Real-Time 3D Tracker in Robot-Based Neurorehabilitation

The chapter describes a computer vision-based robot-assisted system used in neurorehabilitation of post-stroke patients that allows the subjects to reach for and grasp objects in a defined workspace. The proposed computer vision technique is used to model objects that have not been preprocessed in a real setting, track them in real time, and provide their actual pose to the robotic device in order to accomplish grasping tasks. The robotic device is composed of three integrated modules: (i) a 4-DOF arm exoskeleton that supports the patient's impaired arm when reaching for the objects; (ii) a 3-DOF actuated wrist exoskeleton for optimizing the hand pose in the grasping task; and (iii) a 2-DOF (flexion/extension) underactuated hand exoskeleton designed to be automatically adjusted for different grasping tasks based on contact forces. The conducted tests have demonstrated the robustness of the proposed approach, and its performance in the neurorehabilitation scenario through reaching and grasping task experiments.