Data processing method and device, electronic equipment and storage medium

Abstract

The invention provides a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of intelligent wearing, and the method comprises the steps: obtaining activity amount data and image data in a historical time period for a target object; wherein the image data is a heat source image of the target object during heat intake in a historical time period; determining a heat consumption difference of the target object in the historical time period based on the activity amount data, the physical parameters of the target object and the image data; wherein the calorie consumption difference represents the difference between the consumed calorie and the intake calorie of the target object in the historical time period; and determining weight management information based on the heat consumption difference and the physical parameters. In the embodiment of the invention, the intake calorie data can be accurately obtained through the image data. Meanwhile, a complete body weight management closed loop is formed in a mode of determining body weight management information through the heat consumption difference and the physical parameters of the target object, and the purpose of precise body weight management is achieved.

Description

Technical Field

[0001] The present application relates to the field of smart wearable technology, and in particular to a data processing method, device, electronic device and storage medium. Background Art

[0002] In the related art, the calorie intake data collected by existing wearable devices during weight management is user input data, and the user input data has the problem of poor accuracy. Therefore, the management information determined by the calorie data input by the user in the related art will have the problem of poor accuracy. Existing wearable devices only display the amount of calories consumed during weight management. This weight management method that only displays the amount of calories consumed has a large number of management loopholes, and cannot form a closed loop of weight management, and thus cannot achieve the purpose of precise weight management. Summary of the invention

[0003] The embodiments of the present application provide a data processing method, device, electronic device, and storage medium, which can improve the accuracy of weight management information and achieve the purpose of precise weight management.

[0004] The technical solution of this application is implemented as follows:

[0005] The present application provides a data processing method, including:

[0006] For the target object, activity data and image data in a historical period are obtained; wherein the image data is a heat source image of the target object when calorie intake occurs in the historical period;

[0007] Determine the calorie consumption difference of the target object in the historical period based on the activity data, the physical parameters of the target object and the image data; wherein the calorie consumption difference represents the difference between the calorie consumption and the calorie intake of the target object in the historical period;

[0008] Weight management information is determined based on the calorie expenditure difference and the physical fitness parameter.

[0009] The present application also provides a data processing device, including:

[0010] A data acquisition unit, for acquiring activity data and image data within a historical period for a target object; wherein the image data is a heat source image of the target object when calorie intake occurs within the historical period;

[0011] a determination unit, configured to determine a calorie consumption difference of the target object in the historical period based on the activity data, the physical parameters of the target object, and the image data; wherein the calorie consumption difference represents a difference between the calorie consumption and the calorie intake of the target object in the historical period;

[0012] The determination unit is further used to determine weight management information based on the calorie consumption difference and the physical parameter.

[0013] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and the processor implements the steps in the above method when executing the computer program.

[0014] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method are implemented.

[0015] In the embodiment of the present application, the activity data and image data in the historical period are obtained for the target object; wherein the image data is the heat source image of the target object when calorie intake in the historical period; the calorie consumption difference of the target object in the historical period is determined based on the activity data, the physical parameters of the target object and the image data; wherein the calorie consumption difference represents the difference between the calorie consumption and the calorie intake of the target object in the historical period; and the weight management information is determined based on the calorie consumption difference and the physical parameters. In the embodiment of the present application, the calorie intake data can be accurately obtained through the image data, and the calorie intake data obtained is more accurate than the method of obtaining the calorie data input by the user in the related art. Moreover, when determining the calorie consumption difference, not only the activity data and image data are taken into account, but also the physical parameters of the target object are taken into account, eliminating the error of the calorie consumption difference caused by individual differences, and the accuracy of the determined calorie consumption difference is also higher. At the same time, the method of determining the weight management information by the calorie consumption difference and the physical parameters of the target object is determined from the perspective of calorie intake and calorie consumption, forming a complete weight management closed loop, and achieving the purpose of accurate weight management. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0017] Figure 2 An optional effect diagram of the data processing method provided in the embodiment of the present application;

[0018] Figure 3 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0019] Figure 4 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0020] Figure 5 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0021] Figure 6 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0022] Figure 7 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0023] Figure 8 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0024] Fig. 9 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0025] Fig.10 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0026] Fig.11 An optional flowchart of a data processing method provided in an embodiment of the present application;

[0027] Fig.12 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application;

[0028] Fig.13 A hardware entity schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions of the present application are further elaborated in detail below in conjunction with the drawings and embodiments. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0030] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0031] If similar descriptions of "first / second" appear in the application documents, the following instructions are added. In the following description, the terms "first\second\third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0033] In the related technology, existing smart wearable devices can realize the collection of human calorie consumption, but the existing wearable devices only collect dynamic calorie consumption, and do not combine calorie intake and static calorie consumption to form a closed loop of weight management. Due to weight management, such as weight loss, the most important thing is to create a calorie gap, that is, exercise consumption is greater than intake, in order to achieve healthy and stable weight management. However, existing smart wearable devices generally only collect dynamic calorie consumption, without intake data, and there is no way to scientifically formulate a weight management plan, and it is impossible to achieve the purpose of precise weight management.

[0034] This application embodiment provides a data processing method, see Figure 1 , is an optional flow chart of the data processing method provided in the embodiment of the present application, which will be combined with Figure 1 The steps shown are explained.

[0035] S101. Acquire activity data and image data of a target object in a historical period; wherein the image data is a heat source image of the target object when calorie intake occurs in the historical period.

[0036] In an embodiment of the present application, the terminal can collect activity data and image data of calorie intake of the target object during a historical period.

[0037] In the embodiment of the present application, the terminal may be a smart wearable device. Figure 2 , the terminal may be a smart watch 100. In some other embodiments, the terminal may also be a smart wearable device such as a smart headset or a smart bracelet. The terminal may collect the activity data of the target object in the historical period through its own sensor, and collect the image data of the target object's calorie intake in the historical period through the image acquisition component. Among them, the terminal may collect image data in response to the operation instruction when the target object takes in calories, and may also collect image data when the sensor senses the calorie intake behavior of the target object.

[0038] Among them, the activity data may include: the number of steps, heart rate data and oxygen uptake data of the target object in the historical period. The heat source included in the image data may include: a solid heat source or a liquid heat source, etc. In the embodiment of the present application, the terminal may be configured with: a sensor for detecting heart rate data, a gyroscope and a global positioning system (GPS) for detecting the number of steps of the target object, and a camera for collecting image data. A Bluetooth component for obtaining the weight data of the target object may also be configured.

[0039] S102: Determine the calorie consumption difference of the target object in the historical period based on the activity data, the physical parameters of the target object and the image data.

[0040] In an embodiment of the present application, the terminal can determine the calorie consumption data of the target object in the historical period based on the activity data and the physical parameters of the target object, and obtain the calorie intake data of the target object in the historical period based on the image data analysis. The calorie consumption difference is determined based on the calorie consumption data and the calorie intake data. Among them, the calorie consumption difference represents the difference between the calories consumed and the calories taken in by the target object in the historical period. The physical parameters of the target object may include at least one of the following: gender parameter, weight parameter, height parameter, physical age parameter and body fat percentage.

