MétaCan
Menu
Back to cohort
Record W3044939136

Improving the ergonomics of hand tracking inputs to VR HMD's

2017· article· en· W3044939136 on OpenAlex
Scott Devine, Chris M. Nicholson, Karen Rafferty, Chris M. Herdman

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

VenueDigital Library (University of West Bohemia) · 2017
Typearticle
Languageen
FieldPsychology
TopicHuman-Automation Interaction and Safety
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceVirtual realityTracking (education)Human–computer interactionSimulationPhysical medicine and rehabilitationPsychologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

This study improves the ergonomics of using the Leap Motion hand tracking device with an Oculus Rift. The improvements\nwere realised through the use of a 3D printed mount that angled the Leap Motion down by 30 degrees.\nThis allowed for users to interact with a virtual environment in which their arms may be held in a biomechanically\nless stressful location, rather than up and in front of their face. To validate the configuration, 15 participants completed\na specially designed task which involved pressing virtual buttons in a given location. The button pressing\ntask was performed in three configurations that compared the angled mount against the standard forward facing\nmount. Results indicate that the angled mount eliminates tracking loses, whilst producing comparable accuracy\nagainst the control condition and allowing the participant to interact in a more natural arm posture.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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