Characterizing postural balance on 2-dimensional compliant surfaces with directional virtual time-to-contact.
Balance control
Directional virtual time-to-contact
Dual-axis robotic platform
Postural balance
Journal
Human movement science
ISSN: 1872-7646
Titre abrégé: Hum Mov Sci
Pays: Netherlands
ID NLM: 8300127
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
09
01
2023
revised:
19
05
2023
accepted:
25
07
2023
pmc-release:
01
10
2024
medline:
11
9
2023
pubmed:
3
8
2023
entrez:
2
8
2023
Statut:
ppublish
Résumé
This study aimed to (1) investigate postural balance control on 2-Dimensional (2D) compliant surfaces using directional virtual time-to-contact (d-VTC), a novel method for VTC calculation; and (2) compare d-VTC with conventional balance measures in this context. A dual-axis robotic platform was used to simulate 2D surfaces/grounds with varying compliance levels. Twenty healthy young adults stood on the platform with either open or closed eyes. Balance was evaluated using d-VTC in multiple aspects, including temporal (VTC mean), spatial (boundary contact - BC), and control aspects (switching rate - SR). Additionally, conventional balance measures, namely center-of-pressure (COP) area and COP root-mean-square (RMS), were employed for further comparisons with d-VTC measures. Normality checks were performed using Shapiro-Wilk tests. Two-way repeated measures ANOVA tests were used to examine the effects of surface compliance and vision on postural balance, followed by post-hoc pairwise comparisons across conditions with Bonferroni correction. The results showed that increasing surface compliance and/or absence of vision caused a significant decrease in VTC mean (all p-values <0.001; all η Balance control is compromised by 2D compliant surfaces, which is exacerbated when vision is absent. Among all balance measures, VTC mean measures demonstrated particularly high sensitivity in identifying decreased balance capabilities, while BC and SR provided new insights into fall risks and balance control mechanisms. These insights may facilitate the development of rehabilitation training or assistive devices for fall prevention.
Sections du résumé
BACKGROUND
BACKGROUND
This study aimed to (1) investigate postural balance control on 2-Dimensional (2D) compliant surfaces using directional virtual time-to-contact (d-VTC), a novel method for VTC calculation; and (2) compare d-VTC with conventional balance measures in this context.
METHODS
METHODS
A dual-axis robotic platform was used to simulate 2D surfaces/grounds with varying compliance levels. Twenty healthy young adults stood on the platform with either open or closed eyes. Balance was evaluated using d-VTC in multiple aspects, including temporal (VTC mean), spatial (boundary contact - BC), and control aspects (switching rate - SR). Additionally, conventional balance measures, namely center-of-pressure (COP) area and COP root-mean-square (RMS), were employed for further comparisons with d-VTC measures. Normality checks were performed using Shapiro-Wilk tests. Two-way repeated measures ANOVA tests were used to examine the effects of surface compliance and vision on postural balance, followed by post-hoc pairwise comparisons across conditions with Bonferroni correction.
RESULTS
RESULTS
The results showed that increasing surface compliance and/or absence of vision caused a significant decrease in VTC mean (all p-values <0.001; all η
CONCLUSION
CONCLUSIONS
Balance control is compromised by 2D compliant surfaces, which is exacerbated when vision is absent. Among all balance measures, VTC mean measures demonstrated particularly high sensitivity in identifying decreased balance capabilities, while BC and SR provided new insights into fall risks and balance control mechanisms. These insights may facilitate the development of rehabilitation training or assistive devices for fall prevention.
Identifiants
pubmed: 37531739
pii: S0167-9457(23)00080-5
doi: 10.1016/j.humov.2023.103134
pmc: PMC10530255
mid: NIHMS1921713
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
103134Subventions
Organisme : NIAMS NIH HHS
ID : R01 AR080826
Pays : United States
Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Références
Front Neurosci. 2018 Mar 20;12:171
pubmed: 29615859
J Mot Behav. 1997 Sep;29(3):263-81
pubmed: 12453785
Motor Control. 2008 Oct;12(4):283-95
pubmed: 18955739
Exp Brain Res. 2020 Jan;238(1):93-99
pubmed: 31792556
Exp Brain Res. 2009 Oct;199(1):1-16
pubmed: 19655130
Physiol Meas. 1996 Nov;17(4):305-12
pubmed: 8953629
Gait Posture. 2009 Apr;29(3):509-13
pubmed: 19168357
Exp Brain Res. 2007 Mar;177(4):471-82
pubmed: 17031683
J Biomech. 2013 Oct 18;46(15):2593-602
pubmed: 24041491
Gait Posture. 2007 Jan;25(1):33-9
pubmed: 16446093
J Biomech. 2023 Jan;146:111428
pubmed: 36610387
IEEE Trans Biomed Eng. 1996 Sep;43(9):956-66
pubmed: 9214811
J Neurophysiol. 2001 Jun;85(6):2630-3
pubmed: 11387407
J Biomech. 2021 Jun 23;123:110485
pubmed: 34004395
Gait Posture. 2008 Nov;28(4):649-56
pubmed: 18602829
Clin Biomech (Bristol, Avon). 2021 Aug;88:105420
pubmed: 34216987
J Gerontol A Biol Sci Med Sci. 1998 Jan;53(1):B71-8
pubmed: 9467425
PLoS One. 2016 Oct 20;11(10):e0164913
pubmed: 27764158
IEEE J Transl Eng Health Med. 2023 Apr 28;11:282-290
pubmed: 37275470
J Gerontol. 1991 May;46(3):M69-76
pubmed: 2030269