WO2018090532A1 - Accurate monitoring method and apparatus for user growth data - Google Patents

Abstract

An accurate monitoring method for growth data of a user, comprising: acquiring attribute data of a user, and recording status data of the user in real-time according to said attribute data, wherein said status data comprises dietary data and/or movement data and/or sleep data; searching for standard data corresponding to the attribute data of said user at a current time from within a data server; and comparing recorded dietary data and/or movement data and/or sleep data to said standard data, and detecting whether the user data meets preset requirements according to a comparison result. The data collected by the present method and the data subjected to comparison are real-time data, and comparison may be conducted automatically, thus making operation more convenient and accuracy in monitoring higher.

Description

Method and device for accurately monitoring user growth data Technical field

The invention belongs to the field of data monitoring, and in particular relates to an accurate monitoring method and device for user growth data.

Background technique

Parents are very concerned about the growth of their children as they grow up. For example, it will pay attention to whether the child's diet is reasonable, or whether the child's daily activities can meet the normal exercise requirements. Therefore, it is possible to find out the nutritional deficiency that the child may have according to the diet, or to judge whether the child is underactive according to the amount of exercise.

In order to get the relevant data of the children, parents often need to spend a lot of time and energy to count. And after getting the statistical data, it is also necessary to ask the professional doctor or expert from time to time whether the data can meet the normal needs. Therefore, the current method of monitoring data for children, or users of other groups, is more cumbersome, and when recording or judging, the accuracy of monitoring may be affected by subjective factors.

Summary of the invention

The object of the present invention is to provide an accurate monitoring method for user growth data, so as to solve the problem that the prior art monitors the user's data, and the monitoring is troublesome and the accuracy is not high.

In a first aspect, an embodiment of the present invention provides an accurate monitoring method for user growth data, where the method includes:

Obtaining attribute data of the user, according to the attribute data, real-time recording of status data of the user, the status data including diet data and/or exercise data and/or sleep data;

Finding, in the data server, standard data corresponding to the attribute data of the user at the current time;

Recording the recorded diet data and/or exercise data and/or sleep data against the standard data Compared, according to the comparison result, it is detected whether the user's data meets the preset requirements.

In conjunction with the first aspect, in a first possible implementation of the first aspect, the attribute data of the user includes one or more of a location where the user is located, an age of the user, a gender of the user, and a career of the user.

With reference to the first aspect, in a second possible implementation manner of the first aspect, the step of searching for the standard data corresponding to the attribute data of the user in the data server at the current time includes:

Searching, in the data server, the dietary data and/or the athletic data and/or the sleep data of the plurality of users corresponding to the attribute data at the current time according to the attribute data of the user;

The plurality of users searched for the current time's diet data and/or exercise data and/or sleep data are averaged to obtain standard data corresponding to the user's attribute data at the current time.

In conjunction with the first aspect, the first possible implementation of the first aspect, the second possible implementation of the first aspect, in a third possible implementation of the first aspect, the dietary data to be recorded and/or The steps of comparing the athletic data and/or sleep data with the standard data include:

Converting the user's diet data into corresponding nutrient element values according to a preset correspondence between food and calories, and/or according to a preset correspondence between exercise type, exercise time and calorie consumption Translating the user's exercise data into a corresponding calorie value, and/or converting the user's eye sleep data into a corresponding sleep score according to a correspondence between sleep quality, sleep duration and sleep score;

The user's nutrient value and/or the user's calorie value and/or the user's sleep score are compared to the nutrient element value and/or calorie value and/or sleep score in the standard data.

With reference to the first aspect, the first possible implementation manner of the first aspect, and the second possible implementation manner of the first aspect, in the fourth possible implementation manner of the first aspect, the step of recording the user's diet data in real time includes: :

Obtaining a picture of the food taken by the user terminal, and identifying the content of the food and the serving size of the food according to the feature information of the picture;

Alternatively, the step of recording the user's motion data in real time includes:

Record the type of user movement and the duration of the movement.

