Modulating hip stiffness with a robotic exoskeleton immediately changes gait
Name
ICRA20_0283_MS_Final.pdf
Description
Accepted version
Size
1.42 MB
Format
Adobe PDF
Checksum (MD5)
9e7ca9aff363d6e07ebc7c37bc53f5a9
Author(s)
Lee, Jongwoo
Warren, Haley R
Agarwal, Vibha
Huber, Meghan E
Hogan, Neville
Date Issued
2020
Journal
Proceedings - IEEE International Conference on Robotics and Automation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Lee, Jongwoo, Warren, Haley R, Agarwal, Vibha, Huber, Meghan E and Hogan, Neville. 2020. "Modulating hip stiffness with a robotic exoskeleton immediately changes gait." Proceedings - IEEE International Conference on Robotics and Automation.
Version
Author's final manuscript
Abstract
© 2020 IEEE. Restoring healthy kinematics is a critical component of assisting and rehabilitating impaired locomotion. Here we tested whether spatiotemporal gait patterns can be modulated by applying mechanical impedance to hip joints. Using the Samsung GEMS-H exoskeleton, we emulated a virtual spring (positive and negative) between the user's legs. We found that applying positive stiffness with the exoskeleton decreased stride time and hip range of motion for healthy subjects during treadmill walking. Conversely, the application of negative stiffness increased stride time and hip range of motion. These effects did not vary over long nor short repeated exposures to applied stiffness. In addition, minimal transient behavior was observed in spatiotemporal measures of gait when the stiffness controller transitioned between on and off states. These results suggest that changes in gait behavior induced by applying hip stiffness were purely a mechanical effect. Together, our findings indicate that applying mechanical impedance using lower-limb assistive devices may be an effective, minimally-encumbering intervention to restore healthy gait patterns.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICRA40945.2020.9197054
