MétaCan
Menu
Back to cohort
Record W2543189930 · doi:10.1109/iembs.2004.1404207

Hybrid RF/IR transcutaneous telemetry for power and high-bandwidth data

2005· article· en· W2543189930 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

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsCybernet Systems Corporation (Canada)
FundersNational Institutes of Health
KeywordsTelemetryRadio frequencyBandwidth (computing)Electrical engineeringComputer scienceElectromagnetic compatibilityDissipationElectronic engineeringEngineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

As neuroprosthetic control systems continue to advance and increase in channel density, there will be a constant need to deliver data at higher bandwidths in and out of the body. Currently, RF telemetry and inductive coupling are the most commonly used methods for transmitting power and electronic data between implants and external systems, and state of the art systems can deliver data rates up to hundreds of kilobits per second. However, it is difficult to operate implanted medical RF links at higher data rates due to electromagnetic compatibility (EMC) constraints. In this study, we investigate the potential for hybrid telemetry systems that use constant-frequency RF inductive links for power and transcutaneous infrared (IR) signals for data. We show that with commercially available infrared communication components, data rates of up to 40 Mbits per second can be transmitted out across 5 mm of skin with an internal device power dissipation under 100 mW.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.490

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 communication0.0000.001
Open science0.0010.000
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 head0.037
GPT teacher head0.271
Teacher spread0.234 · 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

Quick stats

Citations50
Published2005
Admission routes1
Has abstractyes

Explore more

Same topicNeuroscience and Neural EngineeringFrench-language works237,207