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ThumbJoy: Using the Thumb’s Metacarpophalangeal Joint as a Joystick Input Device

2023· article· en· W4389296625 on OpenAlexaff
Kyungeun Jung, Kun-Woo Song, Seungmin Lee

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsThumbJoystickMetacarpophalangeal jointComputer scienceIndex fingerVirtual realityHaptic technologyComputer visionImmersion (mathematics)Inertial measurement unitJoint (building)SimulationArtificial intelligenceEngineeringMathematicsMedicine

Abstract

fetched live from OpenAlex

We introduce ThumbJoy, which utilizes the physical movement of the left thumb metacarpophalangeal (MCP) joint along with its psychophysical qualities as a joystick. Using an inertial measurement unit (IMU), ThumbJoy avoids the restraints of hand tracking occlusion, allowing more contact area for the thumb thus providing self-haptics. We first conducted a pilot study of 20 participants to systematically analyze the characteristics of the MCP joint. Using these results, we implemented an algorithm that converts joint movement to a planar 2D axis movement. We then conducted a user study comparing ThumbJoy with conventional interaction mediums in a virtual reality (VR) environment. Through this, we demonstrate that ThumbJoy can provide an intuitive method of control while increasing immersion and enjoyment in VR along with the use of self-haptics.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.182
GPT teacher head0.359
Teacher spread0.177 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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