Real-time motion detection for physical fitness & rehabilitation

The evolution of digitally connected devices and artificial intelligence has opened the door for novel health and fitness applications that can be used by individuals at a time and in an environment convenient to them. The purpose of our research is to develop low cost and accessible platforms that requires no additional hardware to provide fitness and training programs.

An online balance training program using augmented reality

Balance exercises are often prescribed for healthy aging to keep the body active, improve balance and coordination, and prevent falls and injuries, as well as, for those doing rehabilitation after injuries or diseases such as stroke. We developed a simple web application (BaART: Balance Augmented Reality Trainer) that uses PoseNet to determine a user’s location and pose to count the number of repetitions that were done successfully. Furthermore, we looked at how augmented reality, and specifically adding a virtual chair, might impact a user’s sense of balance. In a study of 20 participants with and without balance disorders, we found that the developed system was easy to use and many would consider using such a system, particularly our older participants who spend more time at home. However, we also found that the virtual object (i.e. chair) was not used by most people. Furthermore, those with balance issues felt they required a real chair for balance and some even felt that the virtual object was distracting from the exercise. In the future, we plan to explore other uses of augmented reality, such as feedback on exercise quality, gaming features, and a virtual avatar trainer.