Multimodal Wearable System for Objective Assessment of Dynamic Rotational Knee Biomechanics Following ACL Injury and Reconstruction: A Clinical Validation Study Using Ensemble Deep Learning

BackgroundThe clinical assessment of knee stability after an Anterior Cruciate Ligament (ACL) injury is routinely conducted via operator-dependent physical examination tests (i.e. pivot shift) and standardized patient-reported outcomes. Unfortunately, both are unable to perceive and quantify the subtle rotational biomechanical deficiencies from an ACL tear. Although specialized laboratory-based motion capture systems may provide objective measurements, they are found in research institutions and thus, are not suitable for clinical use. In contrast, GATOR PRO is a clinic-based multimodal wearable sensor system that uses a machine learning (ML) model (ensemble deep learning) to differentiate a