JMIR Publications

ABSTRACT

Background:

Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are not only used by consumers to monitor their behavior, but also by researchers to track the behavior of large samples and health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high cost and accuracy concerns may be barriers to widespread adoption.

Objective:

This study investigated the concurrent validity of six low-cost activity trackers: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0 and Xiaomi MiBand 2 for measuring steps, moderate to vigorous physical activity (MVPA) and total sleep time (TST).

Methods:

A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore 1 low-cost tracker and 1 high-cost tracker (Fitbit Charge HR) on the non-dominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and wore a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+/BodyMedia SenseWear using Mean Absolute Percentage Error scores (MAPE), correlations and Bland-Altman plots in IBM SPSS 24.0.

Results:

Large variations were shown between trackers. Low-cost trackers showed moderate to very strong correlations (Spearman r=0.53-0.91) and low to good agreement (interclass correlation coefficient, ICC=0.51-0.90) for measuring steps. Weak to moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed very weak to strong correlations (Spearman r=0.04-0.73) and low agreement (interclass correlation coefficient, ICC=0.05-0.52). Bland-Altman revealed a variation between over- and undercounting for measuring steps, MVPA and TST depending on the used low-cost tracker. None of the trackers, including the Fibit (high-cost one), showed high validity to measure MVPA.

Conclusions:

This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for measurement of steps, there was evidence of validity for measurement of sleep in some trackers, whereas validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with the Xiaomi having the highest validity for measurement of steps, and the VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.