Haptic Human-Human Interaction During an Ankle Tracking Task: Effects of
Virtual Connection Stiffness
Abstract
While treating sensorimotor impairments, a therapist may provide
physical assistance by guiding their patient’s limb to teach a desired
movement. In this scenario, a key aspect is the compliance of the
interaction, as the therapist can provide subtle cues or impose a
movement as demonstration. One approach to studying these interactions
involves haptically connecting two individuals through robotic
interfaces. Upper-limb studies have shown that pairs of connected
individuals estimate one another’s goals during tracking tasks by
exchanging haptic information, resulting in improved performance
dependent on the ability of one’s partner and the stiffness of the
virtual connection. In this study, our goal was to investigate whether
these findings generalize to the lower-limb during an ankle tracking
task. Pairs of healthy participants (i.e., dyads) independently tracked
target trajectories with and without connections rendered between two
ankle robots. We tested the effects of connection stiffness as well as
visual noise to manipulate the correlation of tracking errors between
partners. In our analysis, we compared changes in task performance
across conditions while tracking with and without the connection. We
found that tracking improvements while connected increased with
connection stiffness, favoring the worse partner in the dyad during hard
connections. We modeled the interaction as three springs in series,
considering the stiffness of the connection and each partners’ ankle, to
show that improvements were likely due to a cancellation of random
tracking errors between partners. These results suggest a simplified
mechanism of improvements compared to what has been reported during
upper-limb dyadic tracking.