A new Kinect-based guidance mode for upper limb robot-aided neurorehabilitation

During typical robot-assisted training sessions, patients are required to execute tasks with the assistance of a robot while receiving feedback on a 2D display. Three-dimensional tasks of this sort require the adoption of stereoscopy to achieve correct visuo-motor-proprioceptive alignment. Stereoscopy often causes side-effects as sickness and tiredness, and it may affect the processes of recovery and cortical reorganization of the patients´ brain in an unclear way. It follows that it is preferrable for a robot-assisted neurorehabilitation therapy to work in a real 3D setup containing real objects rather than using virtual reality. In this paper, we propose a new system for robot-assisted neurorehabilitation scenarios which allows patients to execute therapy by manipulating real, generic 3D objects. The proposed system is based on a new algorithm for identification and tracking of generic objects which makes efficient use of a Microsoft Kinect sensor. We discuss the results of several experiments conducted in order to test robustness, accuracy and speed of the tracking algorithm and the feasibility of the integrated system.