Intelligent generation method for healthy diet suggestions of user

Abstract

According to the intelligent generation method for the healthy diet suggestions of the user, the category and the content of the nutrition ingested by the user are calculated, and if the change amplitude between the historical health state index and the current-day health state index of the user is larger than the preset amplitude threshold value, the healthy diet suggestions of the user are generated. If yes, calculating a difference proportion of corresponding health state data in the historical health state indexes and the health state indexes of the day, selecting target health state data, and adjusting diet data of the user; the category and content of food ingested by a user are obtained through automatic analysis, the category and content of nutrition ingested are calculated, and whether the health state data of the user is abnormal or not is judged according to the change amplitude between the historical health state index of the user and the health state index of the day. If yes, the diet data of the user is adjusted according to the abnormal data to obtain healthy diet data, so that the health state data of the user is tracked in real time, and healthy diet is accurately recommended to improve the diet health of the user.

Description

Technical Field

[0001] This application relates to the technical field of healthy diet management, and specifically to an intelligent generation method for users' healthy diet suggestions. Background Art

[0002] With the improvement of people's living standards and the enhancement of health awareness, the demand for nutritional management of food intake is increasing day by day. However, traditional food nutrition analysis methods often require manual weighing, classification, and nutritional calculation of food. This method is not only time-consuming and laborious, but also easily affected by human factors, resulting in low accuracy of analysis results. Therefore, a method that can automatically identify the ingested food and nutrients and accurately give healthy diet suggestions to the eaters is needed. Summary of the Invention

[0003] To solve the above technical problems, this application is proposed. Embodiments of this application provide an intelligent generation method for users' healthy diet suggestions.

[0004] This application provides an intelligent generation method for users' healthy diet suggestions, including: obtaining the user's diet data; wherein, the diet data includes the categories and contents of the food ingested by the user; based on the categories and contents of the food ingested by the user, calculating the nutritional categories and nutritional contents ingested by the user; obtaining the user's daily health status indicators; wherein, the daily health status indicators include the change curve of the user's health status data on the current day; calculating the change range between the user's historical health status indicators and the current day's health status indicators; if the change range is greater than a preset range threshold, then calculating the difference ratio of the corresponding health status data in the historical health status indicators and the current day's health status indicators; selecting the health status data corresponding to the difference ratio exceeding the preset ratio threshold as the target health status data; based on the target health status data, adjusting the user's diet data to obtain the user's healthy diet data.

[0005] In one embodiment, calculating the change range between the user's historical health status indicators and the current day's health status indicators includes: calculating the change range of each health status data in the historical health status indicators and the current day's health status indicators at the same moment; based on the change range at each moment, comprehensively calculating the change range of each health status data.

[0006] In one embodiment, if the change range is greater than a preset range threshold, calculating the difference ratio of the corresponding health status data in the historical health status indicator and the current-day health status indicator includes: if the change range of one piece of health status data is greater than the range threshold, calculating the difference ratio of this health status data in the historical health status indicator and the current-day health status indicator; wherein, the difference ratio is the ratio of the difference between this health status data in the historical health status indicator and the current-day health status indicator to this health status data in the historical health status indicator.

[0007] In one embodiment, adjusting the user's diet data based on the target health status data to obtain the user's healthy diet data includes: based on the target health status data, determining the food category that causes the change in the target health status data; adjusting the food category or content in the user's diet data that causes the change in the target health status data to obtain the user's healthy diet data.

[0008] In one embodiment, the intelligent generation method for the user's healthy diet advice further includes: obtaining the user's current-day exercise data; dynamically adjusting the range threshold based on the user's current-day exercise data and the user's historical exercise data.

[0009] In one embodiment, dynamically adjusting the range threshold based on the user's current-day exercise data and the user's historical exercise data includes: if the current-day exercise data is higher than the user's historical exercise data, increasing the range threshold.

[0010] In one embodiment, obtaining the user's diet data includes: obtaining the user's diet pictures; identifying the diet pictures to obtain the diet data.

