Comparing the performance of three generations of ActiGraph accelerometers

Rothney, Megan P.; Apker, Gregory; Song, Yanna; Chen, Kong Y.

doi:10.1152/japplphysiol.90641.2008

Cited by 155 publications

(161 citation statements)

References 24 publications

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“…Though different accelerometer models have demonstrated comparability in trials for moderate and vigorous physical activity counts, 47 there appear to be differences at lower intensity levels that have implications for sedentary behavior measures. 48,49 To inform analyses, the accelerometer models are being compared in small studies, and correction algorithms to adjust for accelerometer model as well as for the difference between the ActiGraph and Actical, are being developed. All countries employed a 60-second epoch for storing data.…”

Section: Objectively-assessed Activity (Preferred)mentioning

confidence: 99%

Advancing Science and Policy Through a Coordinated International Study of Physical Activity and Built Environments: IPEN Adult Methods

Kerr¹,

Sallis²,

Owen³

et al. 2013

Journal of Physical Activity and Health

153

201

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Background:National and international strategies to increase physical activity emphasize environmental and policy changes that can have widespread and long-lasting impact. Evidence from multiple countries using comparable methods is required to strengthen the evidence base for such initiatives. Because some environment and policy changes could have generalizable effects and others may depend on each country’s context, only international studies using comparable methods can identify the relevant differences.Methods:Currently 12 countries are participating in the International Physical Activity and the Environment Network (IPEN) study. The IPEN Adult study design involves recruiting adult participants from neighborhoods with wide variations in environmental walkability attributes and socioeconomic status (SES).Results:Eleven of twelve countries are providing accelerometer data and 11 are providing GIS data. Current projections indicate that 14,119 participants will provide survey data on built environments and physical activity and 7145 are likely to provide objective data on both the independent and dependent variables. Though studies are highly comparable, some adaptations are required based on the local context.Conclusions:This study was designed to inform evidence-based international and country-specific physical activity policies and interventions to help prevent obesity and other chronic diseases that are high in developed countries and growing rapidly in developing countries.

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Section: Objectively-assessed Activity (Preferred)mentioning

confidence: 99%

Advancing Science and Policy Through a Coordinated International Study of Physical Activity and Built Environments: IPEN Adult Methods

Kerr¹,

Sallis²,

Owen³

et al. 2013

Journal of Physical Activity and Health

153

201

View full text Add to dashboard Cite

show abstract

“…Accelerometer Previous studies have found the ActiGraph to be reliable and valid (15,(23)(24)(25) . A recent study (26) showed that 1 d of accelerometer data is adequate for estimating weekly moderate-to-vigorous PA (MVPA) in a representative US sample aged 20-85 years but we adopted a more stringent criterion because we aimed to examine hourly PA patterns.…”

Section: Measurementsmentioning

confidence: 99%

A cluster analysis of patterns of objectively measured physical activity in Hong Kong

Lee

McDowell

et al. 2012

Public Health Nutr.

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Objective: The health benefits of exercise are clear. In targeting interventions it would be valuable to know whether characteristic patterns of physical activity (PA) are associated with particular population subgroups. The present study used cluster analysis to identify characteristic hourly PA patterns measured by accelerometer. Design: Cross-sectional design. Setting: Objectively measured PA in Hong Kong adults. Subjects: Four-day accelerometer data were collected during 2009 to 2011 for 1714 participants in Hong Kong (mean age 44?2 years, 45?9 % male). Results: Two clusters were identified, one more active than the other. The 'active cluster' (n 480) was characterized by a routine PA pattern on weekdays and a more active and varied pattern on weekends; the other, the 'less active cluster' (n 1234), by a consistently low PA pattern on both weekdays and weekends with little variation from day to day. Demographic, lifestyle, PA level and health characteristics of the two clusters were compared. They differed in age, sex, smoking, income and level of PA required at work. The odds of having any chronic health conditions was lower for the active group (adjusted OR 5 0?62, 95 % CI 0?46, 0?84) but the two groups did not differ in terms of specific chronic health conditions or obesity. Conclusions: Implications are drawn for targeting exercise promotion programmes at the population level.

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“…Second, data processing differs across devices Chen & Bassett, 2005), which is especially problematic in combination with the first problem. Accordingly, different devices produce significantly different numbers of counts for the exact same movements (Rothney, Apker, Song, & Chen, 2008). One possible reason for that is the so-called plateau phenomenon (cf.…”

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confidence: 99%

Individual classification of elementary school children’s physical activity: A time-efficient, group-based approach to reference measurements

2016

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The objective measurement of physical activity using accelerometers is becoming increasingly popular. There is little consensus, however, about how to analyze acceleration data. One promising approach is the use of reference measurements in which the subjects conduct specific activities. This makes it possible to identify data patterns that indicate these activities for each subject. The drawback of this approach is its rather high cost, in terms of both time and money. We propose a new approach in which a group of children conduct the reference measurements at the same time. We trained support vector machine models on the accelerometer data of 70 children (ages 8-11 years) to predict their activities during those reference measurements. We correctly classified activities with an accuracy of 96.9 % when fitting the individual models for each subject, and 87.5 % when fitting general models for all subjects. The obtained accuracies were comparable to results reported in previous reference measurement studies, in which each subject was measured individually. They were higher than the accuracies obtained by the traditional approach, which transfers accelerometer data to counts and classifies those on the basis of predefined cut points. We concluded that our approach can yield a valuable contribution, particularly to studies with larger samples.

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Comparing the performance of three generations of ActiGraph accelerometers

Abstract: Rothney MP, Apker GA, Song Y, Chen KY. Comparing the performance of three generations of ActiGraph accelerometers.

Cited by 155 publications

References 24 publications

Advancing Science and Policy Through a Coordinated International Study of Physical Activity and Built Environments: IPEN Adult Methods

Advancing Science and Policy Through a Coordinated International Study of Physical Activity and Built Environments: IPEN Adult Methods

A cluster analysis of patterns of objectively measured physical activity in Hong Kong

Individual classification of elementary school children’s physical activity: A time-efficient, group-based approach to reference measurements

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