In a second aspect, an embodiment of the present invention provides an accurate monitoring device for user growth data, where the device includes:

a data acquisition unit, configured to acquire attribute data of the user, and record, according to the attribute data, status data of the user, where the status data includes diet data and/or exercise data and/or sleep data;

a data search unit, configured to search, in the data server, standard data corresponding to the attribute data of the user at the current time;

The data comparison unit is configured to compare the recorded diet data and/or the motion data and/or the sleep data with the standard data, and detect, according to the comparison result, whether the user's data meets a preset requirement.

With reference to the second aspect, in a first possible implementation manner of the second aspect, the attribute data of the user includes one or more of a location where the user is located, an age of the user, a gender of the user, and a career of the user.

With reference to the second aspect, in a second possible implementation manner of the second aspect, the data searching unit includes:

a multi-user data search sub-unit, configured to search, in the data server, the diet data and/or the motion data and/or the sleep data of the plurality of users corresponding to the attribute data at the current time according to the attribute data of the user;

The average sub-unit is configured to average the diet data and/or the motion data and/or the sleep data of the plurality of users at the current time to obtain standard data corresponding to the attribute data of the user at the current time.

With reference to the second aspect, the first possible implementation manner of the second aspect, and the second possible implementation manner of the second aspect, in a third possible implementation manner of the second aspect, the data comparison unit includes:

a conversion subunit, configured to convert the user's diet data into a corresponding nutrient element value according to a preset correspondence between food and calories, and/or according to a preset exercise type, exercise time, and calorie consumption Corresponding relationship, converting the user's exercise data into a corresponding calorie value, and/or converting the user's eye sleep data into a corresponding sleep score according to a correspondence between sleep quality, sleep duration and sleep score;

Comparing subunits for using the user's nutrient value and/or user calorie value and/or user The sleep score is compared to the nutrient value and/or calorie value and/or sleep score in the standard data.

With reference to the second aspect, the first possible implementation manner of the second aspect, and the second possible implementation manner of the second aspect, in a fourth possible implementation manner of the second aspect, the data acquiring unit includes:

a first obtaining subunit, configured to acquire a picture of the user's terminal to take a diet, and identify the content of the food and the serving size of the food according to the feature information of the picture;

Alternatively, a second acquisition sub-unit is used to record the type of user motion and the duration of the motion.

In the present invention, by acquiring the attribute data of the user and recording the user's diet data and/or motion data and/or sleep data in real time by the user's terminal, the attribute data of the user can be used to search and search in the data server. The standard data corresponding to the attribute data of the user, and the standard data is standard data of the current time, and the recorded user's diet data and/or motion data and/or sleep data are compared with the current time standard data, and may be real-time. The user's data is checked according to the preset requirements. Since the data collected by the present invention and the compared data are real-time data and can be automatically compared, the operation is more convenient and the detection accuracy is higher.

DRAWINGS

1 is a flowchart of implementing an accurate monitoring method for user growth data according to a first embodiment of the present invention;

2 is a flowchart of implementing an accurate monitoring method for user growth data according to a second embodiment of the present invention;

3 is a flowchart of implementing an accurate monitoring method for user growth data according to a third embodiment of the present invention;

4 is a schematic structural diagram of an apparatus for accurately monitoring user growth data according to a fourth embodiment of the present invention;

FIG. 5 is a schematic structural diagram of an accurate monitoring terminal for user growth data according to a fifth embodiment of the present invention.

detailed description

The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

The purpose of the embodiments of the present invention is to provide an accurate monitoring method and device for user growth data, so as to solve the problem in the prior art, in order to monitor the user's life or growth data, the user often needs to find a physical abnormality that may occur in the user. The user's data is recorded, and due to the lack of record standards, the recorded data is greatly affected by personal subjective factors, and the accuracy of the data record is not high. When judging according to the recorded data, it is often necessary to record for a period of time before consulting with a doctor or an expert, and data detection is troublesome. Moreover, due to the subjective judgment of the user, the user's data abnormality cannot be found in time, and the possible problems cannot be noticed as early as possible. The invention will now be further described with reference to the accompanying drawings.

