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Smartwatch calorie estimation accuracy study
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2026-09-09 17:09 UTC → 2026-09-09 18:18 UTC ·
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A study conducted by Florida International University and published in the journal PLOS One has found that popular smartwatches provide inaccurate estimates of calories burned during exercise. Researchers compared the Apple Watch Series 8, Fitbit Sense 2, Samsung Galaxy Watch 5, and Garmin Forerunner 955 against a clinical-grade COSMED K5 metabolic system. The findings indicate an average error margin between 15% and 25%. While the Apple Watch was identified as the most accurate device, it still overestimated energy use. Garmin and Samsung models showed the highest levels of overestimation. The study also noted that Fitbit experienced technical glitches during testing, resulting in missing or implausibly low readings, which led researchers to exclude much of its data from the final analysis. Building on these findings, a study published in the journal Sensors by researchers at the University of Michigan School of Kinesiology suggests that many smartwatch health metrics are algorithmic estimates rather than direct physiological measurements. Assistant professor Adam Lepley noted that while outputs like resting heart rate, step counts, and outdoor pace tend to be more reliable, complex metrics—including calories burned, sleep stages, body composition, and hydration levels—are often generated by combining sensor signals with proprietary algorithms and user assumptions. Accuracy can be further influenced by skin tone, tattoos, sweat, temperature, and device fit. Experts The wearable technology market is currently evolving from simple activity tracking toward advanced health monitoring and researchers suggest that these devices AI-driven intervention. Companies like Samsung are most effective for tracking personal long-term trends integrating BioActive sensors to measure blood oxygen and body composition, while Apple is leveraging Apple Intelligence to provide dynamic fitness recommendations. Additionally, new devices like the Luna Plus, showcased at IFA Berlin, utilize transcutaneous auricular vagus nerve stimulation (taVNS) to actively intervene in physiological states rather than serving as precise laboratory-grade instruments. just logging data.
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- 2026-09-09 18:18 UTC Smartwatch calorie estimation accuracy study
- 2026-09-09 17:09 UTC Smartwatch calorie estimation accuracy study
- 2026-09-06 13:49 UTC Smartwatch calorie estimation accuracy study
- 2026-09-04 13:03 UTC Smartwatch calorie estimation accuracy study
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