Evidence map›Paper›PMID 36881586›Full record

ArticlePloS one2023

Ankle strategies for step-aside movement during quiet standing.

Lingchao Xie, Sanghyun Cho

Abstract read
In one paragraph

Article in PloS one, 2023. 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

The trial behind it

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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

Corrections and comments

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

2 authors.

Lingchao XieDepartment of Physical Therapy, Yonsei University, Wonju, South Korea.ORCID 0000-0003-3690-2463
Sanghyun ChoDepartment of Physical Therapy, Yonsei University, Wonju, South Korea.ORCID 0000-0003-2643-474X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mediolateral ankle strategy plays a crucial role in providing ankle stability in ground obstacle-avoidance behavior. This is achieved by changing basic walking patterns according to the characteristics of the obstacle. In daily life, it is more common to use step-aside movement (i.e., dodging step) for collision avoidance rather than side-stepping (i.e., widening standing base) when encountering an approaching pedestrian or bicycle. While studies have been conducted on the mediolateral ankle strategy contribution in obstacle avoidance using side-stepping, knowledge of step-aside movement is still inadequate. Therefore, we conducted an electromyography (EMG) analysis on the tibialis anterior (TA), peroneus longus (PL), and soleus (SOL) muscles, as well as measured center of pressure (CoP) displacement, and vertical ground reaction force (vGRF) of the standing leg, in order to understand the role of ankle muscles in step-aside movement during quiet standing. Fifteen healthy young men repeated twelve step-aside movements in both left and right directions. A Bayesian one-sample t-test was used to determine the sufficient step and participant counts. Multiple linear regression analysis was used to investigate the correlation between the muscle activity and CoP displacement or vGRF. The regression coefficients (β) of the left push phase and the right loading phase were tested against zero using a Bayesian one-sample t-test to identify the correlation between independent and dependent variables. We used the one-dimensional statistical parametric mapping (SPM1d) method to analyze the differences between and within the groups of EMG data based on the continuous time series. The results showed that the PL displayed a substantial contribution to the mediolateral ankle strategy during the push phase of step-aside movement, and also contributed to maintaining ankle stability during the loading phase. This suggested that screening for PL weakness and providing appropriate interventions and/or training approaches is especially critical for populations with walking stability problems.

Indexed as

AnkleAnkle JointBayes TheoremHumansLegMaleMovement

Identifiers

PMID36881586
PMCPMC9990923

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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.