Responses to untrained and unexpected balance perturbations following reactive balance training among people with chronic stroke: a feasibility study
Bibliographic record
Abstract
TRIAL DESIGN: Pilot study embedded within an assessor-blinded parallel randomized controlled trial. OBJECTIVE: To determine the feasibility and utility of using unexpected and untrained balance perturbations in future studies assessing the efficacy of reactive balance training (RBT) post-stroke. METHODS: Participants were community-dwelling adults with chronic stroke who could walk independently without a gait aid for > 10 m. Participants were assigned using blocked stratified randomization to six weeks of RBT or "traditional" balance training (control group). Outcomes were proportion of unexpected slips triggered as intended; state anxiety, perceptions of situations, and participants' subjective responses to the unexpected slip perturbation; and spatiotemporal and kinematic features of unperturbed and perturbed walking pre- and post-training. Assessors were blinded to group allocation. RESULTS: 28 participants were randomized (15 RBT, 13 control). Nine RBT participants and seven control participants were eligible and consented to additional data collection for the pilot study. 12 participants (six per group) completed the post-training unexpected slip data collection and were included in analysis of pilot objectives. All unexpected slips triggered as intended. Participants did not report increased state anxiety or concerns about the unexpected slip. Spatiotemporal and kinematic data suggested better stability following the unexpected slip for RBT than control participants; however, there were also between-group differences in spatiotemporal and kinematic features of walking pre- and post-training. CONCLUSIONS: Unexpected slips are feasible in research. However, their value as outcomes in clinical trials may depend on balancing the groups on prognostic factors. TRIAL REGISTRATION: ISRCTN05434601.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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.
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".