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Record W2328963433 · doi:10.1109/embc.2014.6943955

Analyzing center of pressure progression during bed exits

2014· article· en· W2328963433 on OpenAlexafffund
Zhaofen Ren, Theresa Grant, Rafik Goubran, M. El-Tanany, Frank Knoefel, Heidi Sveistrup, Martin Bilodeau, Jeffrey W. Jutai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsBruyèreUniversity of OttawaCarleton University
FundersCanadian Institutes of Health Research
KeywordsCenter of pressure (fluid mechanics)TrajectoryEvent (particle physics)Intervention (counseling)Center (category theory)Physical medicine and rehabilitationMovement (music)Computer scienceSimulationMedicineEngineeringAcousticsNursing

Abstract

fetched live from OpenAlex

This paper presents a new approach for analyzing center of pressure (COP) progression using pressure data collected from a pressure-sensitive array placed under the bed mattress. Pressure data were collected from a young female participant who was healthy and an older 78 year old female participant who had a history of falls. Information relevant to movement direction, time, path trajectory, magnitude and frequency was presented in three dimensional plots and color differentiated displays. When tested on data collected from an older participant who experienced a fall, this method of analyzing COP was able to illustrate distinct differences in bed exit patterns used pre and post fall episode. This analysis approach shows the potential to detect changes in bed exit patterns indicative of a critical health event. Future applications include home monitoring to assist with early intervention in the event of bed mobility decline.

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)0.000
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.362
Teacher spread0.342 · 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
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

Citations16
Published2014
Admission routes2
Has abstractyes

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