Linked Life Data

19566269

Source:http://linkedlifedata.com/resource/pubmed/id/19566269

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2009-7-1
pubmed:abstractText
Regularity statistics have been previously applied to walking gait measures in the hope of gaining insight into the complexity of gait under different conditions and in different populations. Traditional regularity statistics are subject to the requirement of stationarity, a limitation for examining changes in complexity under dynamic conditions such as exhaustive exercise. Using a novel measure, control entropy (CE), applied to triaxial continuous accelerometry, we report changes in complexity of walking and running during increasing speeds up to exhaustion in highly trained runners. We further apply Karhunen-Loeve analysis in a new and novel way to the patterns of CE responses in each of the three axes to identify dominant modes of CE responses in the vertical, mediolateral, and anterior/posterior planes. The differential CE responses observed between the different axes in this select population provide insight into the constraints of walking and running in those who may have optimized locomotion. Future comparisons between athletes, healthy untrained, and clinical populations using this approach may help elucidate differences between optimized and diseased locomotor control.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1089-7682
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
19
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
026109
pubmed:meshHeading
pubmed:year
2009
pubmed:articleTitle
Control entropy identifies differential changes in complexity of walking and running gait patterns with increasing speed in highly trained runners.
pubmed:affiliation
Applied Physiology Laboratory, Eastern Michigan University, Ypsilanti, Michigan 48197, USA.
pubmed:publicationType
Journal Article