Accuracy of a New Activity Monitor for Assessing Exercise Intensity during Walking
Bibliographic record
Abstract
1391 To better understand the dose-response relationship between physical activity (PA) and health outcomes, it is necessary to accurately quantify daily PA. Based on pedometer research, a target of 10,000 steps/day has been promoted. Increasingly, researchers are proposing that the intensity of PA may be more important than the total amount; with medium and high intensity PA being particularly effective. Walking speed is a direct measure of intensity during walking. A new ankle-mounted accelerometer-based activity monitor (Dynastream Innovations, Inc., Alberta, Canada) is available that not only tracks step count, but also walking speed and distance traveled. PURPOSE: To determine the accuracy of this new activity monitor for counting steps and computing distance traveled at 3 walking speeds in populations of children, adults, and seniors. METHODS: Eight adults, 8 children, and 8 seniors (over 60 yrs of age) were recruited to perform five 200 m walks wearing the uncalibrated activity monitor. Three trials were performed at a comfortable self-selected walking speed (SSWS). For the fourth trial the subjects walked “as slowly as you ever would in daily life”, and for the last trial the subjects received the same instruction for fast walking. The adult group also performed 3 trials of a step protocol: they walked a prescribed number of steps (18 or 22), stopped for an interval (20 s), and then repeated the pattern 5 times. This protocol tests the step count in a challenging stop-start situation. Walking time was recorded from the monitor. Output from the activity monitor was compared with the measured or counted values. RESULTS: The average age of the participants was 8.0, 24.4, and 72.6 yrs for the children, adults, and seniors respectively. The SSWS ranged from 0.74–2.0 m/s. Differences in walking speed between groups were statistically significant for all 3 speeds (p < 0.05). Calculating the average percent difference between the distances measured with the activity monitor and the true distance, the accuracy of the monitor was 94%. There were no statistically significant differences in the accuracy of the distance computation between groups or between walking speeds (p > 0.22). The step count accuracy during the step protocol was more than 99%. CONCLUSIONS: Very accurate step counts can be achieved with this new activity monitor. Accurate measurements of the distance walked were demonstrated in 3 populations (adults, children, and seniors) across a range of SSWS. Since speed is simply distance per time, the walking speed accuracy is expected to match the distance accuracy at 94%. Measurement of walking speed enables assessment of the impact of intensity of PA on health outcomes.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".