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Catrine Tudor-Locke, John M. Schuna Jr, Damon L. Swift, Amber T. Dragg, Allison B. Davis, Corby K. Martin, William D. Johnson and Timothy S. Church

censor very-low-force accelerations in an attempt to make the steps per day outputs more comparable. In brief, steps accumulated during minutes associated with <500 activity counts per minute were censored to accommodate for known differences in between-device sensitivity. 11 , 30 – 32 Participants

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Kosuke Tamura, Jeffrey S. Wilson, Robin C. Puett, David B. Klenosky, William A. Harper and Philip J. Troped

points) and (2) using a combination of accelerometer counts and GPS speed. For the second approach, intensity of activity was classified based on average speed from the GPS device for a given minute, the metabolic equivalent (MET) value for bicycling at that speed, 31 and activity counts from

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Alexander H.K. Montoye, Kimberly A. Clevenger, Kelly A. Mackintosh, Melitta A. McNarry and Karin A. Pfeiffer

(EE) using accelerometers is common for determining the volume and intensity of PA, and accurate EE measurement is critical for identification of, and intervention in, youth with low PA. Due to memory capacity and battery life limitations, early accelerometers summarized raw data into ‘activity counts

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Emma L. J. Eyre, Jason Tallis, Susie Wilson, Lee Wilde, Liam Akhurst, Rildo Wanderleys and Michael J. Duncan

associated health outcomes. Accelerometers are a widely used tool to determine physical activity levels in public health research. Many accelerometer-based tools exist, providing an activitycount’ as their output. These counts are applied to thresholds which determine durations and frequencies of

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Jaehun Jung, Willie Leung, Bridgette Marie Schram and Joonkoo Yun

sample and age), publication year, number of days for data collection, and physical activity levels data. Physical activity levels data were included if it was provided as either (a) average minutes spent in physical activity or (b) physical activity counts measured by accelerometers, so that the effect

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Alex V. Rowlands

metrics do lend themselves to the creation of population-specific physical activity percentiles that would facilitate interpretation in relation to norms, as Wolff-Hughes et al ( 47 ) have done with US children’s age- and sex-specific percentile curves for total activity counts per day for ActiGraph. To

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Robert W. Motl and Rachel Bollaert

under free-living conditions, and specific algorithms can be applied for quantifying the intensity of activity based on the classification of arbitrary units (i.e., accelerometer/activity counts) over a specified time period or epoch (i.e., 1 min) into “buckets” or categories. The classification

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Jodie Andruschko, Anthony D. Okely and Phil Pearson

. Activity counts per 30-sec were uploaded to determine the amount of time spent sedentary, and in light, moderate, and vigorous intensity activity during the monitoring period based on the classifications of Freedson, Melanson, and Sirard ( 1998 ). Analyses were conducted separately for weekdays and weekend

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Jocelyn F. Hafer, Mark S. Miller, Jane A. Kent and Katherine A. Boyer

. Participants wore accelerometers (GT3X; ActiGraph, Pensacola, FL) at the hip for at least 5 days (including at least 1 weekend day). Weekly time spent in MVPA 43 and weekly activity counts were determined for all participants. Gait analyses were performed from data collected during walking overground at 1.4 m

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Jocelyn Kernot, Lucy Lewis, Tim Olds and Carol Maher

.56 to 0.64. 34 Secondary Physical Activity Outcomes In addition to the primary outcomes, accelerometer-derived total activity counts (ActiGraph GT3X+) and self-reported MVPA (AAS) were secondary outcomes for this study. Other Secondary Outcomes A secondary aim of this study was to determine whether the