Evidence map›Paper›PMID 32377224›Full record

ArticleComputational and mathematical methods in medicine2020

Examining Human Unipedal Quiet Stance: Characterizing Control through Jerk.

Matthew R Semak, Jeremiah Schwartz, Gary Heise

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.2field-weighted citation impact, top 12% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
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

3 authors at 1 institution in 1 country.

Matthew R SemakDepartment of Physics and Astronomy, University of Northern Colorado, Greeley, CO 80639, USA.ORCID https://orcid.org/0000-0002-9133-7156
Jeremiah SchwartzDepartment of Physics and Astronomy, University of Northern Colorado, Greeley, CO 80639, USA.
Gary HeiseSchool of Sport and Exercise Science, University of Northern Colorado, Greeley, CO 80639, USA.
University of Northern Colorado · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We investigated the quality of smoothness during human unipedal quiet stance. Smoothness is quantified by the time rate of change of the accelerations, or jerks, associated with the motion of the foot and can be seen as an indicative of how controlled the balance process is. To become more acquainted with this as a quantity, we wanted to establish whether or not it can be modeled as a (stationary) stochastic process and, if so, explore its temporal scaling behavior. Specifically, our study focused on the jerk concerning the center-of-pressure (COP) for each foot. Data were collected via a force plate for individuals attempting to maintain upright posture using one leg (with eyes open). Positive tests for stochasticity allowed us to treat the time series as a stochastic process and, given this, we took the jerk to be proportional to the increment of the force realizations. Detrended fluctuation analysis was the primary tool used to explore the scaling behavior. Results suggest that both the medial-lateral and anterior-posterior components of the jerk display persistent and antipersistent correlations which can be modeled by fractional Gaussian noise over three different temporal scaling regions. Finally, we discussed certain possible implications of these features such as a jerk-based control over the force on the foot's COP.

Indexed as

Standing PositionAdultAlgorithmsBiomechanical PhenomenaFootHumansMiddle AgedModels, BiologicalNormal DistributionPostural BalancePostureStochastic ProcessesTransducersYoung Adult

Identifiers

PMID32377224
PMCPMC7199553
OpenAlexW2997707977

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.