CN118538368A - Health management system based on cloud - Google Patents
- ️Fri Aug 23 2024
CN118538368A - Health management system based on cloud - Google Patents
Health management system based on cloud Download PDFInfo
-
Publication number
- CN118538368A CN118538368A CN202411017043.0A CN202411017043A CN118538368A CN 118538368 A CN118538368 A CN 118538368A CN 202411017043 A CN202411017043 A CN 202411017043A CN 118538368 A CN118538368 A CN 118538368A Authority
- CN
- China Prior art keywords
- health
- data
- individual
- user
- behavior Prior art date
- 2024-07-29 Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Biomedical Technology (AREA)
- Pathology (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Nutrition Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biophysics (AREA)
- Physical Education & Sports Medicine (AREA)
- Medical Treatment And Welfare Office Work (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
本发明涉及健康监测技术领域,具体为一种基于云的健康管理系统,系统包括数据标准化与权重确定模块、组合优化评分模块、多目标健康管理策略模块和健康改善模块。本发明,通过集成的云基础架构优化了健康数据的收集与处理流程,使得个体健康监测变得更加灵活和实时,能够即时同步并分析来自多源的健康数据,包括生理和行为指标,实现数据的高效整合与动态权重调整,使健康状态评估更加准确,支持生成精确的健康评分,能够根据实时数据调整健康管理策略,优化个体的健康管理,能够自动识别健康目标间的冲突,并基于个体的健康历史与偏好生成定制的健康改善措施,增加了干预措施的适应性和有效性。
The present invention relates to the field of health monitoring technology, specifically to a cloud-based health management system, the system including a data standardization and weight determination module, a combination optimization scoring module, a multi-objective health management strategy module and a health improvement module. The present invention optimizes the collection and processing process of health data through an integrated cloud infrastructure, making individual health monitoring more flexible and real-time, and can instantly synchronize and analyze health data from multiple sources, including physiological and behavioral indicators, to achieve efficient data integration and dynamic weight adjustment, making health status assessment more accurate, supporting the generation of accurate health scores, and being able to adjust health management strategies according to real-time data, optimize individual health management, automatically identify conflicts between health goals, and generate customized health improvement measures based on individual health history and preferences, thereby increasing the adaptability and effectiveness of intervention measures.
Description
技术领域Technical Field
本发明涉及健康监测技术领域,尤其涉及一种基于云的健康管理系统。The present invention relates to the technical field of health monitoring, and in particular to a cloud-based health management system.
背景技术Background Art
健康监测技术领域涉及使用多种设备和系统来实时或定期收集、分析和解释个体的健康相关数据。技术通常包括可穿戴设备、移动应用、远程监控设备和专门的医疗仪器,通过设备和应用跟踪各种生理参数,包括心率、血压、血糖水平和体温等。能够通过收集数据提供实时反馈,用于预防疾病、管理慢性病症、优化治疗方案和提高生活质量。The field of health monitoring technology involves the use of a variety of devices and systems to collect, analyze and interpret an individual's health-related data in real time or periodically. Technologies typically include wearable devices, mobile applications, remote monitoring devices and specialized medical instruments, which track various physiological parameters, including heart rate, blood pressure, blood sugar levels and body temperature, through devices and applications. The ability to provide real-time feedback through the collection of data is used to prevent diseases, manage chronic conditions, optimize treatment plans and improve quality of life.
其中,健康管理系统旨在管理个人的健康状况,通过收集、存储和分析用户的健康数据,支持健康风险评估、疾病预防和日常健康习惯的跟踪。利用集成的软件和硬件工具来监控用户的健康状况,提供定制的健康改善建议,并管理用户的医疗记录和治疗历程,辅助用户更好地理解和管理自己的健康状况,从而提高生活质量。Among them, the health management system is designed to manage personal health conditions, and supports health risk assessment, disease prevention, and tracking of daily health habits by collecting, storing, and analyzing users' health data. It uses integrated software and hardware tools to monitor users' health conditions, provide customized health improvement suggestions, and manage users' medical records and treatment history, helping users better understand and manage their health conditions, thereby improving their quality of life.
传统健康管理系统依靠分散的设备收集健康数据,缺乏高效的数据整合和实时更新机制,导致信息孤岛现象,处理速度和数据的实时性受限,在紧急情况下会导致关键健康信息的延迟处理,影响健康管理的实时性。传统系统缺乏针对个体差异的深度定制,忽视了用户间的生理和生活习惯差异,导致管理建议的适用性和用户满意度低。Traditional health management systems rely on scattered devices to collect health data, lacking efficient data integration and real-time update mechanisms, leading to information islands, limited processing speed and data real-time performance, and delayed processing of key health information in emergency situations, affecting the real-time performance of health management. Traditional systems lack deep customization for individual differences, ignoring differences in physiology and living habits among users, resulting in low applicability of management recommendations and low user satisfaction.
发明内容Summary of the invention
本发明的目的是解决现有技术中存在的缺点,而提出的一种基于云的健康管理系统。The purpose of the present invention is to solve the shortcomings of the prior art and to propose a cloud-based health management system.
为了实现上述目的,本发明采用了如下技术方案:一种基于云的健康管理系统,所述系统包括:In order to achieve the above object, the present invention adopts the following technical solution: a cloud-based health management system, the system comprising:
数据标准化与权重确定模块基于可穿戴设备和医疗仪器,收集用户的生理和行为指标数据,对指标数据进行标准化处理,剔除异常数据,并传送至云端服务器,根据当前医疗研究信息,对差异化指标数据分配匹配权重,得到标准化数据和动态权重表;The data standardization and weight determination module collects the user's physiological and behavioral indicator data based on wearable devices and medical instruments, standardizes the indicator data, removes abnormal data, and transmits it to the cloud server. According to the current medical research information, it assigns matching weights to the differentiated indicator data to obtain standardized data and a dynamic weight table;
组合优化评分模块基于所述标准化数据和动态权重表,结合用户个体差异和健康目标,调整差异化指标数据的权重,利用云端计算资源,根据调整后的指标数据权重,计算用户个人的健康状态评分,得到个人健康信息。The combined optimization scoring module adjusts the weights of differentiated indicator data based on the standardized data and dynamic weight table, combined with individual differences and health goals of users, and uses cloud computing resources to calculate the user's personal health status score according to the adjusted indicator data weights to obtain personal health information.
多目标健康管理策略模块基于所述个人健康信息,结合用户的健康历史和个人偏好,评估多个健康目标之间的冲突,选择关键健康目标,生成健康管理策略;The multi-objective health management strategy module evaluates conflicts between multiple health goals based on the personal health information, combines the user's health history and personal preferences, selects key health goals, and generates a health management strategy;
健康改善模块基于所述健康管理策略,制定匹配的健康改善措施,发送至用户终端,并监测用户反馈和健康数据的变化,调整优化健康改善措施,生成目标健康改善措施。The health improvement module formulates matching health improvement measures based on the health management strategy, sends them to the user terminal, monitors user feedback and changes in health data, adjusts and optimizes the health improvement measures, and generates target health improvement measures.
