Evidence map›Paper›PMID 35891095›Full record

ArticleSensors (Basel, Switzerland)2022

Prediction of Stability during Walking at Simulated Ship's Rolling Motion Using Accelerometers.

Jungyeon Choi, Brian A Knarr, Yeongjin Gwon, Jong-Hoon Youn

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

4 authors.

Jungyeon ChoiCollege of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE 68182, USA.ORCID 0000-0001-9612-3029
Brian A KnarrDepartment of Biomechanics, University of Nebraska at Omaha, Omaha, NE 68182, USA.ORCID 0000-0002-8997-1377
Yeongjin GwonDepartment of Biostatistics, University of Nebraska Medical Center, Omaha, NE 68198, USA.
Jong-Hoon YounCollege of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE 68182, USA.

Funding

Office of Research and Creative Activity (ORCA) of the University of Nebraska at Omaha 42-1209-1223
6 · The paper itself

Abstract

Due to a ship's extreme motion, there is a risk of injuries and accidents as people may become unbalanced and be injured or fall from the ship. Thus, individuals must adjust their movements when walking in an unstable environment to avoid falling or losing balance. A person's ability to control their center of mass (COM) during lateral motion is critical to maintaining balance when walking. Dynamic balancing is also crucial to maintain stability while walking. The margin of stability (MOS) is used to define this dynamic balancing. This study aimed to develop a model for predicting balance control and stability in walking on ships by estimating the peak COM excursion and MOS variability using accelerometers. We recruited 30 healthy individuals for this study. During the experiment, participants walked for two minutes at self-selected speeds, and we used a computer-assisted rehabilitation environment (CAREN) system to simulate the roll motion. The proposed prediction models in this study successfully predicted the peak COM excursion and MOS variability. This study may be used to protect and save seafarers or passengers by assessing the risk of balance loss.

Indexed as

GaitPostural BalanceAccelerometryBiomechanical PhenomenaHumansShipsWalkingaccelerometerCARENcenter of massgait stabilitymargin of stabilityship rolling

Identifiers

PMID35891095
PMCPMC9320816

What OpenQuestion holds

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LicenceCC BY
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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.