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Record W2925813576 · doi:10.1109/jerm.2019.2909386

RF Injection Network Development for Testing of Active Implantable Medical Devices Exposed to RF Fields in 1.5 T MRI Systems

2019· article· en· W2925813576 on OpenAlexafffund
Ali Attaran, William B. Handler, Blaine A. Chronik

Bibliographic record

VenueIEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology · 2019
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsAttenuator (electronics)Radio frequencyElectronic engineeringRF power amplifierComputer scienceElectronic componentEngineeringElectrical engineeringAttenuationAmplifierPhysics

Abstract

fetched live from OpenAlex

This paper presents the design, construction, and testing of an RF injection network for MR-conditional medical testing of devices for use within 1.5 T MRI scanners (i.e., frequency of 63.4 MHz). The system was developed to meet the requirements of ISO/TS 10974:2018(E). A directional lumped element coupler, power splitter, an attenuator/isolator, low-pass filter, and high-pass filter were designed and implemented as part of the network. The RF injection network was developed in both a compact version implemented in a single PCB and discrete PCB version for use in different situations. The performance of each designed component was simulated and compared to measurement results. As an application example, a neuromodulation system was tested using the developed RF injection network for conductive emission testing.

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)0.001
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 score0.296
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.018
GPT teacher head0.272
Teacher spread0.254 · 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

Citations5
Published2019
Admission routes2
Has abstractyes

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Same venueIEEE Journal of Electromagnetics RF and Microwaves in Medicine and BiologySame topicElectrostatic Discharge in ElectronicsFrench-language works237,207