A nutritional health management system and method based on endocrine patients

Abstract

The present invention provides a nutrition and health management system and method based on endocrine patients, including: a data acquisition module for collecting information data of target patients, and analyzing the information data of target patients to determine nutrition demand elements; a program formulation module for formulating nutrition and health management programs according to nutrition demand elements; a monitoring module for monitoring the endocrine index transformation characteristics of target patients based on nutrition and health management programs within a preset time period; a dynamic optimization module for dynamically optimizing nutrition and health management programs according to index transformation characteristics, and generating an adaptive health dynamic management library based on target patients according to the optimization results. Effectively realize intelligent nutrition and health management of target patients, and provide convenience for health management.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a nutrition and health management system and method based on endocrine patients. Background Art

[0002] At present, the endocrine system plays a key role in regulating the physiological functions of the human body and maintaining homeostasis. There are many types of endocrine diseases, such as diabetes, thyroid disease, adrenal disease, etc. These diseases often have a significant impact on the patient's metabolism, energy consumption and nutritional needs;

[0003] Currently, there are some challenges and deficiencies in the management of endocrine patients. The complexity of the nutritional needs of patients with endocrine diseases is not well understood. The nutritional needs of patients with different endocrine diseases vary greatly, and their needs may change dynamically as the disease progresses and treatment proceeds.

[0004] However, traditional nutrition management methods are often more general, lacking specific considerations for endocrine diseases, and cannot meet the individualized nutritional needs of patients. Nutrition-related problems encountered by patients in daily life cannot be answered promptly and effectively, which can easily lead to incorrect dietary behaviors and health concepts. It is also difficult for medical staff to grasp the actual situation of patients in a timely manner, affecting the intervention effect.

[0005] Therefore, in order to overcome the above technical problems, the present invention provides a nutritional health management system and method based on endocrine patients. Summary of the invention

[0006] The present invention provides a nutrition and health management system and method based on endocrine patients, which is used to collect information data of target patients, so as to facilitate effective analysis of the information data, and then accurately determine the nutrition and health management plan formulated based on nutritional elements, and monitor the indicator transformation characteristics of the target patients based on the nutrition and health management plan within a preset time period, so as to facilitate effective determination of the target patients' adaptability to the nutrition and health management plan, and dynamically optimize the nutrition and health management plan through the indicator transformation characteristics, so as to realize dynamic management of the target patients, and effectively realize intelligent nutrition and health management of the target patients by constructing an adaptive health dynamic management library, thereby providing convenience for health management.

[0007] The present invention provides a nutritional health management system based on endocrine patients, comprising:

[0008] A data collection module is used to collect information data of target patients and analyze the information data of target patients to determine nutritional requirement elements;

[0009] The program formulation module is used to formulate nutrition and health management programs based on nutritional demand elements;

[0010] A monitoring module is used to monitor the endocrine index change characteristics of the target patient based on the nutrition and health management plan within a preset time period;

[0011] The dynamic optimization module is used to dynamically optimize the nutrition and health management plan according to the indicator transformation characteristics, and generate an adaptive health dynamic management library based on the target patients according to the optimization results.

[0012] Preferably, a nutrition and health management system based on endocrine patients, a data acquisition module, comprises:

[0013] The information collection unit is used to obtain data collection dimensions, and collect information according to the data collection dimensions to obtain multi-dimensional information data.

[0014] The data analysis unit is used to analyze multi-dimensional information data and output the nutritional requirement elements of the target patients.

[0015] Preferably, a nutrition and health management system based on endocrine patients, the information collection unit comprises:

[0016] The request acquisition subunit is used to obtain a request for access permission to retrieve information of a target patient, wherein the request for access permission includes: an identity tag of the target patient and an access permission code;

[0017] The request determination subunit is used to transmit the access permission request to the patient information database for matching, and determine whether the information data of the target patient can be retrieved according to the access permission request;

[0018] The first matching subunit is configured to:

[0019] Performing a first match between the identity tag of the target patient in the access permission request and the identity tag set in the patient information database;

[0020] If the identity tag of the target patient does not exist in the identity tag set in the matching result, it is determined that the information data of the target patient cannot be retrieved according to the retrieval permission request;

[0021] If the target patient's identity tag exists in the identity tag set in the matching result, the corresponding target authorization code is retrieved from the patient information database according to the target patient's identity tag;

[0022] The second matching subunit is used for:

[0023] Perform a second match between the access permission code and the target authorization code;

[0024] If the access permission code does not match the target authorization code, it is determined that the target patient's information data cannot be retrieved according to the access permission request;

[0025] An information data retrieval subunit, configured to retrieve information data matching the target patient from a patient information database based on the target authorization code and the identity tag of the target patient if the retrieval authority code matches the target authorization code;

[0026] Multi-dimensional division sub-units are used to:

[0027] Read the data collection dimensions and determine the dimension identifier corresponding to each data collection dimension;

[0028] Data matching criteria for information collection based on dimension identifier configuration;

[0029] The information data is identified according to the data matching standard, and the information data is divided according to the identification to obtain the sub-information data segment corresponding to each data collection dimension.

[0030] Preferably, a nutritional health management system based on endocrine patients, a data analysis unit, comprises:

[0031] A data acquisition subunit is used to extract keywords from the collected information data, determine the medical detection dimensions contained in the information data based on the keywords, and split the information data based on the medical detection dimensions to obtain multi-category detection data;

[0032] The data analysis subunit is used to:

[0033] Retrieving nutrient element detection indicators and corresponding indicator values ​​from a server based on nutrient element detection requirements, and building a nutrient element detection system based on the nutrient element detection indicators and corresponding indicator values;

[0034] Based on the nutrient element detection system, each category of test data is analyzed separately to obtain the nutrient element amount contained in each category of test data, and the nutrient element amount corresponding to each category of test data is weighted and summed to obtain the multi-dimensional nutrient element ratio of the target patient;

[0035] The nutritional requirement element determination unit is used to compare the nutritional element ratio with the benchmark nutritional element ratio, and determine the nutritional requirement element based on the comparison result. At the same time, a visualization template is called up, and the nutritional requirement element and the multi-dimensional nutritional element ratio are visualized based on the visualization template.

