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Real-Time Heart Rate Monitoring via Batteryless RFID Tags

2024· article· en· W4400648299 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
TopicIoT-based Smart Home Systems
Canadian institutionsUniversity of Alberta
FundersMinistère de la Défense NationaleInnovation for Defence Excellence and Security
KeywordsComputer scienceEmbedded system

Abstract

fetched live from OpenAlex

This paper introduces a system wherein a battery-less RFID tag is capable of sensing the heartbeats of a mobile individual, while an RFID reader wirelessly detects them. The key advantage of the designed tag is its transmission of sensed data through the phase of the reflected signal to the reader, rather than its amplitude, rendering it more immune to noise and disturbance. The tag comprises three blocks: heartbeat detection, energy harvester, and three-port RFID structure. The main power consumption of the proposed tag is by the microcontroller, which consumes a maximum of 1.69 μA at a 3.6 V power supply, making it a suitable option for energy harvesting applications. The minimum detectable pulse width of heartbeats by this system is measured at 60 ms, indicating that heart rates up to 250 bpm can be detected by this system, considering a duty cycle equal to 25% for the pulse.

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 categoriesInsufficient payload (model declined to judge)
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 score0.408
Threshold uncertainty score0.996

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)0.0000.005

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 head0.007
GPT teacher head0.219
Teacher spread0.211 · 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

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