep monitoring data with abnormal monitoring quality (or the monitoring quality of the sleep monitoring data is poor), then determining prompt information for prompting the user to improve the monitoring quality of the wearable electronic equipment during the sleep of the user according to the determined reason, and pushing corresponding suggestions or services to the user. For example, in the case that it is determined that the reason for the sleep monitoring data with abnormal monitoring quality is that the degree of tightness of the wearable electronic device worn by the user during sleep does not meet the measurement requirement, determining the prompt information for improving the monitoring quality as prompt information about correct wearing of the wearable electronic device; determining prompt information for improving the monitoring quality as prompt information about stable sleep under the condition that the reason of the sleep monitoring data with abnormal monitoring quality is determined to be that the monitoring quality is influenced by the action amplitude or the action frequency when the user wears the wearable electronic equipment during the sleep; in the case where it is determined that the reason for the presence of the sleep monitoring data with abnormal monitoring quality is that the wearable electronic device is pressed during the sleep of the user, the prompt information for improving the monitoring quality is determined as the recommended prompt information about the wearing part, and then the specific reasons are sent to the user.

According to the technical scheme, the reason that the monitoring quality is abnormal can be determined to exist in the acquired sleep monitoring data of the wearable electronic device 100, wearing and sleep advice is provided for a user, and therefore the monitoring quality of the sleep monitoring data of the intelligent wearable electronic device 100 is improved.

In particular embodiments of the present application, the wearable electronic device 100 may be a variety of devices, including but not limited to a smart watch, a smart band or glasses, a helmet, a headband, and other wearable electronic devices, medical detection instruments, and so forth. In the following description, for simplicity of explanation, the smart band 100 is taken as an example to explain the technical solution of the present application.

Electronic device 200 may be a client capable of communicating with wearable electronic device 100, and may be capable of assisting wearable electronic device 100 in completing registration, controlling firmware updates of wearable electronic device 100, receiving sleep monitoring data of wearable electronic device 100, assisting wearable electronic device 100 in analyzing sleep monitoring data for monitoring and prompting a wearing pattern, sleep condition of a user. It is to be appreciated that the electronic device 200 can include, but is not limited to, a laptop computer, a desktop computer, a tablet computer, a smartphone, a server, a wearable electronic device, a head-mounted display, a mobile email device, a portable game console, a portable music player, a reader device, a television with one or more processors embedded or coupled therein, or other electronic device capable of accessing a network. In the following description, for simplicity of explanation, the mobile phone 200 is taken as an example to illustrate the technical solution of the present application.

Fig. 2 is a schematic diagram illustrating a hardware structure of a smart bracelet 100 according to some embodiments of the present application. The smart band may include a smart band body 100. In one embodiment of the present application, the main body of the smart bracelet 100 may include a touch screen 101 (also referred to as a touch screen panel), a display screen 102, a housing including a front case (not shown in fig. 2) and a bottom case (not shown in fig. 2), and a processor 103, a Micro Control Unit (MCU) 104, a memory 105, a wireless communication module 106, a pressure sensor 107, a PPG sensor 108, an acceleration sensor 109, a power supply 111, a power management system 112, and the like.

The following introduces each functional component of the smart bracelet 100 respectively:

the touch screen 101, which may also be referred to as a touch panel, may collect touch operations of the user on the smart band 100 (for example, operations of the user on or near the touch panel by using any suitable object or accessory such as a finger or a stylus pen), and drive a corresponding connection device according to a preset program.

The display screen 102 may be used to display information entered by the user or to provide prompt information to the user and various menus on the bracelet. Further, the touch screen 101 may cover the display screen 102, and when the touch screen 101 detects a touch operation on or near the touch screen 101, the touch operation is transmitted to the processor 103 to determine the type of the touch event, and then the processor 103 provides a corresponding visual output on the display screen 102 according to the type of the touch event. For example, in some embodiments of the present application, when there is sleep monitoring data with abnormal monitoring quality in the sleep monitoring data of the smart band 100, a reason for the abnormal monitoring quality of the sleep monitoring data is determined, and after determining prompt information for prompting the user to improve the monitoring quality of the smart band 100 during the sleep of the user according to the reason, the prompt information (e.g., a teaching video of how to correctly wear the smart band 100, etc.) may be displayed on the display screen 102.

The processor 103 is used for system scheduling, touch screen 101, control display screen 102, bluetooth 106 support, and the like.

A micro control unit 104 for controlling the sensor, performing calculations on sensor data, communicating with the processor 103, etc. The sensors may include, among others, 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 analyzes PPG data (e.g., heart rate peak interval, heart rate peak amplitude) and ACC data (e.g., ACC data fluctuation interval, ACC data fluctuation amplitude) respectively acquired by the PPG sensor and the acceleration sensor to determine the reason for the abnormal monitoring quality of the sleep monitoring data. Furthermore, it is understood that in other embodiments, the above processing of the PPG data and the ACC data may also be performed by the processor 103, which is not limited herein.

The memory 105 is used for storing software programs and data, and the processor 103 executes various functional applications and data processing of the smart band 100 by operating 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 acquired by a PPG sensor or store ACC data acquired by an acceleration sensor. Meanwhile, the memory may also store registration information, login information, and the like of the user.

The wireless communication module 106 and the smart band 100 may interact with other electronic devices (e.g., a mobile phone, a tablet computer, etc.) through the wireless communication module, and may be connected to a network or a server through the electronic devices. The wireless communication module may provide a solution for wireless communication applied to the smart band 100, including Wireless Local Area Networks (WLANs), (such as wireless fidelity (Wi-Fi) networks), bluetooth (blue tooth, BT), global Navigation Satellite System (GNSS), frequency Modulation (FM), near Field Communication (NFC), infrared (IR), and the like.

It is understood that the structure shown in fig. 2 is only one specific structure for implementing the functions of the smart band 100 in the technical solution of the present application, and the smart band 100 or other types of wearable electronic devices having other structures and capable of implementing similar functions are also applicable to the technical solution of the present application, and are not limited herein.

The technical scheme of the present application is described in detail below with reference to specific scenarios.

In some embodiments of the present application, the smart band 100 may independently complete the whole technical solution, for example, the smart band 100 monitors the sleep condition of the user, and determines the monitoring quality of the sleep monitoring data of the smart band 100 during the sleep of the user according to the sleep monitoring data (such as PPG data and ACC data) of the user monitored by the smart band 100 during the sleep, and determines the reason why the monitoring quality of the sleep monitoring data is abnormal when the monitoring quality of the sleep monitoring data is abnormal, and then based on the specific reason, pushes a suggestion that the monitoring quality of the sleep monitoring data of the smart band 100 is better to the user through the mobile phone 200 in a targeted manner.

In addition, in other embodiments of the present application, the reason why the monitoring quality of the sleep monitoring data is abnormal may also be determined by the mobile phone 200. For example, when the user wishes to reduce the power consumption of the smart band 100, the user may choose to give the cell phone 200 the cause of the abnormal monitoring quality of the sleep monitor data, and display only the prompting information for prompting on the smart band 100 side. Specifically, at this time, the smart band 100 may send the monitored sleep monitoring data of the user during sleep to the mobile phone 200 in a bluetooth or wireless network manner, then the mobile phone 200 determines the monitoring quality of the sleep monitoring data according to the received sleep monitoring data, and determines the reason for the abnormal monitoring quality of the sleep monitoring data, and finally determines the prompt information of the user prompting the user according to the reason for the abnormal monitoring quality of the sleep monitoring data of the user during sleep monitored by the smart band 100, and then the mobile phone 200 sends the prompt information to the smart band 100 side worn by the user, and displays the prompt information on the display screen of the smart band 100 side.

