Making Sense of Complex Running Metrics Using a Modified Running Shoe

Abstract

Running is a widely popular physical activity that offers many health benefits. As runners progress with their training, understanding one’s own body becomes a key concern in achieving wellbeing through running. While extensive bodily sensing opportunities exist for runners, understanding complex sensor data is a challenge. In this paper, we investigate how data from shoe-worn sensors can be visualised to empower runners to improve their technique. We designed GraFeet—an augmented running shoe that visualises kinesiological data about the runner’s feet and gait. We compared our prototype with a standard sensor dashboard in a user study where users ran with the sensor and analysed the generated data after the run. GraFeet was perceived as more usable; producing more insights and less confusion in the users. Based on our inquiry, we contribute findings about using data from body-worn sensors to support physically active individuals.