The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis

Abstract People with multiple sclerosis (PwMS) demonstrate gait impairments that are related to falls. However, redundancy exists when reporting gait outcomes. This study aimed to develop an MS-specific model of gait and examine differences between fallers and non-fallers. 122 people with relapsing–...

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Autores principales:	Andrew S. Monaghan, Jessie M. Huisinga, Daniel S. Peterson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/68dc8d3de4174b0dba3824cf8b7e838f
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spelling	oai:doaj.org-article:68dc8d3de4174b0dba3824cf8b7e838f2021-12-02T17:40:48ZThe application of principal component analysis to characterize gait and its association with falls in multiple sclerosis10.1038/s41598-021-92353-22045-2322https://doaj.org/article/68dc8d3de4174b0dba3824cf8b7e838f2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92353-2https://doaj.org/toc/2045-2322Abstract People with multiple sclerosis (PwMS) demonstrate gait impairments that are related to falls. However, redundancy exists when reporting gait outcomes. This study aimed to develop an MS-specific model of gait and examine differences between fallers and non-fallers. 122 people with relapsing–remitting MS and 45 controls performed 3 timed up-and-go trials wearing inertial sensors. 21 gait parameters were entered into a principal component analysis (PCA). The PCA-derived gait domains were compared between MS fallers (MS-F) and MS non-fallers (MS-NF) and correlated to cognitive, clinical, and quality-of-life outcomes. Six distinct gait domains were identified: pace, rhythm, variability, asymmetry, anterior–posterior dynamic stability, and medial–lateral dynamic stability, explaining 79.15% of gait variance. PwMS exhibited a slower pace, larger variability, and increased medial–lateral trunk motion compared to controls (p < 0.05). The pace and asymmetry domains were significantly worse (i.e., slower and asymmetrical) in MS-F than MS-NF (p < 0.001 and p = 0.03, respectively). Fear of falling, cognitive performance, and functional mobility were associated with a slower gait (p < 0.05). This study identified a six-component, MS-specific gait model, demonstrating that PwMS, particularly fallers, exhibit deficits in pace and asymmetry. Findings may help reduce redundancy when reporting gait outcomes and inform interventions targeting specific gait domains.Andrew S. MonaghanJessie M. HuisingaDaniel S. PetersonNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Andrew S. Monaghan Jessie M. Huisinga Daniel S. Peterson The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis
description	Abstract People with multiple sclerosis (PwMS) demonstrate gait impairments that are related to falls. However, redundancy exists when reporting gait outcomes. This study aimed to develop an MS-specific model of gait and examine differences between fallers and non-fallers. 122 people with relapsing–remitting MS and 45 controls performed 3 timed up-and-go trials wearing inertial sensors. 21 gait parameters were entered into a principal component analysis (PCA). The PCA-derived gait domains were compared between MS fallers (MS-F) and MS non-fallers (MS-NF) and correlated to cognitive, clinical, and quality-of-life outcomes. Six distinct gait domains were identified: pace, rhythm, variability, asymmetry, anterior–posterior dynamic stability, and medial–lateral dynamic stability, explaining 79.15% of gait variance. PwMS exhibited a slower pace, larger variability, and increased medial–lateral trunk motion compared to controls (p < 0.05). The pace and asymmetry domains were significantly worse (i.e., slower and asymmetrical) in MS-F than MS-NF (p < 0.001 and p = 0.03, respectively). Fear of falling, cognitive performance, and functional mobility were associated with a slower gait (p < 0.05). This study identified a six-component, MS-specific gait model, demonstrating that PwMS, particularly fallers, exhibit deficits in pace and asymmetry. Findings may help reduce redundancy when reporting gait outcomes and inform interventions targeting specific gait domains.
format	article
author	Andrew S. Monaghan Jessie M. Huisinga Daniel S. Peterson
author_facet	Andrew S. Monaghan Jessie M. Huisinga Daniel S. Peterson
author_sort	Andrew S. Monaghan
title	The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis
title_short	The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis
title_full	The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis
title_fullStr	The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis
title_full_unstemmed	The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis
title_sort	application of principal component analysis to characterize gait and its association with falls in multiple sclerosis
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/68dc8d3de4174b0dba3824cf8b7e838f
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The application of principal component analysis to characterize gait and its association with falls in multiple sclerosis

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