[0041] In the embodiment of the present application, the calorie value of the calorie consumption data may be greater than the calorie value of the calorie intake data, and the calorie value of the calorie consumption data may also be less than the calorie value of the calorie intake data.

[0042] In an embodiment of the present application, the terminal can determine the dynamic calorie consumption data of the target object in a historical period based on the activity data, determine the static calorie consumption data of the target object in a historical period based on the physical parameters of the target object, and determine the calorie consumption data of the target object in a historical period based on the static calorie consumption data and the dynamic calorie consumption data.

[0043] Among them, the target object's calorie consumption is divided into two parts: static calorie consumption data and dynamic calorie consumption data. Static calorie consumption data is the calories consumed by the fixed metabolism when the target object is at rest; dynamic calorie consumption data is the calories accumulated and estimated based on the number of steps of the target object. The purpose of collecting activity data is to obtain dynamic calorie consumption. The number of steps can be comprehensively determined by the human body's arm swing and GPS positioning, and then the dynamic calorie consumption can be calculated. The calculation of static calorie consumption is based on the height and weight of the target object, and the heart rate is inserted into the model to calculate calorie consumption.

[0044] S103: Determine weight management information based on the calorie consumption difference and the physical fitness parameter.

[0045] In the embodiment of the present application, the terminal can determine the weight management information of the target object to reach the planned weight based on the calorie consumption difference and the physical parameters of the target object. The weight management information can represent the calorie data required for the target object to consume or ingest to reach the planned weight.

[0046] In some other embodiments, the terminal can determine the calorie data required for the target object to reduce or increase a unit weight through the physical parameters of the target object, and then determine the expected weight after a predetermined period of time in combination with the difference in calorie consumption in the historical period. The calorie data required to reach the planned weight can be determined based on the expected weight, and then the calorie data can be displayed. The expected weight can also be displayed.

[0047] Exemplarily, the terminal can calculate tomorrow's expected weight based on the user's gender parameters, weight parameters, height parameters, physical age parameters, body fat percentage, and calorie consumption difference measured on the day, combined with a predetermined weight-to-calorie conversion equation; it can also calculate next week's expected weight based on this week's gender parameters, weight parameters, height parameters, physical age parameters, body fat percentage, and calorie consumption difference.

[0048] In the embodiment of the present application, the calorie collection module based on artificial intelligence obtains the calorie intake data, and the calorie consumption module obtains the full collection of dynamic and static calorie consumption data. The calculation module can calculate the calorie consumption difference, and specify a scientific weight management plan based on the target weight input by the target object. The prediction module calculates the expected weight of the wearer based on the calorie consumption difference and the collected physical parameters of the target object. The following will explain them separately.

[0049] In the embodiment of the present application, the terminal can obtain the physical parameters such as gender parameters, height parameters, physical age parameters, etc. input by the target object. The target object obtains its accurate weight parameters through a weight scale with Bluetooth function, and transmits it to the terminal via Bluetooth. The terminal can obtain the weight management goal and weight loss cycle input by the target object. The terminal plans reasonable daily calorie consumption and calorie intake data according to the weight management goal and weight loss cycle. If the calorie intake data has too little calories, the target object is prompted that the scheme is not feasible. The terminal can collect image data of each meal of the target object in the historical period, and obtain the volume and type of each heat source according to the image data analysis, and then calculate the calorie intake data. The target object can set the exercise mode on the terminal before exercising. When the target object exercises, the terminal will detect the intensity and duration of the exercise through the heart rate detector, and then calculate the first part of the dynamic calorie consumption data of the target object. When the target object is walking, the terminal detects the number of steps of the target object through GPS and gyroscope, and then calculates the second part of the dynamic calorie consumption data of walking. The total dynamic calorie consumption data is determined based on the first part of the calorie consumption data and the second part of the calorie consumption data. The total calorie consumption data of the target object for the day is obtained through dynamic calorie consumption data and static calorie consumption data. The calorie consumption difference is determined by the calorie intake data and the total calorie consumption data. The expected weight is determined based on the calorie consumption difference and physical parameters. An example is "the calorie consumption data of the target object is x, the calorie intake data of the target object is y, the current weight is w, and your expected weight the next day is z. According to your weight management plan, you currently need to exercise to consume a value in order to maintain your planned weight." If the daily weight loss does not reach the planned weight, the daily calorie consumption data and calorie intake data are dynamically adjusted according to the physical parameters of the target object. The calorie intake data cannot be lower than the minimum intake threshold, and the calorie consumption data cannot be greater than the highest consumption threshold. If the formulated daily calorie consumption data and calorie intake data cannot meet the threshold conditions, the target object's weight management plan period is automatically postponed.

[0050] In the embodiment of the present application, the activity data and image data in the historical period are obtained for the target object; wherein the image data is the heat source image of the target object when calorie intake in the historical period; the calorie consumption difference of the target object in the historical period is determined based on the activity data, the physical parameters of the target object and the image data; wherein the calorie consumption difference represents the difference between the calorie consumption and the calorie intake of the target object in the historical period; and the weight management information is determined based on the calorie consumption difference and the physical parameters. In the embodiment of the present application, the calorie intake data can be accurately obtained through the image data, and the calorie intake data obtained is more accurate than the method of obtaining the calorie data input by the user in the related art. Moreover, when determining the calorie consumption difference, not only the activity data and image data are taken into account, but also the physical parameters of the target object are taken into account, eliminating the error of the calorie consumption difference caused by individual differences, and the accuracy of the determined calorie consumption difference is also higher. At the same time, the method of determining the weight management information by the calorie consumption difference and the physical parameters of the target object is determined from the perspective of calorie intake and calorie consumption, forming a complete weight management closed loop, and achieving the purpose of accurate weight management.

[0051] In some embodiments, see Figure 3 , Figure 3 An optional flowchart of the method for processing item information provided in an embodiment of the present application is shown below. Figure 1 The illustrated S102 may also be implemented through S104 to S106 , which will be described in conjunction with each step.

[0052] S104: Determine the calorie intake data of the target object in the historical period based on the image data.

[0053] In an embodiment of the present application, the terminal can analyze and process the image data based on a preset image processing model to obtain calorie intake data corresponding to the heat source in the image data.

[0054] In the embodiment of the present application, the terminal can analyze and process the image data based on a preset image processing model to obtain each heat source and its corresponding volume in the image data. The heat data of each heat source is determined based on the volume of each heat source, and the heat data of each heat source is added to obtain the intake heat data.

[0055] In an embodiment of the present application, the terminal is equipped with a camera. The camera collects image data of the target object in the historical period, and processes the image data through an image recognition method based on artificial intelligence to identify the type and volume of the ingested food, and then calculates the intake calorie data. The method of image recognition is to first use a deep learning algorithm for target detection (including but not limited to FASTER-RCNN, YOLO) to determine the food contained in the image data, and then use a training set generation algorithm to classify the food in the image data, and obtain the volume of each food. The calorie data of each food is determined based on the volume of each food, and the calorie data of each food is added to obtain the intake calorie data.

[0056] S105. Determine the calorie consumption data of the target object in the historical period based on the activity data and the physical parameters.

