The Contribution of Gait Speed and Gait Variability to Accuracy of Pedometers in People with Walking Disabilities
Bibliographic record
Abstract
PURPOSE: To determine the independent contribution of gait speed and gait variability to the accuracy of pedometers in people with neurological walking impairments. METHODS: One pedometer (Digiwalker SW-200) was positioned on each of the right and the left waistband of the participants. Participants walked 100 m at their self selected walking speed, with their usual walking aide. Pedometer counted steps were recorded and the actual number of steps taken were counted using a tally counter. Gait speed was determined from the 100m walk. To measure gait variability, participants walked on a paper walkway with ink pads on their shoes, and step length was measured over 10m. The step length coefficient of variation (standard deviation/mean) (C V) was determined individually for each person, and represented gait variability. A stepwise linear regression analysis was used to determine the independent contribution of gait speed and gait variability to error score (actual steps - pedometer recorded steps). Mean percent accuracy ([#pedometer counted steps/#actual steps] X 100) was also calculated and the sample was dichotomized by gait speed and gait variability to further explore the contribution of each to pedometer accuracy. RESULTS: Twenty eight men and 18 women (age 54 ± 14years) with neurological conditions such as stroke and multiple sclerosis volunteered to participate in this study. Fourteen participants walked with a cane, 4 with a four wheeled walker, and the remainder used no walking aides. Gait speed ranged from 12 to 96 m/min with mean gait speed of 53.8 ±21.1 m/min. Mean percent accuracy for the full sample was 89.0 %, indicating that the pedometer counted 89 % of the actual steps taken. Gait speed and gait variability together accounted for 49% of the variance in error score, with gait speed accounting for 42%. The results for pedometer percent accuracy for the groups split by gait speed and gait variability are displayed in the table below.TableCONCLUSION: Gait speed is the most important determinant of the accuracy of pedometry in people with walking disabilities.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".