ACL injuries hit over 200,000 people a year in the U.S., and that number keeps climbing. Even after surgery and months of physiotherapy, only 55% of athletes make it back to competitive sport, and half of those never regain their pre-injury form.
During recovery, clinicians rely on eyeballing strength and range of motion rather than quantitative data, which means some athletes return too soon and re-injure, while others recover fully but remain sidelined out of caution.
Throughout the 2026–2027 academic year, our team worked through every stage of the engineering design process to create a solution for ACL rehabilitation.
The result is Mustang Motion: a smart, 3D-printed knee brace designed to provide clinicians with quantitative data to better monitor and guide patient recovery.
The knee brace integrates sensors positioned above and below the knee to measure knee range of motion and quadriceps muscle activation, allowing more informed clinical decisions throughout the rehabilitation process.
Entirely 3D printed, multiple filament types were used to address biocompatibility
Adjustable strap to fit different leg sizes comfortably
Hinge used at the knee to allow easy flexion and extension of the quadriceps
CAD developed through OnShape, FEA in SolidWorks
Sensor data streams wirelessly to a computer app in real time
The app shows live knee movement and muscle activity side-by-side for both legs
Machine learning model estimates recovery progress and predicts when someone's ready to return to sport
Arduino Nano measures the range of motion
In-house EMG sensors detect muscle activity in the quads and hamstrings
Two rechargeable 9V batteries power the whole system for about a day of use
Out of 10 teams, Western placed 1st provincially and 4th overall. It was a long day of testing, pitching and technical discussion. Huge thank you to the TNBC committee, and we'll see you guys next year!