[0036] Preferably, a nutrition and health management system based on endocrine patients, a program formulation module, includes:

[0037] Nutritional analysis unit for:

[0038] Obtain the obtained nutritional requirement elements, and at the same time, obtain the current multi-dimensional nutritional element ratio of the target patient, and determine the required amount of the nutritional requirement elements based on the multi-dimensional nutritional element ratio and the reasonable nutritional element ratio target;

[0039] Determine the current nutritional element level of the target patient based on the nutritional requirement elements and the corresponding required amounts, and determine multi-category nutritional element intervention measures for the target patient based on the nutritional element level;

[0040] Nutrition and health management program determination unit is used to:

[0041] Determine the supplementary weights of multiple nutrient element intervention measures for nutrient elements, and divide the nutrient requirement elements proportionally based on the supplementary weights to obtain the sub-requirements corresponding to each category of nutrient element intervention measures;

[0042] Obtaining the physical index data of the target patient, and analyzing the physical index data to determine the physical function level of the target patient;

[0043] Based on the physical function level, determine the dietary intake corresponding to the sub-required nutritional elements of the target patient under each category of nutritional element intervention measures, and divide the dietary intake into multiple frequency time nodes to obtain the single dietary intake;

[0044] Based on the division results, the single dietary amounts corresponding to the different categories of nutrient element intervention measures at the same time node are summarized to obtain the single multi-category dietary amounts of the target patients, and the single multi-category dietary amounts are bound to the corresponding dietary time nodes;

[0045] Get a nutrition and health management plan based on the binding results.

[0046] Preferably, a nutritional health management system based on endocrine patients, a monitoring module, comprises:

[0047] A first change curve determination unit is used to collect a data set of changes in nutritional requirement elements of a target patient based on a nutritional health management program within a preset time period, and to construct a first data change curve corresponding to the data set of changes in nutritional requirement elements of the target patient within the preset time period;

[0048] A second change curve determination unit, used to collect an endocrine indicator change data set of a target patient based on a nutrition and health management program within a preset time period, and construct a second data change curve corresponding to the endocrine indicator change data set of the target patient within the preset time period;

[0049] a correlation factor determination unit, configured to overlap the first data change curve and the second data change curve according to a preset time period, and obtain a correlation factor between the first data change curve and the second data change curve;

[0050] The endocrine indicator change characteristic determination unit is used to determine the endocrine indicator change characteristics corresponding to the target patient's nutritional requirement elements changing within a preset time period based on the associated factors.

[0051] Preferably, a nutrition and health management system based on endocrine patients, a dynamic optimization module, comprises:

[0052] A result acquisition unit is used to acquire the obtained endocrine index transformation characteristics, and determine the change amplitude of the content of the nutritional requirement elements of the target patient under the nutritional health management program based on the endocrine index transformation characteristics, and at the same time, based on the preset monitoring sensor, perform multi-frequency random collection of the endocrine sign data of the target patient under the nutritional health management program to obtain endocrine data groups at different times;

[0053] Effect verification unit, used for:

[0054] Based on the specific time corresponding to the endocrine data group, the change amplitude of the content of the nutritional requirement element is serialized to obtain the stage change characteristics of the content of the nutritional requirement element, and the stage change characteristics of the content of the nutritional requirement element at the same time are first associated with the endocrine data;

[0055] At the same time, the first correlation results at different times are subjected to a second correlation to obtain a control data group, and the target change characteristics caused by the change amplitude of the endocrine data of the target patient relative to the content of the nutritional requirement element are determined based on the control data group;

[0056] Dynamic optimization unit for:

[0057] Determine the endocrine optimization trend of the target patient based on the target change characteristics, and when the endocrine optimization trend does not meet the preset change benchmark value, determine the category of the nutrient element to be optimized and the corresponding optimization parameter based on the control data group;

[0058] Based on the categories of nutritional elements to be optimized and the corresponding optimization parameters, the coordinated adjustment parameters of the nutritional health management plan are determined, and the nutritional health management plan is dynamically optimized based on the coordinated adjustment parameters.

[0059] Preferably, a nutrition and health management system based on endocrine patients, a dynamic optimization module, comprises:

[0060] A result statistics unit is used to obtain dynamic optimization parameters corresponding to the dynamic optimization results of the nutrition and health management plan of the target patient in different time periods, and encapsulate the dynamic optimization parameters to obtain a dynamic optimization mechanism;

[0061] The adaptive health dynamic management library construction unit is used to add object tags to the dynamic optimization mechanism, and summarize the dynamic optimization mechanisms of the same target patient in different time periods based on the object tags, and build an adaptive health dynamic management library for the target patient based on the summary results.

[0062] Preferably, a nutrition and health management system based on endocrine patients, a dynamic optimization module, comprises:

[0063] An update data monitoring unit, used to monitor in real time whether there is update data when generating an adaptive health dynamic management library based on a target patient;

[0064] A positioning unit, used for locating target original nutrition and health management data in the adaptive dynamic management library based on the updated data when the updated data exists;

[0065] A calculation unit, used for calculating the similarity between the updated data and the target original nutrition and health management data;

[0066] ;

[0067] in, Indicates the similarity between the updated data and the target original nutrition and health management data; Indicates update data; Indicates the target original nutritional health data value; A semantic vector representing the updated data; A semantic vector representing the target original nutritional health data; The modulus of the semantic vector representing the updated data; The modulus of the semantic vector representing the target original nutrition and health data;

[0068] Update the judgment function building unit to:

[0069] According to the similarity between the updated data and the target original nutrition and health management data, an update judgment function is constructed;

[0070] ;

[0071] in, represents the update decision function; Indicates the lower similarity threshold; Indicates the upper threshold of similarity;

[0072] The updating determination unit is used to:

[0073] when When the update data is not updated in the adaptive health dynamic management library, it is determined that the update data is not updated;

[0074] when When the data is updated, it is determined that the update data will be updated in the adaptive health dynamic management library.