[0057] In an embodiment of the present application, the terminal can calculate the dynamic calorie consumption data of the target object in a historical period through the activity data, calculate the static calorie consumption data of the target object in a historical period based on the physical parameters, and add the dynamic calorie consumption data and the static calorie consumption data to obtain the calorie consumption data.

[0058] S106: Determine the calorie consumption difference of the target object in the historical period based on the calorie consumption data and the calorie intake data.

[0059] In the embodiment of the present application, the terminal can use the calorie value of the calorie consumption data to subtract the calorie value of the calorie intake data to obtain the calorie consumption difference of the target object in the historical period.

[0060] In the embodiment of the present application, the terminal can calculate the calorie consumption difference Z (kcal) by (static calorie consumption data M+dynamic calorie consumption data C)-calorie intake data K=calorie consumption difference Z (kcal).

[0061] In the embodiment of the present application, the calorie intake data is obtained by analyzing the image data, and the dynamic and static calorie consumption is fully collected based on the activity data and physical parameters of the target object, so that weight management becomes a closed loop. And the calorie consumption difference can be determined based on the calorie consumption data and the calorie intake data, and then a scientific weight management plan can be formulated in combination with the calorie consumption difference to achieve the purpose of accurate weight management.

[0062] In some embodiments, see Figure 4 , Figure 4 An optional flowchart of the method for processing item information provided in an embodiment of the present application is shown below. Figure 3 The illustrated S104 to S105 may also be implemented through S107 to S111 , which will be described in conjunction with each step.

[0063] S107, analyzing the image data to obtain multiple types of heat sources included in the image data, and attribute data corresponding to each type of the heat source.

[0064] In the embodiment of the present application, the terminal can process the image data through the deep learning algorithm of target detection, analyze each heat source included in the image data, and then classify the heat sources to obtain each type of heat source. And the attribute data of each type of heat source. Among them, the attribute data is a unit for measuring the heat of each type of heat source.

[0065] In some other embodiments, the attribute data of each type of heat source may include: volume, bottle, weight, etc.

[0066] For example, a type of heat source may include: bread, and its corresponding attribute data is volume. A type of heat source may also include: beverage, and its corresponding attribute data is bottle.

[0067] S108: Determine the calorie intake data based on each type of the calorie source and the attribute data corresponding to each type of the calorie source.

[0068] In the embodiment of the present application, after determining the attribute data of each type of heat source, the terminal can query the unit heat of each type of heat source, and determine the calorie intake data based on the unit (attribute data) of heat measurement corresponding to each type of heat source and the unit heat.

[0069] In an embodiment of the present application, the terminal queries the heat database to obtain the unit heat corresponding to each type of heat source; wherein the heat database includes the corresponding relationship between each type of the heat source and the corresponding unit heat; and the heat intake data is determined based on the attribute data corresponding to each type of heat source and the unit heat.

[0070] S109: Determine the dynamic calorie consumption data of the target object in the historical period based on the activity data.

[0071] In an embodiment of the present application, the terminal may calculate the dynamic calorie consumption data of the target object during the historical period by using the activity data acquired for the target object during the historical period.

[0072] In the embodiment of the present application, the activity data may include at least one of: the number of steps, heart rate data, and oxygen uptake data. The terminal calculates the corresponding dynamic calorie consumption data based on at least one of the number of steps, heart rate data, and oxygen uptake data.

[0073] For example, the dynamic calorie consumption data can be determined by obtaining heart rate data through heart rate detection technology (such as photocapacitance pulse wave recording, which detects the amount of blood flowing through the wrist at a specific time through the red light reflected by the blood, thereby determining the heart rate data), and calculating the oxygen uptake. The dynamic calorie consumption data is then obtained based on the relationship that 1 liter of oxygen is equal to 5 kilocalories.

[0074] S110. Determine static calorie consumption data of the target object in the historical period based on the physical parameters.

[0075] In an embodiment of the present application, the terminal can determine the static calorie data consumed by the target object per unit time based on the physical parameters of the target object, and determine the static calorie consumption data of the target object in the historical period according to the multiple relationship between the historical period and the unit time.

[0076] In the embodiment of the present application, the physical parameter includes at least one of the following: gender parameter, weight parameter, height parameter, physical age parameter. The static calorie consumption data is positively correlated with the weight parameter of the target object, positively correlated with the height parameter, and negatively correlated with the physical age parameter.

[0077] In some other embodiments, the static calorie consumption data of males in a unit time can be determined by 9.99×W+6.25×H-4.92×A+5=M (male). The static calorie consumption data of females in a unit time can be determined by 9.99×W+6.25×H-4.92×A-161=M (female). Wherein, M represents the static calorie consumption data, in kcal; W represents the weight, in kg; H represents the height, in cm; and A represents the age.

[0078] S111. Determine the calorie consumption data based on the dynamic calorie consumption data and the static calorie consumption data.

[0079] In the embodiment of the present application, the dynamic calorie consumption data and the static calorie consumption data can be added to obtain the calorie consumption data of the target object in the historical period. When adding the dynamic calorie consumption data and the static calorie consumption data, the calorie units corresponding to the dynamic calorie consumption data and the static calorie consumption data need to be unified.

[0080] In the embodiment of the present application, the calorie intake data is determined by analyzing and processing the image data, so that the determined calorie intake data is more accurate. Moreover, the dynamic calorie consumption data and static calorie consumption data of the target object are taken into consideration when determining the calorie consumption data, so that the consideration is more sufficient and the determined calorie consumption data is more accurate.

[0081] In some embodiments, see Figure 5 , Figure 5An optional flowchart of the method for processing item information provided in an embodiment of the present application is shown below. Figure 4 The illustrated S107 to S108 may also be implemented through S201 to S213, which will be described in conjunction with each step.

[0082] S201, collecting image data.

[0083] In the embodiment of the present application, a camera is configured on the terminal, and image data can be collected through the camera when the target object takes in calories.

[0084] S202: Identify the heat source.

[0085] In an embodiment of the present application, the terminal may first utilize a deep learning algorithm for target detection to process image data to identify multiple heat sources, and detect attribute data corresponding to each heat source.

[0086] S203. Classify heat sources.

[0087] In the embodiment of the present application, the terminal may also classify multiple heat sources in the image data using a classification algorithm to obtain heat sources of each category, and add the attribute data of at least one heat source included in each category to obtain the attribute data of each category of heat sources.

[0088] S204: Whether the heat source has been initialized as a variable.

[0089] In the embodiment of the present application, the terminal can traverse each heat source and detect whether a corresponding variable is formed for each heat source.

[0090] S205, determining VA1 of each type of heat source.

[0091] In the embodiment of the present application, the terminal may form a variable A1 for storing a type of heat source object and initialize it to null. When a classified heat source is detected, the detected classified object may be obtained for the type of heat source and the object may be assigned to the variable A1. The volume of the heat source is determined and added to the volume VA1 of the type of heat source.

[0092] S206, query unit heat.

[0093] In the embodiment of the present application, the terminal can query the unit heat of the object from the database.

[0094] S207, multiply the unit heat by VA1 and assign the result to CA1.