Embodiment 1:

FIG. 1 is a flowchart showing an implementation process of an accurate monitoring method for user growth data according to a first embodiment of the present invention, which is described in detail as follows:

In step S101, attribute data of the user is acquired, and according to the attribute data, status data of the user is recorded in real time, and the status data includes diet data and/or exercise data and/or sleep data.

Specifically, the user of the present invention can collect required data by means of an intelligent terminal, for example, by means of smart phone input, or by combining a smart phone with a data acquisition device such as a smart bracelet to obtain attribute data and status data of the user. . After obtaining the user's state data and attribute data, the data may be sent to the data server for query, and the result data of the query may be returned.

Specifically, the attribute data of the user in the embodiment of the present invention may include one or more of a location where the user is located, an age of the user, a gender of the user, and a career of the user.

The location where the user is located may be the city where the user is located, or the area or street where the user is located. Through the location of the user included in the attribute data of the user, the corresponding standard data can be set according to the location of the user, so that the comparison of the user state data is more accurate. Like the user is at In the city A, when the standard data is searched and compared, the city A is searched for the status data of other users having the same current user attribute.

The age of the user, depending on the age group, uses different precision ranges. For example, it is possible to adopt a method in which the range of accuracy is gradually reduced as the age increases. For example, for newborn children, when monitoring their sleep data, the age range can be the exact number of days or months in the age. For adolescents, the age range can be determined to the specific age, and for adults, a larger age range can be collected as the user's age.

The gender of the user generally includes males and females. Due to different genders, the user's status data is different. For example, in the adolescent stage, the boy's development time is often later than that of the girl, so the user's status data, such as height data, will be different. In addition, there will be differences in the amount of exercise data between men and women in the adolescent stage.

The occupation of the user is generally directed to an adult user. For users of different occupations, the corresponding status data will be different. For example, white-collar users who sit at a desk for a long time are more focused on the monitoring of motion data in the state data, and for users who need to work day and night, the monitoring of the user's sleep data is emphasized.

In the real-time recording step of the user's status data, the real-time recording therein makes the recording of the user data more timely. Compared with the manner in which the user records the consultation after half a year in the prior art, the collection record of the user data state of the present invention may include data collection of each user meal, accurate to the motion data of each minute or every second. Acquisition or collection of sleep data. Automatic analysis of data collected in real time can effectively improve the convenience of data analysis and recording. In particular, compared with the prior art, the acquisition of the data of the present invention is more accurate than the manner in which data is reviewed after waiting for problems.

The status data may include one or more of diet data, exercise data, and sleep data. Of course, it is not necessarily limited thereto, and the user's state data may also include the user's height, weight, vision, skin color, and the like.

The dietary data may include the portion of the user's diet, the type of diet, and the like. That is the weight of the diet. For example, if the user eats a steamed bun, the type of the user's diet may be a pasta. The serving size may be about 200 g. When the user eats a green vegetable bun, the type of the user's diet may include the pasta and the green vegetables, and the pasta is 120 g. The serving size of green vegetables is 5g.

The motion data may include the type of user motion and/or the duration of the motion type. For example, if the user walks for 1 km, the user's motion type may be recorded as walking, and the duration of the motion may be 20 minutes. The type of exercise may include walking, running, kicking, swimming, playing basketball, and the like. Depending on the type of exercise, the amount of heat consumed per unit time will vary. Similarly, for the same type of exercise, the amount of heat consumed is different for different durations.

