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Record W2087879039 · doi:10.1167/8.6.426

Life-span study of visually driven postural reactivity: A fully immersive virtual reality approach

2010· article· en· W2087879039 on OpenAlexaff
Selma Greffou, Jocelyn Faubert

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAudiologyPhysical medicine and rehabilitationPsychologyVirtual realityFixation (population genetics)Sensory cueLife spanStereoscopyVisual acuityDevelopmental psychologyMedicineCognitive psychologyComputer scienceComputer visionOphthalmologyArtificial intelligence

Abstract

fetched live from OpenAlex

The objective of this study was to assess the development of visuo-motor integration across life-span by measuring the postural reactivity in response to an immersive moving virtual tunnel. Seventy participants whose ages ranged from 5 to 75 years old were tested. They had a normal or corrected to normal visual acuity and a normal stereoscopic vision. Each participant was placed in a virtual tunnel that oscillated in an anterior-posterior fashion at 0.125 Hz, 0.25 Hz and 0.5 Hz. Participants' Body Sway (BS) and Instability Index (II) were measured with a magnetic motion sensor located at the head level. The same two measures were also taken during the fixation of the static tunnel condition and during the eyes closed condition (no visual cues available). A significant main effect of age was found for both BS and II, where children (5 to 16 year-old) and the elderly (65 year-old onward) were more reactive to the stimulation than were the adults (17 to 60 year-old) for all dynamic conditions. Our results suggest that visuo-motor integration, as defined by postural reactivity is not fully developed until 16 to 19 years old as indicated by younger than 16 year-old children's over-reliance on vision to control their posture. This over-reliance on vision disappears during adulthood but seems to come back at an advanced age (65 years onward). Possible explanations are that children over-rely on vision because the primary elements for postural control are not fully developed; whereas in aging it might be explained by a degradation of these systems forcing observers to “spread the load” across alternate sensory systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.325
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2010
Admission routes1
Has abstractyes

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