Accuracy of the SenseWear Armband during Short Bouts of Exercise

TL;DR

This study evaluates how well the SenseWear Armband estimates energy expenditure during short exercise sessions compared to a gold standard method.

Contribution

The study provides new insights into the accuracy of the SenseWear Armband during short intervals of walking and running.

Findings

The SenseWear Armband overestimated energy expenditure during walking and running at 75% speed.

It underestimated energy expenditure at higher running intensities but not significantly.

Activity-specific algorithms improved estimates but did not justify adding extra sensors.

Abstract

A goal of mobile monitoring is to approximate metabolic energy expenditure (EE) during activities of daily living and exercise. Many physical activity monitors are inaccurate with respect to estimated EE and differentiating between activities that occur over short intervals. The objective of our study was to assess the validity of the SenseWear Armband (SWA) compared to indirect calorimetry (IC) during short intervals of walking and running. Twenty young, fit participants walked (preferred speed) and ran (75%, 85%, and 95% of predicted VO2max run speeds) on a treadmill. EE estimates from IC, SWA, and prediction equations that used the SWA, speed, and heart rate were examined during each 4 min interval and across the whole protocol (Total). The level of significance was p < 0.05. The SWA overestimated EE relative to IC by 1.62 kcal·min−1 while walking and 1.05 kcal·min−1 while running at 75%. However, it underestimated EE at the 85% (0.05 kcal·min−1) and 95% (0.92 kcal·min−1) speeds, but not significantly, and overestimated total EE by 28.29 kcal. Except for walking, our results suggest that the SWA displayed a good level of agreement (ICC = 0.76 to 0.84) with IC measures. Activity-specific algorithms using SWA, speed, and heart rate improved EE estimates, based on the standard error of the estimates, but perhaps not enough to justify extra sensors. The SWA may enable EE estimation of locomotion outside the laboratory, including those with short bouts of high intensity activity, but continued development of the SWA, or devices like it, is needed to enable accurate monitoring.

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