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      The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study

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          Abstract

          Background

          Technological advances have seen a burgeoning industry for accelerometer-based wearable activity monitors targeted at the consumer market. The purpose of this study was to determine the convergent validity of a selection of consumer-level accelerometer-based activity monitors.

          Methods

          21 healthy adults wore seven consumer-level activity monitors (Fitbit One, Fitbit Zip, Jawbone UP, Misfit Shine, Nike Fuelband, Striiv Smart Pedometer and Withings Pulse) and two research-grade accelerometers/multi-sensor devices (BodyMedia SenseWear, and ActiGraph GT3X+) for 48-hours. Participants went about their daily life in free-living conditions during data collection. The validity of the consumer-level activity monitors relative to the research devices for step count, moderate to vigorous physical activity (MVPA), sleep and total daily energy expenditure (TDEE) was quantified using Bland-Altman analysis, median absolute difference and Pearson’s correlation.

          Results

          All consumer-level activity monitors correlated strongly (r > 0.8) with research-grade devices for step count and sleep time, but only moderately-to-strongly for TDEE (r = 0.74-0.81) and MVPA (r = 0.52-0.91). Median absolute differences were generally modest for sleep and steps (<10% of research device mean values for the majority of devices) moderate for TDEE (<30% of research device mean values), and large for MVPA (26-298%). Across the constructs examined, the Fitbit One, Fitbit Zip and Withings Pulse performed most strongly.

          Conclusions

          In free-living conditions, the consumer-level activity monitors showed strong validity for the measurement of steps and sleep duration, and moderate valid for measurement of TDEE and MVPA. Validity for each construct ranged widely between devices, with the Fitbit One, Fitbit Zip and Withings Pulse being the strongest performers.

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          Most cited references21

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          Calibration of the Computer Science and Applications, Inc. accelerometer.

          We established accelerometer count ranges for the Computer Science and Applications, Inc. (CSA) activity monitor corresponding to commonly employed MET categories. Data were obtained from 50 adults (25 males, 25 females) during treadmill exercise at three different speeds (4.8, 6.4, and 9.7 km x h(-1)). Activity counts and steady-state oxygen consumption were highly correlated (r = 0.88), and count ranges corresponding to light, moderate, hard, and very hard intensity levels were or = 9499 cnts x min(-1), respectively. A model to predict energy expenditure from activity counts and body mass was developed using data from a random sample of 35 subjects (r2 = 0.82, SEE = 1.40 kcal x min(-1)). Cross validation with data from the remaining 15 subjects revealed no significant differences between actual and predicted energy expenditure at any treadmill speed (SEE = 0.50-1.40 kcal x min(-1)). These data provide a template on which patterns of activity can be classified into intensity levels using the CSA accelerometer.
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            Validity of 10 electronic pedometers for measuring steps, distance, and energy cost.

            This study examined the effects of walking speed on the accuracy and reliability of 10 pedometers: Yamasa Skeletone (SK), Sportline 330 (SL330) and 345 (SL345), Omron (OM), Yamax Digiwalker SW-701 (DW), Kenz Lifecorder (KZ), New Lifestyles 2000 (NL), Oregon Scientific (OR), Freestyle Pacer Pro (FR), and Walk4Life LS 2525 (WL). Ten subjects (33 +/- 12 yr) walked on a treadmill at various speeds (54, 67, 80, 94, and 107 m x min-1) for 5-min stages. Simultaneously, an investigator determined steps by a hand counter and energy expenditure (kcal) by indirect calorimetry. Each brand was measured on the right and left sides. Correlation coefficients between right and left sides exceeded 0.81 for all pedometers except OR (0.76) and SL345 (0.57). Most pedometers underestimated steps at 54 m x min-1, but accuracy for step counting improved at faster speeds. At 80 m x min-1 and above, six models (SK, OM, DW, KZ, NL, and WL) gave mean values that were within +/- 1% of actual steps. Six pedometers displayed the distance traveled. Most of them estimated mean distance to within +/- 10% at 80 m x min-1 but overestimated distance at slower speeds and underestimated distance at faster speeds. Eight pedometers displayed kilocalories, but except for KZ and NL, it is unclear whether this should reflect net or gross kilocalories. If one assumes they display net kilocalories, the general trend was an overestimation of kilocalories at every speed. If one assumes they display gross kilocalorie, then seven of the eight pedometers were accurate to within +/-30% at all speeds. In general, pedometers are most accurate for assessing steps, less accurate for assessing distance, and even less accurate for assessing kilocalories.
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              Validation of the Fitbit One activity monitor device during treadmill walking.

              In order to quantify the effects of physical activity such as walking on chronic disease, accurate measurement of physical activity is needed. The objective of this study was to determine the validity and reliability of a new activity monitor, the Fitbit One, in a population of healthy adults. Cross-sectional study. Thirty healthy adults ambulated at 5 different speeds (0.90, 1.12, 1.33, 1.54, 1.78 m/s) on a treadmill while wearing three Fitbit One activity monitors (two on the hips and one in the pocket). The order of each speed condition was randomized. Fitbit One step count output was compared to observer counts and distance output was compared to the calibrated treadmill output. Two-way repeated measures ANOVA, concordance correlation coefficients, and Bland and Altman plots were used to assess validity and intra-class correlation coefficients (ICC) were used to assess reliability. No significant differences were noted between Fitbit One step count outputs and observer counts, and concordance was substantial (0.97-1.00). Inter-device reliability of the step count was high for all walking speeds (ICC ≥ 0.95). Percent relative error was less than 1.3%. The distance output of the Fitbit One activity monitors was significantly different from the criterion values for each monitor at all speeds (P<0.001) and exhibited poor concordance (0.0-0.05). Inter-device reliability was excellent for all treadmill speeds (ICC ≥ 0.90). Percent relative error was high (up to 39.6%). The Fitbit One activity monitors are valid and reliable devices for measuring step counts in healthy young adults. The distance output of the monitors is inaccurate and should be noted with caution. Copyright © 2013 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                ferty02f@mymail.unisa.edu.au
                Alex.Rowlands@unisa.edu.au
                tim.olds@unisa.edu.au
                carol.maher@unisa.edu.au
                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central (London )
                1479-5868
                27 March 2015
                27 March 2015
                2015
                : 12
                : 42
                Affiliations
                Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute, University of South Australia, GPO Box 2471, 5001 Adelaide, Australia
                Article
                201
                10.1186/s12966-015-0201-9
                4416251
                25890168
                7b462fea-9344-44e4-867e-2dcbffd263a3
                © Ferguson et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 13 August 2014
                : 9 March 2015
                Categories
                Research
                Custom metadata
                © The Author(s) 2015

                Nutrition & Dietetics
                actigraphy,physical activity,sleep,validity,triaxial accelerometer,activity monitor

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