Application of Machine Learning to Vision-Based Pose Data for Exercise Classification

The research will be using visual information from the phone’s camera as well as demographic information from participants and implement various machine learning algorithms such as random forests, support vector machines, etc. to provide feedback regarding different exercises to the participant. Specifically, the algorithms will classify the exercise types. Furthermore, these algorithms will be optimized for use on smart phones. The partner organization intends to incorporate the algorithms in their mobile app for mass use. Such research methods allow for a more health-conscious use of smart phones and would give the partner organization a significant edge in technological development in the health-related sector.

Faculty Supervisor:

William Dale Stevens

Student:

Amir Zarie

Partner:

FITFI Inc

Discipline:

Psychology

Sector:

Professional, scientific and technical services

University:

York University