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Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis

Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease. This update critically...

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Autores principales: Shanahan, Camille J., Boonstra, Frederique M. C., Cofré Lizama, L. Eduardo, Strik, Myrte, Moffat, Bradford A., Khan, Fary, Kilpatrick, Trevor J., van der Walt, Anneke, Galea, Mary P., Kolbe, Scott C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799707/
https://www.ncbi.nlm.nih.gov/pubmed/29449825
http://dx.doi.org/10.3389/fneur.2017.00708
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author Shanahan, Camille J.
Boonstra, Frederique M. C.
Cofré Lizama, L. Eduardo
Strik, Myrte
Moffat, Bradford A.
Khan, Fary
Kilpatrick, Trevor J.
van der Walt, Anneke
Galea, Mary P.
Kolbe, Scott C.
author_facet Shanahan, Camille J.
Boonstra, Frederique M. C.
Cofré Lizama, L. Eduardo
Strik, Myrte
Moffat, Bradford A.
Khan, Fary
Kilpatrick, Trevor J.
van der Walt, Anneke
Galea, Mary P.
Kolbe, Scott C.
author_sort Shanahan, Camille J.
collection PubMed
description Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease. This update critically evaluates advanced gait and balance analysis technologies and their applicability to identifying early lower limb dysfunction in people with MS. Non-wearable (motion capture systems, force platforms, and sensor-embedded walkways) and wearable (pressure and inertial sensors) biomechanical analysis systems have been developed to provide quantitative gait and balance assessments. Non-wearable systems are highly accurate, reliable and provide detailed outcomes, but require cumbersome and expensive equipment. Wearable systems provide less detail but can be used in community settings and can provide real-time feedback to patients and clinicians. Biomechanical analysis using advanced gait and balance analysis technologies can identify changes in gait and balance in early MS and consequently have the potential to significantly improve monitoring of mobility changes in MS.
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spelling pubmed-57997072018-02-15 Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis Shanahan, Camille J. Boonstra, Frederique M. C. Cofré Lizama, L. Eduardo Strik, Myrte Moffat, Bradford A. Khan, Fary Kilpatrick, Trevor J. van der Walt, Anneke Galea, Mary P. Kolbe, Scott C. Front Neurol Neuroscience Subtle gait and balance dysfunction is a precursor to loss of mobility in multiple sclerosis (MS). Biomechanical assessments using advanced gait and balance analysis technologies can identify these subtle changes and could be used to predict mobility loss early in the disease. This update critically evaluates advanced gait and balance analysis technologies and their applicability to identifying early lower limb dysfunction in people with MS. Non-wearable (motion capture systems, force platforms, and sensor-embedded walkways) and wearable (pressure and inertial sensors) biomechanical analysis systems have been developed to provide quantitative gait and balance assessments. Non-wearable systems are highly accurate, reliable and provide detailed outcomes, but require cumbersome and expensive equipment. Wearable systems provide less detail but can be used in community settings and can provide real-time feedback to patients and clinicians. Biomechanical analysis using advanced gait and balance analysis technologies can identify changes in gait and balance in early MS and consequently have the potential to significantly improve monitoring of mobility changes in MS. Frontiers Media S.A. 2018-02-02 /pmc/articles/PMC5799707/ /pubmed/29449825 http://dx.doi.org/10.3389/fneur.2017.00708 Text en Copyright © 2018 Shanahan, Boonstra, Cofré Lizama, Strik, Moffat, Khan, Kilpatrick, van der Walt, Galea and Kolbe. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Shanahan, Camille J.
Boonstra, Frederique M. C.
Cofré Lizama, L. Eduardo
Strik, Myrte
Moffat, Bradford A.
Khan, Fary
Kilpatrick, Trevor J.
van der Walt, Anneke
Galea, Mary P.
Kolbe, Scott C.
Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis
title Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis
title_full Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis
title_fullStr Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis
title_full_unstemmed Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis
title_short Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis
title_sort technologies for advanced gait and balance assessments in people with multiple sclerosis
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799707/
https://www.ncbi.nlm.nih.gov/pubmed/29449825
http://dx.doi.org/10.3389/fneur.2017.00708
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