[0095] In the embodiment of the present application, the terminal may multiply the unit heat by the corresponding total volume VA1, and assign the heat information of the variable A1 to the variable CA1 of the accumulated heat of the category.

[0096] S208: Has the heat source been processed?

[0097] In the embodiment of the present application, after processing one heat source, it is determined whether each heat source in the image data has been processed. If not all heat sources have been processed, the next heat source is traversed.

[0098] S209, generate a new variable B1, and assign the type of heat source to it.

[0099] In the embodiment of the present application, when it is detected that the heat source category corresponding to the new heat source has not been initialized as a variable, a new variable B1 is formed, and the heat source category of the new heat source is assigned to the variable B1.

[0100] S210, query unit heat.

[0101] In the embodiment of the present application, the terminal can query the unit heat of the new heat source in the database.

[0102] S211. Determine VB1 of the new heat source.

[0103] In the embodiment of the present application, the terminal can determine the volume of the heat source to be added to the volume VB1 of this type of heat source.

[0104] S212, multiply the unit heat by VB1 and assign the result to CB1.

[0105] In the embodiment of the present application, the terminal can multiply the unit heat by the corresponding total volume VB1, and assign the heat information of the variable B1 to the variable CB1 of the category cumulative heat. Then, it is determined whether each heat source in the image data has been processed. If all heat sources have been processed, S213 is executed.

[0106] S213, CA1+CB1+...CZ1...are all recognized calorie intake data.

[0107] In the embodiment of the present application, the terminal adds the calories of each type of heat source (CA1+CB1+...CZ1) to obtain the calorie intake data of the target object in the historical period.

[0108] In an embodiment of the present application, the terminal includes a Hypertext Transfer Protocol (HTTP) interface, which is of POST type. The image data is placed in the interface body, the type is multipart / form-data, and a JavaScript Object Notation (JSON) is returned. The foodType field indicates the category of the current heat source. After the target object uses a camera to shoot the image data, it submits the image data through the interface, obtains the heat source category information, and calls the database to query the unit heat information corresponding to the food category. The heat information of multiple heat sources is added to obtain the total intake heat data.

[0109] In some embodiments, see Figure 6 , Figure 6 An optional flowchart of the method for processing item information provided in an embodiment of the present application is shown below. Figure 1 The illustrated S103 can also be implemented through S112 to S113, which will be described in conjunction with each step.

[0110] S112: Determine the expected weight of the target object after a predetermined period of time based on the calorie consumption difference and the physical fitness parameter.

[0111] In an embodiment of the present application, the terminal can determine the unit calorie consumption difference required for the target object to reduce or increase unit weight based on the physical parameters of the target object. Then, based on the multiple relationship between the calorie consumption difference and the unit calorie consumption difference, the expected weight after the predetermined period is determined. The predetermined period is the same as the duration represented by the historical period. The predetermined period may also be different from the duration represented by the historical period.

[0112] In the embodiment of the present application, when the calorie consumption difference indicates that the calorie intake data is less than the calorie consumption data, the expected weight of the target object can be determined based on the calorie consumption difference and the unit calorie consumption difference required for the target object to reduce a unit weight. When the calorie consumption difference indicates that the calorie intake data is greater than the calorie consumption data, the expected weight of the target object can be determined based on the calorie consumption difference and the unit calorie consumption difference required for the target object to increase a unit weight.

[0113] In some embodiments, the shown S112 may also be implemented by S1121 or S1122, which will be described in conjunction with the steps.

[0114] S1121. Determine a unit calorie consumption difference in a calorie mapping set based on the physical fitness parameter corresponding to the target object, and determine an expected weight based on the calorie consumption difference and the unit calorie consumption difference.

[0115] In an embodiment of the present application, the terminal can determine the corresponding unit calorie consumption difference in the calorie mapping set based on the gender parameter, weight parameter, height parameter, physical age parameter and body fat rate of the target object. Then the expected weight is determined based on the multiple relationship between the calorie consumption difference and the unit calorie consumption difference. Among them, the calorie mapping set includes multiple physical parameters, and the unit calorie consumption difference for reducing or increasing unit weight for each physical parameter. The unit calorie consumption difference represents the unit calories required for the target object to reduce or increase unit weight.

[0116] The calorie mapping set includes multiple physical parameters consisting of different gender parameters, weight parameters, height parameters, physical age parameters and body fat percentage. For each physical parameter object, there is a corresponding unit calorie consumption difference for reducing or increasing unit weight.

[0117] S1122: Process the calorie consumption difference and the physical parameters corresponding to the target object through a preset model to obtain the expected weight.

[0118] In an embodiment of the present application, the terminal can process the calorie consumption difference and the gender parameter, weight parameter, height parameter, physical age parameter and body fat percentage corresponding to the target object based on a preset model to obtain the expected weight. The preset model is obtained based on the sample physical parameters of each sample object and the unit calorie consumption difference of each sample object when the unit weight is reduced or increased. The sample physical parameters may include at least one of the following: the gender parameter, weight parameter, height parameter, physical age parameter and body fat percentage of the sample object.

[0119] In the embodiment of the present application, it can be determined that the equation for converting unit weight into heat can be obtained. The traditional empirical equation is that 1kg of body weight requires an intake consumption difference of 7700 kcal. However, this empirical equation obviously does not take into account the physical parameters of the end user, such as gender parameters, weight parameters, height parameters, physical age parameters and body fat percentage. The implementation of the weight conversion heat equation considering these factors is expressed as follows: the heat range equivalent to 1kg of body weight is set to 0-10000 kcal, and 0-10000 kcal is divided into several intervals, such as 0-100 kcal for interval 1, 100-200 kcal for interval 2, ..., 9900-10000 kcal for interval 100. Sample objects are sampled in advance through experiments to obtain the heat required to reduce 1kg of body weight by sample objects of different genders, weights, heights, ages, and body fat percentages. And the heat required to reduce 1kg of body weight by the sample object is classified according to the heat range equivalent to 1kg of body weight divided. The preset model is obtained by taking "sex, weight, height, age, and body fat percentage" as input and "calories required to reduce 1kg of weight" as the result label as the training set. For example, the physical parameters of a sampled object include: female, weight 100, height 165, age 20, and body fat percentage 25%. In the current state, reducing 1kg of weight requires 7630 kcal, which falls within the range of 7600-7700 kcal. Then, "female, weight 100, height 165, age 20, body fat percentage 25%" is taken as input, and "7600-7700 kcal interval" is taken as the result label to train the classification deep learning algorithm to obtain the preset model.

[0120] S113: Determine the weight management information based on the expected weight and the planned weight after the predetermined period of time.

[0121] In an embodiment of the present application, the terminal can determine the difference between the expected weight and the planned weight, and then determine the calorie data (weight management information) required to achieve the planned weight based on the unit calorie consumption difference required to reduce or increase the unit weight of the target object. The planned weight is determined based on the acquired weight management plan data. The weight management plan data may include: weight loss plan data and weight gain plan data.

