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Comparison of Four Fitbit and Jawbone Activity Monitors with a Research-Grade Actigraph Accelerometer for Estimating Physical Activity and Energy Expenditure Mary T

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Comparison of Four Fitbit and Jawbone Activity Monitors with a Research-Grade Actigraph Accelerometer for Estimating Physical Activity and Energy Expenditure Mary T Masthead Logo Digital Commons @ George Fox University Faculty Publications - Department of Health and Department of Health and Human Performance Human Performance 2018 Comparison of Four Fitbit and Jawbone Activity Monitors with a Research-Grade ActiGraph Accelerometer for Estimating Physical Activity and Energy Expenditure Mary T. Imboden George Fox University Michael B. Nelson Ball State University Leonard A. Kaminsky Ball State University Alexander HK Montoye Ball State University Follow this and additional works at: https://digitalcommons.georgefox.edu/hhp_fac Part of the Physical Therapy Commons, and the Sports Sciences Commons Recommended Citation Imboden, Mary T.; Nelson, Michael B.; Kaminsky, Leonard A.; and Montoye, Alexander HK, "Comparison of Four Fitbit and Jawbone Activity Monitors with a Research-Grade ActiGraph Accelerometer for Estimating Physical Activity and Energy Expenditure" (2018). Faculty Publications - Department of Health and Human Performance. 15. https://digitalcommons.georgefox.edu/hhp_fac/15 This Article is brought to you for free and open access by the Department of Health and Human Performance at Digital Commons @ George Fox University. It has been accepted for inclusion in Faculty Publications - Department of Health and Human Performance by an authorized administrator of Digital Commons @ George Fox University. For more information, please contact [email protected]. Comparison of four Fitbit and Jawbone activity monitors with a research-grade ActiGraph accelerometer for estimating physical activity and energy expenditure Mary T Imboden,1 Michael B Nelson,1 Leonard A Kaminsky,2 Alexander HK Montoye1 1Clinical Exercise Physiology ABSTRACT translating these accelerations into PA variables Program, Ball State University, Background/aim Consumer-based physical activity such as steps, energy expenditure (EE) and time Muncie, Indiana, USA 2Fisher Institute of Health and (PA) monitors have become popular tools to track PA spent in moderate-intensity or vigorous-intensity Well-Being, Ball State University, behaviours. Currently, little is known about the validity PA (active minutes). However, accelerometers have Muncie, Indiana, USA of the measurements provided by consumer monitors. mainly been used in research settings and are rarely We aimed to compare measures of steps, energy used by consumers for personal PA tracking. Correspondence to expenditure (EE) and active minutes of four consumer More recently, consumer-based PA moni- Alexander HK Montoye, monitors with one research-grade accelerometer within a tors, which use accelerometer technology, have Integrative Physiology and Health Science, Department, semistructured protocol. become popular as personal PA tracking tools. In Alma College, 614 W. Superior, Methods Thirty men and women (18–80 years old) 2013, consumer monitor sales were estimated at Alma, MI 48801, USA; wore Fitbit One (worn at the waist), Fitbit Zip (waist), $330 million worldwide, with approximately 87% montoyeah@ alma. edu Fitbit Flex (wrist), Jawbone UP24 (wrist) and one coming from Fitbit (Fitbit, San Francisco, Cali- waist-worn research-grade accelerometer (ActiGraph) fornia, USA) and Jawbone (Jawbone, San Francisco, while participating in an 80 min protocol. A validated California, USA) brands.3 Like research-grade accel- EE prediction equation and active minute cut-points erometers, consumer monitors estimate PA vari- were applied to ActiGraph data. Criterion measures ables including steps taken, EE and active minutes. were assessed using direct observation (step count) However, consumer monitors offer numerous and portable metabolic analyser (EE, active minutes). advantages over most research-grade accelerome- A repeated measures analysis of variance (ANOVA) ters, including real-time feedback, easy synchroni- was used to compare differences between consumer sation to smartphone or computer applications, and monitors, ActiGraph, and criterion measures. Similarly, a goal-tracking. repeated measures ANOVA was applied to a subgroup of Despite the recent widespread adoption of subjects who didn’t cycle. consumer monitors, little research has compared Results Participants took 3321±571 steps, had their accuracy with research-grade accelerometers. 