BackgroundWrist-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.ObjectiveThe 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.MethodsWe 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/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 an 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.ResultsFitbit 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.ConclusionsTwo 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.

Background: Real-time continuous glucose monitoring (CGM) devices help detect glycemic excursions associated with exercise, meals, and insulin dosing in patients with type 1 diabetes (T1D). However, the delay between interstitial and blood glucose may result in CGM underestimating the true change in glycemia during activity. The purpose of this study was to examine CGM discrepancies during exercise and the meal postexercise versus self-monitoring of blood glucose (SMBG). Methods: Seventeen adults with T1D using insulin pump therapy and CGM completed 60 min of aerobic exercise on three occasions. A standardized meal was given 30 min postexercise. SMBG was measured during exercise and in recovery using OmniPod Ò Personal Diabetes Manager (PDM; Insulet, Billerica, MA) with builtin glucose meter (FreeStyle; Abbott Laboratories, Abbott Park, IL), while CGM was measured with Dexcom G4 Ò with 505 algorithm (n = 4) or G5 Ò (n = 13), which were calibrated with subjects' own PDM. Results: SMBG showed a large drop in glycemia during exercise, while CGM showed a lag of 12-11 (meanstandard deviation) minutes and bias of-7-19 mg/dL/min during activity. Mean absolute relative difference (MARD) for CGM versus SMBG was 13 (6-22)% [median (interquartile range)] during exercise and 8 (5-14)% during mealtime. Clarke error grids showed CGM values were in zones A and B 94%-99% of the time for SMBG. Conclusion: In summary, the drop in CGM lags behind the drop in blood glucose during prolonged aerobic exercise by 12-11 min, and MARD increases to 13 (6-22)% during exercise as well. Therefore, if hypoglycemia is suspected during exercise, individuals should confirm glucose levels with a capillary glucose measurement.

OBJECTIVE To reduce exercise-associated hypoglycemia, individuals with type 1 diabetes on continuous subcutaneous insulin infusion typically perform basal rate reductions (BRRs) and/or carbohydrate feeding, although the timing and amount of BRRs necessary to prevent hypoglycemia are unclear. The goal of this study was to determine if BRRs set 90 min pre-exercise better attenuate hypoglycemia versus pump suspension (PS) at exercise onset. RESEARCH DESIGN AND METHODS Seventeen individuals completed three 60-min treadmill exercise (∼50% of VO2peak) visits in a randomized crossover design. The insulin strategies included 1) PS at exercise onset, 2) 80% BRR set 90 min pre-exercise, and 3) 50% BRR set 90 min pre-exercise. RESULTS Blood glucose level at exercise onset was higher with 50% BRR (191 ± 49 mg/dL) vs. 80% BRR (164 ± 41 mg/dL; P &lt; 0.001) and PS (164 ± 45 mg/dL; P &lt; 0.001). By exercise end, 80% BRR showed the smallest drop (−31 ± 58 mg/dL) vs. 50% BRR (−47 ± 50 mg/dL; P = 0.04) and PS (−67 ± 41 mg/dL; P &lt; 0.001). With PS, 7 out of 17 participants developed hypoglycemia versus 1 out of 17 in both BRR conditions (P &lt; 0.05). Following a standardized meal postexercise, glucose rose with PS and 50% BRR (both P &lt; 0.05), but failed to rise with 80% BRR (P = 0.16). Based on interstitial glucose, overnight mean percent time in range was 83%, 83%, and 78%, and time in hypoglycemia was 2%, 1%, and 5% with 80% BRR, 50% BRR, and PS, respectively (all P &gt; 0.05). CONCLUSIONS Overall, a 50–80% BRR set 90 min pre-exercise improves glucose control and decreases hypoglycemia risk during exercise better than PS at exercise onset, while not compromising the postexercise meal glucose control.

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Exercising while fasted with type 1 diabetes facilitates weight loss; however, the best strategy to maintain glucose stability remains unclear. RESEARCH DESIGN AND METHODSFifteen adults on continuous subcutaneous insulin infusion completed three sessions of fasted walking (120 min at 45% VO 2max ) in a randomized crossover design: 50% basal rate reduction, set 90 min pre-exercise (290 min 50% BRR ); usual basal rate with carbohydrate intake of 0.3 g/kg/h (CHO-only); and combined 50% basal rate reduction set at exercise onset with carbohydrate intake of 0.3 g/kg/h (Combo). RESULTSCombo had a smaller change in glucose (5 6 47 mg/dL) versus CHO-only (249 6 61 mg/dL, P 5 0.03) or 290 min 50% BRR (234 6 45 mg/dL). The 290 min 50% BRR strategy produced higher b-hydroxybutyrate levels (0.4 6 0.3 vs. 0.1 6 0.1 mmol/ L) and greater fat oxidation (0.51 6 0.2 vs. 0.39 6 0.1 g/min) than CHO-only (both P < 0.05). CONCLUSIONSAll strategies examined produced stable glycemia for fasted exercise, but a 50% basal rate reduction, set 90 min pre-exercise, eliminates carbohydrate needs and enhances fat oxidation better than carbohydrate feeding with or without a basal rate reduction set at exercise onset.Prolonged exercise in a fasted state may be preferable for people with diabetes since it increases lipid oxidation and is associated with better glucose stability than nonfasted exercise (1,2). On the basis of consensus, individuals with type 1 diabetes on continuous subcutaneous insulin infusion (CSII) can attempt to prevent hypoglycemia during fasted exercise by supplementing with carbohydrates and/or by performing a temporary basal rate reduction (3). The objective of this study was to compare three common strategies used for fasted exercise in individuals on CSII.