Fukuda and Babinski-Weil tests: Within-subject variability and test-retest reliability in nondisabled adults
Bibliographic record
Abstract
The Fukuda Stepping Test and the Babinski-Weil test are clinical assessments that presumably reveal unilateral vestibular hypofunction. However, abnormal performances on both of these two tests have been found in nondisabled individuals. This study compared measures of lateral and longitudinal displacements and body rotation for both tests, as well as the within-subject variability and test-retest reliability of the measures. In addition, correlations between hand and foot dominance and these measures were studied. Fifty young, nondisabled participants performed three trials of the 100-step Fukuda test and three trials of the Babinski-Weil test. The testing session was repeated 7 d later (retest). Lateral displacement, body rotation, and within-subject variability of these two measures were larger on the Fukuda than the Babinski-Weil test. No difference in test-retest reliability was found between the two tests, and a significant correlation was found between body rotation on the Fukuda test and score on the Waterloo Footedness Questionnaire. There may have been smaller variability in results of the Babinski-Weil test because it contains fewer steps (36) than the 100-step Fukuda test. Future research should compare tests with an equal number of steps; but, in the meantime, the Babinski-Weil test seems to have better psychometric properties than the Fukuda test, at least in nondisabled individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".