Analyzing Knee Kinematics after Anterior Cruciate Ligament Reconstruction Using Fuzzy Logic

Abstract

Rupture of anterior cruciate ligament (ACL) is a serious problem on playing sports, and may cause knee pain or hemarthrosis. To restore the damaged ACL, many ACL reconstruction operations have been proposed. Therefore, analyzing the knee kinematics after ACL reconstruction is important to evaluate the ACL reconstruction operations and to improve them. However, few methods for quantitatively analyzing the three-dimensional knee motions have been proposed. Many methods of analyzing knee motions have used the image matching. However, the target images are always clearly, that has many noises, artifacts of metals and overlap of bones. The accuracy of image matching is heavily dependent on the quality of image. Then, we should perform the image denoising. In this paper, we propose a fuzzy image matching for analyzing knee kinematics after ACL reconstructions. To introduce the fuzzy logic to the image matching in our proposed method, may improve the accuracy of image matching.