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Record W4413405550 · doi:10.3389/fnhum.2025.1654630

Posturographic analysis of induced emotion: a scoping review

2025· review· en· W4413405550 on OpenAlexaff
Adrien Hakimi, Adrien Nourry, Harold Mouras, Thierry Lelard

Bibliographic record

VenueFrontiers in Human Neuroscience · 2025
Typereview
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsPsychologyPhysical medicine and rehabilitationCognitive psychologyMedicine

Abstract

fetched live from OpenAlex

Posturography is a useful technique that allows to explore postural control, a complex motor skill enabling body orientation and stability. Analyzing postural control is one way to assess body responses to various emotional stimuli. By examining the displacement of the center of pressure, it is possible to investigate postural adjustments of individuals confronted with emotional stimuli. This scoping review focuses on the use of this methodology over the last decade. Forty-eight studies were included, covering a wide range of emotional themes studied around the world. Posturography appears to be a frequently used tool for assessing responses to emotional content. There is a high variability in the methods used in these studies and sometimes a lack of information regarding methodological concerns. This review provides methodological recommendations to standardize reporting in posturographic studies of emotions. It is likely that more and more topics will be studied in the coming years.

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)0.006
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0120.011
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.048
GPT teacher head0.402
Teacher spread0.353 · 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 designSystematic review
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

Citations1
Published2025
Admission routes1
Has abstractyes

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