S-fit: Knowledge guided fitness pattern mining framework

Health applications have gone beyond fitness data visualization in terms of graphs and trends, and are transitioning towards generating correlation, significant, worst and trending patterns. Novel ways to deal with fitness data patterns are emerging because of advances in (1) Fitness knowledge discovery (2) Fitness data representation and (3) Behavioral and psychological aspects in mining [1]. We propose a health data analytics framework - `S Fit´ that aggregates ontology-based fitness knowledge and user generated health data to extract patterns. These patterns are generated considering psychological, behavioral, and physiological traits of a user. In the process, `Healthification´ of all applications on the mobile phone is realized in terms of personalization of existing features, addition of new features and providing unique user experience.