A Faster, More Effective Way to Identify and Prevent Sports Injuries

New research is underway at the University of Waikato’s Adams Centre for High Performance that aims to develop an easy test which will identify those at highest risk of lower body sports injuries.

PhD student Ivana Hanzlíková is running the project, working with the latest 3D motion capture technology to devise the sport-related standardised screening system under the supervision of Dr Kim Hébert-Losier, Senior Lecturer in Biomechanics.

Increased participation in physical activities also increases the likelihood of suffering sport-related injuries. Lower extremity injuries account for 50% of all sport injuries, with ankles and knees being the most common injury sites. Sports that have the highest rate of overall lower body injury include American football, soccer, netball, volleyball, and basketball where it is common to land on one leg. Ivana says the injuries often involve complex movements, such as side-cutting, pivoting, or cross-cutting. “There is already a lot of evidence that we can reduce these injuries using sports exercise programmes. But we need to find athletes who are at risk to actually apply this to.”

So far she has tested 18 participants, but needs 24 more. Those who want to be involved need to be 16-35 years old and participating in some sport which involves changes in direction – soccer, basketball, handball, netball, rugby, and hockey. They can be competing at any level, but can’t currently have an injury – although a history of injury is not a problem.  The research test sessions are 1.5 to 2 hours long (most of the time involves the placement of markers), and are carried out at the Adams Centre in Mt Maunganui where the 3D motion capture technology is housed.

As a benefit, the athletes will get full reports on their risk profiles, pinpointing the specific areas which are most vulnerable for them indvidually. They will be provided with suggestions to target the problems, including exercises. The video below includes the 3D skeletal representations of the data used in the research project.