Optimizing track cycling performance through neuromechanical measurement and modelling

Current performance optimization models of track cycling are inadequate to estimate conditions such as the start of the race and during positional changes of the athletes. Monitoring muscle excitation is a valuable way to quantify metabolic changes since it does not discriminate the energy source. Muscle excitation is therefore a good parameter to explore the influence of the energy utilization aspect of model predictions. Therefore, the goal of this proposed research project is to improve existing predictive models of team pursuit performance by incorporating information about muscle excitation in response to all demands inherent to track cycling. Enhanced models will be used to improve innovative products developed by Alphamantis Technologies currently used by the Canadian National Cycling Team as well as commercially available software and training devices. This research will help Canada achieve podium performances and become a world leader in high performance cycling.

Faculty Supervisor:

Marc Klimstra

Student:

Oliver Blake

Partner:

Les Technologies Alphamantis Inc.

Discipline:

Physics / Astronomy

Sector:

Medical devices

University:

University of Victoria