Research On Intelligent Generalization Of Personalized Healthcare Solution

In our country,people’s health is facing more and more challenges nowadays.In order to stay healthy,people’s concepts about health have transformed greatly,from passive disease treatment to active health management.Personalized health management is more and more important.This paper proposed a mechanism to intelligently generate personalized healthcare solutions in order to guide users to have scientific exercise and healthy diet.In order to generate the contents of healthcare solutions,this paper adopted parallel reasoning using matrix calculation to get users’ daily personalized appropriate exercise and food based on fuzzy petri nets transformed from large-scale of healthcare knowledge,which used users’ basic information,health information and external environmental information as initial inputs.In the meantime,system design and development of the personalized healthcare solution generation system was completed.System tests showed that the reasoning algorithm based on fuzzy petri nets can effectively produce personalized exercise and diet solutions for different users based on their unique situations.As for solution quantification,this paper adopted an optimization model based on non-linear programming.The quantification of exercise solution was based on the idea that daily energy consumption through exercise should be as close as possible to the optimal value.As for the quantification of diet solutions,the core idea was that energy abtained from food everyday should be as close as possible to the daily optimal energy intake,considering the constraints of reasonable range of energy and food intake.These two optimal values were both affected by personalized information like sex,age,BMI,daily physical activities,etc.Examples showed that this optimization model can produce reasonable quantification for personalized healcare solutions,which made the excersice and diet solutions very practical and meaningful.