Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
389377 | Fuzzy Sets and Systems | 2016 | 20 Pages |
Abstract
Self-tracking our physical activity allows us to acquire a better self-knowledge about our physical, and even mental health condition. Currently, the description of the time series provided by sensors is done by means of graphics and tables, that are hard to interpret by non-expert humans. Here, we present a computational application that dynamically describes in natural language the physical activity. The final reports are adapted to the everyday language and user's needs. The application highlights the relevant information obtained at different levels of temporal detail. We have included experimental results that demonstrate the flexibility and applicability of the new tool.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Daniel Sanchez-Valdes, Alberto Alvarez-Alvarez, Gracian Trivino,