Sensory reweighting for balance in people living with Parkinson’s Disease: Postural adaptation, muscle co-contraction, and perceptual delays
Bibliographic record
Abstract
BACKGROUND: Postural instability is common in people with Parkinson's Disease (PwPD), increasing their risk of injurious falls. Evidence suggests a sensory reweighting deficit in PwPD, along with compensatory muscle co-contraction in response to postural challenges. During balance tasks requiring sensory reweighting, older adults exhibit elevated postural sway and muscle co-contraction, as well as longer perceptual delays, compared to young adults. Such responses may be exacerbated in PwPD, with implications for fall risk. RESEARCH QUESTION: The aim of this study was to assess postural sway, muscle co-contraction, and perceptual delays in PwPD and healthy age-matched controls during a sensory reweighting balance task. METHODS: Eleven PwPD and 16 control participants completed a sensory reweighting protocol: standing without vision on a fixed platform (2-min), which then undergoes a period of body sway-referencing (3-min) before returning to its fixed position (2.5-min). Anteroposterior (AP) path length, co-contraction index (CCI), and perceptual delay were analysed across task phases. RESULTS: PwPD showed a longer delay in perceiving when the body sway-referenced platform returned to a fixed position. This perceptual delay in PwPD (43.40-s) was over double that observed in control participants (21.25-s). AP path length and co-contraction aftereffects were longer in control participants than PwPD. SIGNIFICANCE: Where conditions require it, PwPD can effectively adjust their reliance on proprioceptive information for postural control. However, the significant delay shown by PwPD in perceiving changes to sensory conditions could be detrimental during everyday sensory transitions, potentially increasing fall risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".