Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). 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 two 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 2TM, Garmin vívosmart® HR+) during dynamic activities. Over a two-day period, 20 healthy adults (age: 27.5 ± 6.0 yrs; BMI: 22.5 ± 2.3 kg/m2; 11 females) performed a maximal oxygen uptake test, free-weight resistance circuit, interval training session, and activities of daily living. Validity was assessed using a HR chest strap (Polar®) and portable indirect calorimetry (Cosmed). Accuracy of the commercial wearables versus research-grade standards was determined using Bland-Altman analysis, correlational analysis, and error bias. 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% ± 16.7 while Fitbit estimated HR with a %RE of -4.7% ± 19.6 across all activities. The highest error was observed during high intensity intervals on bike (Fitbit: -11.4% ± 35.7; Garmin: -14.3% ± 20.5) and lowest error during high intensity intervals on treadmill (Fitbit: -1.7% ± 11.5; Garmin: -0.5% ± 9.4). Fitbit and Garmin EE estimates differed significantly with Garmin having less negative bias (Fitbit: -19.3% ± 29.9, Garmin: -1.6% ± 30.6, P<.001) across all activities, with both correlating poorly with indirect calorimetry measures. Conclusions: Two common wrist-worn devices 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.

Glucose monitoring either by self-monitoring of blood glucose (SMBG) or continuous glucose monitoring (CGM) plays an important role in diabetes management and in reducing risk for diabetes-related complications. However, despite evidence supporting the role of glucose monitoring in better patient health outcomes, studies also reveal relatively poor adherence rates to SMBG and CGM use and numerous patient-reported barriers. Fortunately, some promising intervention strategies have been identified that promote at least short-term improvements in patients’ adherence to SMBG. These include education, problem solving, contingency management, goal setting, cognitive behavioral therapy, and motivational interviewing. Specific to CGM, interventions to promote greater use among patients are currently under way, yet one pilot study provides data suggesting better maintenance of CGM use in patients showing greater readiness for behavior change. The purpose of this review is to summarize the literature specific to glucose monitoring in patients with diabetes focusing specifically on current adherence rates, barriers to monitoring, and promising intervention strategies that may be ready to deploy now in the clinic setting to promote greater patient adherence to glucose monitoring. Yet, to continue to help patients with diabetes adhere to glucose monitoring, future research is needed to identify the treatment strategies and the intervention schedules that most likely lead to long-term maintenance of optimal glycemic monitoring levels.