Functional Data Analysis for Gait Analysis after Stroke

Variability is one of the key determinants of gait after stroke. Functional Data Analysis (FDA) is a suitable tool to deal with variability associated with movement analysis patterns. In this contribution (FDA) has been applied for the analysis 53 post-stroke patients. Functional Principal Components Analysis (FPCA) has been applied. Dependence of velocity on the functional state of the patient has been found as well as other mechanisms that are hidden in conventional parametric analysis of the curves.