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Record W4388534864 · doi:10.1080/14763141.2023.2275258

The one-week and three-month reliability of acceleration outcomes from an insole-embedded inertial measurement unit during treadmill running

2023· article· en· W4388534864 on OpenAlexafffund
Sean K.T. Gaiesky, Lauren Fridman, Tom Michie, Paul Blazey, Nicholas Trân, Amy Schneeberg, Christopher Napier

Bibliographic record

VenueSports Biomechanics · 2023
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsVancouver Coastal Health Research InstituteVancouver Coastal HealthStemcell TechnologiesSimon Fraser University
FundersMitacsMichael Smith Health Research BC
KeywordsReliability (semiconductor)TreadmillAccelerationTerm (time)GaitPhysical medicine and rehabilitationAccelerometerInertial measurement unitPhysical therapyInertial frame of referenceMedicineMathematicsSimulationComputer sciencePhysics

Abstract

fetched live from OpenAlex

Inertial measurement units (IMUs) represent an exciting opportunity for researchers to broaden our understanding of running-related injuries, and for clinicians to expand their application of running gait analysis. The primary aim of our study was to investigate the 1-week (short-term) and 3-month (long-term) reliability of peak resultant, vertical, and anteroposterior accelerations derived from insole-embedded IMUs. The secondary aim was to assess the reliability of peak acceleration variability and left–right limb symmetry in all directions over the short and long term. A sample of healthy adult rearfoot runners (n = 23; age 41.7 ± 11.2 years) ran at a variety of speeds (2.5 m/s, 3.0 m/s, and 3.5 m/s) on a treadmill in standardised footwear with insole-embedded IMUs in each shoe. Peak accelerations exhibited good to excellent short-term reliability and moderate to excellent long-term reliability in all directions. Peak acceleration variability showed poor to good short- and long-term reliability, whereas the symmetry of peak accelerations demonstrated moderate to excellent and moderate to good short- and long-term reliability, respectively. Our results demonstrate how insole-embedded IMUs represent a viable option for clinicians to measure peak accelerations within the clinic.

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)0.001
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 score0.502
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.054
GPT teacher head0.249
Teacher spread0.195 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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