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Record W4407385018 · doi:10.1038/s44385-025-00007-z

Neckband-type earphone for continuous monitoring of cardiovascular symptoms via self-powered box knot pulse-wave sensor

2025· article· en· W4407385018 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

Venuenpj Biomedical Innovations. · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsSimon Fraser University
FundersMitacs
KeywordsKnot (papermaking)Pulse Wave AnalysisPulse (music)AcousticsMedicineComputer sciencePhysicsPulse wave velocityMaterials scienceInternal medicineTelecommunicationsComposite materialBlood pressure

Abstract

fetched live from OpenAlex

Abstract Blood pressure (BP) assessment is one of the essential vital signs in the clinical field because of its significant relation with various chronic diseases. For effective continuous BP monitoring at home, the system should be portable, user-friendly, and comfortable for the patient, ensuring convenience during continuous data collection. Here, a wearable neckband-type earphone for continuous monitoring of cardiovascular symptoms and BP in a non-invasive and wireless manner via a Self-powered Box Knot Pulsewave sensor (SBKP) has been reported. The multi-stacked architecture of the SBKP, inspired by the knotting craft, holds a sensitivity and resolution of 38.17 mV Pa −1 , and 0.006 kPa, respectively, which allows for the measurement of the human pulse waves from the cheek, neck, and wrist. Additionally, its low energy consumption sensor, achieved by the triboelectric mechanism, enables us to develop additional user-convenient auxiliary care systems: continuous BP monitoring with potential music therapy.

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 score0.273
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.243
Teacher spread0.229 · 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