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Record W1991711416 · doi:10.1109/tce.2012.6311332

Three dimensional touchless tracking of objects using integrated capacitive sensors

2012· article· en· W1991711416 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.

Bibliographic record

VenueIEEE Transactions on Consumer Electronics · 2012
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCapacitive sensingRobustness (evolution)CapacitanceComputer scienceTracking (education)Electronic engineeringElectronicsNoise (video)Tracking systemEngineeringElectrical engineeringArtificial intelligenceElectrodeKalman filter

Abstract

fetched live from OpenAlex

In this paper, a capacitive motion tracking system is proposed for detecting the motion of a user's hand or finger as s/he interacts with mobile computing devices such as cellular phones and tablets. The main benefits of using capacitive sensing technique over the other existing ones are its low power dissipation, ease of integration, cost effectiveness, and noise immunity. A differential sensing method has been implemented to enhance the robustness and accuracy of capacitance sensing. Simulation results are found to be in good agreement with experimental data in predicting the behavior of the sensing system consisting of sensing electrodes and readout electronics. Experimental measurements demonstrate the applicability of the proposed system in tracking user's finger within a 10cm range from the sensor's plane.

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 categoriesMeta-epidemiology (narrow)
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 score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.292
Teacher spread0.236 · 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