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Record W6962971805 · doi:10.21227/wysp-gt69

Wearable Physiological and Blood Pressure Measurements During Activities of Daily Living

2021· dataset· en· W6962971805 on OpenAlexaffabout

Bibliographic record

VenueIEEE DataPort · 2021
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhotoplethysmogramBlood pressureVESTWearable computerActivity monitorPlethysmographSphygmomanometerThigh

Abstract

fetched live from OpenAlex

The purpose of this data collection was for the validation of a cuffless blood pressure estimation model during activities of daily living. Data were collected on five young healthy individuals (four males, age 28 ± 6.6 yrs) of varied fitness levels, ranging from sedentary to regularly active, and free of cardiovascular and peripheral vascular disease. Arterial blood pressure was continuously measured using finger PPG (Portapres; Finapres Medical Systems, the Netherlands). The Astroskin wearable body metrics vest (Carré Technologies Inc., Canada) was used for electrocardiogram (ECG), photoplethysmogram (PPG), and tri-axial acceleration measurements. The PAT was calculated internally at 256 Hz. An iPhone SE was fixed to the thigh to record the orientation to identify the body posture.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.014

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 head0.056
GPT teacher head0.278
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreDataset

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

Citations3
Published2021
Admission routes2
Has abstractyes

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