A Stereo Vision Approach for Cooperative Robotic Movement Therapy

Movement therapy is an integrating part of stroke rehabilitation. The positive influence of intensive, repetitive motion training and the importance of active patient participation trigger the development of cooperative robotic assistants. We suggest a device for the re-education of upper limb movements in hemiparetic patients where a light-weight robotic arm that supports the deficient arm is equipped with a stereoscopic camera system. It follows the movements of the healthy arm that wears a sleeve equipped with flat round reflective markers detected by the cameras. We introduce an advanced robust and real-time algorithm to provide the tracking information. It performs a sparse marker based point cloud registration based on subpixel precision contour fits to enable high accuracy pose estimates while being capable of online model adjustments. The update rate of the tracking is 9 ms and the precision of the system is measured to be 0.5 mm. Tests with healthy subjects show that the system is able to accurately reproduce the movement of the healthy arm on an impaired arm.