In addition, in some other embodiments of the present application, the determination of the monitoring quality of the sleep monitoring data may also be performed by the server 300. For example, the smart band 100 sends sleep monitoring data monitored by the smart band 100 to the server 300 in a wireless communication manner during the sleep period of the user, then the server 300 determines the monitoring quality of the sleep monitoring data according to the received sleep monitoring data during the sleep period of the user, determines the reason for the abnormal monitoring quality of the sleep monitoring data, and finally pushes monitoring quality prompt information capable of improving the sleep monitoring data of the smart band 100 during the sleep period of the user to the user in a targeted manner according to the reason for the abnormal monitoring quality of the sleep monitoring data of the user monitored by the smart band 100 during the sleep period.

For convenience of explanation, the following description will be given by taking an example in which the determination of the monitoring quality of the sleep monitoring data and the determination of the cause of the abnormality of the monitoring quality of the sleep monitoring data are performed on the smart band 100 side, and the relevant prompt information is pushed on the mobile phone 200 side.

Fig. 3a shows a flow chart of the solution according to the present application, according to an embodiment of the present application. As shown in fig. 3 a:

a301: sleep monitoring data during a user's sleep is acquired. For example, PPG data during sleep of the user or ACC data during sleep of the user is acquired, wherein the PPG data may include heart rate fluctuation amplitude, heart rate fluctuation interval, pulse data, blood oxygen value, electrocardiogram data, etc. of the user, and the ACC data may be ACC data fluctuation interval, ACC data fluctuation amplitude, data monitored by a gyroscope, etc.

a302: judging 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 band 100 is normal, a303 is performed, and if the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal, a304 is performed.

a303: the corresponding sleep monitor data is marked as "normal" and is not prompted to the user.

a304: further, it is determined whether the monitoring quality of the sleep monitor data of the smart band 100 is abnormal due to a large number of user actions, if the monitoring quality of the sleep monitor data of the smart band 100 is abnormal due to a large number of user actions, a305 and a310 are performed, and if the monitoring quality is not abnormal due to a large number of user actions, a306 is performed.

a305: the method comprises the steps of marking abnormal conditions on corresponding sleep monitoring data and marking reasons causing abnormal monitoring quality, for example, marking U1 to indicate that the abnormal reasons are more user actions, and then determining prompt information according to the reasons causing the abnormal monitoring quality.

a306: whether the monitoring quality of the sleep monitoring data of the smart bracelet 100 is abnormal or not is further judged because the user wears the bracelet too loosely or too tightly. If the smart band 100 is worn too loosely or too tightly by the user, a307 and a310 are performed, and if the monitoring quality of the sleep monitoring data of the smart band 100 is not abnormal due to the fact that the smart band is worn too loosely or too tightly by the user, a308 is performed.

a307: the method comprises the steps of marking abnormal conditions of corresponding sleep monitoring data, simultaneously marking reasons causing abnormal monitoring quality, for example, marking U2 to indicate that the abnormal reasons are 'too loose or too tight when a user wears an intelligent bracelet', and then determining prompt information according to the reasons causing abnormal monitoring quality.

a308: whether the intelligent bracelet is pressed or not is further judged. If the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal because the smart band 100 is pressed, a309 and a310 are performed.

a309: the corresponding sleep monitoring data is marked with 'abnormal' and the reason causing the monitoring quality abnormity is marked at the same time, for example, the mark 'U3' is used for representing that the abnormity reason is 'the intelligent bracelet 100 is pressed', and then prompt information is determined according to the reason causing the monitoring quality abnormity.

a310: and sending corresponding prompt information to the mobile phone.

As shown in fig. 3a, in the above technical solution process, there is a sequential limitation on the manner of determining the reason for the abnormal monitoring quality of the sleep monitoring data. In some embodiments of the present application, the manner of determining the reason for the abnormal monitoring quality of the sleep monitoring data may also be performed simultaneously. For example, it is determined whether the reason causing the abnormality of the sleep monitor data is "user action is too much", "user wearing is too loose or too tight", "smart band is pressed", and if it is determined that the reason causing the abnormality of the sleep monitor data of the smart band 100 is a combination of the above-mentioned reasons, for example, the monitoring abnormality of the sleep monitor data satisfies both "user action is too much" and "smart band is pressed". At this time, when the sleep monitoring data is marked as abnormal, the sleep monitoring data with abnormal monitoring quality can be marked as ' U1U3 ', wherein ' U1 ' indicates that the reason of the abnormal monitoring quality is ' user action is more, ' U3 ' indicates that the reason of the abnormal monitoring quality is ' intelligent bracelet is pressed ', and meanwhile, various prompt messages are determined simultaneously according to the reason of the abnormal monitoring quality of the sleep monitoring data.

In addition, it is understood that in other embodiments of the present application, the manner of determining the reason for the abnormal monitoring quality of the sleep monitoring data may also be determined not according to the order of a304, a306, and a308, and the determination order may be arbitrary, for example, in a specific implementation process, the manner may be:

firstly, whether the reason that the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal is caused by 'the user wears the smart band loose or too tightly' (a 306), if the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal not caused by the user wearing the smart band loose or too tightly, then whether the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal because 'the user acts much' (a 304) is judged, and if the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal not caused by the user acting much, then whether the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal because 'the smart band is pressed' is judged (a 308). In this determination manner, other steps are consistent with the technical solution flow described in fig. 3a, and are not described herein again.

Fig. 3b shows a specific situation that after the reason causing the abnormal monitoring quality of the sleep monitoring data of the smart band 100 is determined through the above technical solution and the prompt message is determined according to the specific abnormal reason, the relevant prompt message is pushed to the user through the mobile phone 200. For example, when it is determined that "there is no problem in wearing and operation of the user b302", that is, the monitoring quality of the sleep monitoring data of the smart band 100 is normal, "no prompt (b 304)" is given to the user; when it is determined that "there is a problem in wearing by the user (b 305)", that is, the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal, if the user is "wear normally but have too many actions at night" (b 306) ", that is, if the user wears the smart band not too tightly or too loosely but has a large action amplitude or a high action frequency, performing" mark data is abnormal and determining that the prompt information is "recommended push for stable sleep, recommended multiple wearing" (b 307); if the user is ' wearing too loosely or too tightly ' (b 308), ' marking data abnormity and determining that the prompt message is ' playing wearing guide video ' (b 309); if the user presses the bracelet to the position (b 310) in the sleeping process, marking data abnormity and determining prompt information as ' suggesting that the bracelet is worn on the opposite hand of the master side lying position ' (b 311) '; if the combination is 'a combination of multiple causes' (b 312) ', the prompt message is determined to be' a combination of multiple suggestions '(b 313)'.

