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Neckband-type Self-powered Pulsewave Sensor for Continuous Blood Pressure Monitoring

2025· article· en· W4416960760 on OpenAlexafffundabout
Tae‐Ho Kim, Dominic Jaworski, Rakesh Sethi, Elise Huisman, Edward J. Park

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsSimon Fraser University
FundersMitacs
KeywordsContinuous monitoringWearable computerRemote patient monitoringBlood pressurePulse (music)Wireless sensor networkContinuous assessmentPressure sensorWork (physics)

Abstract

fetched live from OpenAlex

For effective continuous blood pressure (BP) monitoring at home, the system should be portable, user-friendly, and comfortable for the patient, ensuring convenience during continuous data collection. In this paper, we report a wearable neckband-type earphone designed for continuous monitoring of cardiovascular symptoms and BP in a non-invasive and wireless manner via a self-powered pulse wave (SPP) sensor. The SPP exhibits a sensitivity of 19.88 mV/Pa, allowing for the measurement of human pulse waves directly on the skin. Additionally, its low energy consumption, achieved through a triboelectric mechanism, enables the development of user-friendly auxiliary care systems, such as continuous BP monitoring integrated with seamless patient-doctor remote communication systems. This work provides an efficient and cost-effective approach toward active and personalized health condition monitoring.Clinical Relevance- Currently, the ratio of medical doctors to patients in hospitals in British Columbia, Canada, is approximately 2.47 per 1,000 individuals . [1] This research, which focuses on out-of-clinic care services for cardiovascular symptoms, aims to reduce the burden on clinicians by enabling continuous remote monitoring and management.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow)
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 score0.133
Threshold uncertainty score1.000

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 head0.008
GPT teacher head0.230
Teacher spread0.222 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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