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      Assessment of the Fitbit Charge 2 for monitoring heart rate

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          Abstract

          Fitness trackers are devices or applications for monitoring and tracking fitness-related metrics such as distance walked or run, calorie consumption, quality of sleep and heart rate. Since accurate heart rate monitoring is essential in fitness training, the objective of this study was to assess the accuracy and precision of the Fitbit Charge 2 for measuring heart rate with respect to a gold standard electrocardiograph. Fifteen healthy participants were asked to ride a stationary bike for 10 minutes and their heart rate was simultaneously recorded from each device. Results showed that the Fitbit Charge 2 underestimates the heart rate. Although the mean bias in measuring heart rate was a modest -5.9 bpm (95% CI: -6.1 to -5.6 bpm), the limits of agreement, which indicate the precision of individual measurements, between the Fitbit Charge 2 and criterion measure were wide (+16.8 to -28.5 bpm) indicating that an individual heart rate measure could plausibly be underestimated by almost 30 bpm.

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          Measuring agreement in method comparison studies.

          Agreement between two methods of clinical measurement can be quantified using the differences between observations made using the two methods on the same subjects. The 95% limits of agreement, estimated by mean difference +/- 1.96 standard deviation of the differences, provide an interval within which 95% of differences between measurements by the two methods are expected to lie. We describe how graphical methods can be used to investigate the assumptions of the method and we also give confidence intervals. We extend the basic approach to data where there is a relationship between difference and magnitude, both with a simple logarithmic transformation approach and a new, more general, regression approach. We discuss the importance of the repeatability of each method separately and compare an estimate of this to the limits of agreement. We extend the limits of agreement approach to data with repeated measurements, proposing new estimates for equal numbers of replicates by each method on each subject, for unequal numbers of replicates, and for replicated data collected in pairs, where the underlying value of the quantity being measured is changing. Finally, we describe a nonparametric approach to comparing methods.
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            Accuracy of Wrist-Worn Heart Rate Monitors.

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              Accuracy of Heart Rate Watches: Implications for Weight Management

              Background Wrist-worn monitors claim to provide accurate measures of heart rate and energy expenditure. People wishing to lose weight use these devices to monitor energy balance, however the accuracy of these devices to measure such parameters has not been established. Aim To determine the accuracy of four wrist-worn devices (Apple Watch, Fitbit Charge HR, Samsung Gear S and Mio Alpha) to measure heart rate and energy expenditure at rest and during exercise. Methods Twenty-two healthy volunteers (50% female; aged 24 ± 5.6 years) completed ~1-hr protocols involving supine and seated rest, walking and running on a treadmill and cycling on an ergometer. Data from the devices collected during the protocol were compared with reference methods: electrocardiography (heart rate) and indirect calorimetry (energy expenditure). Results None of the devices performed significantly better overall, however heart rate was consistently more accurate than energy expenditure across all four devices. Correlations between the devices and reference methods were moderate to strong for heart rate (0.67–0.95 [0.35 to 0.98]) and weak to strong for energy expenditure (0.16–0.86 [-0.25 to 0.95]). All devices underestimated both outcomes compared to reference methods. The percentage error for heart rate was small across the devices (range: 1–9%) but greater for energy expenditure (9–43%). Similarly, limits of agreement were considerably narrower for heart rate (ranging from -27.3 to 13.1 bpm) than energy expenditure (ranging from -266.7 to 65.7 kcals) across devices. Conclusion These devices accurately measure heart rate. However, estimates of energy expenditure are poor and would have implications for people using these devices for weight loss.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Project administrationRole: Writing – original draft
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Methodology
                Role: Formal analysisRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 February 2018
                2018
                : 13
                : 2
                : e0192691
                Affiliations
                [1 ] TSW XP Lab, Treviso, Italy
                [2 ] Leeds Institute for Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
                [3 ] Leeds Institute for Data Analytics, University of Leeds, Leeds, United Kingdom
                [4 ] School of Electronic and Electrical Engineering, University of Leeds, Leeds, West Yorkshire, United Kingdom
                [5 ] School of Medicine, Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, West Yorkshire, United Kingdom
                University of Illinois at Urbana-Champaign, UNITED STATES
                Author notes

                Competing Interests: The authors declare that the funding organization (TSW XP Lab) only provided financial support in the form of authors’ salaries [SB, CC, EB] and/or research materials, and did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the “Author Contribution” section. The authors also confirm that this commercial affiliation does not alter their adherence to all PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0002-9169-513X
                http://orcid.org/0000-0001-7035-3096
                Article
                PONE-D-17-29021
                10.1371/journal.pone.0192691
                5831032
                29489850
                c3da284a-22c9-4798-8ca6-6e33cbad8d87
                © 2018 Benedetto et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 August 2017
                : 29 January 2018
                Page count
                Figures: 4, Tables: 2, Pages: 10
                Funding
                This work was supported by TSW XP Lab, which only provided financial support in the form of authors’ salaries [SB, CC, EB] and/or research materials. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the “Author Contributions” section.
                Categories
                Research Article
                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Electrophysiological Techniques
                Cardiac Electrophysiology
                Electrocardiography
                Medicine and Health Sciences
                Cardiology
                Heart Rate
                Medicine and Health Sciences
                Public and Occupational Health
                Physical Activity
                Physical Fitness
                Engineering and Technology
                Equipment
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                Public and Occupational Health
                Physical Activity
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                Medicine and Health Sciences
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                Biology and Life Sciences
                Physiology
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                Medicine and Health Sciences
                Physiology
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                All relevant data are within the paper and its Supporting Information files.

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