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Record W3061000716 · doi:10.2196/18888

Effects of Avatar Perspective on Joint Excursions Used to Play Virtual Dodgeball: Within-Subject Comparative Study

2020· article· en· W3061000716 on OpenAlexaffvenue
Susanne M. van der Veen, Alexander Stamenkovic, Megan E. Applegate, Samuel T. Leitkam, Christopher France, James S. Thomas

Bibliographic record

VenueJMIR Serious Games · 2020
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsMcGill University
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsAvatarPerspective (graphical)PsychologyExcursionMotion (physics)Computer scienceComputer visionHuman–computer interactionArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Visual representation of oneself is likely to affect movement patterns. Prior work in virtual dodgeball showed greater excursion of the ankles, knees, hips, spine, and shoulder occurs when presented in the first-person perspective compared to the third-person perspective. However, the mode of presentation differed between the two conditions such that a head-mounted display was used to present the avatar in the first-person perspective, but a 3D television (3DTV) display was used to present the avatar in the third-person. Thus, it is unknown whether changes in joint excursions are driven by the visual display (head-mounted display versus 3DTV) or avatar perspective during virtual gameplay. OBJECTIVE: This study aimed to determine the influence of avatar perspective on joint excursion in healthy individuals playing virtual dodgeball using a head-mounted display. METHODS: Participants (n=29, 15 male, 14 female) performed full-body movements to intercept launched virtual targets presented in a game of virtual dodgeball using a head-mounted display. Two avatar perspectives were compared during each session of gameplay. A first-person perspective was created by placing the center of the displayed content at the bridge of the participant's nose, while a third-person perspective was created by placing the camera view at the participant's eye level but set 1 m behind the participant avatar. During gameplay, virtual dodgeballs were launched at a consistent velocity of 30 m/s to one of nine locations determined by a combination of three different intended impact heights and three different directions (left, center, or right) based on subject anthropometrics. Joint kinematics and angular excursions of the ankles, knees, hips, lumbar spine, elbows, and shoulders were assessed. RESULTS: The change in joint excursions from initial posture to the interception of the virtual dodgeball were averaged across trials. Separate repeated-measures ANOVAs revealed greater excursions of the ankle (P=.010), knee (P=.001), hip (P=.0014), spine (P=.001), and shoulder (P=.001) joints while playing virtual dodgeball in the first versus third-person perspective. Aligning with the expectations, there was a significant effect of impact height on joint excursions. CONCLUSIONS: As clinicians develop treatment strategies in virtual reality to shape motion in orthopedic populations, it is important to be aware that changes in avatar perspective can significantly influence motor behavior. These data are important for the development of virtual reality assessment and treatment tools that are becoming increasingly practical for home and clinic-based rehabilitation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.328
Teacher spread0.284 · 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 designQualitative
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

Citations9
Published2020
Admission routes2
Has abstractyes

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