MétaCan
Menu
Back to cohort

The One-week Reliability Of Spatiotemporal Running Gait Characteristics Using Insole-embedded Inertial Measurement Units.

2023· article· en· W4387062309 on OpenAlexaff
Sean K.T. Gaiesky, Min-Ju Kim, Meihui Li, Christopher Napier

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2023
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIntraclass correlationSwingGaitReliability (semiconductor)Inertial measurement unitTreadmillPhysical medicine and rehabilitationGait analysisSimulationComputer sciencePhysical therapyMathematicsMedicineStatisticsEngineeringReproducibilityArtificial intelligence

Abstract

fetched live from OpenAlex

Traditional running gait analysis suffers from accessibility issues due to the requirement of expensive laboratory-based equipment. Cost-effective, user-friendly insole-embedded inertial measurement units (IMUs) provide clinicians with the opportunity to democratize gait analysis. However, prior to the clinical application of insole-embedded IMUs, their reliability must be investigated. PURPOSE: To investigate the 1-week reliability of insole-embedded IMU-derived running gait spatiotemporal variables. METHODS: A total of 8 (5 males, 3 females; 6 rearfoot strike, 2 non-rearfoot strike) recreationally active adults (age: 27.1 ± 4.7 years; BMI: 21.4 ± 2.2 kg/m2) attended 2 sessions separated by 7 days. All participants completed a 3-minute warm-up at a self-selected speed before completing three 30-second trials in random order at 2.5, 3.0, and 3.5 m/s on a treadmill in standardized footwear. Spatiotemporal running gait variables (left/right ground contact time (GCT) (ms), left/right swing time (ms), flight time (ms), duty factor (DF), and step rate (steps/min)) were calculated using insole-embedded triaxial IMUs placed within each shoe. Inter-session reliability was measured using intraclass correlation coefficient (ICC) model (2,1), minimal detectable change (MDC), and the standard error of measurement (SEM). All statistical analyses were performed using SPSS (Version 27). RESULTS: Good to excellent 1-week reliability was exhibited across all speeds for step rate (ICC range: 0.84 – 0.96), flight time (0.96 – 0.97), left swing time (0.95 – 0.98), right swing time (0.93 – 0.98), left GCT (0.91 – 0.97), right GCT (0.88 – 0.94), and DF (0.93 – 0.97). Correspondingly, relatively low SEM (range: 1.1 – 4.4%) and MDC (range: 3.0 – 12.2%) values were observed for all variables across all speeds except for flight time at the 2.5 m/s speed (SEM: 6.8 %; MDC: 18.8%). As a general trend, reliability measures improved as speed increased. CONCLUSION: The results of this study suggest that insole-embedded IMUs can provide clinicians with reliable running-related spatiotemporal variables over a 1-week period. Aside from flight time at the lowest speed, the good-to-excellent ICC scores, and relatively low SEM and MDC values mean clinicians can confidently track these variables week-to-week. Supported by Mitacs.

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)0.003
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.066
GPT teacher head0.317
Teacher spread0.252 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueMedicine & Science in Sports & ExerciseSame topicDiabetic Foot Ulcer Assessment and ManagementFrench-language works237,207