MétaCan
Menu
Back to cohort

Radar-Based Human Pulse Sensing through a Resonator-Based Superstrate

2024· article· en· W4400650756 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadar Systems and Signal Processing
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaMitacsGoogle
KeywordsResonatorRadarPulse (music)Materials scienceRadar detectionOptoelectronicsComputer scienceElectronic engineeringAcousticsTelecommunicationsPhysicsEngineering

Abstract

fetched live from OpenAlex

This work presents a novel approach where a superstrate is used to re-purpose a commercial off-the-shelf mm-wave radar by Infineon for near-field human pulse sensing. The superstrate is realized through low-cost PCB technology. it consists of couplers, a microstrip line, and a transverse slot in the ground plane. The superstrate was designed using full-wave EM simulations, along with a numerical-based model to predict the output of the radar in the presence of the superstrate. The superstrate was fabricated, and the combined sensor was tested on human participants. The preliminary measurement results match the expected theoretical pulse waveform. Hence, proving the feasibility of the proposed approach in near-field pulse sensing applications.

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: none
Teacher disagreement score0.759
Threshold uncertainty score0.758

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 head0.020
GPT teacher head0.248
Teacher spread0.228 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same topicRadar Systems and Signal ProcessingFrench-language works237,207