本发明改进有,所述对指标数据进行标准化处理的方法为:The present invention is improved in that the method for standardizing the indicator data is:
基于可穿戴设备和医疗仪器,收集用户的血压、胆固醇水平、血糖、睡眠质量、运动频率和饮食习惯数据,计算每项指标的平均值和标准偏差;Based on wearable devices and medical instruments, collect users' blood pressure, cholesterol level, blood sugar, sleep quality, exercise frequency and eating habits data, and calculate the mean and standard deviation of each indicator;
基于所述每项指标的平均值和标准偏差,通过公式:Based on the mean and standard deviation of each indicator, the formula:
对每个指标数据进行转换处理,得到标准化指标值; Convert each indicator data to obtain standardized indicator value ;
其中,表示第个指标数据,表示指标的平均值,表示指标的标准偏差,是 第个指标的重要性权重,是常数,是标准化指标值; in, Indicates Indicator data, Represents the average value of the indicator. represents the standard deviation of the indicator, It is The importance weight of each indicator is is a constant, is the standardized indicator value;
基于所述标准化指标值,与预设阈值进行对比,剔除超过和低于预设阈值的标 准化指标值,得到标准化数据,并将标准化数据和对应的原始指标数据一并传送至云端 服务器。 Based on the standardized index value , compared with the preset threshold, and the standardized indicator values exceeding and below the preset threshold are eliminated , obtain standardized data, and transmit the standardized data and the corresponding original indicator data to the cloud server.
本发明改进有,所述对差异化指标数据分配匹配权重的方法为:The present invention is improved in that the method for allocating matching weights to differentiated indicator data is:
从云端服务器获取标准化后的健康指标数据,健康指标数据包括血压、胆固醇水平、血糖、睡眠质量、运动频率和饮食习惯,根据当前医疗研究信息,分析差异化健康指标对健康状态的影响,通过公式:Obtain standardized health indicator data from the cloud server. The health indicator data includes blood pressure, cholesterol level, blood sugar, sleep quality, exercise frequency and eating habits. According to the current medical research information, analyze the impact of differentiated health indicators on health status through the formula:
对每个健康指标分配权重,得到基础权重;Assign weights to each health indicator to obtain basic weights;
其中,是归一化常数,和分别表示第和第个健康指标的风险系数,和分 别是第和第个健康指标的适应性调整系数,表示第个健康指标的基础权重,表示自 然对数的底数,表示健康指标总数; in, is the normalization constant, and Respectively represent and The risk factor of each health indicator is and They are and The adaptive adjustment coefficient of each health indicator is Indicates The basic weight of the health indicator, represents the base of natural logarithms, Indicates the total number of health indicators;
基于所述基础权重,对差异化健康指标的基础权重进行整理,得到动态权重表。Based on the basic weights, the basic weights of the differentiated health indicators are sorted to obtain a dynamic weight table.
本发明改进有,所述调整差异化指标数据的权重的方法为:The present invention is improved in that the method for adjusting the weight of the differentiated indicator data is:
基于所述标准化数据和动态权重表,收集用户个体的健康目标和个体差异信息,包括年龄、性别、健康状况和生活习惯,得到用户个体信息;Based on the standardized data and the dynamic weight table, the user's individual health goals and individual difference information, including age, gender, health status and living habits, are collected to obtain the user's individual information;
基于所述用户个体信息,通过公式:Based on the user individual information, through the formula:
对每个健康指标进行权重调整,得到调整后的权重; Adjust the weight of each health indicator to obtain the adjusted weight ;
其中,是第个健康指标调整后的权重,和分别表示第和第个健康指 标的基础权重,和分别代表第和第个健康指标的个体条件调整系数,和分别表示 第和第个健康指标的健康目标调整系数,表示健康指标的总数。 in, It is The adjusted weights of the health indicators are and Respectively represent and The basic weight of the health indicator, and Respectively represent and The individual condition adjustment coefficient of each health indicator is and Respectively represent and The health target adjustment coefficient of each health indicator is Indicates the total number of health indicators.
本发明改进有,所述个人健康信息的获取步骤为:The present invention is improved in that the steps of obtaining the personal health information are:
基于所述调整后的权重,通过公式: Based on the adjusted weights , through the formula:
计算个人健康评分;Calculate personal health score;
其中,是个人健康评分,表示健康指标的总数,是第个健康指标调整后 的权重,表示第个健康指标的实际测量值,是加权因子,是稳定因子; in, is a personal health score, Represents the total number of health indicators, It is The adjusted weights of the health indicators are Indicates The actual measured value of the health indicator, is the weighting factor, is a stabilizing factor;
基于所述个人健康评分,评估用户个人的健康状态,得到个人健康信息。Based on the personal health score, the user's personal health status is evaluated to obtain personal health information.
本发明改进有,所述健康管理策略的获取步骤为:The present invention is improved in that the steps of obtaining the health management strategy are:
基于所述个人健康信息,收集用户的血糖、血压和体重指标的历史数据和当前状态,分析评估多个健康目标之间的冲突,通过公式:Based on the personal health information, the historical data and current status of the user's blood sugar, blood pressure and weight indicators are collected, and the conflicts between multiple health goals are analyzed and evaluated through the formula:
计算健康策略得分S;Calculate the health strategy score S;
其中,S为健康策略得分,表示第个健康目标的优先级,代表第个健康目标的 潜在贡献,是非线性调节参数,代表健康目标的总数; Among them, S is the health strategy score, Indicates Prioritize health goals, Representative potential contribution to health goals, is a nonlinear adjustment parameter, represents the total number of health goals;
基于所述健康策略得分S,识别对应的健康目标,得到健康管理策略。Based on the health strategy score S, the corresponding health goal is identified to obtain a health management strategy.
本发明改进有,所述制定匹配的健康改善措施的方法为:The present invention is improved in that the method for formulating matching health improvement measures is:
基于所述健康管理策略,提取用户的当前行为指标数据,包括饮食量、运动时长和作息时长,通过公式:Based on the health management strategy, the user's current behavior indicator data is extracted, including the amount of food consumed, exercise duration, and rest duration, through the formula:
计算调整后行为量; Calculate adjusted behavior volume ;
其中,代表第类健康行为的调整后行为量,是第类健康行为的当前基准值,是健康策略得分,是第类健康行为的变化系数,是调整强度系数,是第类健康行 为的调整方向系数,是第类健康行为的调整量系数,是常数; in, Representative The adjusted amount of healthy behaviors, It is Current baseline values for health behaviors, is the health strategy score, It is The coefficient of variation of health behavior, is the adjustment strength coefficient, It is The adjustment direction coefficient of the health behavior class, It is The adjustment coefficient of the health behavior type, is a constant;
基于所述调整后行为量,制定匹配的健康改善措施,将调整后行为量应用于用 户的日常生活中,调整饮食计划、运动时长和作息时间。 Based on the adjusted behavior , formulate matching health improvement measures, apply the adjusted behavior amount to the user's daily life, and adjust the diet plan, exercise duration, and rest time.
本发明改进有,所述目标健康改善措施的获取步骤为:The present invention is improved in that the steps of obtaining the target health improvement measures are:
基于所述调整后行为量,收集用户反馈和健康数据,通过分析健康评分变化,判 断健康评分是否达到预期值,识别当前健康改善措施的有效性,并在当前健康改善措施无 效时,通过公式: Based on the adjusted behavior , collect user feedback and health data, analyze the changes in health scores, determine whether the health scores have reached the expected value, identify the effectiveness of current health improvement measures, and when the current health improvement measures are ineffective, use the formula:
计算优化后的调整量; Calculate the optimized adjustment ;
其中,表示第类健康行为优化后的调整量,表示第类健康行为当前的调整 量,调整强度系数,是第类健康行为的调整方向系数,是第类健康行为的调整量系 数,是健康评分的偏差量,是第类健康行为的变化系数,是用户反馈系数,是常 数; in, Indicates The adjustment amount after the optimization of healthy behaviors, Indicates The current adjustment amount of the health behavior, Adjust the strength factor, It is The adjustment direction coefficient of the health behavior class, It is The adjustment coefficient of the health behavior type, is the deviation of the health score, It is The coefficient of variation of health behavior, is the user feedback coefficient, is a constant;
基于所述优化后的调整量,将优化后的调整量应用于用户的日常生活中,优化 饮食计划、运动时长和作息时间,生成目标健康改善措施。 Based on the optimized adjustment amount , apply the optimized adjustments to the user's daily life, optimize diet plans, exercise duration, and rest schedules, and generate targeted health improvement measures.
