Sensory feedback curbs the impact of nGVS on postural control in older adults
Bibliographic record
Abstract
Noisy galvanic vestibular stimulation (nGVS) has been shown to improve postural control. However, the focus has been on the vestibular system, failing to account for other sensory inputs. The aim of the present study was thus to examine the relative impact of the various sensory feedback sources on the improvement of postural control following nGVS in older adults. Fourty-seven participants (20 controls; 27 older adults) were recruited for this study. Participants performed the modified clinical test of sensory integration as part of the postural control assessment. Older adults received an nGVS or sham stimulation which was compared to their baseline measurements and to an optimal performance (control group comprised of young adults). Results suggest that the nGVS-induced improvement of postural control in older individuals is significant only in conditions where visual and somatosensory feedback were hindered.The data also suggest that improvements in these conditions is more significant in individuals with reduced vestibular feedback. The study confirms the potential impact of nGVS for the rehabilitation of balance difficulties in the elderly population, most particularly in conditions with less reliable somatosensory and visual inputs. nGVS effects are thus modulated by sensory feedback with a dominant effect of somatosensory and visual sensory cues.
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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 | 0.003 |
| 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) | 0.002 | 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".