Validity of the Fitbit One for Measuring Activity in Community-Dwelling Stroke Survivors
Bibliographic record
Abstract
Purpose: We determined the correlation between the Fitbit One and Actical accelerometer for quantifying the 3-day step count and activity levels in community-dwelling individuals with stroke. Method: Twelve participants with a mean age of 62.6 (SD 9.3) years wore both the Fitbit One and the Actical on the non-paretic ankle for 3 days. Regression analyses were performed to examine concurrent validity between the devices for step counts and sedentary, light, moderate, and vigorous activity. The relative error of the Fitbit One compared with the Actical in measuring step count was calculated. Results: Participants spent about 80% of their days being sedentary. The associations between the Fitbit One and the Actical were r>0.80 for step count and light-intensity activity across the 3 days of free-living activity. The overall relative error in measuring step count was 3.8%, with differences between those with walking speeds of less than 0.58 metres per second and 0.58 metres per second or more (27.4% [SD 34.2] vs. –8.0% [SD 10.7], p<0.001). Conclusions: The Fitbit One was associated with the Actical accelerometer in measuring step count and light-intensity activity during free-living activity after stroke, but had lower error in capturing step count for those with faster walking speeds. The Fitbit One may not be valid for capturing higher intensity activity after stroke.
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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 | 0.000 | 0.000 |
| 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".