A Method to Study Precision Grip Control in Viscoelastic Force Fields Using a Robotic Gripper

Instrumented objects and multipurpose haptic displays have commonly been used to investigate sensorimotor control of grasping and manipulation. A major limitation of these devices, however, is the extent to which the experimenter can vary the interaction dynamics to fully probe sensorimotor control mechanisms. We propose a novel method to study precision grip control using a grounded robotic gripper with two moving, mechanically coupled finger pads instrumented with force sensors. The device is capable of stably rendering virtual mechanical properties with a wide dynamic range of achievable impedances. Eight viscoelastic force fields with different combinations of stiffness and damping parameters were implemented, and tested on eight healthy subjects performing 30 consecutive repetitions of a grasp, hold, and release task with time and position constraints. Rates of thumb and finger force were found to be highly correlated (r>0.9) during grasping, revealing that, despite the mechanical coupling of the two finger pads, subjects performed grasping movements in a physiological fashion. Subjects quickly adapted to the virtual dynamics (within seven trials), but, depending on the presented force field condition, used different control strategies to correctly perform the task. The proof of principle presented in this paper underscores the potential of such a one-degree-of-freedom robotic gripper to study neural control of grasping, and to provide novel insights on sensorimotor control mechanisms.