[0011] In one embodiment, identifying the diet pictures to obtain the diet data includes: identifying the diet pictures to obtain the categories of the foods ingested by the user; measuring the weights of the foods ingested by the user to obtain the content of the foods ingested by the user.

[0012] In one embodiment, selecting the health status data corresponding to the difference ratio exceeding a preset ratio threshold as the target health status data includes: sorting the difference ratios of all health status data from small to large; selecting the first or the first few health status data corresponding to the difference ratios as the target health status data.

[0013] In one embodiment, after obtaining the user's healthy diet data, the intelligent generation method for the user's healthy diet advice further includes: recommending the user's healthy diet data to the user.

[0014] The intelligent generation method for user's healthy diet advice provided by this application obtains the user's diet data; among them, the diet data includes the types and amounts of foods ingested by the user; based on the types and amounts of foods ingested by the user, calculates the types and amounts of nutrients ingested by the user; obtains the user's daily health status indicators; among them, the daily health status indicators include the change curve of the user's health status data on the current day; calculates the change range between the user's historical health status indicators and the current day's health status indicators; if the change range is greater than the preset range threshold, calculates the difference ratio of the corresponding health status data in the historical health status indicators and the current day's health status indicators; selects the health status data corresponding to the difference ratio exceeding the preset ratio threshold as the target health status data; based on the target health status data, adjusts the user's diet data to obtain the user's healthy diet data; by automatically analyzing, knows the types and amounts of foods ingested by the user, calculates the types and amounts of nutrients ingested, judges whether there is an abnormality in the user's health status data according to the change range between the user's historical health status indicators and the current day's health status indicators, and if so, adjusts the user's diet data according to the abnormal data to obtain healthy diet data, so as to track the user's health status data in real time and accurately recommend a healthy diet to improve the user's diet health. Brief Description of the Drawings

[0015] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other objects, features, and advantages of the present application will become more obvious. The accompanying drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation to the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0016] Figure 1 It is a flowchart of the intelligent generation method for user's healthy diet advice provided by an exemplary embodiment of the present application.

[0017] Figure 2 It is a structural diagram of the intelligent generation system for user's healthy diet advice provided by an exemplary embodiment of the present application.

[0018] Figure 3 It is a structural diagram of an electronic device provided by an exemplary embodiment of the present application. Detailed Description of the Embodiments

[0019] Next, exemplary embodiments of the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein.

[0020] Figure 1It is a schematic flowchart of a method for intelligently generating user's healthy diet suggestions provided by an exemplary embodiment of the present application. As Figure 1 shown, the method for intelligently generating user's healthy diet suggestions includes the following steps: Step 110: Obtain the user's diet data.

[0021] Among them, the diet data includes the types and amounts of foods ingested by the user. By obtaining the types and amounts of foods ingested by the user, the types and corresponding amounts of the user's diet are determined, serving as the total intake value of the user and the basis for subsequent healthy diet suggestions.

[0022] Step 120: Calculate the types and amounts of nutrients ingested by the user based on the types and amounts of foods ingested by the user.

[0023] According to the types and amounts of foods ingested by the user, calculate the types and amounts of nutrients ingested by the user to determine the types and amounts of various nutrients actually ingested by the user, serving as the input data for subsequent evaluation of whether the user's diet is healthy.

[0024] Step 130: Obtain the user's daily health status indicators.

[0025] Among them, the daily health status indicators include the change curve of the user's health status data on the day. By monitoring the user's daily health status indicators, such as the health status indicators collected at specific times (before meals and after meals, etc.), it serves as the main reference curve for measuring the user's physical state.

[0026] Step 140: Calculate the change range between the user's historical health status indicators and the daily health status indicators.

[0027] By calculating the change range between the user's historical health status indicators and the daily health status indicators, the change amount of the user's health status indicators in the later stage of the day's diet is determined, thereby determining the impact of the types and amounts of the day's diet on the user's health.

[0028] Step 150: If the change range is greater than a preset range threshold, calculate the difference ratio of the corresponding health status data in the historical health status indicators and the daily health status indicators.

