MétaCan
Menu
Back to cohort
Record W2167140366 · doi:10.1109/ccece.2002.1013098

A posture monitoring system using accelerometers

2003· article· en· W2167140366 on OpenAlexaff
R.J. Nevins, N.G. Durdle, V.J. Raso

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAccelerometerData loggerSagittal planeComputer scienceSimulationActivity monitorComputer hardwarePhysical medicine and rehabilitationPhysical activityMedicineOperating system

Abstract

fetched live from OpenAlex

A new method of monitoring spinal posture in the sagittal plane is presented. Posture is measured during activities of daily living utilizing accelerometer inclinations of six points along a subject's spine. The over sampled, low frequency filtered data can be monitored and collected over extended periods (up to four weeks) utilizing the inexpensive, low-power, portable data logger developed in the course of this research. The data logger utilizes 7 processors to collect and store data onto an MS-DOS formatted CompactFlash card for later analysis. Two trials were done: regimented postures across a one hour period and unregimented activities during a five hour period. Data was then visualized graphically and compared to noted postures and activities. The system was designed to be accurate to within /spl plusmn/0.5/spl deg/. Measured precision was found to be within /spl plusmn/0.39/spl deg/. This system will be useful for monitoring changes in back curvature resulting from surgery or treatment.

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 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 score0.055
Threshold uncertainty score0.309

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 head0.061
GPT teacher head0.310
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations35
Published2003
Admission routes1
Has abstractyes

Explore more

Same topicAutomotive and Human Injury BiomechanicsFrench-language works237,207