Evidence map›Paper›PMID 32958807›Full record

ArticleScientific reports2020

Age-related differences in gait adaptations during overground walking with and without visual perturbations using a virtual reality headset.

Muyinat Y Osaba, Dario Martelli, Antonio Prado, Sunil K Agrawal, Anil K Lalwani

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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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3 · Its place in the literature

Who cites it

20 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

5 authors.

Muyinat Y Osaba *Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA.
Dario Martelli *Department of Mechanical Engineering, University of Alabama, Tuscaloosa, AL, USA.
Antonio PradoDepartment of Mechanical Engineering, Columbia University, New York, NY, USA.
Sunil K AgrawalDepartment of Mechanical Engineering, Columbia University, New York, NY, USA.
Anil K LalwaniDepartment of Otolaryngology-Head and Neck Surgery, Columbia University Vagelos College of Physicians and Surgeons, 180 Fort Washington Avenue, Harkness Pavilion, 8th Floor, New York, NY, 10032, USA. Anil.Lalwani@columbia.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Older adults have difficulty adapting to new visual information, posing a challenge to maintain balance during walking. Virtual reality can be used to study gait adaptability in response to discordant sensorimotor stimulations. This study aimed to investigate age-related modifications and propensity for visuomotor adaptations due to continuous visual perturbations during overground walking in a virtual reality headset. Twenty old and twelve young subjects walked on an instrumented walkway in real and virtual environments while reacting to antero-posterior and medio-lateral oscillations of the visual field. Mean and variability of spatiotemporal gait parameters were calculated during the first and fifth minutes of walking. A 3-way mixed-design ANOVA was performed to determine the main and interaction effects of group, condition and time. Both groups modified gait similarly, but older adults walked with shorter and slower strides and did not reduce stride velocity or increase stride width variability during medio-lateral perturbations. This may be related to a more conservative and anticipatory strategy as well as a reduced perception of the optic flow. Over time, participants adapted similarly to the perturbations but only younger participants reduced their stride velocity variability. Results provide novel evidence of age- and context-dependent visuomotor adaptations in response to visual perturbations during overground walking and may help to establish new methods for early identification and remediation of gait deficits.

Indexed as

Adaptation, PhysiologicalAdultAgedExercise TestFemaleGaitHumansMaleOptic FlowPostural BalanceVirtual RealityVisual FieldsWalkingYoung Adult

Identifiers

PMID32958807
PMCPMC7505838

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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.