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Record W4406224492 · doi:10.1002/alz.083889

Exploring virtual reality gaming‐related cybersickness in Alzheimer’s disease

2024· article· en· W4406224492 on OpenAlex
Rashmita Chatterjee, Zahra Moussavi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Technologies in Various Fields
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsVirtual realityPsychologyComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

Abstract Background In the last decade, virtual reality has become a popular tool for rehabilitation. It is quite useful in spatial rehabilitation for Alzheimer’s disease (AD) as it allows safe navigation in a virtual environment which looks realistic. However, a drawback of virtual reality is cybersickness. The symptoms and severities of cybersickness can vary among users. Possible cybersickness symptoms include headache, nausea, disorientation. Cybersickness can be distracting for participants and can affect their performance on the virtual reality task. Hence, in our rehabilitation game called Barn Ruins Navigation (BRN), we used software design mechanisms that would reduce cybersickness, including (1) keeping the field of view to 60 degrees, (2) lowering speed of rotation and translation, (3) using a joystick which causes less cybersickness, and (4) using a laptop screen instead of a head‐mounted display. There have been contradicting results on the effects cybersickness has on people with AD. We wanted to test if cybersickness felt by the BRN game differed between people with AD and cognitively healthy adults. Method Cybersickness was measured using the Simulator Sickness Questionnaire (SSQ) after playing BRN. Thirty adults were recruited for the BRN validation study between the ages of 20‐88. This includes ten younger adults (five males, 26±3.39 years), ten cognitively healthy older adults (three males, 70.7±5.31 years), and ten people living with mild to moderate AD (seven males, 77.8±5.94 years). All participants played the game once. Result Regression analysis on the data showed that males had significantly lower SSQ scores by about 17.47 points compared to females (p = 0.0106), while adjusting for participant groups. The AD group had the highest SSQ scores in comparison to cognitively healthy older adults and younger adults while adjusting for sex. Only the younger adults had a statistically lower SSQ score than the AD group by 18 points (p = 0.023). Conclusion We found males were less prone to cybersickness than females, matching the cybersickness literature. Our study found people with AD were more prone to cybersickness, however not to a statistically higher degree than cognitively healthy older adults. We would need a larger sample size to draw solid conclusions.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.001
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 head0.080
GPT teacher head0.295
Teacher spread0.215 · 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