[0075] The present invention provides a method for nutritional health management of endocrine patients, comprising:

[0076] Step 1: Collect the target patient's information data, and analyze the target patient's information data to determine the nutritional requirement elements;

[0077] Step 2: Develop a nutrition and health management plan based on nutritional requirements;

[0078] Step 3: Monitor the endocrine index change characteristics of the target patient based on the nutrition and health management plan within a preset time period;

[0079] Step 4: Dynamically optimize the nutrition and health management plan according to the indicator transformation characteristics, and generate an adaptive health dynamic management library based on the target patients according to the optimization results.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] By collecting information data of target patients, it is convenient to effectively analyze the information data, and then accurately determine the nutrition and health management plan based on nutritional elements. By monitoring the indicator change characteristics of the target patients based on the nutrition and health management plan within a preset time period, it is convenient to effectively determine the target patients' adaptability to the nutrition and health management plan, and dynamically optimize the nutrition and health management plan through the indicator change characteristics to achieve dynamic management of target patients. By building an adaptive health dynamic management library, intelligent nutrition and health management of target patients can be effectively achieved, providing convenience for health management.

[0082] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0083] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0085] Figure 1 This is a structural diagram of a nutrition and health management system based on endocrine patients in an embodiment of the present invention;

[0086] Figure 2 This is a structural diagram of a dynamic optimization module in a nutrition and health management system for endocrine patients according to an embodiment of the present invention;

[0087] Figure 3 The present invention is a flowchart of a method for nutritional health management for endocrine patients according to an embodiment of the present invention. DETAILED DESCRIPTION

[0088] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0089] Embodiment 1:

[0090] This embodiment provides a nutritional health management system based on endocrine patients, such as Figure 1 As shown, including:

[0091] A data collection module is used to collect information data of target patients and analyze the information data of target patients to determine nutritional requirement elements;

[0092] The program formulation module is used to formulate nutrition and health management programs based on nutritional demand elements;

[0093] A monitoring module is used to monitor the indicator change characteristics of the target patient based on the nutrition and health management plan within a preset time period;

[0094] The dynamic optimization module is used to dynamically optimize the nutrition and health management plan according to the indicator transformation characteristics, and generate an adaptive health dynamic management library based on the target patients according to the optimization results.

[0095] In this embodiment, the information data of the target patient may include: the endocrine disease type, medical history, various physiological indicators and physical condition of the target patient.

[0096] In this embodiment, the nutritional requirement elements may be elements such as proteins, vitamins, and minerals required by endocrine patients (i.e., target patients), and are used to characterize the elements that the target patients currently need to supplement, which are one or more of the elements such as proteins, vitamins, and minerals.

[0097] In this embodiment, the nutritional health management plan may be an implementation plan that represents the combination of dietary types, dietary quantity restrictions, dietary time points, time intervals, etc. for the target patient, which is formulated based on the currently required nutritional requirement elements.

[0098] In this embodiment, the preset time period may be set in advance to limit the indicator change state of the target patient within the preset time period (wherein the indicator change characteristics may be used to characterize the change of the target patient's physical indicators, and the physical indicators may include data indicators such as the target patient's blood pressure, blood sugar, and blood lipids).

[0099] In this embodiment, the adaptive health dynamic management library can be a database that stores strategies for dynamically adjusting the health of the current target patient, which is used to implement intelligent nutritional health management for endocrine patients (target patients) and provide convenience for health management.

[0100] The working principle and beneficial effects of the above technical scheme are: by collecting information data of target patients, it is convenient to effectively analyze the information data, and then accurately determine the nutritional health management plan based on nutritional elements; by monitoring the indicator change characteristics of the target patients based on the nutritional health management plan within a preset time period, it is convenient to effectively determine the target patients' adaptability to the nutritional health management plan, and dynamically optimize the nutritional health management plan through the indicator change characteristics to achieve dynamic management of target patients; by building an adaptive health dynamic management library, it is possible to effectively realize intelligent nutritional health management of target patients, providing convenience for health management.

[0101] Embodiment 2:

[0102] Based on Example 1, this embodiment provides a nutrition and health management system based on endocrine patients, and the data acquisition module includes:

[0103] The information collection unit is used to obtain data collection dimensions, and collect information according to the data collection dimensions to obtain multi-dimensional information data.

[0104] The data analysis unit is used to analyze multi-dimensional information data and output the nutritional requirement elements of the target patients.

[0105] In this embodiment, the data collection dimension may be a data collection type that characterizes the data collection for the target patient, including the medical history and physiological indicators of the target patient.

[0106] In this embodiment, the multi-dimensional information data refers to the final result obtained after multi-dimensional data collection is performed on the target patient according to the determined data collection dimensions.

[0107] The working principle and beneficial effects of the above technical solution are: by determining the data collection dimensions for the target patients, it is possible to collect various types of data of the target patients according to the data collection dimensions, effectively acquire the multi-dimensional information data, and after analyzing the multi-dimensional information data, accurately and reliably determine the nutritional requirement elements of the target patients, thereby facilitating accurate and reliable nutritional health management of endocrine patients based on the nutritional requirement elements.

[0108] Embodiment 3:

[0109] Based on Example 1, this embodiment provides a nutrition and health management system based on endocrine patients, and the information collection unit includes:

[0110] The request acquisition subunit is used to obtain a request for access permission to retrieve information of a target patient, wherein the request for access permission includes: an identity tag of the target patient and an access permission code;

[0111] The request determination subunit is used to transmit the access permission request to the patient information database for matching, and determine whether the information data of the target patient can be retrieved according to the access permission request;

[0112] The first matching subunit is used for:

[0113] Performing a first match between the identity tag of the target patient in the access permission request and the identity tag set in the patient information database;

[0114] If the identity tag of the target patient does not exist in the identity tag set in the matching result, it is determined that the information data of the target patient cannot be retrieved according to the retrieval permission request;

[0115] If the target patient's identity tag exists in the identity tag set in the matching result, the corresponding target authorization code is retrieved from the patient information database according to the target patient's identity tag;

[0116] The second matching subunit is used for:

[0117] Perform a second match between the access permission code and the target authorization code;

[0118] If the access permission code does not match the target authorization code, it is determined that the target patient's information data cannot be retrieved according to the access permission request;

[0119] An information data retrieval subunit, configured to retrieve information data matching the target patient from a patient information database based on the target authorization code and the identity tag of the target patient if the retrieval authority code matches the target authorization code;

[0120] Multi-dimensional division sub-units are used to:

[0121] Read the data collection dimensions and determine the dimension identifier corresponding to each data collection dimension;

[0122] Data matching criteria for information collection based on dimension identifier configuration;

[0123] The information data is identified according to the data matching standard, and the information data is divided according to the identification to obtain the sub-information data segment corresponding to each data collection dimension.

