Automated Camera-Based Estimation of Rehabilitation Criteria Following ACL Reconstruction
This addresses the issue of limited access to time- and cost-intensive screenings for patients undergoing ACL rehabilitation, though it is incremental as it applies existing computer vision techniques to a specific medical domain.
The paper tackled the problem of automating rehabilitation assessments after ACL reconstruction by introducing a camera-based method to estimate leg press displacement and force, achieving 89.7% and 85.3% accuracy compared to standard measurements.
Anterior cruciate ligament (ACL) reconstruction necessitates months of rehabilitation, during which a clinician evaluates whether a patient is ready to return to sports or occupation. Due to their time- and cost-intensive nature, these screenings to assess progress are unavailable to many. This paper introduces an automated, markerless, camera-based method for estimating rehabilitation criteria following ACL reconstruction. To evaluate the performance of this novel technique, data were collected weekly from 12 subjects as they used a leg press over the course of a 12-week rehabilitation period. The proposed camera-based method for estimating displacement and force was compared to encoder and force plate measurements. The leg press displacement and force values were estimated with 89.7% and 85.3% accuracy, respectively. These values were then used to calculate lower-limb symmetry and to track patient progress over time.