The role of user preference in the customized control of robotic exoskeletons: Supplementary dataset

This dataset accompanies the following manuscript submitted to Science Robotics: "The role of user preference in the customized control of robotic exoskeletons" (In Review)<br><strong>Abstract: </strong>User preference is a promising objective for the control of robotic exoskeletons since it may capture the multifactorial nature of exoskeleton use. However, to utilize it, we must first understand its characteristics in the context of exoskeleton control. Here, we systematically measure the control preferences of individuals wearing bilateral ankle exoskeletons during walking. We investigate users’ repeatability identifying their preferences and how preference changes with walking speed, device exposure, and between individuals with different technical backgrounds. Twelve naive and twelve knowledgeable non-disabled participants identified their preferred assistance in repeated trials by simultaneously self-tuning the magnitude and timing of peak torque. They were blinded to the control parameters and relied solely on their perception of the assistance to guide their tuning. We found that participants’ preferences ranged from 7.9-19.4 Newton-meters and 54.1-59.2 percent of the gait cycle. Across trials, participants repeatably identified their preferences with a mean standard deviation of 1.7 Newton-meters and 1.5 percent of the gait cycle. Within a trial, participants converged on their preference in 105 seconds. As the experiment progressed, naive users preferred higher torque magnitude. At faster walking speeds, these individuals were more precise at identifying the magnitude of their preferred assistance. Knowledgeable users preferred higher torque than naive users. These results highlight that although preference is a dynamic quantity, individuals can reliably identify their preferences. This work motivates strategies for the control of lower-limb exoskeletons in which individuals customize assistance according to their unique preferences and provides meaningful insight into how users interact with exoskeletons.