Backster: Wearable Tracking and Visual Feedback of the Torso
Humans typically have difficulty accurately judging the position and orientation of their body, leading to incorrect self-evaluation of form while performing specific tasks such as exercises or stretches. Sports and fitness related injuries often occur because of poor form or incorrect positioning of the torso. Current motion tracking solutions either cannot be implemented easily and cost-effectively in a recreational environment or do not provide high enough accuracy to be useful.
Backster is a shirt that tracks the movements of the user’s torso via six absolute orientation sensors. The system gathers data and then processes it into a real-time computer model of the upper body to allow the user to better understand their form during various exercises, thus allowing them to correct and learn as the exercise is performed. The shirt is washable and the sensors are repositionable to allow for an accurate and individualized experience suitable for a multitude of body types. Additionally, Backster connects to a computer via Bluetooth to ensure full range of untethered motion and ease of use.
For select exercises, the system models not only the torso but also an idealized target pose of the spine and shoulders to provide an exercise-specific goal for the user. Comparison tests between Backster and a camera motion capture system showed less than two and half degrees deviation on average. Backster is a lightweight, inexpensive, and accurate wearable tracking system with applications ranging from physical therapy to personal fitness. Team Spinal Map is comprised of Elyse Chase, Kevin Crossley, Sterling Graham, Nancy Linxuan Fang, Marshall Pritt, and Alysha Singh and is advised by Dr. Bruce Kothmann.
Overall, this project received the Francis G. Tatnall Prize Winner for an outstanding project showing ingenuity, proficiency and usefulness from the Mechanical Engineering and Applied Mechanics Department at the University of Pennsylvania. Afterwards, we went on to compete at the School of Engineering and Applied Science competition were awarded first place.