[0124] In this embodiment, the identity tag may be a marking symbol used to distinguish different patients.

[0125] In this embodiment, the access permission code may be specific code information corresponding to different access permissions.

[0126] In this embodiment, the identity tag set may be all identity tags corresponding to different patients contained in the patient information database.

[0127] In this embodiment, the target authorization code can be the identity and authority code corresponding to the target patient in the patient information database, which is used to match and verify with the retrieval authority code in the retrieval authority request, thereby facilitating the corresponding retrieval of the target patient's information data according to the target authorization code.

[0128] In this embodiment, the dimension identifier may be a marking symbol used to distinguish different data collection dimensions.

[0129] In this embodiment, the data matching standard is used to limit the criteria for dividing the collected information data into different dimensions, with the purpose of matching the collected information data of the target patient with the corresponding data collection dimensions, wherein the sub-information data segment is the specific information data corresponding to each dimension.

[0130] The working principle and beneficial effects of the above technical solution are: by obtaining the retrieval permission request for information retrieval, the identity tag and the corresponding retrieval permission code of the target patient are accurately and effectively determined according to the retrieval permission request; secondly, the identity tag and the retrieval permission code are matched with the identity tag set and the target authorization code corresponding to different patients in the patient information database respectively, and finally, the information data corresponding to the target patient is accurately and effectively retrieved in multiple dimensions according to the matching result; finally, the retrieved information data is divided according to the data collection dimension, so as to realize the accurate and effective acquisition of the multi-dimensional information data of the target patient, and provide reliable data support for building the corresponding health management plan for the target patient.

[0131] Embodiment 4:

[0132] Based on Example 2, this embodiment provides a nutrition and health management system based on endocrine patients, and the data analysis unit includes:

[0133] A data acquisition subunit is used to extract keywords from the collected information data, determine the medical detection dimensions contained in the information data based on the keywords, and split the information data based on the medical detection dimensions to obtain multi-category detection data;

[0134] The data analysis subunit is used to:

[0135] Retrieving nutrient element detection indicators and corresponding indicator values ​​from a server based on nutrient element detection requirements, and building a nutrient element detection system based on the nutrient element detection indicators and corresponding indicator values;

[0136] Based on the nutrient element detection system, each category of test data is analyzed separately to obtain the nutrient element amount contained in each category of test data, and the nutrient element amount corresponding to each category of test data is weighted and summed to obtain the multi-dimensional nutrient element ratio of the target patient;

[0137] The nutritional requirement element determination unit is used to compare the nutritional element ratio with the benchmark nutritional element ratio, and determine the nutritional requirement element based on the comparison result. At the same time, a visualization template is called up, and the nutritional requirement element and the multi-dimensional nutritional element ratio are visualized based on the visualization template.

[0138] In this embodiment, the keyword may be a key data segment in the information data that can represent the main content of the information data.

[0139] In this embodiment, the medical examination dimension may be the type of medical examination performed on the target patient represented in the information data, such as blood sugar, blood pressure, heart rate, etc.

[0140] In this embodiment, the multi-category detection data may be specific data content of multiple different categories obtained by dividing the information data according to the medical detection dimension.

[0141] In this embodiment, the requirements for nutrient element detection are known in advance and are used to characterize the rigor of nutrient element detection, etc.

[0142] In this embodiment, the nutrient element detection index refers to the standards and rules that need to be followed when detecting the nutrient elements, wherein the index value is used to characterize the specific requirements or degrees defined by different nutrient element detection indexes.

[0143] In this embodiment, the amount of nutrient elements refers to the specific content or value of each nutrient element contained in the detection data of each category.

[0144] In this embodiment, the nutritional element ratio is used to characterize the proportion of different nutritional elements in the current body of the target patient, so as to facilitate the determination of the nutritional requirement elements of the target patient.

[0145] In this embodiment, the base nutrient element ratio is known in advance.

[0146] The working principle and beneficial effects of the above technical solution are: by splitting the collected information data, the information data is split into different categories of detection data, and the nutrient element detection indicators and corresponding indicator values ​​are retrieved to achieve accurate and effective determination of the multi-dimensional nutrient element ratios of the target patients; secondly, by comparing the multi-dimensional nutrient element ratios with the benchmark nutrient element ratios, the nutritional requirement elements of the target patients are accurately and effectively locked, and the nutritional requirement elements and the multi-dimensional nutrient element ratios are visualized, which is convenient for the target patients to intuitively and effectively understand their own conditions, and also convenient for reliable nutritional health management of the target patients based on the nutritional requirement elements.

[0147] Embodiment 5:

[0148] Based on Example 1, this embodiment provides a nutrition and health management system based on endocrine patients, and a program formulation module, including:

[0149] Nutritional analysis unit for:

[0150] Obtain the obtained nutritional requirement elements, and at the same time, obtain the current multi-dimensional nutritional element ratio of the target patient, and determine the required amount of the nutritional requirement elements based on the multi-dimensional nutritional element ratio and the reasonable nutritional element ratio target;

[0151] Determine the current nutritional element level of the target patient based on the nutritional requirement elements and the corresponding required amounts, and determine multi-category nutritional element intervention measures for the target patient based on the nutritional element level;

[0152] Nutrition and health management program determination unit is used to:

[0153] Determine the supplementary weights of multiple nutrient element intervention measures for nutrient elements, and divide the nutrient requirement elements proportionally based on the supplementary weights to obtain the sub-requirements corresponding to each category of nutrient element intervention measures;

[0154] Obtaining the physical index data of the target patient, and analyzing the physical index data to determine the physical function level of the target patient;

[0155] Based on the physical function level, determine the dietary intake corresponding to the sub-required nutritional elements of the target patient under each category of nutritional element intervention measures, and divide the dietary intake into multiple frequency time nodes to obtain the single dietary intake;

[0156] Based on the division results, the single dietary amounts corresponding to the different categories of nutrient element intervention measures at the same time node are summarized to obtain the single multi-category dietary amounts of the target patients, and the single multi-category dietary amounts are bound to the corresponding dietary time nodes;

[0157] Get a nutrition and health management plan based on the binding results.

