Validation of Youth Oriented Activity Trackers: Comprehensive Laboratory- and Field-Based Validation

Abstract

BackgroundCommercial activity trackers are growing in popularity among adults and some are beginning to be marketed to children. There is, however, a paucity of independent research examining the validity of these devices to detect physical activity of different intensity levels.ObjectivesThe purpose of this study was to determine the validity of the output from 3 commercial youth-oriented activity trackers in 3 phases: (1) orbital shaker, (2) structured indoor activities, and (3) 4 days of free-living activity.MethodsFour units of each activity tracker (Movband [MB], Sqord [SQ], and Zamzee [ZZ]) were tested in an orbital shaker for 5-minutes at three frequencies (1.3, 1.9, and 2.5 Hz). Participants for Phase 2 (N=14) and Phase 3 (N=16) were 6-12 year old children (50% male). For Phase 2, participants completed 9 structured activities while wearing each tracker, the ActiGraph GT3X+ (AG) research accelerometer, and a portable indirect calorimetry system to assess energy expenditure (EE). For Phase 3, participants wore all 4 devices for 4 consecutive days. Correlation coefficients, linear models, and non-parametric statistics evaluated the criterion and construct validity of the activity tracker output.ResultsOutput from all devices was significantly associated with oscillation frequency (r=.92-.99). During Phase 2, MB and ZZ only differentiated sedentary from light intensity (P<.01), whereas the SQ significantly differentiated among all intensity categories (all comparisons P<.01), similar to AG and EE. During Phase 3, AG counts were significantly associated with activity tracker output (r=.76, .86, and .59 for the MB, SQ, and ZZ, respectively).ConclusionsAcross study phases, the SQ demonstrated stronger validity than the MB and ZZ. The validity of youth-oriented activity trackers may directly impact their effectiveness as behavior modification tools, demonstrating a need for more research on such devices.

Evaluating the Validity of Current Mainstream Wearable Devices in Fitness Tracking Under Various Physical Activities: Comparative Study

“…For the measurement of energy consumption, John et al [ 32 ] evaluated the accuracies of the Sense Wear Armband monitor and the BodyMedia Mini in measuring the energy consumption in the natural state of life over 14 consecutive days and showed that the accuracies of the latest devices were significantly improved compared with those of older models, with the MAPE being reduced to 0.10 and 0.11, respectively. Calabro et al [ 33 ] examined the accuracies of three types of wearable devices—the Movband, the Sqord, and the Zamzee—in measuring energy consumption and found that the accuracy was acceptable even for children. Lee et al [ 34 ] asked 60 subjects to simultaneously wear eight types of wearable devices in a natural state of life for 69 min and used the Oxycon mobile 5.0 as the gold standard of energy consumption measurement and found that, except for the Basis Band (MAPE=0.23), the majority of the devices had good accuracy, maintaining a MAPE at approximately 0.12.…”

Use of consumer monitors for estimating energy expenditure in youth

“…Consumer PAMs are widely popular, and there is corresponding interest in their validity, particularly for devices made by industry leaders such as Apple, Fitbit, and Samsung. However, there has been disproportional focus on PAM validity and use for adults (Bai et al 2016;Chowdhury et al 2017;Dominick et al 2016;El-Amrawy and Nounou 2015;Evenson et al 2015;Ferguson et al 2015;Kaewkannate and Kim 2016;Kooiman et al 2015;Lee et al 2014;Nelson et al 2016;Woodman et al 2016) versus youth (Sirard et al 2017), and it is important to assess the two groups separately (Ainsworth et al 2018;Butte et al 2018;McMurray et al 2015;Pfeiffer et al 2018).…”

Comparison of Polar Active Watch and Waist- and Wrist-Worn ActiGraph Accelerometers for Measuring Children’s Physical Activity Levels during Unstructured Afterschool Programs

“…It has been reported that differences in PA estimates between activity monitors differently affect user’s perceived rewards for the same activity [ 20 ], which may negatively influence motivation to engage in PA [ 21 ], and be partly responsible for high levels of abandonment of activity monitors [ 20 ]. In addition, there is a growing number of studies utilizing consumer-grade activity monitors for research purposes, either as an assessment tool, intervention component, or both, where high levels of accuracy and comparability with other research-grade monitors are demanded [ 22 ]. Several studies have been conducted to address this issue by examining the validity and reliability of consumer-grade PA monitors for the assessment of different PA metrics [ 23 , 24 , 25 ].…”