End-user Techniques for Aggregating and Analyzing Exercise and Physical Data

Launched in 2016, the University of Michigan's Exercise & Sport Science Initiative (ESSI) draws on the expertise of faculty from a wide range of disciplines across campus, Michigan Athletics and industry partners to optimize performance and health for people of all ages and abilities.

The research team has proposed a plan to build a "data warehouse" that would enable recreational athletes, coaches and even fans to collect physical data from various sources, such as FitBits, smartwatches and phones in order to improve their performance.

Start date: April 12, 2017
End date: April 11, 2019

 

Read More

The project, End-user Techniques for Aggregating and Analyzing Exercise and Physical Data, aims to develop tools that will allow non-programmers to collect and integrate "big data" from multiple sensors. The team could then visualize, analyze and share these data and act on the collected data to improve athletic performance and training. Currently, none of these applications are possible without significant programming expertise and effort, the researchers say.

They anticipate that some of their users would be interested in maximizing their athletic performance, while others might be interested in fitness gains, and still others might be interested in rehabilitating or recovering from injuries. The researchers believe that if they are successful in working with recreational athletes, they may be able to apply their findings in more professional team settings as well.

Grants

The University of Michigan's Exercise & Sport Science Initiative (ESSI), $198,327