The specific mode of judging the quality of monitoring the sleep monitor data of the smart band 100 and the mode of determining the reason for the abnormal quality of monitoring the sleep monitor data of the smart band 100 are as follows:

acquiring sleep monitoring data during sleep of a user

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

In some embodiments of the present application, the smart band 100 may acquire sleep monitoring data during a user's sleep period in a time-sharing manner, or may acquire sleep monitoring data during a user's sleep period in a real-time manner. For example, a user's sleep is generally divided into daytime and nighttime. However, the day may be only half an hour or 1 hour of afternoon nap, which is a short time, so the smart band 100 can monitor the user in real time to obtain the sleep monitoring data of the user at that time; at night, the general sleep time of the user is 7-8 hours, and at this time, if the real-time monitoring is performed, the power consumption of the bracelet 100 is increased, so the sleep monitoring data of the user can be acquired in different time periods (for example, the sleep monitoring data from 9 pm to 3 am or the sleep monitoring data from 1 am to 5 am). Or, because the possibility that the afternoon nap can enter deep sleep in the daytime is low, and the condition of sleep apnea of the user is less, the sleep monitoring data during the sleep period of the user can be acquired in different time periods, while in the evening, the sleep time of the user is sufficient, the condition of sleep apnea is more, and the sleep monitoring data of the user at the moment can be monitored and acquired in real time.

Hereinafter, the real-time monitoring of the user by the smart band 100 from 1 pm to 5 pm will be specifically described as an example.

Determining a monitoring quality of the acquired sleep monitoring data

And judging the monitoring quality of the acquired sleep monitoring data, wherein the sleep monitoring data comprises the heart rate peak interval and the heart rate peak amplitude obtained by the PPG sensor 108. Of course, it is understood that in other embodiments, the sleep monitor data may also be other data characteristics characterizing the sleep monitor data monitoring quality of the smart band, such as related pulse data, blood pressure data, and the like.

In an embodiment of the present application, smart band 100 may determine the monitoring quality of sleep monitoring data of the smart band based on the heart rate peak interval and the heart rate peak amplitude obtained by PPG sensor 108. For example, a heart rate peak interval threshold T1 and a heart rate peak amplitude threshold A1 may be preset by a historical heart rate peak interval and a historical heart rate peak amplitude monitored by the smart band 100 in advance, and when the heart rate peak interval duration acquired by the smart band 100 is less than T1 and the heart rate peak amplitude is less than A1, the monitoring quality of the sleep monitoring data of the smart band is normal at this time, otherwise, the monitoring quality of the sleep monitoring data of the smart band is considered to be abnormal.

For example, in a specific implementation process, the smart band 100 monitors the heart rate peak interval T1, T2, T3 · tn and the heart rate peak amplitude a1, a2, a3 · an of the user in the time period T, and then the smart band 100 calculates the average heart rate peak interval of the user in the time period T according to the formula (one)

And average heart rate peak amplitude

(in other embodiments, it may also be the variance, range, etc. of the heart rate peak and heart rate interval of the user over time period T)

Where μ represents the average value of data, h1, h2, h3 … hn represents data, and n represents the number of data

Meanwhile, the smart band 100 sets a heart rate peak interval threshold T1 and a heart rate peak amplitude threshold A1 according to the monitored historical heart rate peak interval and the monitored historical heart rate peak amplitude (the values of T1 and A1 may be specifically set by calculating an average value or a variance of the historical heart rate peak interval and the historical heart rate peak amplitude), and then the smart band 100 sets an average heart rate peak interval of the user in the time period T

And average heart rate peak amplitude

Comparing a preset heart rate peak interval threshold value T1 with a preset heart rate peak amplitude threshold value A1, and if the average heart rate peak interval of the user in the time period T is

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

If the amplitude value of the wave crest of the preset heart rate is smaller than the threshold value A1, the monitoring quality of the sleep monitoring data of the smart bracelet is considered to be normal, and if the average heart rate wave crest interval of the user in the time period T is smaller than the threshold value A1, the monitoring quality of the sleep monitoring data of the smart bracelet is considered to be normal

Greater than a preset heart rate peak interval threshold value T1 or an average heart rate peak amplitude value

If the amplitude value is larger than a preset heart rate peak amplitude threshold value A1, the monitoring quality of the sleep monitoring data of the smart band is considered to be abnormal.

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

For example, in one embodiment of the present application, the smart band 100 may also determine the monitoring quality of the sleep monitoring data of the smart band 100 based on the ACC data. In specific implementation, when the amplitude of fluctuation 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 band is normal at this time. Specifically, the smart band 100 presets an ACC data fluctuation amplitude threshold value A2 and an ACC data fluctuation interval threshold value T2 according to the monitored historical ACC data fluctuation interval and historical ACC data fluctuation amplitude of the user (the values of A2 and T2 may be set specifically by calculating the average value or variance of the historical ACC data fluctuation interval and the historical ACC data fluctuation amplitude), and meanwhile, the smart band 100 monitors the ACC data fluctuation amplitude b1, b2, b3 · · bn and the ACC data fluctuation interval c1, c2, c3 · · c4 of the user in the time period T, and calculates the average fluctuation amplitude bur of the ACC data of the user in the time period T according to the formula (one)

And average fluctuation interval

And averaging the fluctuation amplitude of the ACC data of the user in the time period T

And average fluctuation interval

Comparing with ACC data fluctuation amplitude threshold A2 and ACC data fluctuation interval threshold T2, if the average fluctuation amplitude of ACC data of the user in the time period T

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

If the average fluctuation amplitude of the ACC data of the user in the time period T is smaller than the ACC data fluctuation interval threshold value T2, the sleep monitoring quality of the smart band 100 is considered to be normal

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

If the variance interval is greater than the threshold T2 of the ACC data, it is determined that the monitoring quality of the sleep monitoring data of the smart band 100 is abnormal.

In addition, in some embodiments of the present application, the smart band 100 may also determine the monitoring quality of the sleep monitoring data in a machine learning manner. For example, in a specific implementation, the smart band 100 manually calibrates historical sleep monitoring data of a monitored user according to the historical sleep monitoring data (where the quality of the historical sleep monitoring data is normal and abnormal), for example, the data with normal quality may be labeled as "normal", and the data with abnormal quality may be labeled as "abnormal". Then, feature extraction is carried out on the historical sleep monitoring data, so that feature vectors are generated, then the extracted feature vectors are input into a Convolutional Neural Network (CNN), and the Convolutional Neural network model is trained so that the quality of the historical physiological data and the quality of the historical physical data can be judged by the model. For example, the difference between the input and the output of the model may be used as a loss function, for example, historical sleep monitoring data is randomly input, the output of the model is compared with the input label of the historical sleep monitoring number, if the input label of the historical sleep monitoring data is "normal" and the output result of the model is "normal", the loss function is considered to be close to 0, the model is trained, if the input label of the historical sleep monitoring data is "abnormal" and the output result is not "abnormal", the loss function is considered not close to 0, the relevant parameters of the model are adjusted, and the next round of training is performed until the loss function between the input and the output is close to 0, and the model training is completed. Then, the sleep monitoring data of the user currently acquired by the smart band 100 is input into the trained convolutional neural network model, and the model can judge the quality of the input sleep monitoring data.

