Different neuromuscular control mechanisms regulate static and dynamic balance: A center-of-pressure analysis in young adults.


Journal

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

Informations de publication

Date de publication:
Aug 2023
Historique:
received: 10 10 2022
revised: 29 05 2023
accepted: 15 06 2023
medline: 31 7 2023
pubmed: 26 6 2023
entrez: 26 6 2023
Statut: ppublish

Résumé

The analysis of the center of pressure (CoP) trajectory, derived from force platforms, is a widely accepted measure to investigate postural balance control. The CoP trajectory could be analyzed as a physiological time-series through a general stochastic modeling framework (i.e., Stabilogram Diffusion Analysis (SDA)). Critical point divides short-term from long-term regions and diffusion coefficients reflect the level of stochastic activity of the CoP. Sample Entropy (SampEn) allows quantifying the CoP complexity in terms of regularity. Thus, this study aimed to understand whether SDA and SampEn could discriminate the neuromuscular control mechanisms underpinning static and dynamic postural tasks. Static balance control and its relationship with dynamic balance control were investigated through the CoP velocity (Mean Velocity) and the area of the 95th percentile ellipse (Area95). Balance was assessed in 15 subjects (age: 23.13 ± 0.99 years; M = 9) over a force platform under two conditions: static (ST) and dynamic, both in anterior-posterior (DAP) and medio-lateral (DML) directions. During the DAP and DML, subjects stood on an unstable board positioned over a force platform. Short-term SDA diffusion coefficients and critical points were lower in ST than in DAP and DML (p < 0.05). SampEn values resulted greater in ST than in DAP and DML (p < 0.001). As expected, lower values of Area95 (p < 0.001) and Mean Velocity (p < 0.001) were detected in the easiest condition, the ST, compared to DAP and DML. No significant correlations between static and dynamic balance performances were detected. Moreover, differences in the diffusion coefficients were detected comparing DAP and DML (p < 0.05). In the anterior-posterior direction, the critical point occurred at relatively small intervals in DML compared to DAP (p < 0.001) and ST (p < 0.001). In the medio-lateral direction, the critical point differed only between DAP and DML (p < 0.05). Overall, SDA analysis pointed out a less tightly regulated neuromuscular control system in the dynamic tasks, with closed-loop corrective feedback mechanisms called into play at different time intervals in the three conditions. SampEn results reflected more attention and, thus, less automatic control mechanisms in the dynamic conditions, particularly in the medio-lateral task. The different neuromuscular control mechanisms that emerged in the static and dynamic balance tasks encourage using both static and dynamic tests for a more comprehensive balance performance assessment.

Identifiants

pubmed: 37364344
pii: S0167-9457(23)00066-0
doi: 10.1016/j.humov.2023.103120
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103120

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Auteurs

Alex Rizzato (A)

Department of Biomedical Sciences, University of Padova, Padova, Italy.

Michael Benazzato (M)

Department of Industrial Engineering, University of Padova, Italy.

Matteo Cognolato (M)

Institute of Information Systems, University of Applied Sciences Western Switzerland (HES-SO), Sierre, Switzerland.

Davide Grigoletto (D)

Department of Biomedical Sciences, University of Padova, Padova, Italy.

Antonio Paoli (A)

Department of Biomedical Sciences, University of Padova, Padova, Italy.

Giuseppe Marcolin (G)

Department of Biomedical Sciences, University of Padova, Padova, Italy. Electronic address: giuseppe.marcolin@unipd.it.

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Classifications MeSH