Abstract
A multidisciplinary design optimization (MDO) approach is proposed to aid in the prediction of non-contact anterior cruciate ligament (ACL) injury mechanisms and risk factors. In this investigation the need for such an approach is argued based on an exhaustive evaluation of diverse factors that cause non-contact ACL injury, and the similarly numerous and different existing study approaches that have been carried out to investigate injury. The proposed MDO approach fuses patient data and existing study approaches via an artificial intelligent (AI) technique—absent in previous biomechanics investigations—so as to offer new insights into ACL injury prevention.
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