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Record W2007423642 · doi:10.1109/memb.2003.1195695

Strategies for dynamic stability during adaptive human locomotion

2003· review· en· W2007423642 on OpenAlexafffund
A.E. Patla

Bibliographic record

VenueIEEE Engineering in Medicine and Biology Magazine · 2003
Typereview
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Waterloo
FundersUniversity of WaterlooSimon Fraser University
KeywordsStability (learning theory)Kinesthetic learningVestibular systemComputer scienceBalance (ability)ModalitiesDynamic balanceControl theory (sociology)Artificial intelligenceControl (management)EngineeringNeurosciencePsychologyMachine learning

Abstract

fetched live from OpenAlex

The focus of this article is how dynamic stability is achieved during locomotion adapted for complex environments that pose dangers to stability. Biped locomotion involves sudden transition from one support surface to another during every step. Therefore, control of legged locomotion, particularly stability, is difficult. We have discussed in detail the various strategies that are available to maintain balance during locomotion. Control of stability and hence locomotion is facilitated by the interplay between various strategies during adaptive locomotion. Sensory information from the three modalities (visual, vestibular, and kinesthetic inputs), knowledge, and prior experience all play a critical role in the control of dynamic stability. While much is known, many details remain to be filled in to complete our understanding of how dynamic stability is maintained during locomotion.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.104
GPT teacher head0.425
Teacher spread0.321 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations243
Published2003
Admission routes2
Has abstractyes

Explore more

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