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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...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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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. |
format | Online Article Text |
id | pubmed-5799707 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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