[0122] In the embodiment of the present application, the terminal can also process the expected weight and the planned weight through a preset functional relationship to determine the calorie data required for the target object to reach the planned weight. When the target object needs to lose weight, the calorie data required to reach the planned weight is the calorie data required to be consumed. When the target object needs to gain weight, the calorie data required to reach the planned weight is the calorie data required to be consumed.

[0123] In an embodiment of the present application, the terminal determines the expected weight of the target object after a predetermined period of time based on the difference in calorie consumption and the physical parameters. Since the weight of the target object cannot change immediately with the amount of exercise after the exercise, the expected weight can be accurately obtained based on the calculated difference in calorie consumption and the physical parameters of the target object in the present application. And the method of determining weight management information based on the expected weight and the planned weight allows the target object to clearly know what amount of exercise is needed to reach the planned weight, thereby achieving the purpose of precise weight management.

[0124] In some embodiments, see Figure 7 , Figure 7 An optional flowchart of the method for processing item information provided in an embodiment of the present application is shown below. Figure 6 The illustrated S113 can also be implemented through S114 to S115, which will be described in conjunction with each step.

[0125] S114: Determine the weight difference between the expected weight and the planned weight.

[0126] In the embodiment of the present application, the terminal can calculate the difference between the expected weight and the planned weight to determine the weight difference, wherein the weight difference is the weight gain or weight loss of the target object to reach the planned weight.

[0127] S115. Determine the calorie data required for the target object to reach the planned weight based on the weight difference, and display it; wherein the weight management information includes: the displayed calorie data.

[0128] In an embodiment of the present application, when the expected weight is greater than the planned weight, the calorie data required for the target object to reach the planned weight can be determined based on the difference between the expected weight and the planned weight, and the unit calorie consumption difference required for the target object to reduce a unit weight. When the expected weight is less than the planned weight, the calorie data required for the target object to reach the planned weight can be determined based on the difference between the planned weight and the expected weight, and the unit calorie consumption difference required for the target object to increase a unit weight. After determining the calorie data required for the target object to reach the planned weight, the terminal can display the weight management information on the display interface: "** more calories are needed to reach the planned weight" information.

[0129] In an embodiment of the present application, the terminal determines the weight difference between the expected weight and the planned weight, and determines the calorie data required for the target object to reach the planned weight based on the weight difference, so that the target object can clearly know how many calories are needed to reach the planned weight, thereby achieving the purpose of precise weight management.

[0130] In some embodiments, see Figure 8 , Figure 8An optional flow chart of the method for processing item information provided in an embodiment of the present application will be described in conjunction with each step.

[0131] S116. Determine a physical fitness test result based on the initial physical fitness parameters of the target object.

[0132] In an embodiment of the present application, the terminal can determine the unit calorie consumption difference (physique test result) required for the target object to reduce unit weight in the heat mapping set based on the initial physical parameters of the target object. The initial physical parameters are the physical parameters of the target object before the historical period. The terminal can also determine the body mass index (physique test result) of the target object based on the weight and height in the initial physical parameters of the target object.

[0133] Among them, when the unit calorie consumption difference is greater than the threshold, it means that the target object consumes too much calories per unit fat and does not need to lose weight. When the unit calorie consumption difference is not greater than the threshold, it means that the target object needs to lose weight. When the body mass index indicates that the target object is overweight, it means that the target object needs to lose weight. When the body mass index indicates that the target object is underweight, it means that the target object needs to gain weight.

[0134] S117. When the physical fitness test result indicates that the target object needs to perform weight management, determine a plurality of planned weights and planned dynamic calorie consumption data corresponding to each planned weight based on the initial physical fitness parameters and the acquired weight management plan data.

[0135] In the embodiment of the present application, when the unit calorie consumption difference is not greater than the threshold value, or the body mass index indicates that the target object is overweight or underweight, the target object is reminded to enter the weight management plan data. The terminal can determine the unit calorie consumption difference required for the target object to consume or increase unit weight according to the initial physical parameters, determine multiple planned weights according to the weight management plan data, and determine the planned dynamic calorie consumption data corresponding to each planned weight based on the difference between the collected weight parameters of the target object and the planned weight, combined with the unit calorie consumption difference.

[0136] In the embodiment of the present application, when the unit calorie consumption difference is not greater than the threshold or the body mass index indicates that the target object is overweight, the target object is reminded to input the weight loss plan data. When the body mass index indicates that the target object is underweight, the target object is reminded to input the weight gain plan data.

[0137] In the embodiment of the present application, the physical fitness test result is determined by the physical fitness parameters of the target object, and a corresponding weight management plan is formulated only when the physical fitness test result indicates that the target object needs to manage its weight. This can keep the target object away from unhealthy conditions and achieve precise weight management.

[0138] In some embodiments, see Fig. 9 , Fig. 9 An optional flowchart of the method for processing item information provided in an embodiment of the present application is shown below. Figure 8 The illustrated S117 can also be implemented through S118 to S120, which will be described in conjunction with each step.

[0139] S118: Determine a plurality of sub-periods and the planned weight corresponding to each sub-period based on the weight change amount and the weight management cycle included in the weight management plan data.

[0140] In the embodiment of the present application, the weight management plan data obtained by the terminal includes: weight change and weight management cycle. The weight management cycle is divided into multiple sub-cycles in a certain order. The weight change is evenly distributed in each sub-cycle to obtain the weight change corresponding to each sub-cycle. Based on the initial weight parameters of the target object combined with the weight change in each sub-cycle, the planned weight corresponding to each sub-cycle is obtained.

[0141] In an embodiment of the present application, the terminal can obtain weight loss plan data. The weight loss plan data includes: weight loss amount and weight management cycle. The weight loss amount can be evenly distributed in each sub-period determined based on the weight management cycle to obtain the corresponding weight loss amount in each sub-period. The planned weight corresponding to each sub-period is obtained based on the initial weight parameters of the target object combined with the weight loss amount in each sub-period.

[0142] In an embodiment of the present application, the terminal can obtain weight gain plan data. The weight gain plan data includes: weight gain amount and weight management cycle. The weight gain amount can be evenly distributed in each sub-period determined based on the weight management cycle to obtain the corresponding weight loss amount in each sub-period. Based on the initial weight parameters of the target object combined with the weight gain amount in each sub-period, the planned weight corresponding to each sub-period is obtained.

[0143] Exemplarily, a method for determining a planned weight corresponding to the nth sub-period for weight loss plan data may include: subtracting the sum of weight loss in the first n sub-periods from the initial weight parameter to obtain the planned weight corresponding to the nth sub-period. A method for determining a planned weight corresponding to the nth sub-period for weight gain plan data may include: adding the sum of weight gain in the first n sub-periods to the initial weight parameter to obtain the planned weight corresponding to the nth sub-period. n is an integer.

[0144] Exemplarily, the weight loss amount may be 10 kg. The weight loss period may be 20 days. One day is determined as a sub-period, and 20 sub-periods are obtained. The terminal evenly distributes the weight loss amount of 10 kg in each sub-period, and the weight loss amount in each sub-period is 0.5 kg. Based on the initial weight parameter of the target object and the weight loss amount in each sub-period, the planned weight corresponding to each sub-period is obtained.