与现有技术相比,本发明的优点和积极效果在于:Compared with the prior art, the advantages and positive effects of the present invention are:
本发明中,通过集成的云基础架构优化了健康数据的收集与处理流程,使得个体健康监测变得更加灵活和实时,能够即时同步并分析来自多源的健康数据,包括生理和行为指标,实现数据的高效整合与动态权重调整,使健康状态评估更加准确,支持生成精确的健康评分,能够根据实时数据调整健康管理策略,优化个体的健康管理,能够自动识别健康目标间的冲突,并基于个体的健康历史与偏好生成定制的健康改善措施,增加了干预措施的适应性和有效性。In the present invention, the collection and processing process of health data is optimized through an integrated cloud infrastructure, making individual health monitoring more flexible and real-time. It can instantly synchronize and analyze health data from multiple sources, including physiological and behavioral indicators, to achieve efficient data integration and dynamic weight adjustment, making health status assessment more accurate, supporting the generation of accurate health scores, adjusting health management strategies based on real-time data, optimizing individual health management, automatically identifying conflicts between health goals, and generating customized health improvement measures based on individual health history and preferences, thereby increasing the adaptability and effectiveness of intervention measures.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1为本发明的系统流程图;Fig. 1 is a system flow chart of the present invention;
图2为本发明对指标数据进行标准化处理的流程图;FIG2 is a flow chart of the standardization process of indicator data according to the present invention;
图3为本发明对差异化指标数据分配匹配权重的流程图;FIG3 is a flow chart of assigning matching weights to differentiated indicator data according to the present invention;
图4为本发明调整差异化指标数据的权重的流程图;FIG4 is a flow chart of adjusting the weight of differentiation index data according to the present invention;
图5为本发明获取个人健康信息的流程图;FIG5 is a flow chart of the present invention for obtaining personal health information;
图6为本发明获取健康管理策略的流程图;FIG6 is a flow chart of obtaining a health management strategy according to the present invention;
图7为本发明制定匹配的健康改善措施的流程图;FIG7 is a flow chart of formulating matching health improvement measures according to the present invention;
图8为本发明获取目标健康改善措施的流程图。FIG8 is a flow chart of obtaining target health improvement measures according to the present invention.
具体实施方式DETAILED DESCRIPTION
为了使本发明的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本发明进行进一步详细说明。应当理解,此处所描述的具体实施例仅仅用以解释本发明,并不用于限定本发明。In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.
在本发明的描述中,需要理解的是,术语“长度”“宽度”“上”“下”“前”“后”“左”“右”“竖直”“水平”“顶”“底”“内”“外”等指示的方位或位置关系为基于附图所示的方位或位置关系,仅是为了便于描述本发明和简化描述,而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作,因此不能理解为对本发明的限制。此外,在本发明的描述中,“多个”的含义是两个或两个以上,除非另有明确具体的限定。In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.
实施例Example
请参阅图1,本发明提供一种技术方案:一种基于云的健康管理系统,系统包括:Please refer to FIG1 . The present invention provides a technical solution: a cloud-based health management system, the system comprising:
数据标准化与权重确定模块基于可穿戴设备和医疗仪器,收集用户的生理和行为指标数据,指标数据包括血压、胆固醇水平、血糖、睡眠质量、运动频率和饮食习惯数据,对指标数据进行标准化处理,剔除异常数据,并传送至云端服务器,根据当前医疗研究信息,对差异化指标数据分配匹配权重,得到标准化数据和动态权重表;The data standardization and weight determination module collects the user's physiological and behavioral indicator data based on wearable devices and medical instruments. The indicator data includes blood pressure, cholesterol level, blood sugar, sleep quality, exercise frequency and eating habits. The indicator data is standardized, abnormal data is eliminated, and transmitted to the cloud server. According to the current medical research information, matching weights are assigned to the differentiated indicator data to obtain standardized data and a dynamic weight table;
组合优化评分模块基于标准化数据和动态权重表,结合用户个体差异和健康目标,调整差异化指标数据的权重,利用云端计算资源,根据调整后的指标数据权重,综合计算用户个人的健康状态评分,得到个人健康信息。The combined optimization scoring module is based on standardized data and a dynamic weight table. It combines individual differences and health goals of users to adjust the weights of differentiated indicator data. It uses cloud computing resources to comprehensively calculate the user's personal health status score based on the adjusted indicator data weights to obtain personal health information.
多目标健康管理策略模块基于个人健康信息,结合用户的健康历史和个人偏好,评估多个健康目标之间的冲突,健康目标包括减重、血糖控制和血压控制,选择关键健康目标,生成健康管理策略;The multi-objective health management strategy module evaluates the conflicts among multiple health goals based on personal health information, combined with the user's health history and personal preferences. Health goals include weight loss, blood sugar control, and blood pressure control, selects key health goals, and generates health management strategies.
健康改善模块基于健康管理策略,制定匹配的健康改善措施,包括调整饮食量、运动时长和作息时长,发送至用户终端,并监测用户反馈和健康数据的变化,调整优化健康改善措施,生成目标健康改善措施。The health improvement module develops matching health improvement measures based on the health management strategy, including adjusting the amount of food, exercise duration, and rest duration, and sends them to the user terminal. It also monitors user feedback and changes in health data, adjusts and optimizes health improvement measures, and generates target health improvement measures.
标准化数据和动态权重表包括调整的数据格式标准、同步更新时间戳和健康指标的实时权重。个人健康信息包括生活习惯得分和生理指标得分。健康管理策略包括个体的饮食量调整、运动频率时长和作息时长调整,目标健康改善措施包括饮食计划、运动计划和生活习惯调整方案。Standardized data and dynamic weight tables include adjusted data format standards, synchronous update timestamps, and real-time weights of health indicators. Personal health information includes lifestyle scores and physiological indicator scores. Health management strategies include individual adjustments to diet, exercise frequency and duration, and work and rest duration. Target health improvement measures include diet plans, exercise plans, and lifestyle adjustment plans.
请参阅图2,对指标数据进行标准化处理的方法为:Please refer to Figure 2. The method for standardizing the indicator data is as follows:
基于可穿戴设备和医疗仪器,收集用户的血压、胆固醇水平、血糖、睡眠质量、运动频率和饮食习惯数据,计算每项指标的平均值和标准偏差;Based on wearable devices and medical instruments, collect users' blood pressure, cholesterol level, blood sugar, sleep quality, exercise frequency and eating habits data, and calculate the mean and standard deviation of each indicator;
基于每项指标的平均值和标准偏差,通过公式:Based on the mean and standard deviation of each indicator, the formula is:
对每个指标数据进行转换处理,得到标准化指标值; Convert each indicator data to obtain standardized indicator value ;
其中,表示第个指标数据,表示指标的平均值,表示指标的标准偏差,是 第个指标的重要性权重,是常数,用于保证分母不为零的稳定性,是标准化指标值; in, Indicates Indicator data, Represents the average value of the indicator. represents the standard deviation of the indicator, It is The importance weight of each indicator is is a constant used to ensure the stability of the denominator not being zero. is the standardized indicator value;
基于标准化指标值,与预设阈值进行对比,剔除超过和低于预设阈值的标准化 指标值,得到标准化数据,并将标准化数据和对应的原始指标数据一并传送至云端服务 器。 Based on standardized indicator values , compared with the preset threshold, and the standardized indicator values exceeding and below the preset threshold are eliminated , obtain standardized data, and transmit the standardized data and the corresponding original indicator data to the cloud server.
