Comparing Two Computational Mechanisms for Explaining Functional Recovery in Robot-Therapy of Stroke Survivors

In this paper we discuss two possible strategies of movement control that can be used by stroke survivors during rehabilitation robotics training. To perform a reaching task in a minimally assistive force field, subjects either can move following the trajectory provided by the assistive force or they can use an internal representation of a minimum jerk trajectory from their starting position to the target. We used the stiffness and damping values directly estimated from the experimental data to simulate the trajectories that result by taking into account both hypotheses. The comparison of the simulated results with the data collected on four hemiparetic subjects supports the hypothesis that the central nervous system (CNS) is still able to correctly plan the movement, although a normal execution is impaired.