The sleep data may include the depth of sleep and the duration of sleep at a certain depth of sleep. By combining the sleep concentration and the sleep duration, it can be converted into the score of the user's sleep. For example, under the first deep sleep condition, the user can get a sleep score of 90 points when the sleep time is 6 hours, and under the second sleep depth condition, The sleep score of 8 hours into sleep is 95 points. Under normal circumstances, the deeper the depth of sleep under the same sleep duration, the higher the score of the obtained sleep score. Correspondingly, under the same sleep depth condition, the longer the sleep duration, the higher the sleep score. However, depending on the user, the sleep duration also corresponds to the sleep duration limit. For example, adults should not sleep more than 10 hours a day.

In step S102, standard data corresponding to the attribute data of the user at the current time is searched in the data server.

Specifically, the data server is configured to connect multiple user terminals, receive data collected by the user terminal, analyze the collected data, and provide corresponding analysis results, and send the data to the user terminal. Alternatively, the data server may also receive a data query request of the terminal, for example, query standard data corresponding to the attribute data of the user, and return the query result to the terminal, where the terminal analyzes or reminds. Moreover, in the present invention, a correspondence table of attribute data and state data is pre-stored in the data server, and the correspondence between the attribute data and the state data in the data server can be updated in real time as the acquired data is acquired. . For example, updating the correspondence between the age of the user and the height.

The standard data may be different from the manner in which the collected state data of the user is described. For example, for dietary data, the collected status data is a defined rice and two meats, and the standard data can be a demand for various nutrients. Therefore, the diet data in the user's state data can be converted into the same description method as the standard data by means of conversion. Of course, the motion data, the sleep data, or other state data in the state data can also be converted in a manner that facilitates comparison between the two.

The standard data can be automatically updated and calculated by the server to obtain the standard data. For example, the current server collects the status data of 10000 users, and updates the status data correspondingly to the standard data corresponding to the attribute data according to the attribute data of 10000 users. The update method may calculate the average value of the state data corresponding to the attribute data of the specific user as the updated standard data within the predetermined duration range of the current time as the end date.

Of course, the standard data may also adopt other real-time update manners, so that the standard data has high precision.

In step S103, the recorded diet data and/or exercise data and/or sleep data are compared with the standard data, and based on the comparison result, it is detected whether the user's data meets the preset requirement.

The status data to be compared differs depending on the user attribute data. According to the attribute data of the user, the status data that the user needs to compare can be obtained. And obtaining standard data corresponding to the attribute data from the data server according to the attribute data of the user, comparing the status data of the user with the standard data, and determining whether the data of the user meets the preset requirement. Since the changes in the state data of the body are more pronounced during the growth of adolescents or children, the method of the present invention is particularly suitable for adolescent or child users.

The preset requirement can be determined by standard data and a specific fluctuation range. For example, when the collected user's state data is within the fluctuation range of the preset standard data, it indicates that the user's data meets the preset requirements. And the detection result can be sent to the user terminal. Or it is possible to give advice combined with the user's attribute data and status data. This includes, but is not limited to, dietary advice, exercise advice, and sleep advice.

The embodiment of the present invention can obtain the user's attribute data, and the user's terminal records the user's diet data and/or motion data and/or sleep data in real time, and can search for the user in the data server through the attribute data of the user. The standard data corresponding to the attribute data, and the standard data is the standard data of the current time, and the recorded user's diet data and/or exercise data and/or sleep data are compared with the current time standard data, and can be viewed in real time. Whether the user's data meets the preset requirements, because the data collected by the present invention and the compared data are real-time data, and can be automatically compared, the operation is more convenient and the detection accuracy is higher.

Embodiment 2:

FIG. 2 is a flowchart showing an implementation process of an accurate monitoring method for user growth data according to a second embodiment of the present invention, which is described in detail as follows:

In step S201, attribute data of the user is acquired, and status data of the user is recorded in real time according to the attribute data, and the status data includes diet data and/or exercise data and/or sleep data.

In step S202, according to the attribute data of the user, the data server searches for the diet data and/or the motion data and/or the sleep data of the plurality of users corresponding to the attribute data at the current time.