In other embodiments of the present application, the smart band 100 may also perform the determination of the data quality of the smart band based on other data, such as blood pressure data. The specific judgment method may be to convert the heart rate data in the PPG data described above into blood pressure data, and then the specific judgment is similar to the above judgment method, which is not described herein again.

In some embodiments of the present application, the smart band 100 may also determine the monitoring quality of the sleep monitor data of the smart band according to the combination of the sleep monitor data. For example, the weight assignment may be performed on each sleep monitoring data, and the specific assignment may be performed according to a condition that each sleep monitoring data reflects the physical health of the user. For example, the heart rate peak interval and the heart rate peak amplitude obviously reflect the physical condition of the user more than the ACC data fluctuation interval and the ACC data fluctuation amplitude, so the weight importance of the heart rate peak interval and the heart rate peak amplitude is higher than that of the ACC data fluctuation interval and the ACC data fluctuation amplitude.

For example, in one specific implementation, the a-heart rate peak interval and heart rate peak amplitude are weighted by 80%, and the ACC data fluctuation interval and ACC data fluctuation amplitude are weighted by 20%. The smart bracelet 100 monitors the heart rate peak interval T1, T2, T3 & cndot & tnand the heart rate peak amplitude a1, a2, a3 & cndot & an of the user in the time period T, and the heart rate peak interval T, T2, T3 & cndot & tnand the heart rate peak amplitude of the user in the time period TACC motion data fluctuation amplitude b1, b2, b3 & cndot & ltb & gt and ACC fluctuation interval c1, c2, c3 & cndot & ltc 4 & gtare calculated, and average heart rate peak interval of the user in the time period T is calculated

And average heart rate peak amplitude

And average fluctuation amplitude of ACC motion data

And average fluctuation interval

Meanwhile, the smart band 100 presets a reliability threshold P of the smart band of the user according to the monitored historical sleep monitoring data, then calculates the reliability of the monitoring quality of the sleep monitoring data of the smart band 100 according to the formula (II) based on the preset weight of each sleep monitoring data of the user,

p = α × (a + T) + β × (B + C) (two)

The intelligent bracelet is characterized in that p represents credibility, alpha represents weight, beta represents weight, A represents heart rate peak amplitude, T represents heart rate peak interval, B represents ACC data fluctuation amplitude, and C represents ACC data fluctuation interval

And then comparing the P with a credibility threshold value P, when the credibility of the user intelligent bracelet is greater than the credibility threshold value P, considering that the monitoring quality of the sleep monitoring data of the intelligent bracelet is normal, and otherwise, considering that the monitoring quality of the sleep monitoring data of the intelligent bracelet is abnormal.

Reason for determining abnormal monitoring quality of sleep monitoring number of smart band

The reason that the monitoring quality of the sleep monitoring data of the smart bracelet is abnormal is determined, and the specific process is as follows:

A. judging whether the reason of abnormal monitoring quality of the sleep monitoring data is large action amplitude or high action frequency of the user during sleep

Often, the user has involuntary movements during sleep, which can be reflected by the data from the ACC sensor or gyro sensor of the smart band. For example, when the user action amplitude is large, the fluctuation of the ACC data becomes strong, specifically, the fluctuation interval and the fluctuation amplitude of the ACC data become large. When the user action amplitude is small, the fluctuation of the ACC data becomes moderate, and the fluctuation interval and the fluctuation amplitude of the corresponding ACC data become small.

In some embodiments, when the monitoring quality of the sleep monitoring data of the smart band 100 is determined to be abnormal, the smart band 100 may preset an ACC data fluctuation amplitude threshold A3 and an ACC data fluctuation interval threshold T3 according to the monitored historical ACC data fluctuation amplitude and ACC data fluctuation interval of the user, and at the same time, the smart band 100 monitors the ACC data fluctuation amplitude b1, b2, b3 · bn and the ACC fluctuation interval c1, c2, c3 · c4 of the user in the time period T, and calculates the average fluctuation amplitude of the ACC data according to the formula (one)

And average fluctuation interval

Calculating the fluctuation amplitude variance D and the fluctuation interval variance E of the ACC data of the user in the time period T according to the formula (III),

wherein, delta ² The variance of the data to be calculated is represented, n represents the number of the data, mu is the average value of the data to be calculated, and X is real-time data monitored by the smart band. In calculation, the amplitude of fluctuation of ACC data can be substituted as mu to obtain delta ² Is thatThe variance D of the fluctuation amplitude of the ACC data, and the interval of the fluctuation of the ACC data is substituted as mu to obtain delta ² Namely the variance E of the fluctuation interval of the ACC data.

Meanwhile, the smart band 100 sets an ACC data fluctuation amplitude threshold A3 and an ACC motion data fluctuation interval threshold T3 according to the monitored historical ACC data fluctuation amplitude and ACC data fluctuation interval of the user. Comparing the variance D of the fluctuation amplitude of the ACC data and the variance E of the fluctuation interval of the ACC data of the user in the time period T with the threshold A3 of the fluctuation amplitude of the ACC data and the threshold T3 of the fluctuation interval of the ACC data respectively, and if the variance D of the fluctuation amplitude of the ACC motion data of the user in the time period T is larger than A3 and the variance E of the fluctuation interval is larger than T3, the current time period is considered as the motion amplitude of the user is large.

Further, the statistical calculation is carried out in the above manner for each time period T of the user sleep stage, and the ratio of the time period with large user action amplitude to the total sleep time of the user is calculated, and if the ratio of the two is higher than the set threshold V1, the data action frequency of the user at the night is considered to be high. For example, the smart band 100 may count the actions of the user in a sleep time period (for example, 8 hours) at night.

Specifically, the smart bracelet 100 may calculate the ACC motion data fluctuation amplitude (d 1, d2, d3 · dn) of the user during the period of 22-00, 00-23.

Then, the fluctuation amplitude variance (D1, D2, D3, D4) and the fluctuation interval variance (E1, E2, E3, E4) of the ACC data of the user in the above time period are calculated according to the formulas (one) and (two), assuming that the time period in which the fluctuation amplitude variance is greater than A3 and the fluctuation interval variance is greater than T3 is 00-01. If the calculation result is larger than V1, the action frequency of the user is high, otherwise, the action frequency of the user is considered to be low.

In some embodiments of the present application, the smart band 100 may further determine whether the user has a time period with a large continuous motion amplitude by the above method for determining the motion amplitude of the user, and if the motion amplitude of the user is always large in a certain continuous time period, it may be determined that the user is awake at night for a long time. And because the long-time night waking can also influence the accuracy of the sleep apnea detection, abnormal marking or prompting can be carried out on the sleep monitoring data in the corresponding time period.

B. Whether the reason for the abnormal monitoring data is that the fastening degree of the intelligent bracelet worn by the user is not appropriate or not is judged

Generally, the monitoring quality of the sleep monitoring data of the smart band is also affected by the way in which the user wears the smart band. When the user wears the bracelet and crosses loosely or when tight, the monitoring quality of the sleep monitor data of intelligence bracelet also can be unusual. And whether the user wears the intelligent bracelet and is too loose or too tight can be judged through acceleration sensor specifically. The ACC sensor can identify the screen direction of the smart band, and when the screen direction of the smart band is in different directions, the monitoring quality of sleep monitoring data of the smart band is abnormal, and a user can be considered to be wearing the smart band too tightly; when the screen direction of intelligence bracelet was in the direction of difference, the monitoring quality of the sleep monitor data of intelligence bracelet all had normally to have unusually, when monitoring quality is inconsistent promptly, then can think that the user wears the bracelet and crosses loosely.

