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Record W2903568723 · doi:10.1109/naecon.2018.8556832

A Clip-on Shoe-Mounted Wearable System for Gait Analysis

2018· article· en· W2903568723 on OpenAlexaff
Pooya Merat, Edward J. Harvey, Georgios D. Mitsis, Vamsy P. Chodavarapu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGait Recognition and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsGait analysisWearable computerComputer scienceGaitPhysical medicine and rehabilitationSimulationEmbedded systemMedicine

Abstract

fetched live from OpenAlex

In this work, we present a low-cost miniature foot-mounted positioning system and its potential for gait analysis. The system includes an inertial measurement unit and three time-of-flight proximity sensors. The addition of proximity sensors can provide an absolute measure for real-time vertical reference for the inertial sensor fusion. An extended Kalman filter is used for sensor fusion which uses the proximity sensor measurements and zero velocity updates to correct for the inertial integration drift. Monitoring of orientation of foot and vertical distance is used to enhance detection of zero velocity periods. The steps are segmented based on the zero velocity periods, and different measures such as foot hight, vertical and horizontal speeds are depicted in graphs.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0170.006

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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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 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

Citations5
Published2018
Admission routes1
Has abstractyes

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