3D Gait Analysis to Identify Running Injury Risk
May 19, 2016
Melbourne Sports & Allied Health Clinic specialises in high precision running assessments, utilising 3-Dimensional (3D) apparatus and expertise (Dr. Oren Tirosh, biomechanist), previously only available to individuals with access to University, Hospital or Sports Institute movement laboratories. Our scope of clientele include runners of all ages and abilities. The following summary outlines the benefits of 3D gait analysis to identify running injury risk, as a pro-active approach - and later evaluating the effectiveness of rehabilitation intervention following an injury. Furthermore, the effect of running in an exerted state (fatigue) on lower extremity kinematics may also be explored.
Running injuries are related to gait mechanics
Research shows that common running injuries are related to gait mechanics that can only be identified using 3D computerised systems (Dierks and Davis, 2008; Souza et al, 2009). 42% of all running injuries are to the knee, followed by 17% to the foot/ankle, 13% to the lower leg and 11% to the hip/pelvis (Taunton et al 2002; Pinshaw et al, 1984). The most common overuse injuries are patellofemoral pain syndrome (runner’s knee), iliotibial band friction syndrome, and tibial stress syndrome (Taunton et al 2002). All of these injuries are associated with deficiencies of both frontal and transverse plane segmental movement patterns that can only be identified utilising 3D computerised systems. For example, patellofemoral pain syndrome is associated with greater peak hip adduction and internal rotation (Dierks and Davis, 2008; Souza et al, 2009; Ferber et al 2003; Willson and Davis, 2008). Iliotibial band syndrome is reported to be associated with greater hip adduction and peak knee internal rotation angles (Ferber et al 2010; Noehren et al, 2007). Large degree of rear-foot eversion at mid-stance may place disproportionate strain on medial fibres of the achilles tendon (Clement et al, 1984).
3D computerised system
Only 3D computerised systems are considered to be sufficiently precise and reliable. It is, therefore, recognised as the “gold standard” of clinical gait used in research, and for surgical decision making in hospitals. It is superior to 2D video analyses methods, commonly used in private practices. Scientifically, 2D video analysis have proven measurement errors that limit the diagnosis and the evaluation of interventions (Nigg and Cole, 1994; Sih et al, 2001; Krosshaug et al, 2007).
3D gait analysis is a non-invasive method of accurately measuring the way you move. Small, spherical reflective markers are attached to the body, and the three-dimensional positions of these markers are measured using infrared cameras as you move. The three-dimensional positions of the markers are then used to create an exact computer model of your running pattern. The personalised model is then used to accurately calculate your joint angles in all three planes.
In 3D gait analysis, the data for a single athlete are interpreted on the basis of 12 graphs, including kinematic variables (see Figure 1). Features that are interpreted clinically include the magnitude and waveforms of the different traces; the difference between the traces and those from healthy controls (plotted in grey); the differences between left (red) and right (blue) traces; and the differences between pre and post intervention. Figure 1 shows 3D gait analysis performed preseason on an athlete, who sustained a knee injury several months following the analysis. It is clear from the analysis that the athlete had excessive hip adduction at initial foot ground contact with peak hip internal rotation at mid stance.
Left leg: Red
Right leg: Blue
Grey area: average (+/- SD) for healthy adults
Vertical line: toe-off
Figure 1. 3D running kinematics obtained from 3D gait analysis.
For more information, please contact Dr. Oren Tirosh.
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