[0145] In some other embodiments, the terminal may also obtain the target weight and weight management period input by the target subject, and determine the weight change amount based on the target weight and the initial weight parameters.

[0146] S119, determining the planned static calorie consumption data and the planned calorie intake data of the target object in each sub-period based on the initial physical parameters.

[0147] In the embodiment of the present application, the terminal can determine the static calorie data consumed by the target object in a unit time according to the initial physical parameters. Based on the multiple relationship between the cycle time of each sub-cycle and the unit time, the planned static calorie consumption data of the target object in each sub-cycle is determined. Then, the planned calorie intake data is determined based on the proportional relationship between the planned calorie intake data and the planned static calorie consumption data.

[0148] For example, when the target object needs to lose weight, the ratio of the planned calorie intake data to the planned static calorie consumption data is 1.1-1.2. When the target object needs to gain weight, the ratio of the planned calorie intake data to the planned static calorie consumption data is greater than 1.1-1.2.

[0149] In the embodiment of the present application, when the planned calorie intake data is greater than the minimum intake threshold, it is determined that the planned calorie intake data meets the condition. When the planned calorie intake data is not greater than the minimum intake threshold, it is determined that the planned calorie intake data does not meet the condition.

[0150] S120. When the planned calorie intake data meets a condition, determine the planned dynamic calorie consumption data corresponding to each planned weight based on the planned static calorie consumption data, the planned calorie intake data and the weight change.

[0151] In an embodiment of the present application, when the planned calorie intake data is greater than the minimum intake threshold, the terminal determines the planned dynamic calorie consumption data corresponding to each planned weight based on the planned static calorie consumption data, the planned calorie intake data and the weight loss.

[0152] In the embodiment of the present application, the terminal determines the planned calorie difference corresponding to each planned weight based on the weight change and the initial physical parameters. The planned dynamic calorie consumption data corresponding to each planned weight is determined based on the planned static calorie consumption data, the planned calorie intake data and the planned calorie difference. The planned calorie difference is equal to the sum of the planned static calorie consumption data and the planned dynamic calorie consumption data, minus the planned calorie intake data.

[0153] In an embodiment of the present application, the terminal evenly distributes the weight change in each sub-period according to the weight change and the weight management cycle, and calculates the planned dynamic calorie consumption data required for the planned weight corresponding to each sub-period, so that the target object can clearly know the amount of activity in each sub-period, thereby achieving precise weight management.

[0154] In some embodiments, see Fig.10 , Fig.10 An optional flowchart of the method for processing item information provided in an embodiment of the present application is shown below. Fig. 9 The illustrated S120 may also be implemented through S121 to S122, which will be described in conjunction with each step.

[0155] S121. Determine a total calorie difference based on the weight change and the initial physical parameters, and distribute the total calorie difference according to the number of the planned weights to determine a planned calorie difference corresponding to each planned weight.

[0156] In an embodiment of the present application, the terminal can determine the unit calorie consumption difference of the target object for reducing unit weight based on the initial physical parameters of the target object. The terminal determines the total calorie difference of the weight loss based on the proportional relationship between the weight change and the unit weight. The total calorie difference is allocated according to the number of multiple planned weights to obtain the planned calorie difference corresponding to each planned weight.

[0157] S122, obtaining the planned dynamic calorie consumption data by subtracting the planned static calorie consumption data from the sum of the planned calorie difference and the planned calorie intake data.

[0158] In the embodiment of the present application, the terminal can obtain the planned dynamic calorie consumption data by adding the planned calorie intake calorie data to the planned calorie difference and then subtracting the planned static calorie consumption data.

[0159] In the embodiment of the present application, the terminal can display prompt information based on the planned dynamic calorie consumption data corresponding to each planned weight.

[0160] In the embodiment of the present application, if the planned dynamic calorie consumption data corresponding to each planned weight is greater than the consumption threshold, the terminal displays a prompt message that the weight management plan data is unreasonable. If the planned dynamic calorie consumption data corresponding to each planned weight is not greater than the consumption threshold, the terminal displays a prompt message that the weight management plan data is reasonable.

[0161] In the embodiment of the present application, the terminal calculates the planned dynamic calorie consumption data required for the planned weight corresponding to each sub-period, so that the target object can clearly know the amount of activity in each sub-period, and achieve accurate weight management. And prompt information can be displayed based on the planned dynamic calorie consumption data corresponding to each planned weight, ensuring the health status of the target object while performing weight management.

[0162] In some embodiments, see Fig.11 , Fig.11 An optional flow chart of the method for processing item information provided in an embodiment of the present application will be described in conjunction with the steps.

[0163] S214, calculating the planned static calorie consumption data.

[0164] In the embodiment of the present application, the terminal calculates the daily planned static calorie consumption data according to the gender, weight, height, and age of the target object. It can also determine the unit calorie consumption difference of the target object to reduce unit weight according to the gender, weight, height, and age of the target object. If the unit calorie consumption difference is too high, the user is prompted that the current weight status is reasonable.

[0165] S215. Calculate the total heat difference.

[0166] In the embodiment of the present application, the terminal obtains the input weight management target value and weight loss cycle, and determines the total calorie difference according to the weight loss of the target object and the unit calorie consumption difference of the target object for reducing unit weight.

[0167] S216. Determine the planned daily calorie difference.

[0168] In the embodiment of the present application, the terminal spreads the target calorie gap to obtain the daily planned calorie difference.

[0169] S217. Calculate the planned calorie intake data.

[0170] In the embodiment of the present application, the terminal determines the planned calorie intake data according to the ratio relationship that the planned calorie intake data is 110%-120% of the static calorie consumption data.

[0171] S218: Whether the conditions are met.

[0172] In the embodiment of the present application, the terminal compares the planned calorie intake data with the minimum intake threshold to determine whether the minimum planned calorie intake data meets the conditions.

[0173] S219: It is suggested that the target is unreasonable.

[0174] In the embodiment of the present application, when the minimum planned calorie intake data is not greater than the minimum intake threshold, it is prompted that the target is unreasonable.

[0175] S220, calculating the daily planned dynamic calorie consumption data.

[0176] In the embodiment of the present application, the terminal can obtain the daily planned dynamic calorie consumption data by adding the minimum planned calorie intake calorie data to the planned calorie difference and then subtracting the planned static calorie consumption data. The daily exercise amount is determined according to the daily planned dynamic calorie consumption data.

[0177] S221: Is it higher than the consumption threshold?

[0178] In the embodiment of the present application, if the amount of exercise exceeds the daily exercise consumption threshold (such as 1000 kcal), the wearer is prompted that the goal is unreasonable. If the amount of exercise does not exceed the daily exercise consumption threshold (such as 1000 kcal), the wearer is prompted that the goal is reasonable.

[0179] In an embodiment of the present application, after each planned weight and the planned dynamic calorie consumption data corresponding to each planned weight are determined according to the weight loss plan data of the target object. The calorie consumption difference of the target object over a period of time is collected and calculated. The terminal determines the unit calorie difference of the target object to reduce unit weight by obtaining the gender, weight, height, age, and body fat percentage of the target object. (At regular intervals, when the target object's weight and body fat percentage change, the corresponding unit calorie consumption difference will also change), the terminal can calculate the equivalent change in weight based on the calorie consumption difference and the unit calorie consumption difference.

