Fitness Scheme Recommendation System And Its Application Based On Auto Encoder

In order to have a healthy physique,more and more people have begun to walk into the gym to exercise.However,due to various factors,many people cannot persist in long-term exercise or even give up halfway through.How to obtain information from massive body composition and dimensional data to guide people to participate in fitness and learn to exercise has become an urgent problem due to lack of mature research and application.At the same time,in the context of the outbreak of the new crown pneumonia this year,the digital health industry has attracted much attention.Among them,wearable devices rely on the popularization of 5G networks,big data,cloud computing,artificial intelligence and other technologies,ushering in major development opportunities.Due to its advantages of portability,multi-functionality,and intelligence,its application scenarios in the personal health and medical field are also becoming more abundant.Therefore,research on the application of wearable devices in the field of personal fitness has practical significance and broad market prospects.The application mode of the wearable device in the personal fitness field is generally to detect body data in real time,and then send it to the mobile terminal through the communication module,and finally the mobile terminal sends the data to the server for calculation and displays the returned result to the user.To a certain auxiliary and guiding role.Based on this model,this paper designs a fitness program recommendation system.The system includes an automatic encoder based on a fully connected neural network and an AKC model of K-means algorithm and an intelligent private education system based on an expert system model.The user can be divided into different body types by inputting the user's body data,and then the personalized fitness program can be recommended through the intelligent personal education system.Finally,this article introduces the application scenarios of wearable miniature near-infrared spectrometer in personal fitness field.Based on this program and the fitness program recommendation system,an Ap client based on the IOS system was developed.Real-time measurement of user data and access to fitness recommendations.Through control experiments,it is proved that the fitness program recommendation system can greatly help the fitness guidance by dividing the user types and recommending fitness programs.The system has made new attempts in application models that use big data to guide personal health.