The accuracy of VO₂ max, heart rate and energy expenditure measurements from Google Pixel Watch 3
- 1School of Public Health, Physiotherapy and Sports Science, University College Dublin, Dublin, Ireland
- 2Rinn Artificial Intelligence, University College Dublin, Dublin, Ireland
- 3School of Medicine and Health, Experimental Exercise Science, Technical University of Munich, Munich, Germany
Abstract
Consumer wearables enable scalable physiological assessment and pre-symptomatic disease detection. However, validation of wearable data remains insufficient in scope and rigour, hindering integration into clinical and public health practice. Here, we evaluated the validity of VO2max, heart rate and energy expenditure from the Google Pixel Watch 3. Thirty-four participants completed a maximal exercise treadmill test using indirect calorimetry, while wearing a Polar H10 chest strap. Pixel Watch estimates of VO2max were generated in free-living conditions; heart rate and energy expenditure estimates were recorded during exercise testing. Bland-Altman analysis showed low bias but wide limits of agreement for VO2max estimates from the Pixel Watch 3 (bias −0.53 mL/kg/min; limits of agreement [LoA] −12.56 to 11.50; mean absolute percentage error [MAPE] 8.65%). Heart rate demonstrated strong agreement with the criterion overall, despite measurement variability (bias −2.39 bpm; LoA −24.42 to 19.65; MAPE 2.73%). The error for energy expenditure varied substantially between participants (bias −8.43 kcal; LoA −72.75 to 55.88; MAPE 15.02%). These results indicate that VO2max estimates lack sufficient individual-level validity for clinical use, although the bias suggests utility for population health monitoring. Heart rate showed acceptable error for exercise monitoring, whereas the large variation in error for energy expenditure limits its practical use. Our findings illustrate that wearable data require condition- and population-specific validation before incorporation into health care pathways.
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BibTeX
@article{lambe2026accuracy,
title = {{The accuracy of VO₂ max, heart rate and energy expenditure measurements from Google Pixel Watch 3}},
author = {Rory Lambe and Moritz Schumann and Sherene Hamilton and Lauren Donnelly and Thomas White and Seán O’Reilly and Saoirse Lally and Cailbhe Doherty},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0356808},
url = {https://doi.org/10.1371/journal.pone.0356808},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - The accuracy of VO₂ max, heart rate and energy expenditure measurements from Google Pixel Watch 3
AU - Rory Lambe
AU - Moritz Schumann
AU - Sherene Hamilton
AU - Lauren Donnelly
AU - Thomas White
AU - Seán O’Reilly
AU - Saoirse Lally
AU - Cailbhe Doherty
PY - 2026
DA - 2026/09/15
JO - PLOS One
DO - 10.1371/journal.pone.0356808
UR - https://doi.org/10.1371/journal.pone.0356808
AB - Consumer wearables enable scalable physiological assessment and pre-symptomatic disease detection. However, validation of wearable data remains insufficient in scope and rigour, hindering integration into clinical and public health practice. Here, we evaluated the validity of VO2max, heart rate and energy expenditure from the Google Pixel Watch 3. Thirty-four participants completed a maximal exercise treadmill test using indirect calorimetry, while wearing a Polar H10 chest strap. Pixel Watch estimates of VO2max were generated in free-living conditions; heart rate and energy expenditure estimates were recorded during exercise testing. Bland-Altman analysis showed low bias but wide limits of agreement for VO2max estimates from the Pixel Watch 3 (bias −0.53 mL/kg/min; limits of agreement [LoA] −12.56 to 11.50; mean absolute percentage error [MAPE] 8.65%). Heart rate demonstrated strong agreement with the criterion overall, despite measurement variability (bias −2.39 bpm; LoA −24.42 to 19.65; MAPE 2.73%). The error for energy expenditure varied substantially between participants (bias −8.43 kcal; LoA −72.75 to 55.88; MAPE 15.02%). These results indicate that VO2max estimates lack sufficient individual-level validity for clinical use, although the bias suggests utility for population health monitoring. Heart rate showed acceptable error for exercise monitoring, whereas the large variation in error for energy expenditure limits its practical use. Our findings illustrate that wearable data require condition- and population-specific validation before incorporation into health care pathways.
SN - 1932-6203
ER -