Prediction of Kinematic and Kinetic Performance in a Drop Vertical Jump with Individual Anthropometric Factors in Adolescent Female Athletes: Implications for Cadaveric Investigations

Abstract

Anterior cruciate ligament injuries are common, expensive to repair, and often debilitate athletic careers. Robotic manipulators have evaluated knee ligament biomechanics in cadaveric specimens, but face limitations such as accounting for variation in bony geometry between specimens that may influence dynamic motion pathways. This study examined individual anthropometric measures for significant linear relationships with in vivo kinematic and kinetic performance and determined their implications for robotic studies. Anthropometrics and 3D motion during a 31 cm drop vertical jump task were collected in high school female basketball players. Anthropometric measures demonstrated differential statistical significance in linear regression models relative to kinematic variables (P-range < 0.01-0.95). However, none of the anthropometric relationships accounted for clinical variance or provided substantive univariate accuracy needed for clinical prediction algorithms (r2 < 0.20). Mass and BMI demonstrated models that were significant (P < 0.05) and predictive (r2 > 0.20) relative to peak flexion moment, peak adduction moment, flexion moment range, abduction moment range, and internal rotation moment range. The current findings indicate that anthropometric measures are less associated with kinematics than with kinetics. Relative to the robotic manipulation of cadaveric limbs, the results do not support the need to normalize kinematic rotations relative to specimen dimensions.

Immediate effect of ACL kinesio taping technique on knee joint biomechanics during a drop vertical jump: a randomized crossover controlled trial

“…Knee joint angles at initial contact (IC) were selected for analysis. IC was defined as a vertical ground reaction force greater than 10 N [17, 18]. The knee joint angles and moments were selected from initial contact to take off from the first landing of each DVJ.…”

Sex-based differences in knee ligament biomechanics during robotically simulated athletic tasks

“…Cadaveric specimens were limited to under 55 years of age, but were not anatomically matched to the in vivo subjects tested. Previous literature had demonstrated that kinematics are not correlated to stature and do not require normalization to specimen anthropometrics, which indicates that in vivo kinematics should be applicable to unmatched anatomical specimens (Bates et al, 2015a). The limbs were tested using a six-degree-of-freedom (6-DOF) robotic manipulator (KR210; KUKA Robotics Corp., Clinton Township, MI) mounted with a six-axis load cell (Theta Model; ATI Industrial Automation, Apex, NC).…”

Effects of Population Variability on Knee Loading During Simulated Human Gait

“…Indeed, investigators have previously examined if individual anatomical measurements correlated with knee kinetics and kinematics in order to compensate for between-specimen variability during robotic simulations. 4 It was concluded that these models failed to account for enough of the variance to serve as clinical predictors. Accordingly, more complex and potentially non-linear statistical methods may be required to model between specimen variability during motion tasks.…”

“…While anthropometric models failed to clinically predict knee kinetics and kinematics, they did exhibit statistically-significant correlations with these outcomes. 4 Similarly, anterior knee laxity has been correlated with the magnitude of anterior tibial translation during weight-bearing and ACL strain during astrometry exams. 29, 40 Neither factor is enough to predict knee kinetic or kinematics individually, but they both have been shown to play definitive roles in the variability of these outcome between subjects.…”

“…Previous studies have attempted to leverage donor data by establishing linear correlations between anthropometric variables and knee kinematics, but have not proven robust enough to predict performance during in vivo athletic tasks. 4 Therefore, this study takes a unique, model-driven approach to investigate an even broader range of factors in order to identify key factors of human knee joints which lead to the most kinetic variability for a standard simulated gait motion. Effects of human tibiofemoral geometry and 6-degree-of-freedom (6DOF) knee stiffness on 6DOF kinetic outputs were considered.…”