More than 55% of all athletic injuries are incurred on the lower extremity, 1-4 while damage specific to the knee accounts for approximately 15% of all athletic injuries. 5 Overall, 43% of these knee injuries are classified as strains or sprains, which makes them the third most prevalent form of lower extremity injury with a rate of 102 incidents per 100,000 athletes per year. 6 Of these knee injuries, it is estimated that 45% involve internal knee trauma, and 49% of those entail anterior cruciate ligament (ACL) rupture, 7 as 1 in 3,000 persons are likely to suffer an ACL disruption each year. 8 However, ACL injury is a sex-specific event, as females are 2 to 10 times more likely to suffer ACL disruption than their male counterparts, 9-14 which produces an incidence rate of 1 ACL tear in every 50 to 70 female athletes per year. 15 These high incidence rates of ACL rupture lead to an estimated 250,000 ACL tears and 127,000 ACL reconstructions (ACLR) annually in the United States. 16,17 With conservative repair estimates ranging from $5,000 to $44,000 per ACLR depending on the type of repair and severity of injury, 13,18-20 the annual medical expense of ACL injury treatments in the United States alone may exceed $2 billion. Worldwide, it is estimated that the annual incidence of ACL tears could reach as high as 2 million patients, 21 which would exponentially increase these costs. Unfortunately, despite the expense associated with ACLR, surgical repair has not been found to significantly reduce the longterm outlook of knee osteoarthritis compared with nonoperative rehabilitation. 22,23 As many as 86% of patients demonstrated early onset osteoarthritis following ACLR and 75% report degradation in knee quality of life within 20 years postsurgery. [23][24][25] For these reasons, the focus on treating ACL injuries may be best served through identification and treatment of modifiable injury risk factors that may prevent ruptures before they happen.Two-and three-dimensional (2D and 3D) motion analysis systems have been used in vivo to identify, classify, and associate biomechanical risk factors with the likelihood of Keywords ► anterior cruciate ligament injury ► injury risk classification ► motion capture ► motion analysis ► neuromuscular training
AbstractAnterior 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 a...