Force platform feedback for standing balance training after stroke
Bibliographic record
Abstract
BACKGROUND: Standing balance deficits are common in individuals after stroke. One way to address these deficits is to provide the individual with feedback from a force platform while balance activities are performed. The feedback can take visual and/or auditory form. OBJECTIVES: To determine if visual or auditory force platform feedback improves the clinical and force platform standing balance outcomes in clients with stroke. SEARCH STRATEGY: We searched the Cochrane Stroke Group trials register (last searched December 2003), and the following electronic bibliographic databases: the Cochrane Central Register of Controlled Trials (The Cochrane Library Issue 3, 2003), MEDLINE (1966 to May 2003), EMBASE (1974 to May 2003), CINAHL (1982 to May 2003), PEDro (May 2003), CIRRIE (May 2003) and REHABDATA (May 2003). Reference lists of articles were reviewed and manufacturers of equipment were contacted. SELECTION CRITERIA: Randomized controlled trials comparing force platform with visual feedback and/or auditory feedback to other balance treatments. DATA COLLECTION AND ANALYSIS: Two reviewers independently assessed trials for inclusion, methodological quality, and data extraction. Trials were combined for meta-analysis according to outcome and type of feedback. MAIN RESULTS: We included seven trials (246 participants). Force platform feedback did not improve clinical measures of balance when moving or walking (Berg Balance Scale and Timed Up and Go). Significant improvements in laboratory force platform indicators of stance symmetry were found for regimens using visual feedback (standardised mean difference (SMD) -0.68, 95% confidence interval (CI) -1.31 to -0.04, p = 0.04) and the concurrent visual and auditory feedback (weighted mean difference (WMD) -4.02, 95% CI -5.99 to -2.04, p = 0.00007). There were no significant effects on laboratory postural sway indicators, clinical outcomes or measures of function at follow-up assessment. REVIEWERS' CONCLUSIONS: Force platform feedback (visual or auditory) improved stance symmetry but not sway in standing, clinical balance outcomes or measures of independence.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".