公式:formula:
参数的含义与获取方式:The meaning and acquisition method of parameters:
:表示第个指标的原始数据,如血压或血糖。数据直接从可穿戴设备和医疗仪 器获取,设备通过传感器在固定时间间隔内采集用户的生理数据。 :Indicates the The raw data of an indicator, such as blood pressure or blood sugar, is obtained directly from wearable devices and medical instruments, which collect the user's physiological data at fixed time intervals through sensors.
:表示对应指标的平均值。通过对一段时间内收集到的数据求算术平均获 得。例如,计算过去30天的血压平均值,需要收集30天内所有血压读数的总和,然后除以读 数的数量。 :Indicates the corresponding The average value of the indicator. The data is averaged. For example, to calculate the average blood pressure for the past 30 days, you would need to collect the sum of all blood pressure readings taken during the 30 days and then divide it by the number of readings.
:表示对应指标的标准偏差,是衡量数据点分散程度的一个统计量。计算标准 偏差时,首先计算每个数据点与平均值的差的平方,求和后除以数据点数量,最后取平方 根。 :Indicates the corresponding The standard deviation of an indicator is a statistic that measures the dispersion of data points. When calculating the standard deviation, first calculate the difference between each data point and the average value. The square of the difference is summed up and divided by the number of data points, and finally the square root is taken.
:是针对第个指标的重要性权重,权重是根据指标对个人健康影响的重要性分 配的。例如,如果研究表明血糖对健康的影响比睡眠质量更直接,血糖的会比睡眠质量 的更高。 :It is for The weights of the indicators are assigned according to their importance to the individual's health. For example, if research shows that blood sugar has a more direct impact on health than sleep quality, blood sugar Better than sleep quality higher.
:是小常数,用来确保在标准偏差非常小或为零时分母不为零。这个值通常设为,足够小以不影响计算结果的精确性。 : is a small constant used to ensure that the denominator is not zero when the standard deviation is very small or zero. This value is usually set to , is small enough not to affect the accuracy of the calculation results.
计算示例:Calculation example:
假设有以下数据和参数设置:Assume the following data and parameter settings:
(假设这是某个用户一天中测量的血糖平均值) (Assume this is the average blood sugar level measured by a user in a day)
(假设这是基于前30天的血糖平均值) (Assuming this is based on the previous 30 day blood sugar average)
(血糖的标准偏差) (Standard deviation of blood sugar)
(血糖的重要性权重,假设在所有健康指标中,血糖对健康影响较大) (The importance weight of blood sugar, assuming that among all health indicators, blood sugar has a greater impact on health)
(小常数) (small constant)
计算标准化分数: Calculating standardized scores :
这个计算结果表示经过权重调整后的标准化血糖水平,可以用来分析用 户的健康状态或作为输入数据进行健康趋势分析。标准化分数有助于将来自不同个体和时 间的血糖数据统一到一个可比较的尺度上。 This calculation result Represents the standardized blood sugar level after weight adjustment, which can be used to analyze the user's health status or as input data for health trend analysis. Standardized scores help to unify blood sugar data from different individuals and time into a comparable scale.
请参阅图3,对差异化指标数据分配匹配权重的方法为:Please refer to Figure 3, the method of assigning matching weights to differentiated indicator data is:
从云端服务器获取标准化后的健康指标数据,健康指标数据包括血压、胆固醇水平、血糖、睡眠质量、运动频率和饮食习惯,根据当前医疗研究信息,分析差异化健康指标对健康状态的影响,通过公式:Obtain standardized health indicator data from the cloud server. The health indicator data includes blood pressure, cholesterol level, blood sugar, sleep quality, exercise frequency and eating habits. According to the current medical research information, analyze the impact of differentiated health indicators on health status through the formula:
对每个健康指标分配权重,得到基础权重;Assign weights to each health indicator to obtain basic weights;
其中,是归一化常数,和分别表示第和第个健康指标的风险系数,系数基于 流行病学研究或临床数据来确定,反映了各个健康指标与健康风险之间的相关强度,和分别是第和第个健康指标的适应性调整系数,根据指标对特定疾病的敏感度或重要性 进行调整,使权重分配更具目标性和针对性,表示第个健康指标的基础权重,表示自 然对数的底数,约等于2.71828,是数学常数,表示健康指标总数; in, is the normalization constant, and Respectively represent and The risk coefficient of each health indicator is determined based on epidemiological research or clinical data, reflecting the strength of the correlation between each health indicator and health risk. and They are and The adaptive adjustment coefficient of each health indicator is adjusted according to the sensitivity or importance of the indicator to a specific disease, making the weight distribution more targeted and specific. Indicates The basic weight of the health indicator, Represents the base of natural logarithms, approximately equal to 2.71828, a mathematical constant. Indicates the total number of health indicators;
基于基础权重,对差异化健康指标的基础权重进行整理,得到动态权重表。Based on the basic weights, the basic weights of differentiated health indicators are sorted out to obtain a dynamic weight table.
公式:formula:
参数的含义与获取方式:The meaning and acquisition method of parameters:
:是归一化常数,用于确保所有指标的权重和为1,用以简化计算,同时保证权重 分配的比例正确性。 : is a normalization constant used to ensure that the sum of the weights of all indicators is 1, to simplify the calculation and ensure the correctness of the proportion of weight distribution.
:自然对数的底数,数学常数,用于执行指数计算,使权重分配对风险系数的敏感 性增加。 : The base of the natural logarithm, a mathematical constant used to perform exponential calculations to make the weight assignment more sensitive to the risk factor.
和:分别代表第和第个健康指标的风险系数。系数根据每个指标与健康结果 的相关研究来确定。例如,如果血压与心脏疾病有很高的关联度,则血压的值会相对较高。 and :Represents the and The risk factor for each health indicator is determined based on research on the association between each indicator and health outcomes. For example, if blood pressure is highly associated with heart disease, then a risk factor for blood pressure is The value will be relatively high.
和:是针对第和第个指标的适应性调整系数,根据指标对特定健康状况的 影响强度设定。系数通过专家评估或历史数据分析得出。 and :It is for and The adaptive adjustment coefficient of each indicator is set according to the intensity of the indicator's impact on a specific health condition. The coefficient is obtained through expert evaluation or historical data analysis.
计算示例:Calculation example:
假设有以下参数设置和数据:Assume the following parameter settings and data:
:健康指标总数 : Total number of health indicators
:归一化常数 : Normalization constant
,,:分别对应血糖、血压和胆固醇的风险系数 , , : Corresponding to the risk factors of blood sugar, blood pressure and cholesterol
,,:对应各指标的适应性调整系数 , , : Adaptive adjustment coefficient corresponding to each indicator
计算步骤:Calculation steps:
计算分母 Calculate the denominator
Sum Sum
计算权重:Calculate weights:
完整的权重结果: The complete weight results are:
计算示例展示了通过给定的风险系数和适应性调整系数计算每个健康指标的权重。The calculation example shows how to calculate the weight of each health indicator by given risk factor and fitness adjustment factor.
