An approach to generate noncontact ACL-injury prone situations on a computer using kinematic data of non-injury situations and Monte Carlo simulation

Abstract

ACL-injuries are one of the most common knee injuries in noncontact sports. Kinematic data of injury prone situations provide important information to study the underlying ACL-injury mechanisms. However, these data are rare. In this work an approach is presented to generate injury prone situations for noncontact ACL-injuries on a computer. The injury prone situations are generated by a musculoskeletal simulation model using kinematic data of a non-injury situation and the method of Monte Carlo simulation. The approach is successfully applied to generate injury prone landings in downhill ski racing. The characteristics of the obtained injury prone landings are consistent with video recordings of injury cases.