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Record W3049182323 · doi:10.1123/jmld.2019-0028

Use of Acoustic Feedback to Change Gait Patterns: Implementation and Transfer to Motor Learning Theory—A Scoping Review

2020· article· en· W3049182323 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 Motor Learning and Development · 2020
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsGaitMotor learningPsychologyAudio feedbackPhysical medicine and rehabilitationMotor skillPopulationCognitive psychologyDevelopmental psychologyMedicineEngineeringNeuroscience

Abstract

fetched live from OpenAlex

Changing gait parameters through acoustic feedback is a promising approach in gait therapy. The question remains to what extent, if any, the theories and concepts of motor learning have been taken into account for acoustic feedback systems development. Fifteen studies were identified for further analysis using a scoping review framework, among which seven had individuals with disordered gait as their population and eight incorporated healthy individuals. It was found that most studies used error feedback and did not test for long-term effects on gait parameters. It can be concluded that future studies should apply motor learning theories and concepts to the development of acoustic feedback devices for gait therapy.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score0.440

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 head0.048
GPT teacher head0.281
Teacher spread0.233 · 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