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.

Optimizing skill acquisition during novel motor tasks and (re)learning lost motor functions have been the interest of many researchers over the past few decades. One approach shown to accelerate motor learning is haptically coupling two individuals through robotic interfaces. Studies have shown that an individual’s solo performance of upper-limb tracking tasks may improve after haptically coupled training with a partner. In this study, our goal was to investigate whether these findings can be translated to lower-limb motor tasks, more specifically, during an ankle position tracking task. Using one-degree-of-freedom ankle  movements, pairs of participants (i.e., dyads) tracked target trajectories while intermittently coupled through a virtual spring rendered between two ankle rehabilitation robots. We compared changes in task performance across trials while training with and without haptic coupling. We found that dyadic haptic coupling did not lead to faster individual learning of the tracking task. Dyadic task performance (i.e., tracking performance while haptically coupled) improved during haptic coupling, likely due to averaging of errors of the dyadic pair during tracking. These results suggest that haptic coupling between unimpaired individuals may not be an effective method of training ankle movements during a simple one-degree-of-freedom task.