[0158] In this embodiment, the multi-dimensional nutrient element ratio may be the ratio relationship between different nutrient elements in the current body of the target patient.

[0159] In this embodiment, the reasonable nutrient element ratio target may be a standard value that needs to be achieved in representing the ratio between different nutrient elements in the target patient's body, that is, representing the proportional relationship between the corresponding nutrient elements under a healthy condition.

[0160] In this embodiment, the nutrient level may be a level that represents the current nutrient level in the target patient.

[0161] In this embodiment, the multi-category nutrient element intervention measures refer to specific intervention measures that need to be taken when supplementing nutrient elements for target patients, including the type and composition of the diet.

[0162] In this embodiment, the supplementation weight is used to characterize the effectiveness of different types of nutrient element intervention measures when supplementing nutrient elements.

[0163] In this embodiment, the proportional splitting can be to split the nutritional requirement elements of the target patient according to the supplementation weights, in order to determine the specific supplementation amounts, i.e., sub-requirements, required when different categories of nutritional element intervention measures are used for nutritional element supplementation.

[0164] In this embodiment, the physical function level may be a representation of the current physical condition of the target patient, including metabolic capacity and the like.

[0165] In this embodiment, the multi-frequency time node division refers to dividing the food intake, so as to facilitate determination of the specific food intake for each time and to facilitate intermittent supplementation of nutrients for the target patients.

[0166] In this embodiment, the target patient's single multi-category dietary intake may be all diets that can supplement different nutritional elements corresponding to each target patient's diet, for example, the total amount of vegetables, meat and other items.

[0167] The working principle and beneficial effects of the above technical scheme are: by determining the current multi-dimensional nutrient element ratio of the target patient, the target patient's nutritional requirement element demand can be accurately and effectively determined according to the multi-dimensional nutrient element ratio, and the target patient's current nutrient element level can be accurately and effectively evaluated according to the obtained demand; secondly, the multi-category nutrient element intervention measures for the target patient are determined according to the obtained nutrient element level, and the sub-requirements corresponding to the multi-category nutrient element intervention measures are locked; finally, considering the target patient's current physical function level, the target patient's single multi-category dietary amount can be accurately and effectively determined according to the target patient's physical function level and sub-requirements; at the same time, each dietary time node is analyzed, and the obtained single multi-category dietary amount and dietary time node are bound, finally, the nutritional health management plan for the target patient is accurately and effectively formulated, ensuring the effectiveness and reliability of nutritional health management for the target patient.

[0168] Embodiment 6:

[0169] Based on Example 1, this embodiment provides a nutrition and health management system based on endocrine patients, and the monitoring module includes:

[0170] A first change curve determination unit is used to collect a data set of changes in nutritional requirement elements of a target patient based on a nutritional health management program within a preset time period, and to construct a first data change curve corresponding to the data set of changes in nutritional requirement elements of the target patient within the preset time period;

[0171] A second change curve determination unit, used to collect an endocrine indicator change data set of a target patient based on a nutrition and health management program within a preset time period, and construct a second data change curve corresponding to the endocrine indicator change data set of the target patient within the preset time period;

[0172] a correlation factor determination unit, configured to overlap the first data change curve and the second data change curve according to a preset time period, and obtain a correlation factor between the first data change curve and the second data change curve;

[0173] The endocrine indicator change characteristic determination unit is used to determine the endocrine indicator change characteristics corresponding to the target patient's nutritional requirement elements changing within a preset time period based on the associated factors.

[0174] In this embodiment, the preset time period is set in advance, for example, it may be one week or one month.

[0175] In this embodiment, the nutritional requirement element change data set may be the change data of the nutritional requirement elements of the target patient under the formulated nutritional health management plan.

[0176] In this embodiment, the first data change curve may be a specific fluctuation of a data set representing a change in a nutritional requirement element over time.

[0177] In this embodiment, the endocrine indicator change data set may be changes in blood sugar, blood lipids, heart rate, etc. of the target patient under the nutrition and health management program.

[0178] In this embodiment, the second data change curve may be a specific fluctuation of the endocrine indicator change data set that represents the development of the data set over time.

[0179] In this embodiment, the correlation factor may be a causal relationship between the first data change curve and the second data change curve, thereby facilitating accurate and effective determination of the endocrine indicator change characteristics of the target patient through changes in nutritional requirement elements.

[0180] The working principle and beneficial effects of the above technical solution are: by monitoring the nutritional requirement element change data set and the endocrine indicator change data set of the target patient within a preset time period and under the nutritional health management plan, and converting the monitored nutritional requirement element change data set and the endocrine indicator change data set into a first data change curve and a second data change curve respectively, it is possible to lock the correlation factors between the nutritional requirement elements and the endocrine indicators according to the first data change curve and the second data change curve, thereby determining the change characteristics of the endocrine indicators according to the correlation factors, and facilitating the effective dynamic optimization of the formulated health management plan according to the determined endocrine indicator change characteristics, thereby improving the effect of health management for endocrine patients.

[0181] Embodiment 7:

[0182] Based on Example 1, this example provides a nutritional health management system for endocrine patients, such as Figure 2 As shown, the dynamic optimization module includes:

[0183] A result acquisition unit is used to acquire the obtained endocrine index transformation characteristics, and determine the change amplitude of the content of the nutritional requirement elements of the target patient under the nutritional health management program based on the endocrine index transformation characteristics, and at the same time, based on the preset monitoring sensor, perform multi-frequency random collection of the endocrine sign data of the target patient under the nutritional health management program to obtain endocrine data groups at different times;

[0184] Effect verification unit, used for:

[0185] Based on the specific time corresponding to the endocrine data group, the change amplitude of the content of the nutritional requirement element is serialized to obtain the stage change characteristics of the content of the nutritional requirement element, and the stage change characteristics of the content of the nutritional requirement element at the same time are first associated with the endocrine data;

[0186] At the same time, the first correlation results at different times are subjected to a second correlation to obtain a control data group, and the target change characteristics caused by the change amplitude of the endocrine data of the target patient relative to the content of the nutritional requirement element are determined based on the control data group;

[0187] Dynamic optimization unit for:

[0188] Determine the endocrine optimization trend of the target patient based on the target change characteristics, and when the endocrine optimization trend does not meet the preset change benchmark value, determine the category of the nutrient element to be optimized and the corresponding optimization parameter based on the control data group;

[0189] Based on the categories of nutritional elements to be optimized and the corresponding optimization parameters, the coordinated adjustment parameters of the nutritional health management plan are determined, and the nutritional health management plan is dynamically optimized based on the coordinated adjustment parameters.

