MétaCan
Menu
Back to cohort
Record W2100573379 · doi:10.1109/memsys.2008.4443595

A hydrogel-based wireless sensor using micromachined variable inductors with folded flex-circuit structures for biomedical applications

2008· article· en· W2100573379 on OpenAlexafffund
V. Sridhar, Kenichi Takahata

Bibliographic record

VenueProceedings, IEEE micro electro mechanical systems · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceInductorInductanceElectromagnetic coilOptoelectronicsCapacitorWirelessElectrical engineeringVoltageComputer scienceEngineering

Abstract

fetched live from OpenAlex

This paper reports a flexible, inductive wireless sensor that can be combined with a variety of hydrogel materials for biomedical applications. The variable inductor is formed by folding coplanar dual spiral coil with 5–10 mm size that are microfabricated using 50-µm-thick copper-clad polyimide film so that when folded, the two coils are aligned to each other and the mutual inductance depends on the gap between the aligned coils. A hydrogel element is sandwiched by the folded substrate to modulate the gap, or inductance of the device as it swells/deswells depending on the target parameter. The response of a variable inductor to the displacement of the coils is measured to be 0.40 nH/µm. A sensitivity of 113 ppm/μm in wireless frequency measurement is obtained using the passive resonant device that combines the variable inductor with a fixed capacitor. The resonant devices are coupled with a commercial hydrogel wound dressing as well as pH-sensitive poly(vinyl alcohol)-poly(acrylic acid) hydrogel. Wireless monitoring of the swelling of the wound dressing is experimentally demonstrated.

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 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 score0.303
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.225
Teacher spread0.203 · 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.

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

Citations8
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueProceedings, IEEE micro electro mechanical systemsSame topicAdvanced Sensor and Energy Harvesting MaterialsFrench-language works237,207