*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
M Wu
BME PhD Proposal Presentation
Date: 2023-03-09
Time: 10:00 am
Location / Meeting Link: Health Sciences Research Building, E382; https://emory.zoom.us/j/95029745884
Committee Members:
Lena Ting, PhD (Advisor); Jun Ueda, PhD; Gregory Sawicki, PhD; Madeleine Hackney, PhD; Trisha Kesar, PhD
Title: Low-force hand interactions to alter human walking
Abstract:
The motivation for this research is to develop intuitive low-force human-robot hand interaction controllers to alter how people walk. Such controllers have potential applications for assistive technology and physical rehabilitation, human-robot collaborative manufacturing, physical education, and recreation. This work is inspired by low-force hand interactions between humans that alter gait without explicit instructions or training. While concepts from human-human interactions can inspire human-robot interactions, the control strategies for modifying gait in human partners are not well understood and have yet to be tested in the context of hand-contact robotic devices. My central hypothesis is that low-force hand interactions in human-human and human-robot pairs alter gait intuitively without relying solely on mechanical effects. In Aim 1, I demonstrate that an expert partner dancer can use hand interactions to alter a novice’s step frequency and characterize the control strategies used. In Aim 2, I develop and validate a novel, high-fidelity emulator robot to enable testing of a variety of hand interaction controllers during gait, especially controllers based on human-human interactions. In Aim 3, I develop a novel robotic controller to alter the user’s gait and implement an admittance controller to follow the user’s intended gait, and compare effects of the controllers on walking using the emulator robot. I will analyze data on full-body kinematics, hand kinetics, and human sensorimotor ability and subjective perceptions to characterize changes to gait and the control strategies that result in these changes.
