Capturing step counts at slow walking speeds in older adults: Comparison of ankle and waist placement of measuring device
Bibliographic record
Abstract
OBJECTIVE: It is important for older adults to be physically active, but many older adults walk slowly. This study examined the accuracy of a commercially available step-count device (Fitbit One) at slow speeds and compared the accuracy of the device when worn at the ankle and waist in older adults. METHODS: The Fitbit One was placed at the ankle and waist of participants (n=42; mean age 73 years) while they performed walking trials at 7 different speeds (0.3-0.9 m/s). Step counts obtained from video recordings were used as the gold standard comparison to determine the accuracy of the device. RESULTS: The ankle-worn device had significantly less error than the waist-worn device at all speeds. The percentage error of the ankle-worn device was less than 10% at speeds of 0.4-0.9 m/s and did not record zero steps at any speed. The percentage error of the waist-worn device was below 10% at only the 2 fastest speeds (0.8 and 0.9 m/s) and recorded zero steps for numerous participants at speeds of 0.3-0.5 m/s. CONCLUSION: The Fitbit One can accurately capture steps at slow speeds when placed at the ankle and thus may be appropriate for capturing physical activity in slow-walking older adults.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".