In some embodiments of the present application, an acceleration sensor 109 is disposed in the smart band 100, and the Z axis is generally perpendicular to the screen (touch screen) of the smart band 100. The smart band 100 can acquire ACC data of a sleep time period of a user through the acceleration sensor 109, and can identify a screen direction of the smart band worn by the user through analysis of ACC data fluctuation, and under a general condition, a screen of the smart band can be: screen up, screen down and screen side up.

For example, if the smart band acceleration sensor 109 recognizes that the value of the Z axis is larger than 0, and the value of the X/Y axis is close to 0, it may be considered that the smart band screen in the time period is facing upward; if the value of the Z axis is smaller than 0 and the value of the X/Y axis is close to 0, the smart band screen in the time period may be considered to be facing downward; if the smart band 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 may be considered that the smart band screen in the time period is placed on the side.

In some embodiments of the present application, the directions of the respective axes of the acceleration sensor 109 in the smart band and the position of the smart band are not limited to the above-mentioned situations, and it can be understood that when the relative positions of the respective axes directions and the smart band screen in the smart band are changed, the above-mentioned identification rules should be changed accordingly. However, as long as the relative position between the direction of each axis of the acceleration sensor 109 and the smart band screen is determined, the rule for identifying the screen direction is also determined, and is not described herein again.

For example, if the monitoring quality of the smart band 100 for acquiring sleep monitoring data in different screen placement states is normal and the characteristics of the sleep monitoring data are consistent, the user is considered to be wearing normally; if the monitoring quality of the smart band 100 for acquiring the sleep monitoring data in different screen placement states is abnormal, it can be considered that the smart band is worn by the user too tightly; if the monitoring quality of the smart band 100 acquiring the sleep monitoring data in different screen placement states is abnormal and the sleep monitoring data is characterized normally, it can be considered that the user wears the smart band too loosely. The consistent characteristic expression of the sleep monitoring data means that similar or identical sleep monitoring data characteristics can periodically appear in different states. For example, when the smart band screen faces upwards and the smart band screen faces downwards, the heart rate of the smart band screen has periodic peaks, wherein the peak amplitudes in the two states are similar or the same, and the peak intervals are also similar or the same.

In other embodiments of the present application, the smart band 100 may further determine the tightness degree of the smart band 100 worn by the user by measuring a position near the human body in the screen of the smart band and adding a pressure sensor 106. For example, the pressure value of the user on the smart band in the sleep time period is obtained through the pressure sensor 106, and if the pressure value is always large, it can be considered that the smart band of the user is worn too tightly; if the pressure value is moderate all the time, the wearing fastening degree of the intelligent bracelet of the user can be considered to be moderate; if the pressure value be in undulant state, can regard as user's intelligence bracelet to wear loosely. Specifically, the smart band 100 may calculate an average value (may also be a variance, etc.) of data of the pressure sensor 106 in a normal wearing time period of the user as reference data, and then compare a real-time pressure value of the pressure sensor 106 in a user sleep time period, which is acquired by the smart band 100, with the reference data, and if a ratio of the real-time pressure value of the pressure sensor 106 in the user sleep time period to the reference data is (0-0.4), it may be considered that the smart band of the user is worn too loosely; if the ratio of the real-time pressure value of the pressure sensor 106 to the reference data in the sleep time period of the user is (0.4-0.6), the intelligent bracelet of the user can be considered to be worn moderately; if the ratio of the real-time pressure value of the pressure sensor 106 to the reference data in the sleep time period of the user is (0.6-1), the intelligent bracelet of the user can be considered to be worn too tightly.

C. Judging whether the reason for the abnormal monitoring data is that the intelligent bracelet of the user is pressed

In some embodiments, whether the user smart band is pressed may be further identified according to the wearing condition of the user smart band identified in step B. In concrete implementation, if the degree of tightness that user's intelligence bracelet was worn is moderate and when user action range is little, the monitoring quality of the sleep monitor data of intelligence bracelet is still unusual, then can think that intelligence bracelet has been pressed. For example, the intelligent bracelet is worn moderately tightly during a sleep period of time, the action amplitude of the user is small, but the monitoring quality of the acquired sleep monitoring data of the user during the sleep period is still abnormal, and then the intelligent bracelet of the user is considered to be pressed. The method for specifically judging the wearing looseness of the smart band and the monitoring quality of the sleep monitoring data of the smart band is consistent with the specific judging method, and details are not repeated here.

Through the judgment of the steps, the reason that the monitoring quality of the sleep monitoring data of the user smart band is abnormal can be detected, and then the abnormal marking is carried out on the sleep monitoring of the user in the corresponding time period.

Corresponding prompt is carried out on the user based on the determined reason for abnormal sleep monitoring data monitoring quality

As shown in fig. 3b, after the reason for the abnormal monitoring quality of the sleep monitoring data is determined, prompt information for prompting the user to improve the monitoring quality of the sleep monitoring data of the smart band is determined, and the prompt information is prompted to the user. The specific prompt may be performed through the smart band 100 or through the mobile phone 200.

In an embodiment of the present application, the mobile phone 200 is used to provide a specific prompt for the user, which includes the following specific steps:

the mobile phone 200 and the smart band 100 perform data synchronization, when the mobile phone 200 identifies that the reason causing the abnormal monitoring quality of the sleep monitoring data of the smart band is "user action amplitude is large or frequency is high", the mobile phone 200 recommends suggestions and services for stable sleep to the user through the user interaction main interface 210, specifically, as shown in fig. 4a, if the user is using the mobile phone, the user can be prompted to have large action amplitude at this time in a form of directly popping up a dialog box, and a "stable sleep miniscule" 211 is pushed to the user, and the user can operate by selecting "quit" 212 or "remind later" 213; if the user is still in a sleep state or other states without using the mobile phone at this time, as shown in fig. 4b, a prompt may be recorded on the mobile phone screen locking interface 220 to display a "stable sleep cookie" (specifically, some health-care exercise videos or sleeping posture department posts, etc.) 211, and the same user may also select "display" 221 and "delete" 222 to perform related operations, so that the user can see related suggestions and does not disturb the sleep or work of the user when using the mobile phone. Meanwhile, the mobile phone 200 may selectively set a time period during which the smart band 100 acquires the sleep monitoring data of the user according to a habit of wearing the smart band 100 by the user, for example, in the time period with the large action amplitude, the mobile phone 200 may enable the smart band 100 not to acquire the sleep monitoring data of the user in the time period by sending an instruction, so as to improve the monitoring quality of the sleep monitoring data of the smart band 100.

