Robot-Assisted Study of Finger Impedance Differentiation in Humans

Abstract Rendering internal impedances is key for developing immersive experiences in virtual reality. While previous research has primarily focused on the rendering of external impedances, rendering changes to the avatar remains an open question. Changes to the avatar are particularly salient for disease education and fostering empathy in healthcare professionals in conditions such as rheumatoid arthritis. As a first step toward this immersive experience, this study explores whether humans can distinguish between joint and endpoint impedances. We developed a novel robotic system stiffness emulation robot and a new controller for an existing haptics glove, and conducted a binary discretion experiment which reveals that the majority of subjects can differentiate the two impedance types.