Accuracy of energy expenditure estimation by the Apple Watch in EMS-supported exercise

<i>Objective.</i>Wearable devices are becoming increasingly prevalent, offering the capability to estimate energy expenditure. Among these devices, the Apple Watch has demonstrated notable results in estimating energy expenditure during physical activity, especially compared to other wearable devices. Its accuracy in determining energy expenditure during electromyostimulation (EMS) training remains unexplored and is investigated in this work.<i>Methods.</i>35 young, healthy adults completed two stepwise increasing bike ergometer protocols (50/30/3 protocol) until the maximum physical load was reached with and without EMS support. Energy expenditure estimates from the Apple Watch Series 7 (Apple Inc., Cupertino, California, USA) were compared against gold-standard spirometric calorimetry measurements.<i>Results.</i>The Apple Watch Series 7 underestimated energy expenditure compared to spirometric calorimetry for all data (mean difference: -27.4 kcal, LoA: 62.2 kcal), for ergometer exercise without EMS (mean difference: -28.8 kcal, LoA: 62.8 kcal), and for ergometer exercise with EMS (mean difference: -26.0 kcal, LoA: 62.4 kcal) data. We observed strong correlations between the Apple Watch Series 7 and spirometric calorimetry, with<i>r</i>= 0.93 (<i>p</i>< 0.001) for all data,<i>r</i>= 0.93 (<i>p</i>< 0.001) for exercise without EMS, and<i>r</i>= 0.93 (<i>p</i>< 0.001) for exercise with EMS.<i>Conclusion.</i>The Apple Watch Series 7 showed consistent accuracy in estimating energy expenditure during ergometer exercise, both with and without EMS. These findings suggest that the device can reliably monitor energy expenditure during EMS training, exhibiting similar accuracy limitations to conventional exercise settings.

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Publication Details

Journal
Physiological Measurement
Published
2025-08-18
DOI
https://doi.org/10.1088/1361-6579/adfcaf
Primary Topic
Green IT and Sustainability
Type
article
Field-Weighted Citation Impact
0.00
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article

Accuracy of energy expenditure estimation by the Apple Watch in EMS-supported exercise

Niklas Pilz, Tomas L. Bothe, Oliver Opatz, V. Heinz et al.
Physiological Measurement
Green IT and Sustainability
article

Accuracy of energy expenditure estimation by the Apple Watch in EMS-supported exercise

Niklas Pilz, Tomas L. Bothe, Oliver Opatz, V. Heinz, Andreas Reinhold Patzak, Leon Fesseler, H. Brandt, Tim Lindner
article en

Abstract

<i>Objective.</i>Wearable devices are becoming increasingly prevalent, offering the capability to estimate energy expenditure. Among these devices, the Apple Watch has demonstrated notable results in estimating energy expenditure during physical activity, especially compared to other wearable devices. Its accuracy in determining energy expenditure during electromyostimulation (EMS) training remains unexplored and is investigated in this work.<i>Methods.</i>35 young, healthy adults completed two stepwise increasing bike ergometer protocols (50/30/3 protocol) until the maximum physical load was reached with and without EMS support. Energy expenditure estimates from the Apple Watch Series 7 (Apple Inc., Cupertino, California, USA) were compared against gold-standard spirometric calorimetry measurements.<i>Results.</i>The Apple Watch Series 7 underestimated energy expenditure compared to spirometric calorimetry for all data (mean difference: -27.4 kcal, LoA: 62.2 kcal), for ergometer exercise without EMS (mean difference: -28.8 kcal, LoA: 62.8 kcal), and for ergometer exercise with EMS (mean difference: -26.0 kcal, LoA: 62.4 kcal) data. We observed strong correlations between the Apple Watch Series 7 and spirometric calorimetry, with<i>r</i>= 0.93 (<i>p</i>< 0.001) for all data,<i>r</i>= 0.93 (<i>p</i>< 0.001) for exercise without EMS, and<i>r</i>= 0.93 (<i>p</i>< 0.001) for exercise with EMS.<i>Conclusion.</i>The Apple Watch Series 7 showed consistent accuracy in estimating energy expenditure during ergometer exercise, both with and without EMS. These findings suggest that the device can reliably monitor energy expenditure during EMS training, exhibiting similar accuracy limitations to conventional exercise settings.

Physiological MeasurementVol. 46(9)
Medizinische Hochschule Hannover (DE), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Franklin University (US), Charité - Universitätsmedizin Berlin (DE)
Openalex Percentile: Top 80%
Green IT and Sustainability
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