[0190] In this embodiment, the change amplitude is used to characterize the change in the content of the nutritional requirement elements of the target patient under the nutritional health management program.

[0191] In this embodiment, the preset monitoring sensor is set in advance.

[0192] In this embodiment, the stage change feature may be the change of the nutritional requirement element over time.

[0193] In this embodiment, the first association may be to compare the phase changes of the content of the nutritional requirement elements at the same time with the endocrine data.

[0194] In this embodiment, the second association may be to associate the first association results at different times, with the purpose of analyzing the first association results at different times and constructing a comparison data set.

[0195] In this embodiment, the target change feature refers to the change trend of the endocrine data due to the change amplitude of the content of the nutritional requirement element.

[0196] In this embodiment, the preset change reference value is set in advance.

[0197] In this embodiment, the categories of nutritional elements to be optimized and the corresponding optimization parameters may be specific categories of nutritional elements that need to be optimized in the nutritional health management plan and the corresponding specific optimization degrees.

[0198] The working principle and beneficial effects of the above technical scheme are as follows: the change amplitude of the content of the nutritional requirement elements of the target patient under the nutritional health management plan and the endocrine sign data at different times are determined by the obtained endocrine indicator change characteristics, and the determined change amplitude of the content of the nutritional requirement elements and the endocrine sign data at different times are compared and analyzed, so as to accurately and effectively determine the target change characteristics of the endocrine data of the target patient relative to the change amplitude of the content of the nutritional requirement elements, and finally, determine the endocrine optimization trend of the target patient according to the obtained target change characteristics, and when the endocrine optimization trend does not meet the preset change benchmark value, determine the category of the nutritional elements to be optimized and the corresponding optimization parameters, so as to realize timely and effective dynamic optimization of the nutritional health management plan according to the category of the nutritional elements to be optimized and the corresponding optimization parameters, thereby ensuring the nutritional health management effect for endocrine patients.

[0199] Embodiment 8:

[0200] Based on any one of Embodiments 1 to 7, this embodiment provides a nutrition and health management system for endocrine patients, a dynamic optimization module, including:

[0201] A result statistics unit is used to obtain dynamic optimization parameters corresponding to the dynamic optimization results of the nutrition and health management plan of the target patient in different time periods, and encapsulate the dynamic optimization parameters to obtain a dynamic optimization mechanism;

[0202] The adaptive health dynamic management library construction unit is used to add object tags to the dynamic optimization mechanism, and summarize the dynamic optimization mechanisms of the same target patient in different time periods based on the object tags, and build an adaptive health dynamic management library for the target patient based on the summary results.

[0203] In this embodiment, the dynamic optimization parameters may be the specific optimization content and the specific optimization parameters corresponding to the optimization of the nutrition and health management program.

[0204] In this embodiment, the dynamic optimization mechanism may be a specific strategy for optimizing the nutrition and health management plan under different circumstances determined by dynamic optimization parameters corresponding to the dynamic optimization results of the nutrition and health management plan in different time periods.

[0205] In this embodiment, the object label may be used to characterize the patients to which the dynamic optimization mechanism can be applied, thereby facilitating targeted and effective optimization of health management plans for different patients based on the object label.

[0206] The working principle and beneficial effects of the above technical solution are: by encapsulating the dynamic optimization parameters corresponding to the dynamic optimization results of the nutritional health management plan of the target patient in different time periods, the dynamic optimization mechanism can be accurately and effectively acquired; secondly, the dynamic optimization mechanisms of the same target patient in different time periods are summarized to accurately and effectively construct an adaptive health dynamic management library for the target patient.

[0207] Embodiment 9:

[0208] Based on any one of Embodiments 1 to 7, this embodiment provides a nutrition and health management system for endocrine patients, a dynamic optimization module, including:

[0209] An update data monitoring unit, used to monitor in real time whether there is update data when generating an adaptive health dynamic management library based on a target patient;

[0210] A positioning unit, used for locating target original nutrition and health management data in the adaptive dynamic management library based on the updated data when the updated data exists;

[0211] A calculation unit, used for calculating the similarity between the updated data and the target original nutrition and health management data;

[0212] ;

[0213] in, Indicates the similarity between the updated data and the target original nutrition and health management data; Indicates update data; Indicates the target original nutritional health data value; A semantic vector representing the updated data; A semantic vector representing the target original nutritional health data; The modulus of the semantic vector representing the updated data; The modulus of the semantic vector representing the target original nutrition and health data;

[0214] Update the judgment function building unit to:

[0215] According to the similarity between the updated data and the target original nutrition and health management data, an update judgment function is constructed;

[0216] ;

[0217] in, represents the update decision function; Indicates the lower similarity threshold; Indicates the upper threshold of similarity;

[0218] The updating determination unit is used to:

[0219] when When the update data is not updated in the adaptive health dynamic management library, it is determined that the update data is not updated;

[0220] when When the data is updated, it is determined that the update data will be updated in the adaptive health dynamic management library.

[0221] In this embodiment, the target original nutrition and health management data may be nutrition and health management data associated with the update data.

[0222] The working principle and beneficial effects of the above technical solution are: by real-time monitoring whether there is updated data in the adaptive health dynamic management library of the target patient, and when more detailed data exists, the target original nutritional health management data in the adaptive dynamic management library is located, and the similarity between the two is calculated based on the positioning result, and an update judgment function is constructed based on the similarity, so as to determine whether to update the updated data in the adaptive health dynamic management library according to the update judgment function, thereby ensuring the real-time effectiveness and reliability of the adaptive health dynamic management library, and providing a guarantee for nutritional health management of endocrine patients.

[0223] Embodiment 10:

[0224] This embodiment provides a nutritional health management method for endocrine patients. Figure 3 As shown, including:

[0225] Step 1: Collect the target patient's information data, and analyze the target patient's information data to determine the nutritional requirement elements;

[0226] Step 2: Develop a nutrition and health management plan based on nutritional requirements;

[0227] Step 3: Monitor the endocrine index change characteristics of the target patient based on the nutrition and health management plan within a preset time period;

[0228] Step 4: Dynamically optimize the nutrition and health management plan according to the indicator transformation characteristics, and generate an adaptive health dynamic management library based on the target patients according to the optimization results.

