During haptic communication, the central nervous system compensates distinctly for delay and noise

Connected humans have been previously shown to exploit the exchange of haptic forces and tactile information to improve their performance in joint action tasks. As human interactions are increasingly mediated through robots and networks it is important to understand the impact that network features such as lag and noise may have on human behaviour. In this paper, we investigated the interaction with a human-like robot controller that provides similar haptic communication behaviour as human-human interaction and examined the influence and compensation mechanisms for delay and noise on haptic communication. The results of our experiments show that participants can distinguish between noise and delay, and make use of compensation mechanisms to preserve performance in both cases. However, while noise is compensated for by increasing co-contraction, delay compensation could not be explained by this strategy. Instead, computational modelling suggested that a feed-forward prediction mechanism is used to compensate for the temporal delay and yield an efficient haptic communication. Author summary Increasingly humans are making use of networks and robots to coordinate haptic interactions through teleoperation. However, with networks comes delays and noise that can change both the force that is transmitted and how we perceive that force. The haptic communication involved in joint actions, such as moving a piano or performing a pair spin, has been shown to improve performance, but how does delay affect this behaviour? We tested how participants tracked a moving target with their right hand when connected to a human-like robotic partner, when perturbed by delay or noise. Through a comparison between noise and delay perturbation in experimental performance and in simulation with a computational model, we found that participants could from small values of perturbation identify if the perturbation was from delay or noise and that they adopted different compensation strategies in each case. ### Competing Interest Statement This work was supported in part by the EU H2020 grant ICT-871803 CONBOTS and by the UK EPSRC EP/R026092/1 FAIRSPACE program. There are no other competing interests