Anterior cruciate ligament (ACL) injury classification system using support vector machine (SVM)

Anterior Cruciate Ligament (ACL) injury is the most common injury among athlete. The existing method applied by medical expert is based on traditional statistics, whereby used naked eye with experience to analysis ACL injury. The contribution proposed is this research study is to replicate medical knowledge into automated system. In this paper, a learning method, Support Vector Machine (SVM), is applied on three (3) different types of ACL injury data, which are normal, partial and crucial. Therefore, classification ACL injury with multi class is one of the most important tasks for applications such as pattern recognition, injury data categorization and etc. Results from this paper shows, SVM able to classify up to 100% for each class and validated through medical expert analysis.