When the reason that the monitoring quality of the sleep monitoring data of the smart band is abnormal is recognized as "the smart band of the user is worn loosely or tightly", the mobile phone 200 recommends suggestions and services for stable sleep to the user through the user interaction interface 210, specifically, as shown in fig. 5a, if the user is using the mobile phone, the user may be prompted in a form of a direct pop-up dialog box that the smart band is not suitable for wearing at the time, and a guidance article or video for correctly wearing the device, such as "smart band wearing manner guidance" (215), is pushed to the user, and the user may operate by selecting "quit" (212) or "remind later" (213); if the user is still in a sleep state or other states without using the mobile phone at the moment, as shown in fig. 5b, a prompt can be recorded on a screen locking interface of the mobile phone to display a smart band wearing mode instruction (215) (for example, a smart band usage manual or a smart band wearing video instruction link, etc.), and the same user can also select to display (221) and delete (222) to perform related operations, so that the user can see related suggestions and does not disturb the sleep or work of the user when using the mobile phone. Meanwhile, the mobile phone 200 may selectively set a time period during which the smart band 100 acquires the sleep monitoring data of the user according to a habit of wearing the smart band 100 by the user, for example, in the time period in which the smart band 100 is worn loosely or tightly, the mobile phone 200 may enable the smart band 100 not to acquire the sleep monitoring data of the user in the time period by sending an instruction, so as to improve the monitoring quality of the sleep monitoring data of the smart band 100.

Similarly, when it is identified that the reason causing the abnormal monitoring quality of the sleep monitoring data of the smart band is "the smart band is pressed", the mobile phone 200 recommends suggestions and services for stable sleep to the user through the user interface 210, and specifically, as shown in fig. 6a, if the user is using the mobile phone, the user may be prompted in the form of a direct pop-up dialog box that the smart band is pressed at this time, and is advised to wear the device on the opposite hand of the main side prone position or adjust the sleeping posture, such as displaying a "sleeping posture guidance" (216) (e.g., a science popularization sticker for healthy sleep, etc.), and the user may operate by selecting "exit" (212) or "remind later" (213); if the user is still in a sleep state or other states without using the mobile phone at the moment, as shown in fig. 6b, a prompt can be recorded on a screen locking interface of the mobile phone to display a sleep posture guide (216), and the same user can select display (221) and delete (222) to perform related operations, so that the user can see related suggestions when using the mobile phone conveniently and the sleep or work of the user is not disturbed. Meanwhile, the mobile phone 200 may selectively set a time period during which the smart band 100 acquires the sleep monitoring data of the user according to a habit of wearing the smart band 100 by the user, for example, in the time period during which the smart band is pressed, the mobile phone 200 may enable the smart band 100 not to acquire the sleep monitoring data of the user during the time period by sending an instruction, so as to improve the monitoring quality of the sleep monitoring data of the smart band 100.

In addition, as described above, in some embodiments of the present application, monitoring and analysis of corresponding sleep monitoring data may also be performed on the mobile phone 200 side, and then the mobile phone 200 directly pushes relevant suggestions to the user according to the cause specifically causing the monitoring quality abnormality of the sleep monitoring data of the smart band 100, as shown in fig. 7:

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

702: and sending the historical sleep monitoring data of the user and the sleep monitoring data acquired in the T time period. The historical sleep monitoring data is used to set a relevant threshold, and the T time period represents a current monitoring time period of the smart band 100.

704: and judging the monitoring quality of the sleep monitoring data acquired in the T time period. The specific determination method is consistent with the above-mentioned determination method at the smart band 100 side, and is not described herein again.

706: if the monitoring quality of the sleep monitoring data of the smart band is judged to be abnormal, the reason for the abnormal monitoring quality of the sleep monitoring data of the smart band is further determined. The specific determination method is consistent with the above-mentioned determination method at the smart band 100 side, and is not described herein again.

708: and according to the specific reason causing the monitoring quality abnormity, related prompt information is pertinently pushed to the user. The specific pushing manner is the same as the above-mentioned pushing manner on the mobile phone 200, and is not described herein again.

Fig. 8 shows a 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 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 (USB) interface 830, a charging management module 840, a power management module 841, a battery 842, an antenna 1, an antenna 2, a mobile communication module 850, a wireless communication module 860, an audio module 870, a speaker 870A, a receiver 870B, a microphone 870C, a headset interface 870D, a sensor module 880, a button 890, a motor 898, an indicator 892, a camera 893, a display 894, and a Subscriber Identification Module (SIM) card interface 895, and the like. Among them, the sensor module 880 may include a pressure sensor 880A, a gyro 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, an ambient light sensor 880L, a bone conduction sensor 880M, and the like.

It is to be understood that the illustrated structure of the embodiments of the invention is not to be construed as a specific limitation to the electronic device 800. In other embodiments of the present application, the electronic device 800 may include more or fewer components than illustrated, or combine certain components, or split certain components, or a different arrangement of components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

Processor 810 may include one or more processing units, such as: the processor 810 may include an Application Processor (AP), a modem processor, a Graphics Processing Unit (GPU), an Image Signal Processor (ISP), a controller, a video codec, a Digital Signal Processor (DSP), a baseband processor, and/or a neural-Network Processing Unit (NPU), etc. The different processing units may be separate devices or may be integrated into one or more processors. For example, the processor 810 may calculate the reliability of the monitoring quality of the sleep monitoring data of the smart band 100, determine the monitoring quality of the sleep monitoring data of the smart band 100, and determine the reason for the abnormal monitoring quality of the sleep monitoring data of the smart band 100.

The controller can generate an operation control signal according to the instruction operation code and the timing signal to complete the control of instruction fetching and instruction execution.

A memory may also be provided in 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 cycled through. If the processor 810 needs to use the instruction or data again, it can be called directly from the memory. Avoiding repeated accesses reduces the latency of the processor 810, thereby increasing the efficiency of the system. Meanwhile, the processor 810 may further store the sleep monitoring data of the user and the historical sleep monitoring data transmitted by the bracelet 100 received by the electronic device 200.

In some embodiments, processor 810 may include one or more interfaces. The interface may include an integrated circuit (12C) interface, an integrated circuit built-in audio (I2S) interface, a Pulse Code Modulation (PCM) interface, a universal asynchronous receiver/transmitter (UART) interface, a Mobile Industry Processor Interface (MIPI), a general-purpose input/output (GPIO) interface, a Subscriber Identity Module (SIM) interface, and/or a Universal Serial Bus (USB) interface, etc.

Micro USB interface, USB Type C interface etc.. The USB interface 830 may be used to connect a charger to charge the electronic device 800, and may also be used to transmit data between the electronic device 800 and a peripheral device. And the earphone can also be used for connecting an earphone and playing audio through the earphone. The interface may also be used to connect other electronic devices, such as AR devices and the like.

It should be understood that the connection relationship between the modules according to the embodiment of the present invention is only illustrative, and is not limited to the structure of the electronic device 800. In other embodiments of the present application, the electronic device 800 may also adopt different interface connection manners or a combination of multiple interface connection manners in the above embodiments.

The charging management module 840 is configured to receive charging input from a charger. The power management module 848 is used to connect the battery 842, the charge management module 840 and the processor 880. The power management module 848 receives input from the battery 842 and/or the charge management module 840 and provides power to the processor 880, the internal memory 821, the display 894, the camera 893, and the wireless communication module 860, among other things. The power management module 848 may also be used to monitor battery capacity, battery cycle count, battery state of health (leakage, impedance), etc. In some other embodiments, the power management module 841 may also be disposed in the processor 880. In other embodiments, the power management module 841 and the charging management module 840 may be disposed in the same device.

