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Stamatis Agiovlasitis, Robert W. Motl, John T. Foley and Bo Fernhall

This study examined the relationship between energy expenditure and wrist accelerometer output during walking in persons with and without Down syndrome (DS). Energy expenditure in metabolic equivalent units (METs) and activity-count rate were respectively measured with portable spirometry and a uniaxial wrist accelerometer in 17 persons with DS (age: 24.7 ± 6.9 years; 9 women) and 21 persons without DS (age: 26.3 ± 5.2 years; 12 women) during six over-ground walking trials. Combined groups regression showed that the relationship between METs and activity-count rate differed between groups (p < .001). Separate models for each group included activity-count rate and squared activity-count rate as significant predictors of METs (p ≤ .005). Prediction of METs appeared accurate based on Bland-Altman plots and the lack of between-group difference in mean absolute prediction error (DS: 17.07%; Non-DS: 18.74%). Although persons with DS show altered METs to activity-count rate relationship during walking, prediction of their energy expenditure from wrist accelerometry appears feasible.

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Benita J. Lalor, Shona L. Halson, Jacqueline Tran, Justin G. Kemp and Stuart J. Cormack

the participant was lying down attempting to sleep or activity counts from the monitor were sufficiently low to indicate that the participant was immobile (ie, where the weighted activity count for an epoch fell below the defined threshold). When these 2 conditions were satisfied simultaneously, time

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Jacopo A. Vitale, Giuseppe Banfi, Andrea Galbiati, Luigi Ferini-Strambi and Antonio La Torre

threshold was selected to detect sleep parameters since it has been shown that the cutoff value of 80 activity counts yields the best combination of sensitivity and specificity in a population of elite athletes. 12 Together with the actigraph, each subject received a sleep diary to record bedtime, wake

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Laura E. Juliff, Jeremiah J. Peiffer and Shona L. Halson

piezoelectric accelerometer, which sampled activity counts in 1-minute epochs. Epoch-for-epoch concordance rates of 81% to 90% with polysomnography (gold standard sleep measure) have been found for sleep/wake activity using Actical® wrist actigraphy monitors. 14 Participants wore the monitor at all times

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Lena Zimmo, Fuad Almudahka, Izzeldin Ibrahim, Mohamed G. Al-kuwari and Abdulaziz Farooq

-worn accelerometers, unless they were uncomfortable. Since there was no planned after-school activity, only school-time data were used. The accelerometer data were collected with a sampling rate of 30 Hz, and activity counts were integrated for every 10 s (epoch). The software identified time without the

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Júlio A. Costa, João Brito, Fábio Y. Nakamura, Eduardo M. Oliveira, Ovidio P. Costa and António N. Rebelo

); latency (time in min attempting to fall asleep); and sleep efficiency (percentage of time in bed that was spent asleep). The sampling frequency was 50 Hz and the epoch of activity counts was 60 seconds. All movements greater than 0.05  g were measured, and values outside the range of 3 to 11 Hz were

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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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Xihe Zhu and Justin A. Haegele

with oxygen consumption ( Kelly, McMillan, Anderson, Fippinger, Fillerup, & Rider, 2013 ). The ActiGraph GT3x output represents data across three axes (mediolateral, vertical, and anteroposterior) separately and provides activity counts as a composite vector magnitude of these three axes. This specific