Specifically, the attribute data of the user may include attribute data of one or more different important levels. In the normal case, other attribute data of the user may be determined according to the age of the user, for example, according to the age of the user, the other attribute data that needs to be determined includes the gender of the user. When the age of the user is a child, it is determined that other attribute data includes the gender of the user, the location of the user, and the like. When the age of the user is an adult, it is determined that other attribute data includes the occupation of the user, the gender of the user, the location of the user, and the like.

The attribute data of the determined user can be established, and the corresponding status data is matched accordingly. The matching process may be performed by a preset matching relationship table in which the state data corresponding to the different attribute data is set. For example, the status data required by the newborn includes sleep data, height data, and weight data. Dietary data can also be included when the newborn reaches the age of eating complementary food.

The data server can collect a large number of user data at the same time, and the data collection manner can be run in the user terminal in real time through a mobile phone APP, and the user terminal of a large number of users is collected. Status data.

In step S203, the plurality of searched users are averaged the diet data and/or the exercise data and/or the sleep data at the current time, and the standard data corresponding to the attribute data of the user at the current time is obtained.

Among the collected large amount of state data, data of other users other than the user's own data that needs to be compared may be classified according to the attributes of the user, and a set of state data of different user attributes is obtained. Then, an average value is calculated for the set of state data of the users of different attributes, and the current time corresponding standard data is obtained. The calculation of the average value may be different according to the calculated state data, and different periods or time points may be selected. For example, for the height, the current time point may be taken, and for the sleep data and the motion data, the calculation may be performed in the day period. .

The standard data can be represented by a common unit or format. For dietary data, it can be expressed by the type of nutrients and nutrients included in the diet, such as vitamin C, protein or other minerals included in the diet. For the motion data, it can be expressed uniformly by the calorie consumption value. For sleep data, it can be represented by setting a uniform sleep score value.

In step S204, the recorded diet data and/or exercise data and/or sleep data are compared with the standard data, and based on the comparison result, it is detected whether the user's data meets the preset requirement.

This step is substantially the same as step S103 in the first embodiment, and details are not described herein again.

The present invention compares the acquired state data with the standard data corresponding to the attributes of the user updated in real time, and thus the compared object is more accurate and time-sensitive. And the comparison result can be obtained in real time, so that the user can find abnormal data more timely, and the user can take measures more effectively for the abnormality.

Embodiment 3:

FIG. 3 is a flowchart showing an implementation process of an accurate monitoring method for user growth data according to a third embodiment of the present invention, which is described in detail as follows:

In step S301, attribute data of the user is acquired.

In step S302, according to the attribute data of the user, acquiring a picture of the user terminal photographing the diet, identifying the content of the food, and the serving size of the food according to the characteristic information of the picture, or This includes the type of user movement and the duration of the movement.

Specifically, the diet data of the user attribute data in the embodiment of the present invention may be acquired by using a camera. An image of the diet may be pre-different in the user terminal or the data server, and the image is calibrated by the feature information of the image.

When the user needs to dine, the food of the meal can be photographed by the camera of the user terminal, and the feature information of the captured picture is extracted by the user terminal or the data server, and compared with the feature information stored in advance, thereby obtaining the name of the food or The nutrients contained in the food.

In addition, you can also get the amount of food according to the container in the picture. Or the name of the food and the portion of the food may also be manually entered by the user.

In step S303, standard data corresponding to the attribute data of the user at the current time is searched in the data server.

In step S304, the recorded diet data and/or exercise data and/or sleep data are compared with the standard data, and based on the comparison result, it is detected whether the user's data meets the preset requirement.

Corresponding to step S302, the step of comparing the recorded dietary data and/or athletic data and/or sleep data with the standard data may include:

Converting the user's diet data into corresponding nutrient element values according to a preset correspondence between food and calories, and/or according to a preset correspondence between exercise type, exercise time and calorie consumption Translating the user's exercise data into a corresponding calorie value, and/or converting the user's eye sleep data into a corresponding sleep score according to a correspondence between sleep quality, sleep duration and sleep score;

The user's nutrient value and/or the user's calorie value and/or the user's sleep score are compared to the nutrient element value and/or calorie value and/or sleep score in the standard data.

