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Record W2994218988 · doi:10.3390/app9245310

Human Balance in Response to Continuous, Predictable Translations of the Support Base: Integration of Sensory Information, Adaptation to Perturbations, and the Effect of Age, Neuropathy and Parkinson’s Disease

2019· article· en· W2994218988 on OpenAlexaff
Antonio Nardone, Marco Schieppati

Bibliographic record

VenueApplied Sciences · 2019
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsMcGill UniversityJewish Rehabilitation Hospital
Fundersnot available
KeywordsPhysical medicine and rehabilitationBalance (ability)Sensory systemParkinson's diseaseDynamic balancePsychologyCognitive psychologyDiseaseNeuroscienceMedicineEngineeringPathology

Abstract

fetched live from OpenAlex

This short narrative review article moves from early papers that described the behaviour of healthy subjects balancing on a motorized platform continuously translating in the antero-posterior direction. Research from the laboratories of two of the authors and related investigations on dynamic balancing behaviour are briefly summarized. More recent findings challenging time-honoured views are considered, such as the statement that vision plays a head-in-space stabilizing role. The time interval to integrate vision or its withdrawal in the balancing pattern is mentioned as well. Similarities and differences between ageing subjects and patients with peripheral or central disorders are concisely reported. The muscle activities recorded during the translation cycles suggest that vision and amplitude changes of the anticipatory postural activities play a predominant role in controlling dynamic balance during prolonged administration of the predictable perturbation. The potential of this paradigm for rehabilitation of balance problems is discussed.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.178

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.014
GPT teacher head0.297
Teacher spread0.283 · 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 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

Citations16
Published2019
Admission routes1
Has abstractyes

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