MétaCan
Menu
Back to cohort
Record W2750971774 · doi:10.1145/3123021.3123043

An empirical study of foot gestures for hands-occupied mobile interaction

2017· article· en· W2750971774 on OpenAlex
Mingming Fan, Yizheng Ding, Fang Shen, Yuhui You, Zhi Yu

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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGestureFoot (prosody)Computer scienceHuman–computer interactionGesture recognitionMobile deviceArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

User-defined foot-gesture is a promising approach to interacting with mobile devices when both hands are occupied. In this research, we first present a survey to identify how often interacting with mobile devices is needed when both hands are busy and how many tasks people commonly would like to do on the devices in such situations. We then present a study to compare a traditional approach with foot-gesture interaction in a simulated hands-occupied scenario. Results show that foot-gesture saved over 70% of the time compared with the traditional approach and was perceived more useful and satisfying.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.234

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 communication0.0000.000
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 head0.061
GPT teacher head0.407
Teacher spread0.346 · 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

Quick stats

Citations15
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicGaze Tracking and Assistive TechnologyFrench-language works237,207