Juan Manuel Belda Lois

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.

A Biomechanical Model for Pathological Tremor Suppression

There are increasing evidences that pathological tremor can be compensated by mechanical means, however any device for tremor suppression by mechanical loading is subject to a number of constrain: the soft tissues, the mechanical impedance of human joints as well as the interactions with the human motor control. Values to quantified all three aspects have been obtained and are consistent with the previous existing knowledge. Results obtained are useful for the design of new tremor suppression strategies.