On the basis of the first embodiment, the embodiment of the present invention further acquires the user's state data, and automatically obtains the user's diet data by taking a photo. In addition, in order to prevent the user from forgetting the data acquisition, the user terminal of the present invention can also set the odor sensor, and when a predetermined scent is detected, a shooting reminder is issued, thereby further improving the convenience of data collection.

Embodiment 4:

FIG. 4 is a schematic structural diagram of an apparatus for accurately monitoring user growth data according to a fourth embodiment of the present invention, which is described in detail as follows:

The user monitoring device of the embodiment of the invention includes:

The data obtaining unit 401 is configured to acquire attribute data of the user, and record, according to the attribute data, status data of the user, where the status data includes diet data and/or exercise data and/or sleep data;

The data searching unit 402 is configured to search, in the data server, standard data corresponding to the attribute data of the user at the current time;

The data comparison unit 403 is configured to compare the recorded diet data and/or the motion data and/or the sleep data with the standard data, and detect, according to the comparison result, whether the user's data meets a preset requirement.

Preferably, the attribute data of the user includes one or more of a location where the user is located, an age of the user, a gender of the user, and a career of the user.

Preferably, the data search unit comprises:

a multi-user data search sub-unit, configured to search, in the data server, the diet data and/or the motion data and/or the sleep data of the plurality of users corresponding to the attribute data at the current time according to the attribute data of the user;

The average sub-unit is configured to average the diet data and/or the motion data and/or the sleep data of the plurality of users at the current time to obtain standard data corresponding to the attribute data of the user at the current time.

Preferably, the data comparison unit comprises:

a conversion subunit, configured to convert the user's diet data into a corresponding nutrient element value according to a preset correspondence between food and calories, and/or according to a preset exercise type, exercise time, and calorie consumption Corresponding relationship, converting the user's exercise data into a corresponding calorie value, and/or converting the user's eye sleep data into a corresponding sleep score according to a correspondence between sleep quality, sleep duration and sleep score;

A comparison subunit for comparing the nutrient value of the user and/or the calorie value of the user and/or the sleep score of the user with a nutrient element value and/or a calorie value and/or a sleep score in the standard data.

Preferably, the data acquisition unit includes:

a first obtaining subunit, configured to acquire a picture of the user's terminal to take a diet, and identify the content of the food and the serving size of the food according to the feature information of the picture;

Alternatively, a second acquisition sub-unit is used to record the type of user motion and the duration of the motion.

The device for accurately monitoring user growth data according to the embodiment of the present invention corresponds to the data monitoring method described in Embodiments 1 to 3, and details are not described herein again.

Embodiment 5

FIG. 5 is a structural block diagram of a monitoring terminal according to a fifth embodiment of the present invention. The monitoring terminal of the embodiment includes: an RF circuit 510, a memory 520, an input unit 530, a display unit 540, an audio circuit 560, and a network module 570. Processor 580, and components such as power supply 590. It will be understood by those skilled in the art that the terminal structure shown in FIG. 5 does not constitute a limitation to the terminal, and may include more or less components than those illustrated, or a combination of certain components, or different component arrangements.

