Aim 1 will establish a testable AR-based smartphone app that measures clinically relevant lower-extremity motion components. Existing AR code will be adapted to identify and quantify hip, knee, and ankle range of motion in both the coronal and sagittal planes. Output will be produced directly to the phone display and can also be downloadable. Both single-motion and sequential-motion (gait) measures will be captured.~Aim 2 will then compare the app-based MCA to traditional gold standard MCA in healthy volunteers. A dedicated human biomechanics lab with capability for MCA with reflective markers will be utilized to test both MCA methods. Patients will perform a box jump and normal walking gait, and the measurements from both the standard marker-based MCA system and the smartphone markerless MCA system will be statistically compared.
The investigators propose to create a markerless smartphone-based MCA application using AR to measure joint motion and gait patterns to address this technology gap for a simple and inexpensive MCA.