Journal of Personalized MedicineBioinformaticsPeer-reviewed journal article
Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort
Anna ShcherbinaiD, C. Mikael MattssoniD, Daryl M. WaggottiD, Heidi SalisburyiD, Jeffrey Wilcox ChristleiD, Trevor J. HastieiD, Matthew Thomas WheeleriD, Euan Angus AshleyiD
Abstract
BackgroundThe ability to measure activity and physiology through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown.\n\nObjectiveTo assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework.\n\nMethodsWe evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 {+/-} 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination.\n\nResultsDevices reported the lowest error for cycling and the highest for walking. Device error was higher for males,greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest.\n\nConclusionsMost wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).\n\nAbbreviations
- Citations
- 625
- FWCI
- 27.22
- Field percentile
- top 1%
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