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Reddy RK, Pooni R, Zaharieva DP, et al. Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study. JMIR Mhealth Uhealth. 2018;6(12):e10338doi: 10.2196/10338.
Reddy, R. K., Pooni, R., Zaharieva, D. P., Senf, B., El Youssef, J., Dassau, E., Doyle Iii, F. J., Clements, M. A., Rickels, M. R., Patton, S. R., Castle, J. R., Riddell, M. C., & Jacobs, P. G. (2018). Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study. JMIR mHealth and uHealth, 6(12), e10338. https://doi.org/10.2196/10338
Reddy, Ravi Kondama, et al. "Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study." JMIR mHealth and uHealth vol. 6,12 (2018): e10338. doi: https://doi.org/10.2196/10338
Reddy RK, Pooni R, Zaharieva DP, Senf B, El Youssef J, Dassau E, Doyle Iii FJ, Clements MA, Rickels MR, Patton SR, Castle JR, Riddell MC, Jacobs PG. Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study. JMIR Mhealth Uhealth. 2018 Dec 10;6(12):e10338. doi: 10.2196/10338. PMID: 30530451; PMCID: PMC6305876.
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JMIR Mhealth Uhealth. 2018 Dec 10;6(12):e10338. doi: 10.2196/10338.

Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study.

JMIR mHealth and uHealth

Ravi Kondama Reddy, Rubin Pooni, Dessi P Zaharieva, Brian Senf, Joseph El Youssef, Eyal Dassau, Francis J Doyle Iii, Mark A Clements, Michael R Rickels, Susana R Patton, Jessica R Castle, Michael C Riddell, Peter G Jacobs

Affiliations

  1. Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, United States.
  2. School of Kinesiology and Health Science, York University, Toronto, ON, Canada.
  3. Harold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, OR, United States.
  4. Harvard John A Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States.
  5. Children's Mercy Kansas City, Kansas City, MO, United States.
  6. Institute for Diabetes, Obesity & Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.
  7. Department of Pediatrics, University of Kansas Medical Center, Kansas City, KS, United States.

PMID: 30530451 PMCID: PMC6305876 DOI: 10.2196/10338

Abstract

BACKGROUND: Wrist-worn activity monitors are often used to monitor heart rate (HR) and energy expenditure (EE) in a variety of settings including more recently in medical applications. The use of real-time physiological signals to inform medical systems including drug delivery systems and decision support systems will depend on the accuracy of the signals being measured, including accuracy of HR and EE. Prior studies assessed accuracy of wearables only during steady-state aerobic exercise.

OBJECTIVE: The objective of this study was to validate the accuracy of both HR and EE for 2 common wrist-worn devices during a variety of dynamic activities that represent various physical activities associated with daily living including structured exercise.

METHODS: We assessed the accuracy of both HR and EE for two common wrist-worn devices (Fitbit Charge 2 and Garmin vívosmart HR+) during dynamic activities. Over a 2-day period, 20 healthy adults (age: mean 27.5 [SD 6.0] years; body mass index: mean 22.5 [SD 2.3] kg/m

RESULTS: Fitbit and Garmin were reasonably accurate at measuring HR but with an overall negative bias. There was more error observed during high-intensity activities when there was a lack of repetitive wrist motion and when the exercise mode indicator was not used. The Garmin estimated HR with a mean relative error (RE, %) of -3.3% (SD 16.7), whereas Fitbit estimated HR with an RE of -4.7% (SD 19.6) across all activities. The highest error was observed during high-intensity intervals on bike (Fitbit: -11.4% [SD 35.7]; Garmin: -14.3% [SD 20.5]) and lowest error during high-intensity intervals on treadmill (Fitbit: -1.7% [SD 11.5]; Garmin: -0.5% [SD 9.4]). Fitbit and Garmin EE estimates differed significantly, with Garmin having less negative bias (Fitbit: -19.3% [SD 28.9], Garmin: -1.6% [SD 30.6], P<.001) across all activities, and with both correlating poorly with indirect calorimetry measures.

CONCLUSIONS: Two common wrist-worn devices (Fitbit Charge 2 and Garmin vívosmart HR+) show good HR accuracy, with a small negative bias, and reasonable EE estimates during low to moderate-intensity exercise and during a variety of common daily activities and exercise. Accuracy was compromised markedly when the activity indicator was not used on the watch or when activities involving less wrist motion such as cycle ergometry were done.

©Ravi Kondama Reddy, Rubin Pooni, Dessi P Zaharieva, Brian Senf, Joseph El Youssef, Eyal Dassau, Francis J Doyle III, Mark A Clements, Michael R Rickels, Susana R Patton, Jessica R Castle, Michael C Riddell, Peter G Jacobs. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 10.12.2018.

Keywords: artificial pancreas; energy metabolism; fitness trackers; heart rate; high-intensity interval training

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