[0229] The working principle and beneficial effects of the above technical scheme are: by collecting information data of target patients, it is convenient to effectively analyze the information data, and then accurately determine the nutritional health management plan based on nutritional elements; by monitoring the indicator change characteristics of the target patients based on the nutritional health management plan within a preset time period, it is convenient to effectively determine the target patients' adaptability to the nutritional health management plan, and dynamically optimize the nutritional health management plan through the indicator change characteristics to achieve dynamic management of target patients; by building an adaptive health dynamic management library, it is possible to effectively realize intelligent nutritional health management of target patients, providing convenience for health management.

[0230] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A nutritional health management system based on endocrine patients, characterized in that: include: A data collection module is used to collect information data of target patients and analyze the information data of target patients to determine nutritional requirement elements; The program formulation module is used to formulate nutrition and health management programs based on nutritional demand elements; A monitoring module is used to monitor the endocrine index change characteristics of the target patient based on the nutrition and health management plan within a preset time period; Dynamic optimization module, used to dynamically optimize the nutrition and health management plan according to the transformation characteristics of endocrine indicators, and generate an adaptive health dynamic management library based on target patients according to the optimization results; The dynamic optimization module comprises: A result acquisition unit is used to acquire the obtained endocrine index transformation characteristics, and determine the change amplitude of the content of the nutritional requirement elements of the target patient under the nutritional health management program based on the endocrine index transformation characteristics, and at the same time, based on the preset monitoring sensor, perform multi-frequency random collection of the endocrine sign data of the target patient under the nutritional health management program to obtain endocrine data groups at different times; Effect verification unit, used for: Based on the specific time corresponding to the endocrine data group, the change amplitude of the content of the nutritional requirement element is serialized to obtain the stage change characteristics of the content of the nutritional requirement element, and the stage change characteristics of the content of the nutritional requirement element at the same time are first associated with the endocrine data; At the same time, the first correlation results at different times are subjected to a second correlation to obtain a control data group, and the target change characteristics caused by the change amplitude of the endocrine data of the target patient relative to the content of the nutritional requirement element are determined based on the control data group; Dynamic optimization unit for: Determine the endocrine optimization trend of the target patient based on the target change characteristics, and when the endocrine optimization trend does not meet the preset change benchmark value, determine the category of the nutrient element to be optimized and the corresponding optimization parameter based on the control data group; Determine the coordinated adjustment parameters of the nutrition and health management plan based on the categories of the nutritional elements to be optimized and the corresponding optimization parameters, and dynamically optimize the nutrition and health management plan based on the coordinated adjustment parameters; The dynamic optimization module comprises: An update data monitoring unit, used to monitor in real time whether there is update data when generating an adaptive health dynamic management library based on a target patient; A positioning unit, used for locating target original nutrition and health management data in the adaptive dynamic management library based on the updated data when the updated data exists; A calculation unit, used for calculating the similarity between the updated data and the target original nutrition and health management data; ； in, Indicates the similarity between the updated data and the target original nutrition and health management data; Indicates update data; Represents the target original nutrition and health management data; A semantic vector representing the updated data; A semantic vector representing the target original nutrition and health management data; The modulus of the semantic vector representing the updated data; The modulus of the semantic vector representing the target original nutrition and health management data; Update the judgment function building unit to: According to the similarity between the updated data and the target original nutrition and health management data, an update judgment function is constructed; ； in, represents the update decision function; Indicates the lower similarity threshold; Indicates the upper threshold of similarity; The updating determination unit is used to: when When the update data is not updated in the adaptive health dynamic management library, it is determined that the update data is not updated; when When the data is updated, it is determined that the update data will be updated in the adaptive health dynamic management library.

2. A nutritional health management system based on endocrine patients according to claim 1, characterized in that: Data acquisition module, including: The information collection unit is used to obtain the data collection dimension, and collect information according to the data collection dimension to obtain multi-dimensional information data. The data analysis unit is used to analyze multi-dimensional information data and output the nutritional requirement elements of the target patients.

3. A nutritional health management system based on endocrine patients according to claim 2, characterized in that: The information collection unit includes: The request acquisition subunit is used to obtain a request for access permission to retrieve information of a target patient, wherein the request for access permission includes: an identity tag of the target patient and an access permission code; The request determination subunit is used to transmit the access permission request to the patient information database for matching, and determine whether the information data of the target patient can be retrieved according to the access permission request; The first matching subunit is used for: Performing a first match between the identity tag of the target patient in the access permission request and the identity tag set in the patient information database; If the identity tag of the target patient does not exist in the identity tag set in the matching result, it is determined that the information data of the target patient cannot be retrieved according to the retrieval permission request; If the target patient's identity tag exists in the identity tag set in the matching result, the corresponding target authorization code is retrieved from the patient information database according to the target patient's identity tag; The second matching subunit is used for: Perform a second match between the access permission code and the target authorization code; If the access permission code does not match the target authorization code, it is determined that the target patient's information data cannot be retrieved according to the access permission request; An information data retrieval subunit, configured to retrieve information data matching the target patient from a patient information database based on the target authorization code and the identity tag of the target patient if the retrieval authority code matches the target authorization code; Multi-dimensional division sub-units are used to: Read the data collection dimensions and determine the dimension identifier corresponding to each data collection dimension; Data matching criteria for information collection based on dimension identifier configuration; The information data is identified according to the data matching standard, and the information data is divided according to the identification to obtain the sub-information data segment corresponding to each data collection dimension.