请参阅图4,调整差异化指标数据的权重的方法为:Please refer to Figure 4. The method for adjusting the weight of the differentiated indicator data is:
基于标准化数据和动态权重表,收集用户个体的健康目标和个体差异信息,包括年龄、性别、健康状况和生活习惯,得到用户个体信息;Based on standardized data and dynamic weight tables, collect individual user health goals and individual difference information, including age, gender, health status and living habits, to obtain individual user information;
基于用户个体信息,通过公式:Based on user individual information, through the formula:
对每个健康指标进行权重调整,得到调整后的权重; Adjust the weight of each health indicator to obtain the adjusted weight ;
其中,是第个健康指标调整后的权重,和分别表示第和第个健康指 标的基础权重,从动态权重表中获取,和分别代表第和第个健康指标的个体条件调整 系数,系数是根据个体的具体条件,如年龄、性别或已知健康状况设定,用于调整原始权重 以更好地反映个体特定需求,和分别表示第和第个健康指标的健康目标调整系数,系 数根据用户的健康目标,如降低血压或改善胆固醇水平设定,用于调整权重以强调用户的 健康优先级,表示健康指标的总数,用于在求和过程中迭代所有指标,确保权重的调整涵 盖所有相关健康指标。 in, It is The adjusted weights of the health indicators are and Respectively represent and The basic weight of each health indicator is obtained from the dynamic weight table. and Respectively represent and The individual condition adjustment coefficient of each health indicator is set according to the individual's specific conditions, such as age, gender, or known health status, and is used to adjust the original weight to better reflect the individual's specific needs. and Respectively represent and The health goal adjustment coefficient for each health indicator is set according to the user's health goal, such as lowering blood pressure or improving cholesterol levels, and is used to adjust the weight to emphasize the user's health priority. Represents the total number of health indicators, used to iterate all indicators during the summation process to ensure that the adjustment of weights covers all relevant health indicators.
公式:formula:
参数的含义与获取方式:The meaning and acquisition method of parameters:
和:是基础健康指标权重。权重反映了不同健康指标在整体健康评估中的重 要性,通过先前步骤获得。 and : is the weight of basic health indicators. The weight reflects the importance of different health indicators in the overall health assessment and is obtained through the previous steps.
和:来自用户档案的个体条件调整系数。这些系数基于个体的具体条件,如年 龄和既往疾病,通常通过分析用户的健康记录和输入信息来设定。 and : Individual condition adjustment factors from the user profile. These factors are based on individual specific conditions, such as age and pre-existing conditions, and are usually set by analyzing the user's health records and input information.
和:根据用户设定的健康目标确定的调整系数,如降低血压或控制血糖。目标 由用户在应用中设定,据此设定相应的系数。 and : An adjustment factor based on a health goal set by the user, such as lowering blood pressure or controlling blood sugar. The goal is set by the user in the app, and the corresponding factor is set accordingly.
:健康指标的总数,这是预先定义的,根据跟踪的健康指标数量确定。 : The total number of health indicators, which is pre-defined and determined based on the number of health indicators tracked.
计算示例:Calculation example:
假设有三个健康指标,其原始权重,个体条件系 数,健康目标系数,并且。 Assume there are three health indicators, and their original weights , individual condition coefficient , health target coefficient ,and .
计算过程:Calculation process:
计算对数乘积:Compute the logarithmic product:
计算权重分母:Calculate the weight denominator:
计算调整后的权重: Calculate the adjusted weights :
计算示例展示了根据用户的个体条件和健康目标调整每个健康指标的权重,确保个性化的健康评分反映了用户的实际需求和健康目标。The calculation example shows how the weight of each health indicator is adjusted according to the user's individual conditions and health goals, ensuring that the personalized health score reflects the user's actual needs and health goals.
请参阅图5,个人健康信息的获取步骤为:Please refer to Figure 5, the steps for obtaining personal health information are:
基于调整后的权重,通过公式: Based on the adjusted weights , through the formula:
计算个人健康评分;Calculate personal health score;
其中,是个人健康评分,表示健康指标的总数,是第个健康指标调整后 的权重,表示第个健康指标的实际测量值,如血压读数、胆固醇水平等。这是直接从用户 的健康数据中获取的量化值,是加权因子,是稳定因子; in, is a personal health score, Represents the total number of health indicators, It is The adjusted weights of the health indicators are Indicates The actual measured values of health indicators, such as blood pressure readings, cholesterol levels, etc. This is a quantitative value obtained directly from the user's health data. is the weighting factor, is a stabilizing factor;
基于个人健康评分,评估用户个人的健康状态,得到个人健康信息。Based on the personal health score, the user's personal health status is evaluated and personal health information is obtained.
公式:formula:
参数的含义与获取方式:The meaning and acquisition method of parameters:
:表示健康指标的总数,直接通过数据项获取。 : Indicates the total number of health indicators, which can be obtained directly through data items.
:表示第个健康指标的调整后权重,通过先前步骤计算得出。 :Indicates the The adjusted weights of the health indicators are calculated in the previous steps.
:代表第个健康指标的实际测量值。例如,血压、血糖等指标的具体数值,直接 从医疗测量设备或用户输入获取。 :Represents The actual measured value of a health indicator. For example, the specific values of blood pressure, blood sugar and other indicators are directly obtained from medical measurement equipment or user input.
和:是用来调节公式的加权因子和稳定因子,根据历史数据进行预设,帮助调 整对低值指标的响应度,避免在很小的情况下出现计算不稳定。 and :It is used to adjust the weighting factor and stability factor of the formula, which is preset according to historical data to help adjust the response to low-value indicators and avoid In some cases, the calculation may be unstable.
计算示例:Calculation example:
假设有以下参数设置和数据:Assume the following parameter settings and data:
总健康指标数 Total health indicators
第一个健康指标:,(假设为血压值) The first health indicator: , (Assumed to be blood pressure value)
第二个健康指标:,(假设为血糖值)The second health indicator: , (Assuming blood sugar level)
第三个健康指标:,(假设为胆固醇值) The third health indicator: , (Assumed cholesterol value)
调整参数:, Adjustment parameters: ,
计算过程:Calculation process:
计算每个健康指标的加权项:Calculate the weighted term for each health indicator:
对于第一个指标:For the first indicator:
对于第二个指标:For the second indicator:
对于第三个指标:For the third indicator:
综合计算健康评分: Comprehensive calculation of health score :
计算示例展示了根据调整后的权重和实际健康数据来计算个人的健康评分,确保评分能够综合反映个体的健康状况并对各个健康指标的变化敏感。The calculation example demonstrates the calculation of an individual’s health score based on the adjusted weights and actual health data, ensuring that the score comprehensively reflects the individual’s health status and is sensitive to changes in various health indicators.
请参阅图6,健康管理策略的获取步骤为:Please refer to Figure 6, the steps for obtaining the health management strategy are:
基于个人健康信息,收集用户的血糖、血压和体重指标的历史数据和当前状态,分析评估多个健康目标之间的冲突,通过公式:Based on personal health information, the historical data and current status of the user's blood sugar, blood pressure and weight indicators are collected, and the conflicts between multiple health goals are analyzed and evaluated through the formula:
计算健康策略得分S;Calculate the health strategy score S;
其中,S为健康策略得分,表示第个健康目标的优先级,代表第个健康目标的 潜在贡献,是非线性调节参数,代表健康目标的总数; Among them, S is the health strategy score, Indicates Prioritize health goals, Representative potential contribution to health goals, is a nonlinear adjustment parameter, represents the total number of health goals;
基于健康策略得分S,识别对应的健康目标,得到健康管理策略。Based on the health strategy score S, the corresponding health goal is identified and the health management strategy is obtained.
公式:formula:
参数的含义与获取方式:The meaning and acquisition method of parameters:
:表示第个健康目标的优先级,根据用户的健康数据和个人偏好通过用户访谈 或问卷调查获取的。 :Indicates the The priority of each health goal is obtained through user interviews or questionnaires based on the user's health data and personal preferences.