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

The antennas 1 and 2 are used for transmitting and receiving electromagnetic wave signals. Each antenna in the electronic device 800 may be used to cover a single or multiple communication bands. Different antennas can also be multiplexed to improve the utilization of the antennas. For example: the antenna 1 may 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 may provide a solution including 2G/3G/4G/5G wireless communication applied on the electronic device 800. The wireless communication module 860 may provide solutions for wireless communication applied to the electronic device 800, including Wireless Local Area Networks (WLANs), such as wireless fidelity (Wi-Fi) networks, bluetooth (BT), global Navigation Satellite Systems (GNSS), frequency Modulation (FM), near Field Communication (NFC), infrared (IR), and the like. The wireless communication module 860 may be one or more devices that integrate at least one communication processing module. The wireless communication module 860 receives electromagnetic waves via the antenna 2, performs frequency modulation and filtering processing on electromagnetic wave signals, and transmits the processed signals to the processor 810. The wireless communication module 860 may also receive signals to be transmitted from the processor 810, frequency modulate them, amplify them, and convert them into electromagnetic waves via the antenna 2 to radiate them.

In some embodiments, the electronic device 800 can be communicatively connected with the smart band 100 through the mobile communication module 850 or the wireless communication module 860.

In some embodiments, antenna 1 of electronic device 800 is coupled to mobile communication module 850 and antenna 2 is coupled to wireless communication module 860, such that electronic device 800 may communicate with networks and other devices via wireless communication techniques. The wireless communication technology may include global system for mobile communications (GSM), general Packet Radio Service (GPRS), code division multiple access (code division multiple access, CDMA), wideband Code Division Multiple Access (WCDMA), time-division code division multiple access (time-division code division multiple access, TD-SCDMA), long Term Evolution (LTE), BT, GNSS, WLAN, NFC, FM, and/or IR technologies, etc. The GNSS may include a Global Positioning System (GPS), a global navigation satellite system (GLONASS), a beidou navigation satellite system (BDS), a quasi-zenith satellite system (QZSS), and/or a Satellite Based Augmentation System (SBAS).

The electronic device 800 implements display functions via the GPU, the display screen 894, and the application processor, among other things. The GPU is a microprocessor for image processing, coupled to a display screen 894 and an application processor. The GPU is 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 may implement a shooting function through the ISP, the camera 893, the video codec, the GPU, the display screen 894, and the application processor, etc. In some embodiments of the present application, the display screen 894 is used to enable human-computer interaction with a user.

The external memory interface 820 may be used to connect an external memory card, such as a Micro SD card, to extend the memory capability of the electronic device 800. The external memory card communicates with the processor 810 through the external memory interface 820 to implement data storage functions. For example, files such as music, video, etc. are saved in an external memory card.

The internal memory 821 may be used to store computer-executable program code, which includes instructions. The internal memory 821 may include a program storage area and a data storage area. The storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, and the like) required by at least one function, and the like. The data storage area may store data created during use of the electronic device 800 (e.g., audio data, phone book, 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, a flash memory device, a Universal Flash Storage (UFS), and the like. The processor 810 performs 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.

Electronic device 800 may implement audio functions via audio module 870, speaker 870A, receiver 870B, microphone 870C, headphone interface 870D, and an application processor, among others. Such as music playing, recording, etc.

The keys 890 include a power-on key, a volume key, and the like. The keys 890 may be mechanical keys. Or may be touch keys. The electronic device 800 may receive a key input, generate a key signal input related to user settings and function control of the electronic device 800.

The motor 891 may generate a vibration cue. The motor 891 may be used for incoming call vibration prompts, as well as for touch vibration feedback. For example, touch operations applied to different applications (e.g., photographing, audio playing, etc.) may correspond to different vibration feedback effects. The motor 891 may also respond to different vibration feedback effects for touch operations applied to different areas of the display screen 894. Different application scenes (such as time reminding, receiving information, alarm clock, game and the like) can also correspond to different vibration feedback effects. The touch vibration feedback effect may also support customization.

Indicator 892 may be an indicator light that may be used to indicate a state of charge, a change in charge, or a message, missed call, notification, etc.

The SIM card interface 895 is used to connect a SIM card.

Referring now to fig. 9, the software system of the electronic device 800 may employ a layered architecture, an event-driven architecture, a microkernel architecture, a microservice architecture, or a cloud architecture. The embodiment of the invention takes an Android system with a layered architecture as an example to exemplarily explain the software structure of the terminal equipment. Fig. 9 is a block diagram of a software configuration of a terminal device according to an embodiment of the present invention.

The layered architecture divides the software into several layers, each layer having a clear role and division of labor. The layers communicate with each other through a software interface. In some embodiments, the Android system is divided into four layers, an application layer, an application framework layer, an Android runtime (Android runtime) and system library, and a kernel layer from top to bottom.

The application layer may include a series of application packages.

As shown in fig. 9, the application package may include phone, camera, gallery, calendar, talk, map, navigation, WLAN, bluetooth, music, video, short message, etc. applications.

The application framework layer provides an Application Programming Interface (API) and a programming framework for the application program of the application layer. The application framework layer includes a number of predefined functions.

As shown in FIG. 9, the application framework layers may include a window manager, content provider, view system, phone manager, resource manager, notification manager, and the like.

The window manager is used for managing window programs. The window manager can obtain the size of the display screen, judge whether a status bar exists, lock the screen, intercept the screen and the like.

The content provider is used to store and retrieve data and make it accessible to applications. The data may include video, images, audio, calls made and received, browsing history and bookmarks, phone books, etc.

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

The telephone manager is used for providing a communication function of the terminal equipment. Such as management of call status (including on, off, etc.).

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

The notification manager enables the application to display notification information in the status bar, can be used to convey notification-type messages, can disappear automatically after a short dwell, and does not require user interaction. Such as a notification manager used to inform download completion, message alerts, etc. The notification manager may also be a notification that appears in the form of a chart or scroll bar text at the top status bar of the system, such as a notification of a background running application, or a notification that appears on the screen in the form of a dialog window. For example, text information is prompted in the status bar, a prompt tone is given, the terminal device vibrates, an indicator light flickers, and the like.

The Android Runtime comprises a core library and a virtual machine. The Android runtime is responsible for scheduling and managing an Android system.

The core library comprises two parts: one part is a function which needs to be called by java language, and the other part is a core library of android.

The application layer and the application framework layer run in a virtual machine. And executing java files of the application program layer and the application program framework layer into a binary file by the virtual machine. The virtual machine is used for performing the functions of object life cycle management, stack management, thread management, safety and exception management, garbage collection and the like.

The system library may include a plurality of functional modules. For example: surface managers (surface managers), media Libraries (Media Libraries), three-dimensional graphics processing Libraries (e.g., openGL ES), 2D graphics engines (e.g., SGL), and the like.

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

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

The three-dimensional graphic processing library is used for realizing three-dimensional graphic drawing, image rendering, synthesis, layer processing and the like.