[0029] If the calculated change range is small, it indicates that the day's diet has little impact on the user's health status. If the change range is greater than the preset range threshold, it indicates that the day's diet has a greater impact on the user's health status. At this time, calculate the difference ratio of each corresponding health status data in the historical health status indicators and the daily health status indicators to determine which health status data causes this change range.

[0030] Step 160: Select the health status data corresponding to the difference ratio exceeding the preset ratio threshold as the target health status data.

[0031] Select the health status data corresponding to the difference ratio exceeding the preset ratio threshold as the target health status data, that is, select the health status data with a larger difference ratio as the target for research and adjustment. In another embodiment, the present application may also sort the difference ratios of all health status data from small to large, and select the first one or the first few as the target health status data.

[0032] Step 170: Based on the target health status data, adjust the user's diet data to obtain the user's healthy diet data.

[0033] After determining the target health status data, consider the foods ingested involved in the target health status data, and adjust the corresponding ingested food categories or amounts based on the user's diet data to obtain the user's healthy diet data, and recommend the healthy diet data to the user to improve the user's health status.

[0034] The intelligent generation method for the user's healthy diet advice provided by the present application includes obtaining the user's diet data, where the diet data includes the categories and amounts of foods ingested by the user; calculating the nutritional categories and nutritional amounts ingested by the user based on the categories and amounts of foods ingested by the user; obtaining the user's current health status indicators, where the current health status indicators include the change curve of the user's health status data on the current day; calculating the change range between the user's historical health status indicators and the current health status indicators; if the change range is greater than the preset range threshold, then calculate the difference ratio of the corresponding health status data in the historical health status indicators and the current health status indicators; select the health status data corresponding to the difference ratio exceeding the preset ratio threshold as the target health status data; based on the target health status data, adjust the user's diet data to obtain the user's healthy diet data; automatically analyze to know the categories and amounts of foods ingested by the user, calculate the ingested nutritional categories and nutritional amounts, judge whether there is an abnormality in the user's health status data according to the change range between the user's historical health status indicators and the current health status indicators, and if so, adjust the user's diet data according to the abnormal data to obtain the healthy diet data, so as to track the user's health status data in real time and accurately recommend a healthy diet to improve the user's diet health.

[0035] In one embodiment, the specific implementation manner of the above step 140 may be: calculate the change range of each health status data in the historical health status indicators and the current health status indicators at the same moment; based on the change range of each moment, comprehensively calculate the change range of each health status data.

[0036] By calculating the change amplitude of each health status data in the historical health status indicators and the current-day health status indicators at the same moment, that is, calculating one change amplitude at the same moment, and comprehensively calculating the change amplitude of each health status data by combining the change amplitudes at each moment. Specifically, the change amplitude of each health status data can be calculated by using the weighted average method from the change amplitudes at each moment, where the weights of the change amplitudes within the preset time before meals and within the preset time after meals are greater than the weights at other moments.

[0037] In one embodiment, the specific implementation manner of the above step 150 can be: If the change amplitude of a health status data is greater than the amplitude threshold, then calculate the difference ratio between the historical health status indicators and the current-day health status indicators for this health status data; where the difference ratio is the ratio of the difference between this health status data in the historical health status indicators and the current-day health status indicators to this health status data in the historical health status indicators.

[0038] If the change amplitude of one or more health status data is greater than the amplitude threshold, it indicates that the change amount of the corresponding health status data is relatively large. At this time, calculate the difference ratio between the historical health status indicators and the current-day health status indicators for this health status data to determine the change ratio of this health status data, so as to determine its influence degree.

[0039] In one embodiment, the specific implementation manner of the above step 170 can be: Based on the target health status data, determine the food category that causes the change in the target health status data; adjust the food category or content in the user's diet data that causes the change in the target health status data to obtain the user's healthy diet data. In a further embodiment, after obtaining the user's healthy diet data in this application, recommend the user's healthy diet data to the user for the user to adjust their diet data.

[0040] Determine the food category that causes the change in the target health status data according to the target health status data, that is, determine the corresponding food type according to the nutritional category corresponding to the target health status data, and then adjust the food type or the corresponding quantity in the user's diet data to obtain the user's new healthy diet data, that is, obtain the user's new diet recommendation.

