A scoping review of non-linear analysis approaches measuring variability in gait due to lower body injury or dysfunction.


Journal

Human movement science
ISSN: 1872-7646
Titre abrégé: Hum Mov Sci
Pays: Netherlands
ID NLM: 8300127

Informations de publication

Date de publication:
Feb 2020
Historique:
received: 19 08 2019
revised: 31 10 2019
accepted: 05 12 2019
entrez: 29 1 2020
pubmed: 29 1 2020
medline: 2 9 2020
Statut: ppublish

Résumé

The aim of this review is to evaluate and summarize existing literature using non-linear analysis methodology to consider variability of human movement due to lower limb injury or dysfunction. Scoping review. An electronic keyword search was performed on three databases to identify appropriate research. This research was then examined for details of measures and methodology, use of control groups and general study characteristics to identify related themes. Fifteen papers were reviewed and synthesized. A range of conditions were studied, mainly affecting knee and ankle joints, and each using different non-linear methods and different equipment (motion capture, accelerometry, and muscle activation) to evaluate the mathematically chaotic nature of the movement and assess the variability in gait. Sample sizes and effect sizes are commonly small in these studies. Non-linear analysis is a potentially useful tool in both diagnosis and evaluation of injury, and this should inform future clinical processes when dealing with injury and movement variability. Despite numerous studies evaluating neurological conditions and ageing, focus on injury is limited, with notable gaps in terms of considering other joints and joint actions, so this should be a promising area of research to develop our understanding of injury and rehabilitation and how this affects gait variability.

Identifiants

pubmed: 31989953
pii: S0167-9457(19)30600-1
doi: 10.1016/j.humov.2019.102562
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

102562

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest None.

Auteurs

Clare Strongman (C)

Cambridge Centre for Sport and Exercise Sciences, Anglia Ruskin University, East Road, Cambridge, UK. Electronic address: clare@cstrongman.co.uk.

Andrew Morrison (A)

Cambridge Centre for Sport and Exercise Sciences, Anglia Ruskin University, East Road, Cambridge, UK. Electronic address: andrew.morrison@anglia.ac.uk.

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Classifications MeSH