Wrist‐worn devices for the measurement of heart rate and energy expenditure: A validation study for the Apple Watch 6, Polar Vantage V and Fitbit Sense
Bibliographic record
Abstract
ABSTRACT The purpose of this study was to investigate the accuracy of 3 recently released wrist‐worn devices (Apple Watch 6, Polar Vantage V and Fitbit Sense) for heart rate and energy expenditure during various activities. The study population consisted of 60 young healthy individuals (30 men and 30 women; age: 24.9 ± 3.0 years, BMI: 23.1 ± 2.7 kg/m2). Heart rate and energy expenditure were measured using the Polar H10 and Metamax 3B, respectively (reference measures) as well as with the 3 wrist‐worn devices during 5 different activities (sitting, walking, running, resistance exercises and cycling). The Apple Watch 6 displayed the highest level of accuracy for heart rate measurement with a coefficient of variation (CV) (%) of less than 5% for all 5 activities, whereas the Polar Vantage V and the Fitbit Sense presented various degrees of accuracy (from high to poor accuracy) dependent on the activity (CVs between 2.44‐8.80% and 4.14‐10.76%, respectively). As for energy expenditure, all 3 devices displayed poor accuracy for all 5 physical activities (CVs between 14.68‐24.85% for Apple Watch 6, 16.54‐25.78% for Polar Vantage V and 13.44‐29.66% for Fitbit Sense). Results of the present study indicate that the Apple Watch 6 was the most accurate for measuring heart rate across all 5 activities, whereas variable levels of accuracy for heart rate measurement for the Polar Vantage V and the Fitbit Sense were observed depending on the activity. As for energy expenditure, all 3 devices showed poor accuracy during all activities. Highlights The Apple Watch 6 was the most accurate for measuring heart rate, whereas the Polar Vantage V and Fitbit Sense showed variable results dependent on the activity The Apple Watch 6, Polar Vantage V and Fitbit Sense showed poor accuracy for energy expenditure during 5 different physical activities Healthcare care professionals, athletes/coaches and the general population may want to proceed with caution on the clinical utility of energy expenditure of these devices during the implementation of an exercise training or nutritional programme.
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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 | 0.005 | 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".