Abstract/Details

Principles of motor adaptation when walking with a powered exoskeleton


2009 2009

Other formats: Order a copy

Abstract (summary)

Robotic exoskeletons are currently developed to augment human motor performance or assist in the gait rehabilitation of individuals with neurological injuries. While the robotic technology is rapidly advancing, there is a large gap in our understanding of how humans respond to exoskeleton assistance during locomotion. To build successful robotic devices, it is critical to understand the principles governing mechanical human-machine interaction. In this dissertation, I used lightweight ankle exoskeletons powered by artificial pneumatic muscles to provide mechanical assistance to neurologically intact human subjects. The exoskeletons allowed me to investigate some general principles of motor adaptation in human walking. In the first experiment, an exoskeleton provided subjects with increased dorsiflexor torque. The results demonstrated that there are different adaptation responses for the type bursts of tibialis anterior recruitment during walking. In the second experiment, an exoskeleton provided plantar flexor torque with two artificial pneumatic muscles, increasing the exoskeleton mechanical output compared to past studies. With this assistance, subjects rapidly decreased soleus recruitment to walk with a total ankle moment pattern similar to unassisted gait. However, subjects adapted at a slower rate for the stronger exoskeleton. In the third experiment, I quantified soleus monosynaptic reflex responses to determine if reflex inhibition is one of the mechanisms for reducing soleus recruitment during robotic-assisted walking. Subjects demonstrated similar soleus H-reflex amplitudes corresponding to background muscle activation during powered versus unpowered walking. This indicates the reflex gain is not modified during short-term adaptation to the robotic exoskeleton. In the final experiment, I used the exoskeleton as a tool to quantify the mechanical output of plantar flexor reflex responses during perturbed gait. I introduced a perturbation by turning off the robotic assistance unexpectedly in midstance. During the perturbed steps, subjects greatly increased muscle activation to maintain total ankle moment patterns similar to unperturbed steps. Overall these studies demonstrated that the nervous system prioritizes a given ankle joint moment pattern during human walking, both with robotic assistance and when encountering gait perturbations. The combined results of these experiments will help guide the design of future robotic devices and could lead to better strategies for robotic-assisted gait rehabilitation.

Indexing (details)


Subject
Physical therapy;
Robotics
Classification
0382: Physical therapy
0771: Robotics
Identifier / keyword
Health and environmental sciences; Applied sciences; Exoskeleton; Gait rehabilitation; Human walking; Inverse dynamics; Locomotion
Title
Principles of motor adaptation when walking with a powered exoskeleton
Author
Kao, Pei-Chun
Number of pages
108
Publication year
2009
Degree date
2009
School code
0127
Source
DAI-B 70/10, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9781109439038
Advisor
Ferris, Daniel P.
University/institution
University of Michigan
University location
United States -- Michigan
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3382231
ProQuest document ID
304934046
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/304934046
Access the complete full text

You can get the full text of this document if it is part of your institution's ProQuest subscription.

Try one of the following:

  • Connect to ProQuest through your library network and search for the document from there.
  • Request the document from your library.
  • Go to the ProQuest login page and enter a ProQuest or My Research username / password.