28±6 active min and expended 294±56 kcal based Lee et al compared the accuracy of consumer moni- on criterion measures. Comparatively, all monitors tors (Fitbit One (FO), Fitbit Zip (FZ), Jawbone underestimated steps and EE by 13%–32% (p<0.01); UP24 (JU)) and one popular research-grade acceler- additionally the Fitbit Flex, UP24, and ActiGraph ometer, the ActiGraph (AG; ActiGraph, Pensacola, underestimated active minutes by 35%–65% (p<0.05). Florida, USA), with indirect calorimetry for esti- Underestimations of PA and EE variables were found to mating EE in a semistructured setting. These be similar in the subgroup analysis. researchers found similar accuracy of the consumer Conclusion Consumer monitors had similar accuracy monitors to the research-grade accelerometer, with for PA assessment as the ActiGraph, which suggests mean absolute per cent error (MAPE) of 10%–12% that consumer monitors may serve to track personal for the consumer monitors and 12.6% for the PA behaviours and EE. However, due to discrepancies research-grade accelerometer compared with indi- among monitors, individuals should be cautious when 4 comparing relative and absolute differences in PA values rect calorimetry. In a similar investigation, Bai et al obtained using different monitors. assessed the accuracy of the Fitbit Flex (FF), JU, and AG against indirect calorimetry for measuring EE in a semistructured setting, finding that the FF, JU, and AG all had MAPE of <20% for EE measurements.5 INTRODUCTION Finally, Murakami et al assessed the accuracy of Physical activity (PA) reduces risk of obesity, 12 activity monitors, including FF, JU, and AG diabetes, hypertension, cardiovascular disease and for measuring EE in a free-living setting compared all-cause mortality.1 National PA guidelines recom- with doubly labelled water. Estimates from the 12 mend that adults participate in ≥150 min/week of devices ranged from 590 to 69 kcal/day lower than moderate-intensity or vigorous-intensity PA as a the doubly labelled water measure.6 While these minimal amount of PA needed to increase or main- studies provide insight into EE prediction, they did tain health.1 Accurate assessment of individuals’ PA, not assess accuracy of steps or active minute esti- including volume, intensity and time, is important.2 mates. Storm et al compared seven activity moni- Accelerometers provide an objective assessment tors, including two research-grade accelerometers, of PA by measuring accelerations of the body and the MoveMonitor and activPAL (PAL Technologies, Glasgow, UK). All monitors underestimated steps compared breathing mask worn by participants and were used to determine with the criterion measure; however, the MoveMonitor acceler- VO₂ in litres per minute (L/min), which was converted by a 11 ometer had the best performance with less than 2% error at all technician to EE by multiplying by 5 kcal per L of O2. All time walking speeds. Two recent studies showed moderate or strong with an EE ≥3.0 METS was summed for a measure of active correlations between consumer monitors and the AG for step minutes. The COSMED has been shown to provide accurate and counting (r=0.80–0.91), EE (r=0.74–0.81) and active minutes reliable measures of VO2 over a wide range of activity intensities (r=0.52–0.91) under free-living conditions. However, these in comparison with metabolic carts and was used as the criterion studies lacked a criterion measure, so accuracy of these devices measure for EE and active minutes in this study.12 could not be determined.7 8 Subjects participated in an 80 min, semistructured activity Due to the widespread use of consumer monitors and other protocol, performing ≥12 activities from a list of 21 choices. PA and health monitoring tools, it is important to gain under- Activities were grouped into the following categories: (1) standing on how consumer monitors compare with a popularly sedentary activities (lying down, watching television, writing, used research-grade accelerometer in terms of accuracy of PA reading, playing cards, and computer use), (2) household activ- measurement and to make comparisons of studies using different ities (standing, dusting, sweeping, vacuuming, folding laundry, types and brands of monitors. Thus, we compared four popular making bed, picking up items from floor, and gardening) and (3) consumer monitors with a commonly used research-grade accel- ambulatory and cycling activities (slow overground walk, brisk erometer in a semistructured environment using a protocol that overground walk, treadmill walk, overground jog, treadmill jog, incorporates similar activities as those performed by adults on a stair climbing, and stationary cycling). Subjects chose the pace, daily basis. duration (2–15 min) and order of activities. At least four activi- ties from each category (sedentary, household, and ambulatory) were performed, and subjects were instructed to spend ≥40 min METHODS in sedentary activities (to replicate adults’ free-living sedentary Healthy adult men (n=15) and women (n=15) who were 18–80 behaviour patterns).12 13 PA variables were recorded from the years of age and able to participate in moderate-to-vigorous consumer monitors at the beginning and end of the protocol; PA participated in this study. The study was approved by Ball therefore,
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