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Record W7006064644

Standardized Application of Force Plate-based Measures of Standing Balance in the Sub-acute Stage of Stroke Recovery

2022· dissertation· W7006064644 on OpenAlexfundno aff

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchUniversity of TorontoToronto Rehabilitation InstituteHeart and Stroke Foundation of Canada
KeywordsBalance (ability)Stroke (engine)Center of pressure (fluid mechanics)Force platformRehabilitationReliability (semiconductor)Concurrent validity
DOInot available

Abstract

fetched live from OpenAlex

People with stroke have poor balance in standing and moving, and experience frequent falls. Impaired balance is a major risk factor for falls in stroke. Therefore, it is important to objectively investigate balance difficulties to develop effective rehabilitation and falls-prevention strategies. Force plate-based balance measures have previously been used to inform clinicians and researchers about balance impairments in the stroke population; however, little is known about their measurement properties, particularly in sub-acute stroke. The overall goal of this dissertation was to establish reliability, validity, and responsiveness of force plate-based measures in sub-acute stroke, and to determine the measures with the best measurement properties. Study 1 established relative and absolute reliabilities for sixteen balance measures, and demonstrated that directional weight-bearing asymmetry (indicates uneven weight distribution), speeds of centre of pressure (indicates neuromuscular control needed for regulating postural fluctuations), and symmetry index (represents contributions of each lower extremity in controlling balance) had the highest relative reliability and lowest measurement error in sub-acute stroke. Study 2 examined concurrent validity of reliable force plate-based measures, and their ability in discriminating different groups. This study found that speed of centre of pressure along the anterior-posterior axis had the highest concurrent validity, while weight-bearing asymmetry had the best capacity to distinguish between people with and without a history of falls, and also between those at high versus low-moderate risks of falls. In Study 3, responsiveness of reliable force plate-based measures, following a period of routine inpatient rehabilitation, was studied. Speed of centre of pressure along the medial-lateral axis, and weight-bearing asymmetry had the highest responsiveness. Additionally, weight-bearing asymmetry and symmetry index were more responsive in individuals who had higher initial reliance on their non-paretic lower extremity for controlling standing balance. Combined, these findings suggest that weight-bearing asymmetry, and speeds of centre of pressure along the anterior-posterior and medial-lateral directions have the overall best measurement properties, which can be used to precisely study balance in people with sub-acute stroke.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.317
Teacher spread0.304 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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