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Record W7117250364 · doi:10.1299/jsmermd.2025.1p1-p08

Pneumatic vibrotactile display using speakers

2025· article· en· W7117250364 on OpenAlex
Keitaro Ihara, Hiroki Ishizuka, Takefumi Hiraki, Yusuke Sakaue, Osamu Oshiro

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

VenueThe Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2025
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsAir compressorGas compressorVibrationCompressed airPresentation (obstetrics)Range (aeronautics)Sound pressurePressure sensor

Abstract

fetched live from OpenAlex

In this study, we developed a pneumatic vibrotactile display that uses sound pressure from a speaker to generate changes in air pressure, which is transmitted to the fingertip via a silicone tube to enable the presentation of vibrations over a wide bandwidth. Generally, pneumatic vibrotactile displays using air compressors have difficulty in presenting vibrations in high frequency bands, especially above 200 Hz, due to limitations in the response speed and control performance of the open/close valve. For this reason, this study attempted to construct a system that can handle a wider range of frequencies by taking advantage of the high responsiveness of the speaker. Specifically, by transmitting air pressure vibrations generated by changes in the speaker’s sound pressure to the fingertips through silicon tubes, this system enables the presentation of tactile stimuli that include high-frequency components, which has been difficult with the conventional air compressor system.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.820

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)0.0000.000

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 head0.041
GPT teacher head0.296
Teacher spread0.256 · 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