Statistical and soft-computing techniques for the prediction of upper arm articular synergies

Abstract

The feasibility of predicting elbow position from shoulder angular trajectories during pointing movements was analyzed. Aiming to achieve this result a hybrid strategy (composed of statistical and soft computing algorithms) was developed. Using a statistical procedure we first clustered the different trajectories and then a neuro-fuzzy system was trained for each group. The results show the feasibility of this approach in terms of mean errors in the prediction of the elbow velocity and position.