Pattern classification of terrain during amputee walking
Name
862818607-MIT.pdf
Description
Full printable version
Size
8.75 MB
Format
Adobe PDF
Checksum (MD5)
3dc13887a73a15cb13f30e48dc3bfc67
Author(s)
Farrell, Matthew Todd
Advisor(s)
Hugh Herr.
Date Issued
2013
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis I study the role of extrinsic (sensors placed on the body) versus intrinsic sensing (instruments placed on an artificial limb) and determine a robust set of sensors from physical and reliability constraints for a terrain adaptation in a robotic ankle prosthesis. Further, during this thesis I collect a novel data-set that contains seven able-bodied participants walking over 19 terrain transitions and 7 non-amputees walking over 9 transitions, forming the largest collection of transitions to date using an exhaustive set of sensors: inertial measurement units, gyroscopes, kinematics from motion capture, and electromyography from 16 sites on the lower limbs for non-amputee subjects and 9 sites or amputee subjects. This work extends previous work [3] by using more conditions, a larger subject group, and more sensors on amputees, and includes non-amputees.I present a novel machine learning algorithm that uses sensor data during rapid transitions from pre-foothold to just prior to post-foothold to predict different terrain boundaries. This advances the field of biomechatronics, our understanding of terrain adaptation in people both with and without amputations, contributes to the development of a fully terrain adaptive robotic ankle prosthesis, and improves the quality of life for the physically challenged. Specifically we set out to prove between pre and post-foothold the ankle and knee positions calculated using an IMU attached to an amputees powered prosthetic ankle can discriminate with greater than 99% accuracy between 9 conditions. Our results suggest that myography as a non-volitional sensing modality for terrain adaptive prostheses was not needed.
Description
Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 113-116).
Subjects
Architecture. Program in Media Arts and Sciences.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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