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Record W4365443142 · doi:10.2196/40806

Appropriate Image Selection With Virtual Reality in Vestibular Rehabilitation: Cross-sectional Study

2023· article· en· W4365443142 on OpenAlexvenueno aff
Kerem Ersin, Emre Gürlek, Hakan Güler, Çiğdem Kalaycık Ertugay, Mustafa Bülent Şerbetçioğlu

Bibliographic record

VenueJMIR Serious Games · 2023
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsnot available
Fundersnot available
KeywordsVestibular systemRehabilitationVirtual realityAudiologyAnxietyPsychologyPhysical medicine and rehabilitationVestibular rehabilitationTrait anxietySensory systemSomatosensory systemMedicinePhysical therapyComputer scienceArtificial intelligenceCognitive psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: While vestibular rehabilitation with virtual reality (VR) is becoming more popular every day, the disadvantages of this method are not yet clear. OBJECTIVE: The aim of this study is to examine the effect of the image to be used in vestibular rehabilitation with VR on the systems that provide body posture. METHODS: The study was carried out with 36 participants (18 women and 18 men) aged 18 to 30 years. To assess balance control components separately, a sensory organization test was administered to the participants in the presence of stressful and relaxing environment images with VR technology. The State-Trait Anxiety Inventory survey was also used to measure the stress values in the created environments. RESULTS: The State-Trait Anxiety Inventory survey revealed that while stressful videos significantly increased stress, relaxing videos reduced stress. Among measurements obtained in the presence of VR, significant decreases were observed mostly in the visual system data. A significant increase in vestibular system data (P=.01) was observed with a decrease in visual system data (P<.001) when the relaxing image was presented. Additionally, there was a significant difference in the somatosensory (P=.001), composite (P=.002), and visual system (P<.001) data in the presence of stressful videos. CONCLUSIONS: Although the use of a VR system for vestibular rehabilitation is relatively new, no extant studies have examined how the image type used in VR can affect the integration of visual system data. Therefore, this study is unique in terms of showing the effects of the stress created by the change in the type of the image used in VR. When VR technology is used for therapeutic vestibular rehabilitation for patients whose balance disorder is due to the vestibular system, stress-free videos should be used. However, the use of stressful videos in VR technology will be beneficial in the rehabilitation of those with balance disorders due to the somatosensory system.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.315
Teacher spread0.297 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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