Motion Analysis and the Anterior Cruciate Ligament: Classification of Injury Risk

Abstract

Anterior cruciate ligament (ACL) injuries are common, catastrophic events that incur large expense and lead to degradation of the knee. As such, various motion capture techniques have been applied to identify athletes who are at increased risk for suffering ACL injuries. The objective of this clinical commentary was to synthesize information related to how motion capture analyses contribute to the identification of risk factors that may predict relative injury risk within a population. Individuals employ both active and passive mechanisms to constrain knee joint articulation during motion. There is strong evidence to indicate that athletes who consistently classify as high-risk loaders during landing suffer from combined joint stability deficits in both the active and passive knee restraints. Implementation of prophylactic neuromuscular interventions and biofeedback can effectively compensate for some of the deficiencies that result from poor control of the active knee stabilizers and reduce the incidence of ACL injuries.