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Record W4284960607 · doi:10.3390/act11070187

PVDF Energy Harvester for Prolonging the Battery Life of Cardiac Pacemakers

2022· article· en· W4284960607 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

VenueActuators · 2022
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFinite element methodCantileverVoltageEnergy harvestingPower (physics)PiezoelectricityBattery (electricity)Displacement (psychology)Energy (signal processing)EngineeringElectrical engineeringStructural engineeringMechanical engineeringComputer sciencePhysics

Abstract

fetched live from OpenAlex

Patients who have an implantable cardiac pacemaker that survive beyond the operational life of the device require replacement surgeries that increase healthcare costs and may possibly introduce post-operative complications such as infection. In this paper, we propose a piezoelectric energy harvester design for powering pacemakers to extend their operational life. The design uses a thin strip of piezoelectric PVDF that captures energy from bending of the lead wire. We assemble a prototype to validate a finite element model, and then use the finite element model to characterize the power output of the design based on a cantilever beam loading condition, where displacement at the cantilever tip simulated heart motion. The voltage output from the prototype was compared to the output from the finite element simulation and the finite element simulation provided a good estimate of the voltage output. Further finite element analysis showed that for a 10 cm long section of the proposed design, a 9.1 mm tip displacement provided a power output of 1 μW and a voltage output of ±1.4 V during each cycle.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.458

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 head0.011
GPT teacher head0.196
Teacher spread0.184 · 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