An innovative approach toward gait feature detection in children with cp

INTRODUCTION and AIM Classifying gait patterns in children with cerebral palsy (CP) and reducing the vast amount of data from gait analysis into a set of clinically relevant gait features remains a challenge [1]. A priori selection of gait features, often based on clinical expert knowledge, can result in either incomplete or redundant data [2]. The goal is to quantify differences in lower limb kinematics between CP children and typically developing controls using principal component analysis (PCA). Secondly, for features that differ between CP and controls, a discriminant analysis (DA) will be applied to determine which features discriminate best between both groups.