Haptic communication between humans is tuned by the hard or soft mechanics of interaction

To move a hard table together, humans may coordinate by following the dominant partner’s motion [1–4], but this strategy is unsuitable for a soft mattress where the perceived forces are small. How do partners readily coordinate in such differing interaction dynamics? To address this, we investigated how pairs tracked a target using flexion-extension of their wrists, which were coupled by a hard, medium or soft virtual elastic band. Tracking performance monotonically increased with a stiffer band for the worse partner, who had higher tracking error, at the cost of the skilled partner’s muscular effort. This suggests that the worse partner followed the skilled one’s lead, but simulations show that the results are better explained by a model where partners share movement goals through the forces, whilst the coupling dynamics determine the capacity of communicable information. This model elucidates the versatile mechanism by which humans can coordinate during both hard and soft physical interactions to ensure maximum performance with minimal effort.Author summary: Humans are talented at coordinating movements with one another through a multitude of objects such as a hard table or a soft mattress. Depending on the softness of the object, the force we perceive from the partner can be strong enough to sense directional cues, or could be too weak to understand the partner’s movement intention. How do we coordinate physical movements governed by such differing mechanics? Our task is inspired by a pair moving through a dancefloor during Tango dancing; we tested subjects in pairs who jointly chased a moving target with their right hands, which were banded together by either a strong, medium or weak elastic band. By measuring the change in each partner’s performance at the task, and the muscular effort they exerted, we characterized the changes in each partner’s behavior as a function of the strength of the elastic band that coupled them together. By employing a computational simulation of the task, we tested different coordination mechanisms to see what explained the data best. We found that, regardless of the coupling strength, each subject infers the movement intention of their partner, but this process deteriorates with softer coupling.