Wearable
technology has become increasingly integrated into our daily lives,
which gathers useful information on the health and exercise patterns of
their wearers. Currently, common fitness wearables provide real-time
statistics as well as a history of exercising
metrics. There are applications that analyse this collected data and
reports back to the uses on their achievements. However, most existing
applications only perform as health monitors rather than as a training
advisor who actively improves the physical status
of the user, such as the roles of a fitness trainer. This project aims
at providing an artificial intelligence solution backed by research in
exercise physiology to the wealth of information collected by modern
wearable devices. The outcome will be an "AI Personal
Trainer" that provides the user with both real-time and long-term
training advice, such as exercise plans and running routes intelligently
tailored to the individual using their unique exercise metrics.
Undergraduate
Research Components:
1) Research
and understand drawbacks of current exercise applications that use
wearable devices to develop a better application experience.
2) Investigate
AI/Machine Learning techniques that can utilise research in exercise
physiology to provide exercise plans, routes,
and real-time training advice much like a personal coach.
Implementation:
Develop a mobile and Internet based software application that realises the
proposed solution.
None
Lab allocations have not been finalised