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Sarah G. Sanders, Elizabeth Yakes Jimenez, Natalie H. Cole, Alena Kuhlemeier, Grace L. McCauley, M. Lee Van Horn and Alberta S. Kong

the GENEActiv wrist-worn accelerometer (GA) were first published for youth in 2013. 7 Studies reporting MVPA measured at the wrist in adolescents are limited and vary in location (United Kingdom, United States, and Spain); in the type of accelerometer used; and in how the data were processed and

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Kayla J. Nuss, Joseph L. Sanford, Lucas J. Archambault, Ethan J. Schlemer, Sophie Blake, Jimikaye Beck Courtney, Nicholas A. Hulett and Kaigang Li

upper arm, (2) determine the accuracy of the total exercise bout EE calculations by both the wrist-worn (WW) Apple Watch and arm-worn (AW) Apple Watch, and (3) compare the HR and EE estimations of the WW and AW Apple Watch. Methods Subject Recruitment and Health Screening All potential participants were

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Jeremy A. Steeves, Scott A. Conger, Joe R. Mitrzyk, Trevor A. Perry, Elise Flanagan, Alecia K. Fox, Trystan Weisinger and Alexander H.K. Montoye

recent study by Conger et al. ( 2016 ) examined the use of a wrist-worn triaxial accelerometer-based activity monitor (ActiGraph GT3X+) to classify upper- and lower-body resistance training exercises. Sixty participants were asked to complete one set of 10 repetitions each for 12 different resistance

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Lisa Price, Katrina Wyatt, Jenny Lloyd, Charles Abraham, Siobhan Creanor, Sarah Dean and Melvyn Hillsdon

accelerometer wear-time period. Recent developments in the design of activity monitors and wear protocols have sought to address these 2 methodological challenges ( 28 ). Evidence demonstrates that the use of a waterproof, wrist-worn accelerometer, designed to be discrete and minimize discomfort, can reduce

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Laura D. Ellingson, Paul R. Hibbing, Gregory J. Welk, Dana Dailey, Barbara A. Rakel, Leslie J. Crofford, Kathleen A. Sluka and Laura A. Frey-Law

, Choi, & Chen, 2008 ), but this wear location may be less comfortable for participants, leading to compliance issues ( Troiano, McClain, Brychta, & Chen, 2014 ). As such, wrist-worn monitors are increasingly being used ( Da Silva et al., 2014 ; Freedson & John, 2013 ; Sabia et al., 2014 ; Troiano et

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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.

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Paul D. Loprinzi and Brandee Smith

Objective:

To use the most recent ActiGraph model (GT9X) to compare counts per minute (CPM) estimates between wrist-worn and waist-worn attachment sites.

Methods:

Participants completed 2 conditions (laboratory [N = 13] and free-living conditions [N = 9]), in which during both of these conditions they wore 2 ActiGraph GT9X accelerometers on their nondominant wrist (side-by-side) and 2 ActiGraph GT9X accelerometers on their right hip in line with the midaxillary line (side-by-side). During the laboratory visit, participants completed 5 treadmill-based trials all lasting 5 min: walk at 3 mph, 3.5 mph, 4 mph, and a jog at 6 mph and 6.5 mph. During the free-living setting, participants wore the monitors for 8 hours. Paired t test, Pearson correlation and Bland-Altman analyses were employed to evaluate agreement of CPM between the attachment sites.

Results:

Across all intensity levels and setting (laboratory and free-living), CPM were statistically significantly and substantively different between waist- and wrist-mounted accelerometry.

Conclusion:

Attachment site drastically influences CPM. As such, extreme caution should be exercised when comparing CPM estimates among studies employing different attachment site methodologies, particularly waist versus wrist.

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Scott A. Conger, Alexander H.K. Montoye, Olivia Anderson, Danielle E. Boss and Jeremy A. Steeves

associated with step counts in wrist-worn devices at slower walking speeds ( Chen, Kuo, Pellegrini, & Hsu, 2016 ; Huang, Xu, Yu, & Shull, 2016 ; Storm, Heller, & Mazza, 2015 ). Speed of movement has been an important variable to consider in determining the validity and accuracy of these accelerometer

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Jennifer L. Huberty, Jeni L. Matthews, Meynard Toledo, Lindsay Smith, Catherine L. Jarrett, Benjamin Duncan and Matthew P. Buman

validated wrist-worn triaxial sensor used to objectively measure physical activity in the free-living setting. However, the validity of both devices in measuring energy expenditure has not been evaluated for yoga. The validation of portable, light-weight devices such as the Actigraph and GENEActiv is

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Erin K. Howie, Joanne A. McVeigh and Leon M. Straker

Background:

There are several practical issues when considering the use of hip-worn or wrist-worn accelerometers. This study compared compliance and outcomes between hip- and wrist-worn accelerometers worn simultaneously by children during an active video games intervention.

Methods:

As part of a larger randomized crossover trial, participants (n = 73, age 10 to 12 years) wore 2 Actical accelerometers simultaneously during waking hours for 7 days, on the hip and wrist. Measurements were repeated at 4 timepoints: 1) at baseline, 2) during traditional video games condition, 3) during active video games condition, 4) during no video games condition. Compliance and intervention effects were compared between hip and wrist.

Results:

There were no statistically significant differences at any timepoint in percentage compliance between hip (77% to 87%) and wrist (79% to 89%). Wrist-measured counts (difference of 64.3 counts per minute, 95% CI 4.4–124.3) and moderate-to-vigorous physical activity (MVPA) (12 min/day, 95% CI 0.3–23.7) were higher during the no video games condition compared with the traditional video games condition. There were no differences in hip-measured counts per minute or MVPA between conditions or sedentary time for hip or wrist.

Conclusions:

There were no differences in compliance between hip- and wrist-worn accelerometers during an intervention trial, however, intervention findings differed between hip and wrist.