Shelfie

Abstract

Self-monitoring devices are becoming increasingly popular in the support of physical activity experiences. These devices mostly represent on-screen data using numbers and graphs and in doing so, they may miss multi-sensorial methods for engaging with data. Embracing the opportunity for pleasurable interactions with one's own data through the use of different materials and digital fabrication technology, we designed and studied three systems that turn this data into 3D-printed plastic artifacts, sports drinks, and 3D-printed chocolate treats. We utilize the insights gained from associated studies, related literature, and our experiences in designing these systems to develop a conceptual framework, “ Shelfie. ” The “ Shelfie ” framework has 13 cards that convey key themes for creating material representations of physical activity data. Through this framework, we present a conceptual understanding of relationships between material representation and physical activity data and contribute guidelines to the design of meaningful material representations of physical activity data.

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

“…For general population, and in clinical applications, an interesting outside-the-box visualisation technique is to involve participants in 3D printing of their activity data (e.g. as food items and allowing better engagement with the exercise or rehabilitation process in a novel and entertaining way as demonstrated by Khot et al[402] with the Shele framework.…”