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      Validity of Wrist-Worn photoplethysmography devices to measure heart rate: A systematic review and meta-analysis

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          Conducting Meta-Analyses inRwith themetaforPackage

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            Testing a tool for assessing the risk of bias for nonrandomized studies showed moderate reliability and promising validity.

            To develop and validate a new risk-of-bias tool for nonrandomized studies (NRSs). We developed the Risk of Bias Assessment Tool for Nonrandomized Studies (RoBANS). A validation process with 39 NRSs examined the reliability (interrater agreement), validity (the degree of correlation between the overall assessments of RoBANS and Methodological Index for Nonrandomized Studies [MINORS], obtained by plotting the overall risk of bias relative to effect size and funding source), face validity with eight experts, and completion time for the RoBANS approach. RoBANS contains six domains: the selection of participants, confounding variables, the measurement of exposure, the blinding of the outcome assessments, incomplete outcome data, and selective outcome reporting. The interrater agreement of the RoBANS tool except the measurement of exposure and selective outcome reporting domains ranged from fair to substantial. There was a moderate correlation between the overall risks of bias determined using RoBANS and MINORS. The observed differences in effect sizes and funding sources among the assessed studies were not correlated with the overall risk of bias in these studies. The mean time required to complete RoBANS was approximately 10 min. The external experts who were interviewed evaluated RoBANS as a "fair" assessment tool. RoBANS shows moderate reliability, promising feasibility, and validity. The further refinement of this tool and larger validation studies are required. Copyright © 2013 Elsevier Inc. All rights reserved.
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              Is Open Access

              Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort

              The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to 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. We 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. Devices 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. In conclusion, most 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/).
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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Journal of Sports Sciences
                Journal of Sports Sciences
                Informa UK Limited
                0264-0414
                1466-447X
                September 01 2020
                June 19 2020
                September 01 2020
                : 38
                : 17
                : 2021-2034
                Affiliations
                [1 ]Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
                [2 ]Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
                [3 ]School of Public Health, Nanjing Medical University, Nanjing, China
                Article
                10.1080/02640414.2020.1767348
                32552580
                8bf40ad0-f979-436d-8a25-9f9c7b569bc7
                © 2020
                History

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