Proprioceptive Motion Feedback and User-Selectable Impedance for Improved Upper-Limb Prosthesis Control

earthblurtingAI and Robotics

Nov 14, 2013 (3 years and 10 months ago)

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M
IME

FACULTY CANDIDATE

SE
MINAR


WINTER 2013

Proprioceptive Motion Feedback and User
-
Selectable
Impedance for Improved Upper
-
Limb
Prosthesis Control

By
Dr. Amy Blank

Laboratory for Computational Sensing and Robotics

John Hopkins University

Abstract

Humans

can use their arms to interact dexterously and dynamically with a wide range of environments.
Present
-
day prosthetic arms have the physical capability to reproduce complex human motions, but their
user feedback and control systems do not allow users to co
ntrol their movement with the same ease and
grace as natural human arms. This work addresses two important aspects of human arm control that are
currently not matched in prosthesis control: proprioceptive motion feedback (sensory feedback about the
positio
n and motion of one’s limbs) and impedance modulation (the ability to change the relationship
between external forces applied to the limb and the resulting limb motion). The goal of this work is to identify
design requirements for proprioceptive motion fee
dback and user
-
selectable impedance in prosthetic limbs.
Toward this end, we developed virtual and actual robotic systems simulating prosthetic arm control, and we
performed able
-
bodied human subject studies in which we explored the potential benefits of p
roprioceptive
motion feedback and user
-
selectable impedance for prosthesis use. The study of proprioceptive motion
feedback showed that proprioceptive motion feedback improves targeting accuracy both with and without
visual feedback. Furthermore, this stud
y quantified performance with able
-
bodied users' real proprioceptive
motion feedback, providing a baseline for comparison of future artificial proprioceptive systems. The studies
of user
-
selectable impedance showed that task
-
dependent impedance improves us
er performance and that
users can understand and quantify these changes in performance to a significant extent with both the virtual
prosthesis and the robot. These studies also identified several factors that would affect subjects' ability to
modulate pro
sthesis impedance, including feedback scaling, training, and compensating for non
-
ideal
characteristics of a physical system. The results reported herein inform the future design of artificial
proprioceptive systems and user
-
selectable impedance systems fo
r prosthetic arms to improve user
performance in a variety of manipulation and interaction tasks.

Speaker’s Brief Biography

Amy Blank completed B.S. degrees in Mechanical Engineering and Electrical Engineering at the
Pennsylvania State University and M.S.E. and Ph.D. degrees in Mechanical Engineering the Johns Hopkins
University, where she is currently working as a postdoctora
l researcher. Her research interests are in theory
and application for design, modeling, and control of robotic manipulators and human
-
robot interaction.
Specific areas of interest include biologically inspired robotic sensing and control strategies, varia
ble
-
impedance robot control, upper
-
limb prosthetics and rehabilitation, and user feedback for prosthesis control
and teleoperation.

Monday
,
February 25, 2013

2
:0
0


3
:00
PM
,

Covell 117 (MIME Library)



School of
Mechanical
,
Industrial
,

& Manufacturing Engineering