StFX Profs And Coach Analysing Data For Runners
February 22nd, 2013
Running is a growth sport in North America, with more people than ever competing in organized races and fun runs. Many amateur athletes are serious enough about training to buy a GPS-heart rate monitor device that logs their heart rate and running route. While this training data seems useful, the information rarely tells the runner much about actual training improvement.
But now two StFX professors, Dr. Dave Risk in earth sciences, and Dr. Dan Kane in human kinetics, and Bernie Chisholm, coach of StFX’s cross-country teams, have received $20,000 in funding from Springboard Atlantic for a one-year research grant to begin a proof-of-concept project that will demonstrate algorithms can be embedded in existing hardware, like GPS heart rate monitors, and used to help runners train more effectively.
Third-year student Elizabeth O’Connell is participating in the Springboard project as a StFX runner and a student researcher.
Runners who are serious about improving commonly use controlled benchmark performance tests, which are often inaccessible for everyday athletes, they say.
“Athletic performance data can potentially be mined from training data that is logged with a typical GPS heart rate monitor watch, but there are surprisingly few examples of algorithms to extract this data,” says Dr. Risk.
Dr. Risk brings computational expertise in the modeling of microbial metabolism to the project, while Dr. Kane contributes in the area of human physiology and performance. Using performance data from some members of Mr. Chisholm’s running team, who will log their runs, upload exercise files, and take occasional performance tests, the project will allow the researchers to compile data that will be compared with that generated from standardized performance tests.
The project team will then use this information and create algorithms that could be embedded directly in GPS-heart rate devices, or in computer programs used by runners.
A second untrained group will also participate, as there may also be applications for similar monitoring techniques within the health sector.