The following describes the components of the terminal in conjunction with Figure 5:

The memory 520 can be used to store software programs and modules, and the processor 580 executes various functional applications and data processing of the terminals by running software programs and modules stored in the memory 520. The memory 520 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application required for at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may be stored according to Data created by the use of the terminal (such as audio data, phone book, etc.). Moreover, memory 520 can include high speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The input unit 530 can be configured to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the terminal. Specifically, the input unit 530 may include a touch panel 531 and other input devices 532. The touch panel 531, also referred to as a touch screen, can collect touch operations on or near the user (such as the user using a finger, a stylus, or the like on the touch panel 531 or near the touch panel 531. Operation) and drive according to a preset program Connection device. Optionally, the touch panel 531 can include two parts: a touch detection device and a touch controller. Wherein, the touch detection device detects the touch orientation of the user, and detects a signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts the touch information into contact coordinates, and sends the touch information. The processor 580 is provided and can receive commands from the processor 580 and execute them. In addition, the touch panel 531 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic waves. In addition to the touch panel 531, the input unit 530 may also include other input devices 532. Specifically, other input devices 532 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control buttons, switch buttons, etc.), trackballs, mice, joysticks, and the like.

The display unit 540 can be used to display information input by the user or information provided to the user as well as various menus of the terminal. The display unit 540 can include a display panel 541. Alternatively, the display panel 541 can be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like. Further, the touch panel 531 can cover the display panel 541. When the touch panel 531 detects a touch operation on or near it, the touch panel 531 transmits to the processor 580 to determine the type of the touch event, and then the processor 580 according to the touch event. The type provides a corresponding visual output on display panel 541. Although the touch panel 531 and the display panel 541 are used as two independent components to implement the input and input functions of the terminal in FIG. 5, in some embodiments, the touch panel 531 may be integrated with the display panel 541. Realize the input and output functions of the terminal.

Audio circuit 560, speaker 561, and microphone 562 can provide an audio interface between the user and the terminal. The audio circuit 560 can transmit the converted electrical data of the received audio data to the speaker 561, and convert it into a sound signal output by the speaker 561. On the other hand, the microphone 562 converts the collected sound signal into an electrical signal, and the audio circuit 560 is used by the audio circuit 560. After receiving, it is converted into audio data, and then processed by the audio data output processor 580, sent to the other terminal via the network module 510, or output the audio data to the memory 520 for further processing.

The network module 570 can include a wireless fidelity (WiFi) module, a wired network module or a radio frequency module, wherein the wireless fidelity module belongs to a short-range wireless transmission technology, and the terminal can help the user to send and receive e-mails, browse web pages, and Access streaming media, etc., it Provide users with wireless broadband Internet access. Although FIG. 5 shows the network module 570, it can be understood that it does not belong to the necessary configuration of the terminal, and can be omitted as needed within the scope of not changing the essence of the invention.

The processor 580 is the control center of the terminal, and connects various parts of the entire terminal using various interfaces and lines, by executing or executing software programs and/or modules stored in the memory 520, and calling data stored in the memory 520, executing The terminal's various functions and processing data, so as to monitor the terminal as a whole. Optionally, the processor 580 may include one or more processing units; preferably, the processor 580 may integrate an application processor and a modem processor, where the application processor mainly processes an operating system, a user interface, an application, and the like. The modem processor primarily handles wireless communications. It will be appreciated that the above described modem processor may also not be integrated into the processor 580.

The terminal also includes a power source 590 (such as a battery) that supplies power to the various components. Preferably, the power source can be logically coupled to the processor 580 through a power management system to manage functions such as charging, discharging, and power management through the power management system.

Although not shown, the terminal may further include a camera, a Bluetooth module, and the like, and details are not described herein again.

In the embodiment of the present invention, the processor 580 included in the terminal further has the following functions: performing attribute data of acquiring a user, and recording status data of the user in real time according to the attribute data, where the status data includes diet data and/or Motion data and/or sleep data; searching for data of the user's attribute data corresponding to the current time in the data server; comparing the recorded diet data and/or exercise data and/or sleep data with the standard data, A program for detecting whether the user's data meets the preset requirements based on the comparison result.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be Electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, or all or part of the technical solution, may be embodied in the form of a software product stored in a storage medium. A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the methods described in various embodiments of the present invention. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .

The above is only the preferred embodiment of the present invention, and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection of the present invention. Within the scope.

