Electrical vestibular stimulation to improve balance in older adults: a pilot randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Falls are the leading cause of injury-related hospitalizations among older adults, often linked to vestibular dysfunction. While vestibular rehabilitation therapy is a standard intervention, designed to compensate for vestibular impairment with proprioceptive and visual cues, potential cumulative effects of noisy Electrical Vestibular Stimulation (nEVS) on balance improvement in older adults are not well understood. OBJECTIVE: This study evaluated the efficacy of cumulative nEVS dosing in improving static balance, its potential mechanisms, and clinical significance. METHODS: A single-blind, pilot randomized controlled trial enrolled 40 older adults (mean age: 77.7 ± 11.8 years). Participants were randomly assigned to a Stimulation group (nEVS intervention) or Sham group. The nEVS regimen included low-amplitude wideband stimulation (± 0.35 mA, 0.001-300 Hz) for 20 min, three times weekly for six weeks. Balance performance was assessed immediately before and after nEVS using a head-mounted sensor to measure physiological vibration acceleration ('Phybrata') power as a measure of postural stability in four conditions: Floor Eyes Open, Floor Eyes Closed, Foam Eyes Open, and Foam Eyes Closed. Follow-ups occurred at 3 months and 6 months post-intervention. RESULTS: The Stimulation group exhibited significant and sustained reductions in Phybrata power with improvements observed as early as Session 3 and persisting through 6 months in Foam EC. Additionally, the Sham group demonstrated smaller reductions in Phybrata power, potentially reflecting a learning effect. CONCLUSION: nEVS may be a safe and effective intervention for improving balance in older adults. Its benefits in addressing age-related deficits in balance and sensory integration highlight its potential for fall prevention and rehabilitation. This study was retrospectively registered as a clinical trial on February 25, 2025 (NCT06846047).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".