TY - JOUR
T1 - Technologies for Advanced Gait and Balance Assessments in People with Multiple Sclerosis
AU - Shanahan, Camille J.
AU - Boonstra, Frederique M. C.
AU - Cofré Lizama, L. Eduardo
AU - Strik, Myrte
AU - Moffat, Bradford A.
AU - Khan, Fary
AU - Kilpatrick, Trevor J.
AU - van der Walt, Anneke
AU - Galea, Mary P.
AU - Kolbe, Scott C.
PY - 2018/2/2
Y1 - 2018/2/2
N2 - 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.
AB - 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.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85117722600&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/29449825
U2 - https://doi.org/10.3389/fneur.2017.00708
DO - https://doi.org/10.3389/fneur.2017.00708
M3 - Review article
C2 - 29449825
SN - 1664-2295
VL - 8
JO - Frontiers in Neurology
JF - Frontiers in Neurology
M1 - 708
ER -