:代表第个健康目标的潜在贡献,通常基于历史数据和医学研究来估计,数据 分析得出每个健康目标对改善用户健康状况的效果。 :Represents The potential contribution of each health goal is usually estimated based on historical data and medical research, and data analysis is used to determine the effect of each health goal on improving the user's health status.
:是非线性调节参数,通过优化实验和统计分析确定,用以调整目标之间的权衡 影响,使模型能更灵活地适应各种健康状况。 : It is a nonlinear adjustment parameter determined through optimization experiments and statistical analysis to adjust the trade-offs between objectives so that the model can adapt more flexibly to various health conditions.
:代表健康目标的总数,这个数量是根据用户目标来设置的。 : Represents the total number of health goals, which is set according to user goals.
计算示例:Calculation example:
假设有三个健康目标,其参数和数据设定如下:Assume that there are three health goals, and their parameters and data are set as follows:
健康目标数量 Number of health goals
第一个目标(减重):,(假设为减重对健康的潜在贡献分) First goal (weight loss): , (Assumed to be the potential contribution of weight loss to health)
第二个目标(血糖控制):,(假设为血糖控制的潜在贡献分) Secondary goal (blood sugar control): , (Assumed to be the potential contribution to blood sugar control)
第三个目标(血压控制):,(假设为血压控制的潜在贡献分) Third goal (blood pressure control): , (Assumed to be the potential contribution to blood pressure control)
调节参数 Adjustment parameters
计算过程:Calculation process:
计算各健康目标的权衡贡献:Calculate the trade-off contribution of each health goal:
对于第一个目标:For the first goal:
对于第二个目标:For the second goal:
对于第三个目标:For the third goal:
综合计算健康策略得分: Comprehensive calculation of health strategy score :
计算示例说明了通过对各健康目标的优先级和潜在贡献进行加权和调节,来计算 出最优的健康管理策略得分,确保健康策略的优化是基于实际的用户偏好和医学数据。 The calculation example shows how to calculate the optimal health management strategy score by weighting and adjusting the priority and potential contribution of each health goal. , ensuring that the optimization of health strategies is based on actual user preferences and medical data.
请参阅图7,制定匹配的健康改善措施的方法为:Please refer to Figure 7. The method of developing matching health improvement measures is:
基于健康管理策略,提取用户的当前行为指标数据,包括饮食量、运动时长和作息时长,通过公式:Based on the health management strategy, extract the user's current behavior indicator data, including diet, exercise duration, and rest duration, through the formula:
计算调整后行为量; Calculate adjusted behavior volume ;
其中,代表第类健康行为的调整后行为量,是第类健康行为的当前基准值,是健康策略得分,是第类健康行为的变化系数,是调整强度系数,是第类健康行 为的调整方向系数,是第类健康行为的调整量系数,是常数; in, Representative The adjusted amount of healthy behaviors, It is Current baseline values for health behaviors, is the health strategy score, It is The coefficient of variation of health behavior, is the adjustment strength coefficient, It is The adjustment direction coefficient of the health behavior class, It is The adjustment coefficient of the health behavior type, is a constant;
基于调整后行为量,制定匹配的健康改善措施,将调整后行为量应用于用户的 日常生活中,调整饮食计划、运动时长和作息时间。 Based on adjusted behavior , formulate matching health improvement measures, apply the adjusted behavior amount to the user's daily life, and adjust the diet plan, exercise duration, and rest time.
公式:formula:
参数的含义与获取方式:The meaning and acquisition method of parameters:
:第类健康行为的当前基准值,直接通过可穿戴设备和医疗仪器获取。:健康 策略得分,用于指导调整的方向和强度,通过先前步骤获得。 : Current baseline values of health behaviors are obtained directly from wearable devices and medical instruments. : Health strategy score, used to guide the direction and intensity of adjustment, obtained through the previous steps.
:针对第类行为的变化系数,根据健康目标的优先级和用户响应的历史数据设 定的。 :For the The coefficient of variation of the class behavior is set based on the priority of health goals and historical data of user responses.
:调整强度系数,用于控制调整的幅度,确保调整不会过大或过小,以适应用户的 实际接受能力和健康需求。 : Adjustment intensity coefficient is used to control the amplitude of adjustment to ensure that the adjustment is not too large or too small to adapt to the user's actual acceptance and health needs.
:用于决定第类健康行为是增加还是减少的系数,通常可以取1或-1,分别 表示增加或减少。 :Used to determine the The coefficient of whether the health behavior is increasing or decreasing, usually Can be 1 or -1, indicating increase or decrease respectively.
:用于调整不同健康行为增加或减少量的系数,这是根据医学建议和用户需求 设定的。 : Coefficients used to adjust the amount of increase or decrease in different health behaviors, which are set based on medical advice and user needs.
:是常数,提供更广泛的调整灵活性。 : are constants, providing wider adjustment flexibility.
计算示例:Calculation example:
假设有以下参数设定:Assume the following parameter settings:
健康行为包括:饮食(),运动(),作息() Healthy behaviors include: diet ( ),sports( ), work and rest ( )
基准值:卡路里,分钟,小时 Baseline value: Calories, minute, Hour
健康策略得分 Health Strategy Score
变化系数:,, Coefficient of variation: , ,
调整强度系数 Adjust the strength factor
调整方向系数:(减少饮食),(增加运动),(增加作息 时间) Adjust the directivity factor: (Reduce diet), (Increase exercise), (Increase work and rest time)
调整量系数:00,0, Adjustment factor: 00, 0,
常数 constant
计算过程:Calculation process:
对于饮食:For diet:
对于运动:For Sports:
对于作息:For work and rest:
计算示例通过健康策略得分和变化系数来调整健康行为,确保了健康改善措 施的个性化和有效性。 Calculation example by health strategy score and coefficient of variation To adjust health behaviors, ensuring the personalization and effectiveness of health improvement measures.
请参阅图8,目标健康改善措施的获取步骤为:Please refer to Figure 8. The steps for obtaining the target health improvement measures are:
基于调整后行为量,收集用户反馈和健康数据,通过分析健康评分变化,判断健 康评分是否达到预期值,识别当前健康改善措施的有效性,并在当前健康改善措施无效时, 通过公式: Based on adjusted behavior , collect user feedback and health data, analyze the changes in health scores, determine whether the health scores have reached the expected value, identify the effectiveness of current health improvement measures, and when the current health improvement measures are ineffective, use the formula:
计算优化后的调整量; Calculate the optimized adjustment ;
其中,表示第类健康行为优化后的调整量,表示第类健康行为当前的调整 量,调整强度系数,是第类健康行为的调整方向系数,是第类健康行为的调整量系 数,是健康评分的偏差量,是第类健康行为的变化系数,是用户反馈系数,是常 数; in, Indicates The adjustment amount after the optimization of healthy behaviors, Indicates The current adjustment amount of the health behavior, Adjust the strength factor, It is The adjustment direction coefficient of the health behavior class, It is The adjustment coefficient of the health behavior type, is the deviation of the health score, It is The coefficient of variation of health behavior, is the user feedback coefficient, is a constant;
基于优化后的调整量,将优化后的调整量应用于用户的日常生活中,优化饮食 计划、运动时长和作息时间,生成目标健康改善措施。 Based on the optimized adjustment , apply the optimized adjustments to the user's daily life, optimize diet plans, exercise duration, and rest schedules, and generate targeted health improvement measures.
公式:formula:
参数的含义与获取方式:The meaning and acquisition method of parameters:
:表示第类健康行为当前的调整量,通过先前步骤计算获得。 :Indicates the The current adjustment amount of the health behavior is calculated through the previous steps.