[0180] In the embodiment of the present application, the terminal obtains the calorie intake data of the target object based on artificial intelligence technology, and the efficiency and accuracy of the scheme are greatly improved; in setting the weight management plan, the indicator adopted by this application is the calorie consumption difference, and the calorie consumption difference is accurately mapped with the physical parameters, eliminating the error of weight management information caused by individual differences; the expected weight management is realized, and the expected calculation method of this patent invention fully considers the wearer's height, weight, gender, body fat percentage and other information, does not rely on the user's own historical data, and has higher accuracy.

[0181] See also Fig.12 , Fig.12 A schematic diagram of the structure of an item information processing device provided in an embodiment of the present application.

[0182] The embodiment of the present application further provides a data processing device 600 , including: a data acquisition unit 601 and a determination unit 602 .

[0183] The data acquisition unit 601 is used to acquire activity data and image data in a historical period for a target object; wherein the image data is a heat source image of the target object when calorie intake occurs in the historical period;

[0184] A determination unit 602 is used to determine a calorie consumption difference of the target object in the historical period based on the activity data, the physical parameters of the target object and the image data; wherein the calorie consumption difference represents a difference between the calorie consumption and the calorie intake of the target object in the historical period;

[0185] The determining unit 602 is further configured to determine weight management information based on the calorie consumption difference and the physical fitness parameter.

[0186] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to determine the calorie intake data of the target object in the historical period based on the image data;

[0187] Determining the calorie consumption data of the target object in the historical period based on the activity data and the physical fitness parameter;

[0188] The calorie expenditure difference of the target object during the historical period is determined based on the calorie expenditure data and the calorie intake data.

[0189] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to analyze the image data to obtain multiple types of heat sources included in the image data, and attribute data corresponding to each type of the heat source; wherein the attribute data is a unit for measuring the heat of each type of the heat source;

[0190] The calorie intake data is determined based on each type of the calorie source and the attribute data corresponding to each type of the calorie source.

[0191] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to query the heat database to obtain the unit heat corresponding to each type of the heat source; wherein the heat database includes the correspondence between each type of the heat source and the corresponding unit heat;

[0192] The calorie intake data is determined based on the attribute data corresponding to each type of the calorie source and the unit calorie.

[0193] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to determine the dynamic calorie consumption data of the target object in the historical period based on the activity data;

[0194] Determining static calorie consumption data of the target object in the historical period based on the physical parameters;

[0195] The calorie expenditure data is determined based on the dynamic calorie expenditure data and the static calorie expenditure data.

[0196] In the embodiment of the present application, the physical parameter includes at least one of the following: gender parameter, weight parameter, height parameter, physical age parameter;

[0197] The static calorie consumption data is positively correlated with the weight parameter of the target object, positively correlated with the height parameter, and negatively correlated with the physical age parameter.

[0198] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to determine the expected weight of the target object after a predetermined period of time based on the calorie consumption difference and the physical parameter;

[0199] The weight management information is determined based on the expected weight and the planned weight after the predetermined period of time; wherein the planned weight is determined based on the acquired weight management plan data.

[0200] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to determine the unit calorie consumption difference in the calorie mapping set based on the physique parameter corresponding to the target object, and determine the expected weight based on the calorie consumption difference and the unit calorie consumption difference; wherein the calorie mapping set includes a plurality of physique parameters, and the unit calorie consumption difference for reducing or increasing a unit weight of an object of each physique parameter;

[0201] The expected weight is obtained by processing the calorie consumption difference and the physical parameters corresponding to the target object through a preset model; wherein the preset model is trained based on the sample physical parameters of each sample object and the unit calorie consumption difference of each sample object when reducing or increasing a unit weight.

[0202] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to determine the weight difference between the expected weight and the planned weight;

[0203] The calorie data required for the target object to reach the planned weight is determined based on the weight difference for display; wherein the weight management information includes: the displayed calorie data.

[0204] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to determine the physical fitness test result based on the initial physical fitness parameters of the target object; wherein the initial physical fitness parameters are the physical fitness parameters of the target object before the historical period;

[0205] In the case where the physical fitness test result indicates that the target object needs to perform weight management, multiple planned weights and planned dynamic calorie consumption data corresponding to each planned weight are determined based on the initial physical fitness parameters and the acquired weight management plan data.

[0206] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to determine a plurality of sub-periods and the planned weight corresponding to each of the sub-periods based on the weight change amount and the weight loss period included in the weight management plan data;

[0207] Determine the planned static calorie consumption data and the planned calorie intake data of the target subject in each of the sub-periods based on the initial physical parameters;

[0208] When the planned calorie intake data meets the conditions, the planned dynamic calorie consumption data corresponding to each planned weight is determined based on the planned static calorie consumption data, the planned calorie intake data and the weight change.

[0209] In the embodiment of the present application, the determination unit 602 in the data processing device 600 is used to determine the total calorie difference based on the weight change and the initial physical parameter, and distribute the total calorie difference according to the number of the plurality of planned weights to determine the planned calorie difference corresponding to each planned weight;

[0210] The planned dynamic calorie consumption data is obtained by subtracting the planned static calorie consumption data from the sum of the planned calorie difference and the planned calorie intake data.

[0211] In the embodiment of the present application, the data processing device 600 is used to display prompt information based on the planned dynamic calorie consumption data corresponding to each planned weight.

[0212] In the embodiment of the present application, the data processing device is used to display a prompt message that the weight management plan data is unreasonable if the planned dynamic calorie consumption data corresponding to each planned weight is greater than the consumption threshold. If the planned dynamic calorie consumption data corresponding to each planned weight is not greater than the consumption threshold, the prompt message that the weight management plan data is reasonable is displayed.

[0213] It should be noted that in the embodiment of the present application, if the above-mentioned data processing method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including a number of instructions to enable a data processing device (which can be a personal computer, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0214] Correspondingly, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the client-side method are implemented.

[0215] Correspondingly, an embodiment of the present application provides an electronic device 700, including a memory 702 and a processor 701, wherein the memory 702 stores a computer program that can be executed on the processor 701, and the processor 701 implements the steps in the above method when executing the program.

[0216] It should be noted here that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0217] It should be noted that Fig.13 A hardware entity diagram of an electronic device provided in an embodiment of the present application, such as Fig.13 As shown, the hardware entity of the electronic device 700 includes: a processor 701 and a memory 702, wherein;

[0218] The processor 701 generally controls the overall operation of the electronic device 700 .

[0219] The memory 702 is configured to store instructions and applications executable by the processor 701, and can also cache data to be processed or processed by the processor 701 and various modules in the electronic device 700 (for example, image data, audio data, voice communication data, and video communication data), which can be implemented through flash memory (FLASH) or random access memory (Random Access Memory, RAM).

[0220] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above-mentioned sequence numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0221] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0222] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0223] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0224] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0225] A person skilled in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a magnetic disk or an optical disk, and other media that can store program codes.

