TRAINER – A Content-Based Recommender System of Training Workouts and Nutritional Diets for Fitness Enthusiasts
Abstract : The TRAINER system is a personalized health and fitness solution developed for the Fitness Zone Fitness Center in Antipolo, Philippines, to address the shortcomings of generic, “one-size-fits-all” training programs. By utilizing a content-based recommender system driven by machine learning, the platform integrates individual user profiles—including fitness levels, personal goals, and dietary preferences—with a curated repository of workouts and nutritional plans. The system features a web-based interface for real-time data collection and progress tracking, employing a continuous feedback loop to ensure recommendations remain dynamic and adaptive. Ultimately, TRAINER seeks to enhance client adherence and health outcomes by providing data-driven, context-aware guidance that bridges the gap between limited instructor availability and the diverse needs of fitness enthusiasts.
Authors
- Tucay Edmundo C.
- Ricafort Reagan B.
Institutions
- AMA Computer University (PH)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-04-16
- DOI
- https://doi.org/10.5281/zenodo.19639793
- Primary Topic
- Mobile Health and mHealth Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00