Research On Mobile Health Management System Based On Knowledge Ontology

In recent years,mobile health management draw widely attention.Research on mobile health services has become a hot topic in computer and other related disciplines.Mobile health services have a variety of advantages that traditional medical service models do not have,such as real-time,home monitoring of physiological characteristics of data,easy to achieve personalized health management,etc..With the help of wireless communication technology,the mobile health care management is composed of three steps:health data acquisition,health assessment and health intervention.In this thesis,pregnant women as the main research object,a mobile health management system is proposed based on the clinical knowledge base.It presents out a detailed analysis and design of following three aspects:health data collection,health ontology knowledge base construction and personalized health intervention.The work of this thesis includes the following three parts:(1)A healthy physiological acquisition system was designed and implemented based on wearable equipment.The major work of this system is to collect the user’s physiological characteristic data through the wearable device,then pass the data to the mobile terminal through the Bluetooth module;The mobile application analyze the data and display the result to user,at the meantime,uploads the result to the server.Then the data mining technology is used to analyze all the collected data and release the analysis result through interface.(2)The pregnancy health evaluation model based on ontology was proposed.First of all,according to the consensus of medical experts,we carried out the ontology representation and rules leaming.And we designed and implemented the evaluated reasoning process based on the clinical knowledge base to realize the intelligent health assessment.(3)A personalized health intervention method based on user behavior was proposed.This method first obtains the App page tag interest model based on the frequent sequence analysis of the group browsing path,and then through the specific user browsing behavior to normalized calculate its interest model for the specific page in the App.After weighted calculate of the two model,the specific user’s interest model has been established.On the basis of the model,send health knowledge to the user,to achieve personalized health education.