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

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.