4. A nutritional health management system based on endocrine patients according to claim 2, characterized in that: Data Analysis Unit, including: A data acquisition subunit is used to extract keywords from the collected information data, determine the medical detection dimensions contained in the information data based on the keywords, and split the information data based on the medical detection dimensions to obtain multi-category detection data; The data analysis subunit is used to: Retrieving nutrient element detection indicators and corresponding indicator values ​​from a server based on nutrient element detection requirements, and building a nutrient element detection system based on the nutrient element detection indicators and corresponding indicator values; Based on the nutrient element detection system, each category of test data is analyzed separately to obtain the nutrient element amount contained in each category of test data, and the nutrient element amount corresponding to each category of test data is weighted and summed to obtain the multi-dimensional nutrient element ratio of the target patient; The nutritional requirement element determination unit is used to compare the nutritional element ratio with the benchmark nutritional element ratio, and determine the nutritional requirement element based on the comparison result. At the same time, a visualization template is called up, and the nutritional requirement element and the multi-dimensional nutritional element ratio are visualized based on the visualization template.

5. A nutritional health management system based on endocrine patients according to claim 1, characterized in that: Program development module, including: Nutritional analysis unit for: Obtain the obtained nutritional requirement elements, and at the same time, obtain the current multi-dimensional nutritional element ratio of the target patient, and determine the required amount of the nutritional requirement elements based on the multi-dimensional nutritional element ratio and the reasonable nutritional element ratio target; Determine the current nutritional element level of the target patient based on the nutritional requirement elements and the corresponding required amounts, and determine multi-category nutritional element intervention measures for the target patient based on the nutritional element level; Nutrition and health management program determination unit is used to: Determine the supplementary weights of multiple nutrient element intervention measures for nutrient elements, and divide the nutrient requirement elements proportionally based on the supplementary weights to obtain the sub-requirements corresponding to each category of nutrient element intervention measures; Obtaining the physical index data of the target patient, and analyzing the physical index data to determine the physical function level of the target patient; Based on the physical function level, determine the dietary intake corresponding to the sub-required nutritional elements of the target patient under each category of nutritional element intervention measures, and divide the dietary intake into multiple frequency time nodes to obtain the single dietary intake; Based on the division results, the single dietary amounts corresponding to the different categories of nutrient element intervention measures at the same time node are summarized to obtain the single multi-category dietary amounts of the target patients, and the single multi-category dietary amounts are bound to the corresponding dietary time nodes; Get a nutrition and health management plan based on the binding results.

6. A nutritional health management system based on endocrine patients according to claim 1, characterized in that: Monitoring modules, including: A first change curve determination unit is used to collect a data set of changes in nutritional requirement elements of a target patient based on a nutritional health management program within a preset time period, and to construct a first data change curve corresponding to the data set of changes in nutritional requirement elements of the target patient within the preset time period; A second change curve determination unit, used to collect an endocrine indicator change data set of a target patient based on a nutrition and health management program within a preset time period, and construct a second data change curve corresponding to the endocrine indicator change data set of the target patient within the preset time period; a correlation factor determination unit, configured to overlap the first data change curve and the second data change curve according to a preset time period, and obtain a correlation factor between the first data change curve and the second data change curve; The endocrine indicator change characteristic determination unit is used to determine the endocrine indicator change characteristics corresponding to the target patient's nutritional requirement elements changing within a preset time period based on the associated factors.

7. A nutritional health management system for endocrine patients according to any one of claims 1 to 6, characterized in that: Dynamic optimization module, including: A result statistics unit is used to obtain dynamic optimization parameters corresponding to dynamic optimization results of nutrition and health management programs of target patients in different time periods, and encapsulate the dynamic optimization parameters in different time periods to obtain dynamic optimization mechanisms in different time periods; The adaptive health dynamic management library construction unit is used to add object tags to the dynamic optimization mechanism, and summarize the dynamic optimization mechanisms of the same target patient in different time periods based on the object tags, and build an adaptive health dynamic management library for the target patient based on the summary results.

8. A nutritional health management method for endocrine patients, characterized in that: include: Step 1: Collect the target patient's information data, and analyze the target patient's information data to determine the nutritional requirement elements; Step 2: Develop a nutrition and health management plan based on nutritional requirements; Step 3: Monitor the endocrine index change characteristics of the target patient based on the nutrition and health management plan within a preset time period; Step 4: Dynamically optimize the nutrition and health management plan according to the transformation characteristics of endocrine indicators, and generate an adaptive health dynamic management library based on target patients according to the optimization results; The step 4 comprises: The endocrine index transformation characteristics are obtained, and based on the endocrine index transformation characteristics, the change amplitude of the content of the nutritional elements required by the target patient under the nutritional health management program is determined. At the same time, the endocrine sign data of the target patient under the nutritional health management program is randomly collected at multiple frequencies based on the preset monitoring sensors to obtain endocrine data groups at different times; Based on the specific time corresponding to the endocrine data group, the change amplitude of the content of the nutritional requirement element is serialized to obtain the stage change characteristics of the content of the nutritional requirement element, and the stage change characteristics of the content of the nutritional requirement element at the same time are first associated with the endocrine data; At the same time, the first correlation results at different times are subjected to a second correlation to obtain a control data group, and the target change characteristics caused by the change amplitude of the endocrine data of the target patient relative to the content of the nutritional requirement element are determined based on the control data group; Determine the endocrine optimization trend of the target patient based on the target change characteristics, and when the endocrine optimization trend does not meet the preset change benchmark value, determine the category of the nutrient element to be optimized and the corresponding optimization parameter based on the control data group; Determine the coordinated adjustment parameters of the nutrition and health management plan based on the categories of the nutritional elements to be optimized and the corresponding optimization parameters, and dynamically optimize the nutrition and health management plan based on the coordinated adjustment parameters; The step 4 comprises: When generating an adaptive health dynamic management library based on target patients, monitor in real time whether there is updated data; When updated data exists, locating the target original nutrition and health management data in the adaptive dynamic management library based on the updated data; Calculate the similarity between the updated data and the target original nutrition and health management data; ； in, Indicates the similarity between the updated data and the target original nutrition and health management data; Indicates update data; Represents the target original nutrition and health management data; A semantic vector representing the updated data; A semantic vector representing the target original nutrition and health management data; The modulus of the semantic vector representing the updated data; The modulus of the semantic vector representing the target original nutrition and health management data; According to the similarity between the updated data and the target original nutrition and health management data, an update judgment function is constructed; ； in, represents the update decision function; Indicates the lower threshold of similarity; Indicates the upper threshold of similarity; when When the update data is not updated in the adaptive health dynamic management library, it is determined that the update data is not updated; when When the data is updated, it is determined that the update data will be updated in the adaptive health dynamic management library.

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