A Framework for Dyadic Physical Interaction Studies During Ankle Motor Tasks
| Autor: | Levi J. Hargrove, Yue Wen, Sangjoon Jonathan Kim, Shaobo Zhan, Kevin M. Lynch, Eric J. Perreault, Emek Bars Kucuktabak, Jose L Pons |
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| Rok vydání: | 2021 |
| Předmět: |
Control and Optimization
Computer science Mechanical Engineering Biomedical Engineering Transparency (human–computer interaction) Computer Science Applications Rendering (computer graphics) Human-Computer Interaction Range (mathematics) Sine wave Experimental system Artificial Intelligence Control and Systems Engineering Human–computer interaction Trajectory Task analysis Robot Computer Vision and Pattern Recognition |
| Zdroj: | IEEE Robotics and Automation Letters. 6:6876-6883 |
| ISSN: | 2377-3774 |
| Popis: | Over the past few decades, there have been many studies of human-human physical interaction to better understand why humans physically interact so effectively and how dyads outperform individuals in certain motor tasks. Because of the different methodologies and experimental setups in these studies, however, it is difficult to draw general conclusions as to the reasons for this improved performance. In this study, we propose an open-source experimental system for the systematic study of the effect of human-human interaction, as mediated by robots, at the ankle joint. We also propose a new framework to study various interactive behaviors (i.e., collaborative, cooperative, and competitive tasks) that can be emulated using a virtual spring connecting human pairs. To validate the proposed experimental framework, we perform a transparency analysis, which is closely related to haptic rendering performance. We compare muscle EMG and ankle motion data while subjects are barefoot, attached to the unpowered robot, and attached to the powered robot implementing transparency control. We also validate the performance in rendering virtual springs covering a range of stiffness values (5–50 Nm/rad) while the subjects track several desired trajectories (sine waves at frequencies between 0.1 and 1.1 Hz). Finally, we demonstrate the feasibility of the system in studying human-human interaction under different interactive behaviors. |
| Databáze: | OpenAIRE |
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