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Record W1974666882 · doi:10.1115/1.4005462

Foot Placement and Balance in 3D

2012· article· en· W1974666882 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Computational and Nonlinear Dynamics · 2012
Typearticle
Languageen
FieldEngineering
TopicRobotic Locomotion and Control
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPendulumDynamic balanceInverted pendulumBalance (ability)GaitEstimatorControl theory (sociology)Work (physics)Multibody systemComputer scienceMathematicsPhysical medicine and rehabilitationEngineeringPhysicsClassical mechanicsNonlinear systemArtificial intelligence

Abstract

fetched live from OpenAlex

Humans use carefully chosen step locations to restore their balance during locomotion and in response to perturbations. Understanding the relationship between foot placement and balance restoration is key to developing useful dynamic human balance diagnostic tests and balance rehabilitation treatments. The link between foot placement and balance restoration is studied in this paper using a simplified monopedal model that has a circular foot, coined the Euler pendulum. The Euler pendulum provides a convenient method of studying the stability properties of three-dimensional (3D) bipedal systems without the burden of large system equations typical of multibody systems. The Euler pendulum has unstable regions of its state-space that can be made to transition to a statically stable region using an appropriate foot placement location prior to contacting the ground. The planar foot placement estimator (FPE) method developed by Wight et al. is extended in this work in order to find foot placement locations in 3D to balance the 3D Euler pendulum. Preliminary experimental data shows that the 3D foot placement estimator (3DFPE) location corresponds very well with human foot placement during walking, gait termination, and when landing from a jump. In addition, a sensitivity analysis revealed that the assumptions of the 3DFPE are reasonable for human movement. Metrics for bipedal instability and balance performance suggested in this work could be of practical significance for health care professionals.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.168

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 head0.005
GPT teacher head0.214
Teacher spread0.208 · 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