ABSTRACT:The relationships between non-contact anterior cruciate ligament injuries and the underlying biomechanics are still unclear, despite large quantities of academic research. The purpose of this research was to study anterior cruciate ligament strain during jump landing by investigating its correlation with sagittal plane kinetic/kinematic parameters and by creating an empirical model to estimate the maximum strain. Whole-body kinematics and ground reaction forces were measured from seven subjects performing single leg jump landing and were used to drive a musculoskeletal model that estimated lower limb muscle forces. These muscle forces and kinematics were then applied on five instrumented cadaver knees using a dynamic knee simulator system. Correlation analysis revealed that higher ground reaction force, lower hip flexion angle and higher hip extension moment among others were correlated with higher peak strain (p < 0.05). Multivariate regression analyses revealed that intrinsic anatomic factors account for most of the variance in strain. Among the extrinsic variables, hip and trunk flexion angles significantly contributed to the strain. The empirical relationship developed in this study could be used to predict the relative strain between jumps of a participant and may be beneficial in developing training programs designed to reduce an athlete's risk of injury. Keywords: ACL; muscle force; musculoskeletal modeling; risk factor; knee injuryDespite the large quantity of research available on non-contact anterior cruciate ligament (ACL) injuries, the contributing factors and their relative contribution to the injury is still under debate. 1 This is in part due to the difficulty of measuring ACL strain in vivo 2 and inability to relate the ACL strain to the possible contributing factors. Unless the relationships between body kinematics, muscle forces and ACL strain is understood, the mechanism of ACL injury will remain unclear. Understanding the mechanics behind these injuries is crucial for injury prevention. Injuries may be prevented if screening and training programs are created for athletes who display at-risk mechanics. [3][4][5] Sagittal plane factors have been identified as important contributors to ACL injury mechanisms. [6][7][8] In addition to these extrinsic biomechanical factors, ACL strain is also dependent on a number of intrinsic anatomic factors such as tibial slope, 9,10 femoral notch width, 11 and ACL size. 12 Although these factors are known correlates with ACL strain, the relative contribution of extrinsic biomechanical and intrinsic anatomical factors is unknown.Pioneering efforts have been made to understand the relationship between knee kinematics, kinetics and ACL strain by surgically placing strain gauges on ligaments in live participants. 13 However, for ethical reasons, such approaches have not been extended to activities that are dynamic in nature. Numerical modelling approaches have been used to address this gap [14][15][16] ; however, model validation is complicated by the lack...

Prophylactic knee brace could reduce the strain in the anterior cruciate ligament of high-risk subjects during drop-landing through altered muscle firing pattern associated with brace wear. This could help reduce the anterior cruciate ligament injury risk.

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Estimation of muscle forces through musculoskeletal simulation is important in understanding human movement and injury. Unmatched filter frequencies used to low-pass filter marker and force platform data can create artifacts during inverse dynamics analysis, but their effects on muscle force calculations are unknown. The objective of this study was to determine the effects of filter cutoff frequency on simulation parameters and magnitudes of lower-extremity muscle and resultant joint contact forces during a high-impact maneuver. Eight participants performed a single-leg jump landing. Kinematics was captured with a 3D motion capture system, and ground reaction forces were recorded with a force platform. The marker and force platform data were filtered using 2 matched filter frequencies (10-10 Hz and 15-15 Hz) and 2 unmatched filter frequencies (10-50 Hz and 15-50 Hz). Musculoskeletal simulations using computed muscle control were performed in OpenSim. The results revealed significantly higher peak quadriceps (13%), hamstrings (48%), and gastrocnemius forces (69%) in the unmatched (10-50 Hz and 15-50 Hz) conditions than in the matched (10-10 Hz and 15-15 Hz) conditions (P < .05). Resultant joint contact forces and reserve (nonphysiologic) moments were similarly larger in the unmatched filter categories (P < .05). This study demonstrated that artifacts created from filtering with unmatched filter cutoffs result in altered muscle forces and dynamics that are not physiologic.