Detecting dynamical boundaries from kinematic data in biomechanics

Simple item page
dc.contributorVirginia Techen
dc.contributor.authorRoss, Shane D.en
dc.contributor.authorTanaka, M. L.en
dc.contributor.authorSenatore, C.en
dc.contributor.departmentBiomedical Engineering and Mechanicsen
dc.date.accessed2013-11-20en
dc.date.accessioned2013-12-04T15:20:24Zen
dc.date.available2013-12-04T15:20:24Zen
dc.date.issued2010-03-01en
dc.description.abstractRidges in the state space distribution of finite-time Lyapunov exponents can be used to locate dynamical boundaries. We describe a method for obtaining dynamical boundaries using only trajectories reconstructed from time series, expanding on the current approach which requires a vector field in the phase space. We analyze problems in musculoskeletal biomechanics, considered as exemplars of a class of experimental systems that contain separatrix features. Particular focus is given to postural control and balance, considering both models and experimental data. Our success in determining the boundary between recovery and failure in human balance activities suggests this approach will provide new robust stability measures, as well as measures of fall risk, that currently are not available and may have benefits for the analysis and prevention of low back pain and falls leading to injury, both of which affect a significant portion of the population.en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRoss, Shane D. and Tanaka, Martin L. and Senatore, Carmine, “Detecting dynamical boundaries from kinematic data in biomechanics,” Chaos 20, 017507 (2010), DOI:http://dx.doi.org/10.1063/1.3267043en
dc.identifier.doihttps://doi.org/10.1063/1.3267043en
dc.identifier.issn1054-1500en
dc.identifier.urihttp://hdl.handle.net/10919/24408en
dc.identifier.urlhttp://scitation.aip.org/content/aip/journal/chaos/20/1/10.1063/1.3267043en
dc.language.isoen_USen
dc.publisherAmerican Institute of Physicsen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectLagrangian coherent structuresen
dc.subjectLow-back-painen
dc.subjectAnkle muscle-stiffnessen
dc.subjectTime-series analysisen
dc.subjectLyapunov exponentsen
dc.subjectPostural controlen
dc.subject2-dimensional turbulenceen
dc.subjectInvariant manifoldsen
dc.subjectBalance lossen
dc.subjectStabilityen
dc.titleDetecting dynamical boundaries from kinematic data in biomechanicsen
dc.title.serialChaosen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
1.3267043.pdf
Size:
1.68 MB
Format:
Adobe Portable Document Format
Description:
Main article
Download

Collections

Scholarly Works, Biomedical Engineering and Mechanics