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Record W2135491399 · doi:10.1109/tbme.2008.921161

Tooth-Click Control of a Hands-Free Computer Interface

2008· article· en· W2135491399 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

VenueIEEE Transactions on Biomedical Engineering · 2008
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsUniversity of Alberta
FundersDalhousie University
KeywordsComputer scienceComputer mouseCursor (databases)Dwell timeInterface (matter)SoftwareAccelerometerControl systemHuman–computer interactionComputer hardwareComputer visionEngineeringMedicineOperating system

Abstract

fetched live from OpenAlex

People with severe upper limb paralysis use devices that monitor head movements to control computer cursors. The three most common methods for producing mouse button clicks are dwell-time, sip-and-puff control, and voice-recognition. Here, we tested a new method in which small tooth-clicks were detected by an accelerometer contacting the side of the head. The resulting signals were paired with head tracking technology to provide combined cursor and button control. This system was compared with sip-and-puff control and dwell-time selection. A group of 17 people with disabilities and ten people without disabilities tested each system by producing mouse clicks as inputs to two software programs. Tooth-click/head-mouse control was much faster than dwell-time control and not quite as fast as sip-and-puff control, but it was more reliable and less cumbersome than the latter.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.567

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 head0.010
GPT teacher head0.208
Teacher spread0.199 · 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