The app, and algorithm behind it, address problems with the pivot test, which is used to assess at what point in the knee’s movement the patient can no longer support weight. The trouble is, the pivot test suffers from a lack of standardization around interpretation of the results and has proven unreliable. Now, researchers at the Orthopaedic Robotics Laboratory of the University of Pittsburgh and Swanson School of Engineering have developed technology to remove the guesswork and interpret pivot test data quantitatively. Information from video tracking of the moving knee is translated into quantifiable results that are analyzed by the app.This will help identify the specifics of each unique injury, allowing the team of physicians involved to give each case the proper treatment. And knees are not the only things that stand to benefit: the ORL’s technology could also be used for procedures in elbow and back injuries. Source: A TABLET-BASED, SINGLE IMAGE DIAGNOSTIC TOOL FOR QUANTITATIVE ANALYSIS OF ACL INJURIESImage: The Orthopaedic Robotics Laboratory