:调整强度系数,用于控制调整的幅度,根据医学建议和个体的健康需求设定, 系数可以通过实验数据和专家意见进行校准,一般在特定范围内取值。 :Adjustment intensity coefficient, used to control the amplitude of adjustment, set according to medical advice and individual health needs. The coefficient can be calibrated through experimental data and expert opinions, and generally takes values within a specific range.
:用于决定第类健康行为是增加还是减少的系数,根据健康改善目标来确定,若 需要增加某一行为则设为1,减少则设为-1。 :Used to determine the The coefficient of whether a health behavior is increased or decreased is determined according to the health improvement goal. If a behavior needs to be increased, it is set to 1, and if it needs to be reduced, it is set to -1.
:用于调整不同健康行为增加或减少量的系数,基于健康目标的具体要求和用 户的个人情况设定,如根据减重目标、运动目标等具体健康目标来确定。 : Coefficient used to adjust the increase or decrease in different health behaviors, based on the specific requirements of the health goals and the user's personal circumstances, such as specific health goals such as weight loss goals and exercise goals.
:健康评分的偏差量,通过将当前健康评分与预期目标健康评分对比得出。 : The deviation of the health score, which is obtained by comparing the current health score with the expected target health score.
:针对第类行为的变化系数,根据健康目标的优先级和用户响应的历史数据设 定。 :For the The coefficient of variation of the class behavior is set based on the priority of health goals and historical data of user responses.
:用户反馈系数,根据用户对当前措施的反馈设定,通过用户对现有健康措施的 反馈调查或评分系统获取,用于反映用户的主观感受和适应程度。 : User feedback coefficient, which is set according to the user's feedback on the current measures. It is obtained through the user's feedback survey or scoring system on the existing health measures, and is used to reflect the user's subjective feelings and degree of adaptation.
:常数,提供调整灵活性,根据经验或标准设定,用于标准化公式中的其他参数, 确保调整幅度合理。 : Constant, providing adjustment flexibility, set based on experience or standards, used to standardize other parameters in the formula to ensure that the adjustment range is reasonable.
计算示例:Calculation example:
假设有以下参数设定:Assume the following parameter settings:
健康行为包括:Healthy behaviors include:
饮食(),运动(),作息() diet( ),sports( ), work and rest ( )
当前调整量:卡路里,分钟,小时 Current adjustment amount: Calories, minute, Hour
健康评分的偏差量 Deviation of health score
变化系数:,, Coefficient of variation: , ,
调整强度系数 Adjust the strength factor
调整方向系数:(减少饮食),(增加运动),(增加作息时 间) Adjust the directivity factor: (Reduce diet), (Increase exercise), (Increase work and rest time)
调整量系数:00,0, Adjustment factor: 00, 0,
用户反馈系数:,, User feedback factor: , ,
常数 constant
计算过程Calculation process
对于饮食:For diet:
对于运动:For Sports:
339 339
对于作息:For work and rest:
656 656
计算示例根据健康评分的偏差量调整健康行为,确保了健康改善措施的科学 性和个性化。 Calculate the deviation of the example according to the health score Adjusting health behaviors ensures that health improvement measures are scientific and personalized.
以上,仅是本发明的较佳实施例而已,并非对本发明作其他形式的限制,任何熟悉本专业的技术人员可能利用上述揭示的技术内容加以变更或改型为等同变化的等效实施例应用于其他领域,但是凡是未脱离本发明技术方案内容,依据本发明的技术实质对以上实施例所做的任何简单修改、等同变化与改型,仍属于本发明技术方案的保护范围。The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.
Claims (8)
1.A cloud-based health management system, the system comprising:
the data standardization and weight determination module collects physiological and behavior index data of a user based on the wearable equipment and the medical instrument, performs standardization processing on the index data, eliminates abnormal data, transmits the abnormal data to the cloud server, and distributes matching weights to the differentiated index data according to current medical research information to obtain standardized data and a dynamic weight table;
The combined optimization scoring module adjusts the weight of the differentiated index data based on the standardized data and the dynamic weight table in combination with the individual difference and the health target of the user, and calculates the health state score of the individual user according to the adjusted index data weight by utilizing cloud computing resources to obtain personal health information;
the multi-target health management strategy module evaluates conflict among a plurality of health targets based on the personal health information in combination with health history and personal preference of the user, selects a key health target and generates a health management strategy;
And the health improvement module formulates matched health improvement measures based on the health management strategy, sends the matched health improvement measures to the user terminal, monitors user feedback and change of health data, adjusts and optimizes the health improvement measures, and generates target health improvement measures.
2. The cloud-based health management system of claim 1, wherein the method for normalizing the index data comprises:
Based on the wearable device and the medical instrument, collecting blood pressure, cholesterol level, blood glucose, sleep quality, exercise frequency and eating habit data of the user, and calculating an average value and a standard deviation of each index;
based on the mean and standard deviation of each index, the formula is as follows:
;
Each index data is converted to obtain a standardized index value ;
Wherein,Represent the firstThe data of the individual indicators are used to determine,The average value of the index is represented,The standard deviation of the index is indicated,Is the firstThe importance weight of the individual indicators is determined,Is a constant value, and is a function of the constant,Is a standardized index value;
based on the normalized index value Comparing with the preset threshold value, and eliminating the standardized index values exceeding and falling below the preset threshold valueAnd obtaining standardized data, and transmitting the standardized data and corresponding original index data to a cloud server.
3. The cloud-based health management system of claim 2, wherein said method of assigning matching weights to differentiated index data is:
the standardized health index data are obtained from the cloud server, the health index data comprise blood pressure, cholesterol level, blood sugar, sleep quality, exercise frequency and eating habit, and according to current medical research information, the influence of differentiated health indexes on the health state is analyzed through the formula:
;
distributing weights to each health index to obtain basic weights;
Wherein, Is a normalization constant that is set to a constant value,AndRespectively represent the firstAnd (d)The risk factor of the individual health indicator,AndRespectively the firstAnd (d)The adaptive adjustment coefficients of the individual health indicators,Represent the firstThe base weight of the individual health indicators is,The base number representing the natural logarithm,Representing the total number of health indicators;
and based on the basic weight, sorting the basic weight of the differentiated health index to obtain a dynamic weight table.
4. The cloud-based health management system of claim 1, wherein the method of adjusting the weight of the differential indicator data is:
based on the standardized data and the dynamic weight table, collecting health targets and individual difference information of the user individuals, including age, gender, health condition and life habit, and obtaining user individual information;
based on the user individual information, the following formula is adopted:
;
each health index is subjected to weight adjustment to obtain an adjusted weight ;
Wherein,Is the firstThe weight of the individual health indicators after adjustment,AndRespectively represent the firstAnd (d)The base weight of the individual health indicators is,AndRespectively represent the firstAnd (d)The individual condition adjustment coefficients of the individual health indicators,AndRespectively represent the firstAnd (d)The health target adjustment coefficients of the individual health indicators,Indicating the total number of health indicators.
5. The cloud-based health management system of claim 4, wherein said step of obtaining personal health information is:
Based on the adjusted weights By the formula:
;
Calculating a personal health score;
Wherein, Is a personal health score of the person,Indicating the total number of health indicators,Is the firstThe weight of the individual health indicators after adjustment,Represent the firstThe actual measured value of the individual health indicator,Is a weighting factor that is used to determine the weight of the sample,Is a stabilizing factor;
And based on the personal health score, evaluating the personal health state of the user to obtain personal health information.
6. The cloud-based health management system of claim 1, wherein the step of obtaining the health management policy is:
based on the personal health information, historical data and current states of blood sugar, blood pressure and weight indexes of the user are collected, conflicts among a plurality of health targets are analyzed and evaluated, and the formula is adopted:
;
Calculating a health strategy score S;
wherein S is a health policy score, Represent the firstThe priority of the individual health objectives,Represents the firstPotential contributions of the individual health objectives are,The parameters of the non-linear adjustment are,Representing the total number of healthy targets;
and identifying a corresponding health target based on the health policy score S to obtain a health management policy.
