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Record W2212836212 · doi:10.1109/have.2015.7359447

Contactless haptic feedback: state of the art

2015· article· en· W2212836212 on OpenAlexaff
Faisal Arafsha, Longyu Zhang, Haiwei Dong, Abdulmotaleb El Saddik

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHaptic technologyComputer scienceField (mathematics)AvatarHuman–computer interactionWork (physics)SimulationEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

This paper discusses some of the recent advances in contactless haptic feedback. We mainly discuss two research methods to produce haptic feedback in 3D space: Air-jet and ultrasound. We discuss and compare technical basics of each technology, and then give a literature review of some of the research done that is closely related to this field. This paper also surveys the stages of the design and implementation of airborne ultrasonic tactile displays (AUTD) by researchers in the University of Tokyo, as well as an application of this research done in the University of Bristol. A comparison is presented showing the main advances in the Tokyo research and the technical tests and implementation differences. A discussion follows covering possible improvements and safety issues on the contactless haptic feedback research in general. We show comments and drawbacks of the current technology. For future work in the field of mid-air haptic feedback, we propose a design method to build a "Touchable Avatar", which is a holographic display with contactless haptic feedback properties. Finally, a conclusion is provided including an outlook of the future applications in the field of contactless haptic feedback.

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 score0.142
Threshold uncertainty score0.678

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.072
GPT teacher head0.291
Teacher spread0.219 · 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

Citations29
Published2015
Admission routes1
Has abstractyes

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