Literature DB >> 23153835

Gait variability and disability in multiple sclerosis.

Michael J Socie1, Robert W Motl, John H Pula, Brian M Sandroff, Jacob J Sosnoff.   

Abstract

Gait variability is clinically relevant in some populations, but there is limited documentation of gait variability in persons with multiple sclerosis (MS). This investigation examined average and variability of spatiotemporal gait parameters in persons with MS and healthy controls and subsequent associations with disability status. 88 individuals with MS (age 52.4±11.1) and 20 healthy controls (age 50.9±8.7) performed two self-paced walking trials on a 7.9-m electronic walkway to determine gait parameters. Disability was indexed by the Expanded Disability Status Scale (EDSS) and ranged between 2.5 and 6.5. Gait variability was indexed by standard deviation (SD) and coefficient of variation (CV=SD/mean) of step time, step length, and step width. Average gait parameters were significantly correlated with EDSS (ρ=0.756-0.609) and were significantly different in individuals with MS compared to controls (p≤0.002). Also, step length (p<0.001) and step time (p<0.001) variability were both significantly greater in MS compared to controls. EDSS was positively correlated with step length variability and individuals with MS who used assistive devices to walk had significantly greater step length variability than those who walked independently (p's<.05). EDSS was correlated with step time and length variability even when age was taken into account. Additionally, Fisher's z test of partial correlations revealed that average gait parameters were more closely related to disability status than gait variability in individuals with MS. This suggests that focusing on average gait parameters may be more important than variability in therapeutic interventions in MS.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 23153835     DOI: 10.1016/j.gaitpost.2012.10.012

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  18 in total

Review 1.  Next Steps in Wearable Technology and Community Ambulation in Multiple Sclerosis.

Authors:  Mikaela L Frechette; Brett M Meyer; Lindsey J Tulipani; Reed D Gurchiek; Ryan S McGinnis; Jacob J Sosnoff
Journal:  Curr Neurol Neurosci Rep       Date:  2019-09-04       Impact factor: 5.081

2.  Machine learning classification of multiple sclerosis patients based on raw data from an instrumented walkway.

Authors:  Wenting Hu; Owen Combden; Xianta Jiang; Syamala Buragadda; Caitlin J Newell; Maria C Williams; Amber L Critch; Michelle Ploughman
Journal:  Biomed Eng Online       Date:  2022-03-30       Impact factor: 2.819

3.  Measurement of foot placement and its variability with inertial sensors.

Authors:  John R Rebula; Lauro V Ojeda; Peter G Adamczyk; Arthur D Kuo
Journal:  Gait Posture       Date:  2013-06-26       Impact factor: 2.840

4.  Cognition is associated with gait variability in individuals with multiple sclerosis.

Authors:  Katherine L Hsieh; Ruopeng Sun; Jacob J Sosnoff
Journal:  J Neural Transm (Vienna)       Date:  2017-10-25       Impact factor: 3.575

5.  Effects of Treadmill Training on Muscle Oxidative Capacity and Endurance in People with Multiple Sclerosis with Significant Walking Limitations.

Authors:  T Bradley Willingham; Jonathan Melbourn; Marina Moldavskiy; Kevin K McCully; Deborah Backus
Journal:  Int J MS Care       Date:  2019 Jul-Aug

6.  Spatial and temporal characteristics of gait as outcome measures in multiple sclerosis (EDSS 0 to 6.5).

Authors:  Jana Lizrova Preiningerova; Klara Novotna; Jan Rusz; Lucie Sucha; Evzen Ruzicka; Eva Havrdova
Journal:  J Neuroeng Rehabil       Date:  2015-02-10       Impact factor: 4.262

7.  Gait variability and multiple sclerosis.

Authors:  Michael J Socie; Jacob J Sosnoff
Journal:  Mult Scler Int       Date:  2013-03-03

8.  Stride-Time Variability and Fall Risk in Persons with Multiple Sclerosis.

Authors:  Yaejin Moon; Douglas A Wajda; Robert W Motl; Jacob J Sosnoff
Journal:  Mult Scler Int       Date:  2015-12-30

9.  Coactivation of Lower Limb Muscles during Gait in Patients with Multiple Sclerosis.

Authors:  Julien Boudarham; Sophie Hameau; Raphael Zory; Alexandre Hardy; Djamel Bensmail; Nicolas Roche
Journal:  PLoS One       Date:  2016-06-23       Impact factor: 3.240

10.  A novel accelerometry-based algorithm for the detection of step durations over short episodes of gait in healthy elderly.

Authors:  M Encarna Micó-Amigo; Idsart Kingma; Erik Ainsworth; Stefan Walgaard; Martijn Niessen; Rob C van Lummel; Jaap H van Dieën
Journal:  J Neuroeng Rehabil       Date:  2016-04-19       Impact factor: 4.262

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