[0041] In one embodiment, the intelligent generation method of the above user's healthy diet advice may further include: Obtain the user's current-day exercise data; Dynamically adjust the amplitude threshold based on the user's current-day exercise data and the user's historical exercise data.

[0042] Real-time collect the user's exercise data through exercise monitoring devices such as sports bracelets to determine the user's exercise data for the day, and dynamically adjust the amplitude threshold based on the exercise data for the day and the user's historical exercise data. In a further embodiment, if the user's exercise data for the day is higher than the historical exercise data, the amplitude threshold can be appropriately increased to reduce the increase in the change amplitude of the health status indicators caused by the increase in exercise volume, thereby improving the accuracy of subsequent healthy diet recommendations.

[0043] In one embodiment, the specific implementation manner of the above step 110 may be: obtain the user's diet picture; identify the diet picture to obtain diet data.

[0044] This application obtains the user's diet picture through an image acquisition device such as a camera, and obtains the user's diet data by identifying the diet picture, that is, automatically obtains the types and contents of the foods ingested by the user, reducing the degree of manual participation.

[0045] In one embodiment, the specific implementation manner of the above step 110 may be: identify the diet picture to obtain the types of foods ingested by the user; measure the weight of the foods ingested by the user to obtain the content of the foods ingested by the user.

[0046] This application compares the image of the ingested food with the food images stored in the database. Based on the similarity between the image of the ingested food and the stored food images, if there is a stored food image with a similarity greater than the threshold, the food category corresponding to the stored food image is used as the food category of the ingested food identified by the image of the ingested food. At the same time, a metering device is used to measure the weight of the foods ingested by the user to obtain the content of the foods ingested by the user. And after obtaining the types and weights of the ingested foods, according to the nutritional components and corresponding nutritional contents of various foods stored in the system, calculate the nutritional components and corresponding nutritional contents of the foods ingested by the user.

[0047] Figure 2 It is a schematic structural diagram of an intelligent generation system for the user's healthy diet recommendations provided by an exemplary embodiment of this application. As Figure 2As shown in the figure, the intelligent generation system 20 for the user's healthy diet advice includes: a diet data acquisition module 21 for acquiring the user's diet data; wherein the diet data includes the types and amounts of foods ingested by the user; a nutrient component calculation module 22 for calculating the types and amounts of nutrients ingested by the user based on the types and amounts of foods ingested by the user; a health index acquisition module 23 for acquiring the user's daily health status index; wherein the daily health status index includes the change curve of the user's health status data on the current day; a change amplitude calculation module 24 for calculating the change amplitude between the user's historical health status index and the daily health status index; a difference ratio calculation module 25 for calculating the difference ratio of the corresponding health status data in the historical health status index and the daily health status index if the change amplitude is greater than a preset amplitude threshold; a target data selection module 26 for selecting the health status data corresponding to the difference ratio exceeding the preset ratio threshold as the target health status data; and a healthy diet generation module 27 for adjusting the user's diet data based on the target health status data to obtain the user's healthy diet data.

[0048] The intelligent generation system for the user's healthy diet advice provided by this application acquires the user's diet data through the diet data acquisition module 21; wherein the diet data includes the types and amounts of foods ingested by the user; the nutrient component calculation module 22 calculates the types and amounts of nutrients ingested by the user based on the types and amounts of foods ingested by the user; the health index acquisition module 23 acquires the user's daily health status index; wherein the daily health status index includes the change curve of the user's health status data on the current day; the change amplitude calculation module 24 calculates the change amplitude between the user's historical health status index and the daily health status index; if the change amplitude is greater than the preset amplitude threshold, the difference ratio calculation module 25 calculates the difference ratio of the corresponding health status data in the historical health status index and the daily health status index; the target data selection module 26 selects the health status data corresponding to the difference ratio exceeding the preset ratio threshold as the target health status data; the healthy diet generation module 27 adjusts the user's diet data based on the target health status data to obtain the user's healthy diet data; by automatically analyzing, it learns the types and amounts of foods ingested by the user, calculates the types and amounts of nutrients ingested, judges whether there is an abnormality in the user's health status data according to the change amplitude between the user's historical health status index and the daily health status index, and if so, adjusts the user's diet data according to the abnormal data to obtain the data of a healthy diet, so as to track the user's health status data in real time and accurately recommend a healthy diet to improve the user's diet health.

