Abstract
Designing the physical coupling between the human body and the wearable robot is a challenging endeavor. The typical approach of tightening the wearable robot against the body, and softening the interface materials does not work well. It makes the task of simultaneously improving comfort, and anchoring the robot to the body at the physical human robot interaction interface (PHRII), difficult. Characterizing this behavior experimentally with sensors at the interface is challenging due to the soft-soft interactions between the PHRII materials and the human tissue. Therefore, modeling the interaction between the wearable robot and the hand is a necessary step to improve design. In this paper, we introduce a methodology to systematically improve the design of the PHRII by combining experimentally measured characteristics of the biological tissue with a novel dynamic modeling tool. Using a novel and scalable simulation framework, HuRoSim, we quantified the interaction between the human hand and an exoskeleton. In the first of our experiments, we use HuRoSim to predict complex interactions between the hand and the coupled exoskeleton. In our second experiment, we then demonstrate how HuRoSim can be coupled with experimental measurements of the stiffness of the dorsal surface of the hand to optimize the design of the PHRII. This approach of data-driven modeling of the interaction between the body and a wearable robot, such as a hand exoskeleton, can be generalized to other forms of wearable devices as well, demonstrating a scalable and systematic method for improving the design of the PHRII for future devices coupled to the body.