7. The cloud-based health management system of claim 1, wherein said method of formulating matched health improvement measures is:
Based on the health management strategy, extracting current behavior index data of the user, including food consumption, exercise duration and work and rest duration, through the formula:
;
Calculating the adjusted behavior quantity ;
Wherein,Represents the firstThe adjusted behavior amount of the health-like behavior,Is the firstThe current benchmark of health-like behavior,Is a health policy score that is a health policy score,Is the firstThe coefficient of variation of the health-like behavior,Is to adjust the intensity coefficient of the light source,Is the firstThe direction factor of the adjustment of the health-like behavior,Is the firstThe adjustment quantity coefficient of the health-like behavior,Is a constant;
based on the adjusted behavior amount Matching health improvement measures are formulated, the adjusted behavior quantity is applied to daily life of a user, and diet plans, exercise duration and work and rest time are adjusted.
8. The cloud-based health management system of claim 7, wherein said target health improvement measure is obtained by:
based on the adjusted behavior amount User feedback and health data are collected, whether the health score reaches an expected value is judged by analyzing the health score change, the effectiveness of the current health improvement measure is identified, and when the current health improvement measure is invalid, the health score is calculated by the formula:
;
calculating the optimized adjustment quantity ;
Wherein,Represent the firstThe adjustment amount after the optimization of the health-like behavior,Represent the firstThe current amount of adjustment for the health-like behavior,The intensity coefficient is adjusted so that the intensity coefficient is adjusted,Is the firstThe direction factor of the adjustment of the health-like behavior,Is the firstThe adjustment quantity coefficient of the health-like behavior,Is the amount of deviation of the health score,Is the firstThe coefficient of variation of the health-like behavior,Is a user feedback coefficient that is used to determine the feedback,Is a constant;
Based on the optimized adjustment amount The optimized adjustment quantity is applied to daily life of a user, and diet plan, exercise duration and work and rest time are optimized, so that target health improvement measures are generated.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202411017043.0A CN118538368B (en) | 2024-07-29 | 2024-07-29 | A cloud-based health management system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202411017043.0A CN118538368B (en) | 2024-07-29 | 2024-07-29 | A cloud-based health management system |
Publications (2)
Publication Number | Publication Date |
---|---|
CN118538368A true CN118538368A (en) | 2024-08-23 |
CN118538368B CN118538368B (en) | 2024-11-22 |
Family
ID=92392297
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202411017043.0A Active CN118538368B (en) | 2024-07-29 | 2024-07-29 | A cloud-based health management system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN118538368B (en) |
Cited By (1)
* Cited by examiner, † Cited by third partyPublication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN119601160A (en) * | 2025-02-07 | 2025-03-11 | 上海智众医疗科技有限公司 | Doctor's advice information generation method based on patient identification |
Citations (4)
* Cited by examiner, † Cited by third partyPublication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120130198A1 (en) * | 2010-11-23 | 2012-05-24 | Beaule Jean-Francois | Systems and method for determining and managing an individual and portable health score |
CN109102888A (en) * | 2017-06-20 | 2018-12-28 | 深圳大森智能科技有限公司 | A kind of human health methods of marking |
CN117524416A (en) * | 2023-11-24 | 2024-02-06 | 上海交通大学医学院附属瑞金医院 | Healthy diet management method and system based on health examination data |
CN117594181A (en) * | 2023-11-06 | 2024-02-23 | 杭州彩湖网络科技有限公司 | Method and system for generating health report based on data detection |
-
2024
- 2024-07-29 CN CN202411017043.0A patent/CN118538368B/en active Active
Patent Citations (4)
* Cited by examiner, † Cited by third partyPublication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120130198A1 (en) * | 2010-11-23 | 2012-05-24 | Beaule Jean-Francois | Systems and method for determining and managing an individual and portable health score |
CN109102888A (en) * | 2017-06-20 | 2018-12-28 | 深圳大森智能科技有限公司 | A kind of human health methods of marking |
CN117594181A (en) * | 2023-11-06 | 2024-02-23 | 杭州彩湖网络科技有限公司 | Method and system for generating health report based on data detection |
CN117524416A (en) * | 2023-11-24 | 2024-02-06 | 上海交通大学医学院附属瑞金医院 | Healthy diet management method and system based on health examination data |
Cited By (1)
* Cited by examiner, † Cited by third partyPublication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN119601160A (en) * | 2025-02-07 | 2025-03-11 | 上海智众医疗科技有限公司 | Doctor's advice information generation method based on patient identification |
Also Published As
Publication number | Publication date |
---|---|
CN118538368B (en) | 2024-11-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20170300655A1 (en) | 2017-10-19 | Apparatus and methodologies for personal health analysis |
US8005690B2 (en) | 2011-08-23 | Dynamic modeling and scoring risk assessment |
RU2712395C1 (en) | 2020-01-28 | Method for issuing recommendations for maintaining a healthy lifestyle based on daily user activity parameters automatically tracked in real time, and a corresponding system (versions) |
CN118538368A (en) | 2024-08-23 | Health management system based on cloud |
CN118737447A (en) | 2024-10-01 | Diabetes risk assessment system |
CN118711822A (en) | 2024-09-27 | Cardiovascular and cerebrovascular disease risk prediction method and system |
CN110911018A (en) | 2020-03-24 | Human health data acquisition system and health monitoring method based on cloud computing |
KR102342770B1 (en) | 2021-12-23 | A health management counseling system using the distribution of predicted disease values |
JP2016538927A (en) | 2016-12-15 | Calculation of human circadian rhythm |
CN118173253B (en) | 2024-07-16 | System and method for analyzing and managing based on patient data |
CN119049680B (en) | 2025-02-25 | Inventory dynamic adjustment system and method based on cloud computing |
CN118571483A (en) | 2024-08-30 | A pregnancy care monitoring system and platform |
CN113871014A (en) | 2021-12-31 | Autonomous health assisting method and device |
CN119008010A (en) | 2024-11-22 | Chronic disease screening and follow-up data collection management method and system |
CN118609847A (en) | 2024-09-06 | Community online intelligent analysis system based on health big data |
CN118737475A (en) | 2024-10-01 | A method and system for intelligently monitoring nutritional intake of pregnant women |
CN118692681B (en) | 2024-10-29 | A heart monitoring information analysis method and system |
CN114830250A (en) | 2022-07-29 | Lifestyle scoring system and method |
CN118866277B (en) | 2025-01-24 | A UTV subject intelligent visit management system and method |
CN118762803B (en) | 2024-11-05 | Dynamic rehabilitation method and system for rehabilitation patient |
CN118824454A (en) | 2024-10-22 | An integrated management method and system for obstetric patient information |
KR20200031383A (en) | 2020-03-24 | Health status and eating habit check system and method of providing customized health information thereof |
CN119480047A (en) | 2025-02-18 | Intelligent nursing plan evaluation method |
CN119791621A (en) | 2025-04-11 | Multifunctional vital sign monitoring method and system |
CN119851904A (en) | 2025-04-18 | Breast cancer risk management and control system and medium |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
2024-08-23 | PB01 | Publication | |
2024-08-23 | PB01 | Publication | |
2024-09-10 | SE01 | Entry into force of request for substantive examination | |
2024-09-10 | SE01 | Entry into force of request for substantive examination | |
2024-11-22 | GR01 | Patent grant | |
2024-11-22 | GR01 | Patent grant |