Claims (10)

An accurate monitoring method for user growth data, characterized in that the method comprises: Obtaining attribute data of the user, according to the attribute data, real-time recording of status data of the user, the status data including diet data and/or exercise data and/or sleep data; Finding, in the data server, standard data corresponding to the attribute data of the user at the current time; The recorded diet data and/or exercise data and/or sleep data are compared with the standard data, and the user's data is detected according to the comparison result to meet the preset requirements. The method according to claim 1, wherein the attribute data of the user includes one or more of a location where the user is located, an age of the user, a gender of the user, and a career of the user. The method according to claim 1, wherein the step of searching for the standard data corresponding to the attribute data of the user in the data server at the current time comprises: Searching, in the data server, the dietary data and/or the athletic data and/or the sleep data of the plurality of users corresponding to the attribute data at the current time according to the attribute data of the user; The plurality of users searched for the current time's diet data and/or exercise data and/or sleep data are averaged to obtain standard data corresponding to the user's attribute data at the current time. The method according to any one of claims 1 to 3, wherein the step of comparing the recorded dietary data and/or athletic data and/or sleep data with the standard data comprises: Converting the user's diet data into corresponding nutrient element values according to a preset correspondence between food and calories, and/or according to a preset correspondence between exercise type, exercise time and calorie consumption Translating the user's exercise data into a corresponding calorie value, and/or converting the user's eye sleep data into a corresponding sleep score according to a correspondence between sleep quality, sleep duration and sleep score; The user's nutrient value and/or the user's calorie value and/or the user's sleep score are compared to the nutrient element value and/or calorie value and/or sleep score in the standard data. The method according to any one of claims 1 to 3, wherein the step of recording the user's dietary data in real time comprises: Obtaining a picture of the food taken by the user terminal, and identifying the content of the food and the serving size of the food according to the feature information of the picture; Alternatively, the step of recording the user's motion data in real time includes: Record the type of user movement and the duration of the movement. An accurate monitoring device for user growth data, characterized in that the device comprises: a data acquisition unit, configured to acquire attribute data of the user, and record, according to the attribute data, status data of the user, where the status data includes diet data and/or exercise data and/or sleep data; a data search unit, configured to search, in the data server, standard data corresponding to the attribute data of the user at the current time; The data comparison unit is configured to compare the recorded diet data and/or the motion data and/or the sleep data with the standard data, and detect, according to the comparison result, whether the user's data meets a preset requirement. The apparatus according to claim 6, wherein the attribute data of the user includes one or more of a location where the user is located, an age of the user, a gender of the user, and a career of the user. The device according to claim 6, wherein the data search unit comprises: a multi-user data search sub-unit, configured to search, in the data server, the diet data and/or the motion data and/or the sleep data of the plurality of users corresponding to the attribute data at the current time according to the attribute data of the user; The average sub-unit is configured to average the diet data and/or the motion data and/or the sleep data of the plurality of users at the current time to obtain standard data corresponding to the attribute data of the user at the current time. The device according to any one of claims 6-8, wherein the data comparison unit comprises: a conversion subunit, configured to convert the user's diet data into a corresponding nutrient element value according to a preset correspondence between food and calories, and/or according to a preset exercise type, exercise time, and calorie consumption Corresponding relationship, converting the user's exercise data into a corresponding calorie value, and/or converting the user's eye sleep data into a corresponding sleep score according to a correspondence between sleep quality, sleep duration and sleep score; A comparison subunit for comparing the nutrient value of the user and/or the calorie value of the user and/or the sleep score of the user with a nutrient element value and/or a calorie value and/or a sleep score in the standard data. The device according to any one of claims 6-8, wherein the data acquisition unit comprises: a first obtaining subunit, configured to acquire a picture of the user's terminal to take a diet, and identify the content of the food and the serving size of the food according to the feature information of the picture; Alternatively, a second acquisition sub-unit is used to record the type of user motion and the duration of the motion.

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