Nonlinear system model and method for computing and optimizing athletic performance and rehabilitation
Despite tremendous advances in sensor technology, computational methods and the science of physiology, athletic training software remain grounded in outdated science or conventional wisdom. While several dynamic approaches have been proposed to model the response of the human body to physical training, they rely on linear assumptions and fail to account for physiological phenomena such as performance saturation and over-training. Moreover, many of them rely on population-based statistical assumptions rather than personal physiology and fitness of humans. There is an opportunity, therefore, for an accurate physiological model and heuristic algorithm to help optimize training routines for athletes, recovering patients, and fitness enthusiast.
Inventors at Duke University have designed a nonlinear model and heuristic algorithm to predict athletic performance and rehabilitation of individuals in a variety of exercise of scenarios and to optimize training routines based on these predictions. Unlike existing models, this approach successfully captures nonlinear phenomenon such as performance saturation and overtraining. It utilizes a dynamical systems model of oxygen uptake to distinguish between aerobic and anaerobic training scenarios. It uses information about an individual’s physiology, fitness, athletic/rehabilitation goals and constraints rather than generalized population-based statistical assumptions. Moreover, the model and the algorithm are implementable using current means of physiological data collection such as accelerometers, EMGs etc.
- Accounts for nonlinear phenomenon such as performance saturation and overtraining
- Uses an oxygen uptake model to distinguish between anaerobic and aerobic activities
- Does not rely on population based statistical assumptions. Uses individual fitness information instead
- Implementable through existing methods of physiological data collection
Duke File (IDF) Number
- Mann, Brian
- Little, Jared
- Mazzoleni, Michael
- Sequeira, Dane
- Turner, Jim
- Patent Number: PCT/US2017/029709
- Title: SYSTEMS AND METHODS FOR IMPROVIING ATHLETIC TRAINING, PERFORMANCE, AND REHABILITATION
- Country: PCT (Not Applicable)
For more information please contact
- Divakaran, Dinesh
Interested in this Technology?
Submit your interest below.