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Hilary Hicks, Alexandra Laffer, Kayla Meyer, and Amber Watts

measure activity in a free-living environment, which is especially important in an older adult population known to spend less time in higher intensity activity and more time being sedentary (e.g., Harvey, Chastin, & Skelton, 2013 ). ActiGraph introduced the low-frequency extension (LFE) filter in 2009

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Kimberly A. Clevenger, Jan Christian Brønd, Daniel Arvidsson, Alexander H.K. Montoye, Kelly A. Mackintosh, Melitta A. McNarry, and Karin A. Pfeiffer

Since the 1980s, accelerometers have been used to estimate free-living energy expenditure and physical activity levels ( Wong et al., 1981 ). ActiGraph accelerometers are the most widely used brand of research-grade monitors ( Migueles et al., 2017 ; Montoye et al., 2016 ) and have been used in

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Katja Krustrup Pedersen, Esben Lykke Skovgaard, Ryan Larsen, Mikkel Stengaard, Søren Sørensen, and Kristian Overgaard

Accelerometry is a widely used method for assessing quantity and quality of physical activity (PA), which is essential in all PA research ( Troiano, McClain, Brychta, & Chen, 2014 ). One of the more commonly used accelerometers in PA research is the ActiGraph, and this device has most frequently

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

activities at specific intensities. Specifically, the ActiGraph, Actical, and Research Tracker 3 (RT3), which is an older model of the Research Tracker 6 (RT6), are the most commonly used accelerometers in physical activity research. Much research has examined the validity and reliability of different

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Jennifer L. Copeland and Dale W. Esliger

Despite widespread use of accelerometers to objectively monitor physical activity among adults and youth, little attention has been given to older populations. The purpose of this study was to define an accelerometer-count cut point for a group of older adults and to then assess the group’s physical activity for 7 days. Participants (N = 38, age 69.7 ± 3.5 yr) completed a laboratory-based calibration with an Actigraph 7164 accelerometer. The cut point defining moderate to vigorous physical activity (MVPA) was 1,041 counts/min. On average, participants obtained 68 min of MVPA per day, although more than 65% of this occurred as sporadic activity. Longer bouts of activity occurred in the morning (6 a.m. to 12 p.m.) more frequently than other times of the day. Almost 14 hr/day were spent in light-intensity activity. This study demonstrates the rich information that accelerometers provide about older adult activity patterns—information that might further our understanding of the relationship between physical activity and healthy aging.

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Leila Hedayatrad, Tom Stewart, and Scott Duncan

currently the preferred method of assessing these behaviors in free-living settings. As there are many types of accelerometers available, it is of importance to investigate comparability between different devices. The ActiGraph GT3X+ (ActiGraph LLC, Pensacola, FL) accelerometer is one of the most commonly

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Kayla J. Nuss, Nicholas A. Hulett, Alden Erickson, Eric Burton, Kyle Carr, Lauren Mooney, Jacob Anderson, Ashley Comstock, Ethan J. Schlemer, Lucas J. Archambault, and Kaigang Li

the wrist-worn device could be worn for 24 hr, the participants did not forget to put it on again after a night of sleep ( Troiano et al., 2014 ). ActiGraph activity monitors have been one of the most popular means of objectively measuring PA in research and clinical interventions and one of the most

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Samantha F. Ehrlich, Amanda J. Casteel, Scott E. Crouter, Paul R. Hibbing, Monique M. Hedderson, Susan D. Brown, Maren Galarce, Dawn P. Coe, David R. Bassett, and Assiamira Ferrara

, large epidemiologic studies favor the use of objective wear-time algorithms, such as the Troiano ( Troiano et al., 2008a ) and Choi ( Choi, Liu, et al., 2011 ) algorithms, though only the Choi algorithm has been validated in wrist-worn devices ( Choi et al., 2012 ). The ActiGraph wGT3X-BT is a popular

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Jennifer M. DiNallo, Danielle Symons Downs, and Guy Le Masurier

Background:

To effectively promote physical activity (PA) and quantify the effects of PA interventions for pregnant women, PA measurement during pregnancy needs improvement. The purpose of this study was to assess PA monitor output during a controlled, treadmill walking protocol among pregnant women at 20- and 32-weeks gestation.

Methods:

Women (N = 43) wore an Actigraph accelerometer, NL1000, and Yamax pedometer during a 20-minute treadmill walking test [5-minute periods at 4 different speeds (54, 67, 80, and 94 m·min−1)] at 20- and 32-weeks gestation.

Results:

Repeated-measures ANOVAs indicated that Actigraph total counts/minute and minutes of moderate-vigorous PA (MVPA), NL1000 steps and minutes MVPA, and Yamax steps decreased from 20- to 32-weeks gestation (P ≤ .05), while body girth circumference and activity monitor tilt increased (P ≤ .05). Repeated measures ANCOVAs, controlling for changes in body girth and monitor tilt, yielded no significant differences in any outcome measures from 20- to 32-weeks gestation.

Conclusions:

Preliminary results suggest physical changes during pregnancy impact activity monitor output in controlled settings. Accurately measuring and statistically controlling for changes in body girth at monitor placement site and monitor tilt may improve the accuracy of activity monitors for use with pregnant populations.

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Orjan Ekblom, Gisela Nyberg, Elin Ekblom Bak, Ulf Ekelund, and Claude Marcus

Background:

Wrist-worn accelerometers may provide an alternative to hip-worn monitors for assessing physical activity as they are easier to wear and may thus facilitate long-term recordings. The current study aimed at a) assessing the validity of the Actiwatch (wrist-worn) for estimating energy expenditure, b) determining cut-off values for light, moderate, and vigorous activities, c) studying the comparability between the Actiwatch and the Actigraph (hip-worn), and d) assessing reliability.

Methods:

For validity, indirect calorimetry was used as criterion measure. ROC-analyses were applied to identify cut-off values. Comparability was tested by simultaneously wearing of the 2 accelerometers during free-living condition. Reliability was tested in a mechanical shaker.

Results:

All-over correlation between accelerometer output and energy expenditure were found to be 0.80 (P < .001).Based on ROC-analysis, cut-off values for 1.5, 3, and 6 METs were found to be 80, 262, and 406 counts per 15 s, respectively. Energy expenditure estimates differed between the Actiwatch and the Actigraph (P < .05). The intra- and interinstrument coefficient of variation of the Actiwatch ranged between 0.72% and 8.4%.

Conclusion:

The wrist-worn Actiwatch appears to be valid and reliable for estimating energy expenditure and physical activity intensity in children aged 8 to 10 years.