Abstract

The time it takes an athlete to recover from an injury can be highly influenced by training procedures as well as the medical care and physical therapy received. When an injury occurs to the muscles or tendons of an athlete, it is desirable to cool the muscles and tendons within the body to reduce inflammation, thereby reducing the recovery time. Consequently, finding a method of treatment that is effective in reducing tendon temperatures is beneficial to increasing the speed at which the athlete is able to recover. In this project, Bayesian inference with Gaussian processes will be used to model the effect that different treatments have in reducing tendon temperature within the ankle. Gaussian processes provide a powerful methodology for modeling data that exhibit complex characteristics such as nonlinear behavior while retaining mathematical simplicity.

Degree

MS

College and Department

Physical and Mathematical Sciences; Statistics

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2009-07-02

Document Type

Selected Project

Handle

http://hdl.lib.byu.edu/1877/etd2992

Keywords

Statistics, Gaussian, Dynamic Linear Model, Tendon, Temperatures

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