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Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis

Gait pattern classification in individuals with lower-limb amputation could help in developing personalized prosthetic prescriptions and tailored gait rehabilitation. However, systematic classifications of gait patterns in this population have been scarcely explored. This study aimed to determine wh...

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Autores principales: Ichimura, Daisuke, Amma, Ryo, Hisano, Genki, Murata, Hiroto, Hobara, Hiroaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778493/
https://www.ncbi.nlm.nih.gov/pubmed/36548294
http://dx.doi.org/10.1371/journal.pone.0279593
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author Ichimura, Daisuke
Amma, Ryo
Hisano, Genki
Murata, Hiroto
Hobara, Hiroaki
author_facet Ichimura, Daisuke
Amma, Ryo
Hisano, Genki
Murata, Hiroto
Hobara, Hiroaki
author_sort Ichimura, Daisuke
collection PubMed
description Gait pattern classification in individuals with lower-limb amputation could help in developing personalized prosthetic prescriptions and tailored gait rehabilitation. However, systematic classifications of gait patterns in this population have been scarcely explored. This study aimed to determine whether the gait patterns in individuals with unilateral transfemoral amputation (UTFA) can be clustered into homogeneous subgroups using spatiotemporal parameters across a range of walking speeds. We examined spatiotemporal gait parameters, including step length and cadence, in 25 individuals with UTFA (functional level K3 or K4, all non-vascular amputations) while they walked on a split-belt instrumented treadmill at eight speeds. Hierarchical cluster analysis (HCA) was used to identify clusters with homogeneous gait patterns based on the relationships between step length and cadence. Furthermore, after cluster formation, post-hoc analyses were performed to compare the spatiotemporal parameters and demographic data among the clusters. HCA identified three homogeneous gait pattern clusters, suggesting that individuals with UTFA have several gait patterns. Further, we found significant differences in the participants’ body height, sex ratio, and their prosthetic knee component among the clusters. Therefore, gait rehabilitation should be individualized based on body size and prosthetic prescription.
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spelling pubmed-97784932022-12-23 Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis Ichimura, Daisuke Amma, Ryo Hisano, Genki Murata, Hiroto Hobara, Hiroaki PLoS One Research Article Gait pattern classification in individuals with lower-limb amputation could help in developing personalized prosthetic prescriptions and tailored gait rehabilitation. However, systematic classifications of gait patterns in this population have been scarcely explored. This study aimed to determine whether the gait patterns in individuals with unilateral transfemoral amputation (UTFA) can be clustered into homogeneous subgroups using spatiotemporal parameters across a range of walking speeds. We examined spatiotemporal gait parameters, including step length and cadence, in 25 individuals with UTFA (functional level K3 or K4, all non-vascular amputations) while they walked on a split-belt instrumented treadmill at eight speeds. Hierarchical cluster analysis (HCA) was used to identify clusters with homogeneous gait patterns based on the relationships between step length and cadence. Furthermore, after cluster formation, post-hoc analyses were performed to compare the spatiotemporal parameters and demographic data among the clusters. HCA identified three homogeneous gait pattern clusters, suggesting that individuals with UTFA have several gait patterns. Further, we found significant differences in the participants’ body height, sex ratio, and their prosthetic knee component among the clusters. Therefore, gait rehabilitation should be individualized based on body size and prosthetic prescription. Public Library of Science 2022-12-22 /pmc/articles/PMC9778493/ /pubmed/36548294 http://dx.doi.org/10.1371/journal.pone.0279593 Text en © 2022 Ichimura et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ichimura, Daisuke
Amma, Ryo
Hisano, Genki
Murata, Hiroto
Hobara, Hiroaki
Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis
title Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis
title_full Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis
title_fullStr Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis
title_full_unstemmed Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis
title_short Spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: A hierarchical cluster analysis
title_sort spatiotemporal gait patterns in individuals with unilateral transfemoral amputation: a hierarchical cluster analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778493/
https://www.ncbi.nlm.nih.gov/pubmed/36548294
http://dx.doi.org/10.1371/journal.pone.0279593
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