Gait measurement in chronic mild traumatic brain injury: A model approach.
Gait
Inertial sensors
Mild traumatic brain injury
Principle component analysis
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
Feb 2020
Historique:
received:
22
04
2019
revised:
08
11
2019
accepted:
14
11
2019
pubmed:
30
11
2019
medline:
1
8
2020
entrez:
30
11
2019
Statut:
ppublish
Résumé
Mild traumatic brain injury (mTBI) can impact gait, with deficits linked to underlying neural disturbances in cognitive, motor and sensory systems. Gait is complex as it is comprised of multiple characteristics that are sensitive to underlying neural deficits. However, there is currently no clear framework to guide selection of gait characteristics in mTBI. This study developed a model of gait in chronic mTBI and replicated this in a separate group of controls, to provide a comprehensive and structured methodology on which to base gait assessment and analysis. Fifty-two people with chronic mTBI and 59 controls completed a controlled laboratory gait assessment; walking for two minutes back and forth over a 13 m distance while wearing five wirelessly synchronized inertial sensors. Thirteen gait characteristics derived from the inertial sensors were selected for entry into the principle component analysis based on previous literature, robustness and novelty. Principle component analysis was then used to derive domains (components) of gait. Four gait domains were derived for our chronic mTBI group (variability, rhythm, pace and turning) and this was replicated in a separate control cohort. Domains totaled 80.8% and 77.4% of variance in gait for chronic mTBI and controls, respectively. Gait characteristic loading was unambiguous for all features, with the exception of gait speed in controls that loaded on pace and rhythm domains. This study contributes a four component model of gait in chronic mTBI and controls that can be used to comprehensively assess and analyze gait and underlying mechanisms involved in impairment, or examine the influence of interventions.
Identifiants
pubmed: 31783306
pii: S0167-9457(19)30290-8
doi: 10.1016/j.humov.2019.102557
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
102557Informations de copyright
Copyright © 2019. Published by Elsevier B.V.
Déclaration de conflit d'intérêts
Declaration of Competing Interest None to declare.