Sean P Sankey1, Raja M Firhad Raja Azidin2, Mark A Robinson2, Bart Malfait3, Kevin Deschamps3, Sabine Verschueren3, Filip Staes3, Jos Vanrenterghem2. 1. Research Institute for Sport and Exercise Sciences, Faculty of Science, Liverpool John Moores University, Liverpool, UK; Engineering, Sport and Sciences, University of Bolton, Bolton, UK. Electronic address: S.Sankey@bolton.ac.uk. 2. Research Institute for Sport and Exercise Sciences, Faculty of Science, Liverpool John Moores University, Liverpool, UK. 3. KU Leuven, Musculoskeletal Rehabilitation Research Group, Department of Rehabilitation Sciences and Physiotherapy, Faculty of Kinesiology and Rehabilitation Sciences, Belgium.
Abstract
INTRODUCTION: Side-cutting tasks are commonly used in dynamic assessment of ACL injury risk, but only limited information is available concerning the reliability of knee loading parameters. The aim of this study was to investigate the reliability of side-cutting data with additional focus on modelling approaches and task execution variables. METHODS: Each subject (n=8) attended six testing sessions conducted by two observers. Kinematic and kinetic data of 45° side-cutting tasks was collected. Inter-trial, inter-session, inter-observer variability and observer/trial ratios were calculated at every time-point of normalised stance, for data derived from two modelling approaches. Variation in task execution variables was regressed against that of temporal profiles of relevant knee data using one-dimensional statistical parametric mapping. RESULTS: Variability in knee kinematics was consistently low across the time-series waveform (≤5°), but knee kinetic variability was high (31.8, 24.1 and 16.9 Nm for sagittal, frontal and transverse planes, respectively) in the weight acceptance phase of the side-cutting task. Calculations conveyed consistently moderate-to-good measurement reliability. Inverse kinematic modelling reduced the variability in sagittal (∼6 Nm) and frontal planes (∼10 Nm) compared to direct kinematic modelling. Variation in task execution variables did not explain any knee data variability. CONCLUSION: Side-cutting data appears to be reliably measured, however high knee moment variability exhibited in all planes, particularly in the early stance phase, suggests cautious interpretation towards ACL injury mechanics. Such variability may be inherent to the dynamic nature of the side-cutting task or experimental issues not yet known.
INTRODUCTION: Side-cutting tasks are commonly used in dynamic assessment of ACL injury risk, but only limited information is available concerning the reliability of knee loading parameters. The aim of this study was to investigate the reliability of side-cutting data with additional focus on modelling approaches and task execution variables. METHODS: Each subject (n=8) attended six testing sessions conducted by two observers. Kinematic and kinetic data of 45° side-cutting tasks was collected. Inter-trial, inter-session, inter-observer variability and observer/trial ratios were calculated at every time-point of normalised stance, for data derived from two modelling approaches. Variation in task execution variables was regressed against that of temporal profiles of relevant knee data using one-dimensional statistical parametric mapping. RESULTS: Variability in knee kinematics was consistently low across the time-series waveform (≤5°), but knee kinetic variability was high (31.8, 24.1 and 16.9 Nm for sagittal, frontal and transverse planes, respectively) in the weight acceptance phase of the side-cutting task. Calculations conveyed consistently moderate-to-good measurement reliability. Inverse kinematic modelling reduced the variability in sagittal (∼6 Nm) and frontal planes (∼10 Nm) compared to direct kinematic modelling. Variation in task execution variables did not explain any knee data variability. CONCLUSION: Side-cutting data appears to be reliably measured, however high knee moment variability exhibited in all planes, particularly in the early stance phase, suggests cautious interpretation towards ACL injury mechanics. Such variability may be inherent to the dynamic nature of the side-cutting task or experimental issues not yet known.
Authors: Sandra J Shultz; Randy J Schmitz; Anne Benjaminse; Malcolm Collins; Kevin Ford; Anthony S Kulas Journal: J Athl Train Date: 2015-09-04 Impact factor: 2.860