Linked Life Data

17123206

Source:http://linkedlifedata.com/resource/pubmed/id/17123206

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2006-11-23
pubmed:abstractText
This article reviews several tools we have developed to improve the understanding of locomotor training following spinal cord injury (SCI), with a view toward implementing locomotor training with robotic devices. We have developed (1) a small-scale robotic device that allows testing of locomotor training techniques in rodent models, (2) an instrumentation system that measures the forces and motions used by experienced human therapists as they manually assist leg movement during locomotor training, (3) a powerful, lightweight leg robot that allows investigation of motor adaptation during stepping in response to force-field perturbations, and (4) computational models for locomotor training. Results from the initial use of these tools suggest that an optimal gait-training robot will minimize disruptive sensory input, facilitate appropriate sensory input and gait mechanics, and intelligently grade and time its assistance. Currently, we are developing a pneumatic robot designed to meet these specifications as it assists leg and pelvic motion of people with SCI.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1938-1352
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
43
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
657-70
pubmed:dateRevised
2009-5-5
pubmed:meshHeading
pubmed:articleTitle
Tools for understanding and optimizing robotic gait training.
pubmed:affiliation
Department of Mechanical and Aerospace Engineering, University of California (UC) Irvine, Irvine, CA 92697-3975, USA. dreinken@uci.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Review, Research Support, N.I.H., Extramural