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

The kernel layer is a layer between hardware and software. The inner core layer at least comprises a display driver, a camera driver, an audio driver and a sensor driver.

Reference in the specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one example embodiment 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 particular computer or other apparatus. Various general-purpose systems may also be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialized apparatus to perform one or more method steps. The structure for a variety of these systems is discussed in the description that follows. In addition, any particular programming language sufficient to implement the techniques and embodiments of the present disclosure may be used. Various programming languages may be used to implement the present disclosure as discussed herein.

Moreover, the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the disclosed subject matter. Accordingly, the present disclosure is intended to be illustrative, but not limiting, of the scope of the concepts discussed herein.

Claims

1. A method of monitoring usage of a wearable electronic device, comprising:

acquiring sleep monitoring data of the wearable electronic device during sleep of a user;

determining the reason of the sleep monitoring data with abnormal monitoring quality under the condition that the sleep monitoring data with abnormal monitoring quality exists in the sleep monitoring data, wherein the reason comprises the following steps: under the condition that the tightness degree of the wearable electronic device worn by the user during the sleeping period meets the measurement requirement and the action amplitude or action frequency of the wearable electronic device worn by the user during the sleeping period does not influence the monitoring quality, determining that the reason is that the wearable electronic device is pressed during the sleeping period of the user;

based on the reason, prompt information for prompting a user to improve monitoring quality of the wearable electronic device during sleep of the user is determined.

2. The method of claim 1, wherein the reason for the presence of sleep monitoring data for monitoring quality anomalies includes at least one of:

the tightness degree of the wearable electronic equipment worn by the user during sleeping does not meet the measurement requirement;

the monitoring quality is influenced by the action amplitude or action frequency of the user wearing the wearable electronic equipment during sleep;

the wearable electronic device is subject to being crushed during sleep of the user.

3. The method of claim 2, wherein determining, based on the reason, prompting information for prompting a user to improve monitoring quality of the wearable electronic device during sleep of the user comprises at least one of:

in the case that the reason is determined that the degree of tightness of the wearable electronic equipment worn by the user during sleep does not meet the measurement requirement, determining prompt information for improving monitoring quality as prompt information about correct wearing of the wearable electronic equipment;

determining prompt information for improving the monitoring quality as prompt information about stable sleep under the condition that the reason is determined that the monitoring quality is influenced by the action amplitude or the action frequency when the user wears the wearable electronic equipment during the sleep;

in a case where it is determined that the reason is that the wearable electronic device is pressed during the sleep of the user, determining the prompt information for improving the monitoring quality as the prompt information about the advice of the wearing part.

4. The method of claim 2 or 3, wherein the determining a cause of the presence of sleep monitoring data for the monitoring quality anomaly comprises:

determining that the reason is that the tightness degree of the wearable electronic equipment worn by the user during the sleep period is greater than the tightness degree which meets the measurement requirement under the condition that the monitoring quality of the sleep monitoring data of the screen of the wearable electronic equipment worn by the user under different orientations is normal and abnormal;

and under the condition that the monitoring quality of the sleep monitoring data of the screen of the wearable electronic equipment worn by the user in different directions is only abnormal, determining that the reason is that the tightness degree of the wearable electronic equipment worn by the user during the sleep is a tightness degree which is tightly closer to the tightness degree meeting the measurement requirement.

5. The method of claim 2 or 3, wherein the wearable electronic device comprises a pressure sensor and a display screen, the pressure sensor being located inside the display screen of the wearable electronic device; and is provided with

The determining that the reason for the sleep monitoring data with the abnormal monitoring quality comprises:

and judging whether the reason of the sleep monitoring data with abnormal monitoring quality is that the tightness degree of the wearable electronic equipment worn by the user in the sleep period does not meet the measurement requirement according to the pressure monitoring data of the pressure sensor.

6. The method of claim 2 or 3, wherein the wearable electronic device comprises an acceleration sensor, and wherein the wearable electronic device comprises a wearable electronic device

7. The method of any of claims 1 to 6, further comprising:

and judging whether the sleep monitoring data with abnormal monitoring quality exists according to the fluctuation condition of the data of the photoplethysmography sensor and/or the fluctuation condition of the measurement data of the acceleration sensor in the acquired sleep monitoring data.

8. The method of claim 1, further comprising:

displaying the determined prompt message for prompting the user to improve the monitoring quality of the wearable electronic device during the user's sleep.

9. The method of claim 1, wherein the obtaining sleep monitoring data of the wearable electronic device during sleep of a user comprises:

receiving the sleep monitoring data from the wearable electronic device.

10. The method of claim 1, further comprising:

sending the determined prompt information for prompting the user to improve the monitoring quality of the wearable electronic device during the sleep period of the user outwards.

11. A method of monitoring usage of a wearable electronic device, comprising:

the wearable electronic device sends sleep monitoring data of the wearable electronic device during sleep of a user, wherein the sleep monitoring data with abnormal monitoring quality exist in the sleep monitoring data, and the sleep monitoring data with abnormal monitoring quality is used for determining the reason of the sleep monitoring data with abnormal monitoring quality, and the method comprises the following steps: under the condition that the tightness degree of the wearable electronic device worn by the user during the sleeping period meets the measurement requirement and the action amplitude or action frequency of the wearable electronic device worn by the user during the sleeping period does not influence the monitoring quality, determining that the reason is that the wearable electronic device is pressed during the sleeping period of the user;

the wearable electronic device receives prompting information for prompting a user to improve monitoring quality of the wearable electronic device during sleep of the user.

12. The method of claim 11, the wearable electronic device receiving prompting information for prompting a user to improve monitoring quality of the wearable electronic device during a user's sleep comprising at least one of:

prompt information regarding proper wearing of the wearable electronic device;

prompt information about stable sleep;

a suggested reminder information about the wearing location.

13. A readable medium of an electronic device, characterized in that the readable medium has stored thereon instructions which, when executed on the electronic device, cause the electronic device to perform the method of any one of claims 1 to 12.

14. An electronic device, comprising: a memory for storing instructions for execution by one or more processors of an electronic device, and the processor, being one of the processors of the electronic device, for performing the method of any one of claims 1 to 12.

15. An electronic device, comprising: a memory, a processor, a photoplethysmography sensor, and an acceleration sensor;

the photoplethysmography sensor to acquire photoplethysmography sensor data of a user of the electronic device during sleep;

the acceleration sensor is used for acquiring monitoring data of the acceleration sensor of a user of the electronic equipment during sleep;

the memory is to store instructions for execution by one or more of the processors of an electronic device;

the processor, being one of processors of an electronic device, configured to perform the method of any one of claims 1 to 12.

16. An electronic device, comprising: the device comprises a memory, a processor, a display screen, a photoplethysmography sensor, a pressure sensor and an acceleration sensor;

the photoplethysmography sensor is to acquire photoplethysmography data of a user of the electronic device during sleep;

the acceleration sensor is used for acquiring monitoring data of the acceleration sensor during the sleep period of a user of the electronic equipment;

the display screen is used for displaying prompt information for prompting a user to improve monitoring quality of the wearable electronic equipment during sleep of the user;

the pressure sensor is positioned on the inner side of the display screen and used for detecting the tightness degree of the electronic equipment worn by a user;