Grasp Coordination in Virtual Environments for Robot-aided Upper Extremity Rehabilitation

This paper explores grasping in robot-aided upper extremity rehabilitation, with a special focus on reaching and grasping exercises and the coordination between load force and grasp force. Six healthy subjects and two hemiparetic subjects performed \pick and place"movements with a haptic robot and virtual environment. These movements were segmented into three phases: grasping, transport and release phase, and the correlation between grasp and load force was calculated over the entire movement and within each phase separately. Results show that the subjects employ same basic mechanism of grasp and load force coordination during a virtual task as in real situations. However, the grasp and load force are partially decoupled due to the nature of the grasping device and the complexity of the task. Furthermore, the coordination is different in different phases and also depends on the level of impairment as well as the level of active support by the rehabilitation robot. The first hemiparetic subject, who can perform reaching movements but cannot open the hand, thus has a lower correlation between grasp force and load force than healthy subjects only in the release phase while the second hemiparetic subject, who has little arm mobility, has a lower correlation in all three phases. Thus, the current work provides basic empirical knowledge that can serve as a basis for future research and for the design of robot-aided reaching and grasping tasks.