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Record W4403306276 · doi:10.3389/frvir.2024.1339296

Detection threshold of distorted self-avatar step length during gait and the effects on the sense of embodiment

2024· article· en· W4403306276 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Virtual Reality · 2024
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsCentre for Interdisciplinary Research in RehabilitationÉcole de Technologie SupérieureUniversité de Montréal
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsAvatarGaitSense (electronics)PsychologyComputer scienceCognitive psychologyComputer visionCommunicationHuman–computer interactionPhysical medicine and rehabilitationMedicineEngineering

Abstract

fetched live from OpenAlex

In immersive VR, a self-avatar that replicates the user’s movements and is viewed from a first-person perspective can substitute the real body. If the avatar’s movements are sufficiently synchronized with the user’s actual movements, the user can experience a sense of embodiment over the avatar. Recent studies have shown that discrepancies between the movements of the avatar and those of the user can be well tolerated while maintaining high levels of embodiment. The point at which a distortion is perceived (detection threshold) and its impact on the level of embodiment has not been studied in lower limb tasks such as gait. This study aimed to identify a detection threshold of gait asymmetry by unilaterally manipulating the step length of a self-avatar, and the effect of this detection on perceived embodiment. A real-time step length distortion model was developed, and a detection threshold between actual and avatar’s gait movement was assessed on thirty healthy participants. The step length was manipulated to introduce gait asymmetry (ascending condition) or start from a large asymmetry that was gradually decreased (descending). The results showed that, on average, the avatar’s step length could be increased by up to 12% before the participants detected the distortion. Furthermore, in the descending condition, they detected increases that were above 9%. The point of detection had no effect on the sense of embodiment as participants still reported being embodied in their avatars, even when they consciously detected the step length distortion. The sense of embodiment was closely correlated with the level of distortion; as distortion increased, embodiment decreased, and vice versa . For a given distortion level, embodiment was similar whether in the ascending or descending condition. This suggests that embodiment can be achieved even when the avatar’s spatial alignment initially differs from the participants’, provided that alignment is gradually restored. These results provide valuable insights into participants’ ability to tolerate movement discrepancies in embodied avatar experiences during gait in virtual environments, with potential applications in motor training and gait 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.

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)0.000
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 score0.667
Threshold uncertainty score0.257

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.262
Teacher spread0.249 · 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