Publication Details
Overview
 
 
Nicolas Van Vlasselaer, Nicolas Van Vlasselaer, Nicolas Van Vlasselaer, Luca Buzzatti, Luca Buzzatti, Luca Buzzatti, Benyameen Keelson, Benyameen Keelson, Benyameen Keelson, Erik Cattrysse, Erik Cattrysse, Erik Cattrysse
 

Unpublished contribution to conference

Abstract ■

4DCT and derivative-based functional data clustering were used to identify distinct patterns of tibiofemoral joint rotation. The approach employed a combination of first derivatives of the rotational motion, functional principal component analysis, and k-means clustering to classify rotational patterns. The method revealed meaningful kinematic variations in healthy knees by focusing on motion trends rather than amplitude. These findings provide a novel framework for assessing pathological deviations, offering potential improvements in diagnostic and therapeutic strategies.

Reference ■