Building a Data Collection Architecture for Exercise Training and Health Monitoring

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The selection of athletes for a sports competition is based on his/her achievements and experience. According to research, in the professional sports program, the selection criteria should be based on the characteristics of the competition, the size, physiology, test value, psychological and physiological development and characteristics of the athletes. However, the qualifications of athletes on cross‐disciplinary and skill have not been fully implemented.This study is to build a data collection architecture for exercise training and health status monitoring for athletes. The data items which will be stored including sports training data, biochemical indicators, dietary intake, psychological and physiological data, fatigue index etc. There is a data analysis platform build for future data processing.The design of the collection architecture is divided into five phases, including definition, capture, contribution, share, and analysis. The definition phase and the capture phase are happened in each data source unit and data are transferred and stored in a central data repository. Each data source plays as a contribution role which will follow a prearranged research protocol of the central repository. The information acquisition and storage mechanism are also designed for the repository. The sharing stage is to design a transferring and sharing mechanism for athlete training and competition data to build an exercise research database which is used as a base in the analysis platform in the repository.The system includes five core modules: Data Contributor, Data Dictionary, Data Access, User Management, and Repository Management. The Data Contributor module provides users with a research case on the web page so that participants can upload data. A screening process is also designed to verify the correctness of the sports data and research database. The Data Dictionary module is to provide the definitions of the Basic Data Elements (BDE) which is the most commonly used fields defined by defined by the project, and Extended Data Elements (EDE) which is the user defined data fields and can be added to the BDE.Data Access module is the control module for data access permission. The owner of the research case can share the information, once shared, all members of the team will have the right to view and obtain all data, and can query the data in the database in the system. The User Management module is the research team member and its data usage rights. The research owner can set the usage rights of each member. The Repository Management module manages the database structure and provides views of the contents of the database. Using the data collection architecture, the researcher can manage, share, distribute, and process the information and training schedules of participating athletes.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.