The persistence of knee extensor moment (KEM) deficits across rehabilitation post-ACL reconstruction (ACLr) may be attributed to difficulty detecting and addressing deficits clinically. During squats, large KEM deficits are present along with much smaller differences in joint or segment angles, making them difficult to detect visually. Data outputs from force plates and video technology may improve clinical identification. Purpose: Investigate the accuracy of three approaches to estimate KEM deficits using outputs from force plate and two-dimensional position data to identify individuals with surgical limb KEM deficits during a bilateral squat. Methods: Forty individuals post-ACLr performed bilateral squats. Kinematic and ground reaction force (GRF) data were collected via 3D motion capture system and tri-axial force plates. Surgical limb deficits were calculated using limb symmetry index (LSI: non-surgical/surgical) at peak knee flexion. Gold standard KEM was calculated using inverse dynamics. Vertical GRF was considered alone, and together with the center of pressure (COP) position to estimate deficits in GRF, and GRF-COP Approaches. Vector Approach used the product of vertical GRF and moment arm calculated using vertical and anterior/posterior GRF, COP and knee position in trigonometric equations. Separate linear regression and ICC(2,k) examined concurrent validity between gold standard LSI and LSI from GRF, GRF-COP, and Vector Approaches. Specificity and sensitivity (LSI threshold ≥ 0.85) determined diagnostic accuracy Results: GRF, GRF-COP, and Vector LSI’s predicted gold standard LSI (R² = 0.56, 0.74, and 0.85 respectively) with ICC(2,k) 0.49, 0.92, and 0.96; sensitivity of 72.2%, 94.4%, 100%, and specificity of 100%, 50%, 100%, respectively. Conclusions: Vertical GRF alone is not adequate to detect KEM deficits. Additional force plate and two-dimensional position data (COP position and moment arm) can strengthen predictive ability and diagnostic accuracy, supporting translation of these variables into commercial products to enhance clinical assessments.
Wang et al. (Tue,) studied this question.