[0226] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can be essentially or partly embodied in the form of a software product that contributes to the relevant technology. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a mobile storage device, a ROM, a magnetic disk, or an optical disk.

[0227] The above is only an implementation method of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A data processing method, characterized in that: Applied to smart wearable devices, including: For the target object, activity data and image data in a historical period are obtained; wherein the image data is a heat source image of the target object when calorie intake occurs in the historical period; Determine the calorie consumption difference of the target object in the historical period based on the activity data, the physical parameters of the target object and the image data; wherein the calorie consumption difference represents the difference between the calorie consumption and the calorie intake of the target object in the historical period; Weight management information is determined based on the calorie expenditure difference and the physical fitness parameter.

2. The data processing method according to claim 1, characterized in that: The determining the calorie consumption difference of the target object in the historical period based on the activity data, the physical parameters of the target object and the image data comprises: determining the caloric intake data of the target object in the historical period based on the image data; Determining the calorie consumption data of the target object in the historical period based on the activity data and the physical fitness parameter; The calorie expenditure difference of the target object during the historical period is determined based on the calorie expenditure data and the calorie intake data.

3. The data processing method according to claim 2, characterized in that: The determining the calorie intake data of the target object in the historical period based on the image data includes: Analyzing the image data to obtain multiple types of heat sources included in the image data, and attribute data corresponding to each type of the heat source; wherein the attribute data is a unit for measuring the heat of each type of the heat source; The calorie intake data is determined based on each type of the calorie source and the attribute data corresponding to each type of the calorie source.

4. The data processing method according to claim 3, characterized in that: The determining the calorie intake data based on each type of the calorie source and the attribute data corresponding to each type of the calorie source includes: Querying in a heat database to obtain the unit heat corresponding to each type of the heat source; wherein the heat database includes a corresponding relationship between each type of the heat source and the corresponding unit heat; The calorie intake data is determined based on the attribute data corresponding to each type of the calorie source and the unit calorie.

5. The data processing method according to claim 2, characterized in that: The step of determining the calorie consumption data of the target object in the historical period based on the activity data and the physical fitness parameter includes: Determine the dynamic calorie consumption data of the target object in the historical period based on the activity data; Determining static calorie consumption data of the target object in the historical period based on the physical parameters; The calorie expenditure data is determined based on the dynamic calorie expenditure data and the static calorie expenditure data.

6. The data processing method according to claim 5, characterized in that: The physical parameters include at least one of the following: gender parameter, weight parameter, height parameter, physical age parameter and body fat percentage; The static calorie consumption data is positively correlated with the weight parameter of the target object, positively correlated with the height parameter, and negatively correlated with the physical age parameter.

7. The data processing method according to any one of claims 1 to 6, characterized in that: The determining of weight management information based on the calorie consumption difference and the physical fitness parameter includes: Determining the expected weight of the target subject after a predetermined period of time based on the calorie consumption difference and the physical fitness parameter; The weight management information is determined based on the expected weight and the planned weight after the predetermined period of time; wherein the planned weight is determined based on the acquired weight management plan data.

8. The data processing method according to claim 7, characterized in that: The determining the expected weight of the target object after a predetermined period of time based on the calorie consumption difference and the physical parameter comprises one of the following: Determining a unit calorie consumption difference in a calorie mapping set based on the physique parameter corresponding to the target object, and determining the expected weight based on the calorie consumption difference and the unit calorie consumption difference; wherein the calorie mapping set includes a plurality of physique parameters, and a unit calorie consumption difference for reducing or increasing a unit weight of an object having each physique parameter; The expected weight is obtained by processing the calorie consumption difference and the physical parameters corresponding to the target object through a preset model; wherein the preset model is trained based on the sample physical parameters of each sample object and the unit calorie consumption difference of each sample object when reducing or increasing a unit weight.

9. The data processing method according to claim 7, characterized in that: The determining the weight management information based on the expected weight and the planned weight after the predetermined period of time includes: determining a weight difference between the expected weight and the planned weight; The calorie data required for the target object to reach the planned weight is determined based on the weight difference for display; wherein the weight management information includes: the displayed calorie data.

10. The data processing method according to any one of claims 1 to 6, characterized in that: Before obtaining the activity data and image data of the target object in the historical period, the method further includes: Determine the physical fitness test result based on the initial physical fitness parameters of the target object; wherein the initial physical fitness parameters are the physical fitness parameters of the target object before the historical period; In the case where the physical fitness test result indicates that the target object needs to perform weight management, multiple planned weights and planned dynamic calorie consumption data corresponding to each planned weight are determined based on the initial physical fitness parameters and the acquired weight management plan data.

11. The data processing method according to claim 10, characterized in that: The determining of a plurality of planned weights based on the initial physical parameters and the acquired weight management plan data, and the planned dynamic calorie consumption data corresponding to each planned weight, includes: Based on the weight change amount and weight management cycle included in the weight loss plan data, determining a plurality of sub-cycles and the planned weight corresponding to each of the sub-cycles; Determine the planned static calorie consumption data and the planned calorie intake data of the target subject in each of the sub-periods based on the initial physical parameters; When the planned calorie intake data meets the conditions, the planned dynamic calorie consumption data corresponding to each planned weight is determined based on the planned static calorie consumption data, the planned calorie intake data and the weight change.

12. The data processing method according to claim 11, characterized in that: The step of determining the planned dynamic calorie consumption data corresponding to each planned weight based on the planned static calorie consumption data, the planned calorie intake data and the weight change includes: Determine a total calorie difference based on the weight change and the initial physical parameter, and distribute the total calorie difference according to the number of the planned weights to determine a planned calorie difference corresponding to each planned weight; The planned dynamic calorie consumption data is obtained by subtracting the planned static calorie consumption data from the sum of the planned calorie difference and the planned calorie intake data.

13. The data processing method according to claim 10, characterized in that: After determining a plurality of planned weights and planned dynamic calorie consumption data corresponding to each planned weight based on the initial physical parameters and the acquired weight management plan data, the method further includes: Prompt information is displayed based on the planned dynamic calorie consumption data corresponding to each planned weight.

14. The data processing method according to claim 13, characterized in that: The display prompt information based on the planned dynamic calorie consumption data corresponding to each planned weight includes one of the following: If the planned dynamic calorie consumption data corresponding to each planned weight is greater than the consumption threshold, a prompt message indicating that the weight management plan data is unreasonable is displayed; If the planned dynamic calorie consumption data corresponding to each planned weight is not greater than the consumption threshold, reasonable prompt information of the weight management plan data is displayed.

15. A data processing device, characterized in that: include: A data acquisition unit, for acquiring activity data and image data within a historical period for a target object; wherein the image data is a heat source image of the target object when calorie intake occurs within the historical period; a determination unit, configured to determine a calorie consumption difference of the target object in the historical period based on the activity data, the physical parameters of the target object, and the image data; wherein the calorie consumption difference represents a difference between the calorie consumption and the calorie intake of the target object in the historical period; The determination unit is further used to determine weight management information based on the calorie consumption difference and the physical parameter.

16. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program executable on the processor, and the processor implements the steps in the method according to any one of claims 1 to 14 when executing the computer program.

17. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 14 are implemented.

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