[0049] In one embodiment, the above-mentioned change amplitude calculation module 24 can be further configured to: calculate the change amplitude of each health status data in the historical health status indicator and the current-day health status indicator at the same moment; based on the change amplitude at each moment, comprehensively calculate the change amplitude of each health status data.

[0050] In one embodiment, the above-mentioned difference ratio calculation module 25 can be further configured to: if the change amplitude of a health status data is greater than the amplitude threshold, calculate the difference ratio of this health status data in the historical health status indicator and the current-day health status indicator; wherein, the difference ratio is the ratio of the difference between this health status data in the historical health status indicator and the current-day health status indicator to this health status data in the historical health status indicator.

[0051] In one embodiment, the above-mentioned healthy diet generation module 27 can be further configured to: based on the target health status data, determine the food categories that cause the change in the target health status data; adjust the food categories or contents in the user's diet data that cause the change in the target health status data to obtain the user's healthy diet data.

[0052] In one embodiment, the above-mentioned intelligent generation system 20 for user's healthy diet suggestions can be further configured to: obtain the user's current-day exercise data; dynamically adjust the amplitude threshold based on the user's current-day exercise data and the user's historical exercise data.

[0053] In one embodiment, the above-mentioned diet data acquisition module 21 can be further configured to: obtain the user's diet pictures; identify the diet pictures to obtain diet data.

[0054] In one embodiment, the above-mentioned diet data acquisition module 21 can be further configured to: identify the diet pictures to obtain the categories of the foods ingested by the user; measure the weights of the foods ingested by the user to obtain the contents of the foods ingested by the user.

[0055] Next, refer to Figure 3 to describe the electronic device according to the embodiment of the present application. The electronic device can be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device can communicate with the first device and the second device to receive the input signals collected from them.

[0056] Figure 3 The block diagram of the electronic device according to the embodiment of the present application is illustrated.

[0057] As Figure 3 shown, the electronic device 10 includes one or more processors 11 and a memory 12.

[0058] The processor 11 may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0059] The memory 12 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage media, and the processor 11 may run the program instructions to implement the methods of the various embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage media.

[0060] In one example, the electronic device 10 may further include: an input device 13 and an output device 14, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0061] When the electronic device is a stand-alone device, the input device 13 may be a communication network connector for receiving the collected input signals from the first device and the second device.

[0062] In addition, the input device 13 may further include, for example, a keyboard, a mouse, and so on.

[0063] The output device 14 may output various information to the outside, including the determined distance information, direction information, etc. The output device 14 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, and so on.

[0064] Of course, for simplicity, Figure 3 only some of the components related to the present application in the electronic device 10 are shown, and components such as buses, input / output interfaces, etc. are omitted. In addition, according to specific application scenarios, the electronic device 10 may further include any other appropriate components.

[0065] In addition to the above methods and devices, the embodiments of the present application may also be a computer program product, which includes computer program instructions, and the computer program instructions, when run by a processor, cause the processor to execute the steps in the methods according to the various embodiments of the present application described in the "Exemplary Method" section above in this specification.

[0066] The computer program product may be written in any combination of one or more programming languages for executing the program code of the operations of the embodiments of the present application. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, executed as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0067] In addition, an embodiment of the present application may also be a computer-readable storage medium storing computer program instructions, which, when run by a processor, cause the processor to execute the steps in the methods according to various embodiments of the present application described in the "Exemplary Method" section above of this specification.

[0068] The computer-readable storage medium may employ any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may, for example, include but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0069] The basic principles of the present application have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present application. In addition, the above-disclosed specific details are only for illustrative purposes and for ease of understanding, and are not limitations. The above details do not limit the present application to necessarily adopt the above specific details for implementation.

