Introduction: The aim of this study was to determine whether using a direct kinematic (DK) or inverse kinematic (IK) modeling approach could influence the estimation of knee joint kinematics, kinetics, and ACL injury risk classification during unanticipated side cutting.
Methods: The three-dimensional motion and force data of 34 amateur Australian rules footballers conducting unanticipated side-cutting maneuvers were collected. The model used during the DK modeling approach was an eight-segment lower body model with the hip, knee, and ankle free to move in six degrees of freedom. During the IK modeling approach, the same eight-segment model was used; however, translational constraints were imposed on the hip, knee, and ankle joints. The similarity between kinematic and kinetic waveforms was evaluated using the root mean square difference (RMSD) and the one-dimensional statistical parametric mapping (SPM1D). The classification of an athlete’s ACL injury risk was determined by correlating their peak knee moments with a predefined injury risk threshold.
Results: The greatest RMSD occurred in the frontal plane joint angles (RMSD = 10.86°) and moments (RMSD = 0.67 ± 0.18 N·m·kg−1), which were also shown to be significantly different throughout the stance phase in the SPM1D analysis. Both DK and IK modeling approaches classified the same athletes as being at risk of ACL injury.
Conclusions: The choice of a DK or an IK modeling approach affected frontal plane estimates of knee joint angles and peak knee moments during the weight acceptance phase of unanticipated side cutting. However, both modeling approaches were similar in their classification of an athlete’s ACL injury risk.
1School of Sport and Exercise Sciences, Liverpool John Moores University, Liverpool, UNITED KINGDOM; and 2School of Sport Science, Exercise and Health, University of Western Australia, Perth, AUSTRALIA
Address for correspondence: Mark Robinson, Tom Reilly Building, Byrom Street Campus, Liverpool, Merseyside, L3 3AF, United Kingdom; E-mail: firstname.lastname@example.org.
Submitted for publication May 2013.
Accepted for publication November 2013.
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