The effect of pedometer position and normal gait asymmetry on step count accuracy
Bibliographic record
Abstract
Manufacturers of pedometers recommend wearing a pedometer on the midline of the right thigh and this recommendation is used in research. However, there is conflicting evidence regarding the effect of pedometer position on accuracy. The purpose of this study was to systematically evaluate the effect of pedometer position on accuracy for 3 modes of gait. The Yamax SW200 pedometer was evaluated in 20 subjects in 5 different positions simultaneously: left mid-axillary, left mid-thigh, umbilical, right mid-thigh, and right mid-axillary. Each subject was asked to walk on a treadmill (54, 80, and 107 m.min(-1)), to walk overground (slow, preferred, and fast speeds), and to ascend and descend stairs. Pedometer steps were recorded and compared with actual steps observed. Using the same protocol, instantaneous triaxial accelerometry was used to explain position-dependent differences in accuracy. At slow speeds, the left mid-axillary position demonstrated the lowest net mean (+/-SD) error across all modes of gait (7.7% (+/-11.6%) overground;-0.6% (+/-2.2%) stairs). The right mid-thigh position had significantly (p<0.01) higher error for treadmill (18.1% (+/-17.3%)), overground (12.9% (+/-15.2%)), and stairs (2.9% (+/-3.9%)). Pedometer position dependent error was demonstrated, with the left mid-axillary position superior to the recommended position of right mid-thigh. The greater accuracy on the left side was wholly explained by gait asymmetry evident in step-induced accelerations recorded at right and left pedometer positions. A model of absolute error based on the ratio of steps at different gait speeds was generated to demonstrate the importance of this finding in pedometer-based lifestyle intervention studies.
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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 | 0.012 |
| 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) | 0.001 | 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".