[0070] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any way. Words such as "including", "comprising", "having", etc. are open-ended terms, meaning "including but not limited to", and can be used interchangeably with each other. The words "or" and "and" used herein refer to the phrase "and / or" and can be used interchangeably with it, unless the context clearly indicates otherwise. The phrase "such as" used herein refers to the phrase "such as but not limited to" and can be used interchangeably with it.

[0071] It should also be noted that in the devices, equipment, and methods of this application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of this application.

[0072] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0073] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. An intelligent generation method for user's healthy diet suggestions, characterized in that, Including: Obtain the user's dietary data; wherein, the dietary data includes the categories and amounts of foods ingested by the user; Based on the categories and amounts of foods ingested by the user, calculate the nutritional categories and nutritional amounts ingested by the user; Obtain the user's daily health status indicators; wherein, the daily health status indicators include the change curve of the user's health status data on the current day; Calculate the change amplitude between the user's historical health status indicators and the current day's health status indicators; If the change amplitude is greater than a preset amplitude threshold, then calculate the difference ratio of the corresponding health status data in the historical health status indicators and the current day's health status indicators; Select the health status data corresponding to the difference ratio exceeding the preset ratio threshold as the target health status data; Based on the target health status data, adjust the user's dietary data to obtain the user's healthy dietary data.

2. The intelligent generation method of user's healthy diet advice according to claim 1, characterized in that The calculating the change amplitude between the user's historical health status indicators and the current day's health status indicators includes: Calculate the change amplitude of each health status data in the historical health status indicators and the current day's health status indicators at the same moment; Based on the change amplitude at each moment, comprehensively calculate the change amplitude of each health status data.

3. The intelligent generation method of user's healthy diet advice according to claim 2, characterized in that, The if the change amplitude is greater than a preset amplitude threshold, then calculate the difference ratio of the corresponding health status data in the historical health status indicators and the current day's health status indicators includes: If the change amplitude of a health status data is greater than the amplitude threshold, then calculate the difference ratio of this health status data in the historical health status indicators and the current day's health status indicators; wherein, the difference ratio is the ratio of the difference between this health status data in the historical health status indicators and the current day's health status indicators to this health status data in the historical health status indicators.

4. The intelligent generation method of user's healthy diet advice according to claim 1, characterized in that The based on the target health status data, adjust the user's dietary data to obtain the user's healthy dietary data includes: Based on the target health status data, determine the food categories that cause the change in the target health status data; Adjust the food categories or amounts in the user's dietary data that cause the change in the target health status data to obtain the user's healthy dietary data.

5. The intelligent generation method of user's healthy diet advice according to claim 1, characterized in that, The intelligent generation method for the user's healthy dietary suggestions further includes: Obtain the user's current day's exercise data; Based on the user's current day's exercise data and the user's historical exercise data, dynamically adjust the amplitude threshold.

6. The intelligent generation method of user's healthy diet advice according to claim 5, characterized in that, The based on the user's current day's exercise data and the user's historical exercise data, dynamically adjust the amplitude threshold includes: If the current day's exercise data is higher than the user's historical exercise data, then increase the amplitude threshold.

7. The intelligent generation method of user's healthy diet advice according to claim 1, characterized in that The obtaining the user's dietary data includes: Obtain the user's dietary pictures; Identify the dietary pictures to obtain the dietary data.

8. The intelligent generation method of user's healthy diet advice according to claim 7, characterized in that The identifying the dietary pictures to obtain the dietary data includes: Identify the dietary pictures to obtain the categories of foods ingested by the user; Measure the weight of the foods ingested by the user to obtain the amounts of foods ingested by the user.

9. The intelligent generation method of user's healthy diet advice according to claim 1, characterized in that, Selecting the health status data corresponding to the difference ratio exceeding a preset ratio threshold as the target health status data includes: Sorting the difference ratios of all health status data from small to large; Selecting the health status data corresponding to the first or the first few difference ratios as the target health status data.

10. The intelligent generation method of user's healthy diet advice according to claim 1, characterized in that, After obtaining the user's healthy diet data, the intelligent generation method for the user's healthy diet advice further includes: Recommending the user's healthy diet data to the user.

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