Evidence map›Paper›PMID 35141819›Full record

ArticleMedical & biological engineering & computing2022

Balance on different unstable supports: a complementary approach based on linear and non-linear analyses.

John McCamley, Elena Bergamini, Eleni Grimpampi

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Article in Medical & biological engineering & computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

John McCamleyHuman Motion Laboratory, MORE Foundation, 18444 N 25th Ave., Suite 110, Phoenix, AZ, 85023, USA.
Elena BergaminiDepartment of Movement, Human and Health Sciences, Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, University of Rome "Foro Italico", Piazza Lauro de Bosis 15, 00135, Rome, Italy. elena.bergamini@uniroma4.it.ORCID http://orcid.org/0000-0002-9055-3981
Eleni GrimpampiDecathlon SportsLab, Movement Sciences Department, 4 Rue Professeur Langevin, 59000, Lille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Maintenance of postural control is a complex task that requires the integration of different sensory-motor processes. To improve postural control, balance training is often implemented using unstable surfaces. Little is known, however, about how different surfaces compare in terms of postural control strategy. Non-linear dynamical system analysis, like recurrent quantification analysis (RQA) applied to the center of pressure (CoP) trajectory, represents a useful tool in this respect. The aim of this study is to investigate the effects of different unstable supports on the CoP trajectory through a complementary approach based on linear and non-linear analyses. Seventeen healthy adults performed barefoot single-leg balance trials on a force plate and on three different balance training devices (soft disc, foam pad, and pillow). Sets of parameters were extracted from the CoP trajectories using classical stabilometric analysis (sway path, mean velocity, root mean square) and RQA (percent recurrence and determinism, maximum line length, entropy). Both classical and RQA analyses highlighted significant differences between stable (force plate) and unstable conditions (p < 0.001). Conversely, only classical stabilometric parameters showed significant differences among the considered balance training devices, indicating that the different characteristics of the devices do not influence the dynamic/temporal structure of the CoP trajectory. Analysis of the center of pressure trajectory during single-leg standing on three different balance training devices and on a rigid surface using both linear and non-linear techniques.

Indexed as

Nonlinear DynamicsPostural BalanceAdultEntropyGravitationHumansBiomechanicsNon-linear dynamicsPostural balanceProprioceptionRecurrence quantification analysis

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.