MétaCan
Menu
Back to cohort
Record W3160417468

Measurement of spontaneous body sway during quiet stand using UWB sensor

2017· article· en· W3160417468 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

VenueIEEE Conference Proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsCarleton University
Fundersnot available
KeywordsRadarQUIETBalance (ability)Ultra-widebandTime domainComputer sciencePhysical medicine and rehabilitationTelecommunicationsMedicineComputer visionPhysics
DOInot available

Abstract

fetched live from OpenAlex

Reduced postural stability is a major contributor to poor balance increasing risk of fall especially among older adults. Monitoring of postural stability on a regular basis may lead to early detection of declining balance and providing an opportunity for timely intervention. Ultra-Wide Band Impulse Radar (UWB-IR) technology has been proposed for security, rescue and vital sign monitoring. The advantage of UWB radar is that it is non-invasive and can be applied for home monitoring. This paper presents the application of UWB radar to measure spontaneous body sway during quiet standing. Three frequency domain based measurement parameters for spontaneous sway are presented. A trial was conducted using four volunteers to demonstrate the ability of the UWB radar to detect body sway.

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 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 score0.005
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 communication0.0000.001
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 head0.042
GPT teacher head0.249
Teacher spread0.207 · 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