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Record W4387801277 · doi:10.1145/3586183.3606713

Transferable Microgestures Across Hand Posture and Location Constraints: Leveraging the Middle, Ring, and Pinky Fingers

2023· article· en· W4387801277 on OpenAlexaff
Nikhita Joshi, Parastoo Abtahi, Raj S. Sodhi, Nitzan Bartov, Jackson Rushing, Christopher Collins, Daniel Vogel, Michael Glueck

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceLeverage (statistics)Middle fingerThumbArtificial intelligenceGestureComputer visionHuman–computer interactionAnatomyMedicine

Abstract

fetched live from OpenAlex

Microgestures can enable auxiliary input when the hands are occupied. Although prior work has evaluated the comfort of microgestures performed by the index finger and thumb, these gestures cannot be performed while the fingers are constrained by specific hand locations or postures. As the hand can be freely positioned with no primary posture, partially constrained while forming a pose, or highly constrained while grasping an object at a specific location, we leverage the middle, ring, and pinky fingers to provide additional opportunities for auxiliary input across varying levels of hand constraints. A design space and applications demonstrate how such microgestures can transfer across hand location and posture constraints. An online study evaluated their comfort and effort and a lab study evaluated their use for task-specific microinteractions. The results revealed that many middle finger microgestures were comfortable, and microgestures performed while forming a pose were preferred over baseline techniques.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.472

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 studies0.0010.000
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 head0.063
GPT teacher head0.292
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

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 designBench or experimental
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

Citations12
Published2023
Admission routes1
Has abstractyes

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