TY - JOUR
T1 - A Framework for Dyadic Physical Interaction Studies during Ankle Motor Tasks
AU - Kim, Sangjoon J.
AU - Wen, Yue
AU - Kucuktabak, Emek Bars
AU - Zhan, Shaobo
AU - Lynch, Kevin
AU - Hargrove, Levi
AU - Perreault, Eric J.
AU - Pons, Jose L.
N1 - Funding Information:
Manuscript received February 24, 2021; accepted June 14, 2021. Date of publication June 24, 2021; date of current version July 26, 2021. This work was supported by the National Science Foundation/National Robotics Initiative under Grant 2024488 and the Turkish Fulbright Commission. This letter was recommended for publication by Associate Editor A. González and Editor G. Venture upon evaluation of the reviewers’ comments. (Sangjoon J. Kim and Yue Wen contributed equally to the work). (Corresponding author: Jose L. Pons.) Sangjoon J. Kim and Yue Wen are with the Legs and Walking Lab of Shirley Ryan AbilityLab and the Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611 USA (e-mail: [email protected]; [email protected]).
Publisher Copyright:
© 2016 IEEE.
PY - 2021/10
Y1 - 2021/10
N2 - 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.
AB - 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.
KW - Physical human-robot interaction
KW - haptics and haptic interfaces
KW - human factors and human-in-The-loop
KW - human-robot teaming
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U2 - 10.1109/LRA.2021.3092265
DO - 10.1109/LRA.2021.3092265
M3 - Article
AN - SCOPUS:85111765173
SN - 2377-3766
VL - 6
SP - 6876
EP - 6883
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 4
M1 - 9464715
ER -